TAXONOMIC SIGNATURES AND METHODS OF DETERMINING THE SAME

SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted in ST26 format and is hereby incorporated by reference in its entirety. Said ST26 copy, created on Mar. 27, 2023, is named SeqLst_BAYM0359WO.xml and is 7.914 bytes in size.

TECHNICAL FIELD AND BACKGROUND

This disclosure relates to the fields of bacteriology, cell biology, physiology, molecular biology, bioinformatics, diagnostics, and medicine.

Targeted metagenomic sequencing is routinely used to identify disease-causing bacteria, archaea and fungi. 16S rRNA gene surveys are also emerging as components of strategies to define disease-specific microbiome markers and are being adopted as diagnostic tools to profile microbiome communities that contribute to clinical pathogenesis¹. However, in order to understand what constitutes a disease-associated or disease-causing microbiome, there is a need to define healthy human microbiome community characteristics and functions across diverse genetic and environmental confounders². Current approaches often yields inconsistent or conflicting results due to inadequate study power and experimental bias. Disclosed herein are methods directed to solving the aforementioned problem, wherein adequate study power is achieved and experimental bias is minimized to improve the consistency of results.

To this end, consortium-driven studies including MetaHIT. Human Microbiome Project. LifeLines and American Gut have made significant inroads into compositional profiling of the human gut microbiome by establishing standard operating procedures that include DNA extraction protocols, 16S primer design and bioinformatics pipelines³. The next phase in identifying robust host-microbiome interactions that modulate human disease requires integrated and sufficiently powered multi-center trials to account for human genetic and environmental variation, but optimal study designs are often logistically impossible and cost prohibitive. Reanalyzing large deposits of publicly available 16S sequencing data represents an alternative approach to mine clinical microbiome associations in order to facilitate precision diagnosis and microbiome-based therapy. Unfortunately, re-analysis of individual microbiome surveys remains a significant bioinformatics challenge due to the lack of appropriate analytical pipelines that provide accurate taxonomic profiling of sequences generated from distinct 16S variable regions across multiple technology platforms. Disclosed herein are methods directed to solving the aforementioned problem, wherein accurate taxonomic profiling of sequences generated form distinct 16S variable regions across multiple technology platforms is achieved.

Gastrointestinal disease is a notable example where clinical microbiome surveys have provided promising insights into microbiome-associations and mechanisms, but systematic review of these largely single-site cohort studies have demonstrated inconsistent findings, in large part due to variations in methods for data generation and analysis as they introduce significant bias for cross-comparisons^4,5. Chronic diarrhea is a major cause of morbidity in the developed world and overlapping disease symptoms are often difficult to diagnose and manage. Thus, there is a need for non-invasive approaches to help differentiate the clinical spectra of common diarrheal symptoms, especially in irritable bowel syndrome (IBS), inflammatory bowel diseases (IBD) including Crohn's disease (CD) and ulcerative colitis (UC), and Clostridiodes difficile infection (CDI) which afflict up to 20% of the population and for which misdiagnosis is frequent. With few reliable disease-specific fecal biomarkers reported for IBD or IBS^6,7, endoscopy remains the gold standard diagnosis combined with laboratory testing and questionnaire. Clinical diagnosis and treatment is complicated further by antibiotic use and susceptibility to CDI which is often a post-infectious trigger of IBS, while IBD patients are often asymptomatically colonized by toxigenic C. difficile^8,9. Disclosed herein are methods directed to solving the aforementioned problem, wherein accurate diagnosis of IBS, IBD (e.g., CD and/or UC), and/or CDI is achieved, thus providing the field with suitable methods for treating the same.

Herein the inventors describe at least methods and compositions that utilize 16S sequencing data to solve the aforementioned problems to provide stake holders with accurate diagnostic and/or method of treatment options for patients experiencing microbiome dysbiosis and/or diarrhea. In some embodiments, the information garnered from 16S sequencing data analysis can be applied to other sequencing and/or detection methods to provide stake holders with accurate diagnostic and/or method of treatment options for patients experiencing microbiome dysbiosis and/or diarrhea.

SUMMARY

Given the risk for antimicrobial resistant (AMR)-pathogens causing life-threating infections and/or quality of life diminishment associated with improper diagnosis, successful infectious disease management is critically dependent on identifying the most susceptible patient and determining the appropriate therapeutic regimen to facilitate rapid clinical intervention. Although the value of precision diagnosis and treatment is well-recognized, neither the current analytical technology nor our understanding of microbiome feature associations are sufficiently well developed to initiate effective implementation.

The present disclosure is directed to methods and compositions that provide for accurate diagnosis and treatment of underlying microbiome dysbiosis in an individual. The methods can determine if an individual has CDI, IBS, IBD UC, or IBD CD. The methods can determine if an individual is at risk for CDI, IBS, IBD UC, or IBD CD. Embodiments of the disclosure provide methods of identifying individuals that have CDI, IBS, IBD UC, or IBD CD (compared to age-matched or sex-matched individuals in the general population who are considered to have a non-dysbiosed microbiome) and identifying individuals that do not have CDI, IBS, IBD UC, or IBD CD (compared to the general population who are considered to have a non-dysbiosed microbiome).

Methods described herein can include treating an individual having diarrhea comprising: measuring for one or more taxonomical features from a biological sample from the individual; and reducing the administration of antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of non-CDI causative diarrhea, or administering antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of pathogenic infection.

Methods can comprise antibiotics and/or antimicrobial treatment comprising at least one of the antibiotics selected from a small molecule antibiotic, an antibiotic derived from a natural product, a microbial composition, an antibody suitable for neutralizing pathogenic infections, a therapeutic, contact isolation, and any combination thereof.

Methods can comprise the proviso that if the non-CDI causative diarrhea is irritable bowel syndrome (IBS), administration of the antibiotic and/or antimicrobial rifaximin is not reduced. Methods can comprise antibiotics and/or antimicrobial treatments comprising at least one of vancomycin, fidaxomicin, and bezlotoxumab. Methods can comprise treatment with fidaxomicin, and optionally the treatment dosage is at least 200 mg twice daily for 10 days, the treatment is vancomycin, and optionally the treatment dosage is at least 125 mg four times per day for 10 days, and/or the treatment is bezlotoxumab.

Methods can comprise pathogenic diarrhea classification or non-CDI causative diarrhea classification characterized by measuring the presence, absence, and/or relative quantity of at least, exactly, or at most 10, 20, 40, 60, 80, 100, or greater than 100, or any range derivable therein, taxonomical features described in any one or more of Tables 9-17. In certain methods, characterization using taxonomical features described in Tables 9-17 is sequential. Methods can comprise more than one characterization using Tables 9-17, comprising first characterizing using Tables 10 and/or 12, followed by characterization using one or more of the remaining Tables.

Methods can comprise measuring of one or more taxonomical features comprising at least one of analyzing one or more nucleic acids in the sample, analyzing one or more metabolites in the sample, and analyzing one or more proteins in the sample. Methods can comprise nucleic acid analysis, wherein the nucleic acid is analyzed by sequencing, polymerase chain reaction, isothermal amplification, bioinformatics, or any combination thereof. Methods can comprise 16S ribosomal RNA analysis. Methods can comprise metabolite analysis by mass spectrometry, ELISA, chromatography, or any combination thereof. Methods can comprise protein analysis by mass spectrometry, ELISA, chromatography, Western blotting, immunoprecipitation, immunoelectrophoresis, or any combination thereof.

Methods can comprise reducing the administration of antibiotics and/or antimicrobial treatments to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of non-CDI causative diarrhea, the subject microbiome is further characterized to determine whether the non-CDI causative diarrhea is associated with irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD), and treatment is modified accordingly. Methods can comprise identifying non-CDI causative diarrhea associated with IBD, wherein the IBD is further characterized to determine whether the IBD is Ulcerative Colitis (UC) or Crohn's Disease (CD), and treatment is modified accordingly.

Methods can comprise measuring of one or more taxonomical features from a biological sample from an individual comprising determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, or all of: Acidaminococcaceae Acidaminococcus; Actinomycetales Actinomycetaceae; Bacillales Gemella; Bacilli Lactobacillus; Betaproteobacteria; Betaproteobacteria Burkholderiales; Bifidobacterium boum; Blautia hominis; Clostridiales Incertae Sedis XI Parvimonas; Enterobacteriaceae Cedecea; Erysipelotrichaceae Faecalicoccus; Faecalimonas umbilicata; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Gammaproteobacteria Enterobacterales; Lachnoclostridium [Clostridium] bolteae; Lachnospiraceae Lachnoclostridium; Megasphaera micronuciformis; Peptoniphilaceae Peptoniphilus; Peptostreptococcaceae Peptostreptococcus; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Terrisporobacter; Proteobacteria Gammaproteobacteria; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Ruminococcaceae Intestinimonas; Ruminococcaceae Subdoligranulum; Solobacterium moorei; Veillonellaceae Veillonella; Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides koreensis; Bacteroides thetaiotaomicron; Bacteroides xylanisolvens; Colidextribacter massiliensis; Coprococcus catus; Coprococcus eutactus; Enterobacterales Enterobacteriaceae; Faecalibacterium prausnitzii; Methanobrevibacter smithii; Phascolarctobacterium faecium; Romboutsia timonensis; and Turicibacter sanguinis; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.

Methods can comprise measuring of one or more taxonomical features from a biological sample from a pediatric individual comprising determining changes in relative abundance, compared to a reference healthy pediatric gut microbiome, of at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 56, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, or all of: Bacilli Lactobacillus; Peptostreptococcaceae Clostridioides; Enterococcaceae Enterococcus; Eggerthellaceae Eggerthella; Erysipelotrichaceae Erysipelatoclostridium; Lachnospiraceae Lachnoclostridium; Firmicutes Bacilli; Enterobacteriaceae Escherichia; Enterobacteriales Enterobacteriaceae; Streptococcaceae Streptococcus; Actinomycetaceae Schaalia; Clostridiaceae Hungatella; Clostridiaceae Clostridium; Corynebacteriaceae Corynebacterium; Veillonellaceae Veillonella; Actinomycetaceae Actinomyces; Fusobacteriaceae Fusobacterium; Erysipelotrichaceae Longicatena; Lachnospiraceae Clostridium XlVa; Lachnospiraceae Eisenbergiella; Peptostreptococcaceae Intestinibacter; Enterobacteriaceae Citrobacter; Peptoniphilaceae Finegoldia; Carnobacteriaceae Granulicatella; Coriobacteriaceae Eggerthella; Peptostreptococcaceae Peptostreptococcus; Drancourtella massiliensis; Peptoniphilaceae Anaerococcus; Bacillales Gemella; Lachnospiraceae Sellimonas; Peptoniphilaceae Peptoniphilus; Pasteurellaceae Rodentibacter; Clostridium sensu stricto; Lachnospiraceae Faecalimonas; Proteobacteria Gammaproteobacteria; Clostridiaceae Lactonifactor; Micrococcaceae Rothia; Leuconostocaceae Weissella; Peptostreptococcaceae Terrisporobacter; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Clostridium XI; Coriobacteriaceae Atopobium; Atopobiaceae Atopobium; Ruminococcaceae Anaeromassilibacillus; Porphyromonadaceae Parabacteroides; Rikenellaceae Alistipes; Lachnospiraceae Eubacterium rectale group; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Porphyromonadacede Odoribacter; Veillonellaceae Dialister; Ruminococcaceae Clostridium IV; Bacteroidia Bacteroidales; Coriobacteriaceae Collinsella; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Clostridium leptum group; Enterobacteriaceae Shimwellia; Acidaminococcaceae Phascolarctobacterium; Staphylococcaceae Staphylococcus; Lachnospiraceae Anaerobutyricum; Erysipelotrichaceae Holdemania; Clostridiales Monoglobus; Porphyromonadaceae Barnesiella; Pasteurellales Pasteurellaceae; Clostridiales Clostridiaceae 1; and Bacteroidales Rikenellaceae; wherein the change in taxonomical feature relative abundance is indicative of CDI associated diarrhea.

Methods can comprise measuring of one or more taxonomical features from a biological sample from a individual comprising determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 56, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, or all of: Anaerostipes hadrus; Faecalibacterium prausnitzii; Lachnospiraceae Coprococcus; Lachnospiraceae [Eubacterium] rectale; Lachnospiraceae Roseburia; Lachnospiraceae Fusicatenibacter; Lachnospiraceae Dorea; Ruminococcaceae Ruminococcus; Roseburia inulinivorans; Dorea longicatena; Roseburia intestinalis; Lachnospiraceae Anaerostipes; Coprococcus comes; Lactobacillus rogosae; Romboutsia timonensis; Saccharibacteria Incertae Sedis; Eubacterium [Eubacterium] eligens; Bacteroides plebeius; Lachnospiraceae Blautia; Roseburia faecis; Blautia obeum; Coprococcus catus; Betaproteobacteria Burkholderiales; Prevotella copri; Burkholderiales Burkholderiaceae; Caulobacter segnis; Caulobacterales Caulobacteraceae; Burkholderiaceae Burkholderia; Burkholderia ambifaria; Prevotellaceae Prevotella; Burkholderiales Comamonadaceae; Burkholderia thailandensis; Alistipes obesi; Blautia stercoris; Ruminococcus bromii; Pelomonas aquatica; Peptostreptococcaceae Romboutsia; Bacteroides coprocola; Streptococcus thermophilus; Ruminococcaceae Oscillibacter; Alistipes ihumii; Ruminococcus callidus; Phyllobacteriaceae Phyllobacterium; Coprococcus eutactus; Peptostreptococcaceae Intestinibacter; Clostridioides difficile; Enterobacterales Enterobacteriaceae; Enterococcaceae Enterococcus; Peptostreptococcaceae Clostridium XI; Gammaproteobacteria Enterobacterales; Bacilli Lactobacillus; Eggerthella lenta; Erysipelatoclostridium [Clostridium] innocuum; Enterobacteriaceae Citrobacter; Lachnospiraceae Clostridium XIVa; Lachnoclostridium [Clostridium] bolteae; Erysipelatoclostridium ramosum; Hungatella effluvia; Veillonella parvula; Lactobacilluseae Lactobacillus; Blautia [Ruminococcus] gnavus; Enterococcus saccharolyticus; and Coriobacteriaceae Eggerthella, wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.

Methods can comprise measuring of one or more taxonomical features from a biological sample from a individual comprising determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least, at most, or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 56, 47, 48, 49, 50, or all of: Anaerostipes hadrus; Lachnospiraceae Dorea; Dorea longicatena; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Blautia obeum; Coprococcus comes; Roseburia intestinalis; Lactobacillus rogosae; Eubacterium [Eubacterium] eligens; Bacteroidia Bacteroidales; Peptostreptococcaceae Romboutsia; Coriobacteriaceae Collinsella; Acidaminococcaceae Acidaminococcus; Prevotellaceae Prevotella; Prevotella copri; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Ruminococcus; Alistipes obesi; Betaproteobacteria Burkholderiales; Ruminococcus bromii; Lachnospiraceae Lachnoclostridium; Bifidobacterium adolescentis; Actinomycetales Actinomycetaceae; Ruminococcaceae Intestinimonas; Bacteroides eggerthii; Clostridioides difficile; Peptostreptococcaceae Clostridium XI; Enterobacteriaceae Citrobacter; Enterobacterales Enterobacteriaceae; Veillonella parvula; Enterococcaceae Enterococcus; Lactobacillies Enterococcaceae; Erysipelatoclostridium [Clostridium] innocuum; Pectobacterium carotovorum; Enterobacteriales Enterobacteriaceae; Bacteroides xylanisolvens; Enterococcus saccharolyticus; Clostridium paraputrificum; Salmonella enterica; Erysipelatoclostridium ramosum; Hungatella effluvia; Bacteroides koreensis; Bacilli Lactobacillus; Blautia product; Klebsiella quasipneumoniae; Ruthenibacterium lactatiformans; Veillonella dispar; Coriobacteriaceae Eggerthella; and Lachnospiraceae Hungatella; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.

Also described herein are complexes comprising a plurality of oligonucleotide primer sets hybridized to nucleic acid template sequences, wherein the nucleic acid template sequences are taxonomically specific sequences associated with taxonomical features identified in tables 9-17. Complexes can comprise at least 5 or at least 10 oligonucleotide primer sets are hybridized to nucleic acid template sequences.

Also described herein are kits for measuring for presence or absence or a certain level of one or more taxonomical feature(s) from a biological sample from an individual, comprising: (a) a plurality of sets of oligonucleotide primers, wherein each set of primers hybridize to a different nucleic acid template sequence for amplifying taxonomically specific sequences; and optionally (b) a polymerase enzyme; wherein the individual sets of oligonucleotide primers hybridize to a taxonomically specific sequence associated with the taxonomical features identified in tables 9-17.

A kit can comprise a master mix further comprises deoxynucleoside triphosphates; and at least one indicator for detecting an amplification product by a change in color or fluorescence. A kit can comprise deoxynucleoside triphosphates comprise dTTP, dGTP, dATP, dCTP and/or dUTP. A kit can comprise at least 5, at least 10, at least 20, at least 40, at least 60, at least 80, at least 100, at least 120, at least 140, at least 160, at least 180, or at least 200 individual sets of oligonucleotide primers. A kit can comprise individual sets of oligonucleotide primers bound to a support substrate. A kit can comprise oligonucleotide primers directed to at least 4, at least or exactly 10, at least or exactly 20, at least or exactly 30, at least or exactly 40, or more than 40, or any range derivable therein, taxonomically specific sequences associated with the following taxonomic features: Bacteroides; Eubacterium rectale; Ruminococcus; Faecalibacterium; Enterococcus; Enterobacteriaceae; Roseburia; Coprococcus; Dorea; Lachnoclostridium; Clostridium XIVa; Erysipelatoclostridium; Alistipes; Fusicatenibacter; Odoribacter; Lactobacillus; Anaerostipes; Collinsella; Clostridioides; Klebsiella; Agathobaculum butyriciproducens; Veillonella; Phascolarctobacterium; Adlercreutzia; Clostridium; Eggerthella; Sutterellaceae Parasutterella; barnesiella; Eubacterium; Clostridium IV; Gemmiger; Streptococcus; Dialister; Escherichia; Colidextribacter; Oxalobacter; Prevotella; Clostridium XVIII; Actinomyces; and Fusobacterium.

The individual may be of any kind, and the methods may be performed before, during, or after the individual has diarrhea. The methods may be performed when the individual is in need of antibiotics and/or antimicrobials of any kind or when the individual has already had antibiotics and/or antimicrobials of any kind. The methods may be performed as routine medical practice for an individual. The methods may be performed as preventative medical practice for an individual.

BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.

FIGS. 1A-1D, describes how taxonomic and clustering accuracy are influenced by 16S amplicon sequence length, orientation and variable region. 1A) Depicts a schematic showing how taxonomic accuracy is improved by increasing amplicon length. 1B) Depicts Spearman correlations of VSEARCH-based de novo clustering with 99% similarity for 16S V1-V3 amplicons of variable length from the same parent 16S sequence. Orange boxes show the optimal sequence length range for clustering (FIGS. 7A-7D show results for other 16S variable regions; the associated Spearman correlation results for other clustering/denoising tools are available upon request). 1C) Depicts confidence score and 1D) depicts accuracy of taxonomic assignment for simulated amplicons; as shown, confidence and accuracy are significantly influenced by sequence length and orientation (FIGS. 9A-9D shows results for other 16S variable regions). “Org.” stands for original amplicon length without trimming; *=p<0.05 (Wilcoxon test; correct vs wrong genus/species annotations at each amplicon length).

FIGS. 2A-2D, describes the Taxa4Meta pipeline and associated taxonomic profiling of 16S amplicon data. 2A) Depicts a schematic of the Taxa4Meta analysis workflow. 2B) Depicts Spearman correlations for family abundances comparing simulated 16S data input (ground truth) with taxonomic output using different taxonomic profilers covering a range of 16S variable regions (FIGS. 11A-11C shows additional benchmarking results). 2C) Depicts hierarchical clustering of family abundance profiles (−log 2 transformation of average relative abundances) generated by different taxonomic profilers. Kruskal-Wallis (KW) test together with Benjamini and Hochberg (BH) correction was used to compare family abundances for each pipeline for each data type: *=p<0.05 false discovery rate (FDR). Shotgun metagenomic and 16S amplicon sequencing were performed on the same human stool DNA (N=27) using 454 pyrosequencing or Illumina platforms. 2D) Depicts how Taxa4Meta abundance profiles showed the highest similarity to shotgun WGS data (Kraken2). Abundance-weighted Jaccard distance was calculated between 16S profiler-specific outputs versus gold standard WGS (Kraken2). The most abundant 29 family features (totaling 0.95±0.07 (SD) of family abundance) across all analyses were used for visualization and benchmarking.

FIGS. 3A-3C, describes how pan-microbiome analysis identifies diarrheal disease-specific taxa. 3A) Depicts β-diversity analysis of Taxa4Meta collapsed species profiles (green ellipse, healthy-associated microbiome; red ellipse, Clostridium difficile Infection (CDI)-associated microbiome). ANOSIM testing was used to compare disease vs controls. Abundance-weighted Jaccard distance was used for β-diversity analysis. 3B) Depicts quantification of FIG. 3A, relative abundance of pathobiome (Enterococcus, Streptococcus, Clostridioides, Escherichia/Shigella, Klebsiella and Pseudomonas) was significantly elevated in Crohn's disease (CD) and CDI patients. ***=p<0.001 (pairwise Wilcoxon test with BH correction). ANOSIM test was performed with 999 permutations. Boxplots show interquartile range (IQR), median and whiskers extended to values <1.5×IQR from 1st and 3rd quartile, respectively. 3C) Depicts average family relative abundance of each disease group (FIG. 16 shows the top 21 abundant family abundances across datasets). *=p<0.05 (KW test with BH correction).

FIGS. 4A-4D, describes how Taxa4Meta mediated pan-microbiome profiling improves supervised classification. 4A) Depicts β-diversity analysis of Taxa4Meta collapsed species profiles for V1V3 and V3V5 amplicon data generated from the same DNA extracts²⁸(control or functional gastrointestinal disorders (FGIDs)). n.s., not significant (pairwise Wilcoxon test with BH correction). 4B) depicts ROC analysis of supervised classification (random forest, (RF)) using 16S-region specific vs. pan-microbiome genera. The roc.test( ) function from pROC package was used to compare two ROC curves: **=p<0.01 (delong method). 4C) Depicts β-diversity analysis of multiple CDI cohorts (datasets #22-27) using collapsed species profiles generated by Taxa4Meta. ***=p<0.001 (pairwise Wilcoxon test with BH correction). 4D) Depicts improved cross-validation of CDI and Control subjects using pan-microbiome profiling of 454 and Illumina data. Ten iterations of random, stratified sub-sampling of training sets were performed. The random forest was used for supervised classification analysis. n.s., not significant (pairwise Wilcoxon test with BH correction). Area-under-the-curve (AUC); classification accuracy (CA). ANOSIM test was performed with 999 permutations. Stacking model of NB, RF and SVM learners was used for supervised classification analysis. Boxplots show interquartile range (IQR), median and whiskers extended to values <1.5×IQR from 1st and 3rd quartile, respectively.

FIGS. 5A-5C, describes supervised classification of chronic diarrheal diseases using pan-microbiome taxonomy. 5A) Depicts an outline of supervised classifications performed across clinical disease groups and matched controls. 5B) Depicts the top 10 species features ranked by random forest across five clinical groups. 5C) Depicts binary classification using Taxa4Meta collapsed species profiles. Individual or combined RF-ranked top Taxa4Meta 100 features were used for binary classification analysis. *=p<0.05; n.s., not significant (pairwise Wilcoxon test). Boxplots show interquartile range (IQR), median and whiskers extended to values <1.5×IQR from 1st and 3rd quartile, respectively.

FIGS. 6A-6B, describes a prototypical pan-microbiome diagnostic workflow for stratifying CDI, inflammatory bowel disease (IBD), and irritable bowel syndrome (IBS) patients. 6A) Depicts a scheme for diarrheal patient stratification using binary classification models. All collapsed species features were used for classification in the training process. 6B) Depicts independent cohort validation of CDI and IBD models. A binary threshold of 0.5 was applied for calculating disease classification accuracy. Cohort information is provided in Table 21. *=p<0.001 (pairwise Wilcoxon test with BH correction). Boxplots show interquartile range (IQR), median and whiskers extended to values <1.5×IQR from 1st and 3rd quartile, respectively.

FIGS. 7A-7C, describes the identification of region-specific optimal length ranges for clustering 16S amplicons. 7A) Depicts Spearman correlations of VSEARCH-based de novo clustering with 99% similarity for 16S V3V5 amplicons of variable length from the same parent 16S sequence. 7B) Depicts Spearman correlations of VSEARCH-based de novo clustering with 99% similarity for 16S V6V9 amplicons of variable length from the same parent 16S sequence. 7C) Depicts Spearman correlations of VSEARCH-based de novo clustering with 99% similarity for 16S V4 amplicons of variable length from the same parent 16S sequence. Orange box highlights variable length input reads used for sequence clustering by Taxa4Meta. *=p<0.05; **=p<0.01 (Wilcoxon test).

FIG. 8, describes how controlling the identity and coverage of sequence alignment minimizes taxonomic over-classification. Taxonomic annotation using the Bayesian LCA-based Taxonomic Classification (BLCA) tool was performed full-length amplicons simulated from unclassified (family level) 16S sequences of RDP database (release 11.5). Ten iterations of BLCA run were performed for 1% of unclassified sequences. Pairwise Wilcoxon test with Benjamini-Hochberg Procedure was used for any two group comparison. Over-classification rate is the classified proportion of BLCA annotation without considering the confidence score of taxonomic assignment. ***=p<0.001 (pairwise Wilcoxon test with BH correction).

FIGS. 9A-9D, describes how taxonomic accuracy is dependent on read length, sequence orientation, and variable 16S amplicon region. Confidence score of taxonomic assignment and the proportion of correct versus wrong annotated reads are plotted for 9A) V1V3, 9B) V3V5, 9C) V4, and 9D) V6V9 regions. Orange box highlights optimal length range for accurate sequence clustering using VSEARCH with 99% similarity. This sequence range was later applied in the Taxa4Meta workflow. Confidence scores are presented as mean±SEM. *=p<0.05 (Wilcoxon test).

FIGS. 10A-10B, describes how confidence thresholds for accurate taxonomic assignment were determined. Different confidence thresholds for taxonomic assignment using the BLCA tool at both genus 10A) and species 10B) rank were benchmarked by calculating the proportion of true positive (TP), false negative (FN), true negative (TN) and false positive (FP) annotations for combined variable length amplicons generated from NCBI 16S RefSeq database with known taxonomic lineage. TP and FP annotations are present while TN and FN annotations are absent in the final annotation output. Data are presented as mean±SEM.

FIGS. 11A-11C, describes the Benchmarking of Taxa4Meta and other pipelines using simulated amplicon data of variable lengths. 11A) Depicts hierarchical clustering of family abundance profiles (−log 2 transformation of relative abundance) generated by different analytic pipelines. NCBI 16S rRNA sequences were used for data simulation, but cutadapt failed to extract targeted regions of some sequences due to strict mapping of degenerate primers to full-length 16S sequence. Read count was randomly generated from 1 to 50 for each amplicon sequence (V1-V3, V3-V5, V4 and V6-V9) prior to length trimming; amplicons with variable lengths (suggested by Taxa4Meta core parameters) were concatenated for benchmarking different pipelines. Average total abundance at family level matched to ground truth is 0.95 with the standard deviation of 0.02 across all results from different pipelines. 11B) Depicts the percentage of undetected families by each pipeline for simulated amplicons of different 16S variable regions. 11C) Depicts relative abundance of C. difficile from simulated amplicon data analyzed by different pipelines. Only two strains of C. difficile were included in NCBI 16S rRNA sequence database, but V3-V5 amplicons of C. difficile were removed during data simulation because their amplicon lengths did not fall into the length range that was used (for more information, see Table 22).

FIGS. 12A-12D, describes how consistent Taxa4Meta-based genus and family abundance profiles are across different sequence strategies. 12A) Depicts total read counts from Taxa4Meta output (mean±SD; ***=p<0.001). 12B) Depicts relative family taxonomic abundance. 12C) Depicts relative abundance of shared and non-shared genera. 12D) Depicts Pearson correlations of the relative abundance of commonly shared genera across different 16S sequencing strategies. All correlations are significant (p<0.001).

FIG. 13, describes how Taxa4Meta analysis results in low error rates in species calls for 16S amplicon data. Species identified by MetaPhlAn2 were used as the reference since it has high precision in species identification. Bacterial tax_ids retrieved from NCBI TaxIdentifier tool for each species identified by different pipelines were used for mapping across taxonomic profiles since species names might be reclassified but tax_ids are preserved. ***=p<0.001 (pairwise Wilcoxon test with BH correction).

FIGS. 14A-14B, describes how meta-analysis controls of diarrheal microbiome datasets show three conventional gut enterotypes. Bray-Curtis dissimilarity metric with nonmetric multidimensional scaling (NMDS) was used in β-diversity analysis procedure for showing abundant taxonomic features at 14A) genus and 14B) family rank that drive sample clustering. ANOSIM analysis was performed with Bray-Curtis distance profile for pairwise comparison. Higher R values (>0.2) of ANOSIM test indicate more difference between groups. The 2D kernel density estimation of samples was measured by geom_density_2d from ggplot2 package and was showed as contours in NMDS ordination plot. The envfit function from vegan package was used for fitting taxonomic features (family relative abundance) to 2-dimensional NMDS ordination plot. ***=p<0.001 (Wilcoxon test).

FIGS. 15A-15B, depicts the Alpha-diversity indices of meta-analysis training datasets. 15A) Depicts Richness and Shannon index for each disease group. 15B) Depicts Richness and Shannon index for each dataset. Log 10 transformation was performed for richness measure from breakaway package. KW test was performed across groups or datasets of each sample group as indicated in each sub-plot. Data are presented as the median with first and third quartiles in the boxplot.

FIG. 16, depicts the taxonomic abundance of meta-analysis training datasets. Hierarchical clustering of family-level relative abundance profiles (−log 2 transformation of median relative abundance) of each sample group of each dataset. Kruskal-Wallis (KW) test together with Benjamini-Hochberg procedure was used to compare family-level relative abundance of sample groups of all dataset: *=p<0.05 (FDR). Only top 21 abundant family features totaling the average relative abundance of 0.93 (standard deviation of 0.095) across all samples were used for heatmap generation and clustering analysis.

FIG. 17, depicts the total relative abundance of classified and unclassified species across adult and pediatric datasets. Data are presented as mean±SD.

FIG. 18, depicts random forest-based feature ranking for pediatric FGID patients using individual or pan-microbiome data.

FIG. 19, describes how pan-microbiome analysis can identify metabolic pathways related to diarrheal disease-specific taxa and metagenomic functions. Depicted is a heatmap of PICRUSt2 pathway analysis showing disease-specific (UC. CDI, CD, Control, IBS) metabolic functions. Median abundance of selected differential pathways was plotted for each adult diarrheal disease (see FIGS. 23A-23E for top 20 differential pathways identified between each adult diarrheal disease and healthy controls.). *=p<0.05 (KW test with BH correction)

FIGS. 20A-20D, describes how gut enterotype clusters can impact the accuracy of supervised classification models. 20A) Depicts a bar graph depicting the relative abundance of five enterotype clusters in meta-analysis adult datasets. DMM was used for enterotyping analysis based on relative abundance profile at family level. 20B) Depicts the distribution of five enterotype clusters in five clinical groups (Control, IBS, UC, CD, and CDI). 20C) Depicts the workflow of random sub-sampling for supervised classification of enterotype-specific gut microbiome. Ninety samples from each clinical group were sampled to create training and validation datasets with the balanced sample count for further classification. 20D) Depicts independent validation of supervised classifiers (random forest) shown in panel C. Top 100 features ranked by random forest were used for classification (for additional details, see Tables 1-17). Each circle represents the overall classification accuracy of each non-trained subsampled dataset. Feature selection was not performed for this analysis. ***=p<0.001; n.s., not significant (pairwise Wilcoxon test with BH correction).

FIGS. 21A-21B, describes supervised classification of chronic diarrheal diseases using pan-microbiome taxonomic and functional-pathway features. 21A) Depicts a comprehensive classification analysis using individual or combined RF-ranked top 100 Taxa4Meta collapsed species and RF-ranked top 100 PICRUSt2 pathways. Statistical test was performed for data excluding results (as outlier) generated with NB learner: *=p<0.05; n.s., not significant (pairwise Wilcoxon test with BH correction). 21B) Depicts how binary classification using Taxa4Meta collapsed species profile demonstrates improved scores of AUC and CA when compared to PICRUSt2 pathway profile independent of different learners. Individual or combined RF-ranked top 100 features of Taxa4Meta and PICRUSt2 were used for binary classification analysis. *=p<0.05; n.s., not significant (Wilcoxon test).

FIG. 22, describes benchmarking of Taxa4Meta and other pipelines using simulated amplicon data of variable ranks. In particular, the figure depicts precision species calls on C. difficile amplicons is associated with 16S variable regions, sequence length and orientation. C. difficile 16S rRNA gene sequences collected from SILVA, RDP and GG databases were confirmed by BLASTN prior to amplicon simulation.

FIGS. 23A-23E, describes the identification of differential metabolic pathways in chronic diarrheal diseases. 23A through 23D) Depict LDA scores of the top 20 Random Forest (RF)-ranked pathways between two adult groups for 23A) CDI vs Control, 23B) CD vs Control, 23C) UC vs Control, 23D) IBS vs Control. 23E) Depicts a heatmap of differential pathways (from A-D) across adult diarrheal patients. Pink box highlights important pathways that can differentiate diarrheal diseases.

FIG. 24, describes AUC and CA values of binary classification models using Taxa4Meta collapsed species and PICRUSt2 pathway profiles. *=p<0.05; n.s., not significant (pairwise Wilcoxon test with BH correction).

DETAILED DESCRIPTION

Described herein are methods and compositions suitable for the treatment of disorders associated with dysbiosis of the microbiome. Use of the one or more compositions may be employed based on methods described herein. Methods and/or compositions described herein may be included as components of one or more kits suitable for treatment of disorders associated with dysbiosis of the microbiome. Other embodiments are discussed throughout this application. Any embodiment discussed with respect to one aspect of the disclosure applies to other aspects of the disclosure as well and vice versa. The embodiments in the Example section are understood to be embodiments that are applicable to all aspects of the technology described herein.

The use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims and/or the specification may mean “one.” but it is also consistent with the meaning of “one or more.” “at least one.” and “one or more than one.”

As used herein, the term “about” or “approximately” refers to a quantity, level, value, number, frequency, percentage, dimension, size, amount, weight or length that varies by as much as 30, 25, 20, 25, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1% to a reference quantity, level, value, number, frequency, percentage, dimension, size, amount, weight or length. In particular embodiments, the terms “about” or “approximately” when preceding a numerical value indicates the value plus or minus a range of 15%, 10%, 5%, or 1%. With respect to biological systems or processes, the term can mean within an order of magnitude, preferably within 5-fold, and more preferably within 2-fold, of a value. Unless otherwise stated, the term ‘about’ means within an acceptable error range for the particular value.

The use of the term “or” in the claims is used to mean “and/or” unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and “and/or.” It is also contemplated that anything listed using the term “or” may also be specifically excluded.

As used in this specification and claim(s), the words “comprising” (and any form of comprising, such as “comprise” and “comprises”), “having” (and any form of having, such as “have” and “has”), “including” (and any form of including, such as “includes” and “include”) or “containing” (and any form of containing, such as “contains” and “contain”) are inclusive or open-ended and do not exclude additional, unrecited elements or method steps.

The term “Antimicrobial” as used herein is a general term for drugs, chemicals, or other substances that either kill or slow the growth of microbes. Among the antimicrobial agents are antibacterial drugs, antiviral agents, antifungal agents, and antiparasitic drugs. In patients this includes drugs and/or treatment that impacts microbiome community composition.

As used herein, the terms “arrays”, “microarrays”, and “DNA chips” refer to an array of distinct oligonucleotides affixed to a substrate, such as glass, plastic, paper, nylon or other type of membrane, filter, chip, or any other suitable solid support. The polynucleotides can be synthesized directly on the substrate, or synthesized separate from the substrate and then affixed to the substrate. The oligonucleotides on the array may be designed to bind or hybridize to specific nucleic acids, such as a specific SNP or a specific CNV, for example.

The terms “Clostridioides difficile infection” “C. difficile infection” or “CDI” as used herein refers to an individual that has presence of Clostridioides difficile in their body to an extent and under conditions in which a sufficient level of toxins from the Clostridioides difficile results in diarrhea. This is in contrast to presence of Clostridioides difficile in an individual that is considered a carrier for the bacteria and that has no diarrhea.

The term “classifier” as used herein refers to an algorithm that implements a disease classification, notably CDI, IBS, IBD UC, and/or IBD CD diagnosis, or CDI, IBS, IBD UC, and/or IBD CD risk, or risk of C. difficile colonization. In other embodiments, the term refers to an algorithm that implements a disease classification for diagnosis or risk or risk of colonization for one or more pathogens other than C. difficile.

The term “feature” as used herein refers to a microbe, biological molecule, and/or metabolic pathway that is representative of a detectable difference between a control or reference standard and the corresponding microbe, biological molecule, and/or metabolic pathway in an individual with or at risk of developing CDI, IBS, IBD UC, and/or IBD CD. A feature may be the presence, absence, and/or levels of a microbe, nucleic acid sequence (such as 16S rRNA), protein, small molecule, metabolic pathway, and/or a combination thereof.

The term “pan-microbiome” as used herein refers to a composite of two or microbiomes, for example, a composite of two or more data sets reflective of two or more microbiomes. A pan-microbiome may be larger than any single microbial community of an individual or a group. In some embodiments, a pan-microbiome includes two or more populations, two or more demographics, and/or data collected through two or more acquisition methodologies.

As used herein, the term “oligonucleotide” refers to a short chain of nucleic acids, cither RNA, DNA, and/or PNA. The length of the oligonucleotide could be less than 10 base pairs, or at minimum or no more than 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49,50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, or 75 base pairs. The oligonucleotide can be synthesized using by methods including phosphodiester synthesis, phosphotriester synthesis, phosphite triester synthesis, phosphoramidite synthesis, solid support synthesis, in vitro transcription, or any other method known in the art.

As used herein, the term “PCR primer” refers to an oligonucleotide that is used to amplify a strand of nucleic acid in a polymerase chain reaction (PCR). Primers may have 50%, 51%, 52%, 53%, 54%, 55%, 56%, 57%, 58%, 59%, 60%, 61%, 62%, 63%, 64%, 65%, 66%, 67%, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, 79%, 80%, 81%, 82%, 83%, 84%, 85%, 86%, 87%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% homology to the template the primers hybridize to, wherein the 3′ nucleotide of the primer is complementary to the template. In some embodiments, lower annealing temperatures are used for initial cycles, for example cycles 1, 2, 3, 4, and/or 5, of the reaction.

“Treatment,” “treat,” or “treating” means a method of reducing the effects of a disease or condition. Treatment can also refer to a method of reducing the disease or condition itself rather than just the symptoms. The treatment can be any reduction from pre-treatment levels and can be but is not limited to the complete ablation of the disease, condition, or the symptoms of the disease or condition. Therefore, in the disclosed methods, treatment” can refer to a 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% reduction in the severity of an established disease or the disease progression, including reduction in the severity of at least one symptom of the disease. For example, a disclosed method for reducing the immunogenicity of cells is considered to be a treatment if there is a detectable reduction in the immunogenicity of cells when compared to pre-treatment levels in the same subject or control subjects. Thus, the reduction can be a 10, 20, 30, 40, 50, 60, 70, 80, 90, 100%, or any amount of reduction in between as compared to native or control levels. It is understood and herein contemplated that “treatment” does not necessarily refer to a cure of the disease or condition, but an improvement in the outlook of a disease or condition. In specific embodiments, treatment refers to the lessening in severity or extent of at least one symptom and may alternatively or in addition refer to a delay in the onset of at least one symptom.

“Subject” may refer to an organism that comprises a microbiome. In certain embodiments, it refers to a human patient. In certain embodiments, it refers to an animal.

Microbiome science is a rapidly evolving field. In particular, advances in sequencing strategies and bioinformatics are facilitating improvements in stake holder's understanding of host-microbiota interactions^1-3. Nevertheless, these technological advances should not dissuade the use of retrospective microbiome data for development of methods of diagnosis, methods of treatment, and/or development of treatment compositions. The scientific community places great value on prior sequencing efforts that have explored microbiome community dynamics in human pathogenesis^4,5,20,22, because these projects could collectively provide critical insight into disease-specific associations. However, individual clinical microbiome surveys often utilize cohort-specific sequencing platforms, 16S primer regions and bioinformatics pipelines, which the inventors have systematically demonstrated herein, requires a consolidated bioinformatics approach to mitigate technological and demographic bias, as well as taxonomic misclassification. The findings presented herein show that previous microbiome meta-analyses have not adequately addressed these limitations^20,22,23. To address this, the inventors designed Taxa4Meta, a bioinformatics pipeline for accurate taxonomic profiling after systematically benchmarking sequence orientation and length so that data output can be reliably utilized from different 16S variable regions. Given the challenges of accurately merging OTU/ASV tables generated from different 16S variable regions, the inventors show that collapsed taxonomic annotations of Taxa4Meta OTU profiles offer a valuable new binning approach to facilitate meta-analysis of diverse 16S amplicon data.

Supervised classification represents an important downstream application of clinical microbiome surveys for development of diagnostic pipelines and the prescribing of subsequent treatment regimens, especially for gastrointestinal diseases where altered community dynamics are reported^{4,5,18,19,21,24-26}. Generally, diagnostic workflows require construction of large curated databases to facilitate cohort-specific classifier training and cross-validation of disease-specific biomarkers. Population-scale meta-analysis represents an attractive approach to adequately power microbiome surveys for disease classification because of the need to control for large variations in human genetics and demographics², as well as the technology bias¹²that contributes to false discovery rates. Notably, when applying the Taxa4Meta pipeline to identical DNA extracts sequenced using different strategies, as shown herein, the inventors have identified several prominent disease classification limitations due to this bias. To compensate for these technological hurdles, the inventors have developed a pan-microbiome profiling concept that achieves superior disease classification accuracy.

Taken together, the inventors have addressed a significant bioinformatics challenge using a new workflow (Taxa4Meta) developed for accurate sequence clustering and taxonomic annotation across multiple 16S regions. As described herein, Taxa4Meta was applied to comprehensively re-analyze diverse 16S datasets generated from multiple retrospective gastrointestinal disease cohorts investigated across four continents. Collapsed species abundance for each 16S dataset were successfully combined for downstream microbiome interpretation and supervised classification of diarrheal patients who are difficult to diagnose because of overlapping gastrointestinal symptoms. This improved classification of diarrheal patients can be leveraged for improved methods of patient treatment, and/or identification of compositions for treatment of the underlying causes of dysbiosis. The “best practices” approach disclosed herein facilitated construction of a prototypic diagnostic workflow based on disease-specific pan-microbiome biomarkers.

Other objects, features and advantages of the present disclosure will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples, while indicating specific embodiments, are given by way of illustration only, since various changes and modifications within the spirit and scope of the immediate disclosure will become apparent to those skilled in the art from this detailed description

I. Diseases Associated with Microbiome Dysbiosis

The human gut microbiome comprises bacteria, viruses, and fungi ideally living symbiotically with their human host. Individual species and collective bacterial functions within the gut microbiome confer many benefits throughout life including metabolizing dietary contributions, educating the immune system, defending against pathogens, and contributing to overall health and optimal growth. The gut microbiome is affected by and influences pathologies including but not limited to inflammatory bowel disease (IBD; both ulcerative colitis (UC) and Crohn's disease (CD)), Clostridium difficile infection (CDI), and irritable bowel syndrome (IBS).

A. Clostridium difficile infection (CDI)

Clostridium difficile is a bacterium that causes an infection (CDI) of the large intestine (colon). Symptoms can range from diarrhea to life-threatening damage to the colon. The bacterium is often referred to as C. difficile or C. diff. Illness from C. difficile typically occurs after use of antibiotic medications. It most commonly affects older adults in hospitals or in long-term care facilities. In the United States, about 200,000 people are infected annually with C. difficile in a hospital or care setting. Thankfully these numbers are trending lower than in previous years because of improved prevention measures. People not in care settings or hospitals also can develop C. difficile infection. Some strains of the bacterium in the general population may cause serious infections or are more likely to affect younger people. In the United States, about 170,000 infections occur annually outside of health care settings, and worryingly these numbers are increasing. Some people carry C. difficile bacteria in their intestines but never become sick. These individuals are carriers of the bacteria and may spread infections. Signs and symptoms usually develop within 5 to 10 days after starting a course of antibiotics. However, they may occur as soon as the first day or up to three months later. The most common signs and symptoms of mild to moderate C. difficile infection are: watery diarrhea three or more times a day for more than one day and/or mild abdominal cramping and tenderness. People who have a severe C. difficile infection tend to become dehydrated and may need to be hospitalized. C. difficile can cause the colon to become inflamed and sometimes form patches of raw tissue that can bleed or produce pus. Signs and symptoms of severe infection include: watery diarrhea as often as 10 to 15 times a day, abdominal cramping and pain (which may be severe), rapid heart rate, dehydration, fever, nausea, increased white blood cell count, kidney failure, loss of appetite, swollen abdomen, weight loss, and/or blood or pus in the stool. C. difficile infection that is severe and sudden, an uncommon condition, may also cause intestinal inflammation leading to enlargement of the colon (also called toxic megacolon) and sepsis. Sepsis is a life-threatening condition that occurs when the body's response to an infection damages its own tissues. People who have these conditions are generally admitted to an intensive care unit.

C. difficile bacteria enter the body through the mouth. They can begin reproducing in the small intestine. When they reach the large intestine (colon), they can release tissue-damaging toxins. These toxins destroy cells, produce patches of inflammatory cells and cellular debris, and cause watery diarrhea. When the bacteria are outside the colon, virtually anywhere in the environment, they are in a dormant state, or essentially quiescent. This enables them to survive for a long time in any number of places, including but not limited to human or animal feces, surfaces in a room, unwashed hands, soil, water, and/or food. When bacteria once again find their way into a person's digestive system, they begin to produce infection again. The ability of dormant C. difficile to survive outside the body enables the generally easy transmission of the bacterium, particularly in the absence of thorough hand-washing and cleaning.

Risk factors associated with developing a C. difficile infection include but are not limited to, taking antibiotics or other medications such as Clindamycin, Cephalosporins, Penicillin's, Fluoroquinolones, and/or potentially certain proton pump inhibitors. The majority of C. difficile infections occur in people who are or who have recently been in a health care setting, including hospitals, nursing homes and long-term care facilities, where germs spread easily, antibiotic use is common and people are especially vulnerable to infection. Additionally, certain medical conditions or procedures may increase an individual's susceptibility to a C. difficile infection, such as IBS, a weakened immune system from a medical condition or treatment (e.g., chemotherapy), chronic kidney disease, a gastrointestinal procedure, and/or other abdominal surgery. Additionally, age is a major risk factor for CDI infection.

Complications associated with C. difficile infection include but are not limited to: dehydration, kidney failure, toxic megacolon, bowel perforation, and/or death. The necessity for swift and correct diagnosis and initiation of appropriate therapeutic interventions are key steps in limiting the impact of this potentially devastating disease. Methods and compositions disclosed facilitate this process.

B. Irritable Bowel Syndrome (IBS)

Irritable bowel syndrome (IBS) is a common disorder that affects the large intestine. Signs and symptoms include cramping, abdominal pain, bloating, gas, and diarrhea or constipation, or both. IBS is a chronic condition that will require long term management. Only a small number of people with IBS have severe signs and symptoms. Some people can control their symptoms by managing diet, lifestyle and stress. More-severe symptoms can be treated with medication and counseling.

The signs and symptoms of IBS vary but are usually present for a long time. The most common include: abdominal pain, cramping or bloating that is related to passing a bowel movement, changes in appearance of bowel movement, changes in how often you are having a bowel movement, and/or other symptoms that are often related include bloating, increased gas or mucus in the stool. Certain severe symptoms associated with IBS may include: weight loss, diarrhea at night, rectal bleeding, iron deficiency anemia, unexplained vomiting, difficulty swallowing, and/or persistent paint hat isn't relieved by passing gas or a bowel movement.

The precise cause of IBS is not yet known. But factors that appear to play a role in IBS disease progression include: muscle contractions of the intestine that are stronger and/or last longer than normal and/or weaker than normal, poor nervous system signaling, severe infection, early life stress, and/or changes in the gut microbiome. IBS symptom “flares” can be triggered by certain foods such as beverages, wheat, dairy, citrus fruits, beans, cabbage, milk and/or carbonated drinks, or stress.

Risk factors associated with IBS include being young, being female, having a family history of IBS, and/or having anxiety, depression and/or other mental health issues.

Major complications associated with IBS include chronic constipation or diarrhea that can cause hemorrhoids, a reduction in the quality of life, and exacerbation of mood disorders.

Correct diagnosis and management of IBS is an essential step in long term management of the disease. Methods and compositions disclosed facilitate this process.

C. Inflammatory Bowel Disease (IBD)

Inflammatory bowel disease (IBD) is an umbrella term used to describe disorders that involve chronic inflammation of your digestive tract. The two major types of IBD include Ulcerative colitis (UC) which involves inflammation and development of ulcers along the superficial lining of the large intestine and rectum; and Crohn's disease (CD) which is characterized by inflammation of the lining of the digestive tract which can also involve the deeper layers of the digestive tract. Both ulcerative colitis and Crohn's disease usually are characterized by diarrhea, rectal bleeding, abdominal pain, fatigue and weight loss. IBD can be debilitating, and can sometimes lead to life-threatening complications.

Symptoms of IBD vary depending on the severity of the associated inflammation, and where in the digestive tract it occurs. Symptoms may range from mild to severe and may be interrupted by periods of remission. Symptoms common to both IBD UC and IBD CD include but are not limited to diarrhea, fatigue, abdominal pain and cramping, blood in the stool, reduced appetite, and/or unintended weight loss.

The exact causes of IBD remain elusive. However, it is thought that diet and stress may be involved, but perhaps these factors just aggravate the disease and are not the root cause. It is also thought that an immune system malfunction may also contribute to IBD development. When the immune system tries to fight off an invading virus or bacterium, an abnormal immune response causes the immune system to attack the cells in the digestive tract, too. Heredity also may play a role in that IBD is more common in people who have family members with the disease. However, most people with IBD don't have this family history.

Risk factors for development of IBD include but are not limited to age, race and/or ethnicity, family history, cigarette smoking and/or nonsteroidal anti-inflammatory medications (e.g., ibuprofen, naproxen sodium, etc.).

Complications associated with UC and/or CD include colon cancer, skin/eye/joint inflammation, medication side effects, primary sclerosing cholangitis, blood clots, bowel obstruction, malnutrition, fistulas, anal fissures, toxic megacolon, severe dehydration and/or perforation of the colon.

Correct diagnosis and management of IBD be it UC or CD is an essential step in long term management of the disease. Methods and compositions disclosed facilitate this process.

II. Methods of Identifying Features, Evaluating Levels of Features, and Classifying Disease State

Disclosed herein are methods of identifying features, and evaluating the presence, absence, or levels of said features in a sample. In certain embodiments, a feature may also be described as a biomarker. In certain embodiments, one or more features are used to classify (e.g., diagnose) a disease state and/or identify one or more effective treatment options for a patient with an intestinal disorder characterized by microbiome dysbiosis (e.g., CDI, IBS, IBD UC, and/or IBD CD). In some embodiments, one or more features are used to diagnose a disease state and/or identify one or more effective treatment options for a patient with an intestinal disorder characterized by diarrhea.

In certain embodiments, a feature is a taxonomical classification. In certain embodiments, a feature is the presence, absence, or level of one or more microbial taxonomic units (e.g., genera, species, etc.). In certain embodiments, a feature is a metabolic pathway. In some embodiments, disclosed herein are methods of using a pan-microbiome profiling pipeline as a method suitable for identification of certain core features that can be used for accurate downstream diagnosis, accurate method of treatment prescription, and/or treatment composition determination.

It is contemplated that features may be evaluated based on one or more associated gene products. In some embodiments, a gene product is an amplicon complementary to at least a portion of a gene. In some embodiments, a gene product is an RNA transcript. In some embodiments, a gene product is a structural and/or functional RNA transcript. In some embodiments, a gene product is a protein expressed by an RNA transcript. In some embodiments, a gene product is a metabolic pathway associated with expression of a number of gene products. In some embodiments, a gene product is a metabolic pathway associated with expression of a number of gene products from a number of different species.

In some embodiments, features are identified using a pan-microbiome approach. In some embodiments, utilization of a pan-microbiome approach to identify features can reduce technical and/or demographic bias. In some embodiments, a pan-microbiome approach is a method that identifies and selects classifier features by analysis of microbiome data generated from two or more different sequencing strategies (e.g., 16S sequencing strategies) and/or two or more populations (e.g., two or more demographically distinct populations). Examples of pan-microbiome approaches are described herein, non-limiting examples of data sets suitable for use in a pan-microbiome approach are listed in Table 21.

In certain embodiments, a meta-analysis to determine the presence, absence, levels, expression, and/or activity of one or more features disclosed herein for correlation with a disease state can be performed. In statistics, a meta-analysis combines the results of several studies that address a set of related research hypotheses. This is normally done by identification of a common measure of effect size, which is modeled using a form of meta-regression. Generally, three types of models can be distinguished in the literature on meta-analysis: simple regression, fixed effects meta-regression and random effects meta-regression. Resulting overall averages when controlling for study characteristics can be considered meta-effect sizes, which are more powerful estimates of the true effect size than those derived in a single study under a given single set of assumptions and conditions. A meta-gene expression value, in this context, is to be understood as being the median of the normalized expression of a marker gene or activity. Normalization of the expression of a marker gene is preferably achieved by dividing the expression level of the individual marker gene to be normalized by the respective individual median expression of this marker genes, wherein said median expression is preferably calculated from multiple measurements of the respective gene in a sufficiently large cohort of test individuals. In some embodiments, a test cohort comprises at least 3, 10, 100, 200, 1000 individuals or more including all values and ranges thereof. In some embodiments, dataset-specific bias can be removed or minimized allowing multiple datasets to be combined for meta-analyses (Sec Sims et al. BMC Medical Genomics (1:42), 1-14, 2008, which is incorporated herein by reference in its entirety). In some embodiments, a meta-analysis cohort comprises the combination of 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45 test cohorts or more including all values and ranges thereof.

A. Identification of Features Suitable for Classification of Disease State

In certain embodiments, determination of features suitable for classification of microbiome dysbiosis disease state and subsequent methods stemming therefrom occurs as represented in FIG. 2.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises simulation of full-length and/or region-specific 16S amplicon data. In certain embodiments, simulation of full-length and/or region-specific 16S amplicon data can be based on reference data bases (e.g., NCBI 16S rRNA RefSeq database (downloaded in July 2019), Ribosomal Database Project (RDP) database (release 11.5)²⁸, etc.). In certain embodiments, bioinformatics tools such as cutadapt (version 2.4)²⁹can be used to extract sequence fragments as full-length amplicons of targeted 16S variable regions (V1-V3, V3-V5, V4 and V6-V9) based on the forward and reverse primers (e.g., primers as listed in Table 22). In some embodiments, an error rate is permitted during sequence extraction, for example, an error rate of 0.05, 0.1, 0.15, 0.2, 0.25, etc. In certain embodiments, an error rate of 0.2 is permitted during sequence extraction. In certain embodiments, sequence length trimming and/or random simulation of sequence abundance and quality scores are performed for specific benchmarking purposes.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises benchmarking of sequence clustering and denoising using simulated amplicons, optionally with variable length. In certain embodiments, when benchmarking the accuracy of clustering or denoising for amplicon data using variable sequence lengths, random count ranging from 1 to 50 (e.g., 1, 2, 3, 4, 5 . . . 45, 46, 47, 48, 49, or 50) can be assigned for one or more or all parent full-length amplicons extracted from a reference database (e.g., NCBI 16S rRNA RefSeq sequences). In some embodiments, sequencing data may be generated in the reverse orientation and/or the forward orientation. In some embodiments, traditional 454 data is generated from reverse orientation, and length trimming from either forward or reverse orientation is applied to one or more, or each type of amplicon data. In some embodiments, length trimming results in 100, 150, 170, 200, 250, 300, 350, 400 and/or 450 bases for variable regions. e.g., V1-V3, V3-V5 and V6-V9 amplicon data. In some embodiments, length trimming results in 100, 150, 170, 200 and/or 250 bases for variable regions, e.g., V4 amplicon data. In some embodiments, random phred quality score (ASCII_BASE=33) ranging from 30 to 42 can be assigned to each base for sequencing denoising. In some embodiments, simulated amplicons of each sequence length represents one sample. In some embodiments, one or more or all samples with the same sequence orientation from the same 16S region can then be included for closed-reference or de novo clustering (e.g., using UCLUST (v1.2.22)³⁰or VSEARCH (v2.9)³¹or denoising using DADA2 (v1.8)³²). In some embodiments, sequence similarity thresholds including 0.97, 0.99 and 1.00 can be evaluated for each clustering strategy. In some embodiments, databases (e.g., the SILVA database (release 132)) can be used for closed-reference OTU picking. In some embodiments, simulated amplicons of variable length originating from the same parent full-length amplicon have the same sequence counts, in such situations, pairwise Spearman correlation analysis can be performed for sequence counts of any two sequence lengths (as two independent samples) in one or more OTU count tables

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises benchmarking of taxonomic over-classification. In some embodiments, taxonomic over-classification for short amplicon data represents an important criteria for controlling false positives. In some embodiments, using default parameters in the Bayesian-based Lowest Common Ancestor (BLCA) tool¹¹and its default database of NCBI 16S rRNA RefSeq can be used to annotate random and repeat sequences that were previously generated for benchmarking IDTAXA and other annotation tools¹⁰. In some embodiments, full-length 16S amplicons of unannotated sequences (e.g., at least down to family rank) are extracted from a suitable database (e.g., RDP database (release 11.5)) and are used for testing BLCA. In certain embodiments, BLASTN search of unannotated sequences against a suitable reference database (e.g., NCBI 16S rRNA RefSeq database) can be used to confirm that no best hits are identified at 97% threshold applied to either or both sequence identity and coverage. In some embodiments, simulated amplicons of unannotated RDP sequences are tested using different thresholds of sequence coverage and identity (e.g., ranging from 0.85 to 1.00 in BLCA). In some embodiments, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, or more iterations of random sub-sampling (e.g., 1%, 2%, 3%, 4%, 5%) and BLCA annotation on those unannotated amplicons are performed for statistical determination of optimal sequence coverage and identity required for BLCA. In some embodiments, ten iterations of random sub-sampling (1%) and BLCA annotation on those unannotated amplicons are performed for statistical determination of optimal sequence coverage and identity required for BLCA. In some embodiments, taxonomic over-classification rate is defined as the classifiable proportion of unannotated amplicons at species level. In some embodiments, the confidence score of taxonomic assignment is not considered at this stage.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises benchmarking of taxonomic accuracy using simulated amplicons of variable length. In some embodiments, benchmarking taxonomic accuracy of BLCA, simulated amplicons of variable length are generated by trimming full-length amplicons derived from a suitable database (e.g., NCBI 16S RefSeq) from either forward or reverse orientation. In some embodiments, trimming of full-length amplicons results in 80, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, 320, 340, 360, 380, 400, 420, 440, and/or 460 bases. In some embodiments, trimming of full-length amplicons results in 100, 150, 170, 200, 250, 300, 350, 400 and 450 bases for V1-V3, V3-V5 and V6-V9 amplicon data, and 100, 150, 170, 200 and 250 bases for V4 amplicon data. In some embodiments, suitable 16S amplicon lengths are determined according to FIG. 1B, FIGS. 7A-7C, FIG. 8, and/or FIGS. 9A-9D. In some embodiments, in addition to the known taxonomic lineage, the parent 16S sequences of simulated amplicons are also present in the BLCA default reference database using NCBI 16S RefSeq, thus taxonomic misclassification can be evaluated. In some embodiments, misclassification rate is defined as the proportion of incorrect annotations for simulated amplicons. In some embodiments, to further determine the optimal confidence threshold of BLCA for mitigating misclassification, amplicons with a selected sequence length range are combined to calculate the proportion of correct versus incorrect annotations using defined thresholds. In some embodiments, the already known taxonomic lineage, true positive (TP) and false negative (FN) hits are correct annotations, whereas true negative (TN) and false positive (FP) hits are incorrect annotations.

In most embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises design of a data analysis pipeline. In certain embodiments, the data analysis pipeline is the Taxa4Meta pipeline. In certain embodiments, data analysis pipelines are generated as a function of benchmarking results. In certain embodiments, a new computational pipeline “Taxa4Meta” can be used to analyze 16S amplicon data with an optimal range of variable sequence lengths. In some embodiments, such a pipeline implements several open-source programs, such as VSEARCH³¹for stringent clustering with a known identity range (e.g., 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, 100% identity; preferably 99% identity). In some embodiments, open-source programs such as VSEARCH can be optimized for 16S amplicon data with the selected variable lengths after quality trimming. In some embodiments, BLCA¹¹can be used with optimal region-specific confidence thresholds for stringent species annotation of OTUs. In certain embodiments, IDTAXA¹⁰can be utilized for annotating OTUs that cannot be annotated down to species resolution. In certain embodiments, collapsed taxonomic profiles from OTU tables are used for downstream analyses during 16S meta-analysis.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises benchmarking of taxonomic profiling accuracy comparing new data analysis pipelines (e.g., Taxa4Meta) with other standard 16S data analysis pipelines. In some embodiments, the feasibility and/or accuracy of different 16S pipelines are tested using the simulated and experimental datasets^12,21, and optionally the tests are designed to retain reads for accurate sequence clustering and for improved taxonomic accuracy. In some embodiments, simulated datasets are prepared from a suitable data base (e.g., NCBI 16S RefSeq as indicated above). In some embodiments, full-length amplicons of V1-V3, V3-V5, V4 and V6-V9 are simulated, and random sequence count ranging from 1 to 50 and random phred quality score (ASCII_BASE=33) ranging from 30 to 42 are generated for each full-length amplicon. In some embodiments, further length trimming is performed for one or more or each of the full-length amplicons, for example but not limited to, V1-V3 forward amplicons (200, 250, 300, 350, 400 and 450 bases), V1-V3 reverse amplicons (300, 350, 400 and 450 bases), V3-V5 forward amplicons (250, 300, 350, 400 and 450 bases), V3-V5 reverse amplicons (300, 350, 400 and 450 bases), both forward and reverse amplicons of V4 (200 and 250 bases), V6-V9 forward amplicons (300, 350, 400 and 450 bases), V6-V9 reverse amplicons (250, 300, 350, 400 and 450 bases). In some embodiments, trimmed amplicons from the same sequence orientation of the same 16S variable region are combined for benchmarking different 16S pipelines. In some embodiments, NCBI 16S taxonomic lineage of NCBI 16S RefSeq is used as the ground truth (reference annotations) for comparison. In some embodiments, a cohort (e.g., a Korean stool microbiome datasct¹²) with the same DNA extracts used for 454 V1-V4, Illumina V1-V3, Illumina V3-V4, Illumina V4, and Illumina shotgun metagenomic sequencing is used as the real human microbiome dataset for benchmarking different 16S pipelines. In some embodiments, primers retained in the sequence reads are removed by positional trimming. In some embodiments, Illumina paired-end reads are merged (e.g., using USEARCH (version 8.1.1831)) with certain parameters (e.g., default parameters) prior to benchmarking 16S pipelines. In certain embodiments, key 16S analysis pipelines can include DADA2-IDTAXA, DADA2-RDP, UCLUST-UCLUST, USEARCH-RDP, Taxa4Meta, Kraken2 and/or MetaPhlAn2. In some embodiments, key 16S analysis pipelines DADA2-IDTAXA, DADA2-RDP. UCLUST-UCLUST, USEARCH-RDP, Taxa4Meta, Kraken2 and/or MetaPhlAn2 are benchmarked with simulated amplicons and/or ground truth datasets (e.g., Korean human microbiome dataset).

In some embodiments, an analysis procedure for a DADA2-IDTAXA pipeline can be performed. In some embodiments, DADA2 (version 1.8) is used for denoising amplicon data after quality filtering with a maximum expected error (e.g., of 2) and a minimum base length (e.g., of 200 bases). In some embodiments, IDTAXA together with its pre-built RDP training set (version 16) is used for taxonomic annotation with the confidence threshold (e.g., of 70) using a number of bootstraps (e.g., 100 bootstraps). In some embodiments, IDTAXA based analysis can only go down to genus level. In some embodiments, an analysis procedure for DADA2-RDP pipeline can be performed. In some embodiments, DADA2 (version 1.8) is used for denoising amplicon data after quality filtering with a maximum expected error (e.g., of 2) and minimum base length (e.g., of 200 bases). In some embodiments, RDP Naive Bayesian Classifier algorithm implemented in DADA2's assignTaxonomy function together with its pre-formatted RDP training set (version 16) is used for taxonomic annotation using a minimum bootstrap confidence (e.g., a minimum bootstrap confidence of 50). In some embodiments, a DADA2-RDP analysis can go down to species level. In some embodiments, an analysis procedure for a UCLUST-UCLUST pipeline can be performed. In some embodiments. UCLUST (version 1.2.22q) is used for clustering amplicon data with known sequence similarity (e.g., of 97%) after quality filtering with the minimum quality threshold (e.g., of 20) and a minimum base length (e.g., of 140 bases). In some embodiments, representative sequence(s) of OTUs are selected (e.g., with pick_rep_set.py script) with default parameters. In some embodiments. UCLUST implemented in assign_taxonomy.py script together with SILVA database (release 123; choice of silva_132_97_16S.fna) is used for taxonomic annotation, which can be down to species level using a minimum bootstrap confidence (e.g., of 0.5). In some embodiments, one or more or all procedures are completed in the QIIME platform (version 1.9.1). In some embodiments, such a pipeline is similar to the meta-analysis method used by Mancabelli et al.²². In some embodiments, an analysis procedure for USEARCH-RDP pipeline can be performed. In some embodiments. USEARCH is used for clustering amplicon data with known sequence similarity (e.g., 100% sequence similarity) after quality filtering with a maximum expected error (e.g., of 2) and a minimum base length (e.g., of 200 bases). In some embodiments, RDP classifier (version 2.12) together with RDP training set (version 16) is used for taxonomic annotation, which can be down to species level using a minimum bootstrap confidence (e.g., of 0.5). In some embodiments, such a pipeline is similar to the meta-analysis method used by Duvallet et al.²⁰). In some embodiments, an analysis procedure for the Taxa4meta pipeline can be performed. In some embodiments. Taxa4Meta (e.g., version 1.22) is used for clustering amplicon data after quality filtering with a maximum expected error (e.g., of 2) and a selected range of variable lengths, optionally as suggested by Taxa4Meta itself. In some embodiments, taxonomic annotation by Taxa4Meta binary classifier can be down to species level. In some embodiments, an analysis procedure for Metagenomic classifiers can be performed. In some embodiments, Paired-end sequences are trimmed and filtered to meet a maximum expected error (e.g., of 2) with a minimum read length (e.g., of 50). In some embodiments, Kraken2 (version 2.0.8) with its pre-built database (minikraken2_v2_8 GB_201904_UPDATE) with default parameters is used for taxonomic profiling for shotgun metagenomic data. In some embodiments, MetaPhlAn2 (version 2.7.7) with it default database (mpa_v20_m200) with default parameters is used for taxonomic profiling for shotgun metagenomic data. In some embodiments, Kraken2 family-level abundance results are used as the reference for comparisons across different 16S pipelines. In some embodiments, given the high precision on species identification, MetaPhlAn2 species-level abundance results are used as the reference for evaluating species calls of different 16S pipelines. In some embodiments, a pseudo sample is created by averaging each family-level abundance of all WGS samples (e.g., 27 WGS samples), then the abundance-weighted Jaccard distance is calculated between the pseudo sample and any real sample analyzed by different pipelines.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises microbiome meta-analysis of diarrheal microbiome datasets. In some embodiments, one or more diarrheal datasets are run on the Taxa4Meta pipeline adopted optimal taxonomic thresholds for each 16S variable region. In some embodiments, Taxa4Meta command queries for diarrheal dataset are similar or the same as those indicated in Table 21. In some embodiments, relative abundance of collapsed species profiles generated from Taxa4Meta OTU count tables are used with or without rarefaction. In some embodiments, relative abundance of collapsed species profiles generated from Taxa4Meta OTU count tables require a minimum number of reads per sample. In some embodiments, a minimum number of reads per sample is 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1050, 1100, 1150, 1200, 1250, 1300, 1350, 1400, 1450, 1500 or more or any range derivable therein. In some embodiments, a minimum number of reads per sample is 1,000 reads per sample. In some embodiments, if species is assigned by Taxa4Meta-BLCA, the taxonomic lineage from NCBI 16S RefSeq is adopted for that species to avoid inconsistency in taxonomic lineage. In some embodiments, merging of Taxa4Meta collapsed species of is based on taxonomic lineages.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises determining predictive metagenome functions. In some embodiments, predictive metagenome functions can be determined using open source software, e.g., PICRUSt2 (see e.g., Holmes et al., Generative models for microbial metagenomics. PLOS One 7, (2012)). In some embodiments, default Taxa4Meta parameters, OTU count tables, and/or OTU sequences are used to infer metabolic pathway abundance profiles for one or more datasets. In some embodiments, merging of PICRUSt2 pathway profiles is based on MetaCyc pathway IDs. In some embodiments, either or both LEfSe analysis (one-against-one test mode; version 1.0) and random forest (RF)-based feature ranking (default parameters in Orange version 3.20) are performed using pathway abundance profiles for diseased (e.g., CDI, IBD CD, IBD UC, and/or IBS) and/or control subjects. In some embodiments, mean decrease accuracy (MDA) score from RF-based analysis is used to rank pathways. In some embodiments, the top 20 pathways must be listed by both RF-based feature ranking result and LEfSe analysis result. In some embodiments, the top 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, or 90 pathways are listed by both RF-based feature ranking results and LEFSe analysis results. In some embodiments, the top ranked pathways are selected for subsequent analysis. In some embodiments, the top ranked pathways are the top 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, or 90 pathways or any range derivable therein. In some embodiments, the top ranked pathways are features indicative of a disease state and/or suitable for binary classification of disease state (see e.g., Tables 1-8).

In some embodiments, data (e.g., relative abundances, associations, metabolic pathways, etc.) associated with a collection of one or more OTUs is collaposed into an enterotype. In some embodiments, an enterotype encompasses two or more OTUs. In some embodiments, an OTU may be collapsed into a simplified genera designation. In some embodiments, an OTU is not collapsed into a simplified genera designation.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises determining α-Diversity and/or β-diversity. In some embodiments, one or more α-diversity indices are calculated at OTU levels. In some embodiments, α-diversity indices are the Shannon index (e.g., alpha_diversity.py in QIIME v1.9.1) and/or the richness index (e.g., breakaway package version 4.7.5). In some embodiments, QIIME v1.9.1, principal coordinate analysis (PCoA) with abundance-weighted Jaccard distance metric is applied for β-diversity analysis using combined collapsed species profile. In some embodiments, ANOSIM test for group comparison is performed using the beta-diversity distance profile and the permutations of 999.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises fitting factors onto β-diversity ordination plot. In some embodiments, fitting factors (e.g., taxa) onto a two-dimensional ordination plot (e.g., first two coordinates) is performed using the envfit function in vegan package (version 2.5-7) or a suitable alternative program. In some embodiments, taxonomic abundance profile at family level is used as one of or the only factor in this analysis. In some embodiments, significance of fitted factors is established using the permutation of 999 in the envfit run.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises microbiome enterotyping. In some embodiments, microbiome enterotyping is performed with family abundance profiles of one or more or all meta-analysis training sets. In some embodiments, Dirichlet multinomial mixtures (DMM) algorithm, a classical method for clustering community profile data, is used for microbiome enterotyping.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises supervised classification and/or independent cohort validation. In some embodiments, supervised classification procedures are performed using Orange software³³(e.g., version 3.20) or a suitable alternative thereof, and applied to the reported cohorts with clinical definitions. In some embodiments, an original sample grouping information from each cohort is adopted. In some embodiments, such an adoption is done so the gold standard definition is clear for each sample. In some embodiments, random forest-based feature ranking was used as a first pass to select the top 100 input features (e.g., taxa, or biochemical pathways) for downstream supervised learning. In some embodiments, unless performing sub-sampling, input samples are used for training procedure. In some embodiments, supervised classification is performed using individual learning algorithms including but not limited to Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes (NB), and/or Neural Network (NN). In some embodiments, a Stack model as an aggregated meta-learner of RF, SVM and NB is assessed. In some embodiments, a 5-fold cross-validation method is applied for sub-sampling of training and test data during a training procedure. In some embodiments, receiver-operating-characteristic (ROC) analysis is performed using the training results. In some embodiments, values of area-under-the curve (AUC) and classification accuracy (CA) are calculated to evaluate the performance of each classification model. In some embodiments, a suitable AUC value is more than 0.80, 0.81, 0.82, 0.83, 0.84. 0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, or 0.99 or any range derivable therein. In some embodiments, a preferred AUC value is more than 0.95, 0.96, 0.97, 0.98, or 0.99 or any range derivable therein. In some embodiments, CA refers to the proportion of correct predicted samples from the classification model compared to the original clinical diagnosis. In some embodiments, a suitable CA value is more than 0.80, 0.81, 0.82, 0.83, 0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, or 0.99 or any range derivable therein. In some embodiments, a preferred CA value is more than 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, or 0.99 or any range derivable therein. In some embodiments, independent validation of classification models is performed using datasets of recently reported microbiome surveys of human diarrheal diseases that were not included in the training set. In some embodiments, one or more validation datasets are analyzed individually using the Taxa4Meta pipeline to generate taxonomic profile data for validating classification models. In some embodiments, CDI and IBD scores refer to the predicted scores of each sample as the class of CDI and IBD, respectively.

In some embodiments, a step in determining features suitable for classification of microbiome dysbiosis associated disease state and/or determination of appropriate treatment methods comprises statistical analysis. In some embodiments, comparisons between two groups are made using non-parametric Mann-Whitney-Wilcoxon two-tailed test or a suitable alternative thereof, and comparisons for more than two groups are made using non-parametric Kruskal-Wallis two-tailed test or a suitable alternative thereof. In some embodiments, multiple comparisons and pairwise Spearman or Pearson correlations are adjusted using the Benjamini-Hochberg (BH) false discovery rate (p<0.05, regarded as statistically significant), or a suitable alternative thereof.

In some embodiments, calculation of a meta-feature value is performed by: (i) determining the feature value of at least two, preferably more features, (ii) “normalizing” the feature value of each individual feature by dividing the value with a coefficient which is approximately the median value of the respective feature in a representative cohort, and (iii) calculating the median of the group of normalized gene expression values. In some embodiments, meta-feature analysis is performed as described herein.

As disclosed herein, in some embodiments, a feature shall be understood to be specifically increased in presence if the abundance level of the feature is at least about 2-fold, 4-fold, 6-fold, 8-fold, 10-fold, 15-fold, 20-fold, 30-fold, 40-fold, 50-fold, 60-fold, 70-fold, 80-fold, 90-fold, 100-fold, 1000-fold, or 10000-fold higher (or any range derivable therein) than in a reference, or in a mixture of references. References include but are not limited to, biological samples from one or more otherwise healthy individuals, biological samples from one or more individuals diagnosed with a different disease, and/or non-diarrheal biological samples from one or more individuals. In some embodiments, references can include normalized values across a cohort.

In certain algorithms a suitable threshold level is first determined for a feature. The suitable threshold level can be determined from measurements of feature presence, absence, and/or levels (e.g., quantity, activity, etc.) in one or more individuals from a test cohort. In some embodiments, median feature values in a multiple expression measurement is taken as a suitable threshold value. In some embodiments, mean feature values in a multiple expression measurement is taken as a suitable threshold value. In some embodiments, mode feature values in a multiple expression measurement is taken as a suitable threshold value. Comparison of multiple features with a threshold level can be performed as follows: 1) The individual features are compared to their respective threshold levels, 2) The number of features, the level of which is above and/or below their respective threshold level, is determined, 3) If a feature value is above its respective threshold level, then the feature level of is taken to be “above the threshold level”, 4) If a feature value is below its respective threshold level, then the feature level is taken to be “below the threshold level”.

In some embodiments, a disease classification may be determined from analysis of a sufficiently large number of features. In this context, a sufficiently large number of features means preferably 10%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 75%, 80%, 85%, 90%, 95%, 98%, 99%, or 100% of the features described by one or more binary tests disclosed herein (see e.g., Tables 2-17).

In certain aspects, the determination of feature presence, absence, and/or levels is on a substrate that allows evaluation of RNA molecule levels from a given sample, such as a gene chip, for example but not limited to Affymetrix™ gene chip, NanoString nCounter™, Illlumina BeadChip™, etc.,

In some embodiments, the determination of feature presence, absence, and/or levels is by 16S rRNA sequencing.

In some embodiments, the determination of feature presence, absence, and/or levels is by RNA sequencing.

In some embodiments, the determination of feature presence, absence, and/or levels is by whole genome sequencing, for example but not limited to, whole genome shotgun sequencing.

In other embodiments, the determination of feature presence, absence, and/or levels is done by polymerase chain reaction (PCR), for example but not limited to, real-time PCR, quantitative real time PCR, reverse transcriptase PCR, multiplexed PCR, nested PCR, long-range PCR, single-cell PCR, fast-cycling PCR, methylation-specific PCR, hot start PCR, high-fidelity PCR, in situ PCR, etc.

In some embodiments, the determination of feature presence, absence, and/or levels is performed by measuring proteins, polypeptides, metabolites, small molecules, etc. instead of nucleic based analyses (e.g., RNA and/or DNA based analyses). In some embodiments, techniques suitable for measuring the same include but are not limited to methods such as western blotting, IP-MS/MS, LC-MS/MS, NMR, PQN, ELISAs, HPLC, etc.

B. Nucleic Acid Based Assays

Screening methods based on differential levels of genes and/or gene products are common place in the art. In accordance with one aspect of the present invention, the differential patterns of features can be determined by measuring the levels of RNA transcripts indicative of these features, or genes whose expression is modulated by the presence or absence of one or more of these features, present in a patient's biological sample (e.g., a fecal sample, swab, irrigation, mucosal biopsy, etc.). Suitable methods for this purpose include, but are not limited to, DNA sequencing, RNA sequencing, RT-PCR, Northern Blot, in situ hybridization, Southern Blot, slot-blotting, nuclease protection assay, and oligonucleotide arrays.

In some embodiments, feature absence, presence, and/or levels are determined from a biological sample obtained from a fecal sample, intestinal biopsy, intestinal swab, mucosal biopsy, and/or intestinal irrigation. In certain embodiments, feature absence, presence, and/or levels are preferably determined from a biological sample obtained from a fecal sample. In some embodiments, a biological sample may be a fixated samples (e.g., those fixed using formalin, paraformaldehyde, paraffin, etc.), blood, tears, semen, saliva, urine, feces, tissue, breast milk, lymph fluid, stool, sputum, cerebrospinal fluid, and/or supernatant from cell lysate.

In certain aspects, RNA isolated from a biological sample can be amplified to cDNA or cRNA before detection and/or quantitation. In some embodiments, isolated RNA can be either total RNA or mRNA. In some embodiments, RNA amplification can be specific or non-specific. In some embodiments, suitable amplification methods include, but are not limited to, reverse transcriptase PCR, isothermal amplification, ligase chain reaction, and Qbeta replicase. In some embodiments, amplified nucleic acid products can be detected and/or quantitated through hybridization to labeled probes. In some embodiments, detection may involve fluorescence resonance energy transfer (FRET) or some other kind of quantum dots.

In some embodiments, amplification primers or hybridization probes for detection of presence, absence, and/or levels of a feature can be prepared from a gene sequence or obtained through commercial sources, such as Affymetrix, NanoString, Illumina BeadChip, etc. In certain embodiments a gene sequence is identical or complementary to at least 8, 10, 12, 14, 16, 18, or 20 contiguous nucleotides of a coding sequence.

In some embodiments, sequences suitable for making probes/primers for detection of a corresponding feature includes those that are identical or complementary to all or part of one or more genes specific to taxonomic units described herein. In some embodiments, sequences suitable for making probes/primers for detection of a corresponding feature includes those that are unique to one or more genes specific to taxonomic units described herein.

In some embodiments, use of a probe or primer of between 13 and 100 nucleotides, preferably between 17 and 100 nucleotides in length, or in some aspects of the invention up to 1-2 kilobases or more in length, allows the formation of a duplex molecule that is both stable and selective. Molecules having complementary sequences over contiguous stretches greater than 20 bases in length are generally preferred, to increase stability and/or selectivity of the hybrid molecules obtained. One will generally prefer to design nucleic acid molecules for hybridization having one or more complementary sequences of 20 to 30 nucleotides, or even longer where desired. Such fragments may be readily prepared, for example, by directly synthesizing the fragment by chemical means or by introducing selected sequences into recombinant vectors for recombinant production.

In some embodiments, each probe/primer comprises at least 15 nucleotides. For instance, each probe can comprise at least or at most 20, 25, 50, 75, 100, 125, 150, 175, 200, 225, 250, 275, 300, 325, 350, 400 or more nucleotides (or any range derivable therein). They may have these lengths and have a sequence that is identical or complementary to a gene or portion of a genome of a taxonomic unit described herein. Preferably, each probe/primer has relatively high sequence complexity and does not have any ambiguous residue (undetermined “n” residues). In some embodiments, probes/primers can hybridize to a target gene, including its RNA transcripts, under stringent or highly stringent conditions. In some embodiments, because each of the features has more gene sequences, it is contemplated that probes and primers may be designed for use with any one or more of these gene sequences. For example, inosine is a nucleotide frequently used in probes or primers to hybridize to more than one sequence. It is contemplated that probes or primers may have inosine or other design implementations that accommodate recognition of more than one sequence for a particular feature.

For applications requiring high selectivity, one will typically desire to employ relatively high stringency conditions to form the hybrids. For example, relatively low salt and/or high temperature conditions, such as provided by about 0.02 M to about 0.10 M NaCl at temperatures of about 50° C. to about 70° C. Such high stringency conditions tolerate little, if any, mismatch between the probe or primers and the template or target strand and would be particularly suitable for isolating specific genes or for detecting specific transcripts. It is generally appreciated that conditions can be rendered more stringent by the addition of increasing amounts of formamide.

In some embodiments, probes/primers for a gene are selected from regions which significantly diverge from the sequences of other genes. Such regions can be determined by checking the probe/primer sequences against relevant genome sequence databases. One algorithm suitable for this purpose is the BLAST algorithm. This algorithm involves first identifying high scoring sequence pairs (HSPs) by identifying short words of length (W) in the query sequence, which either match or satisfy some positive-valued threshold score (T) when aligned with a word of the same length in a database sequence. T is referred to as the neighborhood word score threshold. These initial neighborhood word hits act as seeds for initiating searches to find longer HSPs containing them. The word hits are then extended in both directions along each sequence to increase the cumulative alignment score. Cumulative scores are calculated using, for nucleotide sequences, the parameters M (reward score for a pair of matching residues; always >0) and N (penalty score for mismatching residues; always <0). The BLAST algorithm parameters W. T. and X determine the sensitivity and speed of the alignment. These parameters can be adjusted for different purposes, as appreciated by one of ordinary skill in the art.

In some embodiments, quantitative RT-PCR (such as TaqMan, ABI) is used for detecting and comparing the levels of RNA transcripts in biological samples. Quantitative RT-PCR involves reverse transcription (RT) of RNA to cDNA followed by relative quantitative PCR (RT-PCR). The concentration of the target DNA in the linear portion of the PCR process is proportional to the starting concentration of the target before the PCR was begun. By determining the concentration of the PCR products of the target DNA in PCR reactions that have completed the same number of cycles and are in their linear ranges, it is possible to determine the relative concentrations of the specific target sequence in the original DNA mixture. If the DNA mixtures are cDNAs synthesized from RNAs isolated from different tissues or cells, the relative abundances of the specific transcripts from which the target sequence was derived may be determined for the respective cells. This direct proportionality between the concentration of the PCR products and the relative transcript abundances is true in the linear range portion of the PCR reaction. The final concentration of the target DNA in the plateau portion of the curve is determined by the availability of reagents in the reaction mix and is independent of the original concentration of target DNA. Therefore, the sampling and quantifying of the amplified PCR products preferably are carried out when the PCR reactions are in the linear portion of their curves. In addition, relative concentrations of the amplifiable cDNAs preferably are normalized to some independent standard, which may be based on either internally existing RNA species or externally introduced RNA species. The abundance of a particular transcript or DNA species may also be determined relative to the average abundance of all transcript or DNA species in the sample.

In some embodiments, PCR amplification utilizes one or more internal PCR standards. The internal standard may be an abundant housekeeping gene in a cell. These standards may be used to normalize expression and/or abundance levels so that the expression and/or abundance levels of different features can be compared directly. A person of ordinary skill in the art would know how to use an internal standard to normalize expression and/or abundance levels.

A problem inherent in clinical samples is that they are generally of variable quantity and/or quality. In some embodiments, this problem can be overcome if the RT-PCR is performed as a relative quantitative RT-PCR with an internal standard in which the internal standard is an amplifiable nucleic acid fragment that is similar or larger than the target nucleic acid fragment and in which the abundance of the nucleic acid fragment encoding the internal standard is roughly 5-100 fold higher than the nucleic acid fragment encoding the target. This assay measures relative abundance, not absolute abundance of the respective nucleic acid species.

In another embodiment, the relative quantitative RT-PCR uses an external standard protocol. Under this protocol, the PCR products are sampled in the linear portion of their amplification curves. The number of PCR cycles that are optimal for sampling can be empirically determined for each target nucleic acid fragment.

Nucleic acid arrays can also be used to detect and compare the differential presence, absence, or levels of microbiome dysbiosis features. Probes suitable for detecting the corresponding features can be stably attached to known discrete regions on a solid substrate. As used herein, a probe is “stably attached” to a discrete region if the probe maintains its position relative to the discrete region during the hybridization and the subsequent washes. Construction of nucleic acid arrays is well known in the art. Suitable substrates for making polynucleotide arrays include, but are not limited to, membranes, films, plastics and quartz wafers.

A nucleic acid array can comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 150, 200, 250 or more different polynucleotide probes, which may hybridize to different and/or the same targets representative of one or more features. Multiple probes for the same feature can be used on a single nucleic acid array. Probes for other features can also be included in the nucleic acid array. Probe combinations suitable for delincation of healthy, CDI, IBS, IBD UC, and/or IBD CD can be included on a nucleic acid array. The probe density on the array can be in any range. In some embodiments, the density may be 50, 100, 200, 300, 400, 500 or more probes/cm2.

Specifically contemplated by the present inventors are chip-based nucleic acid technologies such as those described by Hacia et al. (1996) and Shoemaker et al. (1996). Briefly, these techniques involve quantitative methods for analyzing large numbers of genes rapidly and accurately. By tagging genes with oligonucleotides or using fixed probe arrays, one can employ chip technology to segregate target molecules as high density arrays and screen these molecules on the basis of hybridization (see also, Pease et al., 1994; and Fodor et al, 1991). It is contemplated that this technology may be used in conjunction with evaluating the presence, absence, and/or levels of one or more features with respect to diagnostic, prognostic, and treatment methods of the disclosure.

The present disclosure may involve the use of arrays or data generated from an array. Data may be readily available. Moreover, an array may be prepared in order to generate data that may then be used in correlation studies.

An array generally refers to ordered macroarrays or microarrays of nucleic acid molecules (probes) that are fully or nearly complementary or identical to a plurality genes and/or gene products and that are positioned on a support material in a spatially separated organization. Macroarrays are typically sheets of nitrocellulose or nylon upon which probes have been spotted. Microarrays position the nucleic acid probes more densely such that up to 10,000 nucleic acid molecules can be fit into a region typically 1 to 4 square centimeters. Microarrays can be fabricated by spotting nucleic acid molecules, e.g., genes, oligonucleotides, etc., onto substrates or fabricating oligonucleotide sequences in situ on a substrate. Spotted or fabricated nucleic acid molecules can be applied in a high density matrix pattern of up to about 30 non-identical nucleic acid molecules per square centimeter or higher, e.g. up to about 100 or even 1000 per square centimeter. Microarrays typically use coated glass as the solid support, in contrast to the nitrocellulose-based material of filter arrays. By having an ordered array of complementing nucleic acid samples, the position of each sample can be tracked and linked to the original sample. A variety of different array devices in which a plurality of distinct nucleic acid probes are stably associated with the surface of a solid support are known to those of skill in the art. Useful substrates for arrays include nylon, glass and silicon. Such arrays may vary in a number of different ways, including average probe length, sequence or types of probes, nature of bond between the probe and the array surface, e.g. covalent or non-covalent, and the like. The labeling and screening methods of the present invention and the arrays are not limited in its utility with respect to any parameter except that the probes detect absence, presence, or levels of one or more features; consequently, methods and compositions may be used with a variety of different types of genes and/or gene products.

Representative methods and apparatus for preparing a microarray have been described, for example, in U.S. Pat. Nos. 5,143,854; 5,202,231; 5,242,974; 5,288,644; 5,324,633; 5,384,261; 5,405,783; 5,412,087; 5,424,186; 5,429,807; 5,432,049; 5,436,327; 5,445,934; 5,468,613; 5,470,710; 5,472,672; 5,492,806; 5,525,464; 5,503,980; 5,510,270; 5,525,464; 5,527,681; 5,529,756; 5,532,128; 5,545,531; 5,547,839; 5,554,501; 5,556,752; 5,561,071; 5,571,639; 5,580,726; 5,580,732; 5,593,839; 5,599,695; 5,599,672; 5,610,287; 5,624,711; 5,631,134; 5,639,603; 5,654,413; 5,658,734; 5,661,028; 5,665,547; 5,667,972; 5,695,940; 5,700,637; 5,744,305; 5,800,992; 5,807,522; 5,830,645; 5,837,196; 5,871,928; 5,847,219; 5,876,932; 5,919,626; 6,004,755; 6,087,102; 6,368,799; 6,383,749; 6,617,112; 6,638,717; 6,720,138, as well as WO 93/17126; WO 95/11995; WO 95/21265; WO 95/21944; WO 95/35505; WO 96/31622; WO 97/10365; WO 97/27317; WO 99/35505; WO 09923256; WO 09936760; WO 0138580; WO 0168255; WO 03020898; WO 03040410; WO 03053586; WO 03087297; WO 03091426; WO 03100012; WO 04020085; WO 04027093; EP 373 203; EP 785 280; EP 799 897 and UK 8 803 000; the disclosures of which are all herein incorporated by reference.

It is contemplated that the arrays can be high density arrays, such that they contain 100 or more different probes. It is contemplated that they may contain 1000, 16,000, 65,000, 250,000 or 1,000,000 or more different probes. The probes can be directed to targets in one or more different organisms. The oligonucleotide probes range from 5 to 50, 5 to 45, 10 to 40, or 15 to 40 nucleotides in length in some embodiments. In certain embodiments, the oligonucleotide probes are 20 to 25 nucleotides in length.

The location and sequence of each different probe sequence in the array are generally known. Moreover, the large number of different probes can occupy a relatively small area providing a high density array having a probe density of generally greater than about 60, 100, 600, 1000, 5,000, 10,000, 40,000, 100,000, or 400,000 different oligonucleotide probes per cm2. The surface area of the array can be about or less than about 1, 1.6, 2, 3, 4, 5, 6, 7, 8, 9, or 10 cm2.

Moreover, a person of ordinary skill in the art could readily analyze data generated using an array. Such protocols include information found in WO 9743450; WO 03023058; WO 03022421; WO 03029485; WO 03067217; WO 03066906; WO 03076928; WO 03093810; WO 03100448, all of which are specifically incorporated by reference.

In some embodiments, nuclease protection assays are used to quantify RNAs derived from a biological sample. There are many different versions of nuclease protection assays known to those practiced in the art. The common characteristic that these nuclease protection assays have is that they involve hybridization of an antisense nucleic acid with the RNA to be quantified. The resulting hybrid double-stranded molecule is then digested with a nuclease that digests single-stranded nucleic acids more efficiently than double-stranded molecules. The amount of antisense nucleic acid that survives digestion is a measure of the amount of the target RNA species to be quantified. An example of a nuclease protection assay that is commercially available is the RNase protection assay manufactured by Ambion, Inc. (Austin, Tex.).

In some embodiments, the presence, absence, and/or levels of one or more features are determined from a biological sample using 3′ RNA sequencing, using products such as Lexogen QuantSeq, QioSeq UPX 3′ Transcriptome, etc. In some embodiments, 3′ RNA sequencing does not require transcripts to be fragmented before reverse transcription, and cDNAs are reverse transcribed only from the 3′ RNA sequencing end of the transcripts, resulting in only one copy of cDNA for each transcript, resulting in a direct 1:1 ratio between RNA and cDNA copy numbers.

In some embodiments, gene expression is determined from a biological sample using specific targeted sequencing, using products such as BioSpyder Temp0-Seq. Ion Ampliseq Transcriptome, etc. In some embodiments, specific targeted sequencing targets RNA sequences by hybridization to DNA oligos followed by removal of unhybridized oligos and amplification of remaining products.

C. Proteins, Polypeptide, Metabolites, Etc. Based Assays

In other embodiments, the differential features (e.g., taxonomic and/or metabolic pathway biomarkers) can be determined by measuring levels of polypeptides encoded by components of the microbiome in a biological sample (e.g., a fecal sample, intestinal swap, intestinal biopsy, intestinal irrigation sample, etc.). Methods suitable for this purpose include, but are not limited to, immunoassays such as ELISA, RIA, FACS, dot blot, Western Blot, immunohistochemistry, and antibody-based radioimaging. Protocols for carrying out these immunoassays are well known in the art. Other methods such as 2-dimensional SDS-polyacrylamide gel electrophoresis can also be used. These procedures may be used to recognize any of the polypeptides encoded or implicated by one or more features described herein.

One example of a method suitable for detecting the levels of target proteins in biological samples is ELISA. In an exemplifying ELISA, antibodies capable of binding to the target proteins encoded by the genome of one or more features are immobilized onto a selected surface exhibiting protein affinity, such as wells in a polystyrene or polyvinylchloride microtiter plate. Then, samples to be tested are added to the wells. After binding and washing to remove non-specifically bound immunocomplexes, the bound antigen(s) can be detected. Detection can be achieved by the addition of a second antibody which is specific for the target proteins and is linked to a detectable label. Detection may also be achieved by the addition of a second antibody, followed by the addition of a third antibody that has binding affinity for the second antibody, with the third antibody being linked to a detectable label. Proper extraction procedures can be used to separate the target proteins from potentially interfering substances.

In another ELISA embodiment, one or more samples containing the target proteins reflective of one or more features are immobilized onto the well surface and then contacted with antibodies. After binding and washing to remove non-specifically bound immunocomplexes, the bound antigen is detected. Where the initial antibodies are linked to a detectable label, the immunocomplexes can be detected directly. The immunocomplexes can also be detected using a second antibody that has binding affinity for the first antibody, with the second antibody being linked to a detectable label.

Another typical ELISA involves the use of antibody competition in the detection. In this ELISA, the target proteins are immobilized on the well surface. The labeled antibodies are added to the well, allowed to bind to the target proteins, and detected by means of their labels. The amount of the target proteins in an unknown sample is then determined by mixing the sample with the labeled antibodies before or during incubation with coated wells. The presence of the target proteins in the unknown sample acts to reduce the amount of antibody available for binding to the well and thus reduces the ultimate signal.

Different ELISA formats can have certain features in common, such as coating, incubating or binding, washing to remove non-specifically bound species, and detecting the bound immunocomplexes. For instance, in coating a plate with either antigen or antibody, the wells of the plate can be incubated with a solution of the antigen or antibody, either overnight or for a specified period of hours. The wells of the plate are then washed to remove incompletely adsorbed material. Any remaining available surfaces of the wells are then “coated” with a non-specific protein that is antigenically neutral with regard to the test samples. Non-limiting examples of these nonspecific proteins include bovine serum albumin (BSA), casein and solutions of milk powder. The coating allows for blocking of nonspecific adsorption sites on the immobilizing surface and thus reduces the background caused by nonspecific binding of antisera onto the surface.

In ELISAs, a secondary or tertiary detection means can also be used. After binding of a protein or antibody to the well, coating with a non-reactive material to reduce background, and washing to remove unbound material, the immobilizing surface is contacted with the control and/or clinical or biological sample to be tested under conditions effective to allow immunocomplex (antigen/antibody) formation. These conditions may include, for example, diluting the antigens and antibodies with solutions such as BSA, bovine gamma globulin (BGG) and phosphate buffered saline (PBS)/Tween and incubating the antibodies and antigens at room temperature for about 1 to 4 hours or at 4° C. overnight. Detection of the immunocomplex then requires a labeled secondary binding ligand or antibody, or a secondary binding ligand or antibody in conjunction with a labeled tertiary antibody or third binding ligand.

After all of the incubation steps in an ELISA, the contacted surface can be washed so as to remove non-complexed material. For instance, the surface may be washed with a solution such as PBS/Tween, or borate buffer. Following the formation of specific immunocomplexes between the test sample and the originally bound material, and subsequent washing, the occurrence of the amount of immunocomplexes can be determined.

To provide a detecting means, the second or third antibody can have an associated label to allow detection. In some embodiments, a label is an enzyme that generates color development upon incubating with an appropriate chromogenic substrate. Thus, for example, one may contact and incubate the first or second immunocomplex with a urease, glucose oxidase, alkaline phosphatase or hydrogen peroxidase-conjugated antibody for a period of time and under conditions that favor the development of further immunocomplex formation (e.g., incubation for 2 hours at room temperature in a PBS-containing solution such as PBS-Tween).

After incubation with a labeled antibody, and subsequent to washing to remove unbound material, the amount of label is quantified, e.g., by incubation with a chromogenic substrate such as urea and bromocresol purple or 2,2′-azido-di-(3-ethyl)-benzhiazoline-6-sulfonic acid (ABTS) and hydrogen peroxide, in the case of peroxidase as the enzyme label. Quantitation can be achieved by measuring the degree of color generation, e.g., using a spectrophotometer.

In some embodiments, another suitable method is RIA (radioimmunoassay). An example of RIA is based on the competition between radiolabeled-polypeptides and unlabeled polypeptides for binding to a limited quantity of antibodies. Suitable radiolabels include, but are not limited to, I125. In some embodiments, a fixed concentration of I125-labeled polypeptide is incubated with a series of dilution of an antibody specific to the polypeptide. When the unlabeled polypeptide is added to the system, the amount of the I125-polypeptide that binds to the antibody is decreased. A standard curve can therefore be constructed to represent the amount of antibody-bound I125-polypeptide as a function of the concentration of the unlabeled polypeptide. From this standard curve, the concentration of the polypeptide in unknown samples can be determined. Various protocols for conducting RIA to measure the levels of polypeptides in a sample are well known in the art.

In some embodiments, suitable antibodies for biomarker detection include, but are not limited to, polyclonal antibodies, monoclonal antibodies, chimeric antibodies, humanized antibodies, single chain antibodies, Fab fragments, and fragments produced by a Fab expression library.

In some embodiments, antibodies can be labeled with one or more detectable moieties to allow for detection of antibody-antigen complexes. In some embodiments, detectable moieties can include compositions detectable by spectroscopic, enzymatic, photochemical, biochemical, bioelectronic, immunochemical, electrical, optical or chemical means. In some embodiments, detectable moieties include, but are not limited to, radioisotopes, chemiluminescent compounds, labeled binding proteins, heavy metal atoms, spectroscopic markers such as fluorescent markers and dyes, magnetic labels, linked enzymes, mass spectrometry tags, spin labels, electron transfer donors and acceptors, and the like.

Protein array technology is discussed in detail in Pandey and Mann (2000) and MacBeath and Schreiber (2000), each of which is herein specifically incorporated by reference. These arrays typically contain thousands of different proteins or antibodies spotted onto glass slides or immobilized in tiny wells and allow one to examine the biochemical activities and binding profiles of a large number of proteins at once. To examine protein interactions with such an array, a labeled protein is incubated with each of the target proteins immobilized on the slide, and then one determines which of the many proteins the labeled molecule binds. In certain embodiments such technology can be used to quantitate a number of proteins in a sample, such as a sample comprising a representative population of a microbiome.

The basic construction of protein chips has some similarities to DNA chips, such as the use of a glass or plastic surface dotted with an array of molecules. These molecules can be DNA or antibodies that are designed to capture proteins. Defined quantities of proteins are immobilized on each spot, while retaining some activity of the protein. With fluorescent markers or other methods of detection revealing the spots that have captured these proteins, protein microarrays are being used as powerful tools in high-throughput proteomics and drug discovery.

The earliest and best-known protein chip is the ProteinChip by Ciphergen Biosystems Inc. (Fremont, Calif.). The ProteinChip is based on the surface-enhanced laser desorption and ionization (SELDI) process. Known proteins are analyzed using functional assays that are on the chip. For example, chip surfaces can contain enzymes, receptor proteins, or antibodies that enable researchers to conduct protein-protein interaction studies, ligand binding studies, or immunoassays. With state-of-the-art ion optic and laser optic technologies, the ProteinChip system detects proteins ranging from small peptides of less than 1000 Da up to proteins of 300 kDa and calculates the mass based on time-of-flight (TOF).

The ProteinChip biomarker system is the first protein biochip-based system that enables biomarker pattern recognition analysis to be done. This system allows researchers to address important clinical questions by investigating the proteome from a range of crude clinical samples (i.e., laser capture microdissected cells, biopsies, tissue, urine, and serum). The system also utilizes biomarker pattern software that automates pattern recognition-based statistical analysis methods to correlate protein expression patterns from clinical samples with disease phenotypes.

In some embodiments, the levels of polypeptides in a biological sample can be determined by detecting the biological activities associated with the polypeptides. If a biological function/activity of a polypeptide is known, suitable in vitro bioassays can be designed to evaluate the biological function/activity, thereby determining the amount of the polypeptide in the sample.

In some embodiments, the levels of polypeptides and/or metabolites in a biological sample can be determined by IP-MS/MS and/or HPLC.

D. Methods of Delineation Between Disease Classification States.

In certain embodiments, one or more features identified herein can be used to delineate between disease classification states, and/or to provide stake holders with a basis for prescribing one or more appropriate methods of treatment.

In certain embodiments, one or more features are the presence, absence, and/or level of one or more a metabolic pathways. In certain embodiments, one or more features associated with a metabolic pathway are described in any one of tables 1-8, and 18.

In certain embodiments, one or more features are the presence, absence, and/or level of one or more taxonomic unit. In certain embodiments, one or more features associated a taxonomic unit are described in any one of tables 9-17, and 19.

In certain embodiments, one or more features are the presence, absence, and/or level of one or more taxonomic units represented by: Bacteroides; Eubacterium rectale; Ruminococcus; Faecalibacterium; Enterococcus; Enterobacteriaceae; Roseburia; Coprococcus; Dorea; Lachnoclostridium; Clostridium XIVa; Erysipelatoclostridium; Alistipes; Fusicatenibacter; Odoribacter; Lactobacillus; Anaerostipes; Collinsella; Clostridioides; Klebsiella; Agathobaculum butyriciproducens; Veillonella; Phascolarctobacterium; Adlercreutzia; Clostridium; Eggerthella; Sutterellaceae Parasutterella; barnesiella; Eubacterium; Clostridium IV; Gemmiger; Streptococcus; Dialister; Escherichia; Colidextribacter; Oxalobacter; Prevotella; Clostridium XVIII; Actinomyces; and Fusobacterium.

In certain embodiments, one or more features associated with the presence, absence, and/or level of one or more a metabolic pathways is used in conjunction with one or more features associated with the presence, absence, and/or level of one or more taxonomic units. In certain embodiments, one or more features associated with a feature are described in any one of tables 1-19.

In certain embodiments, a disease classification can be determined by the presence, absence, or relative level of at least one of AST-PWY (L-arginine degradation II (AST pathway)), ECASYN-PWY (enterobacterial common antigen biosynthesis), THREOCAT-PWY (superpathway of L-threonine metabolism), PPGPPMET-PWY (ppGpp biosynthesis), PWY0-1338 (polymyxin resistance), PWY-6263 (superpathway of menaquinol-8 biosynthesis II), PWY-7371 (1,4-dihydroxy-6-naphthoate biosynthesis II), PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I), P221-PWY (octane oxidation), PWY-6749 (CMP-legionaminate biosynthesis I), PWY-7456 (mannan degradation), NONMEVIPP-PWY (methylerythritol phosphate pathway I), PWY-5097 (L-lysine biosynthesis VI), PWY-5505 (L-glutamate and L-glutamine biosynthesis), PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II), PWY-7663 (gondoate biosynthesis (anaerobic)), THRESYN-PWY (superpathway of L-threonine biosynthesis), HEMESYN2-PWY (heme biosynthesis II (anaerobic)), PWY-5304 (superpathway of sulfur oxidation (archaca), PWY-6478 (GDP-D-glycero-alpha-D-manno-heptose biosynthesis), PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV), and/or PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP).

In certain embodiments, an increased abundance relative to an appropriate control of at least one of or all of AST-PWY (L-arginine degradation II (AST pathway)), ECASYN-PWY (enterobacterial common antigen biosynthesis), THREOCAT-PWY (superpathway of L-threonine metabolism), PPGPPMET-PWY (ppGpp biosynthesis), and/or PWY0-1338 (polymyxin resistance) is associated with CDI causative diarrhea. In certain embodiments, following detection of one or more of the indicative features, an individual is then treated accordingly.

In certain embodiments, an increased abundance relative to an appropriate control of at least one of or all of PWY-6263 (superpathway of menaquinol-8 biosynthesis II), PWY-7371 (1,4-dihydroxy-6-naphthoate biosynthesis II), PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I), P221-PWY (octane oxidation), PWY-6749 (CMP-legionaminate biosynthesis I), and/or PWY-7456 (mannan degradation) is associated with IBD UC causative diarrhea. In certain embodiments, following detection of one or more of the indicative features, an individual is then treated accordingly.

In certain embodiments, an increased abundance relative to an appropriate control of at least one of or all of NONMEVIPP-PWY (methylerythritol phosphate pathway I), PWY-5097 (L-lysine biosynthesis VI), PWY-5505 (L-glutamate and L-glutamine biosynthesis), PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II), PWY-7663 (gondoate biosynthesis (anaerobic)), THRESYN-PWY (superpathway of L-threonine biosynthesis), HEMESYN2-PWY (heme biosynthesis II (anaerobic)), PWY-5304 (superpathway of sulfur oxidation (archaca), PWY-6478 (GDP-D-glycero-alpha-D-manno-heptose biosynthesis), PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV), and/or PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP) is associated with IBD causative. In certain embodiments, following detection of one or more of the indicative features, an individual is then treated accordingly.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Acidaminococcaceae Acidaminococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Acidaminococcaceae Phascolarctobacterium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Actinobacteria Actinobacteria, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Actinomycetaceae Actinomyces, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Actinomycetaceae Schaalia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Actinomycetales Actinomycetaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Adlercreutzia equolifaciens, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Agathobaculum butyriciproducens, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Alistipes ihumii, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Alistipes obesi, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Alistipes shahii, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Anderostipes hadrus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Atopobiaceae Atopobium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacillales Gemella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacillales Incertae Sedis Gemella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacilli Lactobacillus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteria Proteobacteria, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroidales Rikenellaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides cellulosilyticus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides coprocola, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides eggerthii, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides koreensis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides nordii, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides plebeius, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides thetaiotaomicron, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroides xylanisolvens, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bacteroidia Bacteroidales, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Betaproteobacteria, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bifidobacteriales Bifidobacteriaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bifidobacterium adolescentis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Bifidobacterium boum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Blautia [Ruminococcus] gnavus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Blautia caecimuris, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Blautia hominis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Blautia obeum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Blautia product, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Blautia stercoris, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Burkholderia ambifaria, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Burkholderia thailandensis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Burkholderiaceae Burkholderia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Burkholderiales Burkholderiaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Burkholderiales Comamonadaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Carnobacteriaceae Granulicatella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Caulobacter segnis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Caulobacteraceae Caulobacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Caulobacterales Caulobacteraceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Chloroplast Streptophyta, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridiaceae Clostridium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridiaceae Hungatella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridiaceae Lactonifactor, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridiales Clostridiaceae 1, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridiales Incertae Sedis XI Parvimonas, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridiales Monoglobus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridioides difficile, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridium paraputrificum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridium sensu stricto, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridium XIVa cluster, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridium XI cluster, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Clostridium XVIII cluster, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Colidextribacter massiliensis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Collinsella aerofaciens, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Coprococcus catus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Coprococcus comes, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Coprococcus eutactus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Coriobacteriaceae Atopobium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Coriobacteriaceae Collinsella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Coriobacteriaceae Eggerthella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Coriobacteriales Coriobacteriaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Corynebacteriaceae Corynebacterium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Dorea formicigenerans, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Dorea longicatena, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Drancourtella massiliensis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Eggerthella lenta, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Eggerthellaceae Eggerthella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterobacterales Enterobacteriaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterobacteriaceae Cedecea, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterobacteriaceae Citrobacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterobacteriaceae Escherichia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterobacteriaceae Shimwellia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterobacteriales Enterobacteriaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterococcaceae Enterococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Enterococcus saccharolyticus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelatoclostridium [Clostridium] innocuum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelatoclostridium ramosum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelotrichaceae Erysipelatoclostridium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelotrichaceae Faecalicoccus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelotrichaceae Holdemania, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelotrichaceae Longicatena, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelotrichaceae Turicibacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Erysipelotrichales Erysipelotrichaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Eubacterium [Eubacterium] eligens, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Eubacterium siraeum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Eubacterium ventriosum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Faecalibacterium prausnitzii, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Faecalimonas umbilicata, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Firmicutes Bacilli, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Firmicutes Clostridia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Fusobacteriaceae Fusobacterium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Fusobacterium nucleatum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Gammaproteobacteria Enterobacterales, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Gemmiger, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Hungatella effluvia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Klebsiella quasipneumoniae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnoclostridium [Clostridium] boltede, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae [Eubacterium] rectale, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Anaerobutyricum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Anaerostipes, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Blautia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Clostridium XIVa, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Coprococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Dorea, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Eisenbergiella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Eubacterium rectale group, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Faecalimonas, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Fusicatenibacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Hungatella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Lachnoclostridium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Roseburia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lachnospiraceae Sellimonas, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lactobacilluseae Lactobacillus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lactobacillus Enterococcaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lactobacillus Streptococcaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Lactobacillus rogosde, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Leuconostocaceae Weissella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Megasphaera micronuciformis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Methanobacteriaceae Methanobrevibacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Methanobrevibacter smithii, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Methylophilaceae Methylophilus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Micrococcaceae Rothia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Oxalobacter formigenes, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Pasteurellaceae Rodentibacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Pasteurellales Pasteurellaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Pectobacterium carotovorum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Pelomonas aquatic, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Pelomonas aquatica, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptoniphilaceae Anaerococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptoniphilaceae Finegoldia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptoniphilaceae Peptoniphilus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptostreptococcaceae Clostridioides, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptostreptococcaceae Clostridium XI, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptostreptococcaceae Intestinibacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptostreptococcaceae Peptostreptococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptostreptococcaceae Romboutsia, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Peptostreptococcaceae Terrisporobacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Phascolarctobacterium faecium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Phyllobacteriaceae Phyllobacterium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Porphyromonadaceae Barnesiella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Porphyromonadacede Odoribacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Porphyromonadacede Parabacteroides, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Prevotella copri, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Prevotellaceae Prevotella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Prevotellamassilia timonensis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Proteobacteria Gammaproteobacteria, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Rikenellaceae Alistipes, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Romboutsia timonensis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Roseburia fuecis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Roseburia intestinalis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Roseburia inulinivorans, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Rosenbergiella collisarenosi, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Rosenbergiella nectarea, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Anaeromassilibacillus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Clostridium IV cluster, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Clostridium leptum group, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Intestinimonas, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Oscillibacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Pseudoflavonifractor, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Ruminococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcaceae Subdoligranulum, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcus bromii, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruminococcus callidus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Ruthenibacterium lactatiformans, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Saccharibacteria Incertae Sedis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Salmonella enterica, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Solobacterium moorei, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Sphingobacteriaceae Pedobacter, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Sphingomonadaceae, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Sphingomonas, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Staphylococcaceae Staphylococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Streptococcaceae Streptococcus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Streptococcus thermophilus, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Sutterellaceae Parasutterella, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Turicibacter sanguinis, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Veillonella dispar, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Veillonella infantium, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Veillonella parvula, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Veillonellaceae Dialister, or a metabolic pathway associated therewith.

In certain embodiments, methods described herein for classification of a disease state may comprise, or expressly does not comprise, detection and/or quantification of Veillonellaceae Veillonella, or a metabolic pathway associated therewith.

In certain embodiments, a binary delineation between disease classification of IBD and IBS comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 metabolic pathway features identified in Table 2.

In certain embodiments, a binary delineation between disease classification of IBD and CDI comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 metabolic pathway features identified in Table 3.

In certain embodiments, a binary delineation between disease classification of IBD (UC) and healthy comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 metabolic pathway features identified in Table 4.

In certain embodiments, a binary delineation between disease classification of IBD (CD) and healthy comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 metabolic pathway features identified in Table 5.

In certain embodiments, a binary delineation between disease classification of IBD (CD) and IBD (UC) comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 metabolic pathway features identified in Table 6.

In certain embodiments, a binary delineation between disease classification of IBS and CDI comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 metabolic pathway features identified in Table 7.

In certain embodiments, a binary delineation between disease classification of IBS and healthy comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 metabolic pathway features identified in Table 8.

In certain embodiments, a series of binary delineations are made to determine a final disease classification. For example but not limited to, delineation according to Table 3, followed by delineation according to Table 2, etc.

In certain embodiments, a binary delineation between disease classification of IBS and IBD comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 taxanomic features identified in Table 11.

In certain embodiments, a binary delineation between disease classification of IBD UC and healthy comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 taxanomic features identified in Table 13.

In certain embodiments, a binary delineation between disease classification of IBD CD and healthy comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 taxanomic features identified in Table 14.

In certain embodiments, a binary delineation between disease classification of IBD CD and IBD UC comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 taxanomic features identified in Table 15.

In certain embodiments, a binary delineation between disease classification of pediatric CDI and pediatric healthy comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 taxanomic features identified in Table 16.

In certain embodiments, a binary delineation between disease classification of pediatric CDI and adult CDI comprises, consists of, or consists essentially of measuring the presence, absence, and/or relative quantity of at least or exactly 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 taxanomic features identified in Table 17.

In certain aspects, methods disclosed herein can relate to a system for performing such methods, the system comprising (a) apparatus or device for storing data regarding feature levels of one or more microbiome components; (b) apparatus or device for determining feature levels of at least one feature; (c) apparatus or device for comparing feature levels of a first feature with a predetermined first threshold value and/or test value; (d) apparatus or device for determining feature level of at least one second or more features; and (c) computing apparatus or device programmed to provide treatment with an appropriate methodology if the data indicates altered feature levels or activity of said first feature as compared to the predetermined first threshold value and/or test value, and, alternatively or in concert, expression level and/or activity of said second or more features as compared to the predetermined second or more feature threshold level and/or test value.

A person skilled in the art readily appreciates that an accurate prognosis can be given or determined if a sufficiently large number of feature levels are analyzed and compared to an appropriate control. In some embodiments, accurate prognosis can facilitate determination of disease recurrence and/or appropriate therapies to provide, including a particular therapy of any kind, such as an antibiotic therapy.

In some embodiments, feature levels and/or patterns can also be compared by using one or more ratios between feature abundance levels associated with an otherwise healthy microbiome and/or one or more dysbiosed microbiomes. Other suitable measures or indicators can also be employed for assessing the relationship or difference between different feature patterns.

In some embodiments, one or more of the features can be used to determine whether a patient with a diarrheal disorder should be treated with antimicrobials and/or antibiotics. In certain embodiments, a pattern of features in a patient fecal sample and/or other microbiome samples may be used to evaluate a patient to determine whether they are likely to respond to one or more therapeutic interventions. In some embodiments, likeliness of a therapeutic response for the patient may be considered with respect to an individual that lacks the particular feature pattern of the patient.

In some embodiments, a subject's (e.g., a patient's) feature levels can be compared to reference feature levels using various methods. In some embodiments, reference levels can be determined using expression levels of a reference based on otherwise healthy patients, all types of FGID patients, and/or all types of CDI, IBS, and/or IBD patients. In some embodiments, reference levels can be based on an internal reference such as a gene, metabolic pathway, and/or microbe that is present ubiquitously. In some embodiments, comparison can be performed using the fold change or the absolute difference between the feature levels to be compared. In some embodiments, one or more taxonomic and/or metabolic features can be used in the comparison.

In some embodiments, it is contemplated that 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, and/or 25 features may be compared to each other and/or to a reference that is internal or external. In some embodiments, it is contemplated that 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, and/or 100 features may be compared to each other and/or to a reference that is internal or external. In some embodiments, it is contemplated that 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 1443, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 82, 183, 184, 185, 186, 187, 188, 189, 190, 191, 191, 192, 193, 194, 195, 196, 197, 198, 199, and/or 200 features may be compared to each other and/or to a reference that is internal or external. In some embodiments, it is contemplated that any number of features identified in Tables 1-19 may be compared to each other and/or to a reference that is internal or external.

In certain embodiments, comparisons or results from comparisons may reveal or be expressed as x-fold increase or decrease in expression relative to a standard or relative to another feature or relative to the same feature but in a different patient cohort (e.g., a disease patient and/or cohort compared to an appropriate health control). In some embodiments, patients with a particular disease diagnosis may have a relatively high level of feature presentation (e.g., over representation) or relatively low level of feature presentation (e.g., under representation) when compared to patients with a different disease diagnosis and/or otherwise healthy patients, or vice versa.

Fold increases or decreases may be, be at least, or be at most 1-, 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, 10-, 11-, 12-, 13-, 14-, 15-, 16-, 17-, 18-, 19-, 20-, 25-, 30-, 35-, 40-, 45-, 50-, 55-, 60-, 65-, 70-, 75-, 80-, 85-, 90-, 95-, 100- or more, or any range derivable therein. Alternatively, differences in expression may be expressed as a percent decrease or increase, such as at least or at most 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 300, 400, 500, 600, 700, 800, 900, 1000, or greater than 1000% difference, or any range derivable therein. In some embodiments, a fold level change for one or more features may not be calculatable, as one or more features may be absent in one or more disease and/or control patients and/or cohorts (e.g., dividing by zero).

Other ways to express relative expression levels are by normalized or relative numbers such as 0, 0.00001, 0.0001, 0.0002, 0.0003, 0.0004, 0.0005, 0.0006, 0.0007, 0.0008, 0.0009, 0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4.0, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, 7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 8.0, 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 9.0, 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7, 9.8, 9.9, 10.0, or any range derivable therein.

In certain embodiments, a feature may be ranked in importance and/or otherwise identified according to a random forest feature rank mean decrease in accuracy. For example, a feature may be considered more integral for appropriate disease classification as a function of the random forest feature rank mean decrease in accuracy. In some embodiments, a higher random forest feature mean decrease in value means the feature has a greater potential disease classification value when compared to a feature with a lower value. In certain embodiments, a feature random forest feature rank mean decrease in accuracy may be 0.00001, 0.0001, 0.0002, 0.0003, 0.0004, 0.0005, 0.0006, 0.0007, 0.0008, 0.0009, 0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, or any range derivable therein.

In some embodiments, algorithms, such as the weighted voting programs, can be used to facilitate the evaluation of feature levels. In addition, in some embodiments, other clinical evidence can be combined with a feature-based test to reduce the risk of false evaluations. In some embodiments, other molecular based evaluations may be considered. In some embodiments, patient questionnaires may be considered. In some embodiments, patient medical histories may be considered. In some embodiments, patient endoscopy results may be considered.

In some embodiments, any biological sample from a patient that accurately represents the microbiome may be used to evaluate the presence, absence, and/or level of any feature discussed herein. In some embodiments, a biological sample from a fecal sample is used. In some embodiments, a biological sample from an endoscopy is used. In some embodiments, a biological sample from a mucosal biopsy is used. In some embodiments, a biological sample from intestinal fluid is used. Evaluation of a biological sample may involve, though it need not involve, panning (enriching) for microbiome components or isolation of specific microbes.

III. Methods of therapeutic intervention

In some embodiments, methods described herein are not limited to intestinal disorders, but are applicable to other microbiome dysbiosis associated disorders.

In certain embodiments, methods of treatment of intestinal disorders are based on features (e.g., taxa and/or metabolic pathways) identified by Taxa4Meta mediated diverse 16S data analysis.

In certain aspects, provided herein are methods for treating a subject determined to have CDI, IBS, IBD UC, and/or IBD CD based on a predetermined profile of one or more taxonomic and/or metabolic pathway features disclosed herein.

In certain embodiments, provided herein are methods for identifying features associated with diseases associated with microbiome dysbiosis, for example but not limited to CDI, IBS, IBD UC, IBD CD, antibiotic-associated diarrhea (AAD), celiac disease, food allergies, autoimmune disease, cancer, and/or graft versus host disease.

In some embodiments, an appropriate therapeutic agent is a small molecule, a biologic (e.g., an antibody, a recombinant protein, a cell therapy, etc.), a microbiota therapy (e.g., fecal transplant, fecal microbiota therapy, etc.), a mineral, a vitamin, a dietary restriction, a life style restriction and/or behavioral therapy.

In some embodiments, an appropriate therapeutic intervention for treating a subject that has received a CDI disease classification include but are not limited to administration of: vancomycin, fidaxomicin, bezlotoxumab, metronidazole (less preferred), fecal microbiota therapy (FMT) (e.g., particularly in cases of recurrent CDI), and/or microbiota consortia products.

In some embodiments, an appropriate therapeutic intervention for treating a subject that has received an IBD disease classification include but are not limited to administration of: anti-inflammatory drugs (e.g., for reduction of digestive tract inflammation), sulfasalazine, corticosteroids, immune suppressants (e.g., to prevent the autoimmune attacks), azathioprinc, antibiotics (e.g., to ameliorate bacterial infections), ciprofloxacin, metronidazole, TNF signaling pathway antagonists, Cimzia, α4β7 integrin antagonists, Entyvio (vedolizumab), Humira (adalimumab), Remicade (infliximab), Simponi (golimumab), Stelara (ustekinumab), anti-diarrheal agents (e.g., to prevent diarrhea and ameliorate associated symptoms), loperamide, diphenoxylate, cholestyramine, analgesics (e.g., to reduce pain and ameliorate associated symptoms), acetaminophen, vitamin and/or mineral supplements, vitamin D, and/or calcium.

In some embodiments, an appropriate therapeutic intervention for treating a subject that has received an IBS disease classification include but are not limited to administration of: bezlotoxumab, anti-diarrheal agents (e.g., to prevent diarrhea and/or ameliorate associated symptoms), loperamide, cholestyramine, colestipol, anticholinergics (e.g., to relieve spasms), dicyclomine, tricyclic antidepressants (e.g., to relieve depression and severe pain), imipramine, desipramine, selective serotonin reuptake inhibitors (SSRIs) (e.g., to relieve depression, pain and/or constipation), fluoxetine, paroxetine, anticonvulsants (e.g., to relieve pain and/or bloating), pregabalin, and/or gabapentin.

Therapy provided herein may comprise administration of a combination of therapeutic agents, such as for example, a first therapy (e.g., antimicrobials) and a second therapy (e.g., dietary restrictions). The therapies may be administered in any suitable manner known in the art. For example, the first and second treatment may be administered sequentially (at different times) or concurrently (at the same time).

In some aspects, the first therapy and the second therapy are administered substantially simultaneously. In some aspects, the first therapy and the second therapy are administered sequentially. In some aspects, the first therapy, the second therapy, and a third therapy are administered sequentially. In some aspects, the first therapy is administered before administering the second therapy. In some aspects, the first therapy is administered after administering the second therapy.

Aspects of the disclosure relate to compositions and methods comprising therapeutic compositions. The different therapies may be administered in one composition or in more than one composition, such as 2 compositions, 3 compositions, or 4 compositions. Various combinations of the agents may be employed.

Therapeutic agents of the disclosure may be administered by the same route of administration or by different routes of administration. In some aspects, the therapy is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by implantation, by inhalation, intrathecally, intraventricularly, or intranasally. In some aspects, the antibiotic is administered intravenously, intramuscularly, subcutaneously, topically, orally, transdermally, intraperitoneally, intraorbitally, by implantation, by inhalation, intrathecally, intraventricularly, or intranasally. The appropriate dosage may be determined based on the type of disease to be treated, severity and course of the disease, the clinical condition of the individual, the individual's clinical history and response to the treatment, and the discretion of the attending physician.

The treatments may include various “unit doses.” Unit dose is defined as containing a predetermined-quantity of the therapeutic composition. The quantity to be administered, and the particular route and formulation, is within the skill of determination of those in the clinical arts. A unit dose need not be administered as a single injection but may comprise continuous infusion over a set period of time. In some aspects, a unit dose comprises a single administrable dose.

The quantity to be administered, both according to number of treatments and unit dose, depends on the treatment effect desired. An effective dose (also “effective amount” or “therapeutically effective amount”) is understood to refer to an amount necessary to achieve a particular effect. In the practice in certain aspects, it is contemplated that doses in the range from 10 mg/kg to 200 mg/kg can affect the protective capability of these agents. Thus, it is contemplated that doses include doses of about 0.1, 0.5, 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, and 200, 300, 400, 500, 1000 μg/kg, mg/kg, μg/day, or mg/day or any range derivable therein. Furthermore, such doses can be administered at multiple times during a day, and/or on multiple days, weeks, or months.

In certain aspects, the effective dose of the pharmaceutical composition is one which can provide a blood level of about 1 μM to 150 μM. In another aspect, the effective dose provides a blood level of about 4 μM to 100 μM.; or about 1 μM to 100 μM; or about 1 μM to 50 μM; or about 1 μM to 40 μM; or about 1 μM to 30 μM; or about 1 μM to 20 μM; or about 1 μM to 10 μM; or about 10 μM to 150 μM; or about 10 μM to 100 μM; or about 10 μM to 50 μM; or about 25 μM to 150 μM; or about 25 μM to 100 M; or about 25 μM to 50 μM; or about 50 μM to 150 μM; or about 50 μM to 100 μM (or any range derivable therein). In other aspects, the dose can provide the following blood level of the agent that results from a therapeutic agent being administered to a subject: about, at least about, or at most about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, or 100 μM or any range derivable therein. In certain aspects, the therapeutic agent that is administered to a subject is metabolized in the body to a metabolized therapeutic agent, in which case the blood levels may refer to the amount of that agent. Alternatively, to the extent the therapeutic agent is not metabolized by a subject, the blood levels discussed herein may refer to the unmetabolized therapeutic agent.

Precise amounts of the therapeutic composition also depend on the judgment of the practitioner and are peculiar to each individual. Factors affecting dose include physical and clinical state of the patient, the route of administration, the intended goal of treatment (alleviation of symptoms versus cure) and the potency, stability and toxicity of the particular therapeutic substance or other therapies a subject may be undergoing.

It will be understood by those skilled in the art and made aware that dosage units of μg/kg or mg/kg of body weight can be converted and expressed in comparable concentration units of μg/ml or mM (blood levels), such as 4 μM to 100 μM. It is also understood that uptake is species and organ/tissue dependent. The applicable conversion factors and physiological assumptions to be made concerning uptake and concentration measurement are well-known and would permit those of skill in the art to convert one concentration measurement to another and make reasonable comparisons and conclusions regarding the doses, efficacies and results described herein.

In certain instances, it will be desirable to have multiple administrations of the composition, e.g., 2, 3, 4, 5, 6 or more administrations. The administrations can be at 1, 2, 3, 4, 5, 6, 7, 8, to 5, 6, 7, 8, 9, 10, 11, or 12 week intervals, including all ranges there between.

The phrases “pharmaceutically acceptable” or “pharmacologically acceptable” refer to molecular entities and compositions that do not produce an adverse, allergic, or other untoward reaction when administered to an animal or human. As used herein, “pharmaceutically acceptable carrier” includes any and all solvents, dispersion media, coatings, anti-bacterial and anti-fungal agents, isotonic and absorption delaying agents, and the like. The use of such media and agents for pharmaceutical active substances is well known in the art. Except insofar as any conventional media or agent is incompatible with the active ingredients, its use in immunogenic and therapeutic compositions is contemplated. Supplementary active ingredients, such as other anti-infective agents and vaccines, can also be incorporated into the compositions.

The active compounds can be formulated for parenteral administration, e.g., formulated for injection via the intravenous, intramuscular, subcutaneous, or intraperitoneal routes. Typically, such compositions can be prepared as either liquid solutions or suspensions; solid forms suitable for use to prepare solutions or suspensions upon the addition of a liquid prior to injection can also be prepared; and, the preparations can also be emulsified.

The pharmaceutical forms suitable for injectable use include sterile aqueous solutions or dispersions; formulations including, for example, aqueous propylene glycol; and sterile powders for the extemporaneous preparation of sterile injectable solutions or dispersions. In all cases the form must be sterile and must be fluid to the extent that it may be easily injected. It also should be stable under the conditions of manufacture and storage and must be preserved against the contaminating action of microorganisms, such as bacteria and fungi.

The proteinaccous compositions may be formulated into a neutral or salt form. Pharmaceutically acceptable salts, include the acid addition salts (formed with the free amino groups of the protein) and which are formed with inorganic acids such as, for example, hydrochloric or phosphoric acids, or such organic acids as acetic, oxalic, tartaric, mandelic, and the like. Salts formed with the free carboxyl groups can also be derived from inorganic bases such as, for example, sodium, potassium, ammonium, calcium, or ferric hydroxides, and such organic bases as isopropylamine, trimethylamine, histidine, procaine and the like.

A pharmaceutical composition can include a solvent or dispersion medium containing, for example, water, ethanol, polyol (for example, glycerol, propylene glycol, and liquid polyethylene glycol, and the like), suitable mixtures thereof, and vegetable oils. The proper fluidity can be maintained, for example, by the use of a coating, such as lecithin, by the maintenance of the required particle size in the case of dispersion, and by the use of surfactants. The prevention of the action of microorganisms can be brought about by various anti-bacterial and anti-fungal agents, for example, parabens, chlorobutanol, phenol, sorbic acid, thimerosal, and the like. In many cases, it will be preferable to include isotonic agents, for example, sugars or sodium chloride. Prolonged absorption of the injectable compositions can be brought about by the use in the compositions of agents delaying absorption, for example, aluminum monostearate and gelatin.

Sterile injectable solutions are prepared by incorporating the active compounds in the required amount in the appropriate solvent with various other ingredients enumerated above, as required, followed by filtered sterilization or an equivalent procedure. Generally, dispersions are prepared by incorporating the various sterilized active ingredients into a sterile vehicle which contains the basic dispersion medium and the required other ingredients from those enumerated above. In the case of sterile powders for the preparation of sterile injectable solutions, the preferred methods of preparation are vacuum-drying and freeze-drying techniques, which yield a powder of the active ingredient, plus any additional desired ingredient from a previously sterile-filtered solution thereof.

Administration of the compositions will typically be via any common route. This includes, but is not limited to oral, or intravenous administration. Alternatively, administration may be by orthotopic, intradermal, subcutaneous, intramuscular, intraperitoneal, or intranasal administration. Such compositions would normally be administered as pharmaceutically acceptable compositions that include physiologically acceptable carriers, buffers or other excipients.

Upon formulation, solutions will be administered in a manner compatible with the dosage formulation and in such amount as is therapeutically or prophylactically effective. The formulations are easily administered in a variety of dosage forms, such as the type of injectable solutions described above.

Various combinations of antimicrobial and/or antibiotic agents or compounds may be employed, for example an antimicrobial is “A” and an additional therapeutic agent is “B” (or a combination of such agents and/or compounds), and given as part of a therapeutic regimen, for example:

A/B/A B/A/B B/B/A A/A/B A/B/B B/A/A A/B/B/B B/A/B/B

B/B/B/A B/B/A/B A/A/B/B A/B/A/B A/B/B/A B/B/A/A

B/A/B/A B/A/A/B A/A/A/B B/A/A/A A/B/A/A A/A/B/A

Administration of a therapeutic compounds or agents to a patient will follow general protocols for the administration of such compounds, taking into account the toxicity, if any, of a therapy. It is expected that treatment cycles would be repeated as necessary. It also is contemplated that various standard therapies, as well as surgical intervention, may be applied in combination with a described therapy.

IV. Kits

In some embodiments, the present invention also concern kits containing compositions of the disclosure or compositions to implement methods of the disclosure. In some aspects, kits can be used to evaluate one or more biomarkers (e.g., features as described herein). In some aspects, kits can be used to detect, for example, absence, presence, and/or level of one or more features described herein. In certain aspects, a kit contains, contains at least or contains at most 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57,58, 59, 60, 61, 62, 63, 64, 65, 66, 100, 132, 500, 1,000 or more probes, primers or primer sets, synthetic molecules or inhibitors, or any value or range and combination derivable therein.

In some embodiments, a kit can be prepared from readily available materials and reagents. For example, such kits can comprise any one or more of the following materials: enzymes, reaction tubes, buffers, detergent, primers, probes, antibodies. In some embodiments, a kit allows a practitioner to obtain biological samples. In another preferred embodiment these kits include the needed apparatus for performing RNA extraction, RT-PCR, oligonucleotide quantification, protein and/or metabolite quantification, and/or gel electrophoresis. Instructions for performing associated assays can also be included in a kit.

In some embodiments, a kit may comprise a number of agents for assessing differential levels and/or expression of a number of features, for example, at least one feature listed in Tables 1-19.

In some embodiments, a kit may comprise reagents for detection of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 and/or 25 features. In some embodiments, a kit may comprise reagents for detection of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, and/or 100 features. In some embodiments, a kit may comprise reagents for detection of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 1443, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 82, 183, 184, 185, 186, 187, 188, 189, 190, 191, 191, 192, 193, 194, 195, 196, 197, 198, 199, and/or 200 or more features.

In some embodiments, a kit is housed in a container. Kits may further comprise instructions for using the kit for assessing expression, means for converting the expression data into expression values and/or means for analyzing expression values to generate prognosis. Agents in a kit for measuring biomarker expression may comprise a plurality of PCR probes and/or primers for qRT-PCR and/or a plurality of antibody or fragments thereof for assessing expression of biomarkers. In another embodiment, agents in a kit for measuring biomarker expression may comprise an array of polynucleotides complementary to mRNAs of biomarkers identified herein. Possible means for converting expression data into expression values and for analyzing expression values to generate scores that predict survival or prognosis may be also included.

In some embodiments, a kit may comprise components, which may be individually packaged or placed in a container, such as a tube, bottle, vial, syringe, or other suitable container means.

Individual components may also be provided in a kit in concentrated amounts; in some aspects, a component is provided individually in the same concentration as it would be in a solution with other components. Concentrations of components may be provided as 1×, 2×, 5×, 10×, or 20× or more.

Kits for using probes, synthetic nucleic acids, nonsynthetic nucleic acids, and/or inhibitors of the disclosure for prognostic or diagnostic applications are included as part of the disclosure. Specifically contemplated are any such molecules corresponding to any biomarker identified herein, which includes nucleic acid primers/primer sets and probes that are identical to or complementary to all or part of a biomarker, which may include noncoding sequences of the biomarker, as well as coding sequences of the biomarker.

In certain aspects, negative and/or positive control nucleic acids, probes, and inhibitors are included in some kit aspects. In addition, a kit may include a sample that is a negative or positive control for copy number or expression of one or more biomarkers.

Any aspect of the disclosure involving specific taxanomic profile and/or metabolic pathway biomarker by name is contemplated also to cover aspects involving biomarkers whose characteristics are at least 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, or 99% identical to the specified taxanomic profile and/or metabolic pathway.

V. Aspects

The following aspects describe certain inventions disclosed herein.

- Aspect 1) A method comprising: applying 16S rRNA variable region-specific amplicon sequence length confidence threshold levels to a meta-analysis 16S rRNA sequencing dataset (e.g., pan-microbiome dataset) comprising sequences derived from diverse 16S rRNA sequencing data, wherein taxonomic misclassification rates are reduced when compared to taxonomic classification produced through global conservative confidence threshold application to all types of 16S amplicon data, and wherein the amplicon sequence length is measured in number of bases in an amplicon.
- Aspect 2) The method of aspect 1, wherein the region-specific amplicon sequence length levels are: ≥200 for V1V3 amplicon forward and ≥300 for V1V3 amplicon reverse; ≥200 for V1V2 amplicon forward and ≥300 for V1V2 amplicon reverse; >200 for V2V3 amplicon forward and ≥300 for V2V3 amplicon reverse; ≥250 for V3V5 amplicon forward and ≥300 for V3V5 amplicon reverse; ≥250 for V3V4 amplicon forward and ≥300 for V3V4 amplicon reverse; ≥250 for V4V5 amplicon forward and ≥300 for V4V5 amplicon reverse; ≥200 for V4 amplicon forward and ≥200 for V4 amplicon reverse; and 2300 for V6V9 amplicon forward and ≥250 for V6V9 amplicon reverse, optionally, wherein the levels are: 200-450 for V1V3 amplicon forward and 300-450 for V1V3 amplicon reverse; 200-450 for V1V2 amplicon forward and 300-450 for V1V2 amplicon reverse; 200-450 for V2V3 amplicon forward and 300-450 for V2V3 amplicon reverse; 250-450 for V3V5 amplicon forward and 300-450 for V3V5 amplicon reverse; 250-450 for V3V4 amplicon forward and 300-450 for V3V4 amplicon reverse; 250-450 for V4V5 amplicon forward and 300-450 for V4V5 amplicon reverse; 200-250 for V4 amplicon forward and 200-250 for V4 amplicon reverse; and 300-450 for V6V9 amplicon forward and 250-450 for V6V9 amplicon reverse.
- Aspect 3) The method of aspect 1 or 2, wherein unstitched forward reads after paired-end merging are included in the dataset to avoid discarding reads with good sequence quality, VSEARCH is used to cluster the data and 99% similarity is applied to defined length ranges in forward and reverse amplicon reads from selected 16S regions, and confident species calls are archived for further downstream use using Bayesian LCA-based Taxonomic Classification Method (BLCA) with stringent alignment.
- Aspect 4) The method of any one of aspects 1-3, wherein stringent alignment parameters of 99% identity and 99% coverage are utilized.
- Aspect 5) The method of any one of aspects 1-4, wherein the taxonomic confidence threshold selections at genus threshold are: 90 for V1V3 amplicon forward, 90 for V1V3 amplicon reverse; 90 for V1V2 amplicon forward, 90 for V1V2 amplicon reverse; 90 for V2V3 amplicon forward, 90 for V2V3 amplicon reverse; 85 for V3V5 amplicon forward, 85 for V3V5 amplicon reverse; 85 for V3V4 amplicon forward, 85 for V3V4 amplicon reverse; 85 for V4V5 amplicon forward, 85 for V4V5 amplicon reverse; 70 for V4 amplicon forward, 70 for V4 amplicon reverse; and/or 90 for V6V9 amplicon forward, 90 for V6V9 amplicon reverse; and/or wherein the taxonomic confidence threshold selection at species threshold are: 60 for V1V3 amplicon forward, 60 for V1V3 amplicon reverse; 60 for V1V2 amplicon forward, 60 for V1V2 amplicon reverse; 60 for V2V3 amplicon forward, 60 for V2V3 amplicon reverse; 50 for V3V5 amplicon forward, 50 for V3V5 amplicon reverse; 50 for V3V4 amplicon forward, 50 for V3V4 amplicon reverse; 50 for V4V5 amplicon forward, 50 for V4V5 amplicon reverse; 50 for V4 amplicon forward, 50 for V4 amplicon reverse; and/or 50 for V6V9 amplicon forward, 50 for V6V9 amplicon reverse.
- Aspect 6) The method of any one of aspects 1-5, wherein the method is used to conduct population-scale meta-analysis to define a microbiome.
- Aspect 7) The method of any one of aspects 1-6, wherein the method is used to conduct population scale meta-analysis to define a healthy human gut microbiome.
- Aspect 8) The method of any one of aspects 1-7, wherein the method is used to conduct population-scale meta-analysis to define microbiome dysbiosis (i.e. non-healthy) in a human gut microbiome, wherein the non-healthy human gut microbiome is associated with irritable bowel syndrome (IBS), inflammatory bowel diseases (IBD), or Clostridiodes difficile infection (CDI).
- Aspect 9) The method of aspect 8, wherein features representative of microbiome dysbiosis associated with IBS, IBD Ulcerative Colitis (UC), IBD Crohn's Disease (CD), and/or CDI are identified.
- Aspect 10) The method of aspect 9, wherein the features associated with IBS, IBD UC. IBD CD, and/or CDI are used for disease classification.
- Aspect 11) The method of aspect 10, wherein a patient with microbiome dysbiosis is diagnosed as having IBS, IBD UC, IBD CD, and/or CDI.
- Aspect 12) The method of aspect 11, wherein a treatment regimen is adjusted or maintained according to the diagnosis.
- Aspect 13) A method of treating an individual having diarrhea comprising: measuring for one or more taxonomical features from a biological sample from the individual; and reducing the administration of antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of non-CDI causative diarrhea, or administering antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of pathogenic infection.
- Aspect 14) The method of aspect 13, wherein the antibiotics and/or antimicrobial treatment comprise at least one of the antibiotics selected from a small molecule antibiotic, an antibiotic derived from a natural product, a microbial composition, an antibody suitable for neutralizing pathogenic infections, a therapeutic, contact isolation, and any combination thereof.
- Aspect 15) The method of aspect 14, with the proviso that if the non-CDI causative diarrhea is irritable bowel syndrome (IBS), administration of the antibiotic and/or antimicrobial rifaximin is not reduced.
- Aspect 16) The method of aspect 14, wherein the antibiotics and/or antimicrobial treatment comprises at least one of vancomycin, fidaxomicin, and bezlotoxumab
- Aspect 17) The method of aspect 16, wherein the treatment is fidaxomicin, and optionally the treatment dosage is at least 200 mg twice daily for 10 days, the treatment is vancomycin, and optionally the treatment dosage is at least 125 mg four times per day for 10 days, and/or the treatment is bezlotoxumab.
- Aspect 18) The method of any one of aspects 13-17, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 10 taxonomical features described in any one of Tables 9-17
- Aspect 19) The method of aspect 18, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 20 taxonomical features described in any one of Tables 9-17.
- Aspect 20) The method of aspect 18, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 40 taxonomical features described in any one of Tables 9-17.
- Aspect 21) The method of aspect 18, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 60 taxonomical features described in any one of Tables 9-17.
- Aspect 22) The method of aspect 18, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 80 taxonomical features described in any one of Tables 9-17.
- Aspect 23) The method of aspect 18, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 100 taxonomical features described in any one Tables 9-17.
- Aspect 24) The method of any one of aspects 19-23, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification comprises characterization using more than one of Tables 9-17.
- Aspect 25) The method of aspect 24, wherein the more than one characterization using Tables 9-17 is sequential.
- Aspect 26) The method of aspect 24 or 25, wherein the more than one characterization using Tables 9-17 comprises first characterizing using Tables 10 and/or 12, followed by characterization using one or more of the remaining Tables.
- Aspect 27) The method of any one of aspects 13-26, wherein the measuring of one or more taxonomical features comprises at least one of analyzing one or more nucleic acids in the sample, analyzing one or more metabolites in the sample, and analyzing one or more proteins in the sample.
- Aspect 28) The method of aspect 27, wherein the nucleic acid is analyzed by sequencing, polymerase chain reaction, isothermal amplification, bioinformatics, or any combination thereof.
- Aspect 29) The method of aspect 28, wherein the nucleic acid analyzed is 16S ribosomal RNA.
- Aspect 30) The method of aspect 27, wherein the metabolites are analyzed by mass spectrometry, ELISA, chromatography, or any combination thereof.
- Aspect 31) The method of aspect 27, wherein the proteins are analyzed by mass spectrometry, ELISA, chromatography, Western blotting, immunoprecipitation, immunoelectrophoresis, or any combination thereof.
- Aspect 32) The method of any one of aspects 13-31, wherein when reducing the administration of antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of non-CDI causative diarrhea, the subject microbiome is further characterized to determine whether the non-CDI causative diarrhea is associated with irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD), and treatment is modified accordingly.
- Aspect 33) The method of aspect 32, wherein the non-CDI causative diarrhea is associated with IBD, the IBD is further characterized to determine whether the IBD is Ulcerative Colitis (UC) or Crohn's Disease (CD), and treatment is modified accordingly.
- Aspect 34) The method of aspect 13, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Sphingobacteriaceae Pedobacter; Saccharibacteria Incertae Sedis; Peptostreptococcaceae Intestinibacter; Bacillales Incertae Sedis Gemella; Veillonella infantium; Chloroplast Streptophyta; Caulobacter segnis; Methylophilaceae Methylophilus; Lactobacillus Streptococcaceae; Burkholderiales Comamonadaceae; Burkholderia ambifaria; Caulobacteraceae Caulobacter; Betaproteobacteria; Phyllobacteriaceae Phyllobacterium; Burkholderiales Burkholderiaceae; Sphingomonadaceae; Sphingomonas; Prevotellamassilia timonensis; Collinsella aerofaciens; Adlercreutzia equolifaciens; Blautia hominis; and Dorea formicigenerans; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 35) The method of aspect 34, wherein an increase in relative abundance of at least one of: Sphingobacteriaceae Pedobacter; Saccharibacteria Incertae Sedis; Peptostreptococcaceae Intestinibacter; Bacillales Incertae Sedis Gemella; Veillonella infantium; Chloroplast Streptophyta; Caulobacter segnis; Methylophilaceae Methylophilus; Lactobacillus Streptococcaceae; Burkholderiales Comamonadaceae; Burkholderia ambifaria; Caulobacteraceae Caulobacter; Betaproteobacteria; Phyllobacteriaceae Phyllobacterium; Burkholderiales Burkholderiaceae; Sphingomonadaceae; Sphingomonas; and Prevotellamassilia timonensis, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 36) The method of aspect 34, wherein a decrease in relative abundance of at least one of: Collinsella aerofaciens; Adlercreutzia equolifaciens; Blautia hominis; and Dorea formicigenerans, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 37) The method of aspect 34-36, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 38) The method of aspect 13, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Acidaminococcaceae Acidaminococcus; Actinomycetales Actinomycetaceae; Bacillales Gemella; Bacilli Lactobacillus; Betaproteobacteria; Betaproteobacteria Burkholderiales; Bifidobacterium boum; Blautia hominis; Clostridiales Incertae Sedis XI Parvimonas; Enterobacteriaceae Cedecea; Erysipelotrichaceae Faecalicoccus; Faecalimonas umbilicata; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Gammaproteobacteria Enterobacterales; Lachnoclostridium [Clostridium] bolteae; Lachnospiraceae Lachnoclostridium; Megasphaera micronuciformis; Peptoniphilaceae Peptoniphilus; Peptostreptococcaceae Peptostreptococcus; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Terrisporobacter; Proteobacteria Gammaproteobacteria; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Ruminococcaceae Intestinimonas; Ruminococcaceae Subdoligranulum; Solobacterium moorei; Veillonellaceae Veillonella; Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides koreensis; Bacteroides thetaiotaomicron; Bacteroides xylanisolvens; Colidextribacter massiliensis; Coprococcus catus; Coprococcus eutactus; Enterobacterales Enterobacteriaceae; Faecalibacterium prausnitzii; Methanobrevibacter smithii; Phascolarctobacterium faecium; Romboutsia timonensis; and Turicibacter sanguinis; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 39) The method of aspect 38, wherein an increase in relative abundance of at least one of: Acidaminococcaceae Acidaminococcus; Actinomycetales Actinomycetaceae; Bacillales Gemella; Bacilli Lactobacillus; Betaproteobacteria; Betaproteobacteria Burkholderiales; Bifidobacterium boum; Blautia hominis; Clostridiales Incertae Sedis XI Parvimonas; Enterobacteriaceae Cedecea; Erysipelotrichaceae Faecalicoccus; Faecalimonas umbilicata; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Gammaproteobacteria Enterobacterales; Lachnoclostridium [Clostridium] boltede; Lachnospiraceae Lachnoclostridium; Megasphaera micronuciformis; Peptoniphilaceae Peptoniphilus; Peptostreptococcaceae Peptostreptococcus; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Terrisporobacter; Proteobacteria Gammaproteobacteria; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Ruminococcaceae Intestinimonas; Ruminococcaceae Subdoligranulum; Solobacterium moorei; and Veillonellaceae Veillonella, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 40) The method of aspect 38, wherein a decrease in relative abundance of at least one of: Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides koreensis; Bacteroides thetaiotaomicron; Bacteroides xylanisolvens; Colidextribacter massiliensis; Coprococcus catus; Coprococcus eutactus; Enterobacterales Enterobacteriaceae; Faecalibacterium prausnitzii; Methanobrevibacter smithii; Phascolarctobacterium faecium; Romboutsia timonensis; and Turicibacter sanguinis, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 41) The method of aspect 38-40, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 42) The method of aspect 13, wherein the individual is a pediatric individual, and wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy pediatric gut microbiome, of at least one of: Bacilli Lactobacillus; Peptostreptococcaceae Clostridioides; Enterococcaceae Enterococcus; Eggerthellaceae Eggerthella; Erysipelotrichaceae Erysipelatoclostridium; Lachnospiraceae Lachnoclostridium; Firmicutes Bacilli; Enterobacteriaceae Escherichia; Enterobacteriales Enterobacteriaceae; Streptococcaceae Streptococcus; Actinomycetaceae Schaalia; Clostridiaceae Hungatella; Clostridiaceae Clostridium; Corynebacteriaceae Corynebacterium; Veillonellaceae Veillonella; Actinomycetaceae Actinomyces; Fusobacteriaceae Fusobacterium; Erysipelotrichaceae Longicatena; Lachnospiraceae Clostridium XIVa; Lachnospiraceae Eisenbergiella; Peptostreptococcaceae Intestinibacter; Enterobacteriaceae Citrobacter; Peptoniphilaceae Finegoldia; Carnobacteriaceae Granulicatella; Coriobacteriaceae Eggerthella; Peptostreptococcaceae Peptostreptococcus; Drancourtella massiliensis; Peptoniphilaceae Anaerococcus; Bacillales Gemella; Lachnospiraceae Sellimonas; Peptoniphilaceae Peptoniphilus; Pasteurellaceae Rodentibacter; Clostridium sensu stricto; Lachnospiraceae Faecalimonas; Proteobacteria Gammaproteobacteria; Clostridiaceae Lactonifactor; Micrococcaceae Rothia; Leuconostocaceae Weissella; Peptostreptococcaceae Terrisporobacter; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Clostridium XI; Coriobacteriaceae Atopobium; Atopobiaceae Atopobium; Ruminococcaceae Anaeromassilibacillus; Porphyromonadaceae Parabacteroides; Rikenellaceae Alistipes; Lachnospiraceae Eubacterium rectale group; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Porphyromonadacede Odoribacter; Veillonellaceae Dialister; Ruminococcaceae Clostridium IV; Bacteroidia Bacteroidales; Coriobacteriaceae Collinsella; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Clostridium leptum group; Enterobacteriaceae Shimwellia; Acidaminococcaceae Phascolarctobacterium; Staphylococcaceae Staphylococcus; Lachnospiraceae Anaerobutyricum; Erysipelotrichaceae Holdemania; Clostridiales Monoglobus; Porphyromonadaceae Barnesiella; Pasteurellales Pasteurellaceae; Clostridiales Clostridiaceae 1; and Bacteroidales Rikenellaceae; wherein the change in taxonomical feature relative abundance is indicative of CDI associated diarrhea.
- Aspect 43) The method of aspect 42, wherein an increase in relative abundance of at least one of: Bacilli Lactobacillus; Peptostreptococcaceae Clostridioides; Enterococcaceae Enterococcus; Eggerthellaceae Eggerthella; Erysipelotrichaceae Erysipelatoclostridium; Lachnospiraceae Lachnoclostridium; Firmicutes Bacilli; Enterobacteriaceae Escherichia; Enterobacteriales Enterobacteriaceae; Streptococcaceae Streptococcus; Actinomycetaceae Schaalia; Clostridiaceae Hungatella; Clostridiaceae Clostridium; Corynebacteriaceae Corynebacterium; Veillonellaceae Veillonella; Actinomycetaceae Actinomyces; Fusobacteriaceae Fusobacterium; Erysipelotrichaceae Longicatena; Lachnospiraceae Clostridium XIVa; Lachnospiraceae Eisenbergiella; Peptostreptococcaceae Intestinibacter; Enterobacteriaceae Citrobacter; Peptoniphilaceae Finegoldia; Carnobacteriaceae Granulicatella; Coriobacteriaceae Eggerthella; Peptostreptococcaceae Peptostreptococcus; Drancourtella massiliensis; Peptoniphilaceae Anaerococcus; Bacillales Gemella; Lachnospiraceae Sellimonas; Peptoniphilaceae Peptoniphilus; Pasteurellaceae Rodentibacter; Clostridium sensu stricto; Lachnospiraceae Faecalimonas; Proteobacteria Gammaproteobacteria; Clostridiaceae Lactonifactor; Micrococcaceae Rothia; Leuconostocaceae Weissella; Peptostreptococcaceae Terrisporobacter; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Clostridium XI; Coriobacteriaceae Atopobium; Atopobiaceae Atopobium; and Ruminococcaceae Anaeromassilibacillus, is indicative of CDI associated diarrhea.
- Aspect 44) The method of aspect 42, wherein a decrease in relative abundance of at least one of: Porphyromonadaceae Parabacteroides; Rikenellaceae Alistipes; Lachnospiraceae Eubacterium rectale group; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Porphyromonadacede Odoribacter; Veillonellaceae Dialister; Ruminococcaceae Clostridium IV; Bacteroidia Bacteroidales; Coriobacteriaceae Collinsella; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Clostridium leptum group; Enterobacteriaceae Shimwellia; Acidaminococcaceae Phascolarctobacterium; Staphylococcaceae Staphylococcus; Lachnospiraceae Anaerobutyricum; Erysipelotrichaceae Holdemania; Clostridiales Monoglobus; Porphyromonadaceae Barnesiella; Pasteurellales Pasteurellaceae; Clostridiales Clostridiaceae 1; and Bacteroidales Rikenellaceae, is indicative of CDI associated diarrhea.
- Aspect 45) The method of aspect 42-44, wherein a change in relative abundance of at least four taxonomical features is indicative of CDI associated diarrhea.
- Aspect 46) The method of aspect 32, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBS or IBD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBD gut microbiome, of at least one of: Blautia stercoris; Saccharibacteria Incertae Sedis; Bacteroides plebeius; Bacteroides nordii; Eubacterium siraeum; Bacteroides cellulosilyticus; Burkholderiales Burkholderiaceae; Caulobacteraceae Caulobacter; Pelomonas aquatic; Burkholderiaceae Burkholderia; Caulobacter segnis; Burkholderia ambifaria; Eubacterium ventriosum; Firmicutes Clostridia; Oxalobacter formigenes; Burkholderiales Comamonadaceae; Veillonella infantium; Bacteroides thetaiotaomicron; Sphingobacteriaceae Pedobacter; Burkholderia thailandensis; Erysipelotrichaceae Turicibacter; Collinsella aerofaciens; Veillonellaceae Veillonella; Lachnospiraceae Lachnoclostridium; Blautia hominis; Gammaproteobacteria Enterobacterales; Bifidobacteriales Bifidobacteriaceae; Ruminococcaceae Intestinimonas; Faecalimonas umbilicata; Actinomycetales Actinomycetaceae; Actinobacteria Actinobacteria; Dorea formicigenerans; and Bacteria Proteobacteria; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 47) The method of aspect 46, wherein an increase in relative abundance of at least one of: Saccharibacteria Incertae Sedis; Bacteroides plebeius; Bacteroides nordii; Eubacterium siraeum; Bacteroides cellulosilyticus; Burkholderiales Burkholderiaceae; Caulobacteraceae Caulobacter; Pelomonas aquatic; Burkholderiaceae Burkholderia; Caulobacter segnis; Burkholderia ambifaria; Eubacterium ventriosum; Firmicutes Clostridia; Oxalobacter formigenes; Burkholderiales Comamonadaceae; Veillonella infantium; Bacteroides thetaiotaomicron; Sphingobacteriaceae Pedobacter; Burkholderia thailandensis; and Erysipelotrichaceae Turicibacter, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 48) The method of aspect 46, wherein a decrease in relative abundance of at least one of: Collinsella aerofaciens; Veillonellaceae Veillonella; Lachnospiraceae Lachnoclostridium; Blautia hominis; Gammaproteobacteria Enterobacterales; Bifidobacteriales Bifidobacteriaceae; Ruminococcaceae Intestinimonas; Faecalimonas umbilicata; Actinomycetales Actinomycetaceae; Actinobacteria Actinobacteria; Dorea formicigenerans; and Bacteria Proteobacteria, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 49) The method of aspect 46-48, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 50) The method of aspect 33, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Lachnospiraceae Lachnoclostridium; Ruminococcaceae Intestinimonas; Acidaminococcaceae Acidaminococcus; Bacilli Lactobacillus; Actinomycetales Actinomycetaceae; Ruminococcaceae Subdoligranulum; Peptostreptococcaceae Romboutsia; Bifidobacterium boum; Bacillales Gemella; Peptostreptococcaceae Peptostreptococcus; Peptoniphilaceae Peptoniphilus; Clostridiales Incertae Sedis XI Parvimonas; Peptostreptococcaceae Terrisporobacter; Erysipelotrichaceae Faecalicoccus; Solobacterium moorei; Bacteroides xylanisolvens; Enterobacterales Enterobacteriaceae; Bacteroides koreensis; Bacteroides cellulosilyticus; Phascolarctobacterium faecium; and Bacteroides thetaiotaomicron, wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 51) The method of aspect 50, wherein an increase in relative abundance of at least one of: Lachnospiraceae Lachnoclostridium; Ruminococcaceae Intestinimonas; Acidaminococcaceae Acidaminococcus; Bacilli Lactobacillus; Actinomycetales Actinomycetaceae; Ruminococcaceae Subdoligranulum; Peptostreptococcaceae Romboutsia; Bifidobacterium boum; Bacillales Gemella; Peptostreptococcaceae Peptostreptococcus; Peptoniphilaceae Peptoniphilus; Clostridiales Incertae Sedis XI Parvimonas; Peptostreptococcaceae Terrisporobacter; Erysipelotrichaceae Faecalicoccus; and Solobacterium moorei, is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 52) The method of aspect 50, wherein a decrease in relative abundance of at least one of: Bacteroides xylanisolvens; Enterobacterales Enterobacteriaceae; Bacteroides koreensis; Bacteroides cellulosilyticus; Phascolarctobacterium faecium; and Bacteroides thetaiotaomicron, is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 53) The method of aspect 50-52, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 54) The method of aspect 33, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Faecalimonas umbilicata; Lachnospiraceae Lachnoclostridium; Lachnoclostridium [Clostridium] bolteae; Proteobacteria Gammaproteobacteria; Bacilli Lactobacillus; Actinomycetales Actinomycetaceae; Gammaproteobacteria Enterobacterales; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Veillonellaceae Veillonella; Acidaminococcaceae Acidaminococcus; Blautia hominis; Bifidobacterium boum; Enterobacteriaceae Cedecea; Ruminococcaceae Intestinimonas; Peptostreptococcaceae Romboutsia; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Megasphaera micronuciformis; Romboutsia timonensis; Faecalibacterium prausnitzii; Coprococcus catus; Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides thetaiotaomicron; Coprococcus eutactus; Turicibacter sanguinis; Colidextribacter massiliensis; and Methanobrevibacter smithii; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 55) The method of aspect 54, wherein an increase in relative abundance of at least one of: Faecalimonas umbilicata; Lachnospiraceae Lachnoclostridium; Lachnoclostridium [Clostridium] bolteae; Proteobacteria Gammaproteobacteria; Bacilli Lactobacillus; Actinomycetales Actinomycetaceae; Gammaproteobacteria Enterobacterales; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Veillonellaceae Veillonella; Acidaminococcaceae Acidaminococcus; Blautia hominis; Bifidobacterium boum; Enterobacteriaceae Cedecea; Ruminococcaceae Intestinimonas; Peptostreptococcaceae Romboutsia; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; and Megasphaera micronuciformis, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 56) The method of aspect 54, wherein a decrease in relative abundance of at least one of: Romboutsia timonensis; Faecalibacterium prausnitzii; Coprococcus catus; Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides thetaiotaomicron; Coprococcus eutactus; Turicibacter sanguinis; Colidextribacter massiliensis; and Methanobrevibacter smithii, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 57) The method of aspect 54-56, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 58) The method of aspect 33, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBD UC gut microbiome, of at least one of: Faecalimonas umbilicata; Blautia [Ruminococcus] gnavus; Lachnoclostridium [Clostridium] boltede; Erysipelatoclostridium ramosum; Veillonellaceae Veillonella; Enterobacterales Enterobacteriaceae; Blautia caecimuris; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Faecalibacterium prausnitzii; Ruminococcaceae Oscillibacter; Ruminococcaceae Clostridium IV; Romboutsia timonensis; Ruminococcaceae Pseudoflavonifractor; Erysipelotrichales Erysipelotrichaceae; and Methanobacteriaceae Methanobrevibacter; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 59) The method of aspect 58, wherein an increase in relative abundance of at least one of: Faecalimonas umbilicata; Blautia [Ruminococcus] gnavus; Lachnoclostridium [Clostridium] bolteae; Erysipelatoclostridium ramosum; Veillonellaceae Veillonella; Enterobacterales Enterobacteriaceae; Blautia caecimuris; Fusobacteriaceae Fusobacterium; and Fusobacterium nucleatum, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 60) The method of aspect 58, wherein a decrease in relative abundance of at least one of: Faecalibacterium prausnitzii; Ruminococcaceae Oscillibacter; Ruminococcaceae Clostridium IV; Romboutsia timonensis; Ruminococcaceae Pseudoflavonifractor; Erysipelotrichales Erysipelotrichaceae; and Methanobacteriaceae Methanobrevibacter, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 61) The method of aspect 58-60, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 62) The method of aspect 13, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of: Anaerostipes hadrus; Faecalibacterium prausnitzii; Lachnospiraceae Coprococcus; Lachnospiraceae [Eubacterium] rectale; Lachnospiraceae Roseburia; Lachnospiraceae Fusicatenibacter; Lachnospiraceae Dorea; Ruminococcaceae Ruminococcus; Roseburia inulinivorans; Dorea longicatena; Roseburia intestinalis; Lachnospiraceae Anaerostipes; Coprococcus comes; Lactobacillus rogosae; Romboutsia timonensis; Saccharibacteria Incertae Sedis; Eubacterium [Eubacterium] eligens; Bacteroides plebeius; Lachnospiraceae Blautia; Roseburia faecis; Blautia obeum; Coprococcus catus; Betaproteobacteria Burkholderiales; Prevotella copri; Burkholderiales Burkholderiaceae; Caulobacter segnis; Caulobacterales Caulobacteraceae; Burkholderiaceae Burkholderia; Burkholderia ambifaria; Prevotellaceae Prevotella; Burkholderiales Comamonadaceae; Burkholderia thailandensis; Alistipes obesi; Blautia stercoris; Ruminococcus bromii; Pelomonas aquatica; Peptostreptococcaceae Romboutsia; Bacteroides coprocola; Streptococcus thermophilus; Ruminococcaceae Oscillibacter; Alistipes ihumii; Ruminococcus callidus; Phyllobacteriaceae Phyllobacterium; Coprococcus eutactus; Peptostreptococcaceae Intestinibacter; Clostridioides difficile; Enterobacterales Enterobacteriaceae; Enterococcaceae Enterococcus; Peptostreptococcaceae Clostridium XI; Gammaproteobacteria Enterobacterales; Bacilli Lactobacillus; Eggerthella lenta; Erysipelatoclostridium [Clostridium] innocuum; Enterobacteriaceae Citrobacter; Lachnospiraceae Clostridium XIVa; Lachnoclostridium [Clostridium] bolteae; Erysipelatoclostridium ramosum; Hungatella effluvia; Veillonella parvula; Lactobacilluseae Lactobacillus; Blautia [Ruminococcus] gnavus; Enterococcus saccharolyticus; and Coriobacteriaceae Eggerthella; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 63) The method of aspect 62, wherein an increase in relative abundance of at least one of: Anaerostipes hadrus; Faecalibacterium prausnitzii; Lachnospiraceae Coprococcus; Lachnospiraceae [Eubacterium] rectale; Lachnospiraceae Roseburia; Lachnospiraceae Fusicatenibacter; Lachnospiraceae Dorea; Ruminococcaceae Ruminococcus; Roseburia inulinivorans; Dorea longicatena; Roseburia intestinalis; Lachnospiraceae Anaerostipes; Coprococcus comes; Lactobacillus rogosae; Romboutsia timonensis; Saccharibacteria Incertae Sedis; Eubacterium [Eubacterium] eligens; Bacteroides plebeius; Lachnospiraceae Blautia; Roseburia faecis; Blautia obeum; Coprococcus catus; Betaproteobacteria Burkholderiales; Prevotella copri; Burkholderiales Burkholderiaceae; Caulobacter segnis; Caulobacterales Caulobacteraceae; Burkholderiaceae Burkholderia; Burkholderia ambifaria; Prevotellaceae Prevotella; Burkholderiales Comamonadaceae; Burkholderia thailandensis; Alistipes obesi; Blautia stercoris; Ruminococcus bromii; Pelomonas aquatica; Peptostreptococcaceae Romboutsia; Bacteroides coprocola; Streptococcus thermophilus; Ruminococcaceae Oscillibacter; Alistipes ihumii; Ruminococcus callidus; Phyllobacteriaceae Phyllobacterium; Coprococcus eutactus; and Peptostreptococcaceae Intestinibacter, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 64) The method of aspect 62, wherein a decrease in relative abundance of at least one of: Clostridioides difficile; Enterobacterales Enterobacteriaceae; Enterobacteriales Enterobacteriaceae; Enterococcaceae Enterococcus; Peptostreptococcaceae Clostridium XI; Gammaproteobacteria Enterobacterales; Bacilli Lactobacilluses; Eggerthella lenta; Erysipelatoclostridium [Clostridium] innocuum; Enterobacteriaceae Citrobacter; Lachnospiraceae Clostridium XIVa; Lachnoclostridium [Clostridium] bolteae; Erysipelatoclostridium ramosum; Hungatella effluvia; Veillonella parvula; Lactobacilluseae Lactobacillus; Blautia [Ruminococcus] gnavus; Enterococcus saccharolyticus; and Coriobacteriaceae Eggerthella, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 65) The method of aspect 62-64, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 66) The method of aspect 13, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of: Anaerostipes hadrus; Lachnospiraceae Dorea; Dorea longicatena; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Blautia obeum; Coprococcus comes; Roseburia intestinalis; Lactobacillus rogosae; Eubacterium [Eubacterium] eligens; Bacteroidia Bacteroidales; Peptostreptococcaceae Romboutsia; Coriobacteriaceae Collinsella; Acidaminococcaceae Acidaminococcus; Prevotellaceae Prevotella; Prevotella copri; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Ruminococcus; Alistipes obesi; Betaproteobacteria Burkholderiales; Ruminococcus bromii; Lachnospiraceae Lachnoclostridium; Bifidobacterium adolescentis; Actinomycetales Actinomycetaceae; Ruminococcaceae Intestinimonas; Bacteroides eggerthii; Clostridioides difficile; Peptostreptococcaceae Clostridium XI; Enterobacteriaceae Citrobacter; Enterobacterales Enterobacteriaceae; Veillonella parvula; Enterococcaceae Enterococcus; Lactobacillus Enterococcaceae; Erysipelatoclostridium [Clostridium] innocuum; Pectobacterium carotovorum; Enterobacteriales Enterobacteriaceae; Bacteroides xylanisolvens; Enterococcus saccharolyticus; Clostridium paraputrificum; Salmonella enterica; Erysipelatoclostridium ramosum; Hungatella effluvia; Bacteroides koreensis; Bacilli Lactobacillus; Blautia product; Klebsiella quasipneumoniae; Ruthenibacterium lactatiformans; Veillonella dispar; Coriobacteriaceae Eggerthella; and Lachnospiraceae Hungatella; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 67) The method of aspect 66, wherein an increase in relative abundance of at least one of: Anaerostipes hadrus; Lachnospiraceae Dorea; Dorea longicatena; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Blautia obeum; Coprococcus comes; Roseburia intestinalis; Lactobacillus rogosae; Eubacterium [Eubacterium] eligens; Bacteroidia Bacteroidales; Peptostreptococcaceae Romboutsia; Coriobacteriaceae Collinsella; Acidaminococcaceae Acidaminococcus; Prevotellaceae Prevotella; Prevotella copri; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Ruminococcus; Alistipes obesi; Betaproteobacteria Burkholderiales; Ruminococcus bromii; Lachnospiraceae Lachnoclostridium; Bifidobacterium adolescentis; Actinomycetales Actinomycetaceae; Ruminococcaceae Intestinimonas; and Bacteroides eggerthii, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 68) The method of aspect 66, wherein a decrease in relative abundance of at least one of: Clostridioides difficile; Peptostreptococcaceae Clostridium XI; Enterobacteriaceae Citrobacter; Enterobacterales Enterobacteriaceae; Veillonella parvula; Enterococcaceae Enterococcus; Lactobacillus Enterococcacede; Erysipelatoclostridium [Clostridium] innocuum; Pectobacterium carotovorum; Enterobacteriales Enterobacteriaceae; Bacteroides xylanisolvens; Enterococcus saccharolyticus; Clostridium paraputrificum; Salmonella enterica; Erysipelatoclostridium ramosum; Hungatella effluvia; Bacteroides koreensis; Bacilli Lactobacillus; Blautia product; Klebsiella quasipneumoniae; Ruthenibacterium lactatiformans; Veillonella dispar; Coriobacteriaceae Eggerthella; and Lachnospiraceae Hungatella, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 69) The method of aspect 66-68, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 70) A method of treating an individual having diarrhea comprising: measuring for one or more metabolic features from a biological sample from the individual; and reducing the administration of antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of non-CDI causative diarrhea; or administering antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of pathogenic infection.
- Aspect 71) The method of aspect 70, wherein the antibiotics and/or antimicrobial treatment comprise at least one of the antibiotics selected from the group consisting of a small molecule antibiotic, an antibiotic derived from a natural product, a microbial composition, an antibody suitable for neutralizing pathogenic infections, a therapeutic, contact isolation, and any combination thereof.
- Aspect 72) The method of aspect 71, with the proviso that if the non-CDI causative diarrhea is irritable bowel syndrome (IBS), administration of the antibiotic and/or antimicrobial rifaximin is not reduced.
- Aspect 73) The method of aspect 71, wherein the antibiotics and/or antimicrobial treatment comprises at least one of vancomycin, fidaxomicin, and bezlotoxumab.
- Aspect 74) The method of aspect 73, wherein the treatment is vancomycin, and optionally the treatment dosage is at least 125 mg four times per day for 10 days, wherein the treatment is fidaxomicin, and optionally the treatment dosage is at least 200 mg twice daily for 10 days, and/or wherein the treatment is bezlotoxumab.
- Aspect 75) The method of any one of aspects 70-74, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 10 metabolic features described in any one of Tables 1-8.
- Aspect 76) The method aspect 75, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 20 metabolic features described in any one of Tables 1-8.
- Aspect 77) The method of aspect 76, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 40 metabolic features described in any one of Tables 1-8.
- Aspect 78) The method of aspect 76, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 60 metabolic features described in any one of Tables 1-8.
- Aspect 79) The method of aspect 76, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 80 metabolic features described in any one of Tables 1-8.
- Aspect 80) The method of aspect 76, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification is characterized by measuring the presence, absence, and/or relative quantity of at least 100 metabolic features described in any one Tables 1-8.
- Aspect 81) The method of any one of aspects 76-80, wherein the pathogenic diarrhea classification or non-CDI causative diarrhea classification comprises characterization using more than one of Tables 1-8.
- Aspect 82) The method of aspect 81, wherein the more than one characterization using Tables 1-8 is sequential.
- Aspect 83) The method of aspect 81 or 82, wherein the more than one characterization using Tables 1-8 comprises first characterizing using Tables 3 and/or 7, followed by characterization using one or more of the remaining Tables.
- Aspect 84) The method of any one of aspects 70-83, wherein the measuring of one or more metabolic features comprises at least one of analyzing one or more nucleic acids in the sample, analyzing one or more metabolites in the sample, and analyzing one or more proteins in the sample.
- Aspect 85) The method of aspect 84, wherein the nucleic acid is analyzed by sequencing, polymerase chain reaction, isothermal amplification, bioinformatics, or any combination thereof.
- Aspect 86) The method of aspect 85, wherein the nucleic acid analyzed is 16S ribosomal RNA.
- Aspect 87) The method of aspect 84, wherein the metabolites are analyzed by mass spectrometry, ELISA, chromatography, or any combination thereof.
- Aspect 88) The method of aspect 84, wherein the proteins are analyzed by mass spectrometry, ELISA, chromatography. Western blotting, immunoprecipitation, immunoelectrophoresis, or any combination thereof.
- Aspect 89) The method of any one of aspects 70-88, wherein when reducing the administration of antibiotics and/or antimicrobial treatment to the individual when the individual has presence or absence or a certain level of one or more feature(s) indicative of non-CDI causative diarrhea, the subject microbiome is further characterized to determine whether the non-CDI causative diarrhea is associated with irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD), and treatment is modified accordingly.
- Aspect 90) The method of aspect 89, wherein the non-CDI causative diarrhea is associated with IBD, the IBD is further characterized to determine whether the IBD is Ulcerative Colitis (UC) or Crohn's Disease (CD), and treatment is modified accordingly.
- Aspect 91) The method of aspect 70, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7159 (chlorophyllide a biosynthesis III (acrobic, light independent)); PWY-5531 (chlorophyllide a biosynthesis II (anaerobic)); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); P562-PWY (myo-inositol degradation I); PWY-3781 (aerobic respiration I (cytochrome c)); TYRFUMCAT-PWY (L-tyrosine degradation I); HCAMHPDEG-PWY (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation to 2-oxopent-4-enoate); PWY-6071 (superpathway of phenylethylamine degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 92) The method of aspect 91, wherein an increase in relative abundance of at least one of: PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7159 (chlorophyllide a biosynthesis III (aerobic, light independent)); PWY-5531 (chlorophyllide a biosynthesis II (anaerobic)); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); P562-PWY (myo-inositol degradation I); PWY-3781 (aerobic respiration I (cytochrome c)); and TYRFUMCAT-PWY (L-tyrosine degradation I), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 93) The method of aspect 91, wherein a decrease in relative abundance of at least one of: HCAMHPDEG-PWY (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation to 2-oxopent-4-enoate); PWY-6071 (superpathway of phenylethylamine degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 94) The method of aspect 91-93, wherein a change in relative abundance of at least three metabolic features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 95) The method of aspect 70, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); DTDPRHAMSYN-PWY (dTDP-L-rhamnose biosynthesis I); FASYN-ELONG-PWY (fatty acid elongation-saturated); GALACTARDEG-PWY (D-galactarate degradation I); GLUCARDEG-PWY (D-glucarate degradation I); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GLUCONEO-PWY (gluconcogenesis I); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); HEMESYN2-PWY (heme biosynthesis II (anacrobic)); HISDEG-PWY (L-histidine degradation I); METHGLYUT-PWY (superpathway of methylglyoxal degradation); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); P163-PWY (L-lysine fermentation to acetate and butanoate); P42-PWY (incomplete reductive TCA cycle); PENTOSE-P-PWY (pentose phosphate pathway); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-1533 (methylphosphonate degradation I); PWY0-41 (allantoin degradation IV (anaerobic)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-5659 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-5705 (allantoin degradation to glyoxylate III); PWY-5913 (TCA cycle VI (obligate autotrophs)); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6353 (purine nucleotides degradation II (acrobic)); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation); PWY-6572 (chondroitin sulfate degradation I (bacterial)); PWY-6588 (pyruvate fermentation to acetone); PWY-6608 (guanosine nucleotides degradation III); PWY-6703 (preQ0 biosynthesis); PWY-6891 (thiazole biosynthesis II (Bacillus)); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY-6901 (superpathway of glucose and xylose degradation); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PWY-7013 (L-1,2-propanediol degradation); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); PWY-7222 (guanosine deoxyribonucleotides de novo biosynthesis II); PWY-7237 (myo-, chiro- and scillo-inositol degradation); PWY-7242 (D-fructuronate degradation); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7456 (mannan degradation); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); TCA (TCA cycle I (prokaryotic)); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); and VALDEG-PWY (L-valine degradation I); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 96) The method of aspect 95, wherein an increase in relative abundance of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); DTDPRHAMSYN-PWY (dTDP-L-rhamnose biosynthesis I); FASYN-ELONG-PWY (fatty acid elongation-saturated); GALACTARDEG-PWY (D-galactarate degradation I); GLUCARDEG-PWY (D-glucarate degradation I); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GLUCONEO-PWY (gluconeogenesis I); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); HISDEG-PWY (L-histidine degradation I); METHGLYUT-PWY (superpathway of methylglyoxal degradation); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); P163-PWY (L-lysine fermentation to acetate and butanoate); P42-PWY (incomplete reductive TCA cycle); PENTOSE-P-PWY (pentose phosphate pathway); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-1533 (methylphosphonate degradation I); PWY0-41 (allantoin degradation IV (anaerobic)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-5659 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-5705 (allantoin degradation to glyoxylate III); PWY-5913 (TCA cycle VI (obligate autotrophs)); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6353 (purine nucleotides degradation II (aerobic)); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation); PWY-6572 (chondroitin sulfate degradation I (bacterial)); PWY-6588 (pyruvate fermentation to acetone); PWY-6608 (guanosine nucleotides degradation III); PWY-6703 (preQ0 biosynthesis); PWY-6891 (thiazole biosynthesis II (Bacillus)); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY-6901 (superpathway of glucose and xylose degradation); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PWY-7013 (L-1,2-propanediol degradation); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); PWY-7222 (guanosine deoxyribonucleotides de novo biosynthesis II); PWY-7237 (myo-, chiro- and scillo-inositol degradation); PWY-7242 (D-fructuronate degradation); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7456 (mannan degradation); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); TCA (TCA cycle I (prokaryotic)); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); and VALDEG-PWY (L-valine degradation I), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 97) The method of any one of aspect 95-96, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 98) The method of aspect 89, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBS or IBD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBS gut microbiome, of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); GALACT-GLUCUROCAT-PWY (superpathway of hexuronide and hexuronate degradation); ANAEROFRUCAT-PWY (homolactic fermentation); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); PWY0-781 (aspartate superpathway); PWY-7242 (D-fructuronate degradation); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-7013 (L-1,2-propanediol degradation); P124-PWY (Bifidobacterium shunt); P122-PWY (heterolactic fermentation); REDCITCYC (TCA cycle VIII (helicobacter)); DENOVOPURINE2-PWY (superpathway of purine nucleotides de novo biosynthesis II); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GALACTARDEG-PWY (D-galactarate degradation I); PWY-6891 (thiazole biosynthesis II (Bacillus)); FUC-RHAMCAT-PWY (superpathway of fucose and rhamnose degradation); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-41 (allantoin degradation IV (anaerobic)); VALDEG-PWY (L-valine degradation I); PWY-7187 (pyrimidine deoxyribonucleotides de novo biosynthesis II); PWY0-1533 (methylphosphonate degradation I); GLUCARDEG-PWY (D-glucarate degradation I); TYRFUMCAT-PWY (L-tyrosine degradation I); PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7094 (fatty acid salvage); and LEU-DEG2-PWY (L-leucine degradation I); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 99) The method of aspect 98, wherein an increase in relative abundance of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); GALACT-GLUCUROCAT-PWY (superpathway of hexuronide and hexuronate degradation); ANAEROFRUCAT-PWY (homolactic fermentation); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); PWY0-781 (aspartate superpathway); PWY-7242 (D-fructuronate degradation); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-7013 (L-1,2-propanediol degradation); P124-PWY (Bifidobacterium shunt); P122-PWY (heterolactic fermentation); REDCITCYC (TCA cycle VIII (helicobacter)); DENOVOPURINE2-PWY (superpathway of purine nucleotides de novo biosynthesis II); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GALACTARDEG-PWY (D-galactarate degradation I); PWY-6891 (thiazole biosynthesis II (Bacillus)); FUC-RHAMCAT-PWY (superpathway of fucose and rhamnose degradation); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-41 (allantoin degradation IV (anacrobic)); VALDEG-PWY (L-valine degradation I); PWY-7187 (pyrimidine deoxyribonucleotides de novo biosynthesis II); PWY0-1533 (methylphosphonate degradation I); and GLUCARDEG-PWY (D-glucarate degradation I), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 100) The method of aspect 98, wherein a decrease in relative abundance of at least one of: TYRFUMCAT-PWY (L-tyrosine degradation I); PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7094 (fatty acid salvage); and LEU-DEG2-PWY (L-leucine degradation I), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 101) The method of aspect 98-100, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 102) The method of aspect 90, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); DTDPRHAMSYN-PWY (dTDP-L-rhamnose biosynthesis I); GLUCONEO-PWY (gluconcogenesis I); PWY-7222 (guanosine deoxyribonucleotides de novo biosynthesis II); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PENTOSE-P-PWY (pentose phosphate pathway); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-6901 (superpathway of glucose and xylose degradation); PWY-5659 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-7456 (mannan degradation); VALDEG-PWY (L-valine degradation I); ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); TCA (TCA cycle I (prokaryotic)); FASYN-ELONG-PWY (fatty acid elongation-saturated); PWY-6703 (preQ0 biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); P42-PWY (incomplete reductive TCA cycle); PWY-5913 (TCA cycle VI (obligate autotrophs)); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); P163-PWY (L-lysine fermentation to acetate and butanoate); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); PWY-7242 (D-fructuronate degradation); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6572 (chondroitin sulfate degradation I (bacterial)); and PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 103) The method of aspect 102, wherein an increase in relative abundance of at least one of: PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); DTDPRHAMSYN-PWY (dTDP-L-rhamnose biosynthesis I); GLUCONEO-PWY (gluconcogenesis I); PWY-7222 (guanosine deoxyribonucleotides de novo biosynthesis II); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PENTOSE-P-PWY (pentose phosphate pathway); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-6901 (superpathway of glucose and xylose degradation); PWY-5659 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-7456 (mannan degradation); VALDEG-PWY (L-valine degradation I); ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); TCA (TCA cycle I (prokaryotic)); FASYN-ELONG-PWY (fatty acid elongation-saturated); PWY-6703 (preQ0 biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); P42-PWY (incomplete reductive TCA cycle); PWY-5913 (TCA cycle VI (obligate autotrophs)); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); P163-PWY (L-lysine fermentation to acetate and butanoate); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); PWY-7242 (D-fructuronate degradation); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6572 (chondroitin sulfate degradation I (bacterial)); and PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation), is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 104) The method of any one of aspects 102-103, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 105) The method of aspect 90, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: HEMESYN2-PWY (heme biosynthesis II (anaerobic)); PWY-6608 (guanosine nucleotides degradation III); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); GALACTARDEG-PWY (D-galactarate degradation I); PWY-7013 (L-1,2-propanediol degradation); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); PWY-6353 (purine nucleotides degradation II (acrobic)); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLUCARDEG-PWY (D-glucarate degradation I); PENTOSE-P-PWY (pentose phosphate pathway); PWY-6891 (thiazole biosynthesis II (Bacillus)); HISDEG-PWY (L-histidine degradation I); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7237 (myo-, chiro- and scillo-inositol degradation); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY-6588 (pyruvate fermentation to acetone); PWY0-1533 (methylphosphonate degradation I); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-41 (allantoin degradation IV (anaerobic)); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); PWY-5705 (allantoin degradation to glyoxylate III); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); and METHGLYUT-PWY (superpathway of methylglyoxal degradation); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 106) The method of aspect 105, wherein an increase in relative abundance of at least one of: HEMESYN2-PWY (heme biosynthesis II (anaerobic)); PWY-6608 (guanosine nucleotides degradation III); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); GALACTARDEG-PWY (D-galactarate degradation I); PWY-7013 (L-1,2-propanediol degradation); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); PWY-6353 (purine nucleotides degradation II (aerobic)); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLUCARDEG-PWY (D-glucarate degradation I); PENTOSE-P-PWY (pentose phosphate pathway); PWY-6891 (thiazole biosynthesis II (Bacillus)); HISDEG-PWY (L-histidine degradation I); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7237 (myo-, chiro- and scillo-inositol degradation); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY-6588 (pyruvate fermentation to acetone); PWY0-1533 (methylphosphonate degradation I); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-41 (allantoin degradation IV (anacrobic)); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); PWY-5705 (allantoin degradation to glyoxylate III); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); and METHGLYUT-PWY (superpathway of methylglyoxal degradation), is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 107) The method of any one of aspects 105-106, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 108) The method of aspect 90, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBD UC gut microbiome, of at least one of: ECASYN-PWY (enterobacterial common antigen biosynthesis); PPGPPMET-PWY (ppGpp biosynthesis); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithine degradation); AST-PWY (L-arginine degradation II (AST pathway)); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); ORNDEG-PWY (superpathway of ornithine degradation); PWY0-1338 (polymyxin resistance); PWY-5028 (L-histidine degradation II); AEROBACTINSYN-PWY (acrobactin biosynthesis); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-321 (phenylacetate degradation I (aerobic)); PWY0-1533 (methylphosphonate degradation I); P241-PWY (coenzyme B biosynthesis); PWY-6148 (tetrahydromethanopterin biosynthesis); PWY-6349 (CDP-archacol biosynthesis); PWY-6654 (phosphopantothenate biosynthesis III); METHANOGENESIS-PWY (methanogenesis from H2 and CO2); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5198 (factor 420 biosynthesis); PWY-6167 (flavin biosynthesis II (archaca)); PWY-6641 (superpathway of sulfolactate degradation); PWY-6350 (archactidylinositol biosynthesis); PWY-6141 (archactidylserine and archaetidylethanolamine biosynthesis); PWY-6174 (mevalonate pathway II (archaca)); P261-PWY (coenzyme M biosynthesis I); and PWY-7391 (isoprene biosynthesis II (engineered)); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 109) The method of aspect 108, wherein an increase in relative abundance of at least one of: ECASYN-PWY (enterobacterial common antigen biosynthesis); PPGPPMET-PWY (ppGpp biosynthesis); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithine degradation); AST-PWY (L-arginine degradation II (AST pathway)); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); ORNDEG-PWY (superpathway of ornithinc degradation); PWY0-1338 (polymyxin resistance); PWY-5028 (L-histidine degradation II); AEROBACTINSYN-PWY (acrobactin biosynthesis); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-321 (phenylacetate degradation I (acrobic)); and PWY0-1533 (methylphosphonate degradation I), is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 110) The method of aspect 108, wherein a decrease in relative abundance of at least one of: P241-PWY (coenzyme B biosynthesis); PWY-6148 (tetrahydromethanopterin biosynthesis); PWY-6349 (CDP-archacol biosynthesis); PWY-6654 (phosphopantothenate biosynthesis III); METHANOGENESIS-PWY (methanogenesis from H2 and CO2); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5198 (factor 420 biosynthesis); PWY-6167 (flavin biosynthesis II (archaca)); PWY-6641 (superpathway of sulfolactate degradation); PWY-6350 (archaetidylinositol biosynthesis); PWY-6141 (archaetidylserine and archactidylethanolamine biosynthesis); PWY-6174 (mevalonate pathway II (archaca)); P261-PWY (coenzyme M biosynthesis I); and PWY-7391 (isoprene biosynthesis II (engineered)), is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 111) The method of any one of aspects 108-110, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 112) The method of aspect 70, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of: P221-PWY (octane oxidation); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); PWY-6263 (superpathway of menaquinol-8 biosynthesis II); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); PWY-5198 (factor 420 biosynthesis); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5531 (chlorophyllide a biosynthesis II (anaerobic)); PWY-6349 (CDP-archacol biosynthesis); PWY-5088 (L-glutamate degradation VIII (to propanoate)); PWY-6350 (archactidylinositol biosynthesis); PWY-7159 (chlorophyllide a biosynthesis III (aerobic, light independent)); PWY0-1533 (methylphosphonate degradation I); ORNDEG-PWY (superpathway of ornithine degradation); PWY0-1338 (polymyxin resistance); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithine degradation); ECASYN-PWY (enterobacterial common antigen biosynthesis); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); GLYCOL-GLYOXDEG-PWY (superpathway of glycol metabolism and degradation); ENTBACSYN-PWY (enterobactin biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-1277 (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 113) The method of aspect 112, wherein an increase in relative abundance of at least one of: P221-PWY (octane oxidation); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); PWY-6263 (superpathway of menaquinol-8 biosynthesis II); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); PWY-5198 (factor 420 biosynthesis); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5531 (chlorophyllide a biosynthesis II (anaerobic)); PWY-6349 (CDP-archacol biosynthesis); PWY-5088 (L-glutamate degradation VIII (to propanoate)); PWY-6350 (archactidylinositol biosynthesis); and PWY-7159 (chlorophyllide a biosynthesis III (aerobic, light independent)), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 114) The method of aspect 112, wherein a decrease in relative abundance of at least one of: PWY0-1533 (methylphosphonate degradation I); ORNDEG-PWY (superpathway of ornithinc degradation); PWY0-1338 (polymyxin resistance); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithine degradation); ECASYN-PWY (enterobacterial common antigen biosynthesis); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); GLYCOL-GLYOXDEG-PWY (superpathway of glycol metabolism and degradation); ENTBACSYN-PWY (enterobactin biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-1277 (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 115) The method of aspect 112-114, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 116) The method of aspect 70, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of the pathways identified in Table 3 as being upregulated greater than 5 fold; wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 117) The method of aspect 116, wherein an increase in relative abundance of at least one of: PWY-6151 (S-adenosyl-L-methionine cycle I); P221-PWY (octane oxidation); PWY-5505 (L-glutamate and L-glutamine biosynthesis); PWY-5121 (superpathway of geranylgeranyl diphosphate biosynthesis II (via MEP)); GLYCOGENSYNTH-PWY (glycogen biosynthesis I (from ADP-D-Glucose)); NONMEVIPP-PWY (methylerythritol phosphate pathway I); PWY-6269 (adenosylcobalamin salvage from cobinamide II); PYRIDNUCSYN-PWY (NAD biosynthesis I (from aspartate)); COA-PWY (coenzyme A biosynthesis I); PWY-5686 (UMP biosynthesis); PWY-7560 (methylerythritol phosphate pathway II); PWY-6386 (UDP-N-acetylmuramoyl-pentapeptide biosynthesis II (lysine-containing)); PWY-6277 (superpathway of 5-aminoimidazole ribonucleotide biosynthesis); PWY-5509 (adenosylcobalamin biosynthesis from cobyrinate a,c-diamide I); PWY-7219 (adenosine ribonucleotides de novo biosynthesis); COBALSYN-PWY (adenosylcobalamin salvage from cobinamide I); PWY-6163 (chorismate biosynthesis from 3-dehydroquinate); PWY-6123 (inosine-5′-phosphate biosynthesis I); GLYCOCAT-PWY (glycogen degradation I (bacterial)); ARO-PWY (chorismate biosynthesis I); PWY-6317 (galactose degradation I (Leloir pathway)); PWY-5097 (L-lysine biosynthesis VI); PWY-6385 (peptidoglycan biosynthesis III (mycobacteria)); COMPLETE-ARO-PWY (superpathway of aromatic amino acid biosynthesis); PWY-6892 (thiazole biosynthesis I (E. coli)); PEPTIDOGLYCANSYN-PWY (peptidoglycan biosynthesis I (meso-diaminopimelate containing)); PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II); PYRIDNUCSAL-PWY (NAD salvage pathway I); PWY-5667 (CDP-diacylglycerol biosynthesis I); PWY-6387 (UDP-N-acetylmuramoyl-pentapeptide biosynthesis I (meso-diaminopimelate containing)); TRNA-CHARGING-PWY (IRNA charging); PWY-5100 (pyruvate fermentation to acetate and lactate II); PWY-7663 (gondoate biosynthesis (anaerobic)); PWY-5104 (L-isoleucine biosynthesis IV); PWY-5973 (cis-vaccenate biosynthesis); PWY0-1319 (CDP-diacylglycerol biosynthesis II); PWY-7221 (guanosine ribonucleotides de novo biosynthesis); PWY4FS-8 (phosphatidylglycerol biosynthesis II (non-plastidic)); PWY-6737 (starch degradation V); PWY-3001 (superpathway of L-isoleucine biosynthesis I); HISTSYN-PWY (L-histidine biosynthesis); PWY-7208 (superpathway of pyrimidine nucleobases salvage); PHOSLIPSYN-PWY (superpathway of phospholipid biosynthesis I (bacteria)); PWY-6121 (5-aminoimidazole ribonucleotide biosynthesis I); PWY-2942 (L-lysine biosynthesis III); SER-GLYSYN-PWY (superpathway of L-serine and glycine biosynthesis I); AEROBACTINSYN-PWY (acrobactin biosynthesis); PWY-6126 (superpathway of adenosine nucleotides de novo biosynthesis II); DAPLYSINESYN-PWY (L-lysine biosynthesis I); NONOXIPENT-PWY (pentose phosphate pathway (non-oxidative branch)); BRANCHED-CHAIN-AA-SYN-PWY (superpathway of branched amino acid biosynthesis); PWY-7229 (superpathway of adenosine nucleotides de novo biosynthesis I); ARGSYNBSUB-PWY (L-arginine biosynthesis II (acetyl cycle)); VALSYN-PWY (L-valine biosynthesis); ILEUSYN-PWY (L-isoleucine biosynthesis I (from threonine)); 1CMET2-PWY (N10-formyl-tetrahydrofolate biosynthesis); GALLATE-DEGRADATION-II-PWY (gallate degradation I); 3-HYDROXYPHENYLACETATE-DEGRADATION-PWY (4-hydroxyphenylacetate degradation); METHYLGALLATE-DEGRADATION-PWY (methylgallate degradation); PWY-7400 (L-arginine biosynthesis IV (archaebacteria)); THRESYN-PWY (superpathway of L-threonine biosynthesis); DENOVOPURINE2-PWY (superpathway of purine nucleotides de novo biosynthesis II); ARGSYN-PWY (L-arginine biosynthesis I (via L-ornithine)); PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP); PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV); POLYAMINSYN3-PWY (superpathway of polyamine biosynthesis II); PWY4FS-7 (phosphatidylglycerol biosynthesis I (plastidic)); PWY0-166 (superpathway of pyrimidine deoxyribonucleotides de novo biosynthesis (E. coli)); GALLATE-DEGRADATION-I-PWY (gallate degradation II); CALVIN-PWY (Calvin-Benson-Bassham cycle); PANTOSYN-PWY (pantothenate and coenzyme A biosynthesis I); PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-7184 (pyrimidine deoxyribonucleotides de novo biosynthesis I); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); and POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 118) The method of any one of aspects 116-117, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 119) The method of aspect 70, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining relative changes in abundance, compared to a reference gut microbiome, in at least one of: AST-PWY (L-arginine degradation II (AST pathway)); ECASYN-PWY (enterobacterial common antigen biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); PPGPPMET-PWY (ppGpp biosynthesis); PWY0-1338 (polymyxin resistance); PWY-6263 (superpathway of menaquinol-8 biosynthesis II); PWY-7371 (1,4-dihydroxy-6-naphthoate biosynthesis II); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); P221-PWY (octane oxidation); PWY-6749 (CMP-legionaminate biosynthesis I); PWY-7456 (mannan degradation); NONMEVIPP-PWY (methylerythritol phosphate pathway I); PWY-5097 (L-lysine biosynthesis VI); PWY-5505 (L-glutamate and L-glutamine biosynthesis); PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II); PWY-7663 (gondoate biosynthesis (anaerobic)); THRESYN-PWY (superpathway of L-threonine biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); PWY-5304 (superpathway of sulfur oxidation (archaca); PWY-6478 (GDP-D-glycero-alpha-D-manno-heptose biosynthesis); PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV); and PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP); wherein increased abundance of at least one of AST-PWY (L-arginine degradation II (AST pathway)); ECASYN-PWY (enterobacterial common antigen biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); PPGPPMET-PWY (ppGpp biosynthesis); and PWY0-1338 (polymyxin resistance) is associated with CDI causative diarrhea and the individual is treated accordingly; wherein increased abundance of at least one of PWY-6263 (superpathway of menaquinol-8 biosynthesis II); PWY-7371 (1,4-dihydroxy-6-naphthoate biosynthesis II); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); P221-PWY (octane oxidation); PWY-6749 (CMP-legionaminate biosynthesis I); and PWY-7456 (mannan degradation) is associated with IBD UC causative diarrhea and the individual is treated accordingly; and wherein increased abundance of at least one of NONMEVIPP-PWY (methylerythritol phosphate pathway I); PWY-5097 (L-lysine biosynthesis VI); PWY-5505 (L-glutamate and L-glutamine biosynthesis); PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II); PWY-7663 (gondoate biosynthesis (anaerobic)); THRESYN-PWY (superpathway of L-threonine biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); PWY-5304 (superpathway of sulfur oxidation (archaca); PWY-6478 (GDP-D-glycero-alpha-D-manno-heptose biosynthesis); PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV); and PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP) is associated with IBD causative diarrhea and the individual is treated accordingly.
- Aspect 120) A method of diagnosing an individual having diarrhea comprising: measuring for presence or absence or a certain level of one or more taxonomical feature(s) from a biological sample from the individual; and classifying the individual as having a CDI associated pathogenic infection, irritable bowel syndrome (IBS), or inflammatory bowel disease (IBD).
- Aspect 121) The method of any one of aspects 120, wherein the diagnosis is characterized by measuring the presence, absence, and/or relative quantity of at least 10 taxonomical features described in any one of Tables 9-17.
- Aspect 122) The method of aspect 120, wherein the diagnosis is characterized by measuring the presence, absence, and/or relative quantity of at least 20 taxonomical features described in any one of Tables 9-17.
- Aspect 123) The method of aspect 120, wherein the diagnosis is characterized by measuring the presence, absence, and/or relative quantity of at least 40 taxonomical features described in any one of Tables 9-17.
- Aspect 124) The method of aspect 120, wherein the diagnosis is characterized by measuring the presence, absence, and/or relative quantity of at least 60 taxonomical features described in any one of Tables 9-17.
- Aspect 125) The method of aspect 120, wherein the diagnosis is characterized by measuring the presence, absence, and/or relative quantity of at least 80 taxonomical features described in any one of Tables 9-17.
- Aspect 126) The method of aspect 120, wherein diagnosis is characterized by measuring the presence, absence, and/or relative quantity of at least 100 taxonomical features described in any one Tables 9-17.
- Aspect 127) The method of any one of aspects 121-126, wherein the diagnosis comprises characterization using more than one of Tables 9-17.
- Aspect 128) The method of aspect 127, wherein the more than one characterization using Tables 9-17 is sequential.
- Aspect 129) The method of aspect 127 or 128, wherein the more than one characterization using Tables 9-17 comprises first characterizing using Tables 10 and/or 12, followed by characterization using one or more of the remaining Tables.
- Aspect 130) The method of any one of aspects 120-129, wherein the measuring of one or more taxonomical features comprises at least one of analyzing one or more nucleic acids in the sample, analyzing one or more metabolites in the sample, and analyzing one or more proteins in the sample.
- Aspect 131) The method of aspect 130, wherein the nucleic acid is analyzed by sequencing, polymerase chain reaction, isothermal amplification, bioinformatics, or any combination thereof.
- Aspect 132) The method of aspect 131, wherein the nucleic acid analyzed is 16S ribosomal RNA.
- Aspect 133) The method of aspect 130, wherein the metabolites are analyzed by mass spectrometry, ELISA, chromatography, or any combination thereof.
- Aspect 134) The method of aspect 130, wherein the proteins are analyzed by mass spectrometry, ELISA, chromatography, Western blotting, immunoprecipitation, immunoelectrophoresis, or any combination thereof.
- Aspect 135) The method of any one of aspects 120-134, wherein the diagnosis is indicative of non-CDI causative diarrhea, the subject microbiome is further characterized to determine whether the non-CDI causative diarrhea is associated with irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD),
- Aspect 136) The method of aspect 135, wherein the non-CDI causative diarrhea is associated with IBD, the IBD is further characterized to determine whether the IBD is Ulcerative Colitis (UC) or Crohn's Disease (CD).
- Aspect 137) The method of aspect 120, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Sphingobacteriaceae Pedobacter; Saccharibacteria Incertae Sedis; Peptostreptococcaceae Intestinibacter; Bacillales Incertae Sedis Gemella; Veillonella infantium; Chloroplast Streptophyta; Caulobacter segnis; Methylophilaceae Methylophilus; Lactobacillus Streptococcaceae; Burkholderiales Comamonadaceae; Burkholderia ambifaria; Caulobacteraceae Caulobacter; Betaproteobacteria; Phyllobacteriaceae Phyllobacterium; Burkholderiales Burkholderiaceae; Sphingomonadaceae; Sphingomonas; Prevotellamassilia timonensis; Collinsella aerofaciens; Adlercreutzia equolifaciens; Blautia hominis; and Dorea formicigenerans; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 138) The method of aspect 137, wherein an increase in relative abundance of at least one of: Sphingobacteriaceae Pedobacter; Saccharibacteria Incertae Sedis; Peptostreptococcaceae Intestinibacter; Bacillales Incertae Sedis Gemella; Veillonella infantium; Chloroplast Streptophyta; Caulobacter segnis; Methylophilaceae Methylophilus; Lactobacillus Streptococcaceae; Burkholderiales Comamonadaceae; Burkholderia ambifaria; Caulobacteraceae Caulobacter; Betaproteobacteria; Phyllobacteriaceae Phyllobacterium; Burkholderiales Burkholderiaceae; Sphingomonadaceae; Sphingomonas; and Prevotellamassilia timonensis, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 139) The method of aspect 137, wherein a decrease in relative abundance of at least one of: Collinsella acrofaciens; Adlercreutzia equolifaciens; Blautia hominis; and Dorea formicigenerans, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 140) The method of aspect 137-139, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 141) The method of aspect 120, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Acidaminococcaceae Acidaminococcus; Actinomycetales Actinomycetaceae; Bacillales Gemella; Bacilli Lactobacillus; Betaproteobacteria; Betaproteobacteria Burkholderiales; Bifidobacterium boum; Blautia hominis; Clostridiales Incertae Sedis XI Parvimonas; Enterobacteriaceae Cedecea; Erysipelotrichaceae Faecalicoccus; Faecalimonas umbilicata; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Gammaproteobacteria Enterobacterales; Lachnoclostridium [Clostridium] bolteae; Lachnospiraceae Lachnoclostridium; Megasphaera micronuciformis; Peptoniphilaceae Peptoniphilus; Peptostreptococcaceae Peptostreptococcus; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Terrisporobacter; Proteobacteria Gammaproteobacteria; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Ruminococcaceae Intestinimonas; Ruminococcaceae Subdoligranulum; Solobacterium moorei; Veillonellaceae Veillonella; Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides koreensis; Bacteroides thetaiotaomicron; Bacteroides xylanisolvens; Colidextribacter massiliensis; Coprococcus catus; Coprococcus eutactus; Enterobacterales Enterobacteriaceae; Faecalibacterium prausnitzii; Methanobrevibacter smithii; Phascolarctobacterium faecium; Romboutsia timonensis; and Turicibacter sanguinis; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 142) The method of aspect 141, wherein an increase in relative abundance of at least one of: Acidaminococcaceae Acidaminococcus; Actinomycetales Actinomycetaceae; Bacillales Gemella; Bacilli Lactobacilluses; Betaproteobacteria; Betaproteobacteria Burkholderiales; Bifidobacterium boum; Blautia hominis; Clostridiales Incertae Sedis XI Parvimonas; Enterobacteriaceae Cedecea; Erysipelotrichaceae Faecalicoccus; Faecalimonas umbilicata; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Gammaproteobacteria Enterobacterales; Lachnoclostridium [Clostridium] bolteae; Lachnospiraceae Lachnoclostridium; Megasphaera micronuciformis; Peptoniphilaceae Peptoniphilus; Peptostreptococcaceae Peptostreptococcus; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Terrisporobacter; Proteobacteria Gammaproteobacteria; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Ruminococcaceae Intestinimonas; Ruminococcaceae Subdoligranulum; Solobacterium moorei; and Veillonellaceae Veillonella, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 143) The method of aspect 141, wherein a decrease in relative abundance of at least one of: Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides koreensis; Bacteroides thetaiotaomicron; Bacteroides xylanisolvens; Colidextribacter massiliensis; Coprococcus catus; Coprococcus eutactus; Enterobacterales Enterobacteriaceae; Faecalibacterium prausnitzii; Methanobrevibacter smithii; Phascolarctobacterium faecium; Romboutsia timonensis; and Turicibacter sanguinis, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 144) The method of aspect 141-143, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 145) The method of aspect 120, wherein the individual is a pediatric individual, and wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy pediatric gut microbiome, of at least one of: Bacilli Lactobacilluses; Peptostreptococcaceae Clostridioides; Enterococcaceae Enterococcus; Eggerthellaceae Eggerthella; Erysipelotrichaceae Erysipelatoclostridium; Lachnospiraceae Lachnoclostridium; Firmicutes Bacilli; Enterobacteriaceae Escherichia; Enterobacteriales Enterobacteriaceae; Streptococcaceae Streptococcus; Actinomycetaceae Schaalia; Clostridiaceae Hungatella; Clostridiaceae Clostridium; Corynebacteriaceae Corynebacterium; Veillonellaceae Veillonella; Actinomycetaceae Actinomyces; Fusobacteriaceae Fusobacterium; Erysipelotrichaceae Longicatena; Lachnospiraceae Clostridium XlVa; Lachnospiraceae Eisenbergiella; Peptostreptococcaceae Intestinibacter; Enterobacteriaceae Citrobacter; Peptoniphilaceae Finegoldia; Carnobacteriaceae Granulicatella; Coriobacteriaceae Eggerthella; Peptostreptococcaceae Peptostreptococcus; Drancourtella massiliensis; Peptoniphilaceae Anaerococcus; Bacillales Gemella; Lachnospiraceae Sellimonas; Peptoniphilaceae Peptoniphilus; Pasteurellaceae Rodentibacter; Clostridium sensu stricto; Lachnospiraceae Faecalimonas; Proteobacteria Gammaproteobacteria; Clostridiaceae Lactonifactor; Micrococcaceae Rothia; Leuconostocaceae Weissella; Peptostreptococcaceae Terrisporobacter; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Clostridium XI; Coriobacteriaceae Atopobium; Atopobiaceae Atopobium; Anaeromassilibacillus; Ruminococcaceae Porphyromonadaceae Parabacteroides; Rikenellaceae Alistipes; Lachnospiraceae Eubacterium rectale group; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Porphyromonadacede Odoribacter; Veillonellaceae Dialister; Ruminococcaceae Clostridium IV; Bacteroidia Bacteroidales; Coriobacteriaceae Collinsella; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Clostridium leptum group; Enterobacteriaceae Shimwellia; Acidaminococcaceae Phascolarctobacterium; Staphylococcaceae Staphylococcus; Lachnospiraceae Anaerobutyricum; Erysipelotrichaceae Holdemania; Clostridiales Monoglobus; Porphyromonadaceae Barnesiella; Pasteurellales Pasteurellaceae; Clostridiales Clostridiaceae 1; and Bacteroidales Rikenellaceae; wherein the change in taxonomical feature relative abundance is indicative of CDI associated diarrhea.
- Aspect 146) The method of aspect 145, wherein an increase in relative abundance of at least one of: Bacilli Lactobacillus; Peptostreptococcaceae Clostridioides; Enterococcaceae Enterococcus; Eggerthellaceae Eggerthella; Erysipelotrichaceae Erysipelatoclostridium; Lachnospiraceae Lachnoclostridium; Firmicutes Bacilli; Enterobacteriaceae Escherichia; Enterobacteriales Enterobacteriaceae; Streptococcus; Actinomycetaceae Streptococcaceae Schaalia; Clostridiaceae Hungatella; Clostridiaceae Clostridium; Corynebacteriaceae Corynebacterium; Veillonellaceae Veillonella; Actinomycetaceae Actinomyces; Fusobacteriaceae Fusobacterium; Erysipelotrichaceae Longicatena; Lachnospiraceae Clostridium XIVa; Lachnospiraceae Eisenbergiella; Peptostreptococcaceae Intestinibacter; Enterobacteriaceae Citrobacter; Peptoniphilaceae Finegoldia; Carnobacteriaceae Granulicatella; Coriobacteriaceae Eggerthella; Peptostreptococcaceae Peptostreptococcus; Drancourtella massiliensis; Peptoniphilaceae Anaerococcus; Bacillales Gemella; Lachnospiraceae Sellimonas; Peptoniphilaceae Peptoniphilus; Pasteurellaceae Rodentibacter; Clostridium sensu stricto; Lachnospiraceae Faecalimonas; Proteobacteria Gammaproteobacteria; Clostridiaceae Lactonifactor; Micrococcaceae Rothia; Leuconostocaceae Weissella; Peptostreptococcaceae Terrisporobacter; Peptostreptococcaceae Romboutsia; Peptostreptococcaceae Clostridium XI; Coriobacteriaceae Atopobium; Atopobiaceae Atopobium; and Ruminococcaceae Anaeromassilibacillus, is indicative of CDI associated diarrhea.
- Aspect 147) The method of aspect 145, wherein a decrease in relative abundance of at least one of: Porphyromonadaceae Parabacteroides; Rikenellaceae Alistipes; Lachnospiraceae Eubacterium rectale group; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Porphyromonadacede Odoribacter; Veillonellaceae Dialister; Ruminococcaceae Clostridium IV; Bacteroidia Bacteroidales; Coriobacteriaceae Collinsella; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Clostridium leptum group; Enterobacteriaceae Shimwellia; Acidaminococcaceae Phascolarctobacterium; Staphylococcaceae Staphylococcus; Lachnospiraceae Anaerobutyricum; Erysipelotrichaceae Holdemania; Clostridiales Monoglobus; Porphyromonadacede Barnesiella; Pasteurellales Pasteurellaceae; Clostridiales Clostridiaceae 1; and Bacteroidales Rikenellaceae, is indicative of CDI associated diarrhea.
- Aspect 148) The method of aspect 145-147, wherein a change in relative abundance of at least four taxonomical features is indicative of CDI associated diarrhea.
- Aspect 149) The method of aspect 135, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBS or IBD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBD gut microbiome, of at least one of: Blautia stercoris; Saccharibacteria Incertae Sedis; Bacteroides plebeius; Bacteroides nordii; Eubacterium siraeum; Bacteroides cellulosilyticus; Burkholderiales Burkholderiaceae; Caulobacteraceae Caulobacter; Pelomonas aquatic; Burkholderiaceae Burkholderia; Caulobacter segnis; Burkholderia ambifaria; Eubacterium ventriosum; Firmicutes Clostridia; Oxalobacter formigenes; Burkholderiales Comamonadaceae; Veillonella infantium; Bacteroides thetaiotaomicron; Sphingobacteriaceae Pedobacter; Burkholderia thailandensis; Erysipelotrichaceae Turicibacter; Collinsella aerofaciens; Veillonellaceae Veillonella; Lachnospiraceae Lachnoclostridium; Blautia hominis; Gammaproteobacteria Enterobacterales; Bifidobacteriales Bifidobacteriaceae; Ruminococcaceae Intestinimonas; Faecalimonas umbilicata; Actinomycetales Actinomycetaceae; Actinobacteria Actinobacteria; Dorea formicigenerans; and Bacteria Proteobacteria; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 150) The method of aspect 149, wherein an increase in relative abundance of at least one of: Saccharibacteria Incertae Sedis; Bacteroides plebeius; Bacteroides nordii; Eubacterium siraeum; Bacteroides cellulosilyticus; Burkholderiales Burkholderiaceae; Caulobacteraceae Caulobacter; Pelomonas aquatic; Burkholderiaceae Burkholderia; Caulobacter segnis; Burkholderia ambifaria; Eubacterium ventriosum; Firmicutes Clostridia; Oxalobacter formigenes; Burkholderiales Comamonadaceae; Veillonella infantium; Bacteroides thetaiotaomicron; Sphingobacteriaceae Pedobacter; Burkholderia thailandensis; and Erysipelotrichaceae Turicibacter, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 151) The method of aspect 149, wherein a decrease in relative abundance of at least one of: Collinsella aerofaciens; Veillonellaceae Veillonella; Lachnospiraceae Lachnoclostridium; Blautia hominis; Gammaproteobacteria Enterobacterales; Bifidobacteriales Bifidobacteriaceae; Ruminococcaceae Intestinimonas; Faecalimonas umbilicata; Actinomycetales Actinomycetaceae; Actinobacteria Actinobacteria; Dorea formicigenerans; and Bacteria Proteobacteria, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 152) The method of aspect 149-151, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 153) The method of aspect 136, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Lachnospiraceae Lachnoclostridium; Ruminococcaceae Intestinimonas; Acidaminococcaceae Acidaminococcus; Bacilli Lactobacillus; Actinomycetales Actinomycetaceae; Ruminococcaceae Subdoligranulum; Peptostreptococcaceae Romboutsia; Bifidobacterium boum; Bacillales Gemella; Peptostreptococcaceae Peptostreptococcus; Peptoniphilaceae Peptoniphilus; Clostridiales Incertae Sedis XI Parvimonas; Peptostreptococcaceae Terrisporobacter; Erysipelotrichaceae Faecalicoccus; Solobacterium moorei; Bacteroides xylanisolvens; Enterobacterales Enterobacteriaceae; Bacteroides koreensis; Bacteroides cellulosilyticus; Phascolarctobacterium faecium; and Bacteroides thetaiotaomicron; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 154) The method of aspect 153, wherein an increase in relative abundance of at least one of: Lachnospiraceae Lachnoclostridium; Ruminococcaceae Intestinimonas; Acidaminococcaceae Acidaminococcus; Bacilli Lactobacilluses; Actinomycetales Actinomycetaceae; Ruminococcaceae Subdoligranulum; Peptostreptococcaceae Romboutsia; Bifidobacterium boum; Bacillales Gemella; Peptostreptococcaceae Peptostreptococcus; Peptoniphilaceae Peptoniphilus; Clostridiales Incertae Sedis XI Parvimonas; Peptostreptococcaceae Terrisporobacter; Erysipelotrichaceae Faecalicoccus; and Solobacterium moorei, is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 155) The method of aspect 153, wherein a decrease in relative abundance of at least one of: Bacteroides xylanisolvens; Enterobacterales Enterobacteriaceae; Bacteroides koreensis; Bacteroides cellulosilyticus; Phascolarctobacterium faecium; and Bacteroides thetaiotaomicron, is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 156) The method of aspect 153-155, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 157) The method of aspect 136, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: Faecalimonas umbilicata; Lachnospiraceae Lachnoclostridium; Lachnoclostridium [Clostridium] bolteae; Proteobacteria Gammaproteobacteria; Bacilli Lactobacillus; Actinomycetales Actinomycetaceae; Gammaproteobacteria Enterobacterales; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Veillonellaceae Veillonella; Acidaminococcaceae Acidaminococcus; Blautia hominis; Bifidobacterium boum; Enterobacteriaceae Cedecea; Ruminococcaceae Intestinimonas; Peptostreptococcaceae Romboutsia; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Megasphaera micronuciformis; Romboutsia timonensis; Faecalibacterium prausnitzii; Coprococcus catus; Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides thetaiotaomicron; Coprococcus eutactus; Turicibacter sanguinis; Colidextribacter massiliensis; and Methanobrevibacter smithii; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 158) The method of aspect 157, wherein an increase in relative abundance of at least one of: Faecalimonas umbilicata; Lachnospiraceae Lachnoclostridium; Lachnoclostridium [Clostridium] bolteae; Proteobacteria Gammaproteobacteria; Bacilli Lactobacillus; Actinomycetales Actinomycetaceae; Gammaproteobacteria Enterobacterales; Rosenbergiella collisarenosi; Rosenbergiella nectarea; Veillonellaceae Veillonella; Acidaminococcaceae Acidaminococcus; Blautia hominis; Bifidobacterium boum; Enterobacteriaceae Cedecea; Ruminococcaceae Intestinimonas; Peptostreptococcaceae Romboutsia; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; and Megasphaera micronuciformis, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 159) The method of aspect 157, wherein a decrease in relative abundance of at least one of: Romboutsia timonensis; Faecalibacterium prausnitzii; Coprococcus catus; Alistipes shahii; Bacteroides cellulosilyticus; Bacteroides thetaiotaomicron; Coprococcus eutactus; Turicibacter sanguinis; Colidextribacter massiliensis; and Methanobrevibacter smithii, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 160) The method of aspect 157-159, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 161) The method of aspect 136, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more taxonomical features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBD UC gut microbiome, of at least one of: Faecalimonas umbilicata; Blautia [Ruminococcus] gnavus; Lachnoclostridium [Clostridium] boltede; Erysipelatoclostridium ramosum; Veillonellaceae Veillonella; Enterobacterales Enterobacteriaceae; Blautia caecimuris; Fusobacteriaceae Fusobacterium; Fusobacterium nucleatum; Faecalibacterium prausnitzii; Ruminococcaceae Oscillibacter; Ruminococcaceae Clostridium IV; Romboutsia timonensis; Ruminococcaceae Pseudoflavonifractor; Erysipelotrichales Erysipelotrichaceae; and Methanobacteriaceae Methanobrevibacter; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 162) The method of aspect 161, wherein an increase in relative abundance of at least one of: Faecalimonas umbilicata; Blautia [Ruminococcus] gnavus; Lachnoclostridium [Clostridium] boltede; Erysipelatoclostridium ramosum; Veillonellaceae Veillonella; Enterobacterales Enterobacteriaceae; Blautia caecimuris; Fusobacteriaceae Fusobacterium; and Fusobacterium nucleatum, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 163) The method of aspect 161, wherein a decrease in relative abundance of at least one of: Faecalibacterium prausnitzii; Ruminococcaceae Oscillibacter; Ruminococcaceae Clostridium IV; Romboutsia timonensis; Ruminococcaceae Pseudoflavonifractor; Erysipelotrichales Erysipelotrichaceae; and Methanobacteriaceae Methanobrevibacter, is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 164) The method of aspect 161-163, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 165) The method of aspect 120, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of: Anaerostipes hadrus; Faecalibacterium prausnitzii; Lachnospiraceae Coprococcus; Lachnospiraceae [Eubacterium] rectale; Lachnospiraceae Roseburia; Lachnospiraceae Fusicatenibacter; Lachnospiraceae Dorea; Ruminococcaceae Ruminococcus; Roseburia inulinivorans; Dorea longicatena; Roseburia intestinalis; Lachnospiraceae Anaerostipes; Coprococcus comes; Lactobacillus rogosae; Romboutsia timonensis; Saccharibacteria Incertae Sedis; Eubacterium [Eubacterium] eligens; Bacteroides plebeius; Lachnospiraceae Blautia; Roseburia faecis; Blautia obeum; Coprococcus catus; Betaproteobacteria Burkholderiales; Prevotella copri; Burkholderiales Burkholderiaceae; Caulobacter segnis; Caulobacterales Caulobacteraceae; Burkholderiaceae Burkholderia; Burkholderia ambifaria; Prevotellaceae Prevotella; Burkholderiales Comamonadaceae; Burkholderia thailandensis; Alistipes obesi; Blautia stercoris; Ruminococcus bromii; Pelomonas aquatica; Peptostreptococcaceae Romboutsia; Bacteroides coprocola; Streptococcus thermophilus; Ruminococcaceae Oscillibacter; Alistipes ihumii; Ruminococcus callidus; Phyllobacteriaceae Phyllobacterium; Coprococcus eutactus; Peptostreptococcaceae Intestinibacter; Clostridioides difficile; Enterobacterales Enterobacteriaceae; Enterococcaceae Enterococcus; Peptostreptococcaceae Clostridium XI; Gammaproteobacteria Enterobacterales; Bacilli Lactobacillus; Eggerthella lenta; Erysipelatoclostridium [Clostridium] innocuum; Enterobacteriaceae Citrobacter; Lachnospiraceae Clostridium XIVa; Lachnoclostridium [Clostridium] bolteae; Erysipelatoclostridium ramosum; Hungatella effluvia; Veillonella parvula; Lactobacilluseae Lactobacillus; Blautia [Ruminococcus] gnavus; Enterococcus saccharolyticus; and Coriobacteriaceae Eggerthella; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 166) The method of aspect 165, wherein an increase in relative abundance of at least one of: Anaerostipes hadrus; Faecalibacterium prausnitzii; Lachnospiraceae Coprococcus; Lachnospiraceae [Eubacterium] rectale; Lachnospiraceae Roseburia; Lachnospiraceae Fusicatenibacter; Lachnospiraceae Dorea; Ruminococcaceae Ruminococcus; Roseburia inulinivorans; Dorea longicatena; Roseburia intestinalis; Lachnospiraceae Anaerostipes; Coprococcus comes; Lactobacillus rogosae; Romboutsia timonensis; Saccharibacteria Incertae Sedis; Eubacterium [Eubacterium] eligens; Bacteroides plebeius; Lachnospiraceae Blautia; Roseburia faecis; Blautia obeum; Coprococcus catus; Betaproteobacteria Burkholderiales; Prevotella copri; Burkholderiales Burkholderiaceae; Caulobacter segnis; Caulobacterales Caulobacteraceae; Burkholderiaceae Burkholderia; Burkholderia ambifaria; Prevotellaceae Prevotella; Burkholderiales Comamonadaceae; Burkholderia thailandensis; Alistipes obesi; Blautia stercoris; Ruminococcus bromii; Pelomonas aquatica; Peptostreptococcaceae Romboutsia; Bacteroides coprocola; Streptococcus thermophilus; Ruminococcaceae Oscillibacter; Alistipes ihumii; Ruminococcus callidus; Phyllobacteriaceae Phyllobacterium; Coprococcus eutactus; and Peptostreptococcaceae Intestinibacter, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 167) The method of aspect 165, wherein a decrease in relative abundance of at least one of: Clostridioides difficile; Enterobacterales Enterobacteriaceae; Enterobacteriales Enterobacteriaceae; Enterococcaceae Enterococcus; Peptostreptococcaceae Clostridium XI; Gammaproteobacteria Enterobacterales; Bacilli Lactobacilluses; Eggerthella lenta; Erysipelatoclostridium [Clostridium] innocuum; Enterobacteriaceae Citrobacter; Lachnospiraceae Clostridium XIVa; Lachnoclostridium [Clostridium] bolteae; Erysipelatoclostridium ramosum; Hungatella effluvia; Veillonella parvula; Lactobacilluseae Lactobacillus; Blautia [Ruminococcus] gnavus; Enterococcus saccharolyticus; and Coriobacteriaceae Eggerthella, is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 168) The method of aspect 165-167, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 169) The method of aspect 120, wherein the measuring of one or more taxonomical features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of: Anaerostipes hadrus; Lachnospiraceae Dorea; Dorea longicatena; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Blautia obeum; Coprococcus comes; Roseburia intestinalis; Lactobacillus rogosae; Eubacterium [Eubacterium] eligens; Bacteroidia Bacteroidales; Peptostreptococcaceae Romboutsia; Coriobacteriaceae Collinsella; Acidaminococcaceae Acidaminococcus; Prevotellaceae Prevotella; Prevotella copri; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Ruminococcus; Alistipes obesi; Betaproteobacteria Burkholderiales; Ruminococcus bromii; Lachnospiraceae Lachnoclostridium; Bifidobacterium adolescentis; Actinomycetales Actinomycetaceae; Ruminococcaceae Intestinimonas; Bacteroides eggerthii; Clostridioides difficile; Peptostreptococcaceae Clostridium XI; Enterobacteriaceae Citrobacter; Enterobacterales Enterobacteriaceae; Veillonella parvula; Enterococcaceae Enterococcus; Lactobacillus Enterococcaceae; Erysipelatoclostridium [Clostridium] innocuum; Pectobacterium carotovorum; Enterobacteriales Enterobacteriaceae; Bacteroides xylanisolvens; Enterococcus saccharolyticus; Clostridium paraputrificum; Salmonella enterica; Erysipelatoclostridium ramosum; Hungatella effluvia; Bacteroides koreensis; Bacilli Lactobacillus; Blautia product; Klebsiella quasipneumoniae; Ruthenibacterium lactatiformans; Veillonella dispar; Coriobacteriaceae Eggerthella; and Lachnospiraceae Hungatella; wherein the change in taxonomical feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 170) The method of aspect 169, wherein an increase in relative abundance of at least one of: Anaerostipes hadrus; Lachnospiraceae Dorea; Dorea longicatena; Lachnospiraceae Coprococcus; Lachnospiraceae Roseburia; Blautia obeum; Coprococcus comes; Roseburia intestinalis; Lactobacillus rogosae; Eubacterium [Eubacterium] eligens; Bacteroidia Bacteroidales; Peptostreptococcaceae Romboutsia; Coriobacteriaceae Collinsella; Acidaminococcaceae Acidaminococcus; Prevotellaceae Prevotella; Prevotella copri; Coriobacteriales Coriobacteriaceae; Ruminococcaceae Ruminococcus; Alistipes obesi; Betaproteobacteria Burkholderiales; Ruminococcus bromii; Lachnospiraceae Lachnoclostridium; Bifidobacterium adolescentis; Actinomycetales Actinomycetaceae; Ruminococcaceae Intestinimonas; and Bacteroides eggerthii, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 171) The method of aspect 169, wherein a decrease in relative abundance of at least one of: Clostridioides difficile; Peptostreptococcaceae Clostridium XI; Enterobacteriaceae Citrobacter; Enterobacterales Enterobacteriaceae; Veillonella parvula; Enterococcaceae Enterococcus; Lactobacilluses Enterococcaceae; Erysipelatoclostridium [Clostridium] innocuum; Pectobacterium carotovorum; Enterobacteriales Enterobacteriaceae; Bacteroides xylanisolvens; Enterococcus saccharolyticus; Clostridium paraputrificum; Salmonella enterica; Erysipelatoclostridium ramosum; Hungatella effluvia; Bacteroides koreensis; Bacilli Lactobacillies; Blautia product; Klebsiella quasipneumoniae; Ruthenibacterium lactatiformans; Veillonella dispar; Coriobacteriaceae Eggerthella; and Lachnospiraceae Hungatella, is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 172) The method of aspect 169-171, wherein a change in relative abundance of at least four taxonomical features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 173) A method of diagnosing an individual having diarrhea comprising: measuring for presence or absence or a certain level of one or more metabolic feature(s) from a biological sample from the individual; and classifying the individual as having a CDI associated pathogenic infection, irritable bowel syndrome (IBS), or inflammatory bowel disease (IBD).
- Aspect 174) The method of aspect 173, wherein the diagnosing is characterized by measuring the presence, absence, and/or relative quantity of at least 10 metabolic features described in any one of Tables 1-8.
- Aspect 175) The method aspect 174, wherein the diagnosing is characterized by measuring the presence, absence, and/or relative quantity of at least 20 metabolic features described in any one of Tables 1-8.
- Aspect 176) The method of aspect 174, wherein the diagnosing is characterized by measuring the presence, absence, and/or relative quantity of at least 40 metabolic features described in any one of Tables 1-8.
- Aspect 177) The method of aspect 174, wherein the diagnosing is characterized by measuring the presence, absence, and/or relative quantity of at least 60 metabolic features described in any one of Tables 1-8.
- Aspect 178) The method of aspect 174, wherein the diagnosing is characterized by measuring the presence, absence, and/or relative quantity of at least 80 metabolic features described in any one of Tables 1-8.
- Aspect 179) The method of aspect 174, wherein the diagnosing is characterized by measuring the presence, absence, and/or relative quantity of at least 100 metabolic features described in any one Tables 1-8.
- Aspect 180) The method of any one of aspects 175-179, wherein the diagnosing comprises characterization using more than one of Tables 1-8.
- Aspect 181) The method of aspect 180, wherein the more than one characterization using Tables 1-8 is sequential.
- Aspect 182) The method of aspect 180 or 181, wherein the more than one characterization using Tables 1-8 comprises first characterizing using Tables 3 and/or 7, followed by characterization using one or more of the remaining Tables.
- Aspect 183) The method of any one of aspects 173-182, wherein the measuring of one or more metabolic features comprises at least one of analyzing one or more nucleic acids in the sample, analyzing one or more metabolites in the sample, and analyzing one or more proteins in the sample.
- Aspect 184) The method of aspect 183, wherein the nucleic acid is analyzed by sequencing, polymerase chain reaction, isothermal amplification, bioinformatics, or any combination thereof.
- Aspect 185) The method of aspect 184, wherein the nucleic acid analyzed is 16S ribosomal RNA.
- Aspect 186) The method of aspect 183, wherein the metabolites are analyzed by mass spectrometry, ELISA, chromatography, or any combination thereof.
- Aspect 187) The method of aspect 183, wherein the proteins are analyzed by mass spectrometry, ELISA, chromatography, Western blotting, immunoprecipitation, immunoelectrophoresis, or any combination thereof.
- Aspect 188) The method of any one of aspects 173-187, wherein the diagnosis is indicative of non-CDI causative diarrhea, the subject microbiome is further characterized to determine whether the non-CDI causative diarrhea is associated with irritable bowel syndrome (IBS) or inflammatory bowel disease (IBD),
- Aspect 189) The method of aspect 188, wherein the non-CDI causative diarrhea is associated with IBD, the IBD is further characterized to determine whether the IBD is Ulcerative Colitis (UC) or Crohn's Disease (CD).
- Aspect 190) The method of aspect 173, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7159 (chlorophyllide a biosynthesis III (aerobic, light independent)); PWY-5531 (chlorophyllide a biosynthesis II (anaerobic)); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); P562-PWY (myo-inositol degradation I); PWY-3781 (aerobic respiration I (cytochrome c)); TYRFUMCAT-PWY (L-tyrosine degradation I); HCAMHPDEG-PWY (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation to 2-oxopent-4-enoate); PWY-6071 (superpathway of phenylethylamine degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 191) The method of aspect 190, wherein an increase in relative abundance of at least one of: PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7159 (chlorophyllide a biosynthesis III (aerobic, light independent)); PWY-5531 (chlorophyllide a biosynthesis II (anacrobic)); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); P562-PWY (myo-inositol degradation I); PWY-3781 (aerobic respiration I (cytochrome c)); and TYRFUMCAT-PWY (L-tyrosine degradation I), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 192) The method of aspect 190, wherein a decrease in relative abundance of at least one of: HCAMHPDEG-PWY (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation to 2-oxopent-4-enoate); PWY-6071 (superpathway of phenylethylamine degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 193) The method of any one of aspects 190-192, wherein a change in relative abundance of at least three metabolic features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 194) The method of aspect 173, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); DTDPRHAMSYN-PWY (dTDP-L-rhamnose biosynthesis I); FASYN-ELONG-PWY (fatty acid elongation-saturated); GALACTARDEG-PWY (D-galactarate degradation I); GLUCARDEG-PWY (D-glucarate degradation I); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GLUCONEO-PWY (gluconcogenesis I); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); HISDEG-PWY (L-histidine degradation I); METHGLYUT-PWY (superpathway of methylglyoxal degradation); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); P163-PWY (L-lysine fermentation to acetate and butanoate); P42-PWY (incomplete reductive TCA cycle); PENTOSE-P-PWY (pentose phosphate pathway); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-1533 (methylphosphonate degradation I); PWY0-41 (allantoin degradation IV (anaerobic)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-5659 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-5705 (allantoin degradation to glyoxylate III); PWY-5913 (TCA cycle VI (obligate autotrophs)); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6353 (purine nucleotides degradation II (aerobic)); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation); PWY-6572 (chondroitin sulfate degradation I (bacterial)); PWY-6588 (pyruvate fermentation to acetone); PWY-6608 (guanosine nucleotides degradation III); PWY-6703 (preQ0 biosynthesis); PWY-6891 (thiazole biosynthesis II (Bacillus)); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY-6901 (superpathway of glucose and xylose degradation); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PWY-7013 (L-1,2-propanediol degradation); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); PWY-7222 (guanosine deoxyribonucleotides de novo biosynthesis II); PWY-7237 (myo-, chiro- and scillo-inositol degradation); PWY-7242 (D-fructuronate degradation); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7456 (mannan degradation); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); TCA (TCA cycle I (prokaryotic)); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); and VALDEG-PWY (L-valine degradation I); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 195) The method of aspect 194, wherein an increase in relative abundance of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); DTDPRHAMSYN-PWY (dTDP-L-rhamnose biosynthesis I); FASYN-ELONG-PWY (fatty acid elongation-saturated); GALACTARDEG-PWY (D-galactarate degradation I); GLUCARDEG-PWY (D-glucarate degradation I); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GLUCONEO-PWY (gluconcogenesis I); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); HEMESYN2-PWY (heme biosynthesis II (anacrobic)); HISDEG-PWY (L-histidine degradation I); METHGLYUT-PWY (superpathway of methylglyoxal degradation); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); P163-PWY (L-lysine fermentation to acetate and butanoate); P42-PWY (incomplete reductive TCA cycle); PENTOSE-P-PWY (pentose phosphate pathway); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-1533 (methylphosphonate degradation I); PWY0-41 (allantoin degradation IV (anaerobic)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-5659 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-5705 (allantoin degradation to glyoxylate III); PWY-5913 (TCA cycle VI (obligate autotrophs)); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6353 (purine nucleotides degradation II (acrobic)); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation); PWY-6572 (chondroitin sulfate degradation I (bacterial)); PWY-6588 (pyruvate fermentation to acetone); PWY-6608 (guanosine nucleotides degradation III); PWY-6703 (preQ0 biosynthesis); PWY-6891 (thiazole biosynthesis II (Bacillus)); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY-6901 (superpathway of glucose and xylose degradation); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PWY-7013 (L-1,2-propanediol degradation); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); PWY-7222 (guanosine deoxyribonucleotides de novo biosynthesis II); PWY-7237 (myo-, chiro- and scillo-inositol degradation); PWY-7242 (D-fructuronate degradation); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7456 (mannan degradation); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); TCA (TCA cycle I (prokaryotic)); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); and VALDEG-PWY (L-valine degradation I), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 196) The method of any one of aspects 194 or 195, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 197) The method of aspect 188, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBS or IBD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBS gut microbiome, of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); GALACT-GLUCUROCAT-PWY (superpathway of hexuronide and hexuronate degradation); ANAEROFRUCAT-PWY (homolactic fermentation); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); PWY0-781 (aspartate superpathway); PWY-7242 (D-fructuronate degradation); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-7013 (L-1,2-propanediol degradation); P124-PWY (Bifidobacterium shunt); P122-PWY (heterolactic fermentation); REDCITCYC (TCA cycle VIII (helicobacter)); DENOVOPURINE2-PWY (superpathway of purine nucleotides de novo biosynthesis II); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GALACTARDEG-PWY (D-galactarate degradation I); PWY-6891 (thiazole biosynthesis II (Bacillus)); FUC-RHAMCAT-PWY (superpathway of fucose and rhamnose degradation); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-41 (allantoin degradation IV (anacrobic)); VALDEG-PWY (L-valine degradation I); PWY-7187 (pyrimidine deoxyribonucleotides de novo biosynthesis II); PWY0-1533 (methylphosphonate degradation I); GLUCARDEG-PWY (D-glucarate degradation I); TYRFUMCAT-PWY (L-tyrosine degradation I); PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7094 (fatty acid salvage); and LEU-DEG2-PWY (L-leucine degradation I); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 198) The method of aspect 197, wherein an increase in relative abundance of at least one of: ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); GALACT-GLUCUROCAT-PWY (superpathway of hexuronide and hexuronate degradation); ANAEROFRUCAT-PWY (homolactic fermentation); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); PWY0-781 (aspartate superpathway); PWY-7242 (D-fructuronate degradation); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-7013 (L-1,2-propanediol degradation); P124-PWY (Bifidobacterium shunt); P122-PWY (heterolactic fermentation); REDCITCYC (TCA cycle VIII (helicobacter)); DENOVOPURINE2-PWY (superpathway of purine nucleotides de novo biosynthesis II); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); GALACTARDEG-PWY (D-galactarate degradation I); PWY-6891 (thiazole biosynthesis II (Bacillus)); FUC-RHAMCAT-PWY (superpathway of fucose and rhamnose degradation); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-41 (allantoin degradation IV (anaerobic)); VALDEG-PWY (L-valine degradation I); PWY-7187 (pyrimidine deoxyribonucleotides de novo biosynthesis II); PWY0-1533 (methylphosphonate degradation I); and GLUCARDEG-PWY (D-glucarate degradation I), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 199) The method of aspect 197, wherein a decrease in relative abundance of at least one of: TYRFUMCAT-PWY (L-tyrosine degradation I); PWY-7431 (aromatic biogenic amine degradation (bacteria)); PWY-7094 (fatty acid salvage); and LEU-DEG2-PWY (L-leucine degradation I), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 200) The method of any one of aspects 197-199, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 201) The method of aspect 189, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); DTDPRHAMSYN-PWY (dTDP-L-rhamnose biosynthesis I); GLUCONEO-PWY (gluconcogenesis I); PWY-7222 (guanosine deoxyribonucleotides de novo biosynthesis II); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PENTOSE-P-PWY (pentose phosphate pathway); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-6901 (superpathway of glucose and xylose degradation); PWY-5659 9 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-7456 (mannan degradation); VALDEG-PWY (L-valine degradation I); ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); TCA (TCA cycle I (prokaryotic)); FASYN-ELONG-PWY (fatty acid elongation-saturated); PWY-6703 (preQ0 biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); P42-PWY (incomplete reductive TCA cycle); PWY-5913 (TCA cycle VI (obligate autotrophs)); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); P163-PWY (L-lysine fermentation to acetate and butanoate); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); PWY-7242 (D-fructuronate degradation); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6572 (chondroitin sulfate degradation I (bacterial)); and PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 202) The method of aspect 201, wherein an increase in relative abundance of at least one of: PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-7220 (adenosine deoxyribonucleotides de novo biosynthesis II); DTDPRHAMSYN-PWY (dTDP-L-rhamnose I); PWY-7222 (guanosine biosynthesis I); GLUCONEO-PWY (gluconcogenesis deoxyribonucleotides de novo biosynthesis II); GLYCOLYSIS (glycolysis I (from glucose 6-phosphate)); POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)); PWY-6969 (TCA cycle V (2-oxoglutarate: ferredoxin oxidoreductase)); PENTOSE-P-PWY (pentose phosphate pathway); PWY-5971 (palmitate biosynthesis II (bacteria and plants)); PWY-7199 (pyrimidine deoxyribonucleosides salvage); PWY-6901 (superpathway of glucose and xylose degradation); PWY-5659 (GDP-mannose biosynthesis); PWY-5695 (urate biosynthesis/inosine 5′-phosphate degradation); PWY-7456 (mannan degradation); VALDEG-PWY (L-valine degradation I); ASPASN-PWY (superpathway of L-aspartate and L-asparagine biosynthesis); TCA (TCA cycle I (prokaryotic)); FASYN-ELONG-PWY (fatty acid elongation-saturated); PWY-6703 (preQ0 biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); P42-PWY (incomplete reductive TCA cycle); PWY-5913 (TCA cycle VI (obligate autotrophs)); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); P163-PWY (L-lysine fermentation to acetate and butanoate); THISYN-PWY (superpathway of thiamin diphosphate biosynthesis I); PWY-7242 (D-fructuronate degradation); PWY-6125 (superpathway of guanosine nucleotides de novo biosynthesis II); PWY-6572 (chondroitin sulfate degradation I (bacterial)); and PWY-6507 (4-deoxy-L-threo-hex-4-enopyranuronate degradation), is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 203) The method of any one of aspects 200-202, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD UC.
- Aspect 204) The method of aspect 189, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference healthy gut microbiome, of at least one of: HEMESYN2-PWY (heme biosynthesis II (anaerobic)); PWY-6608 (guanosine nucleotides degradation III); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); GALACTARDEG-PWY (D-galactarate degradation I); PWY-7013 (L-1,2-propanediol degradation); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); PWY-6353 (purine nucleotides degradation II (acrobic)); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLUCARDEG-PWY (D-glucarate degradation I); PENTOSE-P-PWY (pentose phosphate pathway); PWY-6891 (thiazole biosynthesis II (Bacillus)); HISDEG-PWY (L-histidine degradation I); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7237 (myo-, chiro- and scillo-inositol degradation); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY-6588 (pyruvate fermentation to acetone); PWY0-1533 (methylphosphonate degradation I); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-41 (allantoin degradation IV (anaerobic)); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); PWY-5705 (allantoin degradation to glyoxylate III); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); and METHGLYUT-PWY (superpathway of methylglyoxal degradation); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 205) The method of aspect 204, wherein an increase in relative abundance of at least one of: HEMESYN2-PWY (heme biosynthesis II (anaerobic)); PWY-6608 (guanosine nucleotides degradation III); SALVADEHYPOX-PWY (adenosine nucleotides degradation II); GALACTARDEG-PWY (D-galactarate degradation I); PWY-7013 (L-1,2-propanediol degradation); GLUCARGALACTSUPER-PWY (superpathway of D-glucarate and D-galactarate degradation); PWY-6353 (purine nucleotides degradation II (aerobic)); P125-PWY (superpathway of (R,R)-butanediol biosynthesis); GLUCUROCAT-PWY (superpathway of & beta; -D-glucuronide and D-glucuronate degradation); GLUCARDEG-PWY (D-glucarate degradation I); PENTOSE-P-PWY (pentose phosphate pathway); PWY-6891 (thiazole biosynthesis II (Bacillus)); HISDEG-PWY (L-histidine degradation I); PWY0-845 (superpathway of pyridoxal 5′-phosphate biosynthesis and salvage); PWY-5028 (L-histidine degradation II); PWY-7328 (superpathway of UDP-glucose-derived O-antigen building blocks biosynthesis); PWY-7237 (myo-, chiro- and scillo-inositol degradation); P162-PWY (L-glutamate degradation V (via hydroxyglutarate)); PWY-6588 (pyruvate fermentation to acetone); PWY0-1533 (methylphosphonate degradation I); PWY-6396 (superpathway of 2,3-butanediol biosynthesis); PYRIDOXSYN-PWY (pyridoxal 5′-phosphate biosynthesis I); PWY-6895 (superpathway of thiamin diphosphate biosynthesis II); PWY0-1241 (ADP-L-glycero-& beta; -D-manno-heptose biosynthesis); PWY0-41 (allantoin degradation IV (anacrobic)); DHGLUCONATE-PYR-CAT-PWY (glucose degradation (oxidative)); PWY-5705 (allantoin degradation to glyoxylate III); GLYCOLYSIS-E-D (superpathway of glycolysis and Entner-Doudoroff); and METHGLYUT-PWY (superpathway of methylglyoxal degradation), is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 206) The method of aspect 204 or 205, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 207) The method of aspect 189, wherein the characterization of the subject microbiome to determine whether the non-CDI causative diarrhea is associated with IBD UC or IBD CD comprises measuring one or more metabolic features from a biological sample from the subject and determining changes in relative abundance, compared to a reference dysbiosis IBD UC gut microbiome, of at least one of: ECASYN-PWY (enterobacterial common antigen biosynthesis); PPGPPMET-PWY (ppGpp biosynthesis); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithine degradation); AST-PWY (L-arginine degradation II (AST pathway)); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); ORNDEG-PWY (superpathway of ornithine degradation); PWY0-1338 (polymyxin resistance); PWY-5028 (L-histidine degradation II); AEROBACTINSYN-PWY (acrobactin biosynthesis); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-321 (phenylacetate degradation I (aerobic)); PWY0-1533 (methylphosphonate degradation I); P241-PWY (coenzyme B biosynthesis); PWY-6148 (tetrahydromethanopterin biosynthesis); PWY-6349 (CDP-archacol biosynthesis); PWY-6654 (phosphopantothenate biosynthesis III); METHANOGENESIS-PWY (methanogenesis from H2 and CO2); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5198 (factor 420 biosynthesis); PWY-6167 (flavin biosynthesis II (archaca)); PWY-6641 (superpathway of sulfolactate degradation); PWY-6350 (archactidylinositol biosynthesis); PWY-6141 (archactidylserine and archaetidylethanolamine biosynthesis); PWY-6174 (mevalonate pathway II (archaca)); P261-PWY (coenzyme M biosynthesis I); and PWY-7391 (isoprene biosynthesis II (engineered)); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 208) The method of aspect 207, wherein an increase in relative abundance of at least one of: ECASYN-PWY (enterobacterial common antigen biosynthesis); PPGPPMET-PWY (ppGpp biosynthesis); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithinc degradation); AST-PWY (L-arginine degradation II (AST pathway)); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); ORNDEG-PWY (superpathway of ornithine degradation); PWY0-1338 (polymyxin resistance); PWY-5028 (L-histidine degradation II); AEROBACTINSYN-PWY (acrobactin biosynthesis); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-321 (phenylacetate degradation I (acrobic)); and PWY0-1533 (methylphosphonate degradation I), is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 209) The method of aspect 207, wherein a decrease in relative abundance of at least one of: P241-PWY (coenzyme B biosynthesis); PWY-6148 (tetrahydromethanopterin biosynthesis); PWY-6349 (CDP-archacol biosynthesis); PWY-6654 (phosphopantothenate biosynthesis III); METHANOGENESIS-PWY (methanogenesis from H2 and CO2); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5198 (factor 420 biosynthesis); PWY-6167 (flavin biosynthesis II (archaca)); PWY-6641 (superpathway of sulfolactate degradation); PWY-6350 (archaetidylinositol biosynthesis); PWY-6141 (archaetidylserine and archactidylethanolamine biosynthesis); PWY-6174 (mevalonate pathway II (archaca)); P261-PWY (coenzyme M biosynthesis I); and PWY-7391 (isoprene biosynthesis II (engineered)), is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 210) The method of any one of aspects 207-209, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD CD.
- Aspect 211) The method of aspect 173, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of: P221-PWY (octane oxidation); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); PWY-6263 (superpathway of menaquinol-8 biosynthesis II); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); PWY-5198 (factor 420 biosynthesis); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5531 (chlorophyllide a biosynthesis II (anaerobic)); PWY-6349 (CDP-archacol biosynthesis); PWY-5088 (L-glutamate degradation VIII (to propanoate)); PWY-6350 (archactidylinositol biosynthesis); PWY-7159 (chlorophyllide a biosynthesis III (aerobic, light independent)); PWY0-1533 (methylphosphonate degradation I); ORNDEG-PWY (superpathway of ornithinc degradation); PWY0-1338 (polymyxin resistance); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithine degradation); ECASYN-PWY (enterobacterial common antigen biosynthesis); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); GLYCOL-GLYOXDEG-PWY (superpathway of glycol metabolism and degradation); ENTBACSYN-PWY (enterobactin biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-1277 (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate); wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 212) The method of aspect 211, wherein an increase in relative abundance of at least one of: P221-PWY (octane oxidation); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); PWY-6263 (superpathway of menaquinol-8 biosynthesis II); CHLOROPHYLL-SYN (chlorophyllide a biosynthesis I (aerobic, light-dependent)); PWY-5198 (factor 420 biosynthesis); PWY-7286 (7-(3-amino-3-carboxypropyl)-wyosine biosynthesis); PWY-5531 (chlorophyllide a biosynthesis II (anaerobic)); PWY-6349 (CDP-archacol biosynthesis); PWY-5088 (L-glutamate degradation VIII (to propanoate)); PWY-6350 (archactidylinositol biosynthesis); and PWY-7159 (chlorophyllide a biosynthesis III (aerobic, light independent)), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 213) The method of aspect 211, wherein a decrease in relative abundance of at least one of: PWY0-1533 (methylphosphonate degradation I); ORNDEG-PWY (superpathway of ornithinc degradation); PWY0-1338 (polymyxin resistance); ORNARGDEG-PWY (superpathway of L-arginine and L-ornithine degradation); ECASYN-PWY (enterobacterial common antigen biosynthesis); ARGDEG-PWY (superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation); GLYCOL-GLYOXDEG-PWY (superpathway of glycol metabolism and degradation); ENTBACSYN-PWY (enterobactin biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); GOLPDLCAT-PWY (superpathway of glycerol degradation to 1,3-propanediol); PWY-6071 (superpathway of phenylethylamine degradation); PWY0-1277 (3-phenylpropanoate and 3-(3-hydroxyphenyl) propanoate degradation); and PWY-6690 (cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate), is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 214) The method of any one of aspects 211-213, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBS.
- Aspect 215) The method of aspect 173, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining changes in relative abundance, compared to a reference dysbiosis gut microbiome from individuals with CDI, of at least one of the pathways identified in Table 3 as being upregulated greater than 5 fold; wherein the change in metabolic feature relative abundance is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 216) The method of aspect 215, wherein an increase in relative abundance of at least one of: PWY-6151 (S-adenosyl-L-methionine cycle I); P221-PWY (octane oxidation); PWY-5505 (L-glutamate and L-glutamine biosynthesis); PWY-5121 (superpathway of geranylgeranyl diphosphate biosynthesis II (via MEP)); GLYCOGENSYNTH-PWY (glycogen biosynthesis I (from ADP-D-Glucose)); NONMEVIPP-PWY (methylerythritol phosphate pathway I); PWY-6269 (adenosylcobalamin salvage from cobinamide II); PYRIDNUCSYN-PWY (NAD biosynthesis I (from aspartate)); COA-PWY (coenzyme A biosynthesis I); PWY-5686 (UMP biosynthesis); PWY-7560 (methylerythritol phosphate pathway II); PWY-6386 (UDP-N-acetylmuramoyl-pentapeptide biosynthesis II (lysine-containing)); PWY-6277 (superpathway of 5-aminoimidazole ribonucleotide biosynthesis); PWY-5509 (adenosylcobalamin biosynthesis from cobyrinate a,c-diamide I); PWY-7219 (adenosine ribonucleotides de novo biosynthesis); COBALSYN-PWY (adenosylcobalamin salvage from cobinamide I); PWY-6163 (chorismate biosynthesis from 3-dehydroquinate); PWY-6123 (inosine-5′-phosphate biosynthesis I); GLYCOCAT-PWY (glycogen degradation I (bacterial)); ARO-PWY (chorismate biosynthesis I); PWY-6317 (galactose degradation I (Leloir pathway)); PWY-5097 (L-lysine biosynthesis VI); PWY-6385 (peptidoglycan biosynthesis III (mycobacteria)); COMPLETE-ARO-PWY (superpathway of aromatic amino acid biosynthesis); PWY-6892 (thiazole biosynthesis I (E. coli)); PEPTIDOGLYCANSYN-PWY (peptidoglycan biosynthesis I (meso-diaminopimelate containing)); PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II); PYRIDNUCSAL-PWY (NAD salvage pathway I); PWY-5667 (CDP-diacylglycerol biosynthesis I); PWY-6387 (UDP-N-acetylmuramoyl-pentapeptide biosynthesis I (meso-diaminopimelate containing)); TRNA-CHARGING-PWY (IRNA charging); PWY-5100 (pyruvate fermentation to acetate and lactate II); PWY-7663 (gondoate biosynthesis (anaerobic)); PWY-5104 (L-isoleucine biosynthesis IV); PWY-5973 (cis-vaccenate biosynthesis); PWY0-1319 (CDP-diacylglycerol biosynthesis II); PWY-7221 (guanosine ribonucleotides de novo biosynthesis); PWY4FS-8 (phosphatidylglycerol biosynthesis II (non-plastidic)); PWY-6737 (starch degradation V); PWY-3001 (superpathway of L-isoleucine biosynthesis I); HISTSYN-PWY (L-histidine biosynthesis); PWY-7208 (superpathway of pyrimidine nucleobases salvage); PHOSLIPSYN-PWY (superpathway of phospholipid biosynthesis I (bacteria)); PWY-6121 (5-aminoimidazole ribonucleotide biosynthesis I); PWY-2942 (L-lysine biosynthesis III); SER-GLYSYN-PWY (superpathway of L-serine and glycine biosynthesis I); AEROBACTINSYN-PWY (acrobactin biosynthesis); PWY-6126 (superpathway of adenosine nucleotides de novo biosynthesis II); DAPLYSINESYN-PWY (L-lysine biosynthesis I); NONOXIPENT-PWY (pentose phosphate pathway (non-oxidative branch)); BRANCHED-CHAIN-AA-SYN-PWY (superpathway of branched amino acid biosynthesis); PWY-7229 (superpathway of adenosine nucleotides de novo biosynthesis I); ARGSYNBSUB-PWY (L-arginine biosynthesis II (acetyl cycle)); VALSYN-PWY (L-valine biosynthesis); ILEUSYN-PWY (L-isoleucine biosynthesis I (from threonine)); 1CMET2-PWY (N10-formyl-tetrahydrofolate biosynthesis); GALLATE-DEGRADATION-II-PWY (gallate degradation I); 3-HYDROXYPHENYLACETATE-DEGRADATION-PWY (4-hydroxyphenylacetate degradation); METHYLGALLATE-DEGRADATION-PWY (methylgallate degradation); PWY-7400 (L-arginine biosynthesis IV (archaebacteria)); THRESYN-PWY (superpathway of L-threonine biosynthesis); DENOVOPURINE2-PWY (superpathway of purine nucleotides de novo biosynthesis II); ARGSYN-PWY (L-arginine biosynthesis I (via L-ornithine)); PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP); PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV); POLYAMINSYN3-PWY (superpathway of polyamine biosynthesis II); PWY4FS-7 (phosphatidylglycerol biosynthesis I (plastidic)); PWY0-166 (superpathway of pyrimidine deoxyribonucleotides de novo biosynthesis (E. coli)); GALLATE-DEGRADATION-I-PWY (gallate degradation II); CALVIN-PWY (Calvin-Benson-Bassham cycle); PANTOSYN-PWY (pantothenate and coenzyme A biosynthesis I); PWY-5484 (glycolysis II (from fructose 6-phosphate)); PWY-7184 (pyrimidine deoxyribonucleotides de novo biosynthesis I); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); and POLYISOPRENSYN-PWY (polyisoprenoid biosynthesis (E. coli)), is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 217) The method of aspect 215 or 216, wherein a change in relative abundance of at least four metabolic features is indicative of non-CDI causative diarrhea associated with IBD.
- Aspect 218) The method of aspect 173, wherein the measuring of one or more metabolic features from a biological sample from the individual comprises determining relative changes in abundance, compared to a reference gut microbiome, in at least one of: AST-PWY (L-arginine degradation II (AST pathway)); ECASYN-PWY (enterobacterial common antigen biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); PPGPPMET-PWY (ppGpp biosynthesis); PWY0-1338 (polymyxin resistance); PWY-6263 (superpathway of menaquinol-8 biosynthesis II); PWY-7371 (1,4-dihydroxy-6-naphthoate biosynthesis II); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); P221-PWY (octane oxidation); PWY-6749 (CMP-legionaminate biosynthesis I); PWY-7456 (mannan degradation); NONMEVIPP-PWY (methylerythritol phosphate pathway I); PWY-5097 (L-lysine biosynthesis VI); PWY-5505 (L-glutamate and L-glutamine biosynthesis); PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II); PWY-7663 (gondoate biosynthesis (anaerobic)); THRESYN-PWY (superpathway of L-threonine biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anacrobic)); PWY-5304 (superpathway of sulfur oxidation (archaca); PWY-6478 (GDP-D-glycero-alpha-D-manno-heptose biosynthesis); PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV); and PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP); wherein increased abundance of at least one of AST-PWY (L-arginine degradation II (AST pathway)); ECASYN-PWY (enterobacterial common antigen biosynthesis); THREOCAT-PWY (superpathway of L-threonine metabolism); PPGPPMET-PWY (ppGpp biosynthesis); and PWY0-1338 (polymyxin resistance) is associated with CDI causative diarrhea and the individual is treated accordingly; wherein increased abundance of at least one of PWY-6263 (superpathway of menaquinol-8 biosynthesis II); PWY-7371 (1,4-dihydroxy-6-naphthoate biosynthesis II); PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I); P221-PWY (octane oxidation); PWY-6749 (CMP-legionaminate biosynthesis I); and PWY-7456 (mannan degradation) is associated with IBD UC causative diarrhea and the individual is treated accordingly; and wherein increased abundance of at least one of NONMEVIPP-PWY (methylerythritol phosphate pathway I); PWY-5097 (L-lysine biosynthesis VI); PWY-5505 (L-glutamate and L-glutamine biosynthesis); PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II); PWY-7663 (gondoate biosynthesis (anaerobic)); THRESYN-PWY (superpathway of L-threonine biosynthesis); HEMESYN2-PWY (heme biosynthesis II (anaerobic)); PWY-5304 (superpathway of sulfur oxidation (archaca); PWY-6478 (GDP-D-glycero-alpha-D-manno-heptose biosynthesis); PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV); and PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP) is associated with IBD causative diarrhea and the individual is treated accordingly.
- Aspect 219) A complex comprising a plurality of oligonucleotide primer sets hybridized to nucleic acid template sequences, wherein the nucleic acid template sequences are taxonomically specific sequences associated with taxonomical features identified in tables 9-17.
- Aspect 220) The complex of aspect 219, wherein at least 5 or at least 10 oligonucleotide primer sets are hybridized to nucleic acid template sequences.
- Aspect 221) A kit for measuring for presence or absence or a certain level of one or more taxonomical feature(s) from a biological sample from an individual, comprising: (a) a plurality of sets of oligonucleotide primers, wherein each set of primers hybridize to a different nucleic acid template sequence for amplying taxonomically specific sequences; and (b) a polymerase enzyme; wherein the individual sets of oligonucleotide primers hybridize to a taxonomically specific sequence associated with the taxonomical features identified in tables 9-17.
- Aspect 222) The kit according to aspect 221, wherein the master mix further comprises deoxynucleoside triphosphates; and at least one indicator for detecting an amplification product by a change in color or fluorescence.
- Aspect 223) The kit according to aspect 222, wherein the deoxynucleoside triphosphates comprise dTTP, dGTP, dATP, dCTP and/or dUTP.
- Aspect 224) The kit according to aspect 221, comprising at least 5, at least 10, at least 20, at least 40, at least 60, at least 80, at least 100, at least 120, at least 140, at least 160, at least 180, or at least 200 individual sets of oligonucleotide primers.
- Aspect 225) The kit according to aspect 221, wherein the individual sets of oligonucleotide primers are bound to a support substrate.
- Aspect 226) A kit for measuring for presence or absence or a certain level of one or more biochemical feature(s) from a biological sample from an individual, comprising: (a) a plurality of wells, wherein at least one well comprises one or more reagents suitable for colorimetric mediated analysis of levels of a metabolite; and (b) a guide for interpreting the colorimetric results; wherein the individual wells comprise reagents suitable for measurement of metabolites associated with the metabolic pathways identified in tables 1-8.
- Aspect 227) The kit according to aspect 226, comprising at least 5, at least 10, at least 20, at least 40, at least 60, at least 80, at least 100, at least 120, at least 140, at least 160, at least 180, or at least 200 individual wells comprising reagents suitable for colorimetric mediated analysis of levels of a metabolite.
- Aspect 228) A composition for treatment of CDI associated microbiome dysbiosis, comprising agents that decrease the activity of at least one metabolic pathway, wherein the metabolic pathway is AST-PWY (L-arginine degradation II (AST pathway)), ECASYN-PWY (enterobacterial common antigen biosynthesis), THREOCAT-PWY (superpathway of L-threonine metabolism), PPGPPMET-PWY (ppGpp biosynthesis), and/or PWY0-1338 (polymyxin resistance).
- Aspect 229) A composition for treatment of IBD UC associated microbiome dysbiosis, comprising agents that decrease the activity of at least one metabolic pathway, wherein the metabolic pathway is PWY-6263 (superpathway of menaquinol-8 biosynthesis II), PWY-7371 (1,4-dihydroxy-6-naphthoate biosynthesis II), PWY-7374 (1,4-dihydroxy-6-naphthoate biosynthesis I), P221-PWY (octane oxidation), PWY-6749 (CMP-legionaminate biosynthesis I), and/or PWY-7456 (mannan degradation).
- Aspect 230) A composition for treatment of IBD associated microbiome dysbiosis, comprising agents that decrease the activity of at least one metabolic pathway, wherein the metabolic pathway is NONMEVIPP-PWY (methylerythritol phosphate pathway I), PWY-5097 (L-lysine biosynthesis VI), PWY-5505 (L-glutamate and L-glutamine biosynthesis), PWY-6122 (5-aminoimidazole ribonucleotide biosynthesis II), PWY-7663 (gondoate biosynthesis (anacrobic)), THRESYN-PWY (superpathway of L-threonine biosynthesis), HEMESYN2-PWY (heme biosynthesis II (anaerobic)), PWY-5304 (superpathway of sulfur oxidation (archaca)), PWY-6478 (GDP-D-glycero-alpha-D-manno-heptose biosynthesis), PWY-7198 (pyrimidine deoxyribonucleotides de novo biosynthesis IV), and/or PWY-7210 (pyrimidine deoxyribonucleotides biosynthesis from CTP).
- Aspect 231) The composition of any one of aspects 228-230, wherein the agent is an antibiotic, antimicrobial, antiviral, small molecule, peptide, amino acid, carbohydrate, sugar, fat, metabolite, oligonucleotide, microbe(s), or any combination thereof.
- Aspect 232) The composition of aspect 231, wherein the composition is formulated for oral delivery, intravenous delivery, or delivery as a suppository.
- Aspect 233) A method of decreasing the rate of CDI associated health care facility epidemics, comprising testing individuals for CDI associated taxonomic features and/or metabolic features as described in any one of tables 1-17, and isolating the individual if they have taxonomic features and/or metabolic features indicative of CDI.
- Aspect 234) A method of identifying features suitable for methods of disease diagnosis and/or treatment regimen prescription comprising, identifying and selecting classifiers using microbiome data generated from two or more different 16S sequencing strategies and/or two or more different populations.
- Aspect 235) The method of aspect 234, wherein the Taxa4Meta data analysis pipeline is used to identify the features.
- Aspect 236) The method of aspect 234 or 235, wherein technical and/or demographic bias is reduced when compared to analysis performed with less than two 16S sequencing strategies and/or different populations.

EXAMPLES

The following examples are included to demonstrate preferred embodiments of the disclosure. It should be appreciated by those of skill in the art that the techniques disclosed in the examples that follow represent techniques discovered by the inventor to function well in the practice of the disclosure, and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the disclosure.

Example 1—Materials and Methods

Simulation of full-length and region-specific 16S amplicon data: two reference databases—NCBI 16S rRNA RefSeq database (downloaded in July 2019) and Ribosomal Database Project (RDP) database (release 11.5)²⁸were downloaded for data simulation. The cutadapt (version 2.4)²⁹was then used to extract sequence fragments as full-length amplicons of targeted 16S variable regions (V1-V3. V3-V5. V4 and V6-V9) based on the forward and reverse primers listed in Table 22; an error rate of 0.2 was permitted during sequence extraction. Further sequence length trimming and random simulation of sequence abundance and quality score were performed for specific benchmarking purposes as indicated below.

Benchmarking of sequence clustering and denoising using simulated amplicons with variable length: for benchmarking the accuracy of clustering or denoising for amplicon data using variable sequence lengths, random count ranging from 1 to 50 was assigned for each parent full-length amplicon extracted from NCBI 16S rRNA RefSeq sequences. Since traditional 454 data is normally generated from reverse orientation, length trimming from either forward or reverse orientation was applied to each type of amplicon data resulting in 100, 150, 170, 200, 250, 300, 350, 400 and 450 bases for V1-V3, V3-V5 and V6-V9 amplicon data and 100, 150, 170, 200 and 250 bases for V4 amplicon data. Random phred quality score (ASCII_BASE=33) ranging from 30 to 42 was assigned to each base for sequencing denoising. Simulated amplicons of each sequence length represents one sample. All samples with the same sequence orientation from the same 16S region were then included for closed-reference or de novo clustering using UCLUST (v1.2.22)³⁰or VSEARCH (v2.9)³¹or denoising using DADA2 (v1.8)³². Sequence similarity thresholds including 0.97, 0.99 and 1.00 were evaluated for each clustering strategy. The comprehensive SILVA database (release 132) was used for closed-reference OTU picking. Because simulated amplicons of variable length originating from the same parent full-length amplicon had the same sequence counts, pairwise Spearman correlation analysis was performed for sequence counts of any two sequence lengths (as two independent samples) in the OTU count tables.

Benchmarking of taxonomic over-classification: taxonomic over-classification for short amplicon data represents an important criteria for controlling false positives. Using the default parameters in the Bayesian-based Lowest Common Ancestor (BLCA) tool¹¹and its default database of NCBI 16S rRNA RefSeq was used to annotate random and repeat sequences that were previously generated for benchmarking IDTAXA and other annotation tools¹⁰. Full-length 16S amplicons of unannotated sequences (at least down to family rank; 868.902 sequences) extracted from RDP database (release 11.5) was further used for testing BLCA. BLASTN search of unannotated sequences against NCBI 16S rRNA RefSeq database also confirmed that no best hits were identified at 97% threshold applied to both sequence identity and coverage. Simulated amplicons of unannotated RDP sequences were tested using different thresholds of sequence coverage and identity ranging from 0.85 to 1.00 in BLCA. Ten iterations of random sub-sampling (1%) and BLCA annotation on those unannotated amplicons were performed for statistical determination of optimal sequence coverage and identity required for BLCA. Taxonomic over-classification rate is defined as the classifiable proportion of unannotated amplicons at species level. The confidence score of taxonomic assignment was not considered at this stage.

Benchmarking of taxonomic accuracy using simulated amplicons of variable length: for benchmarking taxonomic accuracy of BLCA, simulated amplicons of variable length were generated by trimming full-length amplicons of NCBI 16S RefSeq from either forward or reverse orientation resulting in 100, 150, 170, 200, 250, 300, 350, 400 and 450 bases for V1-V3, V3-V5 and V6-V9 amplicon data, and 100, 150, 170, 200 and 250 bases for V4 amplicon data. In addition to the known taxonomic lineage, the parent 16S sequences of simulated amplicons are also present in the BLCA default reference database using NCBI 16S RefSeq, thus taxonomic misclassification could be evaluated. Misclassification rate is defined as the proportion of incorrect annotations for simulated amplicons. To further determine the optimal confidence threshold of BLCA for mitigating misclassification, amplicons with a selected sequence length range were combined to calculate the proportion of correct versus incorrect annotations using defined thresholds. Given the already known taxonomic lineage, true positive (TP) and false negative (FN) hits are correct annotations, whereas true negative (TN) and false positive (FP) hits are incorrect annotations.

Design of the Taxa4Meta pipeline: based on the results of the inventors comprehensive benchmarking, the inventors constructed a new computational pipeline “Taxa4Meta” for analyzing 16S amplicon data with an optimal range of variable sequence lengths. This pipeline implements several open-source programs including VSEARCH³¹for stringent clustering (99% identity) optimized for 16S amplicon data with the selected variable lengths after quality trimming. BLCA¹¹with optimal region-specific confidence thresholds for stringent species annotation of OTUs. and IDTAXA¹⁰for annotating OTUs that could not be annotated down to species resolution. Collapsed taxonomic profiles from OTU tables were used for downstream analyses during 16S meta-analysis.

Benchmarking of taxonomic profiling accuracy using Taxa4Meta versus other 16S pipelines: to test the feasibility and accuracy of different 16S pipelines using the simulated and experimental datasets^12,21for data processing and is designed to retain reads for accurate sequence clustering and improved taxonomic accuracy. Simulated datasets were prepared from NCBI 16S RefSeq as indicated above: full-length amplicons of V1-V3, V3-V5, V4 and V6-V9 were simulated, random sequence count ranging from 1 to 50 and random phred quality score (ASCII_BASE=33) ranging from 30 to 42 were generated for each full-length amplicon. Further length trimming was performed for each full-length amplicons: V1-V3 forward amplicons (200, 250, 300, 350, 400 and 450 bases), V1-V3 reverse amplicons (300, 350, 400 and 450 bases), V3-V5 forward amplicons (250, 300, 350, 400 and 450 bases), V3-V5 reverse amplicons (300, 350, 400 and 450 bases), both forward and reverse amplicons of V4 (200 and 250 bases), V6-V9 forward amplicons (300, 350, 400 and 450 bases), V6-V9 reverse amplicons (250, 300, 350, 400 and 450 bases). Trimmed amplicons from the same sequence orientation of the same 16S variable region were combined for benchmarking different 16S pipelines. NCBI 16S taxonomic lineage of NCBI 16S RefSeq was used as the ground truth (reference annotations) for comparison.

A Korean stool microbiome dataset¹²with the same DNA extracts used for 454 V1-V4, Illumina V1-V3, Illumina V3-V4, Illumina V4, and Illumina shotgun metagenomic sequencing was used as the real human microbiome dataset for benchmarking different 16S pipelines. Primers retained in the sequence reads were removed by positional trimming. Illumina paired-end reads were merged using USEARCH (version 8.1.1831) with default parameters prior to benchmarking 16S pipelines.

Key 16S pipelines including DADA2-IDTAXA, DADA2-RDP, UCLUST-UCLUST, USEARCH-RDP, Taxa4Meta, Kraken2 and MetaPhlAn2 were benchmarked with the simulated amplicons and Korean human microbiome dataset. Specifically, the analysis procedure for each pipeline were described below:

DADA2-IDTAXA pipeline. DADA2 (version 1.8) was used for denoising amplicon data after quality filtering with maximum expected error of 2 and minimum length of 200 bases. IDTAXA together with its pre-built RDP training set (version 16) was used for taxonomic annotation (could only down to genus level) with the confidence threshold of 70 using 100 bootstraps.

DADA2-RDP pipeline. DADA2 (version 1.8) was used for denoising amplicon data after quality filtering with maximum expected error of 2 and minimum length of 200 bases. RDP Naive Bayesian Classifier algorithm implemented in DADA2's assignTaxonomy function together with its pre-formatted RDP training set (version 16) was used for taxonomic annotation (could down to species level) using minimum bootstrap confidence of 50.

UCLUST-UCLUST pipeline. UCLUST (version 1.2.22q) was used for clustering amplicon data with 97% sequence similarity after quality filtering with the minimum quality threshold of 20 and the minimum length of 140 bases. Representative sequence of OTUs were selected with pick_rep_set.py script with default parameters. UCLUST implemented in assign_taxonomy.py script together with SILVA database (release 123; choice of silva_132_97_16S.fna) was used for taxonomic annotation, which could be down to species level using minimum bootstrap confidence of 0.5. All procedures were completed in QIIME platform (version 1.9.1). This pipeline is similar to the meta-analysis method used by Mancabelli et al.²²

USEARCH-RDP pipeline. USEARCH was used for clustering amplicon data with 100% sequence similarity after quality filtering with maximum expected error of 2 and minimum length of 200 bases. RDP classifier (version 2.12) together with RDP training set (version 16) was used for taxonomic annotation, which could be down to species level using minimum bootstrap confidence of 0.5. This pipeline is similar to the meta-analysis method used by Duvallet et al.²⁰

Taxa4Meta pipeline. Taxa4Meta (version 1.22) was used for clustering amplicon data after quality filtering with maximum expected error of 2 and selected range of variable lengths as suggested by Taxa4Meta itself. Taxonomic annotation by Taxa4Meta binary classifier could be down to species level.

Metagenomic classifiers. Paired-end sequences were trimmed and filtered to meet a maximum expected error of 2 with a minimum read length of 50. Kraken2 (version 2.0.8) with its pre-built database (minikraken2_v2_8 GB_201904_UPDATE) with default parameters was used for taxonomic profiling for shotgun metagenomic data. MetaPhlAn2 (version 2.7.7) with it default database (mpa_v20_m200) with default parameters was used for taxonomic profiling for shotgun metagenomic data. Kraken2 family-level abundance results were used as the reference for comparisons across different 16S pipelines. Given the high precision on species identification. MetaPhlAn2 species-level abundance results were used as the reference for evaluating species calls of different 16S pipelines. A pseudo sample was created by averaging each family-level abundance of all 27 WGS samples, then the abundance-weighted Jaccard distance was calculated between the pseudo sample and any real sample analyzed by different pipelines.

Microbiome meta-analysis of diarrheal microbiome datasets: each diarrheal dataset run on the Taxa4Meta pipeline adopted optimal taxonomic thresholds for each 16S variable region. Taxa4Meta command for each dataset was indicated in Table 21. Relative abundance of collapsed species profiles generated from each Taxa4Meta OTU count table was used without rarefaction but required a minimum 1.000 reads per sample. If species was assigned by Taxa4Meta-BLCA, the taxonomic lineage from NCBI 16S RefSeq was adopted for that species to avoid inconsistency in taxonomic lineage. Merging of Taxa4Meta collapsed species of all datasets was based on taxonomic lineages.

Predictive metagenome functions: PICRUSt2 (see e.g., Holmes et al., Generative models for microbial metagenomics. PLOS One 7, (2012)) with default parameters used Taxa4Meta OTU count tables and OTU sequences to infer metabolic pathway abundance profiles for each dataset. Merging of PICRUSt2 pathway profiles of all datasets was based on MetaCyc pathway IDs. Both LEfSe analysis (one-against-one test mode; version 1.0) and random forest (RF)-based feature ranking (default parameters in Orange version 3.20) were performed using pathway abundance profiles for each disease (CDI/CD/UC/IBS) and Control subjects. Mean decrease accuracy (MDA) score from RF-based analysis was used to rank pathways. Top 20 pathways must be listed by both RF-based feature ranking result and LEfSe analysis result, and was selected for downstream analysis including heatmap generation.

α-Diversity and β-diversity analyses: two α-diversity indices were calculated at OTU level including Shannon index (alpha_diversity.py in QIIME v1.9.1) and richness index (breakaway package version 4.7.5). In QIIME v1.9.1. Principal coordinate analysis (PCoA) with abundance-weighted Jaccard distance metric was applied for β-diversity analysis using combined collapsed species profile. ANOSIM test for group comparison was performed using the beta-diversity distance profile and the permutations of 999.

Fitting factors onto β-diversity ordination plot: fitting factors (taxa) onto a two-dimensional ordination plot (first two coordinates) was performed using the envfit function in vegan package (version 2.5-7). Taxonomic abundance profile at family level was used as factors in this analysis. Significance of fitted factors was established using the permutation of 999 in the envfit run.

Microbiome enterotyping: Microbiome enterotyping was performed with family abundance profiles of all meta-analysis adult training sets. Dirichlet multinomial mixtures (DMM) algorithm, a classical method for clustering community profile data, was used for microbiome enterotyping in this study.

Supervised classification and independent cohort validation: all supervised classification procedures were performed using Orange software³³(version 3.20) applied to the reported cohorts with clinical definitions. We adopted the original sample grouping information from each cohort, so the gold standard definition is clear for each sample. Unless otherwise stated, random forest-based feature ranking was used as a first pass to select top 100 input features (taxa or pathway) for downstream supervised learning. Unless performing sub-sampling of samples, all input samples was used for training procedure. Supervised classification was performed using individual learning algorithms including Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes (NB) and Neural Network (NN). A Stack model as an aggregated meta-learner of RF, SVM and NB was also assessed. Unless otherwise stated, a 5-fold cross-validation method was applied for sub-sampling of training and test data during the training procedure. Receiver-operating-characteristic (ROC) analysis was performed using the training results. Values of area-under-the curve (AUC) and classification accuracy (CA) were calculated to evaluate the performance of each classification model. CA refers to the proportion of correct predicted samples from the classification model compared to the original clinical diagnosis. Independent validation of classification models was performed using datasets of recently reported microbiome surveys of human diarrheal diseases that were not included in the training set. Each validation dataset was analyzed individually using Taxa4Meta pipeline to generate taxonomic profile data for validating classification models. CDI and IBD scores refer to the predicted scores of each sample as the class of CDI and IBD, respectively.

Statistical analysis: unless otherwise stated, comparisons between two groups were made using non-parametric Mann-Whitney-Wilcoxon two-tailed test, and comparisons for more than two groups were made using non-parametric Kruskal-Wallis two-tailed test. Multiple comparisons and pairwise Spearman or Pearson correlations were adjusted using the Benjamini-Hochberg (BH) false discovery rate (p<0.05, regarded as statistically significant).

Data availability: data accession numbers and reference to publicly available 16S datasets including training and validation datasets are listed in Table 21.

Code availability: the code for Taxa4Meta is available at https://github.com/qinglong89/Taxa4Meta. Benchmarking analyses and codes for amplicon data simulation and analysis, and the scripts of benchmarking analysis of different 16S pipelines can be accessed at https://github.com/qinglong89/Taxa4Meta-ParameterBenchmarking.

Example 2—Data Tables

TABLE 1

Disease-specific pathway features (metabolic pathway)

MetaCyc
Pathway
Abundance (median)

Pathway ID
description
CD
UC
CDI
Ctrl
IBS
Specificity

AST-PWY
L-arginine
163.46
22.28
504.16
13.06
12.32
CDI

degradation II

(AST pathway)

ECASYN-
enterobacterial
343.84
41.13
726.13
25.74
12.83
CDI

PWY
common antigen

biosynthesis

THREOCAT-
superpathway of
99.87
19.97
251.61
11.10
3.28
CDI

PWY
L-threonine

metabolism

PPGPPMET-
ppGpp
773.66
110.34
1396.50
62.07
82.71
CDI

PWY
biosynthesis

PWY0-1338
polymyxin
217.53
37.29
516.94
17.90
11.72
CDI

resistance

PWY-6263
superpathway of
223.72
2885.87
14.98
792.45
1229.92
UC

menaquinol-8

biosynthesis II

PWY-7371
1,4-dihydroxy-6-
78.11
1246.50
5.00
312.42
470.08
UC

naphthoate

biosynthesis II

PWY-7374
1,4-dihydroxy-6-
31.17
731.28
0.33
199.35
269.79
UC

naphthoate

biosynthesis I

P221-PWY
octane oxidation
945.76
2359.46
4.00
725.62
991.05
UC

PWY-6749
CMP-
2605.54
11572.94
443.55
3313.21
4371.99
UC

legionaminate

biosynthesis I

PWY-7456
mannan
11104.22
26108.29
1456.44
4288.02
7878.13
UC

degradation

NONMEVIPP-
methylerythritol
59111.79
101543.99
9563.19
17865.06
30036.41
IBD

PWY
phosphate

pathway I

PWY-5097
L-lysine
68211.98
113250.49
11456.24
20079.19
33973.70
IBD

biosynthesis VI

PWY-5505
L-glutamate and
45879.23
70219.69
5003.82
15125.30
21801.52
IBD

L-glutamine

biosynthesis

PWY-6122
5-aminoimidazole
65716.57
105563.32
11025.56
18871.61
31355.19
IBD

ribonucleotide

biosynthesis II

PWY-7663
gondoate
78634.26
118643.90
13238.23
20807.55
37675.48
IBD

biosynthesis

(anaerobic)

THRESYN-
superpathway of
65062.46
106314.58
10222.53
18718.10
31205.23
IBD

PWY
L-threonine

biosynthesis

HEMESYN2-
heme
6747.68
5529.64
2549.51
794.28
1432.83
IBD

PWY
biosynthesis II

(anaerobic)

PWY-5304
superpathway of
11101.08
18412.38
552.78
3885.00
5899.68
IBD

sulfur oxidation

(archaea)

PWY-6478
GDP-D-glycero-
5214.73
5706.07
627.92
1111.34
1992.51
IBD

alpha-D-manno-

heptose

biosynthesis

PWY-7198
pyrimidine
7291.60
8216.14
437.81
2364.29
3442.81
IBD

deoxyribonucleotides

de novo

biosynthesis IV

PWY-7210
pyrimidine
8669.00
10308.98
566.65
2882.09
4152.64
IBD

deoxyribonucleotides

biosynthesis

from CTP

CD = Crohn's Disease; UC = Ulcerative Colitis; CDI = Clostridiodes difficile Infection; Ctrl = Control; IBS = Irritable Bowel Syndrome; IBD = Inflammatory Bowel Disease.

TABLE 2

IBD vs IBS delineation features - (metabolic pathway)

FC

MetaCyc
Pathway
RFFR
IBD vs
Abundance (IBD)
Abundance (IBS)

Pathway ID
description
#
MDA
IBS
M
SD
DP
M
SD
DP

PWY-6876
isopropanol
1
0.016132
1.66
723.95
3230.75
0.89
435.82
1957.09
0.98

biosynthesis

PWY-5100
pyruvate
2
0.015964
4.67
135870.24
152815.93
1.00
29089.95
17522.28
1.00

fermentation to

acetate and

lactate II

PWY-7376
cob(II)yrinate
3
0.014280
1.18
67.09
1063.06
0.36
56.93
251.97
0.54

a,c-diamide

biosynthesis II

(late cobalt

incorporation)

PWY-5507
adenosylcobalamin
4
0.013715
4.85
368.53
1339.55
0.56
75.98
227.22
0.63

biosynthesis I

(early cobalt

insertion)

P381-PWY
adenosylcobalamin
5
0.012953
0.64
40.46
245.62
0.36
62.75
260.44
0.53

biosynthesis II

(late cobalt

incorporation)

PWY-5121
superpathway of
6
0.012701
4.54
127725.86
145558.38
1.00
28115.14
15593.29
1.00

geranylgeranyl

diphosphate

biosynthesis II

(via MEP)

PWY-6892
thiazole
7
0.011727
4.96
119155.10
141683.42
1.00
24004.43
15083.44
1.00

biosynthesis I

(E. coli)

ASPASN-
superpathway
8
0.011352
5.15
124206.27
151781.39
1.00
24106.22
15009.33
1.00

PWY
of L-aspartate

and L-

asparagine

biosynthesis

TYRFUMCAT-
L-tyrosine
9
0.011017
0.02
153.79
1444.97
0.64
8292.04
25541.88
0.71

PWY
degradation I

PWY-6122
5-aminoimidazole
10
0.010214
3.94
138322.07
155913.44
1.00
35079.61
17750.87
1.00

ribonucleotide

biosynthesis II

PWY-7431
aromatic
11
0.009966
0.14
125.58
1193.86
0.90
887.36
3722.68
0.97

biogenic amine

degradation

(bacteria)

PWY-7094
fatty acid
12
0.009691
0.09
833.48
3751.14
0.70
9353.82
28181.45
0.76

salvage

PWY-3781
aerobic
13
0.009635
0.24
4627.12
22834.50
0.87
18914.47
55652.73
0.97

respiration I

(cytochrome c)

PWY-7221
guanosine
14
0.009578
4.10
139893.46
161207.20
1.00
34118.96
16764.40
1.00

ribonucleotides

de novo

biosynthesis

PWY-6277
superpathway of
15
0.009356
3.94
138322.07
155913.44
1.00
35079.61
17750.87
1.00

5-aminoimidazole

ribonucleotide

biosynthesis

GALACT-
superpathway
16
0.009320
5.47
55138.14
73119.47
1.00
10083.39
6875.72
1.00

GLUCUROCAT-
of hexuronide

PWY
and hexuronate

degradation

THRESYN-
superpathway
17
0.009171
4.07
142354.23
163498.18
1.00
34985.56
17229.65
1.00

PWY
of L-threonine

biosynthesis

GLYCOCAT-
glycogen
18
0.008796
4.35
159288.63
184015.95
1.00
36577.81
20297.09
1.00

PWY
degradation I

(bacterial)

ANAEROFRUCAT-
homolactic
19
0.008761
5.05
113262.98
139978.58
1.00
22408.10
13981.72
1.00

PWY
fermentation

PWY-6609
adenine and
20
0.008691
4.46
121062.47
138331.24
1.00
27163.52
16702.31
1.00

adenosine

salvage III

DHGLUCONATE-
glucose
21
0.008217
18.85
55.86
1116.50
0.25
2.96
14.02
0.38

PYR-CAT-
degradation

PWY
(oxidative)

LEU-DEG2-
L-leucine
22
0.007897
0.08
535.70
4673.65
0.66
6338.85
19428.76
0.71

PWY
degradation I

PWY-5097
L-lysine
23
0.007734
3.93
147736.56
168639.95
1.00
37580.67
18590.79
1.00

biosynthesis VI

PWY-6317
galactose
24
0.007726
4.36
117717.50
139097.49
1.00
26969.73
17589.78
1.00

degradation I

(Leloir pathway)

PWY-6386
UDP-N-
25
0.007528
3.91
129151.67
145723.67
1.00
33067.64
16734.16
1.00

acetylmuramoyl-

pentapeptide

biosynthesis II

(lysine-

containing)

P4-PWY
superpathway
26
0.007027
4.79
58287.69
83243.88
1.00
12169.85
8822.67
1.00

of L-lysine, L-

threonine and

L-methionine

biosynthesis I

GLUCUROCAT-
superpathway
27
0.006872
5.77
57309.57
88753.82
1.00
9930.86
6803.57
1.00

PWY
of β-D-

glucuronide

and D-

glucuronate

degradation

PWY0-781
aspartate
28
0.006856
5.28
50130.99
78655.15
1.00
9493.70
7322.25
1.00

superpathway

ANAGLYCOLYSIS-
glycolysis III
29
0.006699
3.97
157412.87
180880.09
1.00
39616.54
19547.45
1.00

PWY
(from glucose)

PWY-6123
inosine-5′-
30
0.006625
4.01
134834.30
154332.32
1.00
33605.59
16812.37
1.00

phosphate

biosynthesis I

PWY-6121
5-aminoimidazole
31
0.006358
3.97
143511.57
164255.51
1.00
36122.21
18777.40
1.00

ribonucleotide

biosynthesis I

PWY-5384
sucrose
32
0.006001
4.90
59115.62
90240.55
1.00
12053.55
10048.97
1.00

degradation IV

(sucrose

phosphorylase)

PWY-7222
guanosine
33
0.005852
4.40
171855.93
208910.59
1.00
39037.26
21505.96
1.00

deoxyribonucleotides

de novo

biosynthesis II

PWY-7242
D-fructuronate
34
0.005446
5.36
108556.86
147295.93
1.00
20258.95
12667.63
1.00

degradation

GOLPDLCAT-
superpathway
35
0.005324
7.27
1469.95
8316.20
0.99
202.18
432.68
0.94

PWY
of glycerol

degradation to

1,3-propanediol

PWY-7013
L-1,2-
36
0.005199
6.66
7931.24
30707.40
1.00
1190.11
2808.39
0.93

propanediol

degradation

P124-PWY
Bifidobacterium
37
0.005185
8.11
19432.49
42956.35
1.00
2397.16
3856.49
1.00

shunt

PWY-6385
peptidoglycan
38
0.004984
3.91
127516.72
144162.90
1.00
32618.20
16544.58
1.00

biosynthesis III

(mycobacteria)

PWY-5347
superpathway of
39
0.004923
4.75
71487.80
98197.58
1.00
15051.58
11206.66
1.00

L-methionine

biosynthesis

(transsulfuration)

PWY-5104
L-isoleucine
40
0.004904
3.76
152215.73
17370.58
1.00
40466.33
21816.16
1.00

biosynthesis IV

P122-PWY
heterolactic
41
0.004838
8.05
15419.45
34825.46
1.00
1916.48
3035.80
1.00

fermentation

PWY-3801
sucrose
42
0.004829
0.24
91.32
1509.62
0.44
383.94
1773.17
0.35

degradation II

(sucrose synthase)

PEPTIDOGLYCANSYN-
peptidoglycan
43
0.004794
3.91
128456.44
145009.61
1.00
32818.46
16611.34
1.00

PWY
biosynthesis I

(meso-

diaminopimelate

containing)

RIBOSYN2-
flavin
44
0.004780
3.90
111745.27
131737.59
1.00
28641.46
15772.99
1.00

PWY
biosynthesis I

(bacteria and

plants)

TRNA-CHARGING-
tRNA charging
45
0.004768
3.90
130149.53
147343.38
1.00
33409.36
17003.72
1.00

PWY

PWY-7392
taxadiene
46
0.004744
4.98
23059.64
39103.88
1.00
4630.54
5243.38
1.00

biosynthesis

(engineered)

REDCITCYC
TCA cycle VIII
47
0.004735
9.15
18764.13
66020.56
1.00
2049.65
5087.08
1.00

(helicobacter)

PWY-2942
L-lysine
48
0.004597
3.97
150432.02
171583.96
1.00
37924.77
18778.14
1.00

biosynthesis III

PWY-6897
thiamin
49
0.004530
3.68
109681.12
128458.10
1.00
29830.89
20011.30
1.00

salvage II

PWY-7663
gondoate
50
0.004456
4.16
179634.67
214427.08
1.00
43224.23
21636.87
1.00

biosynthesis

(anaerobic)

TRPSYN-
L-tryptophan
51
0.004398
3.88
115192.82
136948.27
1.00
29664.21
16817.20
1.00

PWY
biosynthesis

PWY-6387
UDP-N-
52
0.004364
3.92
129174.34
145705.81
1.00
32982.38
16688.93
1.00

acetylmuramoyl-

pentapeptide

biosynthesis I

(meso-

diaminopimelate

containing)

PWY-621
sucrose
53
0.004344
4.44
128851.46
156513.66
1.00
29024.02
20621.37
1.00

degradation III

(sucrose invertase)

DENOVOPURINE2-
superpathway of
54
0.004273
5.42
106393.82
136843.29
1.00
19628.63
13926.57
1.00

PWY
purine nucleotides

de novo

biosynthesis II

PWY-7539
6-hydroxymethyl-
55
0.004264
3.83
108766.15
131626.36
1.00
28384.93
19568.26
1.00

dihydropterin

diphosphate

biosynthesis III

(Chlamydia)

PWY-6147
6-hydroxymethyl-
56
0.004173
3.80
105610.99
126859.73
1.00
27827.44
19724.99
1.00

dihydropterin

diphosphate

biosynthesis I

GLUCARGALACTSUPER-
superpathway
57
0.004170
9.76
4466.91
21210.22
0.99
457.74
911.54
1.00

PWY
of D-glucarate

and D-galactarate

degradation

COA-PWY
coenzyme A
58
0.004159
3.92
123757.36
139748.39
1.00
31573.49
15899.61
1.00

biosynthesis I

GALACTARDEG-
D-galactarate
59
0.004147
9.76
4466.91
21210.22
0.99
457.74
911.54
1.00

PWY
degradation I

PWY-7220
adenosine
60
0.004002
4.40
171855.93
208910.59
1.00
39037.26
21505.96
1.00

deoxyribonucleotides

de novo

biosynthesis II

PWY-5973
cis-vaccenate
61
0.003973
4.04
161442.82
191518.09
1.00
39974.77
20024.39
1.00

biosynthesis

PWY-6891
thiazole
62
0.003908
7.07
29308.66
58392.26
1.00
4147.43
4624.29
1.00

biosynthesis II

(Bacillus)

GLUTORN-
L-ornithine
63
0.003844
3.53
98956.14
117099.43
1.00
28029.94
21071.03
1.00

PWY
biosynthesis

PWY-7560
methylerythritol
64
0.003834
3.92
134182.83
154729.56
1.00
34272.25
17397.13
1.00

phosphate

pathway II

PANTO-
phosphopantothenate
65
0.003824
3.75
102917.05
125172.63
1.00
27427.71
17827.49
1.00

PWY
biosynthesis I

PWY0-
superpathway
66
0.003812
4.19
70319.66
91976.78
1.00
16778.62
11799.80
1.00

1297
of purine

deoxyribonucleosides

degradation

PWY-7208
superpathway
67
0.003802
3.81
146949.20
165685.83
1.00
38548.99
20856.81
1.00

of pyrimidine

nucleobases

salvage

PWY-181
photorespiration
68
0.003727
1.86
260.96
3493.16
0.55
140.42
530.40
0.58

NONMEVIPP-
methylerythritol-
69
0.003667
3.92
134182.83
154729.56
1.00
34272.25
17397.13
1.00

PWY
phosphate

pathway I

FUC-RHAMCAT-
superpathway
70
0.003625
5.03
30651.10
41677.69
1.00
6087.89
4750.90
1.00

PWY
of fucose and

rhamnose

degradation

PWY-6895
superpathway
71
0.003621
6.13
51188.48
76665.18
1.00
8355.66
7332.84
1.00

of thiamin

diphosphate

biosynthesis II

ARGORNPROST-
arginine,
72
0.003543
4.02
5675.54
8978.45
1.00
1410.86
2008.22
1.00

PWY
ornithine and

proline

interconversion

PWY-6703
preQ0
73
0.003505
3.89
82160.52
110131.25
1.00
21142.14
17391.99
1.00

biosynthesis

PWY-7219
adenosine
74
0.003491
3.92
150642.61
171191.32
1.00
38393.50
19673.06
1.00

ribonucleotides

de novo

biosynthesis

FOLSYN-
superpathway of
75
0.003452
4.00
115361.09
138014.61
1.00
28875.19
16869.28
1.00

PWY
tetrahydrofolate

biosynthesis

and salvage

PWY0-41
allantoin
76
0.003451
15.37
3484.63
18488.68
0.99
226.74
473.49
0.93

degradation IV

(anaerobic)

PYRIDNUCSYN-
NAD
77
0.003421
3.88
111276.25
130486.87
1.00
28698.20
15283.44
1.00

PWY
biosynthesis I

(from aspartate)

PWY-7229
superpathway
78
0.003373
4.02
157364.23
181723.85
1.00
39152.22
20656.79
1.00

of adenosine

nucleotides de

novo

biosynthesis I

PWY-6737
starch
79
0.003316
4.04
187661.83
223111.56
1.00
46433.64
24911.85
1.00

degradation V

P221-PWY
octane oxidation
80
0.003294
3.00
5761.91
12779.90
0.97
1918.80
2782.48
0.94

PWY-5188
tetrapyrrole
81
0.003292
2.76
48681.91
67878.32
1.00
17660.45
15639.69
1.00

biosynthesis I

(from glutamate)

PWY-7199
pyrimidine
82
0.003273
5.15
91237.42
116483.90
1.00
17703.08
11591.36
1.00

deoxyribonucleosides

salvage

GLYCOGENSYNTH-
glycogen
83
0.003266
3.47
131973.83
153409.27
1.00
38040.27
19979.74
1.00

PWY
biosynthesis I

(from ADP-D-

Glucose)

VALDEG-
L-valine
84
0.003235
11.83
36.29
189.04
0.39
3.07
23.73
0.18

PWY
degradation I

P164-PWY
purine
85
0.003099
3.91
31488.58
50403.11
1.00
8061.70
6927.39
1.00

nucleobases

degradation I

(anaerobic)

PWY-6471
peptidoglycan
86
0.003092
4.06
47677.60
63879.56
1.00
11749.05
9689.53
1.00

biosynthesis IV

(Enterococcus

faecium)

P441-PWY
superpathway of
87
0.003085
4.80
48761.56
68746.80
1.00
10157.31
8805.55
1.00

N-acetylneuraminate

degradation

PWY-6163
chorismate
88
0.003063
3.75
136555.50
153849.19
1.00
36411.39
19257.17
1.00

biosynthesis

from 3-

dehydroquinate

PWY-7187
pyrimidine
89
0.003060
5.06
69465.91
89894.29
1.00
13715.69
9154.58
1.00

deoxyribonucleotides

de novo

biosynthesis II

PWY0-
methylphosphonate
90
0.003047
21.15
9321.47
52007.08
0.99
440.83
961.71
1.00

1533
degradation I

PWY-7332
superpathway
91
0.003044
2.20
4098.00
13921.69
0.98
1866.86
3130.64
0.99

of UDP-N-

acetylglucosamine-

derived O-antigen

building blocks

biosynthesis

CALVIN-
Calvin-
92
0.003036
3.73
156447.97
176810.12
1.00
41919.47
23350.92
1.00

PWY
Benson-

Bassham cycle

PWY-3001
superpathway
93
0.003021
3.93
144728.31
165925.82
1.00
36808.04
19082.06
1.00

of L-isoleucine

biosynthesis I

GLCMANNANAUT-
superpathway of
94
0.003016
3.98
55949.28
66026.69
1.00
14050.92
9665.99
1.00

PWY
N-acetylglucosamine,

N-acetylmannosamine

and N-acetylneuraminate

degradation

PWY-6263
superpathway
95
0.002974
3.51
7706.21
15896.50
0.95
2196.54
3113.85
0.95

of menaquinol-

8 biosynthesis II

P562-PWY
myo-inositol
96
0.002962
1.27
9881.76
42205.37
1.00
7805.01
18297.70
1.00

degradation I

PWY-5686
UMP
97
0.002937
3.82
146755.20
166508.73
1.00
38378.86
20600.14
1.00

biosynthesis

PWY-6126
superpathway
98
0.002929
4.02
150054.04
173856.36
1.00
37349.40
19833.46
1.00

of adenosine

nucleotides de

novo

biosynthesis II

PWY-5531
chlorophyllide
99
0.002923
0.40
16.30
94.77
0.42
40.43
387.08
0.45

a biosynthesis

II (anaerobic)

GLUCARDEG-
D-glucarate
100
0.002911
6.88
4907.86
21407.69
1.00
713.12
954.82
1.00

PWY
degradation I

IBD = Inflammatory Bowel Disease;

IBS = Irritable Bowel Syndrome;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 3

IBD vs CDI delineation features - (metabolic pathway)

FC

MetaCyc
Pathway
RFFR
IBD
Abundance (IBD)
Abundance (CDI)

Pathway ID
description
#
MDA
vs CDI
M
SD
DP
M
SD
DP

PWY-6151
S-adenosyl-L-
1
0.022939
11.44
107683.22
124365.32
1.00
9411.61
7522.84
1.00

methionine

cycle I

P221-PWY
octane oxidation
2
0.021292
16.52
5761.91
12779.90
0.97
348.70
1946.70
0.61

PWY-5505
L-glutamate and
3
0.020324
13.15
96135.88
117872.52
1.00
7310.25
7222.51
1.00

L-glutamine

biosynthesis

PWY-5121
superpathway of
4
0.019277
11.33
127725.86
145558.38
1.00
11275.00
9094.58
1.00

geranylgeranyl

diphosphate

biosynthesis II

(via MEP)

GLYCOGENSYNTH-
glycogen
5
0.017609
11.84
131973.83
153409.27
1.00
11149.92
9865.46
1.00

PWY
biosynthesis I

(from ADP-D-

Glucose)

NONMEVIPP-
methylerythritol
6
0.017089
11.41
134182.83
154729.56
1.00
11765.12
9593.11
1.00

PWY
phosphate

pathway I

PWY-6269
adenosylcobalamin
7
0.016927
11.30
98727.92
112284.20
1.00
8739.20
7664.91
1.00

salvage from

cobinamide II

PYRIDNUCSYN-
NAD
8
0.014565
12.04
111276.25
130486.87
1.00
9244.66
7697.40
1.00

PWY
biosynthesis I

(from aspartate)

COA-PWY
coenzyme A
9
0.014128
10.61
123757.36
139748.39
1.00
11669.39
8761.12
1.00

biosynthesis I

PWY-5686
UMP
10
0.012670
10.63
146755.20
166508.73
1.00
13799.67
10365.94
1.00

biosynthesis

PWY-7560
methylerythritol
11
0.012584
11.41
134182.83
154729.56
1.00
11765.12
9593.11
1.00

phosphate

pathway II

PWY-6386
UDP-N-
12
0.012251
10.49
129151.67
145723.67
1.00
12310.17
9381.48
1.00

acetylmuramoyl-

pentapeptide

biosynthesis II

(lysine-containing)

PWY-6277
superpathway of
13
0.011979
10.45
138322.07
155913.44
1.00
13242.31
10142.08
1.00

5-aminoimidazole

ribonucleotide

biosynthesis

PWY-5509
adenosylcobalamin
14
0.011397
11.34
98134.29
111713.94
1.00
8656.86
7613.93
1.00

biosynthesis from

cobyrinate a,c-

diamide I

PWY-7219
adenosine
15
0.010926
10.56
150642.61
171191.32
1.00
14262.17
10745.91
1.00

ribonucleotides

de novo

biosynthesis

COBALSYN-
adenosylcobalamin
16
0.010834
10.70
101783.99
114902.71
1.00
9508.59
8221.80
1.00

PWY
salvage from

cobinamide I

PWY-6163
chorismate
17
0.010562
10.79
136555.50
153849.19
1.00
12651.08
9738.48
1.00

biosynthesis

from 3-

dehydroquinate

PWY-5861
superpathway of
18
0.010286
4.23
16460.72
52245.15
1.00
3894.44
4510.05
0.99

demethylmenaquinol-

8 biosynthesis

PWY-6123
inosine-5′-
19
0.010226
10.67
134834.30
154332.32
1.00
12632.90
9679.61
1.00

phosphate

biosynthesis I

PWY-5837
1,4-dihydroxy-
20
0.010086
4.03
12463.62
49647.52
1.00
3094.02
3998.36
1.00

2-naphthoate

biosynthesis I

PWY-5863
superpathway
21
0.010056
4.04
13008.58
49499.71
1.00
3219.88
3983.44
1.00

of phylloquinol

biosynthesis

GLYCOCAT-
glycogen
22
0.009741
11.42
159288.63
184015.95
1.00
13942.78
11948.63
1.00

PWY
degradation I

(bacterial)

ARO-PWY
chorismate
23
0.009344
10.36
130093.56
146728.47
1.00
12557.51
9830.31
1.00

biosynthesis I

PWY-5897
superpathway
24
0.009053
4.31
17927.39
53168.30
1.00
4162.12
4654.22
1.00

of menaquinol-

11 biosynthesis

PWY-6317
galactose
25
0.008715
10.53
117717.50
139097.49
1.00
11183.74
9380.07
1.00

degradation I

(Leloir pathway)

PWY-5840
superpathway
26
0.008484
4.41
18365.80
52805.78
1.00
4165.06
4482.90
1.00

of menaquinol-

7 biosynthesis

PWY-5097
L-lysine
27
0.008451
10.58
147736.56
168639.95
1.00
13962.57
10737.14
1.00

biosynthesis VI

PWY-6385
peptidoglycan
28
0.008358
10.42
127516.72
144162.90
1.00
12234.28
9272.55
1.00

biosynthesis III

(mycobacteria)

COMPLETE-ARO-
superpathway
29
0.008283
10.41
136769.77
154592.26
1.00
13134.09
10317.24
1.00

PWY
of aromatic

amino acid

biosynthesis

PWY-6892
thiazole
30
0.008222
12.69
119155.10
141683.42
1.00
9387.20
7923.11
1.00

biosynthesis I

(E. coli)

PEPTIDOGLYCANSYN-
peptidoglycan
31
0.007798
10.38
128456.44
145009.61
1.00
12377.64
9359.46
1.00

PWY
biosynthesis I

(meso-

diaminopimelate

containing)

PWY-6122
5-aminoimidazole
32
0.007775
10.45
138322.07
155913.44
1.00
13242.31
10142.08
1.00

ribonucleotide

biosynthesis II

PWY-5899
superpathway
33
0.007749
4.31
17927.39
53168.30
1.00
4162.12
4654.22
1.00

of menaquinol-

13 biosynthesis

PYRIDNUCSAL-
NAD salvage
34
0.007732
12.01
114532.43
133167.55
1.00
9539.35
8058.22
1.00

PWY
pathway I

PWY-5838
superpathway
35
0.007583
4.37
18629.77
53691.09
1.00
4262.18
4746.55
0.99

of menaquinol-

8 biosynthesis I

PWY-5667
CDP-
36
0.007056
10.07
145849.97
165605.02
1.00
14479.76
11114.39
1.00

diacylglycerol

biosynthesis I

PWY0-
methylphosphonate
37
0.007041
3.60
9321.47
52007.08
0.99
2590.86
3843.40
1.00

1533
degradation I

PWY-6387
UDP-N-
38
0.006878
10.33
129174.34
145705.81
1.00
12506.69
9467.25
1.00

acetylmuramoyl-

pentapeptide

biosynthesis I

(meso-

diaminopimelate

containing)

TRNA-CHARGING-
tRNA charging
39
0.006824
10.43
130149.53
147343.38
1.00
12475.49
9660.68
1.00

PWY

PWY-5100
pyruvate
40
0.006692
10.51
135870.24
152815.93
1.00
12921.80
9801.95
1.00

fermentation to

acetate and

lactate II

PWY-7663
gondoate
41
0.006475
10.95
179634.67
214427.08
1.00
16407.13
12555.92
1.00

biosynthesis

(anaerobic)

PWY-5104
L-isoleucine
42
0.006468
11.05
152215.73
173701.58
1.00
13779.72
11296.81
1.00

biosynthesis IV

PWY-5973
cis-vaccenate
43
0.006339
10.67
161442.82
191518.09
1.00
15125.38
11673.99
1.00

biosynthesis

PWY-5898
superpathway
44
0.006194
4.31
17927.39
53168.30
1.00
4162.12
4654.22
1.00

of menaquinol-

12 biosynthesis

PWY0-
CDP-
45
0.006165
10.07
145849.97
165605.02
1.00
14479.76
11114.39
1.00

1319
diacylglycerol

biosynthesis II

PWY-7221
guanosine
46
0.006083
10.56
139893.46
161207.20
1.00
13250.25
10071.10
1.00

ribonucleotides

de novo

biosynthesis

PWY4FS-8
phosphatidylglycerol
47
0.005787
9.66
118520.55
138335.79
1.00
12271.48
9713.41
1.00

biosynthesis II

(non-plastidic)

PWY-6737
starch
48
0.005476
12.22
187661.83
223111.56
1.00
15361.05
13716.01
1.00

degradation V

PWY-3001
superpathway
49
0.005435
10.91
144728.31
165925.82
1.00
13263.33
10722.63
1.00

of L-isoleucine

biosynthesis I

HISTSYN-
L-histidine
50
0.005147
11.62
125494.23
146173.13
1.00
10804.07
8915.40
1.00

PWY
biosynthesis

PWY-7208
superpathway
51
0.005014
10.30
146949.20
165685.83
1.00
14263.75
10855.98
1.00

of pyrimidine

nucleobases

salvage

PHOSLIPSYN-
superpathway of
52
0.004984
9.85
132254.48
15309.74
1.00
13420.46
10360.64
1.00

PWY
phospholipid

biosynthesis I

(bacteria)

PWY-6121
5-aminoimidazole
53
0.004984
10.53
143511.57
164255.51
1.00
13634.17
10455.30
1.00

ribonucleotide

biosynthesis I

PWY-2942
L-lysine
54
0.004862
10.45
150432.02
171583.96
1.00
14401.68
11021.52
1.00

biosynthesis III

PWY-5850
superpathway
55
0.004651
4.37
13692.01
50596.90
0.99
3131.89
4208.09
0.98

of menaquinol-

6 biosynthesis I

SER-GLYSYN-
superpathway
56
0.004639
10.88
127879.50
145388.75
1.00
11750.83
10070.81
1.00

PWY
of L-serine and

glycine

biosynthesis I

AEROBACTINSYN-
aerobactin
57
0.004630
10.50
1057.02
12646.97
0.66
100.68
344.92
0.76

PWY
biosynthesis

PWY-5860
superpathway of
58
0.004627
4.37
12152.27
49430.15
0.99
2779.78
3938.60
0.98

demethylmenaquinol-

6 biosynthesis I

PWY-6126
superpathway
59
0.004418
10.19
150054.04
173856.36
1.00
14721.48
11085.79
1.00

of adenosine

nucleotides de

novo

biosynthesis II

DAPLYSINESYN-
L-lysine
60
0.004098
9.47
96805.58
114220.94
1.00
10219.74
8756.71
1.00

PWY
biosynthesis I

NONOXIPENT-
pentose phosphate
61
0.004084
9.82
193969.86
231579.44
1.00
19746.16
15361.51
1.00

PWY
pathway (non-

oxidative branch)

PWY-5862
superpathway of
62
0.004033
4.37
12153.96
49429.80
0.99
2779.78
3938.60
0.98

demethylmenaquinol-

9 biosynthesis

BRANCHED-
superpathway
63
0.003957
10.75
144717.57
166226.20
1.00
13457.08
11094.56
1.00

CHAIN-
of branched

AA-SYN-PWY
amino acid

biosynthesis

PWY-5845
superpathway
64
0.003895
4.37
13694.42
50596.39
0.99
3131.89
4208.09
0.98

of menaquinol-

9 biosynthesis

PWY-7229
superpathway
65
0.003788
10.20
157364.23
181723.85
1.00
15431.50
11650.85
1.00

of adenosine

nucleotides de

novo

biosynthesis I

ARGSYNBSUB-
L-arginine
66
0.003781
10.18
87902.52
107302.81
1.00
8634.15
7616.24
1.00

PWY
biosynthesis II

(acetyl cycle)

VALSYN-
L-valine
67
0.003573
10.56
152045.37
173516.28
1.00
14398.84
11832.67
1.00

PWY
biosynthesis

PROTOCATECHUATE-
protocatechuate
68
0.003571
2.74
1541.18
13248.14
0.78
563.24
1894.30
0.81

ORTHO-
degradation II

CLEAVAGE-PWY
(ortho-cleavage

pathway)

ILEUSYN-
L-isoleucine
69
0.003556
10.56
152045.37
173516.28
1.00
14398.84
11832.67
1.00

PWY
biosynthesis I

(from threonine)

1CMET2-
N10-formyl-
70
0.003516
10.82
125376.15
144992.96
1.00
11590.50
9125.00
1.00

PWY
tetrahydrofolate

biosynthesis

GALLATE-
gallate
71
0.003490
6.55
327.66
5244.51
0.40
50.04
171.58
0.62

DEGRADATION-
degradation I

II-PWY

3-
4-
72
0.003424
14.69
7016.55
47433.58
0.83
477.80
1818.62
0.89

HYDROXYPHENYLACETATE-
hydroxyphenylacetate

DEGRADATION-PWY
degradation

METHYLGALLATE-
methylgallate
73
0.003355
6.70
416.35
6281.48
0.53
62.13
211.04
0.64

DEGRADATION-PWY
degradation

PWY-5896
superpathway
74
0.003350
4.37
13692.01
50596.90
0.99
3131.89
4208.09
0.98

of menaquinol-

10 biosynthesis

PPGPPMET-
ppGpp
75
0.003332
4.26
13669.70
58706.41
0.96
3209.93
4853.66
0.96

PWY
biosynthesis

ALL-
superpathway
76
0.003329
4.37
13199.81
55694.03
0.93
3017.70
4247.08
0.95

CHORISMATE-
of chorismate

PWY
metabolism

PWY-7400
L-arginine
77
0.003315
10.39
94035.64
110597.42
1.00
9053.26
7680.28
1.00

biosynthesis IV

(archaebacteria)

THRESYN-
superpathway
78
0.003298
10.96
142354.23
163498.18
1.00
12990.68
10283.94
1.00

PWY
of L-threonine

biosynthesis

DENOVOPURINE2-
superpathway of
79
0.003294
9.33
106393.82
136843.29
1.00
11398.08
9115.62
1.00

PWY
purine nucleotides

de novo

biosynthesis II

ARGSYN-
L-arginine
80
0.003257
10.36
93779.91
110424.01
1.00
9052.44
7686.03
1.00

PWY
biosynthesis I

(via L-ornithine)

PWY-7210
pyrimidine
81
0.003243
9.87
17450.16
22166.30
0.99
1768.37
2590.34
0.92

deoxyribonucleotides

biosynthesis

from CTP

GLUCARDEG-
D-glucarate
82
0.003177
2.22
4907.86
21407.69
1.00
2209.18
3044.60
0.99

PWY
degradation I

PWY-7198
pyrimidine
83
0.003093
9.75
14466.52
18873.23
0.99
1483.19
2294.17
0.92

deoxyribonucleotides

de novo

biosynthesis IV

POLYAMINSYN3-
superpathway
84
0.003047
11.06
12425.67
20513.46
1.00
1123.63
1443.18
1.00

PWY
of polyamine

biosynthesis II

PWY4FS-7
phosphatidylglycerol
85
0.003018
9.66
118520.55
138335.79
1.00
12271.48
9713.41
1.00

biosynthesis I

(plastidic)

PWY0-166
superpathway of
86
0.002971
8.20
67662.59
88147.86
1.00
8253.14
6687.14
1.00

pyrimidine

deoxyribonucleotides

de novo

biosynthesis

(E. coli)

GALLATE-
gallate
87
0.002955
6.84
343.14
5245.90
0.53
50.17
171.78
0.64

DEGRADATION-I-
degradation II

PWY

PWY-5181
toluene
88
0.002921
4.52
1307.02
11902.37
0.72
289.01
672.79
0.78

degradation III

(aerobic) (via

p-cresol)

GLUCOSE1PMETAB-
glucose and
89
0.002879
4.60
15548.88
53407.74
0.99
3377.19
4632.05
0.98

PWY
glucose-1-

phosphate

degradation

CALVIN-
Calvin-
90
0.002853
9.87
156447.97
176810.12
1.00
15850.71
12125.61
1.00

PWY
Benson-

Bassham cycle

PANTOSYN-
pantothenate
91
0.002826
11.18
107386.72
127772.17
1.00
9601.39
7781.20
1.00

PWY
and coenzyme

A biosynthesis I

PWY-5484
glycolysis II
92
0.002816
9.81
126725.58
161436.81
1.00
12922.99
10052.31
1.00

(from fructose

6-phosphate)

PWY-5417
catechol
93
0.002813
1.73
540.85
6287.09
0.71
313.16
1142.85
0.79

degradation III

(ortho-cleavage

pathway)

PWY-7184
pyrimidine
94
0.002806
7.71
58848.19
82997.79
1.00
7634.11
6451.00
1.00

deoxyribonucleotides

de novo

biosynthesis I

HEMESYN2-
heme
95
0.002799
6.64
29068.34
65254.98
1.00
4380.26
5254.43
1.00

PWY
biosynthesis II

(anaerobic)

PWY-6182
superpathway
96
0.002709
2.17
489.00
6089.83
0.70
225.23
534.94
0.78

of salicylate

degradation

PWY-6906
chitin
97
0.002685
0.83
84.08
256.80
0.69
100.73
367.28
0.65

derivatives

degradation

PWY-3781
aerobic
98
0.002668
3.39
4627.12
22834.50
0.87
1366.89
6073.16
0.89

respiration I

(cytochrome c)

ARGORNPROST-
arginine,
99
0.002656
3.11
5675.54
8978.45
1.00
1826.62
2647.27
1.00

PWY
ornithine and

proline

interconversion

POLYISOPRENSYN-
polyisoprenoid
100
0.002655
9.57
92086.27
118040.44
1.00
9617.67
7682.53
1.00

PWY
biosynthesis

(E. coli)

IBD = Inflammatory Bowel Disease;

CDI = Clostridiodes difficile Infection;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 4

IBD (Ulcerative Colitis) vs Control delineation features - (metabolic pathway)

MetaCyc
Pathway
RFFR
FC
Abundance (UC)
Abundance (Ctrl)

Pathway ID
description
#
MDA
UC vs Ctrl
M
SD
DP
M
SD
DP

PWY-5484
glycolysis II
1
0.013468
5.34
137874.28
163049.92
1.00
25795.46
58601.44
1.00

(from fructose

6-phosphate)

PWY-7220
adenosine
2
0.012501
5.02
187150.53
217714.47
1.00
37306.88
84124.81
1.00

deoxyribonucleotides

de novo

biosynthesis II

DTDPRHAMSYN-
dTDP-L-
3
0.012165
5.39
189125.72
234912.05
1.00
35109.82
75193.40
1.00

PWY
rhamnose

biosynthesis I

GLUCONEO-
gluconeogenesis I
4
0.011578
5.19
143219.37
167868.16
1.00
27620.28
63540.87
1.00

PWY

PWY-7222
guanosine
5
0.010944
5.02
187150.53
217714.47
1.00
37306.88
84124.81
1.00

deoxyribonucleotides

de novo

biosynthesis II

PWY-6737
starch
6
0.010427
4.97
216898.43
245631.54
1.00
43660.03
89100.84
1.00

degradation V

GLYCOLYSIS
glycolysis I
7
0.009969
5.00
151732.58
173723.01
1.00
30345.44
65251.30
1.00

(from glucose

6-phosphate)

FERMENTATION-
mixed acid
8
0.009004
4.81
87462.44
101627.24
1.00
18196.38
37540.58
1.00

PWY
fermentation

RIBOSYN
flavin
9
0.007731
4.85
124769.36
141377.01
1.00
25710.38
56666.93
1.00

2-PWY
biosynthesis I

(bacteria and

plants)

ANAEROFRUCAT-
homolactic
10
0.007429
4.67
121247.42
135856.30
1.00
25969.53
52349.57
1.00

PWY
fermentation

POLYISOPRENSYN-
polyisoprenoid
11
0.007394
5.57
103349.13
126047.74
1.00
18570.50
48260.04
1.00

PWY
biosynthesis

(E. coli)

PWY-6969
TCA cycle V (2-
12
0.007367
6.00
123707.97
159065.04
1.00
20619.10
56313.80
1.00

oxoglutarate:ferredoxin

oxidoreductase)

THRESYN-
superpathway
13
0.006838
4.68
158299.07
173526.15
1.00
33804.17
69499.08
1.00

PWY
of L-threonine

biosynthesis

PWY-7221
guanosine
14
0.006629
4.66
155880.21
170218.31
1.00
33485.60
67311.36
1.00

ribonucleotides

de novo

biosynthesis

PENTOSE-P-
pentose
15
0.006569
6.35
94692.24
125567.44
1.00
14915.57
40468.42
1.00

PWY
phosphate

pathway

PWY-5973
cis-vaccenate
16
0.006501
4.80
180359.77
202158.96
1.00
37597.57
77633.61
1.00

biosynthesis

PWY-5097
L-lysine
17
0.006420
4.52
163088.19
175254.73
1.00
36065.98
71069.75
1.00

biosynthesis VI

PWY-5971
palmitate
18
0.006350
5.13
66234.32
96843.59
1.00
12902.75
46991.68
1.00

biosynthesis II

(bacteria and

plants)

HISTSYN-
L-histidine
19
0.006209
4.69
143551.66
158396.25
1.00
30588.45
60932.50
1.00

PWY
biosynthesis

PWY-7200
superpathway
20
0.005995
4.91
64690.73
76056.16
1.00
13163.34
32475.36
1.00

of pyrimidine

deoxyribonucleoside

salvage

PWY-6126
superpathway
21
0.005993
4.68
166511.68
182033.40
1.00
35557.29
73657.90
1.00

of adenosine

nucleotides de

novo

biosynthesis II

PWY0-
anhydromuropeptides
22
0.005971
4.76
49694.18
70536.52
1.00
10433.27
26429.41
1.00

1261
recycling

TRNA-
tRNA charging
23
0.005964
4.50
144826.75
155388.02
1.00
32210.70
64009.96
1.00

CHARGING-PWY

PWY-5101
L-isoleucine
24
0.005927
4.50
183959.02
197410.19
1.00
40907.22
78658.73
1.00

biosynthesis II

PYRIDNUCSAL-
NAD salvage
25
0.005849
4.67
128877.76
142195.58
1.00
27573.47
56793.93
1.00

PWY
pathway I

PWY-6471
peptidoglycan
26
0.005815
3.66
56783.16
62569.90
1.00
15517.50
26202.50
1.00

biosynthesis IV

(Enterococcus

faecium)

PWY-7199
pyrimidine
27
0.005786
5.14
105140.04
125489.97
1.00
20465.73
48211.04
1.00

deoxyribonucleosides

salvage

PWY-6901
superpathway
28
0.005719
5.79
93437.75
115918.50
1.00
16138.44
42305.62
1.00

of glucose and

xylose

degradation

PWY-6612
superpathway of
29
0.005486
4.77
113726.13
128397.78
1.00
23842.31
53794.55
1.00

tetrahydrofolate

biosynthesis

PWY-7229
superpathway
30
0.005395
4.68
174435.87
190236.65
1.00
37269.82
76809.15
1.00

of adenosine

nucleotides de

novo

biosynthesis I

PWY-5265
peptidoglycan
31
0.005341
3.50
958.53
3382.00
0.89
273.60
1410.22
0.80

biosynthesis II

(staphylococci)

BRANCHED-
superpathway
32
0.005160
4.51
161266.67
173339.12
1.00
35733.57
69393.77
1.00

CHAIN-AA-
of branched

SYN-PWY
amino acid

biosynthesis

PWY-5659
GDP-mannose
33
0.005106
5.15
111981.31
134669.98
1.00
21758.46
52092.19
1.00

biosynthesis

PWY-6123
inosine-5′-
34
0.005059
4.64
151796.28
166324.65
1.00
32731.91
67616.56
1.00

phosphate

biosynthesis I

PWY-3001
superpathway
35
0.005059
4.62
161565.25
175615.84
1.00
34993.92
70100.63
1.00

of L-isoleucine

biosynthesis I

PWY-2942
L-lysine
36
0.004924
4.56
166999.88
179907.40
1.00
36593.12
72497.97
1.00

biosynthesis III

PWY-5695
urate
37
0.004904
5.09
129768.00
151875.33
1.00
25478.81
61554.77
1.00

biosynthesis/

inosine 5′-

phosphate

degradation

PWY-7456
mannan
38
0.004826
6.37
59391.38
79508.41
0.99
9327.98
25079.05
0.99

degradation

FOLSYN-
superpathway of
39
0.004747
4.80
125689.08
141712.00
1.00
26199.43
57898.05
1.00

PWY
tetrahydrofolate

biosynthesis

and salvage

VALDEG-
L-valine
40
0.004739
5.79
48.88
214.52
0.39
8.44
70.49
0.24

PWY
degradation I

ANAGLYCOLYSIS-
glycolysis III
41
0.004500
4.52
173969.55
188915.73
1.00
38524.25
76074.72
1.00

PWY
(from glucose)

PWY-5121
superpathway of
42
0.004451
4.59
145660.32
158877.65
1.00
31735.49
6396
1.00

geranylgeranyl

diphosphate

biosynthesis II

(via MEP)

PWY-7219
adenosine
43
0.004385
4.56
168432.85
181595.69
1.00
36934.72
73745.19
1.00

ribonucleotides

de novo

biosynthesis

TRPSYN-
L-tryptophan
44
0.004322
4.86
128144.72
146779.35
1.00
26384.56
58066.86
1.00

PWY
biosynthesis

ASPASN-
superpathway
45
0.004278
5.01
139280.20
163853.94
1.00
27802.72
61241.17
1.00

PWY
of L-aspartate

and L-

asparagine

biosynthesis

PWY-5103
L-isoleucine
46
0.004253
4.53
160258.88
172574.42
1.00
35363.64
68670.88
1.00

biosynthesis III

SER-GLYSYN-
superpathway
47
0.004235
4.56
143605.20
155090.21
1.00
31513.44
61945.68
1.00

PWY
of L-serine and

glycine

biosynthesis I

TCA
TCA cycle I
48
0.004201
6.17
98126.13
130990.80
1.00
15894.91
44406.77
1.00

(prokaryotic)

COA-PWY
coenzyme A
49
0.004073
4.52
138903.51
149373.92
1.00
30734.70
62246.18
1.00

biosynthesis I

PWY4FS-7
phosphatidylglycerol
50
0.004060
4.12
128337.23
136928.30
1.00
31156.08
55249.99
1.00

biosynthesis I

(plastidic)

FASYN-ELONG-
fatty acid
51
0.004052
5.86
142121.29
184812.05
1.00
24234.67
67787.32
1.00

PWY
elongation --

saturated

PANTOSYN-
pantothenate
52
0.004050
4.88
121558.14
138828.52
1.00
24898.21
53813.43
1.00

PWY
and coenzyme

A biosynthesis I

P124-PWY
Bifidobacterium
53
0.003954
3.42
16833.53
24551.47
1.00
4916.18
11478.79
1.00

shunt

P161-PWY
acetylene
54
0.003925
3.76
79808.50
85551.86
1.00
21213.96
36857.71
1.00

degradation

GALACTARDEG-
D-galactarate
55
0.003924
3.84
2111.64
7543.61
1.00
549.35
4744.41
0.99

PWY
degradation I

P122-PWY
heterolactic
56
0.003886
3.87
13280.01
19573.61
1.00
3434.87
7997.81
1.00

fermentation

PEPTIDOGLYCANSYN-
peptidoglycan
57
0.003861
4.49
142567.46
152892.70
1.00
31783.86
62985.20
1.00

PWY
biosynthesis I

(meso-

diaminopimelate

containing)

PWY4FS-8
phosphatidylglycerol
58
0.003841
4.12
128337.23
136928.30
1.00
31156.08
55249.99
1.00

biosynthesis II

(non-plastidic)

1CMET2-
N10-formyl-
59
0.003810
4.67
138685.80
152817.72
1.00
29667.15
61241.36
1.00

PWY
tetrahydrofolate

biosynthesise

PWY-7539
6-hydroxymethyl-
60
0.003796
4.99
119874.08
140866.61
1.00
24023.34
57775.64
1.00

dihydropterin

diphosphate

biosynthesis III

(Chlamydia)

VALSYN-
L-valine
61
0.003760
4.47
169183.59
181085.81
1.00
37825.61
73282.50
1.00

PWY
biosynthesis

PWY-5686
UMP
62
0.003728
4.52
163185.12
174833.16
1.00
36137.39
71110.33
1.00

biosynthesis

PWY-6151
S-adenosy1-L-
63
0.003710
4.32
118471.43
124314.40
1.00
27430.06
52342.86
1.00

methionine

cycle I

PWY-7663
gondoate
64
0.003678
4.94
201476.18
230015.10
1.00
40750.28
88888.09
1.00

biosynthesis

(anaerobic)

PWY-6163
chorismate
65
0.003673
4.46
152411.28
162586.14
1.00
34156.88
67511.88
1.00

biosynthesis

from 3-

dehydroquinate

PWY-6703
preQ0
66
0.003672
5.41
90603.31
113287.04
1.00
16750.81
43567.02
1.00

biosynthesis

PWY-6897
thiamin
67
0.003672
4.61
119488.56
134963.50
1.00
25927.29
55804.92
1.00

salvage II

UDPNAGSYN-
UDP-N-acetyl-
68
0.003670
4.04
71406.12
80670.82
1.00
17690.50
33505.78
1.00

PWY
D-glucosamine

biosynthesis I

GLUCARGALACTSUPER-
superpathway
69
0.003637
3.84
2111.64
7543.61
1.00
549.35
4744.41
0.99

PWY
of D-glucarate

and D-

galactarate

degradation

PWY-5384
sucrose
70
0.003626
4.00
59513.26
72971.49
1.00
14862.20
23647.49
1.00

degradation IV

(sucrose

phosphorylase)

PWY-6386
UDP-N-
71
0.003607
4.48
143589.59
154313.45
1.00
32031.44
63604.98
1.00

acetylmuramoy

1-pentapeptide

biosynthesis II

(lysine-

containing)

HEMESYN2-
heme
72
0.003588
8.97
23668.19
43786.66
1.00
2637.17
8694.63
1.00

PWY
biosynthesis II

(anaerobic)

GLYCOCAT-
glycogen
73
0.003568
4.54
179426.89
196539.01
1.00
39548.53
74794.98
1.00

PWY
degradation I

(bacterial)

P42-PWY
incomplete
74
0.003556
6.00
155257.55
197154.84
1.00
25857.31
68620.11
1.00

reductive TCA

cycle

PYRIDNUCSYN-
NAD
75
0.003545
4.77
126496.08
140748.67
1.00
26519.01
54429.15
1.00

PWY
biosynthesis I

(from

aspartate)

PWY-5913
TCA cycle VI
76
0.003542
6.26
74796.51
107950.49
1.00
11957.29
33291.95
1.00

(obligate

autotrophs)

PWY0-
methylphosphonate
77
0.003373
3.72
3150.67
14618.07
0.99
847.56
6164.16
0.99

1533
degradation I

PHOSLIPSYN-
superpathway of
78
0.003368
4.25
143655.43
152059.19
1.00
33765.68
63738.88
1.00

PWY
phospholipid

biosynthesis I

(bacteria)

GLUCARDEG-
D-glucarate
79
0.003367
2.84
2458.14
7559.79
1.00
865.69
4838.01
1.00

PWY
degradation I

NONMEVIPP-
methylerythritol
80
0.003331
4.63
152085.59
167020.40
1.00
32817.44
66602.58
1.00

PWY
phosphate

pathway I

PWY-922
mevalonate
81
0.003279
2.94
1362.33
3932.81
1.00
463.57
1958.69
0.98

pathway I

P162-PWY
L-glutamate
82
0.003271
5.69
2551.20
7942.49
0.99
448.71
887.20
0.99

degradation V (via

hydroxyglutarate)

PWY0-845
superpathway
83
0.003260
7.62
72147.89
105611.49
1.00
9473.82
32432.50
1.00

of pyridoxal 5′-

phosphate

biosynthesis

and salvage

PANTO-
phosphopantothenate
84
0.003239
4.99
116332.92
136488.66
1.00
23307.92
51652.13
1.00

PWY
biosynthesis I

PWY490-3
nitrate
85
0.003228
2.86
20420.91
23998.68
1.00
7137.14
15395.49
1.00

reduction VI

(assimilatory)

P163-PWY
L-lysine
86
0.003154
5.33
3410.33
6556.32
0.99
639.47
1586.14
0.99

fermentation to

acetate and

butanoate

PWY-7371
1,4-dihydroxy-
87
0.003138
4.68
4501.75
8592.10
0.97
962.58
2626.82
0.98

6-naphthoate

biosynthesis II

OANTIGEN-
O-antigen
88
0.003093
4.26
93156.54
102747.40
1.00
21891.17
41689.77
1.00

PWY
building blocks

biosynthesis

(E. coli)

PWY-7374
1,4-dihydroxy-
89
0.003088
4.99
3178.58
5725.74
0.93
637.49
1685.39
0.94

6-naphthoate

biosynthesis I

THISYN-
superpathway
90
0.003066
5.52
109721.45
138174.15
1.00
19862.69
54220.75
1.00

PWY
of thiamin

diphosphate

biosynthesis I

PWY-7242
D-fructuronate
91
0.003064
5.23
116772.26
144256.32
1.00
22323.68
52697.65
1.00

degradation

PWY-6125
superpathway
92
0.003007
5.59
104612.32
135029.70
1.00
18719.56
49663.94
1.00

of guanosine

nucleotides de

novo

biosynthesis II

PWY-7013
L-1,2-
93
0.002955
3.61
5596.39
19114.27
1.00
1548.37
13949.03
1.00

propanediol

degradation

PWY-6572
chondroitin
94
0.002934
10.46
50801.13
99501.47
0.99
4856.97
19285.21
0.99

sulfate

degradation I

(bacterial)

P221-PWY
octane
95
0.002919
2.63
5790.85
11690.85
0.99
2201.27
4989.83
0.99

oxidation

PWY-6507
4-deoxy-L-
96
0.002917
6.02
104716.90
139954.39
1.00
17403.45
48947.31
1.00

threo-hex-4-

enopyranuronate

degradation

PWY-6641
superpathway
97
0.002909
3.95
286.50
782.30
0.53
72.45
219.02
0.56

of sulfolactate

degradation

PWY-5667
CDP-
98
0.002901
4.38
160781.08
173346.52
1.00
36676.06
68483.69
1.00

diacylglycerol

biosynthesis I

PWY-5910
superpathway of
99
0.002886
2.97
1859.35
5098.98
1.00
625.10
2449.67
0.98

geranylgeranyl

diphosphate

biosynthesis I

(via mevalonate)

PWY-7208
superpathway
100
0.002847
4.50
164374.02
176488.98
1.00
36522.63
73296.77
1.00

of pyrimidine

nucleobases

salvage

IBD = Inflammatory Bowel Disease;

UC = Ulcerative Colitis;

Ctrl = Control;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 5

IBD (Crohn's Disease) vs Control delineation features - (metabolic pathway)

MetaCyc
Pathway
RFFR
FC
Abundance (CD)
Abundance (Ctrl)

Pathway ID
description
#
MDA
CD vs Ctrl
M
SD
DP
M
SD
DP

P164-PWY
purine
1
0.016694
4.75
39670.34
67177.84
1.00
8351.71
14822.92
1.00

nucleobases

degradation I

(anaerobic)

HEMESYN2-
heme
2
0.016193
13.48
35555.30
83683.62
1.00
2637.17
8694.63
1.00

PWY
biosynthesis II

(anaerobic)

PWY-6608
guanosine
3
0.013893
5.35
57468.79
97578.54
1.00
10750.82
21503.38
1.00

nucleotides

degradation III

SALVADEHYPOX-
adenosine
4
0.013769
6.02
44006.85
77885.11
1.00
7304.37
11647.54
1.00

PWY
nucleotides

degradation II

GALACTARDEG-
D-galactarate
5
0.013575
13.28
7296.20
30138.69
0.99
549.35
4744.41
0.99

PWY
degradation I

FUC-RHAMCAT-
superpathway
6
0.013508
4.49
30253.56
45999.22
1.00
6741.81
13553.66
1.00

PWY
of fucose and

rhamnose

degradation

PWY-7013
L-1,2-
7
0.012895
6.93
10736.01
40305.80
0.99
1548.37
13949.03
1.00

propanediol

degradation

PWY-6749
CMP-
8
0.012567
1.59
9692.48
20449.22
0.99
6084.38
9079.26
1.00

legionaminate

biosynthesis I

GLUCARGALACTSUPER-
superpathway
9
0.011496
13.28
7296.20
30138.69
0.99
549.35
4744.41
0.99

PWY
of D-glucarate

and D-

galactarate

degradation

TRPSYN-
L-tryptophan
10
0.009349
3.78
99634.26
122465.54
1.00
26384.56
58066.86
1.00

PWY
biosynthesis

PWY-6147
6-hydroxymethyl-
11
0.008923
4.02
95540.73
120570.43
1.00
23773.45
55311.45
1.00

dihydropterin

diphosphate

biosynthesis I

PWY-6353
purine
12
0.008566
5.26
47585.56
77325.28
1.00
9044.31
15206.57
1.00

nucleotides

degradation II

(aerobic)

P125-PWY
superpathway
13
0.008003
14.09
3230.07
12327.63
1.00
229.19
592.66
0.99

of (R,R)-

butanediol

biosynthesis

GLUCUROCAT-
superpathway
14
0.007973
5.11
59892.43
105510.95
1.00
11711.24
23892.96
1.00

PWY
of β-D-

glucuronide

and D-

glucuronate

degradation

PWY-7220
adenosine
15
0.007777
4.11
153483.18
196473.92
1.00
37306.88
84124.81
1.00

deoxyribonucleotides

de novo

biosynthesis II

GALACT-
superpathway
16
0.007634
4.43
52193.98
72901.05
1.00
11783.19
25094.72
1.00

GLUCUROCAT-
of hexuronide

PWY
and hexuronate

degradation

GLUCARDEG-
D-glucarate
17
0.007549
9.07
7850.61
30420.23
0.99
865.69
4838.01
1.00

PWY
degradation I

PWY-7222
guanosine
18
0.007456
4.11
153483.18
196473.92
1.00
37306.88
84124.81
1.00

deoxyribonucleotides

de novo

biosynthesis II

PENTOSE-P-
pentose
19
0.007329
5.59
83420.89
130091.59
1.00
14915.57
40468.42
1.00

PWY
phosphate

pathway

PWY-7539
6-hydroxymethyl-
20
0.007035
3.97
95422.67
118360.58
1.00
24023.34
57775.64
1.00

dihydropterin

diphosphate

biosynthesis III

(Chlamydia)

PWY-6891
thiazole
21
0.006703
6.31
37674.05
78490.10
1.00
5971.37
17637.92
1.00

biosynthesis II

(Bacillus)

PWY-7663
gondoate
22
0.006638
3.76
153397.37
191013.74
1.00
40750.28
88888.09
1.00

biosynthesis

(anaerobic)

GLUCONEO-
gluconeogenesis I
23
0.006519
4.10
113287.39
150720.86
1.00
27620.28
63540.87
1.00

PWY

HISDEG-
L-histidine
24
0.006455
5.67
51973.76
86358.88
1.00
9158.46
31562.90
1.00

PWY
degradation I

PWY-6263
superpathway
25
0.006421
2.02
4234.14
11042.21
0.93
2100.71
5484.38
0.98

of menaquinol-

8 biosynthesis II

FUCCAT-
fucose
26
0.006342
4.50
31323.36
51124.44
1.00
6953.38
12213.82
1.00

PWY
degradation

PWY0-845
superpathway
27
0.006076
6.19
58606.74
103927.00
0.99
9473.82
32432.50
1.00

of pyridoxal 5′-

phosphate

biosynthesis

and salvage

RIBOSYN2-
flavin
28
0.005982
3.74
96099.98
117380.33
1.00
25710.38
56666.93
1.00

PWY
biosynthesis I

(bacteria and

plants)

GALACTUROCAT-
D-galacturonate
29
0.005915
4.45
74289.85
110692.53
1.00
16708.71
38794.58
1.00

PWY
degradation I

PWY-7371
1,4-dihydroxy-
30
0.005862
2.15
2067.29
9774.12
0.93
962.58
2626.82
0.98

6-naphthoate

biosynthesis II

CALVIN-
Calvin-
31
0.005669
3.57
138657.97
168279.01
1.00
38789.56
77297.80
1.00

PWY
Benson-

Bassham cycle

1CMET2-
N10-formyl-
32
0.005663
3.69
109387.84
133407.05
1.00
29667.15
61241.36
1.00

PWY
tetrahydrofolate

biosynthesis

ASPASN-
superpathway
33
0.005613
3.82
106098.60
133809.01
1.00
27802.72
61241.17
1.00

PWY
of L-aspartate

and L-

asparagine

biosynthesis

PWY-7229
superpathway
34
0.005411
3.67
136856.78
168865.72
1.00
37269.82
76809.15
1.00

of adenosine

nucleotides de

novo

biosynthesis I

PWY-5028
L-histidine
35
0.005344
92.77
10707.61
55776.82
0.88
115.42
525.00
0.66

degradation II

POLYISOPRENSYN-
polyisoprenoid
36
0.005300
4.23
78556.66
106197.98
1.00
18570.50
48260.04
1.00

PWY
biosynthesis

(E. coli)

GOLPDLCAT-
superpathway
37
0.005276
3.78
1999.50
11011.75
0.99
528.96
6087.60
0.99

PWY
of glycerol

degradation to

1,3-

propanediol

PWY-7328
superpathway
38
0.005245
8.02
36501.90
82385.95
1.00
4548.81
13394.71
1.00

of UDP-

glucose-

derived O-

antigen

building blocks

biosynthesis

PWY-5676
acetyl-CoA
39
0.005186
2.69
14818.09
29450.20
0.99
5508.55
16400.91
1.00

fermentation to

butanoate II

PWY-6612
superpathway of
40
0.004984
4.02
95935.61
125669.15
1.00
23842.31
53794.55
1.00

tetrahydrofolate

biosynthesis

PWY-7237
myo-, chiro-
41
0.004951
7.57
44697.50
120409.47
1.00
5907.27
15779.62
1.00

and scillo-

inositol

degradation

PWY-5097
L-lysine
42
0.004922
3.58
129295.28
158559.53
1.00
36065.98
71069.75
1.00

biosynthesis VI

PWY-6471
peptidoglycan
43
0.004861
2.37
36739.48
63784.59
1.00
15517.50
26202.50
1.00

biosynthesis IV

(Enterococcus

faecium)

P162-PWY
L-glutamate
44
0.004787
11.01
4941.47
13423.77
0.98
448.71
887.20
0.99

degradation V

(via

hydroxyglutarate)

NONOXIPENT-
pentose
45
0.004705
3.73
175905.63
236171.09
1.00
47150.96
90843.66
1.00

PWY
phosphate

pathway (non-

oxidative

branch)

P381-PWY
adenosylcobalamin
46
0.004651
1.17
52.08
349.59
0.34
44.58
315.65
0.34

biosynthesis II

(late cobalt

incorporation)

THRESYN-
superpathway
47
0.004638
3.64
123200.37
148501.98
1.00
33804.17
69499.08
1.00

PWY
of L-threonine

biosynthesis

PWY-6588
pyruvate
48
0.004545
6.92
24791.84
48898.19
1.00
3584.20
7857.69
1.00

fermentation to

acetone

PWY-5005
biotin
49
0.004458
3.01
4932.46
14746.58
0.97
1637.01
6066.53
0.99

biosynthesis II

PWY-5973
cis-vaccenate
50
0.004426
3.69
138718.68
175425.39
1.00
37597.57
77633.61
1.00

biosynthesis

ARGORNPROST-
arginine,
51
0.004411
2.11
4884.11
9264.15
1.00
2313.51
6466.68
1.00

PWY
ornithine and

proline

interconversion

PWY-6897
thiamin
52
0.004373
3.78
97899.86
119256.02
1.00
25927.29
55804.92
1.00

salvage II

FOLSYN-
superpathwayof
53
0.004333
3.93
102954.52
132523.76
1.00
26199.43
57898.05
1.00

PWY
tetrahydrofolate

biosynthesis

and salvage

PWY0-
methylphosphonate
54
0.004302
19.74
16734.20
74852.92
0.99
847.56
6164.16
0.99

1533
degradation I

PWY-6396
superpathway
55
0.004283
10.30
2818.46
6448.24
1.00
273.69
669.20
0.99

of 2,3-

butanediol

biosynthesis

PWY-7376
cob(II)yrinate
56
0.004263
2.39
125.18
1574.90
0.35
52.48
565.70
0.35

a,c-diamide

biosynthesis II

(late cobalt

incorporation)

PWY-6277
superpathway
57
0.004088
3.47
118847.46
140173.41
1.00
34211.58
67927.32
1.00

of 5-

aminoimidazole

ribonucleotide

biosynthesis

DTDPRHAMSYN-
dTDP-L-
58
0.004029
3.57
125482.40
148314.44
1.00
35109.82
75193.40
1.00

PWY
rhamnose

biosynthesis I

PYRIDOXSYN-
pyridoxal 5′-
59
0.004018
6.29
49561.69
87964.19
0.99
7874.62
29079.28
1.00

PWY
phosphate

biosynthesis I

PANTO-
phosphopantothenate
60
0.004016
3.72
86801.13
108009.43
1.00
23307.92
51652.13
1.00

PWY
biosynthesis I

PWY-6876
isopropanol
61
0.003974
3.21
726.65
3973.66
0.85
226.52
916.56
0.87

biosynthesis

PWY-5686
UMP
62
0.003923
3.51
127018.63
153797.12
1.00
36137.39
71110.33
1.00

biosynthesis

PANTOSYN-
pantothenate
63
0.003872
3.63
90363.19
110841.09
1.00
24898.21
53813.43
1.00

PWY
and coenzyme

A biosynthesis I

PWY-7560
methylerythritol
64
0.003859
3.43
112677.00
135610.11
1.00
32817.44
66602.58
1.00

phosphate

pathway II

PWY-7374
1,4-dihydroxy-
65
0.003845
1.64
1047.15
2383.26
0.88
637.49
1685.39
0.94

6-naphthoate

biosynthesis I

PWY-6895
superpathway
66
0.003701
5.23
53144.48
88992.18
1.00
10160.16
32128.66
1.00

of thiamin

diphosphate

biosynthesis II

PYRIDNUCSYN-
NAD
67
0.003684
3.51
92993.32
114472.99
1.00
26519.01
54429.15
1.00

PWY
biosynthesis I

(from aspartate)

PWY-6387
UDP-N-
68
0.003683
3.51
112245.75
133752.60
1.00
31963.32
63342.58
1.00

acetylmuramoy

1-pentapeptide

biosynthesis I

(meso-

diaminopimelate

containing)

PWY0-
ADP-L-
69
0.003673
8.33
23709.16
65604.48
1.00
2845.86
10461.74
1.00

1241
glycero-β-

D-manno-heptose

biosynthesis

PWY-5100
pyruvate
70
0.003535
3.53
120253.39
144453.37
1.00
34069.08
66777.05
1.00

fermentation to

acetate and

lactate II

PWY0-41
allantoin
71
0.003521
23.89
5721.43
26198.07
0.99
239.53
766.40
0.99

degradation IV

(anaerobic)

ANAGLYCOLYSIS-
glycolysis III
72
0.003487
3.57
137524.04
168787.18
1.00
38524.25
76074.72
1.00

PWY
(from glucose)

RHAMCAT-
L-rhamnose
73
0.003485
4.26
56913.94
79913.50
1.00
13374.68
37212.50
1.00

PWY
degradation I

GLUTORN-
L-ornithine
74
0.003416
3.75
88647.53
113606.60
1.00
23616.52
46464.24
1.00

PWY
biosynthesis

TRNA-
tRNA charging
75
0.003370
3.49
112518.40
135123.34
1.00
32210.70
64009.96
1.00

CHARGING-PWY

PWY-6641
superpathway
76
0.003319
0.42
30.61
232.54
0.32
72.45
219.02
0.56

of sulfolactate

degradation

PWY-7111
pyruvate
77
0.003284
3.64
151140.97
194928.89
1.00
41507.13
77556.59
1.00

fermentation to

isobutanol

(engineered)

NONMEVIPP-
methylerythritol
78
0.003273
3.43
112677.00
135610.11
1.00
32817.44
66602.58
1.00

PWY
phosphate

pathway I

PWY-7242
D-fructuronate
79
0.003250
4.42
98688.06
150425.27
1.00
22323.68
52697.65
1.00

degradation

COA-PWY
coenzyme A
80
0.003236
3.43
105562.92
124974.11
1.00
30734.70
62246.18
1.00

biosynthesis I

PWY-7219
adenosine
81
0.003202
3.50
129271.94
155301.58
1.00
36934.72
73745.19
1.00

ribonucleotides

de novo

biosynthesis

PWY-7221
guanosine
82
0.003170
3.60
120689.24
147567.92
1.00
33485.60
67311.36
1.00

ribonucleotides

de novo

biosynthesis

PWY-7456
mannan
83
0.003110
3.50
32642.66
51192.93
0.99
9327.98
25079.05
0.99

degradation

PWY-6126
superpathway
84
0.003103
3.66
130284.17
161476.86
1.00
35557.29
73657.90
1.00

of adenosine

nucleotides de

novo

biosynthesis II

PWY-6123
inosine-5′-
85
0.003046
3.50
114458.58
135960.11
1.00
32731.91
67616.56
1.00

phosphate

biosynthesis I

PWY-6386
UDP-N-
86
0.003007
3.49
111808.01
132780.27
1.00
32031.44
63604.98
1.00

acetylmuramoyl-

pentapeptide

biosynthesis II

(lysine-

containing)

PWY-6121
5-aminoimidazole
87
0.002999
3.54
122644.71
146484.55
1.00
34599.61
69821.14
1.00

ribonucleotide

biosynthesis I

PWY-6148
tetrahydromethanopterin
88
0.002996
0.39
136.10
1147.78
0.24
349.98
1424.19
0.47

biosynthesis

P241-PWY
coenzyme B
89
0.002972
0.41
118.44
1062.23
0.25
286.39
1179.05
0.48

biosynthesis

DHGLUCONATE-
glucose
90
0.002941
6.44
113.02
1654.90
0.22
17.54
290.23
0.24

PYR-CAT-PWY
degradation

(oxidative)

PWY-5705
allantoin
91
0.002936
10.96
9273.30
42040.00
1.00
846.36
1653.24
1.00

degradation to

glyoxylate III

PWY-5484
glycolysis II
92
0.002893
4.39
113333.13
158613.50
1.00
25795.46
58601.44
1.00

(from fructose

6-phosphate)

PWY-5695
urate biosynthesis/
93
0.002884
4.00
101818.99
131759.35
1.00
25478.81
61554.77
1.00

inosine 5′-

phosphate

degradation

PWY-5659
GDP-mannose
94
0.002882
3.95
85855.38
112494.73
1.00
21758.46
52092.19
1.00

biosynthesis

GLYCOLYSIS-
superpathway
95
0.002856
6.17
53985.43
109050.32
1.00
8754.08
21993.00
1.00

E-D
of glycolysis

and Entner-

Doudoroff

PWY-6122
5-aminoimidazole
96
0.002
3.47
118847.46
140173.41
1.00
34211.58
67927.32
1.00

ribonucleotide

biosynthesis II

PWY0-1319
CDP-
97
0.002830
3.49
127913.86
154073.64
1.00
36676.06
68483.69
1.00

diacylglycerol

biosynthesis II

PWY-5121
superpathway of
98
0.002828
3.35
106181.94
124526.29
1.00
31735.49
63961.74
1.00

geranylgeranyl

diphosphate

biosynthesis II

(via MEP)

PWY-6892
thiazole
99
0.002813
3.87
105937.16
132442.65
1.00
27367.72
60807.66
1.00

biosynthesis I

(E. coli)

METHGLYUT-
superpathway of
100
0.002806
20.68
7581.18
27714.20
0.92
366.61
2302.30
0.87

PWY
methylglyoxal

degradation

IBD = Inflammatory Bowel Disease;

CD = Crohn's Disease;

Ctrl = Control;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 6

IBD (Crohn's Disease) vs IBD (Ulcerative Colitis) delineation features - (metabolic pathway)

FC

MetaCyc

CD

Pathway
Pathway
RFFR
vs
Abundance (CD)
Abundance (UC)

ID
description
#
MDA
UC
M
SD
DP
M
SD
DP

PWY-6749
CMP-
1
0.025173
0.47
9692.48
20449.22
0.99
20493.05
25683.99
1.00

legionaminate

biosynthesis I

PWY-6471
peptidoglycan
2
0.017712
0.65
36739.48
63784.59
1.00
56783.16
62569.90
1.00

biosynthesis

IV

(Enterococcus

faecium)

PWY-7371
1,4-dihydroxy-
3
0.010028
0.46
2067.29
9774.12
0.93
4501.75
8592.10
0.97

6-naphthoate

biosynthesis II

GALACTARDEG-
D-galactarate
4
0.009754
3.46
7296.20
30138.69
0.99
2111.64
7543.61
1.00

PWY
degradation I

PWY-7374
1,4-dihydroxy-
5
0.009713
0.33
1047.15
2383.26
0.88
3178.58
5725.74
0.93

6-naphthoate

biosynthesis I

PWY-6876
isopropanol
6
0.009252
1.01
726.65
3973.66
0.85
721.71
2449.90
0.93

biosynthesis

ECASYN-
enterobacterial
7
0.009012
5.81
16749.34
68566.19
0.93
2882.39
14532.68
0.92

PWY
common

antigen

biosynthesis

GLUCARGALACTSUPER-
superpathway
8
0.008454
3.46
7296.20
30138.69
0.99
2111.64
7543.61
1.00

PWY
of D-glucarate

and D-

galactarate

degradation

PPGPPMET-
ppGpp
9
0.008081
5.23
24469.33
82492.18
0.96
4679.44
21894.98
0.97

PWY
biosynthesis

PWY-6263
superpathway
10
0.008059
0.40
4234.14
11042.21
0.93
10596.57
18534.83
0.97

of menaquinol-

8 biosynthesis

II

P125-PWY
superpathway
11
0.007435
4.00
3230.07
12327.63
1.00
807.17
3187.08
1.00

of (R,R)-

butanediol

biosynthesis

P241-PWY
coenzyme B
12
0.007167
0.07
118.44
1062.23
0.25
1789.01
14962.53
0.48

biosynthesis

GLUCARDEG-
D-glucarate
13
0.006880
3.19
7850.61
30420.23
0.99
2458.14
7559.79
1.00

PWY
degradation I

ORNARGDEG-
superpathway
14
0.006817
6.02
17688.65
80891.73
0.92
2936.87
16065.76
0.92

PWY
of L-arginine

and L-

ornithine

degradation

P163-PWY
L-lysine
15
0.006795
1.16
3957.48
14136.09
0.95
3410.33
6556.32
0.99

fermentation to

acetate and

butanoate

ENTBACSYN-
enterobactin
16
0.006712
4.74
19333.03
69230.60
0.93
4079.12
17264.38
0.94

PWY
biosynthesis

PWY-5676
acetyl-CoA
17
0.006685
0.80
14818.09
29450.20
0.99
18533.37
22958.79
1.00

fermentation to

butanoate II

METHGLYUT-
superpathway
18
0.006611
3.81
7581.18
27714.20
0.92
1989.59
9476.50
0.91

PWY
of

methylglyoxal

degradation

PWY-6148
tetrahydro-
19
0.006542
0.13
136.10
1147.78
0.24
1073.05
6587.85
0.47

methanopterin

biosynthesis

AST-PWY
L-arginine
20
0.006463
5.89
13603.70
62119.58
0.94
2310.21
13702.45
0.93

degradation II

(AST pathway)

ARGDEG-
superpathway
21
0.006279
6.02
17688.65
80891.73
0.92
2936.87
16065.76
0.92

PWY
of L-arginine,

putrescine, and

4-

aminobutanoate

degradation

PWY-6349
CDP-archaeol
22
0.006072
0.07
95.29
837.95
0.24
1378.29
11158.08
0.47

biosynthesis

ORNDEG-
superpathway
23
0.006005
6.67
27281.35
134846.88
0.92
4090.39
24269.34
0.92

PWY
of ornithine

degradation

ARGORNPROST-
arginine,
24
0.005927
0.77
4884.11
9264.15
1.00
6334.38
8686.73
1.00

PWY
ornithine and

proline

interconversion

PWY0-
polymyxin
25
0.005909
6.60
14029.39
61630.04
0.93
2125.72
11455.28
0.93

1338
resistance

PWY-6654
phosphopantothenate
26
0.005889
0.09
139.12
1195.47
0.24
1622.79
12105.03
0.47

biosynthesis III

METHANOGENESIS-
methanogenesis
27
0.005595
0.06
125.20
1139.21
0.24
1980.08
16737.43
0.47

PWY
from H2 and

CO2

PWY-7286
7-(3-amino-3-
28
0.005543
0.07
102.64
926.00
0.24
1479.95
12108.99
0.47

carboxypropyl)-

wyosine

biosynthesis

PWY-5028
L-histidine
29
0.005461
5.99
10707.61
55776.82
0.88
1786.65
11778.28
0.80

degradation II

PWY-5005
biotin
30
0.005436
1.49
4932.46
14746.58
0.97
3318.25
8271.36
0.99

biosynthesis II

PWY490-3
nitrate
31
0.005356
0.84
17051.49
29294.28
1.00
20420.91
23998.68
1.00

reduction VI

(assimilatory)

PWY-5198
factor 420
32
0.005320
0.06
87.93
791.45
0.30
1380.26
11688.75
0.50

biosynthesis

GOLPDLCAT-
superpathway
33
0.005305
1.94
1999.50
11011.75
0.99
1029.13
5049.35
0.99

PWY
of glycerol

degradation to

1,3-

propanediol

PWY-5971
palmitate
34
0.005280
0.66
43665.81
77524.57
0.99
66234.32
96843.59
1.00

biosynthesis II

(bacteria and

plants)

THREOCAT-
superpathway
35
0.005256
4.09
4389.34
16490.46
0.89
1073.37
6560.79
0.85

PWY
of L-threonine

metabolism

PWY-6167
flavin
36
0.005244
0.11
226.93
1870.77
0.23
2148.85
14314.41
0.46

biosynthesis II

(archaea)

PWY-6641
superpathway
37
0.005215
0.11
30.61
232.54
0.32
286.50
782.30
0.53

of sulfolactate

degradation

P162-PWY
L-glutamate
38
0.005157
1.94
4941.47
13423.77
0.98
2551.20
7942.49
0.99

degradation V

(via

hydroxyglutarate)

AEROBACTINSYN-
aerobactin
39
0.005127
9.00
2052.74
18637.22
0.75
228.13
1661.90
0.59

PWY
biosynthesis

PWY-7332
superpathway
40
0.005045
0.48
2593.14
8043.83
0.97
5350.75
17266.53
0.98

of UDP-N-

acetylglucosamine-

derived O-

antigen

building blocks

biosynthesis

PWY-6350
archaetidylinositol
41
0.004967
0.07
91.42
810.90
0.24
1350.14
11043.42
0.47

biosynthesis

PWY-6141
archaetidylserine
42
0.004906
0.07
87.56
782.56
0.23
1320.34
10921.33
0.46

and

archaetidyl-

ethanolamine

biosynthesis

PWY-7090
UDP-2,3-
43
0.004854
0.69
261.32
1550.59
0.90
380.07
1053.00
0.96

diacetamido-

2,3-dideoxy-

α-D-

mannuronate

biosynthesis

P341-PWY
glycolysis V
44
0.004584
2.49
469.35
2385.08
0.93
188.79
582.49
0.94

(Pyrococcus)

PWY-6174
mevalonate
45
0.004537
0.07
100.06
845.39
0.24
1420.14
11234.68
0.47

pathway II

(archaea)

PWY-7377
cob(II)yrinate
46
0.004479
1.31
16450.03
30146.81
1.00
12584.43
20579.09
1.00

a,c-diamide

biosynthesis I

(early cobalt

insertion)

FUC-
superpathway
47
0.004346
0.98
30253.56
45999.22
1.00
30982.04
37742.79
1.00

RHAMCAT-
of fucose and

PWY
rhamnose

degradation

PWY-6071
superpathway
48
0.004303
7.21
14199.29
70940.66
0.88
1968.50
12637.00
0.82

of

phenylethylamine

degradation

ALL-
superpathway
49
0.004285
4.14
22525.78
78364.40
0.93
5436.31
21101.09
0.94

CHORISMATE-
of chorismate

PWY
metabolism

P261-PWY
coenzyme M
50
0.004238
0.07
99.15
850.63
0.35
1471.73
12152.92
0.54

biosynthesis I

PWY-7456
mannan
51
0.004122
0.55
32642.66
51192.93
0.99
59391.38
79508.41
0.99

degradation

P221-PWY
octane
52
0.004029
0.99
5727.15
13988.98
0.96
5790.85
11690.85
0.99

oxidation

P562-PWY
myo-inositol
53
0.003898
3.41
16086.23
60565.51
1.00
4716.79
12464.95
1.00

degradation I

PWY-5384
sucrose
54
0.003897
0.99
58637.96
107456.98
1.00
59513.26
72971.49
1.00

degradation IV

(sucrose

phosphorylase)

PWY-6396
superpathway
55
0.003855
2.42
2818.46
6448.24
1.00
1166.35
4297.04
1.00

of 2,3-

butanediol

biosynthesis

P23-PWY
reductive TCA
56
0.003807
1.67
32942.69
71062.88
1.00
19685.12
36592.60
1.00

cycle I

CODH-
reductive
57
0.003796
0.77
3232.52
9289.40
0.91
4221.31
8656.55
0.96

PWY
acetyl

coenzyme A

pathway

GLYOXYLATE-
glyoxylate
58
0.003767
4.18
19384.88
70479.27
0.95
4637.72
19200.94
0.94

BYPASS
cycle

PWY-6478
GDP-D-
59
0.003743
0.74
14946.39
23226.40
0.99
20199.10
33354.36
1.00

glycero-

α-D-

manno-heptose

biosynthesis

PWY-6545
pyrimidine
60
0.003742
0.62
26564.62
37952.18
1.00
43085.77
51661.16
1.00

deoxyribo-

nucleotides

de novo

biosynthesis III

PWY-7003
glycerol
61
0.003653
1.48
6909.54
16016.37
1.00
4675.89
9592.01
1.00

degradation to

butanol

PWY-4984
urea cycle
62
0.003632
0.69
29111.32
52060.45
1.00
42029.55
58090.15
1.00

PWY-7234
inosine-5′-
63
0.003582
1.31
39456.42
85085.98
1.00
30101.06
40109.85
1.00

phosphate

biosynthesis III

PWY-7315
dTDP-N-
64
0.003562
1.88
41775.44
86794.48
1.00
22180.45
29288.33
1.00

acetylthomosamine

biosynthesis

POLYAMINSYN3-
superpathway
65
0.003518
0.93
11903.43
21575.86
0.99
12860.41
19593.62
1.00

PWY
of polyamine

biosynthesis II

PWY-7431
aromatic
66
0.003484
3.58
206.91
1765.80
0.88
57.87
95.09
0.92

biogenic amine

degradation

(bacteria)

PWY0-321
phenylacetate
67
0.003478
7.12
14965.65
74424.12
0.89
2102.46
13279.66
0.83

degradation I

(aerobic)

P164-PWY
purine
68
0.003470
1.61
39670.34
67177.84
1.00
24677.59
28306.57
1.00

nucleobases

degradation I

(anaerobic)

PWY-5837
1,4-dihydroxy-
69
0.003404
4.01
21114.38
70449.19
1.00
5262.20
16610.11
1.00

2-naphthoate

biosynthesis I

PWY-5910
superpathway
70
0.003360
2.76
5129.11
20263.63
0.99
1859.35
5098.98
1.00

of

geranylgeranyl

diphosphate

biosynthesis I

(via

mevalonate)

PWY-7391
isoprene
71
0.003354
0.13
28.73
172.00
0.28
226.77
1083.71
0.51

biosynthesis II

(engineered)

PWY-5860
superpathway
72
0.003344
3.93
20493.78
69433.67
0.99
5208.29
19043.16
0.99

of

demethyl-

menaquinol-6

biosynthesis I

PWY-6590
superpathway
73
0.003334
0.86
12239.63
24318.59
0.99
14219.17
25405.60
1.00

of Clostridium

acetobutylicum

acidogenic

fermentation

PWY-5863
superpathway
74
0.003318
3.78
21736.06
70020.79
1.00
5743.29
17235.41
1.00

of phylloquinol

biosynthesis

UDPNAGSYN-
UDP-N-acetyl-
75
0.003317
0.87
61879.77
95631.95
1.00
71406.12
80670.82
1.00

PWY
D-glucosamine

biosynthesis I

PWY-5862
superpathway
76
0.003312
3.93
20494.10
69433.58
0.99
5211.12
19042.72
0.99

of

demethyl-

menaquinol-9

biosynthesis

GLUCUROCAT-
superpathway
77
0.003247
1.09
59892.43
105510.95
1.00
55159.45
71915.55
1.00

PWY
of β-D-

glucuronide

and D-

glucuronate

degradation

SULFATE-
superpathway
78
0.003227
1.11
44075.94
96361.28
1.00
39611.04
52690.94
1.00

CYS-
of sulfate

PWY
assimilation

and cysteine

biosynthesis

PWY0-41
allantoin
79
0.003209
3.53
5721.43
26198.07
0.99
1622.59
6935.06
1.00

degradation IV

(anaerobic)

CENTFERM-
pyruvate
80
0.003188
0.87
9980.77
20181.96
0.99
11492.63
20929.21
1.00

PWY
fermentation to

butanoate

PWY-4722
creatinine
81
0.003181
0.84
32.74
344.87
0.46
39.08
115.39
0.63

degradation II

PWY0-
methylphosphonate
82
0.003141
5.31
16734.20
74852.92
0.99
3150.67
14618.07
0.99

1533
degradation I

PWY-6588
pyruvate
83
0.003107
1.53
24791.84
48898.19
1.00
16207.15
22849.74
1.00

fermentation to

acetone

PWY-5022
4-
84
0.003096
2.09
6568.44
14597.17
1.00
3144.44
6518.85
1.00

aminobutanoate

degradation

V

GLYCOL-
superpathway
85
0.003092
2.93
8884.31
30714.59
0.95
3030.63
11373.87
0.94

GLYOXDEG-
of glycol

PWY
metabolism

and

degradation

PWY-5304
superpathway
86
0.003053
0.72
27360.21
41955.12
1.00
37846.89
56131.80
1.00

of sulfur

oxidation

(Acidianus

ambivalens)

PWYO-
ADP-L-
87
0.003041
2.23
23709.16
65604.48
1.00
10616.61
19216.83
1.00

1241
glycero-

β-D-

manno-heptose

biosynthesis

PWY-1861
formaldehyde
88
0.003020
1.13
25745.51
60581.05
1.00
22801.52
40131.28
1.00

assimilation II

(RuMP Cycle)

PWY-5861
superpathway
89
0.002959
3.02
25927.96
72438.40
1.00
8579.61
22408.94
1.00

of

demethyl-

menaquinol-8

biosynthesis

OANTIGEN-
O-antigen
90
0.002921
0.77
72081.20
97443.41
1.00
93156.54
102747.40
1.00

PWY
building blocks

biosynthesis

(E. coli)

PWY0-
anhydromuropeptides
91
0.002918
1.15
57381.54
130699.40
1.00
49694.18
70536.52
1.00

1261
recycling

SO4ASSIM-
sulfate
92
0.002915
1.46
32883.27
94534.32
1.00
22540.46
33854.40
1.00

PWY
reduction I

(assimilatory)

LACTOSECAT-
lactose and
93
0.002907
1.43
2329.83
5552.10
1.00
1627.19
2787.73
1.00

PWY
galactose

degradation I

HEME-
heme
94
0.002898
3.82
17782.97
63997.61
1.00
4657.67
14559.92
1.00

BIOSYNTHESIS-
biosynthesis I

II
(aerobic)

PWY-6165
chorismate
95
0.002897
0.67
175.66
762.40
0.69
262.88
754.27
0.80

biosynthesis II

(archaea)

PWY-7013
L-1,2-
96
0.002884
1.92
10736.01
40305.80
0.99
5596.39
19114.27
1.00

propanediol

degradation

PWY-922
mevalonate
97
0.002881
2.98
4060.72
17004.71
0.99
1362.33
3932.81
1.00

pathway I

PWY-5838
superpathway
98
0.002861
2.65
28203.17
73545.04
1.00
10660.29
25407.65
1.00

of menaquinol-

8 biosynthesis

I

PWY-5154
L-arginine
99
0.002851
0.73
55076.89
88495.48
1.00
75404.45
93843.05
1.00

biosynthesis III

(via N-acetyl-

L-citrulline)

SALVADEHYPOX-
adenosine
100
0.002848
1.53
44006.85
77885.11
1.00
28718.36
35343.32
1.00

PWY
nucleotides

degradation II

IBD = Inflammatory Bowel Disease; CD = Crohn's Disease; UC = Ulcerative Colitis; Ctrl = Control; RFFR = Random Forest Feature Rank; # = Rank; MDA = Mean Decrease Accuracy; FC = Fold Change; M = Mean; SD = Standard Deviation; DP = Detection Prevalence;

TABLE 7

IBS vs CDI delineation features - (metabolic pathway)

FC

MetaCyc

IBS

Pathway
Pathway
RFFR
vs
Abundance (IBS)
Abundance (CDI)

ID
description
#
MDA
CDI
M
SD
DP
M
SD
DP

PYRIDNUCSYN-
NAD
1
0.022964
3.10
28698.20
15283.44
1.00
9244.66
7697.40
1.00

PWY
biosynthesis I

(from

aspartate)

PWY-5509
adenosylcobalamin
2
0.022107
3.27
28274.99
16265.25
1.00
8656.86
7613.93
1.00

biosynthesis

from

cobyrinate a,c-

diamide I

GLYCOGENSYNTH-
glycogen
3
0.020387
3.41
38040.27
19979.74
1.00
11149.92
9865.46
1.00

PWY
biosynthesis I

(from ADP-D-

Glucose)

HISTSYN-
L-histidine
4
0.020134
3.03
32757.25
18079.33
1.00
10804.07
8915.40
1.00

PWY
biosynthesis

PWY-6269
adenosylcobalamin
5
0.019140
3.26
28462.22
16377.77
1.00
8739.20
7664.91
1.00

salvage from

cobinamide II

PYRIDNUCSAL-
NAD salvage
6
0.018534
3.10
29619.59
15707.18
1.00
9539.35
8058.22
1.00

PWY
pathway I

PWY-5104
L-isoleucine
7
0.016583
2.94
40466.33
21816.16
1.00
13779.72
11296.81
1.00

biosynthesis

IV

NONMEVIPP-
methylerythritol
8
0.016184
2.91
34272.25
17397.13
1.00
11765.12
9593.11
1.00

PWY
phosphate

pathway I

PWY-6163
chorismate
9
0.016044
2.88
36411.39
19257.17
1.00
12651.08
9738.48
1.00

biosynthesis

from 3-

dehydroquinate

PWY-6151
S-adenosyl-L-
10
0.014754
3.10
29177.44
15680.40
1.00
9411.61
7522.84
1.00

methionine

cycle I

PWY-5101
L-isoleucine
11
0.014462
2.90
44537.47
25489.34
1.00
15339.54
12681.90
1.00

biosynthesis II

PANTOSYN-
pantothenate
12
0.014348
2.92
28076.23
16189.06
1.00
9601.39
7781.20
1.00

PWY
and coenzyme

A biosynthesis

I

PWY-5686
UMP
13
0.014067
2.78
38378.86
20600.14
1.00
13799.67
10365.94
1.00

biosynthesis

COBALSYN-
adenosylcobalamin
14
0.013167
3.08
29249.71
16412.21
1.00
9508.59
8221.80
1.00

PWY
salvage from

cobinamide I

PWY-5103
L-isoleucine
15
0.012875
2.89
38191.84
21780.55
1.00
13221.92
10973.04
1.00

biosynthesis III

PWY-3001
superpathway
16
0.012006
2.78
36808.04
19082.06
1.00
13263.33
10722.63
1.00

of L-isoleucine

biosynthesis I

PWY-7400
L-arginine
17
0.011770
3.00
27180.25
16920.29
1.00
9053.26
7680.28
1.00

biosynthesis

IV

(archaebacteria)

COA-PWY
coenzyme A
18
0.011481
2.71
31573.49
15899.61
1.00
11669.39
8761.12
1.00

biosynthesis I

PWY-7560
methylerythritol
19
0.011154
2.91
34272.25
17397.13
1.00
11765.12
9593.11
1.00

phosphate

pathway II

RIBOSYN2-
flavin
20
0.010712
2.85
28641.46
15772.99
1.00
10066.39
8106.69
1.00

PWY
biosynthesis I

(bacteria and

plants)

BRANCHED-
superpathway
21
0.009937
2.91
39111.81
23166.45
1.00
13457.08
11094.56
1.00

CHAIN-
of branched

AA-SYN-
amino acid

PWY
biosynthesis

PWY-5860
superpathway
22
0.009666
0.21
575.99
1472.32
0.96
2779.78
3938.60
0.98

of demethyl-

menaquinol-6

biosynthesis I

PWY-6122
5-
23
0.009549
2.65
35079.61
17750.87
1.00
13242.31
10142.08
1.00

aminoimidazole

ribonucleotide

biosynthesis II

P221-PWY
octane
24
0.009145
5.50
1918.80
2782.48
0.94
348.70
1946.70
0.61

oxidation

PWY-7219
adenosine
25
0.008760
2.69
38393.50
19673.06
1.00
14262.17
10745.91
1.00

ribonucleotides

de novo

biosynthesis

PWY-7374
1,4-dihydroxy-
26
0.008460
7.82
657.25
1065.52
0.89
84.04
289.90
0.50

6-naphthoate

biosynthesis I

PWY-7221
guanosine
27
0.008369
2.57
34118.96
16764.40
1.00
13250.25
10071.10
1.00

ribonucleotides

de novo

biosynthesis

PWY-6876
isopropanol
28
0.008211
3.99
435.82
1957.09
0.98
109.31
427.04
0.62

biosynthesis

AEROBACTINSYN-
aerobactin
29
0.007987
0.34
33.89
199.40
0.34
100.68
344.92
0.76

PWY
biosynthesis

PWY-5097
L-lysine
30
0.007645
2.69
37580.67
18590.79
1.00
13962.57
10737.14
1.00

biosynthesis

VI

PWY-5862
superpathway
31
0.007625
0.21
580.37
1491.91
0.96
2779.78
3938.60
0.98

of demethyl-

menaquinol-9

biosynthesis

PWY-5850
superpathway
32
0.007478
0.24
740.62
1757.63
0.96
3131.89
4208.09
0.98

of menaquinol-

6 biosynthesis

I

ARO-PWY
chorismate
33
0.007434
2.87
36039.29
19742.83
1.00
12557.51
9830.31
1.00

biosynthesis I

GLUTORN-
L-ornithine
34
0.007347
3.19
28029.94
21071.03
1.00
8786.17
7431.15
1.00

PWY
biosynthesis

PWY-6897
thiamin
35
0.007259
2.95
29830.89
20011.30
1.00
10120.35
8107.46
1.00

salvage II

PWY-5973
cis-vaccenate
36
0.007039
2.64
39974.77
20024.39
1.00
15125.38
11673.99
1.00

biosynthesis

PWY0-
methylphosphonate
37
0.006996
0.17
440.83
961.71
1.00
2590.86
3843.40
1.00

1533
degradation I

ORNDEG-
superpathway
38
0.006698
0.14
259.97
864.26
0.80
1817.47
3431.71
0.94

PWY
of ornithine

degradation

SER-
superpathway
39
0.006690
2.99
35169.03
20840.49
1.00
11750.83
10070.81
1.00

GLYSYN-
of L-serine and

PWY
glycine

biosynthesis I

TRPSYN-
L-tryptophan
40
0.006615
2.94
29664.21
16817.20
1.00
10083.33
8605.07
1.00

PWY
biosynthesis

GLUCARDEG-
D-glucarate
41
0.006503
0.32
713.12
954.82
1.00
2209.18
3044.60
0.99

PWY
degradation I

COMPLETE-
superpathway
42
0.006351
2.87
37695.43
20612.00
1.00
13134.09
10317.24
1.00

ARO-
of aromatic

PWY
amino acid

biosynthesis

ARGSYN-
L-arginine
43
0.006330
3.00
27182.21
17021.12
1.00
9052.44
7686.03
1.00

PWY
biosynthesis I

(via L-

ornithine)

VALSYN-
L-valine
44
0.006304
2.86
41221.30
24359.88
1.00
14398.84
11832.67
1.00

PWY
biosynthesis

ANAGLYCOLYSIS-
glycolysis III
45
0.006284
2.57
39616.54
19547.45
1.00
15433.71
11898.53
1.00

PWY
(from glucose)

PWY0-
polymyxin
46
0.006129
0.12
208.68
708.05
0.88
1669.87
3136.81
0.94

1338
resistance

PWY-6263
superpathway
47
0.005997
5.48
2196.54
3113.85
0.95
401.07
993.92
0.76

of menaquinol-

8 biosynthesis

II

PWY-7371
1,4-dihydroxy-
48
0.005991
4.89
1049.32
1966.55
0.95
214.45
753.96
0.76

6-naphthoate

biosynthesis II

PWY-5896
superpathway
49
0.005912
0.24
740.62
1757.63
0.96
3131.89
4208.09
0.98

of menaquinol-

10 biosynthesis

PWY-6277
superpathway
50
0.005811
2.65
35079.61
17750.87
1.00
13242.31
10142.08
1.00

of 5-

aminoimidazole

ribonucleotide

biosynthesis

PWY-5845
superpathway
51
0.005765
0.24
745.67
1779.05
0.96
3131.89
4208.09
0.98

of menaquinol-

9 biosynthesis

PWY-6123
inosine-5′-
52
0.005721
2.66
33605.59
16812.37
1.00
12632.90
9679.61
1.00

phosphate

biosynthesis I

ORNARGDEG-
superpathway
53
0.005704
0.14
226.66
792.76
0.81
1590.90
2877.92
0.94

PWY
of L-arginine

and L-

ornithine

degradation

ALL-
superpathway
54
0.005499
0.22
660.84
1761.20
0.88
3017.70
4247.08
0.95

CHORISMATE-
of chorismate

PWY
metabolism

PWY-6387
UDP-N-
55
0.005411
2.64
32982.38
16688.93
1.00
12506.69
9467.25
1.00

acetylmuramoyl-

pentapeptide

biosynthesis I

(meso-

diaminopimelate

containing)

ECASYN-
enterobacterial
56
0.005236
0.15
287.81
929.31
0.84
1973.75
3351.22
0.94

PWY
common

antigen

biosynthesis

PWY4FS-7
phosphatidyl-
57
0.004955
2.73
33519.39
19371.51
1.00
12271.48
9713.41
1.00

glycerol

biosynthesis I

(plastidic)

ILEUSYN-
L-isoleucine
58
0.004852
2.86
41221.30
24359.88
1.00
14398.84
11832.67
1.00

PWY
biosynthesis I

(from

threonine)

PWY-5505
L-glutamate
59
0.004847
3.28
23972.87
16186.06
1.00
7310.25
7222.51
1.00

and L-

glutamine

biosynthesis

ARGDEG-
superpathway
60
0.004835
0.14
226.66
792.76
0.81
1590.90
2877.92
0.94

PWY
of L-arginine,

putrescine, and

4-

aminobutanoate

degradation

P125-PWY
superpathway
61
0.004809
0.32
231.37
328.15
1.00
733.15
1571.48
0.99

of (R,R)-

butanediol

biosynthesis

GLYCOL-
superpathway
62
0.004791
0.16
284.90
791.20
0.97
1763.59
2790.66
0.95

GLYOXDEG-
of glycol

PWY
metabolism

and

degradation

PWY-6386
UDP-N-
63
0.004758
2.69
33067.64
16734.16
1.00
12310.17
9381.48
1.00

acetylmuramoyl-

pentapeptide

biosynthesis II

(lysine-

containing)

ARGSYNBSUB-
L-arginine
64
0.004717
3.13
27062.34
18615.53
1.00
8634.15
7616.24
1.00

PWY
biosynthesis II

(acetyl cycle)

ENTBACSYN-
enterobactin
65
0.004667
0.18
496.80
1444.67
0.90
2705.67
3835.84
0.95

PWY
biosynthesis

PWY-6385
peptidoglycan
66
0.004633
2.67
32618.20
16544.58
1.00
12234.28
9272.55
1.00

biosynthesis III

(mycobacteria)

THRESYN-
superpathway
67
0.004283
2.69
34985.56
17229.65
1.00
12990.68
10283.94
1.00

PWY
of L-threonine

biosynthesis

1CMET2-
N10-formyl-
68
0.004256
2.78
32237.40
17679.11
1.00
11590.50
9125.00
1.00

PWY
tetrahydrofolate

biosynthesis

CHLOROPHYLL-
chlorophyllide
69
0.004180
20.42
41.09
387.43
0.45
2.01
16.04
0.12

SYN
a biosynthesis I

(aerobic, light-

dependent)

PWY-6121
5-
70
0.004175
2.65
36122.21
18777.40
1.00
13634.17
10455.30
1.00

aminoimidazole

ribonucleotide

biosynthesis I

PEPTIDOGLYCANSYN-
peptidoglycan
71
0.004073
2.65
32818.46
16611.34
1.00
12377.64
9359.46
1.00

PWY
biosynthesis I

(meso-

diaminopimelate

containing)

PWY-5840
superpathway
72
0.003908
0.47
1968.52
3031.91
0.99
4165.06
4482.90
1.00

of menaquinol-

7 biosynthesis

GLUCOSE1PMETAB-
glucose and
73
0.003862
0.36
1220.90
2500.90
1.00
3377.19
4632.05
0.98

PWY
glucose-1-

phosphate

degradation

PWY-5898
superpathway
74
0.003817
0.44
1842.63
2934.13
0.99
4162.12
4654.22
1.00

of menaquinol-

12 biosynthesis

THREOCAT-
superpathway
75
0.003685
0.15
222.56
878.03
0.63
1442.16
3317.05
0.92

PWY
of L-threonine

metabolism

PWY-6737
starch
76
0.003682
3.02
46433.64
24911.85
1.00
15361.05
13716.01
1.00

degradation V

PWY-5198
factor 420
77
0.003618
9.78
83.15
311.29
0.41
8.50
56.00
0.10

biosynthesis

PWY-7286
7-(3-amino-3-
78
0.003512
9.43
96.80
355.08
0.39
10.27
67.59
0.09

carboxypropyl)-

wyosine

biosynthesis

GOLPDLCAT-
superpathway
79
0.003491
0.15
202.18
432.68
0.94
1327.51
3027.64
0.99

PWY
of glycerol

degradation to

1,3-

propanediol

TRNA-
tRNA charging
80
0.003406
2.68
33409.36
17003.72
1.00
12475.49
9660.68
1.00

CHARGING-

PWY

PWY-5531
chlorophyllide
81
0.003376
12.96
40.43
387.08
0.45
3.12
29.33
0.13

a biosynthesis

II (anaerobic)

PWY-5837
1,4-dihydroxy-
82
0.003372
0.35
1068.41
2492.81
0.99
3094.02
3998.36
1.00

2-naphthoate

biosynthesis I

PANTO-
phospho-
83
0.003348
2.99
27427.71
17827.49
1.00
9188.30
7627.50
1.00

PWY
pantothenate

biosynthesis I

PWY-6071
superpathway
84
0.003346
0.16
89.88
427.71
0.55
568.88
1706.56
0.90

of

phenylethylamine

degradation

PWY-6349
CDP-archaeol
85
0.003344
9.74
93.10
337.26
0.39
9.56
61.83
0.09

biosynthesis

PWY-5899
superpathway
86
0.003325
0.44
1842.63
2934.13
0.99
4162.12
4654.22
1.00

of menaquinol-

13 biosynthesis

PWY-2942
L-lysine
87
0.00331
2.63
37924.77
18778.14
1.00
14401.68
11021.52
1.00

biosynthesis III

PWY-5863
superpathway
88
0.003302
0.36
1152.27
2434.84
0.99
3219.88
3983.44
1.00

of phylloquinol

biosynthesis

PWY-5088
L-glutamate
89
0.003221
6.96
209.24
1073.54
0.39
30.06
372.41
0.17

degradation

VIII (to

propanoate)

GALACTARDEG-
D-galactarate
90
0.003178
0.30
457.74
911.54
1.00
1522.96
2545.94
0.98

PWY
degradation I

PWY-6350
archaetidylinositol
91
0.003156
9.68
88.45
322.32
0.39
9.14
59.35
0.09

biosynthesis

CALVIN-
Calvin-
92
0.003140
2.64
41919.47
23350.92
1.00
15850.71
12125.61
1.00

PWY
Benson-

Bassham cycle

PWY-5861
superpathway
93
0.003113
0.42
1653.88
3067.35
0.99
3894.44
4510.05
0.99

of demethyl-

menaquinol-8

biosynthesis

PWY4FS-8
phosphatidyl-
94
0.003073
2.73
33519.39
19371.51
1.00
12271.48
9713.41
1.00

glycerol

biosynthesis II

(non-plastidic)

PWY-7159
chlorophyllide
95
0.003022
12.96
40.43
387.08
0.45
3.12
29.33
0.13

a biosynthesis

III (aerobic,

light

independent)

PHOSLIPSYN-
superpathway
96
0.002996
2.69
36158.35
20262.73
1.00
13420.46
10360.64
1.00

PWY
of

phospholipid

biosynthesis I

(bacteria)

PWY0-
3-
97
0.002930
0.12
82.25
397.30
0.61
688.95
2092.65
0.87

1277
phenylpropanoate

and 3-(3-

hydroxyphenyl)pro-

panoate

degradation

PWY-5304
superpathway
98
0.002906
3.96
8480.96
8403.25
0.99
2141.59
3792.29
0.99

of sulfur

oxidation

(Acidianus

ambivalens)

PWY-6690
cinnamate and
99
0.002899
0.09
49.91
274.08
0.61
549.96
1846.32
0.87

3-

hydroxycinnamate

degradation to

2-oxopent-4-

enoate

GLUCARGALACTSUPER-
superpathway
100
0.002897
0.30
457.74
911.54
1.00
1522.96
2545.94
0.98

PWY
of D-glucarate

and D-

galactarate

degradation

IBS = Irritable Bowel Syndrome; CDI = Clostridiodes difficile Infection; RFFR = Random Forest Feature Rank; # = Rank; MDA = Mean Decrease Accuracy; FC = Fold Change; M = Mean; SD = Standard Deviation; DP = Detection Prevalence;

TABLE 8

IBS vs Control delineation features - (metabolic pathway)

FC

MetaCyc

IBS

Pathway
Pathway
RFFR
vs
Abundance (IBS)
Abundance (Ctrl)

ID
description
#
MDA
Ctrl
M
SD
DP
M
SD
DP

PWY-7431
aromatic
1
0.014123
14.22
887.36
3722.68
0.97
62.42
336.03
0.87

biogenic amine

degradation

(bacteria)

PWY-5384
sucrose
2
0.011419
0.81
12053.55
10048.97
1.00
14862.20
23647.49
1.00

degradation IV

(sucrose

phosphorylase)

PWY-7539
6-
3
0.011042
1.18
28384.93
19568.26
1.00
24023.34
57775.64
1.00

hydroxymethyl-

dihydropterin

diphosphate

biosynthesis III

(Chlamydia)

PWY-6147
6-
4
0.010145
1.17
27827.44
19724.99
1.00
23773.45
55311.45
1.00

hydroxymethyl-

dihydropterin

diphosphate

biosynthesis I

PWY-6897
thiamin
5
0.009322
1.15
29830.89
20011.30
1.00
25927.29
55804.92
1.00

salvage II

FOLSYN-
superpathway
6
0.009318
1.10
28875.19
16869.28
1.00
26199.43
57898.05
1.00

PWY
of

tetrahydrofolate

biosynthesis

and salvage

PWY-6612
superpathway
7
0.008412
1.10
26345.17
15621.53
1.00
23842.31
53794.55
1.00

of

tetrahydrofolate

biosynthesis

PANTO-
phosphopantothenate
8
0.008230
1.18
27427.71
17827.49
1.00
23307.92
51652.13
1.00

PWY
biosynthesis I

TRPSYN-
L-tryptophan
9
0.008122
1.12
29664.21
16817.20
1.00
26384.56
58066.86
1.00

PWY
biosynthesis

PWY-6471
peptidoglycan
10
0.007584
0.76
11749.05
9689.53
1.00
15517.50
26202.50
1.00

biosynthesis

IV

(Enterococcus

faecium)

AEROBACTINSYN-
aerobactin
11
0.007503
1.44
33.89
199.40
0.34
23.54
124.70
0.55

PWY
biosynthesis

PWY-5862
superpathway
12
0.006770
0.42
580.37
1491.91
0.96
1368.48
7127.97
0.96

of

demethyl-

menaquinol-9

biosynthesis

RIBOSYN2-
flavin
13
0.006589
1.11
28641.46
15772.99
1.00
25710.38
56666.93
1.00

PWY
biosynthesis I

(bacteria and

plants)

PWY-5850
superpathway
14
0.006559
0.43
740.62
1757.63
0.96
1715.12
8129.74
0.96

of menaquinol-

6 biosynthesis

I

PWY-5860
superpathway
15
0.006553
0.42
575.99
1472.32
0.96
1368.24
7127.97
0.96

of

demethylmena

quinol-6

biosynthesis I

THREOCAT-
superpathway
16
0.006475
0.46
222.56
878.03
0.63
487.43
6491.20
0.77

PWY
of L-threonine

metabolism

PWY-5896
superpathway
17
0.006405
0.43
740.62
1757.63
0.96
1715.12
8129.74
0.96

of menaquinol-

10 biosynthesis

PWY-5973
cis-vaccenate
18
0.006371
1.06
39974.77
20024.39
1.00
37597.57
77633.61
1.00

biosynthesis

PWY-7663
gondoate
19
0.006351
1.06
43224.23
21636.87
1.00
40750.28
88888.09
1.00

biosynthesis

(anaerobic)

PWY-5845
superpathway
20
0.006241
0.43
745.67
1779.05
0.96
1715.46
8129.75
0.96

of menaquinol-

9 biosynthesis

PWY-6122
5-
21
0.005919
1.03
35079.61
17750.87
1.00
34211.58
67927.32
1.00

aminoimidazole

ribonucleotide

biosynthesis II

PWY-7159
chlorophyllide
22
0.005875
4.89
40.43
387.08
0.45
8.26
66.18
0.25

a biosynthesis

III (aerobic,

light

independent)

PWY-5531
chlorophyllide
23
0.005705
4.89
40.43
387.08
0.45
8.26
66.18
0.25

a biosynthesis

II (anaerobic)

PANTOSYN-
pantothenate
24
0.005661
1.13
28076.23
16189.06
1.00
24898.21
53813.43
1.00

PWY
and coenzyme

A biosynthesis

I

PWY-6478
GDP-D-
25
0.005598
0.79
2886.94
2928.03
1.00
3648.36
12511.71
1.00

glycero-

α-D-

manno-heptose

biosynthesis

PYRIDNUCSAL-
NAD salvage
26
0.005370
1.07
29619.59
15707.18
1.00
27573.47
56793.93
1.00

PWY
pathway I

CHLOROPHYLL-
chlorophyllide
27
0.005349
4.74
41.09
387.43
0.45
8.68
68.06
0.25

SYN
a biosynthesis I

(aerobic, light-

dependent)

P562-PWY
myo-inositol
28
0.005304
4.89
7805.01
18297.70
1.00
1595.53
6010.83
1.00

degradation I

NONMEVIPP-
methylerythritol
29
0.005289
1.04
34272.25
17397.13
1.00
32817.44
66602.58
1.00

PWY
phosphate

pathway I

P221-PWY
octane
30
0.005180
0.87
1918.80
2782.48
0.94
2201.27
4989.83
0.99

oxidation

PWY-3781
aerobic
31
0.004797
14.00
18914.47
55652.73
0.97
1350.90
12245.02
0.85

respiration I

(cytochrome c)

PWY-6703
preQ0
32
0.004679
1.26
21142.14
17391.99
1.00
16750.81
43567.02
1.00

biosynthesis

PYRIDNUCSYN-
NAD
33
0.004640
1.08
28698.20
15283.44
1.00
26519.01
54429.15
1.00

PWY
biosynthesis I

(from

aspartate)

PWY-6588
pyruvate
34
0.004599
1.12
4021.28
4225.75
1.00
3584.20
7857.69
1.00

fermentation to

acetone

THRESYN-
superpathway
35
0.004566
1.03
34985.56
17229.65
1.00
33804.17
69499.08
1.00

PWY
of L-threonine

biosynthesis

PWY-6123
inosine-5′-
36
0.004536
1.03
33605.59
16812.37
1.00
32731.91
67616.56
1.00

phosphate

biosynthesis I

COA-PWY
coenzyme A
37
0.004452
1.03
31573.49
15899.61
1.00
30734.70
62246.18
1.00

biosynthesis I

PWY-3001
superpathway
38
0.004356
1.05
36808.04
19082.06
1.00
34993.92
70100.63
1.00

of L-isoleucine

biosynthesis I

PWY-6277
superpathway
39
0.004286
1.03
35079.61
17750.87
1.00
34211.58
67927.32
1.00

of 5-

aminoimidazole

ribonucleotide

biosynthesis

PWY-7377
cob(II)yrinate
40
0.004245
0.91
4178.37
4919.06
1.00
4593.83
12482.29
1.00

a,c-diamide

biosynthesis I

(early cobalt

insertion)

PWY-6892
thiazole
41
0.004164
0.88
24004.43
15083.44
1.00
27367.72
60807.66
1.00

biosynthesis I

(E. coli)

PWY-7209
superpathway
42
0.004036
0.56
8.24
37.62
0.22
14.68
77.78
0.28

of pyrimidine

ribonucleosides

degradation

P122-PWY
heterolactic
43
0.004004
0.56
1916.48
3035.80
1.00
3434.87
7997.81
1.00

fermentation

PWY-5121
superpathway
44
0.003978
0.89
28115.14
15593.29
1.00
31735.49
63961.74
1.00

of

geranylgeranyl

diphosphate

biosynthesis II

(via MEP)

PWY-5507
adenosylcobalamin
45
0.003896
0.85
75.98
227.22
0.63
89.34
312.06
0.40

biosynthesis I

(early cobalt

insertion)

CODH-
reductive
46
0.003864
0.88
752.09
1110.08
0.88
858.65
2009.75
0.95

PWY
acetyl

coenzyme A

pathway

ASPASN-
superpathway
47
0.003805
0.87
24106.22
15009.33
1.00
27802.72
61241.17
1.00

PWY
of L-aspartate

and L-

asparagine

biosynthesis

PWY-5005
biotin
48
0.003798
0.96
1570.46
2924.05
1.00
1637.01
6066.53
0.99

biosynthesis II

ANAGLYCOLYSIS-
glycolysis III
49
0.003794
1.03
39616.54
19547.45
1.00
38524.25
76074.72
1.00

PWY
(from glucose)

PWY-7219
adenosine
50
0.003776
1.04
38393.50
19673.06
1.00
36934.72
73745.19
1.00

ribonucleotides

de novo

biosynthesis

PWY-6470
peptidoglycan
51
0.003776
0.82
1073.61
1624.85
0.94
1308.86
3807.12
0.98

biosynthesis V

(β-lactam

resistance)

PWY0-
anhydromuropeptides
52
0.003769
0.87
9061.13
7252.08
1.00
10433.27
26429.41
1.00

1261
recycling

PWY-6387
UDP-N-
53
0.003709
1.03
32982.38
16688.93
1.00
31963.32
63342.58
1.00

acetylmuramoyl-

pentapeptide

biosynthesis I

(meso-

diaminopimelate

containing)

PWY-5097
L-lysine
54
0.003698
1.04
37580.67
18590.79
1.00
36065.98
71069.75
1.00

biosynthesis

VI

PWY-7560
methylerythritol
55
0.003697
1.04
34272.25
17397.13
1.00
32817.44
66602.58
1.00

phosphate

pathway II

1CMET2-
N10-formyl-
56
0.003683
1.09
32237.40
17679.11
1.00
29667.15
61241.36
1.00

PWY
tetrahydrofolate

biosynthesis

PEPTIDOGLYCANSYN-
peptidoglycan
57
0.003643
1.03
32818.46
16611.34
1.00
31783.86
62985.20
1.00

PWY
biosynthesis I

(meso-

diaminopimelate

containing)

PWY-5971
palmitate
58
0.003616
0.86
11036.11
9374.84
0.97
12902.75
46991.68
1.00

biosynthesis II

(bacteria and

plants)

P124-PWY
Bifidobacterium
59
0.003573
0.49
2397.16
3856.49
1.00
4916.18
11478.79
1.00

shunt

HCAMHPDEG-
3-
60
0.003547
0.22
49.91
274.08
0.61
224.09
3798.41
0.69

PWY
phenylpropanoate

and 3-(3-

hydroxyphenyl)pro-

panoate

degradation to

2-oxopent-4-

enoate

GLYCOCAT-
glycogen
61
0.003545
0.92
36577.81
20297.09
1.00
39548.53
74794.98
1.00

PWY
degradation I

(bacterial)

PWY-7332
superpathway
62
0.003526
1.64
1866.86
3130.64
0.99
1135.16
3807.64
0.99

of UDP-N-

acetylglucosamine-

derived O-

antigen

building blocks

biosynthesis

PWY0-321
phenylacetate
63
0.003478
0.25
97.88
458.92
0.59
384.08
5893.00
0.73

degradation I

(aerobic)

CALVIN-
Calvin-
64
0.003453
1.08
41919.47
23350.92
1.00
38789.56
77297.80
1.00

PWY
Benson-

Bassham cycle

PWY-6891
thiazole
65
0.003426
0.69
4147.43
4624.29
1.00
5971.37
17637.92
1.00

biosynthesis II

(Bacillus)

TYRFUMCAT-
L-tyrosine
66
0.003394
162.96
8292.04
25541.88
0.71
50.88
672.98
0.49

PWY
degradation I

PWY-6901
superpathway
67
0.003392
0.88
14133.50
11721.70
1.00
16138.44
42305.62
1.00

of glucose and

xylose

degradation

PWY-6121
5-
68
0.003379
1.04
36122.21
18777.40
1.00
34599.61
69821.14
1.00

aminoimidazole

ribonucleotide

biosynthesis I

PWY-6386
UDP-N-
69
0.003369
1.03
33067.64
16734.16
1.00
32031.44
63604.98
1.00

acetylmuramoyl-

pentapeptide

biosynthesis II

(lysine-

containing)

PWY-6385
peptidoglycan
70
0.003368
1.04
32618.20
16544.58
1.00
31498.67
62616.82
1.00

biosynthesis III

(mycobacteria)

PWY-5104
L-isoleucine
71
0.003362
1.06
40466.33
21816.16
1.00
38032.50
72813.36
1.00

biosynthesis

IV

PWY-6071
superpathway
72
0.00336
0.24
89.88
427.71
0.55
374.41
5866.29
0.72

of

phenylethylamine

degradation

RHAMCAT-
L-rhamnose
73
0.003357
0.92
12302.08
9773.21
1.00
13374.68
37212.50
1.00

PWY
degradation I

PWY-7229
superpathway
74
0.003348
1.05
39152.22
20656.79
1.00
37269.82
76809.15
1.00

of adenosine

nucleotides de

novo

biosynthesis I

PWY-5180
toluene
75
0.003289
1.15
560.43
1701.69
0.72
487.77
5058.33
0.71

degradation I

(aerobic) (via

o-cresol)

P461-PWY
hexitol
76
0.003286
0.99
6458.37
8233.31
0.99
6535.35
17451.16
1.00

fermentation to

lactate,

formate,

ethanol and

acetate

PWY-7221
guanosine
77
0.003258
1.02
34118.96
16764.40
1.00
33485.60
67311.36
1.00

ribonucleotides

de novo

biosynthesis

GLUTORN-
L-ornithine
78
0.003245
1.19
28029.94
21071.03
1.00
23616.52
46464.24
1.00

PWY
biosynthesis

PWY-1861
formaldehyde
79
0.003241
0.95
5230.18
6529.30
0.99
5534.53
15193.86
1.00

assimilation II

(RuMP Cycle)

PWY-6609
adenine and
80
0.003216
0.86
27163.52
16702.31
1.00
31727.63
63046.81
1.00

adenosine

salvage III

ANAEROFRUCAT-
homolactic
81
0.003208
0.86
22408.10
13981.72
1.00
25969.53
52349.57
1.00

PWY
fermentation

P162-PWY
L-glutamate
82
0.003202
1.54
691.93
1607.02
0.96
448.71
887.20
0.99

degradation V

(via

hydroxyglutarate)

PWY-6396
superpathway
83
0.003194
1.01
275.96
417.27
1.00
273.69
669.20
0.99

of 2,3-

butanediol

biosynthesis

P125-PWY
superpathway
84
0.003160
1.01
231.37
328.15
1.00
229.19
592.66
0.99

of (R,R)-

butanediol

biosynthesis

PWYG-
mycolate
85
0.003135
0.89
16761.86
12981.23
1.00
18886.83
63656.02
1.00

321
biosynthesis

PWY-6163
chorismate
86
0.003131
1.07
36411.39
19257.17
1.00
34156.88
67511.88
1.00

biosynthesis

from 3-

dehydroquinate

PWY-5686
UMP
87
0.003129
1.06
38378.86
20600.14
1.00
36137.39
71110.33
1.00

biosynthesis

PWY-5705
allantoin
88
0.003119
0.99
834.17
801.60
1.00
846.36
1653.24
1.00

degradation to

glyoxylate III

PWY0-
3-
89
0.003119
0.26
82.25
397.30
0.61
318.48
5027.86
0.69

1277
phenylpropanoate

and 3-(3-hydroxy-

phenyl)propanoate

degradation

GLUCUROCAT-
superpathway
90
0.003117
0.85
9930.86
6803.57
1.00
11711.24
23892.96
1.00

PWY
of β-D-

glucuronide

and D-

glucuronate

degradation

FASYN-
superpathway
91
0.003117
0.88
13225.39
10552.14
1.00
15098.44
51390.08
1.00

INITIAL-
of fatty acid

PWY
biosynthesis

initiation (E.

coli)

ARGORNPROST-
arginine,
92
0.003117
0.61
1410.86
2008.22
1.00
2313.51
6466.68
1.00

PWY
ornithine and

proline

interconversion

PWY-5103
L-isoleucine
93
0.003077
1.08
38191.84
21780.55
1.00
35363.64
68670.88
1.00

biosynthesis III

PWY-5667
CDP-
94
0.003073
1.08
39618.43
22110.97
1.00
36676.06
68483.69
1.00

diacylglycerol

biosynthesis I

PWY0-862
(5Z)-dodec-5-
95
0.003031
0.88
15346.68
11982.52
1.00
17509.60
58833.48
1.00

enoate

biosynthesis

PWY-6690
cinnamate and
96
0.003024
0.22
49.91
274.08
0.61
224.09
3798.41
0.69

3-

hydroxycinnamate

degradation to

2-oxopent-4-

enoate

PWY-5088
L-glutamate
97
0.003003
3.17
209.24
1073.54
0.39
66.06
357.04
0.42

degradation

VIII (to

propanoate)

PWY0-
CDP-
98
0.002978
1.08
39618.43
22110.97
1.00
36676.06
68483.69
1.00

1319
diacylglycerol

biosynthesis II

LACTOSECAT-
lactose and
99
0.002966
0.85
476.71
937.69
0.95
559.72
2143.31
0.99

PWY
galactose

degradation I

PWY-2941
L-lysine
100
0.002951
0.67
2868.11
3966.27
1.00
4274.30
9871.39
1.00

biosynthesis II

IBS = Irritable Bowel Syndrome;

Ctrl = Control;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 9

IBS vs Control delineation features - (taxonomy)

Feature
FC

(Taxonomic order: Kingdom;
IBS
Abundance
Abundance

Phylum; Class; Order;
RFFR
vs
(Ctrl)
(IBS)

Family; Genus; Species)
#
MDA
Ctrl
M
SD
DP
M
SD
DP

Bacteria; Other; Other; Other;
1
0.018394
1.007746
0.005479
0.021341
0.819038
0.005521
0.011388
0.966102

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
2
0.012333
3.716663
0.002311
0.004024
0.911088
0.008589
0.017120
0.903148

Clostridiales; Lachnospiraceae;

Anaerostipes; Other

Bacteria; Firmicutes; Other;
3
0.012236
1.476355
0.000772
0.001531
0.731172
0.001140
0.001970
0.869249

Other; Other; Other; Other

Bacteria; Bacteroidetes;
4
0.010558
44.235186
0.000000
0.000004
0.006276
0.000009
0.000033
0.121065

Sphingobacteriia; Sphingobacteriales;

Sphingobacteriaceae; Pedobacter;

Other

Bacteria; Firmicutes; Clostridia;
5
0.010242
2.249361
0.013600
0.022700
0.991632
0.030591
0.053003
0.924939

Clostridiales; Lachnospiraceae;

Blautia; Other

Bacteria; Firmicutes; Bacilli;
6
0.010107
3.008967
0.000579
0.011930
0.434100
0.001743
0.006303
0.602906

Lactobacillales; Streptococcaceae;

Streptococcus; Streptococcus

thermophilus

Bacteria; Firmicutes; Bacilli;
7
0.009640
1.648123
0.000149
0.000878
0.277197
0.000246
0.000996
0.559322

Lactobacillales; Streptococcaceae;

Streptococcus; Streptococcus

parasanguinis

Bacteria; Actinobacteria; Actinobacteria;
8
0.009473
0.499128
0.003260
0.011115
0.519874
0.001627
0.007075
0.292978

Coriobacteriales; Coriobacteriaceae;

Collinsella; Other

Bacteria; Firmicutes; Clostridia;
9
0.009386
0.749057
0.041475
0.042224
0.967573
0.031067
0.038784
0.978208

Clostridiales; Ruminococcaceae;

Faecalibacterium; Other

Bacteria; Actinobacteria; Coriobacteriia;
10
0.009017
0.129289
0.010594
0.025323
0.555439
0.001370
0.005518
0.351090

Coriobacteriales; Coriobacteriaceae;

Collinsella; Collinsella aerofaciens

Bacteria; Candidatus
11
0.008915
14.347685
0.000016
0.000094
0.109833
0.000232
0.001213
0.295400

Saccharibacteria; Saccharibacteria_—

genera_incertae_sedis; Other;

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
12
0.008694
3.868790
0.000389
0.001534
0.315900
0.001507
0.004129
0.435835

Clostridiales; Lachnospiraceae;

Blautia; Blautia stercoris

Bacteria; Proteobacteria;
13
0.008468
0.311194
0.000389
0.006951
0.187238
0.000121
0.000994
0.394673

Gammaproteobacteria; Pseudomonadales;

Pseudomonadaceae; Pseudomonas;

Other

Bacteria; Firmicutes; Clostridia;
14
0.008360
10.002237
0.000189
0.001137
0.438285
0.001891
0.008662
0.590799

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Other

Bacteria; Firmicutes; Clostridia;
15
0.008041
4.587045
0.000891
0.003813
0.756276
0.004088
0.010861
0.801453

Clostridiales; Peptostreptococcaceae;

Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
16
0.007743
0.513588
0.041765
0.060175
0.972803
0.021450
0.045829
0.927361

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

vulgatus

Bacteria; Bacteroidetes; Bacteroidia;
17
0.007300
1.615243
0.010596
0.035655
0.311715
0.017116
0.050016
0.539952

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

plebeius

Bacteria; Firmicutes; Clostridia;
18
0.006978
2.262828
0.002631
0.004823
0.891213
0.005954
0.013082
0.893462

Clostridiales; Lachnospiraceae;

Roseburia; Other

Bacteria; Firmicutes; Bacilli;
19
0.006728
1.498175
0.000033
0.000095
0.231172
0.000049
0.000115
0.421308

Lactobacillales; Carnobacteriaceae;

Granulicatella; Other

Bacteria; Firmicutes; Clostridia;
20
0.006484
1.176775
0.016905
0.025464
0.755230
0.019894
0.026907
0.869249

Clostridiales; Ruminococcaceae;

Faecalibacterium; Faecalibacterium

prausnitzii

Bacteria; Bacteroidetes; Bacteroidia;
21
0.006241
1.501339
0.026934
0.054373
0.777197
0.040437
0.064921
0.842615

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides dorei

Bacteria; Actinobacteria;
22
0.006237
0.142245
0.000809
0.004296
0.456067
0.000115
0.000526
0.389831

Coriobacteriia; Eggerthellales;

Eggerthellaceae; Adlercreutzia;

Adlercreutzia equolifaciens

Bacteria; Bacteroidetes; Bacteroidia;
23
0.006185
1.108835
0.036984
0.104763
0.619247
0.041010
0.107593
0.777240

Bacteroidales; Prevotellaceae;

Prevotella; Other

Bacteria; Firmicutes; Clostridia;
24
0.006130
0.963933
0.047176
0.039074
0.991632
0.045474
0.037841
0.968523

Clostridiales; Lachnospiraceae;

Other; Other

Bacteria; Firmicutes; Bacilli;
25
0.005797
13.117334
0.000002
0.000022
0.029289
0.000024
0.000095
0.162228

Bacillales; Bacillales_Incertae Sedis

XI; Gemella; Other

Bacteria; Firmicutes; Negativicutes;
26
0.005660
NA -
0.000000
0.000000
0.000000
0.000048
0.000333
0.096852

Veillonellales; Veillonellaceae;

Div

Veillonella; Veillonella

by 0

infantium

Bacteria; Firmicutes; Clostridia;
27
0.005564
1.469854
0.004115
0.005620
0.901674
0.006049
0.009841
0.796610

Clostridiales; Lachnospiraceae;

Dorea; Other

Bacteria; Firmicutes; Clostridia;
28
0.005365
1.009624
0.026222
0.040290
0.913180
0.026474
0.041908
0.820823

Clostridiales; Lachnospiraceae;

Blautia; Blautia wexlerae

Bacteria; Firmicutes; Clostridia;
29
0.005248
1.256043
0.017321
0.019449
0.981172
0.021757
0.027256
0.934625

Clostridiales; Lachnospiraceae;

Lachnospiracea_incertae_sedis;

Other

Bacteria; Firmicutes; Clostridia;
30
0.004950
2.391660
0.001974
0.005469
0.876569
0.004722
0.010883
0.857143

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Other

Bacteria; Bacteroidetes; Bacteroidia;
31
0.004935
1.268464
0.030745
0.095100
0.539749
0.038999
0.113177
0.685230

Bacteroidales; Prevotellaceae;

Prevotella; Prevotella copri

Bacteria; Cyanobacteria/Chloroplast;
32
0.004899
5.476367
0.000125
0.001867
0.233264
0.000683
0.004707
0.382567

Chloroplast; Chloroplast;

Streptophyta; Other; Other

Bacteria; Proteobacteria;
33
0.004866
101182.303196
0.000000
0.000001
0.004184
0.005094
0.028774
0.099274

Alphaproteobacteria; Caulobacterales;

Caulobacteraceae; Caulobacter;

Caulobacter segnis

Bacteria; Proteobacteria;
34
0.004862
NA -
0.000000
0.000000
0.000000
0.000009
0.000056
0.089588

Betaproteobacteria; Nitrosomonadales;

Div

Methylophilaceae; Methylophilus;

by 0

Other

Bacteria; Firmicutes; Clostridia;
35
0.004704
1.003530
0.016348
0.020690
0.988494
0.016406
0.016525
0.944310

Clostridiales; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
36
0.004631
0.650077
0.001006
0.004950
0.701883
0.000654
0.001669
0.748184

Bacteroidales; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
37
0.004626
0.562319
0.030320
0.042820
0.952929
0.017049
0.027156
0.903148

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

uniformis

Bacteria; Firmicutes; Bacilli;
38
0.004625
22.272015
0.000002
0.000023
0.050209
0.000044
0.000234
0.121065

Lactobacillales; Streptococcaceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
39
0.004592
0.675049
0.011136
0.014246
0.933054
0.007517
0.010821
0.871671

Clostridiales; Lachnospiraceae;

Fusicatenibacter;

Fusicatenibacter saccharivorans

Bacteria; Firmicutes; Clostridia;
40
0.004525
0.952312
0.000797
0.003787
0.583682
0.000759
0.002089
0.716707

Clostridiales; Lachnospiraceae;

Lachnoclostridium; [Clostridium]

bolteae

Bacteria; Proteobacteria;
41
0.004522
14.064952
0.000002
0.000026
0.020921
0.000028
0.000177
0.133172

Betaproteobacteria; Burkholderiales;

Comamonadaceae; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
42
0.004481
0.839811
0.061864
0.066323
0.995816
0.051954
0.062313
0.961259

Bacteroidales; Bacteroidaceae;

Bacteroides; Other

Bacteria; Firmicutes; Clostridia;
43
0.004471
0.830226
0.018787
0.024996
0.982218
0.015597
0.018427
0.934625

Clostridiales; Ruminococcaceae;

Other; Other

Bacteria; Firmicutes; Negativicutes;
44
0.004449
3.265531
0.002311
0.007033
0.512552
0.007546
0.022229
0.631961

Selenomonadales; Veillonellaceae;

Dialister; Other

Bacteria; Firmicutes; Clostridia;
45
0.004449
0.151074
0.001034
0.005783
0.419456
0.000156
0.000820
0.36396

Clostridiales; Lachnospiraceae;

Blautia; Blautia hominis

Bacteria; Proteobacteria;
46
0.004420
123819.901979
0.000001
0.000015
0.003138
0.087316
0.269557
0.099274

Betaproteobacteria; Burkholderiales;

Burkholderiaceae; Burkholderia;

Other

Bacteria; Firmicutes; Clostridia;
47
0.004342
2.825478
0.000261
0.001295
0.320084
0.000738
0.002749
0.450363

Clostridiales; Peptostreptococcaceae;

Romboutsia; Other

Bacteria; Proteobacteria;
48
0.004217
NA -
0.000000
0.000000
0.000000
0.000010
0.000036
0.096852

Betaproteobacteria; Burkholderiales;

Div

Burkholderiaceae; Burkholderia;

by 0

Burkholderia ambifaria

Bacteria; Proteobacteria;
49
0.004194
13.513031
0.000020
0.000091
0.140167
0.000274
0.000849
0.210654

Betaproteobacteria; Other; Other;

Other; Other

Bacteria; Proteobacteria;
50
0.004125
NA -
0.000000
0.000000
0.000000
0.000283
0.001381
0.101695

Alphaproteobacteria; Caulobacterales;

Div

Caulobacteraceae; Caulobacter;

by 0

Other

Bacteria; Firmicutes; Clostridia;
51
0.004081
0.000000
0.000334
0.001238
0.169456
0.000000
0.000000
0.000000

Clostridiales; Lachnospiraceae;

Dorea; Dorea formicigenerans

Bacteria; Proteobacteria;
52
0.004054
0.308358
0.018587
0.056891
0.816946
0.005732
0.028681
0.765133

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
53
0.003999
1.495197
0.007223
0.026249
0.260460
0.010799
0.032470
0.433414

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

coprocola

Bacteria; Proteobacteria;
54
0.003960
386.174767
0.000000
0.000005
0.008368
0.000118
0.001758
0.099274

Alphaproteobacteria; Rhizobiales;

Phyllobacteriaceae; Phyllobacterium;

Other

Bacteria; Actinobacteria;
55
0.003950
0.328857
0.000223
0.000872
0.456067
0.000073
0.000244
0.331719

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
56
0.003944
0.670233
0.007882
0.013361
0.888075
0.005283
0.010157
0.767554

Clostridiales; Lachnospiraceae;

Blautia; Blautia obeum

Bacteria; Firmicutes; Clostridia;
57
0.003905
0.566696
0.007247
0.013333
0.910042
0.004107
0.005814
0.779661

Clostridiales; Lachnospiraceae;

Blautia; Blautia faecis

Bacteria; Proteobacteria;
58
0.003889
NA -
0.000000
0.000000
0.000000
0.000554
0.001748
0.096852

Betaproteobacteria; Burkholderiales;

Div

Burkholderiaceae; Other; Other

by 0

Bacteria; Actinobacteria;
59
0.003789
0.339497
0.000169
0.000438
0.498954
0.000057
0.000132
0.440678

Actinobacteria; Actinomycetales;

Actinomycetaceae; Schaalia; Schaalia

odontolytica

Bacteria; Firmicutes; Clostridia;
60
0.003757
0.525861
0.015276
0.024437
0.915272
0.008033
0.011088
0.849879

Clostridiales; Lachnospiraceae;

Blautia; Blautia luti

Bacteria; Proteobacteria;
61
0.003749
8.446078
0.000005
0.000044
0.024059
0.000039
0.000211
0.118644

Alphaproteobacteria; Sphingomonadales;

Sphingomonadaceae; Sphingomonas;

Other

Bacteria; Bacteroidetes; Bacteroidia;
62
0.003732
0.909853
0.000241
0.001067
0.518828
0.000219
0.000524
0.639225

Bacteroidales; Porphyromonadaceae;

Odoribacter; Other

Bacteria; Firmicutes; Clostridia;
63
0.003685
0.979763
0.027343
0.033723
0.892259
0.026790
0.042600
0.927361

Clostridiales; Lachnospiraceae;

Not Available; [Eubacterium]

rectale

Bacteria; Firmicutes; Erysipelotrichia;
64
0.003664
3.717831
0.000012
0.000046
0.188285
0.000046
0.000161
0.341404

Erysipelotrichales; Erysipelotrichaceae;

Solobacterium; Solobacterium

moorei

Bacteria; Firmicutes; Clostridia;
65
0.003661
0.891194
0.007228
0.030628
0.802301
0.006442
0.014729
0.920097

Clostridiales; Peptostreptococcaceae;

Romboutsia; Romboutsia

timonensis

Bacteria; Bacteroidetes; Bacteroidia;
66
0.003640
1.195185
0.001405
0.008557
0.092050
0.001679
0.006990
0.208232

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

coprophilus

Bacteria; Firmicutes; Clostridia;
67
0.003590
0.718857
0.006404
0.011919
0.855649
0.004604
0.008826
0.723971

Clostridiales; Ruminococcaceae;

Ruminococcus; Ruminococcus

faecis

Bacteria; Firmicutes; Clostridia;
68
0.003561
1.364636
0.000871
0.003572
0.674686
0.001188
0.004845
0.714286

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia hominis

Bacteria; Firmicutes; Clostridia;
69
0.003550
1.192065
0.016148
0.023196
0.965481
0.019249
0.028624
0.905569

Clostridiales; Lachnospiraceae;

Anaerostipes; Anaerostipes

hadrus

Bacteria; Bacteroidetes; Bacteroidia;
70
0.003507
0.621597
0.002446
0.004682
0.764644
0.001521
0.002372
0.799031

Bacteroidales; Odoribacteraceae;

Odoribacter; Odoribacter

splanchnicus

Bacteria; Firmicutes; Clostridia;
71
0.003468
1.506781
0.002996
0.007844
0.741632
0.004514
0.012317
0.876513

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Intestinibacter

bartlettii

Bacteria; Firmicutes; Clostridia;
72
0.003456
0.663227
0.004547
0.006250
0.803347
0.003015
0.004631
0.685230

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus

comes

Bacteria; Firmicutes; Clostridia;
73
0.003452
1.108955
0.000966
0.002406
0.737448
0.001071
0.002925
0.791768

Clostridiales; Ruminococcaceae;

Flavonifractor; Flavonifractor

plautii

Bacteria; Proteobacteria;
74
0.003434
3.979368
0.000078
0.000419
0.219665
0.000310
0.000933
0.302663

Betaproteobacteria; Burkholderiales;

Other; Other; Other

Bacteria; Actinobacteria;
75
0.003422
0.541252
0.010770
0.034421
0.756276
0.005829
0.020871
0.799031

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Other

Bacteria; Firmicutes; Clostridia;
76
0.003386
0.684883
0.009032
0.011433
0.851464
0.006186
0.008890
0.736077

Clostridiales; Lachnospiraceae;

Dorea; Dorea longicatena

Bacteria; Firmicutes; Clostridia;
77
0.003354
1.413307
0.003746
0.007142
0.809623
0.005294
0.008906
0.818402

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia

inulinivorans

Bacteria; Firmicutes; Clostridia;
78
0.003339
0.800991
0.002003
0.003530
0.778243
0.001605
0.002634
0.750605

Clostridiales; Ruminococcaceae;

Agathobaculum; Agathobaculum

butyriciproducens

Bacteria; Actinobacteria;
79
0.003318
0.249526
0.000541
0.001754
0.474895
0.000135
0.000423
0.401937

Coriobacteriia; Eggerthellales;

Eggerthellaceae; Eggerthella; Eggerthella

lenta

Bacteria; Firmicutes; Clostridia;
80
0.003248
4.372868
0.000058
0.000380
0.228033
0.000254
0.001565
0.326877

Other; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
81
0.003228
1.458281
0.001533
0.004041
0.702929
0.002235
0.007078
0.760291

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

ovatus

Bacteria; Verrucomicrobia;
82
0.003213
1.194589
0.008451
0.033406
0.643305
0.010095
0.050965
0.523002

Verrucomicrobiae; Verrucomicrobiales;

Verrucomicrobiaceae; Akkermansia;

Other

Bacteria; Bacteroidetes; Bacteroidia;
83
0.003175
10.476223
0.000154
0.001694
0.024059
0.001615
0.015875
0.118644

Bacteroidales; Prevotellaceae;

Prevotellamassilia; Prevotellamassilia

timonensis

Bacteria; Firmicutes; Clostridia;
84
0.003156
1.104880
0.001354
0.004548
0.874477
0.001496
0.016614
0.808717

Clostridiales; Ruminococcaceae;

Ruthenibacterium; Ruthenibacterium

lactatiformans

Bacteria; Firmicutes; Bacilli;
85
0.003148
2.724265
0.000012
0.000040
0.216527
0.000034
0.000112
0.326877

Lactobacillales; Streptococcaceae;

Streptococcus; Streptococcus

sanguinis

Bacteria; Firmicutes; Clostridia;
86
0.003145
1.605750
0.004544
0.010129
0.852510
0.007296
0.018218
0.820823

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia intestinalis

Bacteria; Firmicutes; Clostridia;
87
0.003137
1.255456
0.000680
0.002129
0.750000
0.000853
0.002469
0.799031

Clostridiales; Lachnospiraceae;

Clostridium XIVa; Other

Bacteria; Bacteroidetes; Bacteroidia;
88
0.003125
0.660533
0.005622
0.013699
0.744770
0.003714
0.010739
0.673123

Bacteroidales; Tannerellaceae;

Parabacteroides; Parabacteroides

distasonis

Bacteria; Firmicutes; Clostridia;
89
0.003125
1.444228
0.000260
0.000949
0.433054
0.000375
0.001684
0.503632

Clostridiales; Ruminococcaceae;

Gemmiger; Other

Bacteria; Bacteroidetes; Other; Other;
90
0.003110
1.917515
0.000343
0.002384
0.446653
0.000658
0.008037
0.554479

Other; Other; Other

Bacteria; Actinobacteria; Actinobacteria;
91
0.003094
0.376749
0.012432
0.030734
0.647490
0.004684
0.011625
0.699758

Bifidobacteriales; Bifidobacteriaceae;

Bifidobacterium; Bifidobacterium

adolescentis

Bacteria; Firmicutes; Clostridia;
92
0.003093
1.117535
0.002972
0.006360
0.816946
0.003321
0.006487
0.767554

Clostridiales; Lachnospiraceae;

Coprococcus; Other

Bacteria; Bacteroidetes; Bacteroidia;
93
0.003082
1.120969
0.005870
0.016013
0.892259
0.006580
0.020688
0.859564

Bacteroidales; Rikenellaceae;

Alistipes; Other

Bacteria; Actinobacteria; Actinobacteria;
94
0.003073
0.648229
0.001571
0.006672
0.605649
0.001018
0.003735
0.690073

Bifidobacteriales; Bifidobacteriaceae;

Bifidobacterium; Bifidobacterium

longum

Bacteria; Bacteroidetes; Bacteroidia;
95
0.003063
1.220566
0.006204
0.016822
0.407950
0.007573
0.020157
0.556901

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

massiliensis

Bacteria; Bacteroidetes; Bacteroidia;
96
0.003052
1.169985
0.004785
0.007226
0.927824
0.005598
0.014935
0.898305

Bacteroidales; Porphyromonadaceae;

Parabacteroides; Other

Bacteria; Firmicutes; Clostridia;
97
0.003025
0.988898
0.000284
0.002487
0.049163
0.000280
0.002139
0.159806

Clostridiales; Ruminococcaceae;

Not Available; [Eubacterium]

siraeum

Bacteria; Firmicutes; Clostridia;
98
0.002968
0.442577
0.001015
0.002715
0.754184
0.000449
0.001329
0.612591

Clostridiales; Ruminococcaceae;

Not Available; [Clostridium]

leptum

Bacteria; Firmicutes; Bacilli;
99
0.002957
1.038942
0.007021
0.016525
0.938285
0.007294
0.018938
0.907990

Lactobacillales; Streptococcaceae;

Streptococcus; Other

Bacteria; Firmicutes; Clostridia;
100
0.002956
1.465496
0.000009
0.000050
0.106695
0.000013
0.000037
0.188862

Clostridiales; Ruminococcaceae;

Pseudoflavonifractor; Other

IBS = Irritable Bowel Syndrome;

Ctrl = Control;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 10

IBD vs CDI delineation features - (taxonomy)

Feature

(Taxonomic order: Kingdom;

FC
Abundance
Abundance

Phylum; Class; Order;
RFFR
IBS vs
(IBS)
(CDI)

Family; Genus; Species)
#
MDA
CDI
M
SD
DP
M
SD
DP

Bacteria; Firmicutes; Clostridia;
1
0.033863
0.000233
0.000005
0.000037
0.026634
0.020265
0.056449
0.764317

Clostridiales; Peptostreptococcaceae;

Clostridioides; Clostridioides difficile

Bacteria; Firmicutes; Clostridia;
2
0.022370
9.117167
0.019249
0.028624
0.905569
0.002111
0.008309
0.275330

Clostridiales; Lachnospiraceae;

Anaerostipes; Anaerostipes hadrus

Bacteria; Firmicutes; Clostridia;
3
0.020724
14.516793
0.019894
0.026907
0.869249
0.001370
0.008726
0.204846

Clostridiales; Ruminococcaceae;

Faecalibacterium; Faecalibacterium

prausnitzii

Bacteria; Firmicutes; Clostridia;
4
0.020152
27.958502
0.003321
0.006487
0.767554
0.000119
0.000698
0.110132

Clostridiales; Lachnospiraceae;

Coprococcus; Other

Bacteria; Proteobacteria;
5
0.018425
0.040278
0.005732
0.028681
0.765133
0.142299
0.194372
0.907489

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
6
0.018083
11.321488
0.026790
0.042600
0.927361
0.002366
0.009054
0.438326

Clostridiales; Lachnospiraceae;

Not Available; [Eubacterium]

rectale

Bacteria; Firmicutes; Clostridia;
7
0.017101
10.343451
0.005954
0.013082
0.893462
0.000576
0.002224
0.306167

Clostridiales; Lachnospiraceae;

Roseburia; Other

Bacteria; Proteobacteria;
8
0.016941
0.038377
0.001194
0.007142
0.610169
0.031113
0.060092
0.856828

Gammaproteobacteria; Enterobacteriales;

Enterobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
9
0.016935
4.285574
0.001605
0.002634
0.750605
0.000374
0.002447
0.145374

Clostridiales; Ruminococcaceae;

Agathobaculum; Agathobaculum

butyriciproducens

Bacteria; Firmicutes; Clostridia;
10
0.016799
6.882997
0.004722
0.010883
0.857143
0.000686
0.003778
0.220264

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Other

Bacteria; Firmicutes; Clostridia;
11
0.016419
13.559941
0.006049
0.009841
0.796610
0.000446
0.002177
0.189427

Clostridiales; Lachnospiraceae;

Dorea; Other

Bacteria; Firmicutes; Clostridia;
12
0.016137
34.131598
0.013466
0.023548
0.791768
0.000395
0.002295
0.204846

Clostridiales; Ruminococcaceae;

Ruminococcus; Other

Bacteria; Bacteroidetes;
13
0.015514
0.759736
0.001521
0.002372
0.799031
0.002001
0.009758
0.178414

Bacteroidia; Bacteroidales;

Odoribacteraceae; Odoribacter;

Odoribacter splanchnicus

Bacteria; Firmicutes; Clostridia;
14
0.015224
4.125927
0.016406
0.016525
0.944310
0.003976
0.012514
0.726872

Clostridiales; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
15
0.013148
3.278837
0.007517
0.010821
0.871671
0.002293
0.012148
0.312775

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Fusicatenibacter

saccharivorans

Bacteria; Firmicutes; Clostridia;
16
0.012788
6.601872
0.005294
0.008906
0.818402
0.000802
0.004536
0.198238

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia inulinivorans

Bacteria; Firmicutes; Clostridia;
17
0.012671
8.124014
0.006186
0.008890
0.736077
0.000761
0.004308
0.162996

Clostridiales; Lachnospiraceae;

Dorea; Dorea longicatena

Bacteria; Other; Other; Other;
18
0.012176
8.581308
0.005521
0.011388
0.966102
0.000643
0.004047
0.594714

Other; Other; Other

Bacteria; Firmicutes; Bacilli;
19
0.012051
0.010131
0.000496
0.004249
0.322034
0.048932
0.144190
0.775330

Lactobacillales; Enterococcaceae;

Enterococcus; Other

Bacteria; Firmicutes; Clostridia;
20
0.011864
14.919897
0.007296
0.018218
0.820823
0.000489
0.002122
0.213656

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia intestinalis

Bacteria; Firmicutes; Clostridia;
21
0.010849
9.790054
0.008589
0.017120
0.903148
0.000877
0.003080
0.431718

Clostridiales; Lachnospiraceae;

Anaerostipes; Other

Bacteria; Firmicutes; Clostridia;
22
0.010778
2.754460
0.045474
0.037841
0.968523
0.016509
0.039130
0.850220

Clostridiales; Lachnospiraceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
23
0.010363
8.786461
0.003015
0.004631
0.685230
0.000343
0.002312
0.129956

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus comes

Bacteria; Bacteroidetes; Bacteroidia;
24
0.010293
2.672755
0.002594
0.006865
0.682809
0.000971
0.006250
0.101322

Bacteroidales; Porphyromonadaceae;

Barnesiella; Other

Bacteria; Firmicutes; Bacilli;
25
0.010209
11.280681
0.004296
0.009065
0.685230
0.000381
0.002913
0.101322

Lactobacillales; Lactobacillaceae;

Lactobacillus; Lactobacillus rogosae

Bacteria; Firmicutes; Clostridia;
26
0.010178
0.103434
0.000069
0.001162
0.016949
0.000667
0.003204
0.458150

Clostridiales; Peptostreptococcaceae;

Clostridium XI; Other

Bacteria; Firmicutes; Clostridia;
27
0.010093
5.279170
0.006442
0.014729
0.920097
0.001220
0.004265
0.345815

Clostridiales; Peptostreptococcaceae;

Romboutsia; Romboutsia timonensis

Bacteria; Firmicutes; Other; Other;
28
0.009571
7.217686
0.001140
0.001970
0.869249
0.000158
0.000446
0.422907

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
29
0.009366
1.717128
0.031067
0.038784
0.978208
0.018092
0.049472
0.491189

Clostridiales; Ruminococcaceae;

Faecalibacterium; Other

Bacteria; Firmicutes; Clostridia;
30
0.008957
1.711171
0.005693
0.008644
0.772397
0.003327
0.019940
0.207048

Clostridiales; Ruminococcaceae;

Gemmiger; Gemmiger formicilis

Bacteria; Candidatus Saccharibacteria;
31
0.008865
162.333853
0.000232
0.001213
0.295400
0.000001
0.000014
0.011013

Saccharibacteria_genera_incertae_sedis;

Other; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
32
0.008829
11.444937
0.005117
0.010630
0.728814
0.000447
0.002306
0.145374

Clostridiales; Eubacteriaceae;

Eubacterium; [Eubacterium]

eligens

Bacteria; Bacteroidetes; Bacteroidia;
33
0.008294
97.826414
0.017116
0.050016
0.539952
0.000175
0.001986
0.039648

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides plebeius

Bacteria; Firmicutes; Clostridia;
34
0.008142
5.048500
0.030591
0.053003
0.924939
0.006060
0.013562
0.709251

Clostridiales; Lachnospiraceae;

Blautia; Other

Bacteria; Firmicutes; Clostridia;
35
0.008129
5.489082
0.003722
0.006315
0.799031
0.000678
0.005538
0.237885

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia faecis

Bacteria; Firmicutes; Clostridia;
36
0.008057
7.786071
0.005283
0.010157
0.767554
0.000678
0.003388
0.213656

Clostridiales; Lachnospiraceae;

Blautia; Blautia obeum

Bacteria; Firmicutes; Clostridia;
37
0.007936
4.220011
0.021757
0.027256
0.934625
0.005156
0.013758
0.632159

Clostridiales; Lachnospiraceae;

Lachnospiracea_incertae_sedis; Other

Bacteria; Firmicutes; Clostridia;
38
0.007862
19.531980
0.000875
0.001532
0.578692
0.000045
0.000265
0.066079

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus catus

Bacteria; Proteobacteria;
39
0.007734
38.633138
0.000310
0.000933
0.302663
0.000008
0.000040
0.070485

Betaproteobacteria; Burkholderiales;

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
40
0.007705
2.980714
0.015597
0.018427
0.934625
0.005233
0.027016
0.561674

Clostridiales; Ruminococcaceae;

Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
41
0.007688
11.365246
0.038999
0.113177
0.685230
0.003431
0.031801
0.176211

Bacteroidales; Prevotellaceae;

Prevotella; Prevotella copri

Bacteria; Proteobacteria;
42
0.007392
5366.285265
0.000554
0.001748
0.096852
0.000000
0.000002
0.002203

Betaproteobacteria; Burkholderiales;

Burkholderiaceae; Other; Other

Bacteria; Proteobacteria;
43
0.007034
NA - Div
0.005094
0.028774
0.099274
0.000000
0.000000
0.000000

Alphaproteobacteria; Caulobacterales;

by 0

Caulobacteraceae; Caulobacter;

Caulobacter segnis

Bacteria; Proteobacteria;
44
0.006272
NA - Div
0.000283
0.001381
0.101695
0.000000
0.000000
0.000000

Alphaproteobacteria; Caulobacterales;

by 0

Caulobacteraceae; Caulobacter; Other

Bacteria; Proteobacteria;
45
0.006261
21616.489716
0.087316
0.269557
0.099274
0.000004
0.000034
0.015419

Betaproteobacteria; Burkholderiales;

Burkholderiaceae; Burkholderia; Other

Bacteria; Proteobacteria;
46
0.006218
19.741194
0.000274
0.000849
0.210654
0.000014
0.000122
0.059471

Betaproteobacteria; Other; Other;

Other; Other

Bacteria; Proteobacteria;
47
0.006198
NA - Div
0.000010
0.000036
0.096852
0.000000
0.000000
0.000000

Betaproteobacteria; Burkholderiales;

by 0

Burkholderiaceae; Burkholderia;

Burkholderia ambifaria

Bacteria; Bacteroidetes; Bacteroidia;
48
0.006085
12.753613
0.041010
0.107593
0.777240
0.003216
0.027796
0.297357

Bacteroidales; Prevotellaceae;

Prevotella; Other

Bacteria; Proteobacteria;
49
0.005983
16.904024
0.000028
0.000177
0.133172
0.000002
0.000018
0.008811

Betaproteobacteria; Burkholderiales;

Comamonadaceae; Other; Other

Bacteria; Proteobacteria;
50
0.005837
0.008974
0.000024
0.000202
0.079903
0.002672
0.010560
0.469163

Gammaproteobacteria;

Enterobacterales; Other; Other;

Other

Bacteria; Firmicutes; Clostridia;
51
0.005830
2.145134
0.004604
0.008826
0.723971
0.002146
0.026081
0.191630

Clostridiales; Ruminococcaceae;

Ruminococcus; Ruminococcus faecis

Bacteria; Firmicutes; Bacilli;
52
0.005590
0.015396
0.000070
0.000623
0.261501
0.004568
0.016546
0.590308

Lactobacillales; Other; Other;

Other

Bacteria; Proteobacteria;
53
0.005507
NA - Div
0.000002
0.000009
0.077482
0.000000
0.000000
0.000000

Betaproteobacteria; Burkholderiales;

by 0

Burkholderiaceae; Burkholderia;

Burkholderia thailandensis

Bacteria; Bacteroidetes; Bacteroidia;
54
0.005493
1.115759
0.000219
0.000524
0.639225
0.000196
0.001077
0.132159

Bacteroidales; Porphyromonadaceae;

Odoribacter; Other

Bacteria; Firmicutes; Clostridia;
55
0.005418
2.642972
0.004107
0.005814
0.779661
0.001554
0.009333
0.266520

Clostridiales; Lachnospiraceae;

Blautia; Blautia faecis

Bacteria; Firmicutes; Clostridia;
56
0.005260
1.851942
0.008033
0.011088
0.849879
0.004338
0.022200
0.301762

Clostridiales; Lachnospiraceae;

Blautia; Blautia luti

Bacteria; Bacteroidetes; Bacteroidia;
57
0.005256
15.164959
0.000849
0.001662
0.583535
0.000056
0.000396
0.059471

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes obesi

Bacteria; Bacteroidetes; Bacteroidia;
58
0.005203
1.402469
0.006580
0.020688
0.859564
0.004691
0.027357
0.407489

Bacteroidales; Rikenellaceae;

Alistipes; Other

Bacteria; Firmicutes; Clostridia;
59
0.004845
1.906142
0.026474
0.041908
0.820823
0.013889
0.039999
0.533040

Clostridiales; Lachnospiraceae;

Blautia; Blautia wexlerae

Bacteria; Actinobacteria;
60
0.004588
0.091461
0.000135
0.000423
0.401937
0.001476
0.005130
0.486784

Coriobacteriia; Eggerthellales;

Eggerthellaceae; Eggerthella;

Eggerthella lenta

Bacteria; Firmicutes; Clostridia;
61
0.004406
90.950753
0.001507
0.004129
0.435835
0.000017
0.000114
0.063877

Clostridiales; Lachnospiraceae;

Blautia; Blautia stercoris

Bacteria; Firmicutes; Clostridia;
62
0.004254
2.088425
0.001188
0.004845
0.714286
0.000569
0.006346
0.213656

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia hominis

Bacteria; Firmicutes; Clostridia;
63
0.004216
2.806961
0.000375
0.001684
0.503632
0.000134
0.001249
0.068282

Clostridiales; Ruminococcaceae;

Gemmiger; Other

Bacteria; Firmicutes; Clostridia;
64
0.004153
11.111505
0.007834
0.018470
0.539952
0.000705
0.004419
0.125551

Clostridiales; Ruminococcaceae;

Ruminococcus; Ruminococcus bromii

Bacteria; Proteobacteria;
65
0.004114
27.234354
0.000532
0.004233
0.118644
0.000020
0.000179
0.050661

Betaproteobacteria; Burkholderiales;

Comamonadaceae; Pelomonas;

Pelomonas aquatica

Bacteria; Firmicutes; Erysipelotrichia;
66
0.004104
0.087663
0.000444
0.003707
0.547215
0.005062
0.019598
0.665198

Erysipelotrichales; Erysipelotrichaceae;

Erysipelatoclostridium;

[Clostridium] innocuum

Bacteria; Firmicutes; Clostridia;
67
0.004010
27.226182
0.000738
0.002749
0.450363
0.000027
0.000160
0.085903

Clostridiales; Peptostreptococcaceae;

Romboutsia; Other

Bacteria; Bacteroidetes; Bacteroidia;
68
0.003987
157.437668
0.010799
0.032470
0.433414
0.000069
0.000843
0.039648

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides coprocola

Bacteria; Proteobacteria;
69
0.003973
0.006062
0.000012
0.000094
0.075061
0.002035
0.008768
0.431718

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Citrobacter; Other

Bacteria; Firmicutes; Clostridia;
70
0.003916
4.231989
0.002048
0.009399
0.719128
0.000484
0.003051
0.235683

Clostridiales; Ruminococcaceae;

Clostridium IV; Other

Bacteria; Firmicutes; Clostridia;
71
0.003898
1.696293
0.004514
0.012317
0.876513
0.002661
0.011396
0.466960

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Intestinibacter

bartlettii

Bacteria; Firmicutes; Bacilli;
72
0.003847
9.436626
0.001743
0.006303
0.602906
0.000185
0.000805
0.273128

Lactobacillales; Streptococcaceae;

Streptococcus; Streptococcus

thermophilus

Bacteria; Firmicutes; Clostridia;
73
0.003647
0.145758
0.000853
0.002469
0.799031
0.005855
0.013353
0.786344

Clostridiales; Lachnospiraceae;

Clostridium XIVa; Other

Bacteria; Proteobacteria;
74
0.003483
0.744367
0.001584
0.003109
0.702179
0.002128
0.007865
0.270925

Deltaproteobacteria; Desulfovibrionales;

Desulfovibrionaceae; Bilophila; Other

Bacteria; Firmicutes; Clostridia;
75
0.003445
7.014507
0.000345
0.001085
0.542373
0.000049
0.000345
0.079295

Clostridiales; Ruminococcaceae;

Oscillibacter; Other

Bacteria; Firmicutes; Clostridia;
76
0.003402
0.070129
0.000759
0.002089
0.716707
0.010829
0.029193
0.711454

Clostridiales; Lachnospiraceae;

Lachnoclostridium; [Clostridium]

bolteae

Bacteria; Firmicutes; Erysipelotrichia;
77
0.003390
0.135249
0.000976
0.004688
0.493947
0.007217
0.022214
0.658590

Erysipelotrichales; Erysipelotrichaceae;

Erysipelatoclostridium;

Erysipelatoclostridium ramosum

Bacteria; Bacteroidetes; Bacteroidia;
78
0.003233
3.500150
0.007788
0.014441
0.692494
0.002225
0.009918
0.209251

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes putredinis

Bacteria; Bacteroidetes; Bacteroidia;
79
0.003162
0.304767
0.000225
0.000559
0.401937
0.000739
0.009585
0.037445

Bacteroidales; Barnesiellaceae;

Coprobacter; Coprobacter fastidiosus

Bacteria; Bacteroidetes; Bacteroidia;
80
0.003158
5.121584
0.000424
0.001182
0.472155
0.000083
0.000540
0.057269

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes ihumii

Bacteria; Firmicutes; Clostridia;
81
0.002980
6.485011
0.001360
0.003041
0.452785
0.000210
0.001505
0.046256

Clostridiales; Ruminococcaceae;

Ruminococcus; Ruminococcus callidus

Bacteria; Firmicutes; Clostridia;
82
0.002965
0.029405
0.000040
0.000243
0.237288
0.001372
0.005976
0.385463

Clostridiales; Clostridiaceae;

Hungatella; Hungatella effluvii

Bacteria; Proteobacteria;
83
0.002963
137.878020
0.000118
0.001758
0.099274
0.000001
0.000010
0.008811

Alphaproteobacteria; Rhizobiales;

Phyllobacteriaceae; Phyllobacterium;

Other

Bacteria; Proteobacteria;
84
0.002874
0.106988
0.000054
0.000399
0.288136
0.000501
0.001112
0.475771

Gammaproteobacteria; Other; Other;

Other; Other

Bacteria; Actinobacteria;
85
0.002843
1.421827
0.001018
0.003735
0.690073
0.000716
0.003769
0.240088

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium longum

Bacteria; Firmicutes; Clostridia;
86
0.002704
0.490765
0.003396
0.005044
0.891041
0.006920
0.021979
0.466960

Clostridiales; Lachnospiraceae;

Ruminococcus2; Other

Bacteria; Firmicutes; Negativicutes;
87
0.002687
0.031220
0.000238
0.001404
0.341404
0.007608
0.034840
0.504405

Veillonellales; Veillonellaceae;

Veillonella; Veillonella parvula

Bacteria; Actinobacteria;
88
0.002663
4.095545
0.004684
0.011625
0.699758
0.001144
0.007492
0.244493

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium adolescentis

Bacteria; Firmicutes; Erysipelotrichia;
89
0.002544
0.248360
0.000046
0.000161
0.341404
0.000186
0.001803
0.068282

Erysipelotrichales; Erysipelotrichaceae;

Solobacterium; Solobacterium moorei

Bacteria; Bacteroidetes; Bacteroidia;
90
0.002539
0.739000
0.051954
0.062313
0.961259
0.070303
0.112647
0.909692

Bacteroidales; Bacteroidaceae;

Bacteroides; Other

Bacteria; Firmicutes; Bacilli;
91
0.002440
0.040370
0.000744
0.009319
0.476998
0.018423
0.083583
0.643172

Lactobacillales; Lactobacilloae;

Lactobacillus; Other

Bacteria; Firmicutes; Clostridia;
92
0.002424
0.185342
0.002506
0.011498
0.600484
0.013521
0.029521
0.647577

Clostridiales; Lachnospiraceae;

Blautia; [Ruminococcus]

gnavus

Bacteria; Bacteroidetes; Bacteroidia;
93
0.002411
1.338446
0.001846
0.005767
0.607748
0.001379
0.012053
0.191630

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes finegoldii

Bacteria; Bacteroidetes; Bacteroidia;
94
0.002347
0.956387
0.002441
0.005129
0.677966
0.002552
0.035517
0.187225

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes shahii

Bacteria; Proteobacteria;
95
0.002339
2.594337
0.000004
0.000023
0.058111
0.000001
0.000016
0.008811

Alphaproteobacteria; Caulobacterales;

Caulobacteraceae; Other; Other

Bacteria; Firmicutes; Clostridia;
96
0.002326
695.608879
0.003620
0.011337
0.382567
0.000005
0.000053
0.015419

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus eutactus

Bacteria; Firmicutes; Bacilli;
97
0.002271
0.005918
0.000001
0.000015
0.007264
0.000148
0.000493
0.312775

Lactobacillales; Enterococcaceae;

Enterococcus; Enterococcus

saccharolyticus

Bacteria; Bacteroidetes; Bacteroidia;
98
0.002243
3.784396
0.000258
0.000824
0.443099
0.000068
0.000612
0.055066

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes indistinctus

Bacteria; Actinobacteria;
99
0.002226
0.067565
0.000029
0.000122
0.208232
0.000435
0.001791
0.281938

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Eggerthella; Other

Bacteria; Firmicutes; Clostridia;
100
0.002209
5.591039
0.001891
0.008662
0.590799
0.000338
0.002766
0.273128

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Other

IBS = Irritable Bowel Syndrome;

CDI = Clostridiodes difficile Infection;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 11

IBS vs IBD delineation features - (taxonomy)

Feature

(Taxonomic order: Kingdom;

FC
Abundance
Abundance

Phylum; Class; Order;
RFFR
IBS vs
(IBS)
(IBD)

Family; Genus; Species)
#
MDA
IBD
M
SD
DP
M
SD
DP

Bacteria; Firmicutes; Clostridia;
1
0.019964
2.064120
0.006442
0.014729
0.920097
0.003121
0.018450
0.360952

Clostridiales; Peptostreptococcaceae;

Romboutsia; Romboutsia timonensis

Bacteria; Proteobacteria;
2
0.018791
0.281149
0.000121
0.000994
0.394673
0.000431
0.010385
0.078095

Gammaproteobacteria; Pseudomonadales;

Pseudomonadaceae; Pseudomonas; Other

Bacteria; Firmicutes; Clostridia;
3
0.017194
3.375668
0.019894
0.026907
0.869249
0.005893
0.019791
0.630476

Clostridiales; Ruminococcaceae;

Faecalibacterium; Faecalibacterium

prausnitzii

Bacteria; Other; Other; Other;
4
0.016740
0.264096
0.005521
0.011388
0.966102
0.020907
0.037823
0.939048

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
5
0.014815
2.330675
0.026790
0.042600
0.927361
0.011495
0.034475
0.402857

Clostridiales; Lachnospiraceae;

Not Available; [Eubacterium]

rectale

Bacteria; Bacteroidetes; Bacteroidia;
6
0.013814
3.890844
0.003581
0.009164
0.803874
0.000920
0.003588
0.313333

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides xylanisolvens

Bacteria; Firmicutes; Bacilli;
7
0.012597
1.577191
0.000049
0.000115
0.421308
0.000031
0.000142
0.112381

Lactobacillales; Carnobacteriaceae;

Granulicatella; Other

Bacteria; Actinobacteria;
8
0.012353
0.194215
0.001370
0.005518
0.351090
0.007053
0.023275
0.728571

Coriobacteriia; Coriobacteriales;

Coriobacteriaceae; Collinsella;

Collinsella aerofaciens

Bacteria; Firmicutes; Negativicutes;
9
0.011956
0.015831
0.000013
0.000172
0.050847
0.000838
0.008203
0.515238

Veillonellales; Veillonellaceae;

Veillonella; Other

Bacteria; Bacteroidetes; Bacteroidia;
10
0.011201
1.777263
0.040437
0.064921
0.842615
0.022753
0.060571
0.389524

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides dorei

Bacteria; Firmicutes; Clostridia;
11
0.010434
1.847237
0.003722
0.006315
0.799031
0.002015
0.008784
0.342857

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia faecis

Bacteria; Firmicutes; Bacilli;
12
0.010179
1.143292
0.000246
0.000996
0.559322
0.000215
0.001645
0.199048

Lactobacillales; Streptococcaceae;

Streptococcus; Streptococcus

parasanguinis

Bacteria; Firmicutes; Clostridia;
13
0.009881
0.000579
0.000001
0.000006
0.016949
0.001136
0.006502
0.476190

Clostridiales; Lachnospiraceae;

Lachnoclostridium; Other

Bacteria; Firmicutes; Clostridia;
14
0.009195
0.034059
0.000156
0.000820
0.363196
0.004586
0.025790
0.334286

Clostridiales; Lachnospiraceae;

Blautia; Blautia hominis

Bacteria; Firmicutes; Clostridia;
15
0.008216
1.857272
0.001605
0.002634
0.750605
0.000864
0.003153
0.328571

Clostridiales; Ruminococcaceae;

Agathobaculum; Agathobaculum

butyriciproducens

Bacteria; Actinobacteria;
16
0.008119
0.421662
0.001627
0.007075
0.292978
0.003859
0.011240
0.681905

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Collinsella;

Other

Bacteria; Proteobacteria;
17
0.008009
0.001191
0.000024
0.000202
0.079903
0.020133
0.079882
0.538095

Gammaproteobacteria; Enterobacterales;

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
18
0.008001
0.770941
0.031067
0.038784
0.978208
0.040297
0.054719
0.911429

Clostridiales; Ruminococcaceae;

Faecalibacterium; Other

Bacteria; Firmicutes; Clostridia;
19
0.007947
15.250702
0.001507
0.004129
0.435835
0.000099
0.000607
0.167619

Clostridiales; Lachnospiraceae;

Blautia; Blautia stercoris

Bacteria; Candidatus Saccharibacteria;
20
0.007790
21.228866
0.000232
0.001213
0.295400
0.000011
0.000057
0.135238

Saccharibacteria_genera_incertae_sedis;

Other; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
21
0.007326
5.471413
0.017116
0.050016
0.539952
0.003128
0.021947
0.278095

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides plebeius

Bacteria; Bacteroidetes; Bacteroidia;
22
0.007307
6.064441
0.000229
0.001087
0.322034
0.000038
0.000392
0.051429

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides nordii

Bacteria; Firmicutes; Clostridia;
23
0.007244
3.259107
0.004722
0.010883
0.857143
0.001449
0.002690
0.775238

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Other

Bacteria; Firmicutes; Bacilli;
24
0.007204
1.641026
0.001743
0.006303
0.602906
0.001062
0.026362
0.294286

Lactobacillales; Streptococcaceae;

Streptococcus; Streptococcus

thermophilus

Bacteria; Firmicutes; Clostridia;
25
0.007050
1.052566
0.005693
0.008644
0.772397
0.005409
0.016380
0.690476

Clostridiales; Ruminococcaceae;

Gemmiger; Gemmiger formicilis

Bacteria; Bacteroidetes; Bacteroidia;
26
0.006989
2.975546
0.002235
0.007078
0.760291
0.000751
0.004555
0.337143

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides ovatus

Bacteria; Bacteroidetes; Other;
27
0.006981
0.409003
0.000658
0.008037
0.554479
0.001610
0.004345
0.674286

Other; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
28
0.006729
3.151968
0.013466
0.023548
0.791768
0.004272
0.012950
0.694286

Clostridiales; Ruminococcaceae;

Ruminococcus; Other

Bacteria; Firmicutes; Clostridia;
29
0.006553
NA - Div
0.000280
0.002139
0.159806
0.000000
0.000000
0.000000

Clostridiales; Ruminococcaceae;

by 0

Not Available; [Eubacterium]

siraeum

Bacteria; Bacteroidetes; Bacteroidia;
30
0.006250
4.220951
0.007573
0.020157
0.556901
0.001794
0.008110
0.190476

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides massiliensis

Bacteria; Bacteroidetes; Bacteroidia;
31
0.006149
5.462881
0.004005
0.017127
0.535109
0.000733
0.006500
0.179048

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

cellulosilyticus

Bacteria; Proteobacteria;
32
0.005748
45122.221500
0.000554
0.001748
0.096852
0.000000
0.000000
0.000952

Betaproteobacteria; Burkholderiales;

Burkholderiaceae; Other; Other

Bacteria; Proteobacteria;
33
0.005548
NA - Div
0.000283
0.001381
0.101695
0.000000
0.000000
0.000000

Alphaproteobacteria; Caulobacterales;

by 0

Caulobacteraceae; Caulobacter; Other

Bacteria; Firmicutes; Bacilli;
34
0.005455
2.190168
0.000725
0.002702
0.256659
0.000331
0.004144
0.036190

Lactobacillales; Streptococcaceae;

Streptococcus; Streptococcus

salivarius

Bacteria; Firmicutes; Clostridia;
35
0.005382
1.226793
0.030591
0.053003
0.924939
0.024936
0.047896
0.984762

Clostridiales; Lachnospiraceae;

Blautia; Other

Bacteria; Proteobacteria;
36
0.005373
2735.033422
0.000532
0.004233
0.118644
0.000000
0.000003
0.006667

Betaproteobacteria; Burkholderiales;

Comamonadaceae; Pelomonas;

Pelomonas aquatica

Bacteria; Firmicutes; Clostridia;
37
0.005362
1.139082
0.005954
0.013082
0.893462
0.005227
0.008361
0.887619

Clostridiales; Lachnospiraceae;

Roseburia; Other

Bacteria; Actinobacteria;
38
0.005163
0.132537
0.000011
0.000045
0.138015
0.000082
0.000245
0.545714

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
39
0.005043
0.304522
0.002506
0.011498
0.600484
0.008229
0.028839
0.841905

Clostridiales; Lachnospiraceae;

Blautia; [Ruminococcus] gnavus

Bacteria; Firmicutes; Other; Other;
40
0.004982
0.644213
0.001140
0.001970
0.869249
0.001770
0.003186
0.906667

Other; Other; Other

Bacteria; Proteobacteria;
41
0.004975
NA - Div
0.087316
0.269557
0.099274
0.000000
0.000000
0.000000

Betaproteobacteria; Burkholderiales;

by 0

Burkholderiaceae; Burkholderia; Other

Bacteria; Proteobacteria;
42
0.004975
11938.331577
0.005094
0.028774
0.099274
0.000000
0.000009
0.007619

Alphaproteobacteria; Caulobacterales;

Caulobacteraceae; Caulobacter;

Caulobacter segnis

Bacteria; Firmicutes; Clostridia;
43
0.004886
1.057123
0.026474
0.041908
0.820823
0.025044
0.061261
0.471429

Clostridiales; Lachnospiraceae;

Blautia; Blautia wexlerae

Bacteria; Actinobacteria;
44
0.004878
0.254780
0.005829
0.020871
0.799031
0.022880
0.052680
0.916190

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Other

Bacteria; Bacteroidetes; Bacteroidia;
45
0.004668
1.699561
0.001521
0.002372
0.799031
0.000895
0.001940
0.653333

Bacteroidales; Odoribacteraceae;

Odoribacter; Odoribacter splanchnicus

Bacteria; Firmicutes; Clostridia;
46
0.004646
2.126594
0.008589
0.017120
0.903148
0.004039
0.011111
0.932381

Clostridiales; Lachnospiraceae;

Anaerostipes; Other

Bacteria; Proteobacteria;
47
0.004596
NA - Div
0.000010
0.000036
0.096852
0.000000
0.000000
0.000000

Betaproteobacteria; Burkholderiales;

by 0

Burkholderiaceae; Burkholderia;

Burkholderia ambifaria

Bacteria; Firmicutes; Clostridia;
48
0.004564
77.864250
0.000246
0.001183
0.147700
0.000003
0.000049
0.004762

Clostridiales; Eubacteriaceae;

Eubacterium; Eubacterium ventriosum

Bacteria; Firmicutes; Clostridia;
49
0.004555
0.021560
0.000008
0.000025
0.142857
0.000350
0.000968
0.463810

Clostridiales; Ruminococcaceae;

Intestinimonas; Other

Bacteria; Firmicutes; Clostridia;
50
0.004546
7.406121
0.000254
0.001565
0.326877
0.000034
0.000078
0.503810

Other; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
51
0.004533
0.267350
0.000654
0.001669
0.748184
0.002447
0.004365
0.805714

Bacteroidales; Other; Other; Other

Bacteria; Actinobacteria;
52
0.004470
0.411025
0.004684
0.011625
0.699758
0.011395
0.038469
0.388571

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium adolescentis

Bacteria; Firmicutes; Clostridia;
53
0.004416
0.261449
0.000759
0.002089
0.716707
0.002905
0.011580
0.394286

Clostridiales; Lachnospiraceae;

Lachnoclostridium; [Clostridium]

bolteae

Bacteria; Bacteroidetes;
54
0.004262
1.162000
0.000219
0.000524
0.639225
0.000188
0.000586
0.511429

Bacteroidia; Bacteroidales;

Porphyromonadaceae; Odoribacter;

Other

Bacteria; Firmicutes; Clostridia;
55
0.004230
2.300468
0.000875
0.001532
0.578692
0.000380
0.001144
0.260952

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus catus

Bacteria; Firmicutes; Bacilli;
56
0.004192
0.548312
0.007294
0.018938
0.907990
0.013303
0.034735
0.982857

Lactobacillales; Streptococcaceae;

Streptococcus; Other

Bacteria; Firmicutes; Clostridia;
57
0.004182
3.709381
0.004088
0.010861
0.801453
0.001102
0.003027
0.803810

Clostridiales; Peptostreptococcaceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
58
0.004180
0.086268
0.000363
0.001754
0.157385
0.004213
0.017069
0.440000

Clostridiales; Lachnospiraceae;

Faecalimonas; Faecalimonas

umbilicata

Bacteria; Bacteroidetes; Bacteroidia;
59
0.004122
1.364547
0.038999
0.113177
0.685230
0.028580
0.096181
0.687619

Bacteroidales; Prevotellaceae;

Prevotella; Prevotella copri

Bacteria; Proteobacteria;
60
0.004103
8.950773
0.000114
0.000372
0.251816
0.000013
0.000090
0.062857

Betaproteobacteria; Burkholderiales;

Oxalobacteraceae; Oxalobacter;

Oxalobacter formigenes

Bacteria; Firmicutes; Clostridia;
61
0.004038
1.483212
0.004604
0.008826
0.723971
0.003104
0.009542
0.689524

Clostridiales; Ruminococcaceae;

Ruminococcus; Ruminococcus faecis

Bacteria; Actinobacteria;
62
0.004000
0.212202
0.000073
0.000244
0.331719
0.000346
0.002140
0.632381

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Other; Other

Bacteria; Actinobacteria;
63
0.003985
0.178684
0.000006
0.000039
0.055690
0.000034
0.000091
0.425714

Actinobacteria; Actinomycetales;

Actinomycetaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
64
0.003962
0.470831
0.000853
0.002469
0.799031
0.001812
0.004738
0.907619

Clostridiales; Lachnospiraceae;

Clostridium XIVa; Other

Bacteria; Firmicutes; Clostridia;
65
0.003886
1.449196
0.000072
0.000325
0.399516
0.000050
0.000200
0.347619

Clostridiales; Not Available;

Intestinimonas; Intestinimonas

butyriciproducens

Bacteria; Firmicutes; Negativicutes;
66
0.003880
0.364950
0.000238
0.001404
0.341404
0.000651
0.015259
0.138095

Veillonellales; Veillonellaceae;

Veillonella; Veillonella parvula

Bacteria; Firmicutes; Clostridia;
67
0.003872
0.771959
0.045474
0.037841
0.968523
0.058907
0.051085
0.991429

Clostridiales; Lachnospiraceae;

Other; Other

Bacteria; Actinobacteria;
68
0.003863
0.024864
0.000001
0.000006
0.024213
0.000030
0.000086
0.400952

Actinobacteria; Other; Other;

Other; Other

Bacteria; Firmicutes; Clostridia;
69
0.003812
0.763719
0.000037
0.000164
0.157385
0.000048
0.000227
0.123810

Clostridiales; Ruminococcaceae;

Anaeromassilibacillus;

Anaeromassilibacillus senegalensis

Bacteria; Firmicutes; Clostridia;
70
0.003772
0.000000
0.000000
0.000000
0.000000
0.000333
0.001662
0.084762

Clostridiales; Lachnospiraceae; Dorea;

Dorea formicigenerans

Bacteria; Firmicutes; Clostridia;
71
0.003710
1.549459
0.021757
0.027256
0.934625
0.014041
0.022190
0.978095

Clostridiales; Lachnospiraceae;

Lachnospiracea_incertae_sedis;

Other

Bacteria; Bacteroidetes;
72
0.003659
1.649128
0.001846
0.005767
0.607748
0.001120
0.010523
0.459048

Bacteroidia; Bacteroidales;

Rikenellaceae; Alistipes;

Alistipes finegoldii

Bacteria; Firmicutes; Clostridia;
73
0.003486
0.657294
0.015597
0.018427
0.934625
0.023730
0.048235
0.938095

Clostridiales; Ruminococcaceae;

Other; Other

Bacteria; Bacteroidetes;
74
0.003476
2.230409
0.002441
0.005129
0.677966
0.001094
0.002698
0.564762

Bacteroidia; Bacteroidales;

Rikenellaceae; Alistipes;

Alistipes shahii

Bacteria; Proteobacteria;
75
0.003405
0.226553
0.000310
0.000933
0.302663
0.001366
0.008723
0.554286

Betaproteobacteria; Burkholderiales;

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
76
0.003385
0.697033
0.000375
0.001684
0.503632
0.000539
0.001815
0.466667

Clostridiales; Ruminococcaceae;

Gemmiger; Other

Bacteria; Proteobacteria;
77
0.003342
7.653116
0.000028
0.00077
0.133172
0.000004
0.000053
0.043810

Betaproteobacteria; Burkholderiales;

Comamonadaceae; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
78
0.003319
1.462976
0.041010
0.107593
0.777240
0.028032
0.087686
0.770476

Bacteroidales; Prevotellaceae;

Prevotella; Other

Bacteria; Firmicutes; Bacilli;
79
0.003301
0.224065
0.000008
0.000030
0.104116
0.000035
0.000166
0.180952

Lactobacillales; Carnobacteriaceae;

Granulicatella; Granulicatella

adiacens

Bacteria; Firmicutes; Clostridia;
80
0.003294
1.197894
0.016406
0.016525
0.944310
0.013696
0.018995
0.987619

Clostridiales; Other; Other; Other

Bacteria; Firmicutes; Negativicutes;
81
0.003268
NA - Div
0.000048
0.000333
0.096852
0.000000
0.000000
0.000000

Veillonellales; Veillonellaceae;

by 0

Veillonella; Veillonella infantium

Bacteria; Bacteroidetes; Bacteroidia;
82
0.003266
14.581027
0.000965
0.004492
0.232446
0.000066
0.000500
0.108571

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides thetaiotaomicron

Bacteria; Firmicutes; Clostridia;
83
0.003255
0.640063
0.004107
0.005814
0.779661
0.006417
0.015065
0.883810

Clostridiales; Lachnospiraceae;

Blautia; Blautia faecis

Bacteria; Proteobacteria;
84
0.003240
0.545020
0.000274
0.000849
0.210654
0.000503
0.003162
0.464762

Betaproteobacteria; Other;

Other; Other; Other

Bacteria; Proteobacteria; Other;
85
0.003233
0.030060
0.000020
0.000084
0.263923
0.000675
0.002153
0.559048

Other; Other; Other; Other

Bacteria; Bacteroidetes;
86
0.003210
41.417105
0.000009
0.000033
0.121065
0.000000
0.000005
0.005714

Sphingobacteriia; Sphingobacteriales;

Sphingobacteriaceae; Pedobacter; Other

Bacteria; Firmicutes; Clostridia;
87
0.003199
1.084354
0.000940
0.003344
0.680387
0.000867
0.007326
0.622857

Clostridiales; Clostridiaceael;

Clostridium sensu stricto; Other

Bacteria; Bacteroidetes;
88
0.003193
0.519496
0.051954
0.062313
0.961259
0.100008
0.102665
0.973333

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Other

Bacteria; Firmicutes; Bacilli;
89
0.003079
0.248198
0.000070
0.000623
0.261501
0.000283
0.002256
0.629524

Lactobacillales; Other; Other;

Other

Bacteria; Bacteroidetes;
90
0.003069
1.250833
0.006299
0.011554
0.728814
0.005036
0.014266
0.706667

Bacteroidia; Bacteroidales;

Tannerellaceae; Parabacteroides;

Parabacteroides merdae

Bacteria; Firmicutes; Clostridia;
91
0.003060
2.006992
0.005294
0.008906
0.818402
0.002638
0.005359
0.748571

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia inulinivorans

Bacteria; Bacteroidetes;
92
0.002978
1.208398
0.006580
0.020688
0.859564
0.005445
0.018848
0.809524

Bacteroidia; Bacteroidales;

Rikenellaceae; Alistipes; Other

Bacteria; Actinobacteria;
93
0.002978
0.564124
0.001018
0.003735
0.690073
0.001805
0.010314
0.364762

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium longum

Bacteria; Proteobacteria;
94
0.002941
NA - Div
0.000002
0.000009
0.077482
0.000000
0.000000
0.000000

Betaproteobacteria; Burkholderiales;

by 0

Burkholderiaceae; Burkholderia;

Burkholderia thailandensis

Bacteria; Firmicutes; Clostridia;
95
0.002938
1.199496
0.007517
0.010821
0.871671
0.006267
0.010773
0.831429

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Fusicatenibacter

saccharivorans

Bacteria; Bacteroidetes; Bacteroidia;
96
0.002910
0.367389
0.021450
0.045829
0.927361
0.058385
0.090300
0.932381

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides vulgatus

Bacteria; Firmicutes; Clostridia;
97
0.002902
1.293624
0.003396
0.005044
0.891041
0.002625
0.008890
0.859048

Clostridiales; Lachnospiraceae;

Ruminococcus2; Other

Bacteria; Firmicutes; Clostridia;
98
0.002888
1.481964
0.019249
0.028624
0.905569
0.012989
0.022303
0.909524

Clostridiales; Lachnospiraceae;

Anaerostipes; Anaerostipes hadrus

Bacteria; Firmicutes; Erysipelotrichia;
99
0.002886
5.893999
0.000738
0.003186
0.411622
0.000125
0.000672
0.412381

Erysipelotrichales; Erysipelotrichaceae;

Turicibacter; Other

Bacteria; Bacteroidetes;
100
0.002850
1.820438
0.001645
0.006094
0.496368
0.000904
0.003470
0.234286

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Bacteroides finegoldii

IBS = Irritable Bowel Syndrome;

IBD = Inflammatory Bowel Disease;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 12

IBD vs CDI delineation features - (taxonomy)

Feature

(Taxonomic order: Kingdom;

FC
Abundance
Abundance

Phylum; Class; Order;
RFFR
IBD vs
(IBD)
(CDI)

Family; Genus; Species)
#
MDA
CDI
M
SD
DP
M
SD
DP

Bacteria; Firmicutes; Clostridia;
1
0.048326
0.003473
0.000070
0.000989
0.020952
0.020265
0.056449
0.764317

Clostridiales; Peptostreptococcaceae;

Clostridioides; Clostridioides difficile

Bacteria; Firmicutes; Clostridia;
2
0.024571
6.152085
0.012989
0.022303
0.909524
0.002111
0.008309
0.275330

Clostridiales; Lachnospiraceae;

Anaerostipes; Anaerostipes hadrus

Bacteria; Firmicutes; Clostridia;
3
0.023410
11.102456
0.004953
0.010473
0.883810
0.000446
0.002177
0.189427

Clostridiales; Lachnospiraceae;

Dorea; Other

Bacteria; Firmicutes; Clostridia;
4
0.022965
0.013233
0.000009
0.000129
0.039048
0.000667
0.003204
0.458150

Clostridiales; Peptostreptococcaceae;

Clostridium XI; Other

Bacteria; Firmicutes; Clostridia;
5
0.020612
9.006374
0.006858
0.011372
0.860000
0.000761
0.004308
0.162996

Clostridiales; Lachnospiraceae;

Dorea; Dorea longicatena

Bacteria; Firmicutes; Clostridia;
6
0.019235
21.367383
0.002538
0.005560
0.817143
0.000119
0.000698
0.110132

Clostridiales; Lachnospiraceae;

Coprococcus; Other

Bacteria; Proteobacteria;
7
0.018423
0.000920
0.000002
0.000018
0.027619
0.002035
0.008768
0.431718

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Citrobacter;

Other

Bacteria; Firmicutes; Clostridia;
8
0.018323
4.115199
0.024936
0.047896
0.984762
0.006060
0.013562
0.709251

Clostridiales; Lachnospiraceae;

Blautia; Other

Bacteria; Firmicutes; Clostridia;
9
0.017080
4.603632
0.004039
0.011111
0.932381
0.000877
0.003080
0.431718

Clostridiales; Lachnospiraceae;

Anaerostipes; Other

Bacteria; Firmicutes; Clostridia;
10
0.016437
4.129236
0.006417
0.015065
0.883810
0.001554
0.009333
0.266520

Clostridiales; Lachnospiraceae;

Blautia; Blautia faecis

Bacteria; Firmicutes; Clostridia;
11
0.016028
2.786414
0.012087
0.020488
0.880952
0.004338
0.022200
0.301762

Clostridiales; Lachnospiraceae;

Blautia; Blautia luti

Bacteria; Firmicutes; Clostridia;
12
0.014830
3.568142
0.058907
0.051085
0.991429
0.016509
0.039130
0.850220

Clostridiales; Lachnospiraceae;

Other; Other

Bacteria; Proteobacteria;
13
0.014519
0.085127
0.012114
0.053094
0.710476
0.142299
0.194372
0.907489

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
14
0.014291
9.080515
0.005227
0.008361
0.887619
0.000576
0.002224
0.306167

Clostridiales; Lachnospiraceae;

Roseburia; Other

Bacteria; Firmicutes; Clostridia;
15
0.013755
8.938892
0.006065
0.014684
0.829524
0.000678
0.003388
0.213656

Clostridiales; Lachnospiraceae;

Blautia; Blautia obeum

Bacteria; Firmicutes; Clostridia;
16
0.012960
12.431066
0.004266
0.007594
0.781905
0.000343
0.002312
0.129956

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus comes

Bacteria; Firmicutes; Negativicutes;
17
0.012150
0.085546
0.000651
0.015259
0.138095
0.007608
0.034840
0.504405

Veillonellales; Veillonellaceae;

Veillonella; Veillonella parvula

Bacteria; Firmicutes; Other;
18
0.012115
11.203883
0.001770
0.003186
0.906667
0.000158
0.000446
0.422907

Other; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
19
0.011966
3.444316
0.013696
0.018995
0.987619
0.003976
0.012514
0.726872

Clostridiales; Other; Other; Other

Bacteria; Firmicutes; Bacilli;
20
0.011536
0.024886
0.001218
0.009072
0.381905
0.048932
0.144190
0.775330

Lactobacillales; Enterococcaceae;

Enterococcus; Other

Bacteria; Firmicutes; Bacilli;
21
0.009876
0.022380
0.000032
0.000422
0.064762
0.001415
0.006020
0.392070

Lactobacillales; Enterococcaceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
22
0.009449
7.242833
0.003542
0.008937
0.771429
0.000489
0.002122
0.213656

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia intestinalis

Bacteria; Firmicutes; Clostridia;
23
0.009315
2.723538
0.014041
0.022190
0.978095
0.005156
0.013758
0.632159

Clostridiales; Lachnospiraceae;

Lachnospiracea_incertae_sedis;

Other

Bacteria; Other; Other; Other;
24
0.008784
32.493142
0.020907
0.037823
0.939048
0.000643
0.004047
0.594714

Other; Other; Other

Bacteria; Firmicutes; Bacilli;
25
0.008722
5.827834
0.002219
0.004944
0.642857
0.000381
0.002913
0.101322

Lactobacillales; Lactobacillaceae;

Lactobacillus; Lactobacillus

rogosae

Bacteria; Firmicutes; Clostridia;
26
0.007865
2.733512
0.006267
0.010773
0.831429
0.002293
0.012148
0.312775

Clostridiales; Lachnospiraceae;

Fusicatenibacter;

Fusicatenibacter saccharivorans

Bacteria; Firmicutes; Clostridia;
27
0.007784
2.111927
0.001449
0.002690
0.775238
0.000686
0.003778
0.220264

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Other

Bacteria; Firmicutes; Clostridia;
28
0.007348
9.273969
0.004146
0.008590
0.703810
0.000447
0.002306
0.145374

Clostridiales; Eubacteriaceae;

Eubacterium; [Eubacterium]

eligens

Bacteria; Actinobacteria;
29
0.007221
3.652602
0.007053
0.023275
0.728571
0.001931
0.012523
0.248899

Coriobacteriia; Coriobacteriales;

Coriobacteriaceae; Collinsella;

Collinsella aerofaciens

Bacteria; Firmicutes; Clostridia;
30
0.006858
2.227315
0.040297
0.054719
0.911429
0.018092
0.049472
0.491189

Clostridiales; Ruminococcaceae;

Faecalibacterium; Other

Bacteria; Firmicutes; Clostridia;
31
0.006769
3.289436
0.002638
0.005359
0.748571
0.000802
0.004536
0.198238

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia inulinivorans

Bacteria; Firmicutes;
32
0.006751
0.087693
0.000444
0.003028
0.646667
0.005062
0.019598
0.665198

Erysipelotrichia;

Erysipelotrichales;

Erysipelotrichaceae;

Erysipelatoclostridium;

[Clostridium] innocuum

Bacteria; Bacteroidetes;
33
0.006385
2.413506
0.005370
0.009744
0.720952
0.002225
0.009918
0.209251

Bacteroidia; Bacteroidales;

Rikenellaceae; Alistipes;

Alistipes putredinis

Bacteria; Bacteroidetes;
34
0.006272
17.358566
0.002447
0.004365
0.805714
0.000141
0.000320
0.341410

Bacteroidia; Bacteroidales;

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
35
0.006201
68.531770
0.001859
0.007589
0.577143
0.000027
0.000160
0.085903

Clostridiales; Peptostreptococcaceae;

Romboutsia; Other

Bacteria; Verrucomicrobia;
36
0.005835
0.216159
0.004967
0.025429
0.47690
0.022979
0.087965
0.546256

Verrucomicrobiae;

Verrucomicrobiales;

Akkermansiaceae; Akkermansia;

Akkermansia muciniphila

Bacteria; Firmicutes; Clostridia;
37
0.005802
4.534829
0.023730
0.048235
0.938095
0.005233
0.027016
0.561674

Clostridiales; Ruminococcaceae;

Other; Other

Bacteria; Actinobacteria;
38
0.005564
5.121888
0.003859
0.011240
0.681905
0.000753
0.004871
0.196035

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Collinsella;

Other

Bacteria; Firmicutes; Clostridia;
39
0.005508
1.912528
0.001088
0.003036
0.729524
0.000569
0.006346
0.213656

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia hominis

Bacteria; Proteobacteria;
40
0.005506
0.013041
0.000001
0.000006
0.030476
0.000061
0.000200
0.193833

Gammaproteobacteria; Enterobacterales;

Pectobacteriaceae; Pectobacterium;

Pectobacterium carotovorum

Bacteria; Proteobacteria;
41
0.005426
0.152818
0.004755
0.018306
0.795238
0.031113
0.060092
0.856828

Gammaproteobacteria; Enterobacteriales;

Enterobacteriaceae; Other; Other

Bacteria; Firmicutes; Negativicutes;
42
0.005414
54.804655
0.001457
0.006792
0.551429
0.000027
0.000283
0.035242

Selenomonadales; Acidaminococcaceae;

Acidaminococcus; Other

Bacteria; Bacteroidetes; Bacteroidia;
43
0.005273
3.411011
0.003311
0.008964
0.650476
0.000971
0.006250
0.101322

Bacteroidales; Porphyromonadaceae;

Barnesiella; Other

Bacteria; Bacteroidetes; Bacteroidia;
44
0.005262
8.717579
0.028032
0.087686
0.770476
0.003216
0.027796
0.297357

Bacteroidales; Prevotellaceae;

Prevotella; Other

Bacteria; Bacteroidetes; Other;
45
0.005006
69.490224
0.001610
0.004345
0.674286
0.000023
0.000069
0.209251

Other; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
46
0.004916
0.084182
0.000920
0.003588
0.313333
0.010934
0.036540
0.528634

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides

xylanisolvens

Bacteria; Firmicutes; Bacilli;
47
0.004874
0.020231
0.000003
0.000033
0.030476
0.000148
0.000493
0.312775

Lactobacillales; Enterococcaceae;

Enterococcus; Enterococcus

saccharolyticus

Bacteria; Firmicutes; Clostridia;
48
0.004689
0.037033
0.000064
0.000752
0.067619
0.001720
0.007262
0.385463

Clostridiales; Clostridiaceae;

Clostridium; Clostridium

paraputrificum

Bacteria; Bacteroidetes;
49
0.004620
8.328950
0.028580
0.096181
0.687619
0.003431
0.031801
0.176211

Bacteroidia; Bacteroidales;

Prevotellaceae; Prevotella;

Prevotella copri

Bacteria; Actinobacteria;
50
0.004186
6.119334
0.000346
0.002140
0.632381
0.000056
0.000234
0.121145

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
51
0.004170
10.828662
0.004272
0.012950
0.694286
0.000395
0.002295
0.204846

Clostridiales; Ruminococcaceae;

Ruminococcus; Other

Bacteria; Bacteroidetes;
52
0.004157
21.255918
0.001190
0.003569
0.533333
0.000056
0.000396
0.059471

Bacteroidia; Bacteroidales;

Rikenellaceae; Alistipes;

Alistipes obesi

Bacteria; Firmicutes; Clostridia;
53
0.004072
1.446276
0.003104
0.009542
0.689524
0.002146
0.026081
0.191630

Clostridiales; Ruminococcaceae;

Ruminococcus; Ruminococcus faecis

Bacteria; Proteobacteria;
54
0.004048
170.525637
0.001366
0.008723
0.554286
0.000008
0.000040
0.070485

Betaproteobacteria; Burkholderiales;

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
55
0.004000
9.637715
0.006795
0.019336
0.617143
0.000705
0.004419
0.125551

Clostridiales; Ruminococcaceae;

Ruminococcus; Ruminococcus bromii

Bacteria; Actinobacteria;
56
0.003957
1.864602
0.022880
0.052680
0.916190
0.012271
0.041291
0.555066

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium; Other

Bacteria; Proteobacteria;
57
0.003954
0.008811
0.000004
0.000080
0.008571
0.000454
0.005274
0.224670

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Salmonella;

Salmonella enterica

Bacteria; Firmicutes; Clostridia;
58
0.003850
7.944086
0.001136
0.006502
0.476190
0.000143
0.002151
0.037445

Clostridiales; Lachnospiraceae;

Lachnoclostridium; Other

Bacteria; Bacteroidetes; Bacteroidia;
59
0.003838
0.447019
0.000895
0.001940
0.653333
0.002001
0.009758
0.178414

Bacteroidales; Odoribacteraceae;

Odoribacter; Odoribacter splanchnicus

Bacteria; Firmicutes; Clostridia;
60
0.003792
1.625713
0.005409
0.016380
0.690476
0.003327
0.019940
0.207048

Clostridiales; Ruminococcaceae;

Gemmiger; Gemmiger formicilis

Bacteria; Actinobacteria;
61
0.003631
9.964229
0.011395
0.038469
0.388571
0.001144
0.007492
0.244493

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium adolescentis

Bacteria; Firmicutes; Clostridia;
62
0.003623
0.268233
0.002905
0.011580
0.394286
0.010829
0.029193
0.711454

Clostridiales; Lachnospiraceae;

Lachnoclostridium; [Clostridium]

bolteae

Bacteria; Firmicutes; Erysipelotrichia;
63
0.003467
0.194184
0.001401
0.006731
0.540952
0.007217
0.022214
0.658590

Erysipelotrichales; Erysipelotrichaceae;

Erysipelatoclostridium;

Erysipelatoclostridium ramosum

Bacteria; Proteobacteria;
64
0.003411
3.992119
0.001540
0.007220
0.550476
0.000386
0.003110
0.143172

Betaproteobacteria; Burkholderiales;

Sutterellaceae; Sutterella; Other

Bacteria; Bacteroidetes;
65
0.003327
1.160602
0.005445
0.018848
0.809524
0.004691
0.027357
0.407489

Bacteroidia; Bacteroidales;

Rikenellaceae; Alistipes; Other

Bacteria; Firmicutes; Clostridia;
66
0.003255
0.101808
0.000140
0.001056
0.422857
0.001372
0.005976
0.385463

Clostridiales; Clostridiaceae;

Hungatella; Hungatella effluvii

Bacteria; Bacteroidetes;
67
0.003255
0.137451
0.000139
0.000922
0.166667
0.001014
0.005458
0.352423

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Bacteroides koreensis

Bacteria; Verrucomicrobia;
68
0.003231
0.239652
0.004987
0.032519
0.579048
0.020811
0.074687
0.500000

Verrucomicrobiae; Verrucomicrobiales;

Verrucomicrobiaceae; Akkermansia;

Other

Bacteria; Firmicutes; Clostridia;
69
0.003080
2.393841
0.004586
0.025790
0.334286
0.001916
0.009484
0.396476

Clostridiales; Lachnospiraceae;

Blautia; Blautia hominis

Bacteria; Firmicutes; Bacilli;
70
0.002959
0.062031
0.000283
0.002256
0.629524
0.004568
0.016546
0.590308

Lactobacillales; Other; Other;

Other

Bacteria; Firmicutes; Clostridia;
71
0.002950
0.067966
0.000258
0.003641
0.151429
0.003790
0.020609
0.418502

Clostridiales; Lachnospiraceae;

Blautia; Blautia producta

Bacteria; Proteobacteria;
72
0.002842
0.000000
0.000000
0.000000
0.000000
0.000053
0.000227
0.160793

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Klebsiella;

Klebsiella quasipneumoniae

Bacteria; Proteobacteria;
73
0.002787
1.652168
0.001624
0.006916
0.468571
0.000983
0.012756
0.061674

Betaproteobacteria; Burkholderiales;

Sutterellaceae; Sutterella;

Sutterella wadsworthensis

Bacteria; Firmicutes; Clostridia;
74
0.002715
1.072168
0.000363
0.001304
0.645714
0.000338
0.002766
0.273128

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Other

Bacteria; Firmicutes;
75
0.002702
0.261395
0.000049
0.000426
0.360000
0.000186
0.001803
0.068282

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Solobacterium;

Solobacterium moorei

Bacteria; Firmicutes; Clostridia;
76
0.002694
0.169285
0.000797
0.002761
0.777143
0.004709
0.015516
0.585903

Clostridiales; Ruminococcaceae;

Ruthenibacterium; Ruthenibacterium

lactatiformans

Bacteria; Firmicutes;
77
0.002692
0.264509
0.000605
0.004367
0.636190
0.002288
0.009327
0.581498

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Clostridium

XVIII; Other

Bacteria; Firmicutes; Clostridia;
78
0.002638
0.361490
0.001102
0.003027
0.803810
0.003049
0.014367
0.709251

Clostridiales; Peptostreptococcaceae;

Other; Other

Bacteria; Actinobacteria;
79
0.002627
2.520416
0.001805
0.010314
0.364762
0.000716
0.003769
0.240088

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium longum

Bacteria; Actinobacteria;
80
0.002581
46.237711
0.000034
0.000091
0.425714
0.000001
0.000009
0.011013

Actinobacteria; Actinomycetales;

Actinomycetaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
81
0.002556
2.307456
0.000864
0.003153
0.328571
0.000374
0.002447
0.145374

Clostridiales; Ruminococcaceae;

Agathobaculum; Agathobaculum

butyriciproducens

Bacteria; Firmicutes; Clostridia;
82
0.002550
0.608632
0.008229
0.028839
0.841905
0.013521
0.029521
0.647577

Clostridiales; Lachnospiraceae;

Blautia; [Ruminococcus]

gnavus

Bacteria; Firmicutes; Clostridia;
83
0.002513
1.803142
0.025044
0.061261
0.471429
0.013889
0.039999
0.533040

Clostridiales; Lachnospiraceae;

Blautia; Blautia wexlerae

Bacteria; Firmicutes; Clostridia;
84
0.002482
29.084736
0.000350
0.000968
0.463810
0.000012
0.000126
0.037445

Clostridiales; Ruminococcaceae;

Intestinimonas; Other

Bacteria; Firmicutes; Clostridia;
85
0.002462
1.391015
0.004213
0.017069
0.440000
0.003029
0.010903
0.334802

Clostridiales; Lachnospiraceae;

Faecalimonas; Faecalimonas

umbilicata

Bacteria; Firmicutes; Clostridia;
86
0.002408
0.379372
0.002625
0.008890
0.859048
0.006920
0.021979
0.466960

Clostridiales; Lachnospiraceae;

Ruminococcus2; Other

Bacteria; Proteobacteria;
87
0.002378
0.227057
0.000021
0.000214
0.102857
0.000092
0.000328
0.262115

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Shigella;

Shigella dysenteriae

Bacteria; Bacteroidetes;
88
0.002364
2.259560
0.058385
0.090300
0.932381
0.025839
0.077907
0.674009

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Bacteroides vulgatus

Bacteria; Bacteroidetes;
89
0.002353
8.917954
0.003676
0.016371
0.485714
0.000412
0.003673
0.077093

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Bacteroides eggerthii

Bacteria; Firmicutes; Clostridia;
90
0.002348
0.309577
0.001812
0.004738
0.907619
0.005855
0.013353
0.786344

Clostridiales; Lachnospiraceae;

Clostridium XIVa; Other

Bacteria; Actinobacteria;
91
0.002301
0.397177
0.000586
0.002024
0.633333
0.001476
0.005130
0.486784

Coriobacteriia; Eggerthellales;

Eggerthellaceae; Eggerthella;

Eggerthella lenta

Bacteria; Bacteroidetes;
92
0.002298
2.850960
0.001917
0.006693
0.488571
0.000672
0.004898
0.072687

Bacteroidia; Bacteroidales;

Prevotellaceae; Paraprevotella;

Other

Bacteria; Firmicutes; Clostridia;
93
0.002296
10.604531
0.000034
0.000078
0.503810
0.000003
0.000020
0.048458

Other; Other; Other; Other

Bacteria; Firmicutes; Negativicutes;
94
0.002252
0.180724
0.002534
0.019512
0.676190
0.014022
0.044571
0.616740

Veillonellales; Veillonellaceae;

Veillonella; Veillonella dispar

Bacteria; Actinobacteria;
95
0.002249
0.188958
0.000082
0.000259
0.501905
0.000435
0.001791
0.281938

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Eggerthella;

Other

Bacteria; Firmicutes; Bacilli;
96
0.002174
0.204004
0.000047
0.000654
0.142857
0.000229
0.004154
0.026432

Lactobacillales; Lactobacillaceae;

Lactobacillus; Lactobacillus sakei

Bacteria; Firmicutes; Bacilli;
97
0.002114
0.963700
0.013303
0.034735
0.982857
0.013804
0.038345
0.894273

Lactobacillales; Streptococcaceae;

Streptococcus; Other

Bacteria; Bacteroidetes; Bacteroidia;
98
0.002069
1.422532
0.100008
0.102665
0.973333
0.070303
0.112647
0.909692

Bacteroidales; Bacteroidaceae;

Bacteroides; Other

Bacteria; Firmicutes; Clostridia;
99
0.002069
1.113561
0.002963
0.010174
0.800952
0.002661
0.011396
0.466960

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Intestinibacter

bartlettii

Bacteria; Firmicutes; Clostridia;
100
0.002000
0.107240
0.000019
0.000167
0.205714
0.000181
0.000841
0.222467

Clostridiales; Lachnospiraceae;

Hungatella; Other

IBD = Inflammatory Bowel Disease;

CDI = Clostridiodes difficile Infection;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 13

IBD (Ulcerative Colitis) vs Control delineation features - (taxonomy)

Feature

(Taxonomic order: Kingdom;
FC

Phylum; Class; Order;
RFFR
UC vs
Abundance (Ctrl)
Abundance (UC)

Family; Genus; Species)
#
MDA
Ctrl
M
SD
DP
M
SD
DP

Bacteria; Firmicutes; Clostridia;
1
0.014379
0.476019
0.027343
0.033723
0.892259
0.013016
0.029152
0.432810

Clostridia; Clostridiales;

Lachnospiraceae; Not Available;

[Eubacterium] rectale

Bacteria; Firmicutes; Clostridia;
2
0.013473
80.381153
0.000004
0.000027
0.059623
0.000284
0.002361
0.500873

Clostridiales; Lachnospiraceae;

Lachnoclostridium; Other

Bacteria; Firmicutes; Clostridia;
3
0.013339
0.799618
0.026222
0.040290
0.913180
0.020967
0.049016
0.474695

Clostridiales; Lachnospiraceae;

Blautia; Blautia wexlerae

Bacteria; Bacteroidetes;
4
0.013137
0.122457
0.005759
0.017531
0.798117
0.000705
0.002697
0.345550

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Bacteroides xylanisolvens

Bacteria; Firmicutes; Clostridia;
5
0.010948
16.491037
0.000028
0.000117
0.142259
0.000467
0.001038
0.565445

Clostridiales; Ruminococcaceae;

Intestinimonas; Other

Bacteria; Bacteroidetes;
6
0.010757
6.242436
0.000343
0.002384
0.446653
0.002144
0.005280
0.692845

Other; Other; Other; Other; Other

Bacteria; Firmicutes;
7
0.009802
5.408171
0.000201
0.002675
0.170502
0.001089
0.004955
0.605585

Negativicutes; Selenomonadales;

Acidaminococcaceae;

Acidaminococcus; Other

Bacteria; Bacteroidetes;
8
0.009746
3.001514
0.001006
0.004950
0.701883
0.003020
0.005204
0.842932

Bacteroidia; Bacteroidales;

Other; Other; Other

Bacteria; Firmicutes; Bacilli;
9
0.008625
5.042526
0.000034
0.000231
0.221757
0.000169
0.002014
0.630017

Lactobacillales; Other; Other; Other

Bacteria; Firmicutes; Other; Other;
10
0.008104
2.427599
0.000772
0.001531
0.731172
0.001875
0.002546
0.942408

Other; Other; Other

Bacteria; Actinobacteria;
11
0.008019
2.363177
0.000030
0.000132
0.206067
0.000071
0.000170
0.609075

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Other; Other

Bacteria; Actinobacteria;
12
0.007946
6.733162
0.000004
0.000028
0.060669
0.000029
0.000075
0.453752

Actinobacteria; Actinomycetales;

Actinomycetaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
13
0.007881
0.679150
0.003574
0.006957
0.786611
0.002427
0.006841
0.413613

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia faecis

Bacteria; Other; Other;
14
0.007376
4.922276
0.005479
0.021341
0.819038
0.026969
0.043756
0.954625

Other; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
15
0.007263
0.455811
0.002003
0.003530
0.778243
0.000913
0.002441
0.382199

Clostridiales; Ruminococcaceae;

Agathobaculum;

Agathobaculum butyriciproducens

Bacteria; Verrucomicrobia;
16
0.007047
0.380353
0.008451
0.033406
0.643305
0.003214
0.014232
0.603839

Verrucomicrobiae; Verrucomicrobiales;

Verrucomicrobiaceae;

Akkermansia; Other

Bacteria; Firmicutes; Clostridia;
17
0.006962
8.265424
0.000006
0.000030
0.071130
0.000048
0.000116
0.431065

Clostridiales; Ruminococcaceae;

Subdoligranulum; Other

Bacteria; Proteobacteria;
18
0.006642
0.191680
0.018587
0.056891
0.816946
0.003563
0.024830
0.661431

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
19
0.006630
0.684426
0.007228
0.030628
0.802301
0.004947
0.024219
0.439791

Clostridiales; Peptostreptococcaceae;

Romboutsia;

Romboutsia timonensis

Bacteria; Bacteroidetes; Bacteroidia;
20
0.006625
0.621235
0.026934
0.054373
0.777197
0.016732
0.043743
0.403141

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides dorei

Bacteria; Proteobacteria;
21
0.006459
34.153918
0.000020
0.000091
0.140167
0.000693
0.003897
0.506108

Betaproteobacteria; Other;

Other; Other; Other

Bacteria; Bacteroidetes;
22
0.006368
1.638540
0.061864
0.066323
0.995816
0.101366
0.098052
0.986038

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides; Other

Bacteria; Firmicutes; Clostridia;
23
0.006271
0.395539
0.004287
0.008920
0.938285
0.001696
0.003399
0.902269

Clostridiales; Lachnospiraceae;

Ruminococcus2; Other

Bacteria; Firmicutes; Clostridia;
24
0.006199
0.496491
0.006404
0.011919
0.855649
0.003180
0.008982
0.766143

Clostridiales; Ruminococcaceae;

Ruminococcus;

Ruminococcus faecis

Bacteria; Actinobacteria;
25
0.006065
1.861459
0.010770
0.034421
0.756276
0.020048
0.036905
0.956370

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae;

Bifidobacterium; Other

Bacteria; Firmicutes; Clostridia;
26
0.005992
2.783800
0.000009
0.000050
0.106695
0.000024
0.000061
0.446771

Clostridiales; Ruminococcaceae;

Pseudoflavonifractor; Other

Bacteria; Firmicutes; Clostridia;
27
0.005931
1.308143
0.041475
0.042224
0.967573
0.054255
0.057663
0.979058

Clostridiales; Ruminococcaceae;

Faecalibacterium; Other

Bacteria; Firmicutes; Clostridia;
28
0.005856
2.611655
0.002631
0.004823
0.891213
0.006872
0.009133
0.952880

Clostridiales; Lachnospiraceae;

Roseburia; Other

Bacteria; Proteobacteria;
29
0.005751
15.517704
0.000078
0.000419
0.219665
0.001207
0.006012
0.596859

Betaproteobacteria; Burkholderiales;

Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
30
0.005694
0.440139
0.001533
0.004041
0.702929
0.000675
0.003398
0.359511

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides ovatus

Bacteria; Firmicutes; Clostridia;
31
0.005620
0.639836
0.011136
0.014246
0.933054
0.007125
0.010254
0.888307

Clostridiales; Lachnospiraceae;

Fusicatenibacter;

Fusicatenibacter saccharivorans

Bacteria; Firmicutes; Clostridia;
32
0.005521
0.564502
0.010075
0.018327
0.817992
0.005688
0.011516
0.780105

Clostridiales; Ruminococcaceae;

Gemmiger; Gemmiger formicilis

Bacteria; Firmicutes; Clostridia;
33
0.005497
7.294859
0.000261
0.001295
0.320084
0.001907
0.007485
0.673647

Clostridiales; Peptostreptococcaceae;

Romboutsia; Other

Bacteria; Actinobacteria;
34
0.005403
0.619451
0.010594
0.025323
0.555439
0.006563
0.018823
0.834206

Coriobacteriia; Coriobacteriales;

Coriobacteriaceae; Collinsella;

Collinsella aerofaciens

Bacteria; Firmicutes; Clostridia;
35
0.005320
2.137281
0.000185
0.000631
0.540795
0.000396
0.001292
0.815009

Clostridiales; Ruminococcaceae;

Flavonifractor; Other

Bacteria; Proteobacteria; Other;
36
0.005199
9.024774
0.000039
0.000258
0.177824
0.000349
0.001180
0.549738

Other; Other; Other; Other

Bacteria; Firmicutes;
37
0.005019
0.862352
0.000031
0.000218
0.186192
0.000027
0.000063
0.530541

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Holdemania; Other

Bacteria; Firmicutes; Clostridia;
38
0.005008
0.748738
0.000058
0.000380
0.228033
0.000043
0.000082
0.589878

Other; Other; Other; Other

Bacteria; Actinobacteria; Actinobacteria;
39
0.004908
8.238295
0.000001
0.000010
0.032427
0.000010
0.000026
0.312391

Bifidobacteriales; Bifidobacteriaceae;

Bifidobacterium;

Bifidobacterium boum

Bacteria; Firmicutes; Clostridia;
40
0.004854
1.549031
0.018787
0.024996
0.982218
0.029101
0.045538
0.984293

Clostridiales; Ruminococcaceae;

Other; Other

Bacteria; Actinobacteria;
41
0.004831
1.322599
0.012432
0.030734
0.647490
0.016442
0.046861
0.406632

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium adolescentis

Bacteria; Bacteroidetes;
42
0.004787
3.407793
0.000153
0.001465
0.195607
0.000522
0.001727
0.525305

Bacteroidia; Bacteroidales;

Rikenellaceae; Other; Other

Bacteria; Bacteroidetes;
43
0.004682
0.181735
0.000507
0.001799
0.414226
0.000092
0.000652
0.155323

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Bacteroides koreensis

Bacteria; Firmicutes; Clostridia;
44
0.004511
0.768938
0.001974
0.005469
0.876569
0.001518
0.002170
0.855148

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Other

Bacteria; Actinobacteria;
45
0.004450
4.165216
0.000034
0.000239
0.065900
0.000142
0.000505
0.380454

Coriobacteriia; Eggerthellales;

Eggerthellaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
46
0.004399
1.650736
0.000018
0.000065
0.200837
0.000030
0.000081
0.534031

Clostridiales; Lachnospiraceae;

Lachnoclostridium; [Clostridium]

citroniae

Bacteria; Bacteroidetes; Bacteroidia;
47
0.004397
0.545097
0.002877
0.004957
0.740586
0.001568
0.003304
0.657941

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes shahii

Bacteria; Firmicutes; Clostridia;
48
0.004335
1.136695
0.000680
0.002129
0.750000
0.000773
0.002754
0.907504

Clostridiales; Lachnospiraceae;

Clostridium XIVa; Other

Bacteria; Firmicutes; Clostridia;
49
0.004244
0.407908
0.012988
0.031050
0.823222
0.005298
0.012954
0.802792

Clostridiales; Ruminococcaceae;

Ruminococcus; Other

Bacteria; Firmicutes; Clostridia;
50
0.004203
1.450417
0.013600
0.022700
0.991632
0.019726
0.031062
0.994764

Clostridiales; Lachnospiraceae;

Blautia; Other

Bacteria; Bacteroidetes; Bacteroidia;
51
0.004159
1.134801
0.030320
0.042820
0.952929
0.034407
0.044854
0.945899

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides uniformis

Bacteria; Firmicutes; Clostridia;
52
0.004083
1.141585
0.004115
0.005620
0.901674
0.004698
0.008841
0.942408

Clostridiales; Lachnospiraceae;

Dorea; Other

Bacteria; Firmicutes; Bacilli;
53
0.004062
1.508857
0.007021
0.016525
0.938285
0.010593
0.027852
0.996510

Lactobacillales; Streptococcaceae;

Streptococcus; Other

Bacteria; Bacteroidetes; Bacteroidia;
54
0.004054
0.173174
0.004707
0.017805
0.510460
0.000815
0.007838
0.212914

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides cellulosilyticus

Bacteria; Firmicutes; Clostridia;
55
0.004046
3.216726
0.000004
0.000025
0.071130
0.000014
0.000057
0.352531

Clostridiales; Eubacteriaceae;

Anaerofustis; Other

Bacteria; Firmicutes; Clostridia;
56
0.004018
0.403832
0.004267
0.014123
0.426778
0.001723
0.007852
0.375218

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus eutactus

Bacteria; Verrucomicrobia;
57
0.003992
0.223330
0.015218
0.049261
0.607741
0.003399
0.014277
0.523560

Verrucomicrobiae; Verrucomicrobiales;

Akkermansiaceae; Akkermansia;

Akkermansia muciniphila

Bacteria; Firmicutes; Negativicutes;
58
0.003975
0.135223
0.007826
0.017524
0.501046
0.001058
0.003282
0.310646

Acidaminococcales; Acidaminococcaceae;

Phascolarctobacterium;

Phascolarctobacterium faecium

Bacteria; Bacteroidetes; Bacteroidia;
59
0.003945
1.635282
0.041765
0.060175
0.972803
0.068297
0.095683
0.961606

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides vulgatus

Bacteria; Actinobacteria;
60
0.003942
1.609195
0.000891
0.003500
0.290795
0.001434
0.004397
0.455497

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium bifidum

Bacteria; Firmicutes; Bacilli; Bacillales;
61
0.003933
6.963814
0.000027
0.000075
0.261506
0.000191
0.001477
0.525305

Other; Gemella; Other

Bacteria; Actinobacteria;
62
0.003871
1.566900
0.001571
0.006672
0.605649
0.002461
0.011990
0.390925

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium longum

Bacteria; Firmicutes; Clostridia;
63
0.003859
1.178341
0.000966
0.002406
0.737448
0.001138
0.003845
0.886562

Clostridiales; Ruminococcaceae;

Flavonifractor;

Flavonifractor plautii

Bacteria; Firmicutes; Clostridia;
64
0.003844
58.184490
0.000001
0.000013
0.018828
0.000063
0.000720
0.167539

Clostridiales; Peptostreptococcaceae;

Peptostreptococcus; Other

Bacteria; Bacteroidetes; Bacteroidia;
65
0.003841
0.821235
0.036984
0.104763
0.619247
0.030373
0.083313
0.818499

Bacteroidales; Prevotellaceae;

Prevotella; Other

Bacteria; Firmicutes; Bacilli;
66
0.003780
2.302825
0.000013
0.000081
0.101464
0.000029
0.000154
0.162304

Lactobacillales; Carnobacteriaceae;

Granulicatella;

Granulicatella adiacens

Bacteria; Firmicutes; Clostridia;
67
0.003665
1.426542
0.000871
0.003572
0.674686
0.001242
0.002653
0.856894

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia hominis

Bacteria; Firmicutes; Negativicutes;
68
0.003608
1.715495
0.000080
0.000497
0.175732
0.000137
0.000744
0.506108

Veillonellales; Veillonellaceae;

Veillonella; Other

Bacteria; Firmicutes; Negativicutes;
69
0.003480
1.505910
0.000733
0.004959
0.304393
0.001104
0.004629
0.626527

Selenomonadales; Veillonellaceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
70
0.003380
1.209792
0.000015
0.000126
0.134937
0.000018
0.000055
0.406632

Clostridiales; Ruminococcaceae;

Anaerotruncus; Other

Bacteria; Firmicutes; Tissierellia;
71
0.003344
234.211022
0.000002
0.000013
0.034519
0.000370
0.003594
0.211169

Tissierellales; Peptoniphilaceae;

Peptoniphilus; Other

Bacteria; Actinobacteria;
72
0.003246
1.848695
0.000223
0.000872
0.456067
0.000412
0.002789
0.726003

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
73
0.003199
0.578007
0.016905
0.025464
0.755230
0.009771
0.025705
0.808028

Clostridiales; Ruminococcaceae;

Faecalibacterium;

Faecalibacterium prausnitzii

Bacteria; Firmicutes; Clostridia;
74
0.003190
94.572109
0.000009
0.000077
0.089958
0.000893
0.012010
0.251309

Clostridiales; Clostridiales_Incertae

Sedis XI; Parvimonas; Other

Bacteria; Firmicutes; Clostridia;
75
0.003177
0.488163
0.000797
0.003787
0.583682
0.000389
0.001687
0.364747

Clostridiales; Lachnospiraceae;

Lachnoclostridium;

[Clostridium] bolteae

Bacteria; Firmicutes; Clostridia;
76
0.003157
1.081872
0.007247
0.013333
0.910042
0.007841
0.017319
0.958115

Clostridiales; Lachnospiraceae;

Blautia; Blautia faecis

Bacteria; Firmicutes; Clostridia;
77
0.003114
1.622099
0.002311
0.004024
0.911088
0.003749
0.012395
0.973822

Clostridiales; Lachnospiraceae;

Anaerostipes; Other

Bacteria; Bacteroidetes; Bacteroidia;
78
0.003106
0.021896
0.003770
0.017430
0.255230
0.000083
0.000612
0.150087

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides thetaiotaomicron

Bacteria; Actinobacteria;
79
0.003095
0.893259
0.000083
0.000480
0.264644
0.000074
0.000270
0.556719

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Eggerthella; Other

Bacteria; Firmicutes; Clostridia;
80
0.003089
1.623955
0.000189
0.001137
0.438285
0.000307
0.001139
0.687609

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Other

Bacteria; Firmicutes; Clostridia;
81
0.003087
5.888868
0.000085
0.000380
0.253138
0.000502
0.002402
0.553229

Clostridiales; Peptostreptococcaceae;

Terrisporobacter; Other

Bacteria; Firmicutes; Erysipelotrichia;
82
0.003087
38.278503
0.000007
0.000074
0.027197
0.000254
0.002137
0.228621

Erysipelotrichales; Erysipelotrichaceae;

Faecalicoccus; Other

Bacteria; Bacteroidetes; Bacteroidia;
83
0.003087
1.019142
0.004785
0.007226
0.927824
0.004877
0.008018
0.916230

Bacteroidales; Porphyromonadaceae;

Parabacteroides; Other

Bacteria; Firmicutes; Clostridia;
84
0.003069
1.016844
0.016348
0.020690
0.988494
0.016624
0.022247
0.993019

Clostridiales; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
85
0.003049
0.825494
0.008663
0.012407
0.783473
0.007151
0.011051
0.792321

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes putredinis

Bacteria; Firmicutes; Clostridia;
86
0.003014
2.221178
0.000238
0.001005
0.315900
0.000528
0.002699
0.488656

Clostridiales; Lachnospiraceae;

Blautia; Blautia hydrogenotrophica

Bacteria; Bacteroidetes; Bacteroidia;
87
0.002991
0.478481
0.000405
0.006638
0.361925
0.000194
0.000596
0.635253

Bacteroidales; Porphyromonadaceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
88
0.002965
0.767881
0.017321
0.019449
0.981172
0.013301
0.017704
0.989529

Clostridiales; Lachnospiraceae;

Lachnospiracea_incertae_sedis; Other

Bacteria; Actinobacteria; Coriobacteriia;
89
0.002946
0.756428
0.000809
0.004296
0.456067
0.000612
0.002776
0.242583

Eggerthellales; Eggerthellaceae;

Adlercreutzia;

Adlercreutzia equolifaciens

Bacteria; Bacteroidetes; Bacteroidia;
90
0.002940
0.456826
0.001710
0.007218
0.498954
0.000781
0.003104
0.246073

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides finegoldii

Bacteria; Actinobacteria;
91
0.002933
0.904545
0.000101
0.000213
0.513598
0.000091
0.000219
0.776614

Actinobacteria; Actinomycetales;

Actinomycetaceae;

Actinomyces; Other

Bacteria; Firmicutes; Clostridia;
92
0.002928
0.463041
0.001179
0.001896
0.610879
0.000546
0.001248
0.333333

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus catus

Bacteria; Firmicutes; Clostridia;
93
0.002916
1.532655
0.000265
0.001097
0.266736
0.000407
0.001456
0.321117

Clostridiales; Ruminococcaceae;

Negativibacillus;

Negativibacillus massiliensis

Bacteria; Firmicutes; Erysipelotrichia;
94
0.002914
6.114725
0.000012
0.000046
0.188285
0.000076
0.000575
0.357766

Erysipelotrichales; Erysipelotrichaceae;

Solobacterium;

Solobacterium moorei

Bacteria; Bacteroidetes; Bacteroidia;
95
0.002893
0.751197
0.008488
0.015847
0.756276
0.006376
0.017283
0.757417

Bacteroidales; Tannerellaceae;

Parabacteroides;

Parabacteroides merdae

Bacteria; Actinobacteria;
96
0.002887
2.537300
0.000008
0.000039
0.114017
0.000020
0.000047
0.420593

Actinobacteria; Other; Other;

Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
97
0.002880
1.254868
0.005870
0.016013
0.892259
0.007366
0.024075
0.872600

Bacteroidales; Rikenellaceae;

Alistipes; Other

Bacteria; Firmicutes; Negativicutes;
98
0.002871
0.472637
0.001273
0.004421
0.533473
0.000602
0.002122
0.382199

Selenomonadales; Acidaminococcaceae;

Phascolarctobacterium; Other

Bacteria; Bacteroidetes; Bacteroidia;
99
0.002855
0.490327
0.002446
0.004682
0.764644
0.001199
0.002404
0.766143

Bacteroidales; Odoribacteraceae;

Odoribacter;

Odoribacter splanchnicus

Bacteria; Firmicutes; Clostridia;
100
0.002854
0.711916
0.001015
0.002715
0.754184
0.000723
0.003535
0.757417

Clostridiales; Ruminococcaceae;

Not Available;

[Clostridium] leptum

IBD = Inflammatory Bowel Disease; UC = Ulcerative Colitis; Ctrl = Control; RFFR = Random Forest Feature Rank; # = Rank; MDA = Mean Decrease Accuracy; FC = Fold Change; M = Mean; SD = Standard Deviation; DP = Detection Prevalence;

TABLE 14

IBD (Crohn's Disease) vs Control delineation features - (taxonomy)

Feature

(Taxonomic order: Kingdom;
FC

Phylum; Class; Order;
RFFR
CD vs
Abundance (Ctrl)
Abundance (CD)

Family; Genus; Species)
#
MDA
Ctrl
M
SD
DP
M
SD
DP

Bacteria; Firmicutes; Clostridia;
1
0.021267
0.353537
0.027343
0.033723
0.892259
0.009667
0.039898
0.366876

Clostridiales; Lachnospiraceae;

Not Available;

[Eubacterium] rectale

Bacteria; Firmicutes; Clostridia;
2
0.019342
0.567358
0.041475
0.042224
0.967573
0.023531
0.045680
0.830189

Clostridiales; Ruminococcaceae;

Faecalibacterium; Other

Bacteria; Firmicutes; Clostridia;
3
0.019271
0.919620
0.018787
0.024996
0.982218
0.017277
0.050587
0.882600

Clostridiales; Ruminococcaceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
4
0.018052
0.128232
0.007228
0.030628
0.802301
0.000927
0.006042
0.266247

Clostridiales; Peptostreptococcaceae;

Romboutsia; Romboutsia timonensis

Bacteria; Bacteroidetes; Bacteroidia;
5
0.016697
0.204739
0.005759
0.017531
0.798117
0.001179
0.004416
0.274633

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides xylanisolvens

Bacteria; Firmicutes; Clostridia;
6
0.015216
1.141805
0.026222
0.040290
0.913180
0.029940
0.073071
0.467505

Clostridiales; Lachnospiraceae;

Blautia; Blautia wexlerae

Bacteria; Firmicutes; Clostridia;
7
0.014032
13.373641
0.000657
0.004356
0.218619
0.008788
0.024397
0.662474

Clostridiales; Lachnospiraceae;

Faecalimonas;

Faecalimonas umbilicata

Bacteria; Firmicutes; Clostridia;
8
0.013927
0.425272
0.003574
0.006957
0.786611
0.001520
0.010646
0.257862

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia faecis

Bacteria; Firmicutes; Clostridia;
9
0.013662
0.073034
0.016905
0.025464
0.755230
0.001235
0.005413
0.417191

Clostridiales; Ruminococcaceae;

Faecalibacterium;

Faecalibacterium prausnitzii

Bacteria; Firmicutes; Clostridia;
10
0.013457
610.962669
0.000004
0.000027
0.059623
0.002159
0.009194
0.446541

Clostridiales; Lachnospiraceae;

Lachnoclostridium; Other

Bacteria; Firmicutes; Clostridia;
11
0.011943
0.401796
0.002003
0.003530
0.778243
0.000805
0.003840
0.264151

Clostridiales; Ruminococcaceae;

Agathobaculum;

Agathobaculum butyriciproducens

Bacteria; Firmicutes; Clostridia;
12
0.011450
0.503572
0.010075
0.018327
0.817992
0.005074
0.020778
0.582809

Clostridiales; Ruminococcaceae;

Gemmiger; Gemmiger formicilis

Bacteria; Firmicutes; Clostridia;
13
0.011427
0.470210
0.011136
0.014246
0.933054
0.005236
0.011289
0.763103

Clostridiales; Lachnospiraceae;

Fusicatenibacter;

Fusicatenibacter saccharivorans

Bacteria; Firmicutes; Clostridia;
14
0.010838
4.504117
0.000680
0.002129
0.750000
0.003062
0.006122
0.907757

Clostridiales; Lachnospiraceae;

Clostridium XIVa; Other

Bacteria; Firmicutes; Clostridia;
15
0.009696
0.234078
0.012988
0.031050
0.823222
0.003040
0.012851
0.563941

Clostridiales; Ruminococcaceae;

Ruminococcus; Other

Bacteria; Firmicutes; Clostridia;
16
0.008564
0.470453
0.006404
0.011919
0.855649
0.003013
0.010184
0.597484

Clostridiales; Ruminococcaceae;

Ruminococcus;

Ruminococcus faecis

Bacteria; Firmicutes; Clostridia;
17
0.008287
0.153682
0.001179
0.001896
0.610879
0.000181
0.000969
0.174004

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus catus

Bacteria; Firmicutes; Clostridia;
18
0.007415
7.431555
0.000797
0.003787
0.583682
0.005926
0.016593
0.429769

Clostridiales; Lachnospiraceae;

Lachnoclostridium;

[Clostridium] bolteae

Bacteria; Firmicutes; Clostridia;
19
0.007217
0.317562
0.002414
0.007114
0.726987
0.000767
0.003426
0.484277

Clostridiales; Ruminococcaceae;

Clostridium IV; Other

Bacteria; Firmicutes; Clostridia;
20
0.007174
0.345504
0.005117
0.009258
0.783473
0.001768
0.005336
0.517820

Clostridiales; Eubacteriaceae;

Eubacterium;

[Eubacterium] eligens

Bacteria; Firmicutes; Clostridia;
21
0.006999
0.375879
0.003746
0.007142
0.809623
0.001408
0.003615
0.568134

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia inulinivorans

Bacteria; Firmicutes; Clostridia;
22
0.006937
0.691676
0.001974
0.005469
0.876569
0.001365
0.003206
0.679245

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Other

Bacteria; Bacteroidetes; Bacteroidia;
23
0.006887
1.113245
0.026934
0.054373
0.777197
0.029984
0.075431
0.373166

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides dorei

Bacteria; Firmicutes; Clostridia;
24
0.006880
0.674096
0.004544
0.010129
0.852510
0.003063
0.008567
0.622642

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia intestinalis

Bacteria; Proteobacteria;
25
0.006862
32.288412
0.000105
0.000705
0.231172
0.003383
0.009955
0.624738

Gammaproteobacteria; Other; Other;

Other; Other

Bacteria; Firmicutes; Clostridia;
26
0.006708
4.893537
0.003177
0.012917
0.672594
0.015546
0.040155
0.903564

Clostridiales; Lachnospiraceae;

Blautia; [Ruminococcus] gnavus

Bacteria; Bacteroidetes; Bacteroidia;
27
0.006671
0.182477
0.002877
0.004957
0.740586
0.000525
0.001528
0.452830

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes shahii

Bacteria; Firmicutes; Bacilli;
28
0.006558
12.509891
0.000034
0.000231
0.221757
0.000420
0.002511
0.628931

Lactobacillales; Other; Other; Other

Bacteria; Actinobacteria;
29
0.006544
9.310713
0.000004
0.000028
0.060669
0.000040
0.000108
0.392034

Actinobacteria; Actinomycetales;

Actinomycetaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
30
0.006511
0.495293
0.007882
0.013361
0.888075
0.003904
0.011642
0.710692

Clostridiales; Lachnospiraceae;

Blautia; Blautia obeum

Bacteria; Bacteroidetes; Bacteroidia;
31
0.006485
0.950779
0.004785
0.007226
0.927824
0.004550
0.011480
0.763103

Bacteroidales; Porphyromonadaceae;

Parabacteroides; Other

Bacteria; Proteobacteria; Other;
32
0.006401
27.580889
0.000039
0.000258
0.177824
0.001067
0.002875
0.570231

Other; Other; Other; Other

Bacteria; Bacteroidetes; Other;
33
0.006058
2.821314
0.000343
0.002384
0.446653
0.000969
0.002709
0.651992

Other; Other; Other; Other

Bacteria; Proteobacteria;
34
0.006018
109.541112
0.000321
0.002652
0.202929
0.035184
0.110490
0.547170

Gammaproteobacteria; Enterobacterales;

Other; Other; Other

Bacteria; Proteobacteria;
35
0.005918
405.991255
0.000000
0.000002
0.013598
0.000052
0.000161
0.266247

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Rosenbergiella;

Rosenbergiella collisarenosi

Bacteria; Bacteroidetes; Bacteroidia;
36
0.005856
0.550090
0.001533
0.004041
0.702929
0.000843
0.005642
0.310273

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides ovatus

Bacteria; Firmicutes; Clostridia;
37
0.005826
0.491817
0.001354
0.004548
0.874477
0.000666
0.001734
0.635220

Clostridiales; Ruminococcaceae;

Ruthenibacterium;

Ruthenibacterium lactatiformans

Bacteria; Proteobacteria;
38
0.005781
530.985698
0.000000
0.000001
0.007322
0.000037
0.000115
0.247379

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Rosenbergiella;

Rosenbergiella nectarea

Bacteria; Firmicutes; Clostridia;
39
0.005758
0.649332
0.007247
0.013333
0.910042
0.004706
0.011591
0.794549

Clostridiales; Lachnospiraceae;

Blautia; Blautia faecis

Bacteria; Bacteroidetes; Bacteroidia;
40
0.005455
1.112833
0.041765
0.060175
0.972803
0.046477
0.081902
0.897275

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides vulgatus

Bacteria; Firmicutes; Clostridia;
41
0.005404
0.527515
0.001015
0.002715
0.754184
0.000536
0.002380
0.469602

Clostridiales; Ruminococcaceae;

Not Available; [Clostridium]

leptum

Bacteria; Other; Other; Other;
42
0.005278
2.486706
0.005479
0.021341
0.819038
0.013624
0.027468
0.920335

Other; Other; Other

Bacteria; Firmicutes; Negativicutes;
43
0.005228
18.334440
0.000307
0.004018
0.348326
0.005635
0.031520
0.643606

Selenomonadales; Veillonellaceae;

Veillonella; Other

Bacteria; Bacteroidetes; Bacteroidia;
44
0.005204
0.134867
0.004707
0.017805
0.510460
0.000635
0.004389
0.138365

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides cellulosilyticus

Bacteria; Firmicutes;
45
0.005122
2.128493
0.000772
0.001531
0.731172
0.001644
0.003814
0.863732

Other; Other; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
46
0.005072
1.746902
0.001006
0.004950
0.701883
0.001758
0.002928
0.761006

Bacteroidales; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
47
0.005022
2.293744
0.013600
0.022700
0.991632
0.031195
0.061840
0.972746

Clostridiales; Lachnospiraceae;

Blautia; Other

Bacteria; Firmicutes; Negativicutes;
48
0.005021
9.433882
0.000201
0.002675
0.170502
0.001899
0.008474
0.486373

Selenomonadales; Acidaminococcaceae;

Acidaminococcus; Other

Bacteria; Bacteroidetes; Bacteroidia;
49
0.004900
1.590217
0.061864
0.066323
0.995816
0.098377
0.108029
0.958071

Bacteroidales; Bacteroidaceae;

Bacteroides; Other

Bacteria; Firmicutes; Clostridia;
50
0.004828
1.277811
0.004115
0.005620
0.901674
0.005258
0.012151
0.813417

Clostridiales; Lachnospiraceae;

Dorea; Other

Bacteria; Bacteroidetes; Bacteroidia;
51
0.004786
0.750583
0.030320
0.042820
0.952929
0.022757
0.044217
0.853249

Bacteroidales; Bacteroidaceae;

Bacteroides; Bacteroides uniformis

Bacteria; Firmicutes; Clostridia;
52
0.004728
3.159827
0.000114
0.000526
0.312762
0.000359
0.001053
0.534591

Clostridiales; Lachnospiraceae;

Lachnoclostridium;

[Clostridium] aldenense

Bacteria; Firmicutes; Negativicutes;
53
0.004647
21.095184
0.000080
0.000497
0.175732
0.001681
0.012096
0.526205

Veillonellales; Veillonellaceae;

Veillonella; Other

Bacteria; Firmicutes; Clostridia;
54
0.004562
0.787579
0.015276
0.024437
0.915272
0.012031
0.022706
0.796646

Clostridiales; Lachnospiraceae;

Blautia; Blautia luti

Bacteria; Firmicutes; Clostridia;
55
0.004460
8.703254
0.001034
0.005783
0.419456
0.008997
0.037618
0.356394

Clostridiales; Lachnospiraceae;

Blautia; Blautia hominis

Bacteria; Verrucomicrobia;
56
0.004385
0.450202
0.015218
0.049261
0.607741
0.006851
0.034258
0.419287

Verrucomicrobiae; Verrucomicrobiales;

Akkermansiaceae; Akkermansia;

Akkermansia muciniphila

Bacteria; Firmicutes; Clostridia;
57
0.004289
0.861990
0.017321
0.019449
0.981172
0.014931
0.026591
0.964361

Clostridiales; Lachnospiraceae;

Lachnospiracea_incertae_sedis; Other

Bacteria; Firmicutes;
58
0.004233
31.793703
0.000010
0.000082
0.121339
0.000303
0.002042
0.450734

Bacilli; Other; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
59
0.004200
0.372854
0.008663
0.012407
0.783473
0.003230
0.007353
0.635220

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes putredinis

Bacteria; Actinobacteria;
60
0.004159
17.534762
0.000001
0.000010
0.032427
0.000021
0.000081
0.264151

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium boum

Bacteria; Firmicutes; Clostridia;
61
0.004122
0.872797
0.004287
0.008920
0.938285
0.003742
0.012570
0.807218

Clostridiales; Lachnospiraceae;

Ruminococcus2; Other

Bacteria; Firmicutes; Clostridia;
62
0.004093
1.235607
0.002631
0.004823
0.891213
0.003251
0.006831
0.809224

Clostridiales; Lachnospiraceae;

Roseburia; Other

Bacteria; Bacteroidetes; Bacteroidia;
63
0.003996
0.012358
0.003770
0.017430
0.255230
0.000047
0.000316
0.058700

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides thetaiotaomicron

Bacteria; Bacteroidetes; Bacteroidia;
64
0.003890
0.216079
0.002446
0.004682
0.764644
0.000529
0.001052
0.517820

Bacteroidales; Odoribacteraceae;

Odoribacter;

Odoribacter splanchnicus

Bacteria; Firmicutes; Clostridia;
65
0.003819
0.257589
0.000465
0.001909
0.313808
0.000120
0.001787
0.077568

Clostridiales; Ruminococcaceae;

Neglecta; Neglecta timonensis

Bacteria; Bacteroidetes; Bacteroidia;
66
0.003787
0.534574
0.005870
0.016013
0.892259
0.003138
0.008754
0.733753

Bacteroidales; Rikenellaceae;

Alistipes; Other

Bacteria; Verrucomicrobia;
67
0.003785
0.842219
0.008451
0.033406
0.643305
0.007117
0.045593
0.549266

Verrucomicrobiae; Verrucomicrobiales;

Verrucomicrobiaceae;

Akkermansia; Other

Bacteria; Actinobacteria;
68
0.003754
2.440230
0.010770
0.034421
0.756276
0.026282
0.066768
0.867925

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae;

Bifidobacterium; Other

Bacteria; Proteobacteria;
69
0.003701
160.305085
0.000000
0.000004
0.014644
0.000049
0.000166
0.257862

Gammaproteobacteria; Enterobacterales;

Enterobacteriaceae; Cedecea; Other

Bacteria; Firmicutes; Clostridia;
70
0.003675
0.193382
0.004267
0.014123
0.426778
0.000825
0.004840
0.259958

Clostridiales; Lachnospiraceae;

Coprococcus;

Coprococcus eutactus

Bacteria; Firmicutes; Clostridia;
71
0.003648
0.857013
0.016148
0.023196
0.965481
0.013839
0.023652
0.844864

Clostridiales; Lachnospiraceae;

Anaerostipes;

Anaerostipes hadrus

Bacteria; Firmicutes; Clostridia;
72
0.003636
7.392951
0.000028
0.000117
0.142259
0.000209
0.000857
0.341719

Clostridiales; Ruminococcaceae;

Intestinimonas; Other

Bacteria; Bacteroidetes; Bacteroidia;
73
0.003635
0.403537
0.008488
0.015847
0.756276
0.003425
0.009210
0.645702

Bacteroidales; Tannerellaceae;

Parabacteroides;

Parabacteroides merdae

Bacteria; Firmicutes;
74
0.003602
0.190737
0.001388
0.005857
0.634937
0.000265
0.000947
0.387841

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Turicibacter;

Turicibacter sanguinis

Bacteria; Firmicutes; Clostridia;
75
0.003402
6.892533
0.000261
0.001295
0.320084
0.001801
0.007718
0.461216

Clostridiales; Peptostreptococcaceae;

Romboutsia; Other

Bacteria; Fusobacteria;
76
0.003364
29.489644
0.000183
0.002664
0.125523
0.005410
0.027960
0.385744

Fusobacteriia; Fusobacteriales;

Fusobacteriaceae; Fusobacterium;

Other

Bacteria; Firmicutes; Clostridia;
77
0.003349
1.898595
0.002311
0.004024
0.911088
0.004388
0.009337
0.882600

Clostridiales; Lachnospiraceae;

Anaerostipes; Other

Bacteria; Firmicutes; Bacilli;
78
0.003317
0.342737
0.003012
0.006257
0.688285
0.001032
0.003323
0.475891

Lactobacillales; Lactobacillus;

Lactobacillus;

Lactobacillus rogosae

Bacteria; Firmicutes; Negativicutes;
79
0.003164
2.557738
0.000733
0.004959
0.304393
0.001876
0.013139
0.626834

Selenomonadales; Veillonellaceae;

Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
80
0.003149
0.386643
0.000507
0.001799
0.414226
0.000196
0.001164
0.180294

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides koreensis

Bacteria; Firmicutes; Clostridia;
81
0.003135
0.622601
0.016348
0.020690
0.988494
0.010178
0.013332
0.981132

Clostridiales; Other; Other; Other

Bacteria; Firmicutes; Bacilli;
82
0.003133
2.358423
0.007021
0.016525
0.938285
0.016557
0.041320
0.966457

Lactobacillales; Streptococcaceae;

Streptococcus; Other

Bacteria; Firmicutes; Clostridia;
83
0.003126
1.147884
0.047176
0.039074
0.991632
0.054152
0.054363
0.985325

Clostridiales; Lachnospiraceae; Other; Other

Bacteria; Firmicutes; Clostridia;
84
0.003116
0.492971
0.000628
0.002760
0.642259
0.000309
0.001143
0.339623

Clostridiales; Eubacteriaceae;

Eubacterium; Other

Bacteria; Firmicutes; Clostridia;
85
0.003108
2.604901
0.000185
0.000631
0.540795
0.000482
0.002604
0.670860

Clostridiales; Ruminococcaceae;

Flavonifractor; Other

Bacteria; Firmicutes; Clostridia;
86
0.003081
0.129616
0.000107
0.000340
0.281381
0.000014
0.000074
0.085954

Clostridiales; Not Available;

Colidextribacter;

Colidextribacter massiliensis

Bacteria; Fusobacteria; Fusobacteriia;
87
0.003058
44.941541
0.000074
0.001650
0.123431
0.003326
0.018044
0.371069

Fusobacteriales; Fusobacteriaceae;

Fusobacterium;

Fusobacterium nucleatum

Archaea; Euryarchaeota; Methanobacteria;
88
0.003030
0.091235
0.005034
0.015858
0.429916
0.000459
0.004455
0.19961

Methanobacteriales; Methanobacteriaceae;

Methanobrevibacter;

Methanobrevibacter smithii

Bacteria; Firmicutes; Negativicutes;
89
0.003013
69.630050
0.000016
0.000306
0.055439
0.001107
0.006836
0.295597

Veillonellales; Veillonellaceae;

Megasphaera;

Megasphaera micronuciformis

Bacteria; Actinobacteria; Coriobacteriia;
90
0.003011
0.695938
0.000809
0.004296
0.456067
0.000563
0.003588
0.165618

Eggerthellales; Eggerthellaceae;

Adlercreutzia;

Adlercreutzia equolifaciens

Bacteria; Proteobacteria;
91
0.002951
3.229609
0.002611
0.011365
0.652720
0.008432
0.025487
0.842767

Gammaproteobacteria; Enterobacteriales;

Enterobacteriaceae; Other; Other

Bacteria; Proteobacteria;
92
0.002951
0.484266
0.004015
0.012731
0.673640
0.001944
0.007159
0.461216

Betaproteobacteria; Burkholderiales;

Sutterellaceae; Parasutterella;

Parasutterella excrementihominis

Bacteria; Firmicutes; Clostridia;
93
0.002938
0.356917
0.000292
0.040
0.543933
0.000104
0.000540
0.310273

Clostridiales; Ruminococcaceae;

Oscillibacter; Other

Bacteria; Firmicutes; Clostridia;
94
0.002903
2.271406
0.000189
0.001137
0.438285
0.000429
0.001476
0.595388

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Other

Bacteria; Firmicutes; Clostridia;
95
0.002872
1.299070
0.000891
0.003813
0.756276
0.001158
0.003329
0.706499

Clostridiales; Peptostreptococcaceae;

Other; Other

Bacteria; Firmicutes; Negativicutes;
96
0.002866
0.399205
0.007826
0.017524
0.501046
0.003124
0.014551
0.272537

Acidaminococcales; Acidaminococcaceae;

Phascolarctobacterium;

Phascolarctobacterium faecium

Bacteria; Bacteroidetes; Bacteroidia;
97
0.002837
0.609067
0.002972
0.006360
0.816946
0.001810
0.003865
0.706499

Bacteroidales; Rikenellaceae;

Alistipes; Other

Bacteria; Actinobacteria; Coriobacteriia;
98
0.002833
1.195718
0.000541
0.001754
0.474895
0.000647
0.001878
0.568134

Eggerthellales; Eggerthellaceae;

Eggerthella; Eggerthella lenta

Bacteria; Firmicutes; Erysipelotrichia;
99
0.002761
0.505132
0.000128
0.000258
0.525105
0.000065
0.000259
0.283019

Erysipelotrichales; Erysipelotrichaceae;

Holdemania;

Holdemania filiformis

Bacteria; Actinobacteria; Actinobacteria;
100
0.002732
0.428909
0.012432
0.030734
0.647490
0.005332
0.023558
0.366876

Bifidobacteriales; Bifidobacteriaceae;

Bifidobacterium;

Bifidobacterium adolescentis

IBD = Inflammatory Bowel Disease; CD = Crohn's Disease; Ctrl = Control; RFFR = Random Forest Feature Rank; # = Rank; MDA = Mean Decrease Accuracy; FC = Fold Change; M = Mean; SD = Standard Deviation; DP = Detection Prevalence;

TABLE 15

IBD (Crohn's Disease) vs IBD (Ulcerative Colitis) delineation features - (taxonomy)

Feature

(Taxonomic order: Kingdom;
FC

Phylum; Class; Order;
RFFR
CD vs
Abundance (UC)
Abundance (CD)

Family; Genus; Species)
#
MDA
UC
M
SD
DP
M
SD
DP

Bacteria; Firmicutes;
1
0.018811
0.593675
0.029101
0.045538
0.984293
0.017277
0.050587
0.882600

Clostridia; Clostridiales;

Ruminococcaceae; Other; Other

Bacteria; Firmicutes;
2
0.017743
21.742695
0.000404
0.002654
0.254799
0.008788
0.024397
0.662474

Clostridia; Clostridiales; Lachnospiraceae;

Faecalimonas;

Faecalimonas umbilicata

Bacteria; Firmicutes; Clostridia;
3
0.015550
0.288627
0.006126
0.010149
0.858639
0.001768
0.005336
0.517820

Clostridiales; Eubacteriaceae;

Eubacterium;

[Eubacterium] eligens

Bacteria; Firmicutes; Clostridia;
4
0.014209
0.433713
0.054255
0.057663
0.979058
0.023531
0.045680
0.830189

Clostridiales; Ruminococcaceae;

Faecalibacterium; Other

Bacteria; Firmicutes; Clostridia;
5
0.013744
0.126355
0.009771
0.025705
0.808028
0.001235
0.005413
0.417191

Clostridiales; Ruminococcaceae;

Faecalibacterium;

Faecalibacterium prausnitzii

Bacteria; Firmicutes; Clostridia;
6
0.011945
0.187625
0.000555
0.002178
0.738220
0.000104
0.000540
0.310273

Clostridiales; Ruminococcaceae;

Oscillibacter; Other

Bacteria; Firmicutes; Clostridia;
7
0.011905
0.384532
0.003662
0.006283
0.898778
0.001408
0.003615
0.568134

Clostridiales; Lachnospiraceae;

Roseburia;

Roseburia inulinivorans

Bacteria; Firmicutes; Clostridia;
8
0.010747
0.163329
0.004694
0.018765
0.832461
0.000767
0.003426
0.484277

Clostridiales; Ruminococcaceae;

Clostridium IV; Other

Bacteria; Firmicutes; Clostridia;
9
0.010424
7.269318
0.002139
0.010083
0.790576
0.015546
0.040155
0.903564

Clostridiales; Lachnospiraceae;

Blautia;

[Ruminococcus] gnavus

Bacteria; Firmicutes; Clostridia;
10
0.010408
0.496429
0.007864
0.016597
0.928447
0.003904
0.011642
0.710692

Clostridiales; Lachnospiraceae;

Blautia; Blautia obeum

Bacteria; Firmicutes; Bacilli;
11
0.010367
0.321841
0.003208
0.005786
0.781850
0.001032
0.003323
0.475891

Lactobacillales; Lactobacillus;

Lactobacillus;

Lactobacillus rogosae

Bacteria; Firmicutes;
12
0.009628
0.257645
0.001027
0.003252
0.741710
0.000265
0.000947
0.387841

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Turicibacter;

Turicibacter sanguinis

Bacteria; Firmicutes; Clostridia;
13
0.008948
0.600193
0.007841
0.017319
0.958115
0.004706
0.011591
0.794549

Clostridiales; Lachnospiraceae;

Blautia; Blautia faecis

Bacteria; Firmicutes; Clostridia;
14
0.008864
0.777271
0.003941
0.009222
0.895288
0.003063
0.008567
0.622642

Clostridiales; Lachnospiraceae;

Roseburia;

Roseburia intestinalis

Bacteria; Proteobacteria;
15
0.008780
4.981155
0.001693
0.007303
0.755672
0.008432
0.025487
0.842767

Gammaproteobacteria; Enterobacteriales;

Enterobacteriaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
16
0.007946
0.991634
0.012133
0.018460
0.951134
0.012031
0.022706
0.796646

Clostridiales; Lachnospiraceae;

Blautia; Blautia luti

Bacteria; Firmicutes; Clostridia;
17
0.007794
3.962467
0.000773
0.002754
0.907504
0.003062
0.006122
0.907757

Clostridiales; Lachnospiraceae;

Clostridium XIVa; Other

Bacteria; Firmicutes; Clostridia;
18
0.007637
0.612288
0.016624
0.022247
0.993019
0.010178
0.013332
0.981132

Clostridiales; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
19
0.007377
0.473113
0.006872
0.009133
0.952880
0.003251
0.006831
0.809224

Clostridiales; Lachnospiraceae;

Roseburia; Other

Bacteria; Firmicutes; Clostridia;
20
0.007300
0.187357
0.004947
0.024219
0.439791
0.000927
0.006042
0.266247

Clostridiales; Peptostreptococcaceae;

Romboutsia;

Romboutsia timonensis

Bacteria; Bacteroidetes; Bacteroidia;
21
0.006420
0.250302
0.001805
0.004505
0.685864
0.000452
0.001638
0.350105

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes obesi

Bacteria; Firmicutes; Clostridia;
22
0.006218
0.727120
0.001242
0.002653
0.856894
0.000903
0.003434
0.576520

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia hominis

Bacteria; Firmicutes; Clostridia;
23
0.006212
0.762807
0.004781
0.007170
0.876091
0.003647
0.008038
0.668'63

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus comes

Bacteria; Firmicutes; Clostridia;
24
0.005971
15.223514
0.000389
0.001687
0.364747
0.005926
0.016593
0.429769

Clostridiales; Lachnospiraceae;

Lachnoclostridium;

[Clostridium] bolteae

Bacteria; Firmicutes; Clostridia;
25
0.005950
0.734461
0.000906
0.003383
0.895288
0.000666
0.001734
0.635220

Clostridiales; Ruminococcaceae;

Ruthenibacterium;

Ruthenibacterium lactatiformans

Bacteria; Firmicutes;
26
0.005897
5.467243
0.000463
0.002414
0.436300
0.002529
0.009513
0.666667

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Erysipelatoclostridium;

Erysipelatoclostridium ramosum

Bacteria; Firmicutes; Clostridia;
27
0.005858
0.130866
0.000024
0.000061
0.446771
0.000003
0.000012
0.132075

Clostridiales; Ruminococcaceae;

Pseudoflavonifractor; Other

Bacteria; Firmicutes; Clostridia;
28
0.005730
1.119331
0.004698
0.008841
0.942408
0.005258
0.012151
0.813417

Clostridiales; Lachnospiraceae;

Dorea; Other

Bacteria; Firmicutes;
29
0.005688
0.647888
0.000100
0.000233
0.568935
0.000065
0.000259
0.283019

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Holdemania;

Holdemania filiformis

Bacteria; Firmicutes; Clostridia;
30
0.005430
0.573849
0.005298
0.012954
0.802792
0.003040
0.012851
0.563941

Clostridiales; Ruminococcaceae;

Ruminococcus; Other

Bacteria; Firmicutes;
31
0.005382
4.109247
0.000251
0.001174
0.591623
0.001031
0.006328
0.689727

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Clostridium XVIII;

Other

Bacteria; Firmicutes; Clostridia;
32
0.005097
0.575653
0.003144
0.006592
0.909250
0.001810
0.003865
0.706499

Clostridiales; Lachnospiraceae;

Coprococcus; Other

Bacteria; Firmicutes;
33
0.005057
15.261253
0.000369
0.002533
0.598604
0.005635
0.031520
0.643606

Negativicutes; Selenomonadales;

Veillonellaceae; Veillonella; Other

Bacteria; Firmicutes; Clostridia;
34
0.004997
0.740979
0.000723
0.003535
0.757417
0.000536
0.002380
0.469602

Clostridiales; Ruminococcaceae; Not

Available; [Clostridium]

leptum

Bacteria; Firmicutes; Clostridia;
35
0.004962
0.734891
0.007125
0.010254
0.888307
0.005236
0.011289
0.763103

Clostridiales; Lachnospiraceae;

Fusicatenibacter;

Fusicatenibacter saccharivorans

Bacteria; Firmicutes; Clostridia;
36
0.004956
0.944848
0.001907
0.007485
0.673647
0.001801
0.007718
0.461216

Clostridiales; Peptostreptococcaceae;

Romboutsia; Other

Bacteria; Proteobacteria;
37
0.004912
6.282996
0.003563
0.024830
0.661431
0.022385
0.072649
0.769392

Gammaproteobacteria;

Enterobacterales;

Enterobacteriaceae; Other; Other

Bacteria; Actinobacteria;
38
0.004903
1.164344
0.006563
0.018823
0.834206
0.007641
0.027702
0.601677

Coriobacteriia; Coriobacteriales;

Coriobacteriaceae; Collinsella;

Collinsella aerofaciens

Bacteria; Proteobacteria;
39
0.004898
0.518059
0.001464
0.007529
0.739965
0.000758
0.008773
0.452830

Gammaproteobacteria; Pasteurellales;

Pasteurellaceae; Haemophilus;

Haemophilus parainfluenzae

Bacteria; Firmicutes; Clostridia;
40
0.004897
0.899522
0.001518
0.002170
0.855148
0.001365
0.003206
0.679245

Clostridiales; Lachnospiraceae;

Fusicatenibacter; Other

Bacteria; Firmicutes; Clostridia;
41
0.004871
1.170455
0.003749
0.012395
0.973822
0.004388
0.009337
0.882600

Clostridiales; Lachnospiraceae;

Anaerostipes; Other

Bacteria; Firmicutes;
42
0.004864
0.586039
0.000154
0.000807
0.544503
0.000090
0.000458
0.253669

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae;

Turicibacter; Other

Bacteria; Firmicutes;
43
0.004844
0.876789
0.001875
0.002546
0.942408
0.001644
0.003814
0.863732

Other; Other; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
44
0.004739
0.680514
0.068297
0.095683
0.961606
0.046477
0.081902
0.897275

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroides vulgatus

Bacteria; Proteobacteria;
45
0.004737
4.399993
0.000769
0.003514
0.521815
0.003383
0.009955
0.624738

Gammaproteobacteria; Other; Other;

Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
46
0.004515
0.282668
0.000510
0.001284
0.544503
0.000144
0.000634
0.301887

Bacteroidales; Porphyromonadaceae;

Butyricimonas; Other

Bacteria; Bacteroidetes; Bacteroidia;
47
0.004514
0.426001
0.007366
0.024075
0.872600
0.003138
0.008754
0.733753

Bacteroidales; Rikenellaceae;

Alistipes; Other

Bacteria; Firmicutes; Clostridia;
48
0.004410
1.581438
0.019726
0.031062
0.994764
0.031195
0.061840
0.972746

Clostridiales; Lachnospiraceae;

Blautia; Other

Bacteria; Firmicutes; Clostridia;
49
0.004371
0.861389
0.062866
0.047874
0.996510
0.054152
0.054363
0.985325

Clostridiales; Lachnospiraceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
50
0.004361
0.892065
0.005688
0.011516
0.780105
0.005074
0.020778
0.582809

Clostridiales; Ruminococcaceae;

Gemmiger; Gemmiger formicilis

Bacteria; Firmicutes; Erysipelotrichia;
51
0.004327
0.844106
0.000304
0.000939
0.521815
0.000257
0.000904
0.299790

Erysipelotrichales; Erysipelotrichaceae;

Erysipelatoclostridium;

[Clostridium] spiroforme

Bacteria; Bacteroidetes; Bacteroidia;
52
0.004279
0.661422
0.034407
0.044854
0.945899
0.022757
0.044217
0.853249

Bacteroidales; Bacteroidaceae;

Bacteroides;

Bacteroide suniformis

Bacteria; Firmicutes; Clostridia;
53
0.004264
1.102315
0.006553
0.009059
0.919721
0.007223
0.013643
0.788260

Clostridiales; Lachnospiraceae;

Dorea; Dorea longicatena

Bacteria; Actinobacteria;
54
0.004179
1.310923
0.020048
0.036905
0.956370
0.026282
0.066768
0.867925

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae;

Bifidobacterium; Other

Bacteria; Firmicutes; Clostridia;
55
0.004168
7.940624
0.001148
0.009254
0.530541
0.009115
0.032504
0.570231

Clostridiales; Lachnospiraceae;

Blautia;

Blautia caecimuris

Bacteria; Bacteroidetes; Bacteroidia;
56
0.004167
0.970509
0.101366
0.098052
0.986038
0.098377
0.108029
0.958071

Bacteroidales; Bacteroidaceae;

Bacteroides; Other

Bacteria; Firmicutes; Clostridia;
57
0.004124
1.126806
0.012282
0.021109
0.963351
0.013839
0.023652
0.844864

Clostridiales; Lachnospiraceae;

Anaerostipes;

Anaerostipes hadrus

Bacteria; Firmicutes; Clostridia;
58
0.003973
2.206604
0.001696
0.003399
0.902269
0.003742
0.012570
0.807128

Clostridiales; Lachnospiraceae;

Ruminococcus2; Other

Bacteria; Bacteroidetes; Bacteroidia;
59
0.003972
0.932920
0.004877
0.008018
0.916230
0.004550
0.011480
0.763103

Bacteroidales; Porphyromonadaceae;

Parabacteroides; Other

Bacteria; Firmicutes; Negativicutes;
60
0.003915
1.457596
0.005449
0.014591
0.650960
0.007942
0.019553
0.637317

Veillonellales; Veillonellaceae;

Dialister; Dialister invisus

Bacteria; Other; Other; Other;
61
0.003783
0.505194
0.026969
0.043756
0.954625
0.013624
0.027468
0.920335

Other; Other; Other

Bacteria; Firmicutes; Clostridia;
62
0.003746
1.096624
0.001056
0.002752
0.884817
0.001158
0.003329
0.706499

Clostridiales; Peptostreptococcaceae;

Other; Other

Bacteria; Firmicutes; Clostridia;
63
0.003738
1.122557
0.013301
0.017704
0.989529
0.014931
0.026591
0.964361

Clostridiales; Lachnospiraceae;

Lachnospiracea_incertae_sedis; Other

Bacteria; Bacteroidetes; Bacteroidia;
64
0.003692
0.556329
0.007016
0.022595
0.774869
0.003903
0.014320
0.626834

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes onderdonkii

Bacteria; Bacteroidetes; Bacteroidia;
65
0.003691
0.440683
0.001199
0.002404
0.766143
0.000529
0.001052
0.517820

Bacteroidales; Odoribacteraceae;

Odoribacter; Odoribacter splanchnicus

Bacteria; Firmicutes; Clostridia;
66
0.003686
0.913324
0.000561
0.001490
0.582897
0.000512
0.002143
0.327044

Clostridiales; Ruminococcaceae;

Gemmiger; Other

Bacteria; Firmicutes;
67
0.003676
0.185996
0.000649
0.006125
0.520070
0.000121
0.000810
0.276730

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae; Other; Other

Bacteria; Firmicutes; Clostridia;
68
0.003673
0.217265
0.000049
0.000144
0.380454
0.000011
0.000049
0.117400

Clostridiales; Clostridiales

Family XIII. Incertae Sedis;

Ihubacter; Ihubacter massiliensis

Bacteria; Bacteroidetes;
69
0.003672
0.580127
0.007912
0.016860
0.858639
0.004590
0.013305
0.704403

Bacteroidia; Bacteroidales;

Bacteroidaceae; Bacteroides;

Bacteroides caccae

Bacteria; Firmicutes; Clostridia;
70
0.003665
0.448301
0.000467
0.001038
0.565445
0.000209
0.000857
0.341719

Clostridiales; Ruminococcaceae;

Intestinimonas; Other

Bacteria; Firmicutes; Clostridia;
71
0.003657
3.249400
0.000111
0.000445
0.483421
0.000359
0.001053
0.534591

Clostridiales; Lachnospiraceae;

Lachnoclostridium;

[Clostridium] aldenense

Bacteria; Firmicutes; Clostridia;
72
0.003640
0.331898
0.000546
0.001248
0.333333
0.000181
0.000969
0.174004

Clostridiales; Lachnospiraceae;

Coprococcus; Coprococcus catus

Bacteria; Bacteroidetes; Bacteroidia;
73
0.003625
0.765360
0.007358
0.023955
0.806283
0.005632
0.017336
0.668763

Bacteroidales; Tannerellaceae;

Parabacteroides;

Parabacteroides distasonis

Bacteria; Firmicutes; Clostridia;
74
0.003556
0.256160
0.000067
0.000156
0.485166
0.000017
0.000079
0.186583

Clostridiales; Ruminococcaceae;

Pseudoflavonifractor;

Pseudoflavonifractor capillosus

Bacteria; Firmicutes; Clostridia;
75
0.003548
0.213138
0.001499
0.004240
0.507853
0.000320
0.001300
0.243187

Clostridiales; Ruminococcaceae;

Ruminococcus;

Ruminococcus callidus

Bacteria; Fusobacteria; Fusobacteriia;
76
0.003532
39.574321
0.000137
0.001627
0.247818
0.005410
0.027960
0.385744

Fusobacteriales; Fusobacteriaceae;

Fusobacterium; Other

Bacteria; Proteobacteria;
77
0.003513
4.627845
0.007603
0.034601
0.530541
0.035184
0.110490
0.547170

Gammaproteobacteria; Enterobacterales;

Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
78
0.003466
0.451673
0.007151
0.011051
0.792321
0.003230
0.007353
0.635220

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes putredinis

Bacteria; Firmicutes; Clostridia;
79
0.003367
0.534609
0.000043
0.000082
0.589878
0.000023
0.000071
0.400419

Other; Other; Other; Other

Bacteria; Firmicutes; Clostridia;
80
0.003294
2.150444
0.000204
0.001014
0.593368
0.000439
0.001235
0.482180

Clostridiales; Lachnospiraceae;

Lachnoclostridium; [Clostridium]

glycyrrhizinilyticum

Bacteria; Firmicutes; Clostridia;
81
0.003279
0.725527
0.000057
0.000204
0.462478
0.000041
0.000195
0.209644

Clostridiales; Not Available;

Intestinimonas;

Intestinimonas butyriciproducens

Bacteria; Firmicutes; Clostridia;
82
0.003270
0.947557
0.003180
0.008982
0.766143
0.003013
0.010184
0.597484

Clostridiales; Ruminococcaceae;

Ruminococcus;

Ruminococcus faecis

Bacteria; Firmicutes; Clostridia;
83
0.003242
0.626182
0.002427
0.006841
0.413613
0.001520
0.010646
0.257862

Clostridiales; Lachnospiraceae;

Roseburia; Roseburia faecis

Bacteria; Firmicutes; Clostridia;
84
0.003234
1.218792
0.000396
0.001292
0.815009
0.000482
0.002604
0.670860

Clostridiales; Ruminococcaceae;

Flavonifractor; Other

Bacteria; Firmicutes; Bacilli;
85
0.003186
1.563053
0.010593
0.027852
0.996510
0.016557
0.041320
0.966457

Lactobacillales; Streptococcaceae;

Streptococcus; Other

Bacteria; Bacteroidetes; Bacteroidia;
86
0.003178
0.334760
0.001568
0.003304
0.657941
0.000525
0.001528
0.452830

Bacteroidales; Rikenellaceae;

Alistipes; Alistipes shahii

Bacteria; Firmicutes; Clostridia;
87
0.003173
1.158885
0.001138
0.003845
0.886562
0.001319
0.003364
0.756813

Clostridiales; Ruminococcaceae;

Flavonifractor;

Flavonifractor plautii

Bacteria; Firmicutes; Clostridia;
88
0.003165
0.775393
0.000399
0.002169
0.539267
0.000309
0.001143
0.339623

Clostridiales; Eubacteriaceae;

Eubacterium; Other

Bacteria; Firmicutes; Clostridia;
89
0.003147
0.870148
0.001917
0.008278
0.783595
0.001668
0.017166
0.555556

Clostridiales; Clostridiaceae;

Clostridium; Other

Bacteria; Firmicutes; Erysipelotrichia;
90
0.003146
0.421941
0.000216
0.001993
0.408377
0.000091
0.000704
0.169811

Erysipelotrichales; Erysipelotrichaceae;

Massilimicrobiota;

Massilimicrobiota timonensis

Bacteria; Actinobacteria;
91
0.003125
0.324292
0.016442
0.046861
0.406632
0.005332
0.023558
0.366876

Actinobacteria; Bifidobacteriales;

Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium adolescentis

Archaea; Euryarchaeota; Methanobacteria;
92
0.003113
0.139399
0.001241
0.011593
0.361257
0.000173
0.001805
0.146751

Methanobacteriales; Methanobacteriaceae;

Methanobrevibacter; Other

Bacteria; Firmicutes; Clostridia;
93
0.003103
1.398687
0.000307
0.001139
0.687609
0.000429
0.001476
0.595388

Clostridiales; Peptostreptococcaceae;

Intestinibacter; Other

Bacteria; Actinobacteria;
94
0.003044
1.207493
0.000536
0.002138
0.687609
0.000647
0.001878
0.568134

Coriobacteriia; Eggerthellales;

Eggerthellaceae;

Eggerthella;

Eggerthella lenta

Bacteria; Firmicutes; Clostridia;
95
0.003018
0.828759
0.000042
0.000161
0.507853
0.000034
0.000163
0.295597

Clostridiales; Ruminococcaceae;

Anaerotruncus;

Anaerotruncus colihominis

Bacteria; Firmicutes; Negativicutes;
96
0.002994
0.674143
0.003059
0.010139
0.670157
0.002062
0.005998
0.582809

Selenomonadales; Veillonellaceae;

Dialister; Other

Bacteria; Bacteroidetes; Bacteroidia;
97
0.002985
0.547289
0.000237
0.000578
0.617801
0.000130
0.000592
0.383648

Bacteroidales; Porphyromonadaceae;

Odoribacter; Other

Bacteria; Fusobacteria;
98
0.002981
16.117410
0.000206
0.002672
0.172775
0.003326
0.018044
0.371069

Fusobacteriia; Fusobacteriales;

Fusobacteriaceae; Fusobacterium;

Fusobacterium nucleatum

Bacteria; Firmicutes; Clostridia;
99
0.002916
0.589134
0.000243
0.002463
0.527051
0.000143
0.000973
0.243187

Clostridiales; Lachnospiraceae;

Eisenbergiella;

Eisenbergiella tayi

Bacteria; Actinobacteria;
100
0.002882
0.727827
0.004403
0.012714
0.762653
0.003205
0.009131
0.584906

Actinobacteria; Coriobacteriales;

Coriobacteriaceae;

Collinsella; Other

IBD = Inflammatory Bowel Disease; CD = Crohn's Disease; UC = Ulcerative Colitis; Ctrl = Control; RFFR = Random Forest Feature Rank; # = Rank; MDA = Mean Decrease Accuracy; FC = Fold Change; M = Mean; SD = Standard Deviation; DP = Detection Prevalence;

TABLE 16

Pediatric CDI vs Pediatric Control delineation features - (taxonomy)

Feature
FC

(Taxonomic order: Kingdom;
CDI

Phylum; Class; Order;
RFFR
vs
Abundance (P-CDI)
Abundance (P-Ctrl)

Family; Genus)
#
MDA
Ctrl
M
SD
DP
M
SD
DP

Bacteria; Firmicutes; Clostridia;
1
0.050880
0.211185
0.009346
0.037604
0.337423
0.044255
0.047610
0.989305

Clostridiales; Ruminococcaceae;

Faecalibacterium

Bacteria; Firmicutes; Clostridia;
2
0.046493
0.380728
0.007797
0.024579
0.472393
0.020480
0.021792
0.994652

Clostridiales; Ruminococcaceae;

Other

Bacteria; Bacteroidetes; Bacteroidia;
3
0.046428
0.161007
0.003392
0.013174
0.306748
0.021069
0.039105
0.973262

Bacteroidales; Porphyromonadaceae;

Parabacteroides

Bacteria; Bacteroidetes; Bacteroidia;
4
0.044322
0.132454
0.010516
0.078929
0.300613
0.079396
0.073106
0.973262

Bacteroidales; Rikenellaceae;

Alistipes

Bacteria; Firmicutes; Clostridia;
5
0.041510
0.076145
0.001182
0.006649
0.177914
0.015519
0.022756
0.935829

Clostridiales; Lachnospiraceae;

[Eubacterium] rectale group

Bacteria; Firmicutes; Clostridia;
6
0.038082
0.063152
0.000387
0.002200
0.122699
0.006126
0.009801
0.903743

Clostridiales; Lachnospiraceae;

Coprococcus

Bacteria; Firmicutes; Clostridia;
7
0.035840
0.151565
0.001147
0.006662
0.245399
0.007567
0.009631
0.962567

Clostridiales; Lachnospiraceae;

Roseburia

Bacteria; Firmicutes; Bacilli;
8
0.035642
842.982629
0.007133
0.018683
0.760736
0.000008
0.000087
0.032086

Lactobacillales; Other; Other

Bacteria; Firmicutes; Clostridia;
9
0.035317
0.812626
0.004717
0.031952
0.177914
0.005805
0.008967
0.946524

Clostridiales; Lachnospiraceae;

Dorea

Bacteria; Firmicutes; Clostridia;
10
0.032443
1.106990
0.004086
0.015414
0.202454
0.003691
0.003880
0.962567

Clostridiales; Lachnospiraceae;

Fusicatenibacter

Bacteria; Bacteroidetes; Bacteroidia;
11
0.030484
0.220839
0.094242
0.201046
0.779141
0.426747
0.201042
0.989305

Bacteroidales; Bacteroidaceae;

Bacteroides

Bacteria; Bacteroidetes; Bacteroidia;
12
0.028713
0.001090
0.000005
0.000042
0.042945
0.004637
0.007784
0.737968

Bacteroidales; Porphyromon

adaceae; Odoribacter

Bacteria; Firmicutes; Clostridia;
13
0.027362
0.666573
0.001482
0.007581
0.208589
0.002224
0.002765
0.914439

Clostridiales; Lachnospiraceae;

Ruminococcus2

Bacteria; Firmicutes; Clostridia;
14
0.025846
#DIV/0!
0.007821
0.031595
0.693252
0.000000
0.000000
0.000000

Clostridiales; Peptostreptococcaceae;

Clostridioides

Bacteria; Firmicutes; Bacilli;
15
0.025100
181.461752
0.110940
0.208194
0.791411
0.000611
0.005278
0.074866

Lactobacillales; Enterococcaceae;

Enterococcus

Bacteria; Firmicutes; Negativicutes;
16
0.023294
0.036064
0.001595
0.012929
0.171779
0.044240
0.074564
0.855615

Selenomonadales; Veillonellaceae;

Dialister

Bacteria; Firmicutes; Clostridia;
17
0.020923
1.049341
0.012709
0.032446
0.509202
0.012112
0.011581
0.983957

Clostridiales; Lachnospiraceae;

Lachnospiracea
_—
incertae
_—
sedis

Bacteria; Bacteroidetes; Bacteroidia;
18
0.018514
0.484277
0.007163
0.038013
0.374233
0.014791
0.022495
0.887701

Bacteroidales; Tannerellaceae;

Parabacteroides

Bacteria; Actinobacteria;
19
0.016877
69.303670
0.006208
0.014624
0.582822
0.000090
0.000324
0.165775

Coriobacteriia; Eggerthellales;

Eggerthellaceae; Eggerthella

Bacteria; Firmicutes; Negativicutes;
20
0.016254
0.124109
0.004752
0.031692
0.220859
0.038293
0.062985
0.850267

Veillonellales; Veillonellaceae;

Dialister

Bacteria; Firmicutes; Erysipelotrichia;
21
0.016027
68.095014
0.032024
0.068740
0.809816
0.000470
0.000938
0.524064

Erysipelotrichales;

Erysipelotrichaceae;

Erysipelatoclostridium

Bacteria; Firmicutes; Clostridia;
22
0.015604
0.038942
0.000123
0.001172
0.116564
0.003148
0.006829
0.802139

Clostridiales; Ruminococcaceae;

Clostridium IV

Bacteria; Firmicutes; Clostridia;
23
0.015165
0.401895
0.012298
0.026170
0.791411
0.030600
0.044063
1.000000

Clostridiales; Lachnospiraceae;

Other

Bacteria; Firmicutes; Clostridia;
24
0.015099
46.107430
0.015279
0.045057
0.711656
0.000331
0.000737
0.449198

Clostridiales; Lachnospiraceae;

Lachnoclostridium

Bacteria; Firmicutes; Clostridia;
25
0.013587
0.250701
0.004879
0.018782
0.269939
0.019461
0.046161
0.871658

Clostridiales; Ruminococcaceae;

Ruminococcus

Bacteria; Firmicutes; Clostridia;
26
0.012836
0.719791
0.005329
0.043906
0.171779
0.007404
0.014245
0.754011

Clostridiales; Ruminococcaceae;

Gemmiger

Bacteria; Bacteroidetes; Bacteroidia;
27
0.012553
0.256510
0.001120
0.006767
0.141104
0.004364
0.007279
0.759358

Bacteroidales; Odoribacteraceae;

Odoribacter

Bacteria; Firmicutes; Bacilli; Other;
28
0.011115
1597.768886
0.000398
0.000891
0.503067
0.000000
0.000003
0.005348

Other; Other

Bacteria; Bacteroidetes; Bacteroidia;
29
0.008453
0.038567
0.000023
0.000204
0.110429
0.000587
0.002368
0.524064

Bacteroidales; Other; Other

Bacteria; Actinobacteria;
30
0.008310
0.036855
0.000050
0.000573
0.061350
0.001367
0.003301
0.545455

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Collinsella

Bacteria; Proteobacteria; Gamma
31
0.008145
35.248715
0.049688
0.127352
0.730061
0.001410
0.012707
0.278075

proteobacteria; Enterobacterales;

Enterobacteriaceae; Escherichia

Bacteria; Firmicutes; Bacilli;
32
0.007536
#DIV/0!
0.004390
0.026302
0.509202
0.000000
0.000000
0.000000

Lactobacillales; Enterococcaceae;

Other

Bacteria; Actinobacteria;
33
0.007293
0.091814
0.000043
0.000440
0.036810
0.000463
0.001174
0.491979

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Other

Bacteria; Proteobacteria; Beta-
34
0.007185
0.331350
0.001844
0.009368
0.171779
0.005565
0.015103
0.663102

proteobacteria;Burkholderiales;

Sutterellaceae; Parasutterella

Bacteria; Proteobacteria; Gamma
35
0.007121
11.015887
0.045087
0.151893
0.840491
0.004093
0.023097
0.315508

proteobacteria; Enterobacteriales;

Enterobacteriaceae; Other

Bacteria; Verrucomicrobia;
36
0.007052
0.446210
0.011846
0.083730
0.226994
0.026547
0.072308
0.711230

Verrucomicrobiae;

Verrucomicrobiales;

Verrucomicrobiaceae; Akkermansia

Bacteria; Firmicutes; Clostridia;
37
0.006994
4.046665
0.091226
0.150407
0.889571
0.022543
0.027331
0.994652

Clostridiales; Lachnospiraceae;

Blautia

Bacteria; Firmicutes; Bacilli;
38
0.006639
17.138984
0.073805
0.133505
0.944785
0.004306
0.010976
0.860963

Lactobacillales; Streptococcaceae;

Streptococcus

Bacteria; Actinobacteria;
39
0.006356
112.944476
0.006408
0.030049
0.613497
0.000057
0.000175
0.192513

Actinobacteria; Actinomycetales;

Actinomycetaceae; Schaalia

Bacteria; Firmicutes; Clostridia;
40
0.006337
4.552891
0.020449
0.063547
0.619632
0.004492
0.007820
0.925134

Clostridiales; Lachnospiraceae;

Anaerostipes

Bacteria; Firmicutes; Clostridia;
41
0.006095
0.604950
0.005139
0.016770
0.693252
0.008495
0.016000
0.978610

Clostridiales; Other; Other

Bacteria; Firmicutes; Clostridia;
42
0.004653
102.734823
0.005096
0.026154
0.417178
0.000050
0.000214
0.117647

Clostridiales; Clostridiaceae;

Hungatella

Bacteria; Firmicutes; Clostridia;
43
0.004264
0.441805
0.000411
0.002207
0.061350
0.000930
0.002675
0.529412

Clostridiales; Ruminococcaceae;

Agathobaculum

Bacteria; Firmicutes; Clostridia;
44
0.003724
17.428965
0.012477
0.035348
0.638037
0.000716
0.001967
0.459893

Clostridiales; Clostridiaceae;

Clostridium

Bacteria; Actinobacteria;
45
0.003601
267.323021
0.000941
0.006184
0.355828
0.000004
0.000033
0.016043

Actinobacteria; Corynebacteriales;

Corynebacteriaceae;

Corynebacterium

Bacteria; Firmicutes; Negativicutes;
46
0.003506
22.237996
0.014643
0.045727
0.705521
0.000658
0.001406
0.513369

Veillonellales; Veillonellaceae;

Veillonella

Bacteria; Actinobacteria;
47
0.003324
38.160755
0.004754
0.018003
0.644172
0.000125
0.000392
0.294118

Actinobacteria; Actinomycetales;

Actinomycetaceae; Actinomyces

Bacteria; Firmicutes; Clostridia;
48
0.002826
0.179629
0.000234
0.001024
0.196319
0.001302
0.003644
0.657754

Clostridiales; Ruminococcaceae;

[Clostridium] leptum group

Bacteria; Fusobacteria; Fusobacteriia;
49
0.002721
604.269814
0.002345
0.012720
0.269939
0.000004
0.000042
0.010695

Fusobacteriales; Fusobacteriaceae;

Fusobacterium

Bacteria; Firmicutes; Erysipelotrichia;
50
0.002687
65.046792
0.007263
0.039105
0.214724
0.000112
0.000571
0.101604

Erysipelotrichales;

Erysipelotrichaceae;

Longicatena

Bacteria; Firmicutes; Clostridia;
51
0.002184
16.416961
0.005463
0.025266
0.607362
0.000333
0.000679
0.475936

Clostridiales; Lachnospiraceae;

Clostridium XIVa

Bacteria; Firmicutes; Clostridia;
52
0.002127
58.218456
0.006237
0.029087
0.312883
0.000107
0.000453
0.192513

Clostridiales; Lachnospiraceae;

Eisenbergiella

Bacteria; Firmicutes; Bacilli;
53
0.002034
3.492105
0.036792
0.134244
0.754601
0.010536
0.043024
0.470588

Lactobacillales; Lactobacillus;

Lactobacillus

Bacteria; Firmicutes; Clostridia;
54
0.002029
10.675751
0.012375
0.031853
0.625767
0.001159
0.003078
0.609626

Clostridiales; Peptostreptococcaceae;

Intestinibacter

Bacteria; Proteobacteria; Gamma
55
0.002012
1804.472700
0.012123
0.075931
0.368098
0.000007
0.000040
0.037433

proteobacteria; Enterobacterales;

Enterobacteriaceae;

Citrobacter

Bacteria; Firmicutes; Clostridia;
56
0.001976
4.588196
0.007839
0.041596
0.349693
0.001709
0.003331
0.770053

Clostridiales; Eubacteriaceae;

Eubacterium

Bacteria; Firmicutes; Tissierellia;
57
0.001962
1208.452523
0.001809
0.016334
0.226994
0.000001
0.000015
0.010695

Tissierellales; Peptoniphilaceae;

Finegoldia

Bacteria; Firmicutes; Bacilli;
58
0.001960
26.900915
0.001663
0.005044
0.552147
0.000062
0.000144
0.245989

Lactobacillales; Carnobacteriaceae;

Granulicatella

Bacteria; Proteobacteria; Gamma
59
0.001871
0.000000
0.000000
0.000000
0.000000
0.000033
0.000323
0.021390

proteobacteria; Enterobacterales;

Enterobacteriaceae; Shimwellia

Bacteria; Firmicutes; Negativicutes;
60
0.001847
0.029768
0.000062
0.00030
0.079755
0.002093
0.006544
0.262032

Selenomonadales;

Acidaminococcaceae;

Phascolarctobacterium

Bacteria; Firmicutes; Bacilli;
61
0.001813
0.177072
0.000428
0.003028
0.251534
0.002417
0.019002
0.128342

Bacillales; Staphylococcaceae;

Staphylococcus

Bacteria; Actinobacteria;
62
0.001787
6.029397
0.000179
0.000538
0.282209
0.000030
0.000119
0.096257

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Eggerthella

Bacteria; Proteobacteria; Beta-
63
0.001776
0.733855
0.002627
0.028696
0.110429
0.003579
0.012621
0.497326

proteobacteria; Burkholderiales;

Sutterellaceae; Sutterella

Bacteria; Firmicutes; Clostridia;
64
0.001762
0.000000
0.000000
0.000000
0.000000
0.000107
0.000304
0.251337

Clostridiales; Lachnospiraceae;

Anaerobutyricum

Bacteria; Firmicutes; Clostridia;
65
0.001728
569.534883
0.001567
0.010485
0.239264
0.000003
0.000024
0.016043

Clostridiales; Peptostreptococcaceae;

Peptostreptococcus

Bacteria; Firmicutes; Erysipelotrichia;
66
0.001727
0.119789
0.000042
0.000214
0.085890
0.000347
0.000870
0.422460

Erysipelotrichales;

Erysipelotrichaceae;

Holdemania

Bacteria; Firmicutes; Clostridia;
67
0.001622
660.751733
0.000755
0.003002
0.208589
0.000001
0.000009
0.016043

Clostridiales; Sellimonas;

Drancourtella

massiliensis

Bacteria; Firmicutes; Clostridia;
68
0.001617
0.166528
0.000167
0.000839
0.085890
0.001004
0.002606
0.385027

Clostridiales; Not

Available; Monoglobus

Bacteria; Firmicutes; Clostridia;
69
0.001614
1.481333
0.002166
0.008636
0.484663
0.001462
0.004526
0.572193

Clostridiales; Ruminococcaceae;

Flavonifractor

Bacteria; Bacteroidetes; Bacteroidia;
70
0.001608
0.078579
0.000601
0.007335
0.042945
0.007652
0.017223
0.310160

Bacteroidales; Porphyromonadaceae;

Barnesiella

Bacteria; Firmicutes; Tissierellia;
71
0.001557
180.170395
0.000727
0.004641
0.214724
0.000004
0.000026
0.026738

Tissierellales; Peptoniphilaceae;

Anaerococcus

Bacteria; Firmicutes; Bacilli;
72
0.001489
21.003684
0.001385
0.006230
0.441718
0.000066
0.000188
0.181818

Bacillales; Not Available;

Gemella

Bacteria; Proteobacteria; Gamma
73
0.001480
1.991330
0.002302
0.021488
0.085890
0.001156
0.008229
0.171123

proteobacteria; Enterobacterales;

Enterobacteriaceae; Enterobacter

Bacteria; Proteobacteria; Gamma
74
0.001461
0.081754
0.000024
0.000123
0.116564
0.000290
0.001314
0.224599

proteobacteria; Pasteurellales;

Pasteurellaceae; Other

Bacteria; Firmicutes; Clostridia;
75
0.001443
17.489209
0.000779
0.004837
0.104294
0.000045
0.000214
0.085561

Clostridiales; Lachnospiraceae;

Sellimonas

Bacteria; Firmicutes; Erysipelotrichia;
76
0.001408
3.234637
0.003352
0.014227
0.306748
0.001036
0.002439
0.588235

Erysipelotrichales;

Erysipelotrichaceae;

Turicibacter

Bacteria; Proteobacteria; Gamma
77
0.001398
2.374310
0.007749
0.038398
0.404908
0.003264
0.019506
0.165775

proteobacteria; Enterobacterales;

Enterobacteriaceae; Klebsiella

Bacteria; Firmicutes; Clostridia;
78
0.001395
1.756974
0.005762
0.015594
0.638037
0.003280
0.007006
0.732620

Clostridiales; Peptostreptococcaceae;

Other

Bacteria; Firmicutes; Tissierellia;
79
0.001352
278.158721
0.003153
0.019435
0.196319
0.000011
0.000061
0.048128

Tissierellales; Peptoniphilaceae;

Peptoniphilus

Bacteria; Proteobacteria; Gamma
80
0.001339
#DIV/0!
0.000009
0.000026
0.159509
0.000000
0.000000
0.000000

proteobacteria; Pasteurellales;

Pasteurellaceae; Rodentibacter

Bacteria; Firmicutes; Other; Other;
81
0.001270
0.284414
0.000051
0.000146
0.306748
0.000180
0.000400
0.395722

Other; Other

Bacteria; Firmicutes; Clostridia;
82
0.001229
0.016839
0.000003
0.000024
0.030675
0.000206
0.001044
0.208556

Clostridiales; Clostridiaceae

1; Other

Bacteria; Firmicutes; Clostridia;
83
0.001194
5.274983
0.006312
0.019947
0.484663
0.001197
0.002673
0.604278

Clostridiales; Clostridiaceae

1; Clostridium sensu stricto

Bacteria; Firmicutes; Clostridia;
84
0.001174
1586439768
0.006459
0.042897
0.233129
0.000004
0.000039
0.016043

Clostridiales; Lachnospiraceae;

Faecalimonas

Bacteria; Proteobacteria; Gamma
85
0.001171
23.242487
0.000064
0.000244
0.226994
0.000003
0.000037
0.005348

proteobacteria; Other; Other; Other

Bacteria; Verrucomicrobia;
86
0.001149
2.407228
0.009958
0.079860
0.276074
0.004137
0.015689
0.385027

Verrucomicrobiae;

Verrucomicrobiales;

Akkermansiaceae; Akkermansia

Bacteria; Firmicutes; Erysipelotrichia;
87
0.001103
3.096942
0.003034
0.007442
0.552147
0.000980
0.001523
0.711230

Erysipelotrichales;

Erysipelotrichaceae;

Clostridium XVIII

Bacteria; Firmicutes; Clostridia;
88
0.001101
11.605259
0.000059
0.000234
0.104294
0.000005
0.000043
0.021390

Clostridiales; Clostridiaceae;

Lactonifactor

Bacteria; Actinobacteria;
89
0.001080
1126.206676
0.002163
0.020292
0.251534
0.000002
0.000016
0.016043

Actinobacteria; Micrococcales;

Micrococcaceae; Rothia

Bacteria; Other; Other; Other; Other;
90
0.001057
0.431657
0.000114
0.000520
0.343558
0.000263
0.000686
0.465241

Other

Bacteria; Firmicutes; Clostridia;
91
0.001042
0.534968
0.000068
0.000308
0.098160
0.000127
0.000391
0.278075

Clostridiales; Catabacteriaceae;

Catabacter

Bacteria; Firmicutes; Bacilli;
92
0.001035
9.743179
0.001311
0.013830
0.073620
0.000135
0.000962
0.064171

Lactobacillales; Leuconostocaceae;

Weissella

Bacteria; Firmicutes; Clostridia;
93
0.001017
11.972136
0.003162
0.015299
0.349693
0.000264
0.000733
0.240642

Clostridiales; Peptostreptococcaceae;

Terrisporobacter

Bacteria; Bacteroidetes; Bacteroidia;
94
0.001012
0.002759
0.000000
0.000003
0.006135
0.000076
0.000234
0.203209

Bacteroidales; Rikenellaceae;

Other

Bacteria; Firmicutes; Clostridia;
95
0.001005
8.367135
0.017548
0.063530
0.490798
0.002097
0.006178
0.534759

Clostridiales; Peptostreptococcaceae;

Romboutsia

Bacteria; Bacteroidetes; Bacteroidia;
96
0.000991
0.359705
0.000048
0.000225
0.085890
0.000134
0.000555
0.155080

Bacteroidales; Porphyromonadaceae;

Porphyromonas

Bacteria; Firmicutes; Clostridia;
97
0.000961
#DIV/0!
0.001633
0.009267
0.208589
0.000000
0.000000
0.000000

Clostridiales; Peptostreptococcaceae;

Clostridium XI

Bacteria; Actinobacteria;
98
0.000960
43.088143
0.000851
0.004649
0.226994
0.000020
0.000079
0.080214

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Atopobium

Bacteria; Actinobacteria;
99
0.000944
75.195507
0.000616
0.002338
0.251534
0.000008
0.000036
0.058824

Coriobacteriia; Coriobacteriales;

Atopobiaceae; Atopobium

Bacteria; Firmicutes; Clostridia;
100
0.000915
#DIV/0!
0.000072
0.000538
0.092025
0.000000
0.000000
0.000000

Clostridiales; Ruminococcaceae;

Anaeromassilibacillus

CDI = Clostridiodes difficile Infection;

Ctrl = Control;

P- = Pediatric;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 17

Pediatric CDI vs Adult CDI delineation features - (taxonomy)

Feature
FC

(Taxonomic order: Kingdom;
CDI
Abundance
Abundance

Phylum; Class; Order;
RFFR
vs
(P-CDI)
(A-CDI)

Family; Genus)
#
MDA
CDI
M
SD
DP
M
SD
DP

Bacteria; Proteobacteria; Gamma
1
0.037538
151.080905
0.000000
0.000002
0.000954
0.000009
0.000026
0.159509

proteobacteria; Pasteurellales;

Pasteurellaceae; Rodentibacter

Bacteria; Proteobacteria;
2
0.025568
0.712858
0.000016
0.000387
0.006679
0.000012
0.000050
0.159509

Betaproteobacteria; Burkholderiales;

Sutterellaceae; Turicimonas

Bacteria; Actinobacteria;
3
0.018837
11.206714
0.000572
0.004184
0.394084
0.006408
0.030049
0.613497

Actinobacteria; Actinomycetales;

Actinomycetaceae; Schaalia

Bacteria; Firmicutes; Clostridia;
4
0.017826
11.661045
0.001505
0.008536
0.330153
0.017548
0.063530
0.490798

Clostridiales; Peptostreptococcaceae;

Romboutsia

Bacteria; Bacteroidetes; Bacteroidia;
5
0.017381
0.537135
0.175453
0.210442
0.922710
0.094242
0.201046
0.779141

Bacteroidales; Bacteroidaceae;

Bacteroides

Bacteria; Firmicutes; Clostridia;
6
0.017077
1.794149
0.050846
0.086265
0.885496
0.091226
0.150407
0.889571

Clostridiales; Lachnospiraceae;

Blautia

Bacteria; Firmicutes; Bacilli;
7
0.016274
37.669569
0.000124
0.001927
0.083969
0.004680
0.032716
0.233129

Lactobacillales; Aerococcaceae;

Abiotrophia

Bacteria; Firmicutes;
8
0.015806
2.407213
0.013303
0.033415
0.801527
0.032024
0.068740
0.809816

Erysipelotrichia; Erysipelotrichales;

Erysipelotrichaceae;

Erysipelatoclostridium

Bacteria; Firmicutes; Clostridia;
9
0.015389
4.414909
0.004632
0.014406
0.599237
0.020449
0.063547
0.619632

Clostridiales; Lachnospiraceae;

Anaerostipes

Bacteria; Firmicutes; Clostridia;
10
0.014791
0.531764
0.010273
0.025945
0.808206
0.005463
0.025266
0.607362

Clostridiales; Lachnospiraceae;

Clostridium XIVa

Bacteria; Actinobacteria;
11
0.014684
3.174081
0.001956
0.005797
0.514313
0.006208
0.014624
0.582822

Coriobacteriia; Eggerthellales;

Eggerthellaceae; Eggerthella

Bacteria; Firmicutes; Bacilli;
12
0.012805
2.205140
0.033469
0.082817
0.907443
0.073805
0.133505
0.944785

Lactobacillales; Streptococcaceae;

Streptococcus

Bacteria; Firmicutes; Bacilli;
13
0.012788
103.234362
0.000008
0.000222
0.006679
0.000865
0.006796
0.110429

Lactobacillales; Aerococcaceae;

Other

Bacteria; Bacteroidetes; Bacteroidia;
14
0.011740
0.223093
0.015206
0.045358
0.614504
0.003392
0.013174
0.306748

Bacteroidales; Porphyromonadaceae;

Parabacteroides

Bacteria; Firmicutes; Clostridia;
15
0.011507
1.561592
0.008139
0.021296
0.667939
0.012709
0.032446
0.509202

Clostridiales; Lachnospiraceae;

Lachnospiracea
_—
incertae
_—
sedis

Bacteria; Proteobacteria; Gamma
16
0.011411
0.634772
0.071029
0.140941
0.880725
0.045087
0.151893
0.840491

proteobacteria; Enterobacteriales;

Enterobacteriaceae; Other

Bacteria; Actinobacteria;
17
0.011042
4.850911
0.000980
0.003992
0.566794
0.004754
0.018003
0.644172

Actinobacteria; Actinomycetales;

Actinomycetaceae; Actinomyces

Bacteria; Firmicutes; Clostridia;
18
0.010988
2.639563
0.004688
0.019981
0.477099
0.012375
0.031853
0.625767

Clostridiales; Peptostreptococcaceae;

Intestinibacter

Bacteria; Proteobacteria; Gamma
19
0.010954
0.330765
0.023428
0.075459
0.644084
0.007749
0.038398
0.404908

proteobacteria; Enterobacterales;

Enterobacteriaceae; Klebsiella

Bacteria; Candidatus
20
0.010741
8.205493
0.000073
0.001179
0.065840
0.000595
0.004970
0.184049

Saccharibacteria;

Saccharibacteria_genera_incertae_sedis;

Other; Other; Other

Bacteria; Firmicutes; Erysipelotrichia;
21
0.010622
#DIV/0!
0.000000
0.000000
0.000000
0.000002
0.000009
0.061350

Erysipelotrichales; Erysipelotrichaceae;

Faecalibaculum

Bacteria; Proteobacteria; Gamma
22
0.010398
1.613390
0.030797
0.091460
0.675573
0.049688
0.127352
0.730061

proteobacteria; Enterobacterales;

Enterobacteriaceae; Escherichia

Bacteria; Firmicutes; Bacilli; Bacillales;
23
0.010168
3.224048
0.000430
0.003268
0.271947
0.001385
0.006230
0.441718

Not Available; Gemella

Bacteria; Firmicutes; Clostridia;
24
0.010037
0.437115
0.003736
0.020683
0.507634
0.001633
0.009267
0.208589

Clostridiales; Peptostreptococcaceae;

Clostridium XI

Bacteria; Deferribacteres;
25
0.009997
17.294619
0.000000
0.000005
0.001908
0.000003
0.000013
0.073620

Deferribacteres; Deferribacterales;

Deferribacteraceae; Mucispirillum

Bacteria; Firmicutes; Bacilli;
26
0.009757
0.880286
0.041795
0.118159
0.806298
0.036792
0.134244
0.754601

Lactobacillales; Lactobacilloae;

Lactobacillus

Bacteria; Firmicutes; Bacilli;
27
0.009695
3.193299
0.000521
0.003417
0.382634
0.001663
0.005044
0.552147

Lactobacillales; Carnobacteriaceae;

Granulicatella

Bacteria; Firmicutes; Erysipelotrichia;
28
0.009667
11.439285
0.000635
0.004394
0.109733
0.007263
0.039105
0.214724

Erysipelotrichales;

Erysipelotrichaceae; Longicatena

Bacteria; Proteobacteria; Epsilon
29
0.008849
0.087054
0.000041
0.000796
0.014313
0.000004
0.000012
0.092025

proteobacteria; Campylobacterales;

Helicobacteraceae; Helicobacter

Bacteria; Firmicutes; Bacilli;
30
0.008768
1.270599
0.087313
0.178981
0.854962
0.110940
0.208194
0.791411

Lactobacillales; Enterococcaceae;

Enterococcus

Bacteria; Firmicutes; Clostridia;
31
0.008158
0.219799
0.006744
0.026190
0.504771
0.001482
0.007581
0.208589

Clostridiales; Lachnospiraceae;

Ruminococcus2

Bacteria; Firmicutes; Clostridia;
32
0.008147
0.685279
0.017946
0.035471
0.865458
0.012298
0.026170
0.791411

Clostridiales; Lachnospiraceae;

Other

Bacteria; Actinobacteria; Actinobacteria;
33
0.007975
5.379831
0.000175
0.001109
0.203244
0.000941
0.006184
0.355828

Corynebacteriales; Corynebacteriaceae;

Corynebacterium

Bacteria; Firmicutes; Bacilli;
34
0.007947
0.614930
0.011599
0.049684
0.661260
0.007133
0.018683
0.760736

Lactobacillales; Other; Other

Bacteria; Firmicutes; Negativicutes;
35
0.007882
0.969644
0.015102
0.052413
0.614504
0.014643
0.045727
0.705521

Veillonellales; Veillonellaceae;

Veillonella

Bacteria; Firmicutes; Clostridia;
36
0.007833
1.293561
0.003973
0.011225
0.730916
0.005139
0.016770
0.693252

Clostridiales; Other; Other

Bacteria; Firmicutes; Negativicutes;
37
0.007592
0.453938
0.010436
0.042733
0.619275
0.004737
0.037434
0.453988

Selenomonadales; Veillonellaceae;

Veillonella

Bacteria; Actinobacteria;
38
0.007582
12.594796
0.000068
0.000474
0.122137
0.000851
0.004649
0.226994

Actinobacteria; Coriobacteriales;

Coriobacteriaceae; Atopobium

Bacteria; Firmicutes; Clostridia;
39
0.007539
0.653632
0.011966
0.039074
0.724237
0.007821
0.031595
0.693252

Clostridiales; Peptostreptococcaceae;

Clostridioides

Bacteria; Other; Other; Other; Other;
40
0.007354
0.203238
0.000559
0.002552
0.521947
0.000114
0.000520
0.343558

Other

Bacteria; Firmicutes; Clostridia;
41
0.007304
1.041457
0.005533
0.023519
0.677481
0.005762
0.015594
0.638037

Clostridiales; Peptostreptococcaceae;

Other

Bacteria; Verrucomicrobia;
42
0.007236
0.648843
0.018257
0.071411
0.470420
0.011846
0.083730
0.226994

Verrucomicrobiae; Verrucomicrobiales;

Verrucomicrobiaceae; Akkermansia

Bacteria; Firmicutes; Bacilli; Other;
43
0.007148
0.735678
0.000541
0.004864
0.383588
0.000398
0.000891
0.503067

Other; Other

Bacteria; Firmicutes; Clostridia;
44
0.007078
8.528665
0.000048
0.000974
0.015267
0.000411
0.002207
0.061350

Clostridiales; Ruminococcaceae;

Agathobaculum

Bacteria; Firmicutes; Clostridia;
45
0.007066
1.137991
0.013426
0.032788
0.810115
0.015279
0.045057
0.711656

Clostridiales; Lachnospiraceae;

Lachnoclostridium

Bacteria; Actinobacteria; Actinobacteria;
46
0.006869
1.952126
0.012501
0.043977
0.559160
0.024403
0.085315
0.490798

Bifidobacteriales; Bifidobacteriaceae;

Bifidobacterium

Bacteria; Firmicutes; Clostridia;
47
0.006849
2.847151
0.001215
0.006227
0.168893
0.003460
0.017320
0.263804

Clostridiales; Lachnospiraceae;

Tyzzerella

Bacteria; Firmicutes; Bacilli;
48
0.006523
0.713944
0.006149
0.029300
0.490458
0.004390
0.026302
0.509202

Lactobacillales; Enterococcaceae;

Other

Bacteria; Proteobacteria; Gamma
49
0.006314
1.003815
0.012077
0.063124
0.492366
0.012123
0.075931
0.368098

proteobacteria; Enterobacterales;

Enterobacteriaceae; Citrobacter

Bacteria; Firmicutes; Clostridia;
50
0.006263
0.897610
0.013901
0.042917
0.643130
0.012477
0.035348
0.638037

Clostridiales; Clostridiaceae;

Clostridium

Bacteria; Bacteroidetes; Bacteroidia;
51
0.006233
0.595628
0.017656
0.064847
0.557252
0.010516
0.078929
0.300613

Bacteroidales; Rikenellaceae;

Alistipes

Bacteria; Firmicutes; Clostridia;
52
0.006158
2.575898
0.001978
0.009577
0.395038
0.005096
0.026154
0.417178

Clostridiales; Clostridiaceae;

Hungatella

Bacteria; Firmicutes; Clostridia;
53
0.005948
2.072889
0.001971
0.010690
0.288168
0.004086
0.015414
0.202454

Clostridiales; Lachnospiraceae;

Fusicatenibacter

Bacteria; Firmicutes; Clostridia;
54
0.005875
2.656411
0.001190
0.006108
0.289122
0.003162
0.015299
0.349693

Clostridiales; Peptostreptococcaceae;

Terrisporobacter

Bacteria; Firmicutes; Erysipelotrichia;
55
0.005854
0.432155
0.007020
0.025301
0.643130
0.003034
0.007442
0.552147

Erysipelotrichales; Erysipelotrichaceae;

Clostridium XVIII

Bacteria; Verrucomicrobia;
56
0.005717
0.767486
0.012974
0.062238
0.416985
0.009958
0.079860
0.276074

Verrucomicrobiae; Verrucomicrobiales;

Akkermansiaceae; Akkermansia

Bacteria; Firmicutes; Clostridia;
57
0.005618
0.898806
0.007022
0.030846
0.540076
0.006312
0.019947
0.484663

Clostridiales; Clostridiaceae

1; Clostridium sensu stricto

Bacteria; Firmicutes; Bacilli;
58
0.005548
1.816253
0.001158
0.008212
0.312977
0.002103
0.008670
0.355828

Lactobacillales; Streptococcaceae;

Lactococcus

Bacteria; Firmicutes; Clostridia;
59
0.005546
2.107635
0.002959
0.017495
0.396947
0.006237
0.029087
0.312883

Clostridiales; Lachnospiraceae;

Eisenbergiella

Bacteria; Firmicutes; Clostridia;
60
0.005541
5.110983
0.001534
0.006380
0.385496
0.007839
0.041596
0.349693

Clostridiales; Eubacteriaceae;

Eubacterium

Bacteria; Bacteroidetes; Bacteroidia;
61
0.005518
0.537346
0.013330
0.041049
0.558206
0.007163
0.038013
0.374233

Bacteroidales; Tannerellaceae;

Parabacteroides

Bacteria; Actinobacteria; Coriobacteriia;
62
0.005414
3.588974
0.000172
0.001659
0.198473
0.000616
0.002338
0.251534

Coriobacteriales; Atopobiaceae;

Atopobium

Bacteria; Firmicutes; Clostridia;
63
0.005301
0.810345
0.005449
0.026062
0.585878
0.004416
0.017277
0.423313

Clostridiales; Ruminococcaceae;

Ruthenibacterium

Bacteria; Proteobacteria; Gamma
64
0.005283
26.586432
0.000201
0.004162
0.010496
0.005340
0.068044
0.073620

proteobacteria; Enterobacterales;

Yersiniaceae; Yersinia

Bacteria; Firmicutes; Clostridia;
65
0.005199
20.835218
0.000057
0.000645
0.067748
0.001183
0.011757
0.098160

Clostridiales; Clostridiales_Incertae

Sedis XI; Finegoldia

Bacteria; Firmicutes; Clostridia;
66
0.005010
2.292412
0.002818
0.014333
0.268130
0.006459
0.042897
0.233129

Clostridiales; Lachnospiraceae;

Faecalimonas

Bacteria; Actinobacteria;
67
0.004778
8.632569
0.000003
0.000050
0.023855
0.000025
0.000116
0.092025

Actinobacteria; Propionibacteriales;

Propionibacteriaceae;

Pseudopropionibacterium

Bacteria; Actinobacteria; Actinobacteria;
68
0.004733
9.367740
0.000231
0.001642
0.341603
0.002163
0.020292
0.251534

Micrococcales; Micrococcaceae;

Rothia

Bacteria; Firmicutes; Clostridia;
69
0.004676
0.673454
0.003217
0.009467
0.612595
0.002166
0.008636
0.484663

Clostridiales; Ruminococcaceae;

Flavonifractor

Bacteria; Firmicutes; Clostridia;
70
0.004577
1.717864
0.002840
0.012164
0.349237
0.004879
0.018782
0.269939

Clostridiales; Ruminococcaceae;

Ruminococcus

Bacteria; Firmicutes; Clostridia;
71
0.004567
2.859750
0.000482
0.005946
0.104962
0.001378
0.007208
0.134969

Clostridiales; Lachnospiraceae;

Robinsoniella

Bacteria; Firmicutes; Clostridia;
72
0.004434
0.840682
0.011117
0.042802
0.461832
0.009346
0.037604
0.337423

Clostridiales; Ruminococcaceae;

Faecalibacterium

Bacteria; Firmicutes; Erysipelotrichia;
73
0.004410
2.179446
0.001538
0.012407
0.292939
0.003352
0.014227
0.306748

Erysipelotrichales; Erysipelotrichaceae;

Turicibacter

Bacteria; Proteobacteria; Gamma
74
0.004235
0.527508
0.023907
0.124063
0.266221
0.012611
0.084066
0.141104

proteobacteria; Pseudomonadales;

Pseudomonadaceae; Pseudomonas

Bacteria; Firmicutes; Clostridia;
75
0.004167
0.750109
0.010395
0.037868
0.557252
0.007797
0.024579
0.472393

Clostridiales; Ruminococcaceae;

Other

Bacteria; Firmicutes; Tissierellia;
76
0.004150
5.907737
0.000306
0.002713
0.166031
0.001809
0.016334
0.226994

Tissierellales; Peptoniphilaceae;

Finegoldia

Bacteria; Actinobacteria; Actinobacteria;
77
0.004137
132.236072
0.000001
0.000007
0.009542
0.000073
0.000758
0.055215

Actinomycetales; Propionibacteriaceae;

Other

Bacteria; Firmicutes; Negativicutes;
78
0.004094
1.456619
0.003390
0.013104
0.270038
0.004939
0.021585
0.165644

Acidaminococcales;

Acidaminococcaceae;

Phascolarctobacterium

Bacteria; Proteobacteria; Gamma
79
0.004070
#DIV/0!
0.000000
0.000000
0.000000
0.000055
0.000409
0.042945

proteobacteria; Enterobacterales;

Serratia; Serratia liquefaciens

Bacteria; Bacteroidetes; Bacteroidia;
80
0.004031
0.274976
0.008745
0.050290
0.405534
0.002405
0.013350
0.226994

Bacteroidales; Prevotellaceae;

Prevotella

Bacteria; Firmicutes; Clostridia;
81
0.003857
1.338720
0.000051
0.000746
0.068702
0.000068
0.000308
0.098160

Clostridiales; Catabacteriaceae;

Catabacter

Bacteria; Firmicutes; Other; Other;
82
0.003677
0.128617
0.000398
0.002477
0.411260
0.000051
0.000146
0.306748

Other; Other

Bacteria; Firmicutes; Clostridia;
83
0.003648
4.203475
0.001122
0.005263
0.240458
0.004717
0.031952
0.177914

Clostridiales; Lachnospiraceae;

Dorea

Bacteria; Proteobacteria; Betaproteobacteria;
84
0.003517
2.284352
0.000242
0.003895
0.072519
0.000552
0.004157
0.128834

Neisseriales; Neisseriaceae;

Eikenella

Bacteria; Firmicutes; Negativicutes;
85
0.003359
1.900190
0.002501
0.010178
0.306298
0.004752
0.031692
0.220859

Veillonellales; Veillonellaceae;

Dialister

Bacteria; Proteobacteria; Gamma
86
0.003323
0.310934
0.002614
0.012587
0.342557
0.000813
0.003609
0.319018

proteobacteria; Pasteurellales;

Pasteurellaceae; Haemophilus

Bacteria; Firmicutes; Erysipelotrichia;
87
0.003322
0.744685
0.000660
0.004626
0.208015
0.000492
0.002420
0.214724

Erysipelotrichales; Erysipelotrichaceae;

Coprobacillus

Bacteria; Firmicutes; Tissierellia;
88
0.003308
2.879399
0.001095
0.008235
0.161260
0.003153
0.019435
0.196319

Tissierellales; Peptoniphilaceae;

Peptoniphilus

Bacteria; Firmicutes; Clostridia;
89
0.003308
1.645935
0.000952
0.008358
0.133588
0.001567
0.010485
0.239264

Clostridiales; Peptostreptococcaceae;

Peptostreptococcus

Bacteria; Proteobacteria; Gamma
90
0.003249
0.175053
0.000364
0.001037
0.373092
0.000064
0.000244
0.226994

proteobacteria; Other; Other;

Other

Bacteria; Firmicutes; Bacilli;
91
0.003152
0.134195
0.003189
0.038590
0.308206
0.000428
0.003028
0.251534

Bacillales; Staphylococcaceae;

Staphylococcus

Bacteria; Firmicutes; Bacilli;
92
0.003143
24.565543
0.000030
0.000212
0.083969
0.000736
0.005383
0.104294

Lactobacillales; Leuconostocaceae;

Leuconostoc

Bacteria; Fusobacteria; Fusobacteriia;
93
0.003109
0.259507
0.009036
0.042807
0.392176
0.002345
0.012720
0.269939

Fusobacteriales; Fusobacteriaceae;

Fusobacterium

Bacteria; Firmicutes; Clostridia;
94
0.003107
2.368769
0.000044
0.000532
0.064885
0.000104
0.000590
0.079755

Clostridiales; Christensenellaceae;

Christensenella

Bacteria; Firmicutes; Negativicutes;
95
0.003105
1.786312
0.000785
0.006558
0.164122
0.001402
0.011199
0.190184

Veillonellales; Veillonellaceae;

Megasphaera

Bacteria; Proteobacteria; Gamma
96
0.002968
0.002014
0.004347
0.038064
0.219466
0.000009
0.000056
0.061350

proteobacteria; Enterobacterales;

Enterobacteriaceae; Salmonella

Bacteria; Firmicutes; Bacilli;
97
0.002926
0.817985
0.000416
0.003045
0.183206
0.000340
0.003049
0.134969

Lactobacillales; Lactobacilloae;

Other

Bacteria; Actinobacteria; Actinobacteria;
98
0.002819
0.190002
0.000943
0.003455
0.330153
0.000179
0.000538
0.282209

Coriobacteriales; Coriobacteriaceae;

Eggerthella

Bacteria; Firmicutes; Clostridia;
99
0.002815
1.077056
0.001097
0.006183
0.292939
0.001182
0.006649
0.177914

Clostridiales; Lachnospiraceae;

[Eubacterium] rectale group

Bacteria; Firmicutes; Clostridia;
100
0.002815
0.360840
0.003179
0.012804
0.391221
0.001147
0.006662
0.245399

Clostridiales; Lachnospiraceae;

Roseburia

CDI = Clostridiodes difficile Infection;

Ctrl = Control;

P- = Pediatric;

A- = Adult;

RFFR = Random Forest Feature Rank;

# = Rank;

MDA = Mean Decrease Accuracy;

FC = Fold Change;

M = Mean;

SD = Standard Deviation;

DP = Detection Prevalence;

TABLE 18

MetaCyc (2022) defined metabolic pathways identified as features

Pathway ID
Pathway description

1CMET2-PWY
N10-formyl-tetrahydrofolate biosynthesis

3-HYDROXYPHENYLACETATE-
4-hydroxyphenylacetate degradation

DEGRADATION-PWY

AEROBACTINSYN-PWY
aerobactin biosynthesis

ALL-CHORISMATE-PWY
superpathway of chorismate metabolism

ANAEROFRUCAT-PWY
homolactic fermentation

ANAGLYCOLYSIS-PWY
glycolysis III (from glucose)

ARGDEG-PWY
superpathway of L-arginine, putrescine, and 4-

aminobutanoate degradation

ARGORNPROST-PWY
arginine, ornithine and proline interconversion

ARGSYNBSUB-PWY
L-arginine biosynthesis II (acetyl cycle)

ARGSYN-PWY
L-arginine biosynthesis I (via L-ornithine)

ARO-PWY
chorismate biosynthesis I

ASPASN-PWY
superpathway of L-aspartate and L-asparagine

biosynthesis

AST-PWY
L-arginine degradation II (AST pathway)

BRANCHED-CHAIN-AA-SYN-
superpathway of branched amino acid biosynthesis

PWY

CALVIN-PWY
Calvin-Benson-Bassham cycle

CENTFERM-PWY
pyruvate fermentation to butanoate

CHLOROPHYLL-SYN
chlorophyllide a biosynthesis I (aerobic, light-dependent)

COA-PWY
coenzyme A biosynthesis I

COBALSYN-PWY
adenosylcobalamin salvage from cobinamide I

CODH-PWY
reductive acetyl coenzyme A pathway

COMPLETE-ARO-PWY
superpathway of aromatic amino acid biosynthesis

DAPLYSINESYN-PWY
L-lysine biosynthesis I

DENOVOPURINE2-PWY
superpathway of purine nucleotides de novo biosynthesis II

DHGLUCONATE-PYR-CAT-
glucose degradation (oxidative)

PWY

DTDPRHAMSYN-PWY
dTDP-L-rhamnose biosynthesis I

ECASYN-PWY
enterobacterial common antigen biosynthesis

ENTBACSYN-PWY
enterobactin biosynthesis

FAO-PWY
fatty acid β-oxidation I

FASYN-ELONG-PWY
fatty acid elongation -- saturated

FASYN-INITIAL-PWY
superpathway of fatty acid biosynthesis initiation

(E. coli)

FERMENTATION-PWY
mixed acid fermentation

FOLSYN-PWY
superpathway of tetrahydrofolate biosynthesis and

salvage

FUCCAT-PWY
fucose degradation

FUC-RHAMCAT-PWY
superpathway of fucose and rhamnose degradation

GALACTARDEG-PWY
D-galactarate degradation I

GALACT-GLUCUROCAT-PWY
superpathway of hexuronide and hexuronate degradation

GALACTUROCAT-PWY
D-galacturonate degradation I

GLCMANNANAUT-PWY
superpathway of N-acetylglucosamine, N-

acetylmannosamine and N-acetylneuraminate

degradation

GLUCARDEG-PWY
D-glucarate degradation I

GLUCARGALACTSUPER-
superpathway of D-glucarate and D-galactarate

PWY
degradation

GLUCONEO-PWY
gluconeogenesis I

GLUCOSE1PMETAB-PWY
glucose and glucose-1-phosphate degradation

GLUCUROCAT-PWY
superpathway of β-D-glucuronide and D-

glucuronate degradation

GLUTORN-PWY
L-ornithine biosynthesis

GLYCOCAT-PWY
glycogen degradation I (bacterial)

GLYCOGENSYNTH-PWY
glycogen biosynthesis I (from ADP-D-Glucose)

GLYCOL-GLYOXDEG-PWY
superpathway of glycol metabolism and degradation

GLYCOLYSIS
glycolysis I (from glucose 6-phosphate)

GLYCOLYSIS-E-D
superpathway of glycolysis and Entner-Doudoroff

GLYCOLYSIS-TCA-GLYOX-
superpathway of glycolysis, pyruvate dehydrogenase,

BYPASS
TCA, and glyoxylate bypass

GLYOXYLATE-BYPASS
glyoxylate cycle

GOLPDLCAT-PWY
superpathway of glycerol degradation to 1,3-propanediol

HCAMHPDEG-PWY
3-phenylpropanoate and 3-(3-hydroxyphenyl)propanoate

degradation to 2-oxopent-4-enoate

HEME-BIOSYNTHESIS-II
heme biosynthesis I (aerobic)

HEMESYN2-PWY
heme biosynthesis II (anaerobic)

HISDEG-PWY
L-histidine degradation I

HISTSYN-PWY
L-histidine biosynthesis

ILEUSYN-PWY
L-isoleucine biosynthesis I (from threonine)

KDO-NAGLIPASYN-PWY
superpathway of (Kdo)2-lipid A biosynthesis

LACTOSECAT-PWY
lactose and galactose degradation I

LEU-DEG2-PWY
L-leucine degradation I

METH-ACETATE-PWY
methanogenesis from acetate

METHANOGENESIS-PWY
methanogenesis from H2 and CO2

METHGLYUT-PWY
superpathway of methylglyoxal degradation

METHYLGALLATE-
methylgallate degradation

DEGRADATION-PWY

NONMEVIPP-PWY
methylerythritol phosphate pathway I

NONOXIPENT-PWY
pentose phosphate pathway (non-oxidative branch)

OANTIGEN-PWY
O-antigen building blocks biosynthesis (E. coli)

ORNARGDEG-PWY
superpathway of L-arginine and L-ornithine degradation

ORNDEG-PWY
superpathway of ornithine degradation

P122-PWY
heterolactic fermentation

P124-PWY

Bifidobacterium shunt

P125-PWY
superpathway of (R,R)-butanediol biosynthesis

P161-PWY
acetylene degradation

P162-PWY
L-glutamate degradation V (via hydroxyglutarate)

P163-PWY
L-lysine fermentation to acetate and butanoate

P164-PWY
purine nucleobases degradation I (anaerobic)

P221-PWY
octane oxidation

P23-PWY
reductive TCA cycle I

P241-PWY
coenzyme B biosynthesis

P261-PWY
coenzyme M biosynthesis I

P341-PWY
glycolysis V (Pyrococcus)

P381-PWY
adenosylcobalamin biosynthesis II (late cobalt

incorporation)

P42-PWY
incomplete reductive TCA cycle

P441-PWY
superpathway of N-acetylneuraminate degradation

P461-PWY
hexitol fermentation to lactate, formate, ethanol and

acetate

P4-PWY
superpathway of L-lysine, L-threonine and L-methionine

biosynthesis I

P562-PWY
myo-inositol degradation I

PANTO-PWY
phosphopantothenate biosynthesis I

PANTOSYN-PWY
pantothenate and coenzyme A biosynthesis I

PENTOSE-P-PWY
pentose phosphate pathway

PEPTIDOGLYCANSYN-PWY
peptidoglycan biosynthesis I (meso-diaminopimelate

containing)

PHOSLIPSYN-PWY
superpathway of phospholipid biosynthesis I (bacteria)

POLYAMINSYN3-PWY
superpathway of polyamine biosynthesis II

POLYISOPRENSYN-PWY
polyisoprenoid biosynthesis (E. coli)

PPGPPMET-PWY
ppGpp biosynthesis

PROTOCATECHUATE-
protocatechuate degradation II (ortho-cleavage pathway)

ORTHO-CLEAVAGE-PWY

PWY0-1241
ADP-L-glycero-β-D-manno-heptose biosynthesis

PWY0-1261
anhydromuropeptides recycling

PWY0-1277
3-phenylpropanoate and 3-(3-hydroxyphenyl)propanoate

degradation

PWY0-1296
purine ribonucleosides degradation

PWY0-1297
superpathway of purine deoxyribonucleosides

degradation

PWY0-1298
superpathway of pyrimidine deoxyribonucleosides

degradation

PWY0-1319
CDP-diacylglycerol biosynthesis II

PWY0-1338
polymyxin resistance

PWY0-1415
superpathway of heme biosynthesis from

uroporphyrinogen-III

PWY0-1533
methylphosphonate degradation I

PWY0-162
superpathway of pyrimidine ribonucleotides de novo

biosynthesis

PWY0-166
superpathway of pyrimidine deoxyribonucleotides de

novo biosynthesis (E. coli)

PWY0-321
phenylacetate degradation I (aerobic)

PWY0-41
allantoin degradation IV (anaerobic)

PWY0-781
aspartate superpathway

PWY0-845
superpathway of pyridoxal 5′-phosphate biosynthesis and

salvage

PWY0-862
(5Z)-dodec-5-enoate biosynthesis

PWY-181
photorespiration

PWY-1861
formaldehyde assimilation II (RuMP Cycle)

PWY-2941
L-lysine biosynthesis II

PWY-2942
L-lysine biosynthesis III

PWY-3001
superpathway of L-isoleucine biosynthesis I

PWY-3781
aerobic respiration I (cytochrome c)

PWY-3801
sucrose degradation II (sucrose synthase)

PWY-4722
creatinine degradation II

PWY490-3
nitrate reduction VI (assimilatory)

PWY-4984
urea cycle

PWY4FS-7
phosphatidylglycerol biosynthesis I (plastidic)

PWY4FS-8
phosphatidylglycerol biosynthesis II (non-plastidic)

PWY-5005
biotin biosynthesis II

PWY-5022
4-aminobutanoate degradation V

PWY-5028
L-histidine degradation II

PWY-5088
L-glutamate degradation VIII (to propanoate)

PWY-5097
L-lysine biosynthesis VI

PWY-5100
pyruvate fermentation to acetate and lactate II

PWY-5101
L-isoleucine biosynthesis II

PWY-5103
L-isoleucine biosynthesis III

PWY-5104
L-isoleucine biosynthesis IV

PWY-5121
superpathway of geranylgeranyl diphosphate

biosynthesis II (via MEP)

PWY-5154
L-arginine biosynthesis III (via N-acetyl-L-citrulline)

PWY-5178
toluene degradation IV (aerobic) (via catechol)

PWY-5180
toluene degradation I (aerobic) (via o-cresol)

PWY-5181
toluene degradation III (aerobic) (via p-cresol)

PWY-5188
tetrapyrrole biosynthesis I (from glutamate)

PWY-5189
tetrapyrrole biosynthesis II (from glycine)

PWY-5198
factor 420 biosynthesis

PWY-5265
peptidoglycan biosynthesis II (staphylococci)

PWY-5304
superpathway of sulfur oxidation (Acidianus ambivalens)

PWY-5347
superpathway of L-methionine biosynthesis

(transsulfuration)

PWY-5384
sucrose degradation IV (sucrose phosphorylase)

PWY-5484
glycolysis II (from fructose 6-phosphate)

PWY-5505
L-glutamate and L-glutamine biosynthesis

PWY-5507
adenosylcobalamin biosynthesis I (early cobalt insertion)

PWY-5509
adenosylcobalamin biosynthesis from cobyrinate a,c-

diamide I

PWY-5531
chlorophyllide a biosynthesis II (anaerobic)

PWY-5659
GDP-mannose biosynthesis

PWY-5667
CDP-diacylglycerol biosynthesis I

PWY-5676
acetyl-CoA fermentation to butanoate II

PWY-5686
UMP biosynthesis

PWY-5695
urate biosynthesis/inosine 5′-phosphate degradation

PWY-5705
allantoin degradation to glyoxylate III

PWY-5837
1,4-dihydroxy-2-naphthoate biosynthesis I

PWY-5838
superpathway of menaquinol-8 biosynthesis I

PWY-5840
superpathway of menaquinol-7 biosynthesis

PWY-5845
superpathway of menaquinol-9 biosynthesis

PWY-5850
superpathway of menaquinol-6 biosynthesis I

PWY-5860
superpathway of demethylmenaquinol-6 biosynthesis I

PWY-5861
superpathway of demethylmenaquinol-8 biosynthesis

PWY-5862
superpathway of demethylmenaquinol-9 biosynthesis

PWY-5863
superpathway of phylloquinol biosynthesis

PWY-5896
superpathway of menaquinol-10 biosynthesis

PWY-5897
superpathway of menaquinol-11 biosynthesis

PWY-5898
superpathway of menaquinol-12 biosynthesis

PWY-5899
superpathway of menaquinol-13 biosynthesis

PWY-5910
superpathway of geranylgeranyldiphosphate biosynthesis

I (via mevalonate)

PWY-5913
TCA cycle VI (obligate autotrophs)

PWY-5971
palmitate biosynthesis II (bacteria and plants)

PWY-5973
cis-vaccenate biosynthesis

PWY-6071
superpathway of phenylethylamine degradation

PWY-6121
5-aminoimidazole ribonucleotide biosynthesis I

PWY-6122
5-aminoimidazole ribonucleotide biosynthesis II

PWY-6123
inosine-5′-phosphate biosynthesis I

PWY-6125
superpathway of guanosine nucleotides de novo

biosynthesis II

PWY-6126
superpathway of adenosine nucleotides de novo

biosynthesis II

PWY-6141
archaetidylserine and archaetidylethanolamine

biosynthesis

PWY-6147
6-hydroxymethyl-dihydropterin diphosphate biosynthesis I

PWY-6148
tetrahydromethanopterin biosynthesis

PWY-6151
S-adenosyl-L-methionine cycle I

PWY-6163
chorismate biosynthesis from 3-dehydroquinate

PWY-6165
chorismate biosynthesis II (archaea)

PWY-6167
flavin biosynthesis II (archaea)

PWY-6174
mevalonate pathway II (archaea)

PWY-621
sucrose degradation III (sucrose invertase)

PWY-6263
superpathway of menaquinol-8 biosynthesis II

PWY-6269
adenosylcobalamin salvage from cobinamide II

PWY-6277
superpathway of 5-aminoimidazole ribonucleotide

biosynthesis

PWY-6317
galactose degradation I (Leloir pathway)

PWY-6349
CDP-archaeol biosynthesis

PWY-6350
archaetidylinositol biosynthesis

PWY-6353
purine nucleotides degradation II (aerobic)

PWY-6385
peptidoglycan biosynthesis III (mycobacteria)

PWY-6386
UDP-N-acetylmuramoyl-pentapeptide biosynthesis II

(lysine-containing)

PWY-6387
UDP-N-acetylmuramoyl-pentapeptide biosynthesis I

(meso-diaminopimelate containing)

PWY-6396
superpathway of 2,3-butanediol biosynthesis

PWY-6470
peptidoglycan biosynthesis V (β-lactam resistance)

PWY-6471
peptidoglycan biosynthesis IV (Enterococcus faecium)

PWY-6478
GDP-D-glycero-α-D-manno-heptose biosynthesis

PWY-6507
4-deoxy-L-threo-hex-4-enopyranuronate degradation

PWY-6545
pyrimidine deoxyribonucleotides de novo biosynthesis III

PWY-6572
chondroitin sulfate degradation I (bacterial)

PWY-6588
pyruvate fermentation to acetone

PWY-6590
superpathway of Clostridium acetobutylicum acidogenic

fermentation

PWY-6608
guanosine nucleotides degradation III

PWY-6609
adenine and adenosine salvage III

PWY-6612
superpathway of tetrahydrofolate biosynthesis

PWY-6641
superpathway of sulfolactate degradation

PWY-6654
phosphopantothenate biosynthesis III

PWY-6690
cinnamate and 3-hydroxycinnamate degradation to 2-

oxopent-4-enoate

PWY-6700
queuosine biosynthesis

PWY-6703
preQ0 biosynthesis

PWY-6737
starch degradation V

PWY-6749
CMP-legionaminate biosynthesis I

PWY-6876
isopropanol biosynthesis

PWY-6891
thiazole biosynthesis II (Bacillus)

PWY-6892
thiazole biosynthesis I (E. coli)

PWY-6895
superpathway of thiamin diphosphate biosynthesis II

PWY-6897
thiamin salvage II

PWY-6901
superpathway of glucose and xylose degradation

PWY-6906
chitin derivatives degradation

PWY-6969
TCA cycle V (2-oxoglutarate:ferredoxin oxidoreductase)

PWY-7003
glycerol degradation to butanol

PWY-7013
L-1,2-propanediol degradation

PWY-7090
UDP-2,3-diacetamido-2,3-dideoxy-α-D-mannuronate biosynthesis

PWY-7094
fatty acid salvage

PWY-7111
pyruvate fermentation to isobutanol (engineered)

PWY-7159
chlorophyllide a biosynthesis III (aerobic, light

independent)

PWY-7184
pyrimidine deoxyribonucleotides de novo biosynthesis I

PWY-7187
pyrimidine deoxyribonucleotides de novo biosynthesis II

PWY-7196
superpathway of pyrimidine ribonucleosides salvage

PWY-7197
pyrimidine deoxyribonucleotide phosphorylation

PWY-7198
pyrimidine deoxyribonucleotides de novo biosynthesis IV

PWY-7199
pyrimidine deoxyribonucleosides salvage

PWY-7200
superpathway of pyrimidine deoxyribonucleoside salvage

PWY-7208
superpathway of pyrimidine nucleobases salvage

PWY-7209
superpathway of pyrimidine ribonucleosides degradation

PWY-7210
pyrimidine deoxyribonucleotides biosynthesis from CTP

PWY-7219
adenosine ribonucleotides de novo biosynthesis

PWY-7220
adenosine deoxyribonucleotides de novo biosynthesis II

PWY-7221
guanosine ribonucleotides de novo biosynthesis

PWY-7222
guanosine deoxyribonucleotides de novo biosynthesis II

PWY-7228
superpathway of guanosine nucleotides de novo

biosynthesis I

PWY-7229
superpathway of adenosine nucleotides de novo

biosynthesis I

PWY-7234
inosine-5′-phosphate biosynthesis III

PWY-7237
myo-, chiro- and scillo-inositol degradation

PWY-7242
D-fructuronate degradation

PWY-7286
7-(3-amino-3-carboxypropyl)-wyosine biosynthesis

PWY-7315
dTDP-N-acetylthomosamine biosynthesis

PWY-7328
superpathway of UDP-glucose-derived O-antigen

building blocks biosynthesis

PWY-7332
superpathway of UDP-N-acetylglucosamine-derived O-

antigen building blocks biosynthesis

PWY-7371
1,4-dihydroxy-6-naphthoate biosynthesis II

PWY-7374
1,4-dihydroxy-6-naphthoate biosynthesis I

PWY-7376
cob(II)yrinate a,c-diamide biosynthesis II (late cobalt

incorporation)

PWY-7377
cob(II)yrinate a,c-diamide biosynthesis I (early cobalt

insertion)

PWY-7391
isoprene biosynthesis II (engineered)

PWY-7392
taxadiene biosynthesis (engineered)

PWY-7400
L-arginine biosynthesis IV (archaebacteria)

PWY-7431
aromatic biogenic amine degradation (bacteria)

PWY-7456
mannan degradation

PWY-7539
6-hydroxymethyl-dihydropterin diphosphate biosynthesis

III (Chlamydia)

PWY-7560
methylerythritol phosphate pathway II

PWY-7663
gondoate biosynthesis (anaerobic)

PWY-841
superpathway of purine nucleotides de novo biosynthesis I

PWY-922
mevalonate pathway I

PWYG-321
mycolate biosynthesis

PYRIDNUCSAL-PWY
NAD salvage pathway I

PYRIDNUCSYN-PWY
NAD biosynthesis I (from aspartate)

PYRIDOXSYN-PWY
pyridoxal 5′-phosphate biosynthesis I

REDCITCYC
TCA cycle VIII (helicobacter)

RHAMCAT-PWY
L-rhamnose degradation I

RIBOSYN2-PWY
flavin biosynthesis I (bacteria and plants)

SALVADEHYPOX-PWY
adenosine nucleotides degradation II

SER-GLYSYN-PWY
superpathway of L-serine and glycine biosynthesis I

SO4ASSIM-PWY
sulfate reduction I (assimilatory)

SULFATE-CYS-PWY
superpathway of sulfate assimilation and cysteine

biosynthesis

TCA
TCA cycle I (prokaryotic)

TCA-GLYOX-BYPASS
superpathway of glyoxylate bypass and TCA

THISYN-PWY
superpathway of thiamin diphosphate biosynthesis I

THREOCAT-PWY
superpathway of L-threonine metabolism

THRESYN-PWY
superpathway of L-threonine biosynthesis

TRNA-CHARGING-PWY
tRNA charging

TRPSYN-PWY
L-tryptophan biosynthesis

TYRFUMCAT-PWY
L-tyrosine degradation I

UDPNAGSYN-PWY
UDP-N-acetyl-D-glucosamine biosynthesis I

VALDEG-PWY
L-valine degradation I

VALSYN-PWY
L-valine biosynthesis

TABLE 19

Taxa4Meta taxonomic classifiers identified as features

Feature (taxonomic order: kingdom; phylum;

class; order; family; genus; species)

Archaea; Euryarchaeota; Methanobacteria; Methanobacteriales; Methanobacteriaceae; Methanobrevibacter;

Methanobrevibacter smithii

Archaea; Euryarchaeota; Methanobacteria; Methanobacteriales; Methanobacteriaceae; Methanobrevibacter;

Other

Bacteria; Actinobacteria; Actinobacteria; Actinomycetales; Actinomycetaceae; Actinomyces; Other

Bacteria; Actinobacteria; Actinobacteria; Actinomycetales; Actinomycetaceae; Other; Other

Bacteria; Actinobacteria; Actinobacteria; Actinomycetales; Actinomycetaceae; Schaalia;

Schaalia odontolytica

Bacteria; Actinobacteria; Actinobacteria; Bifidobacteriales; Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium adolescentis

Bacteria; Actinobacteria; Actinobacteria; Bifidobacteriales; Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium bifidum

Bacteria; Actinobacteria; Actinobacteria; Bifidobacteriales; Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium boum

Bacteria; Actinobacteria; Actinobacteria; Bifidobacteriales; Bifidobacteriaceae; Bifidobacterium;

Bifidobacterium longum

Bacteria; Actinobacteria; Actinobacteria; Bifidobacteriales; Bifidobacteriaceae; Bifidobacterium;

Other

Bacteria; Actinobacteria; Actinobacteria; Bifidobacteriales; Bifidobacteriaceae; Other; Other

Bacteria; Actinobacteria; Actinobacteria; Coriobacteriales; Coriobacteriaceae; Collinsella; Other

Bacteria; Actinobacteria; Actinobacteria; Coriobacteriales; Coriobacteriaceae; Eggerthella; Other

Bacteria; Actinobacteria; Actinobacteria; Coriobacteriales; Coriobacteriaceae; Other; Other

Bacteria; Actinobacteria; Actinobacteria; Other; Other; Other; Other

Bacteria; Actinobacteria; Coriobacteriia; Coriobacteriales; Coriobacteriaceae; Collinsella;

Collinsella aerofaciens

Bacteria; Actinobacteria; Coriobacteriia; Eggerthellales; Eggerthellaceae; Adlercreutzia;

Adlercreutzia equolifaciens

Bacteria; Actinobacteria; Coriobacteriia; Eggerthellales; Eggerthellaceae; Eggerthella; Eggerthella

lenta

Bacteria; Actinobacteria; Coriobacteriia; Eggerthellales; Eggerthellaceae; Gordonibacter;

Gordonibacter pamelaeae

Bacteria; Actinobacteria; Coriobacteriia; Eggerthellales; Eggerthellaceae; Other; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

acidifaciens

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

caccae

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

cellulosilyticus

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

coprocola

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

coprophilus

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

dorei

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

eggerthii

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

finegoldii

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

koreensis

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

massiliensis

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

nordii

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

ovatus

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

plebeius

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

thetaiotaomicron

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

uniformis

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

vulgatus

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Bacteroides

xylanisolvens

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Bacteroidaceae; Bacteroides; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Barnesiellaceae; Coprobacter; Coprobacter

fastidiosus

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Odoribacteraceae; Odoribacter; Odoribacter

splanchnicus

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Other; Other; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Porphyromonadaceae; Barnesiella; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Porphyromonadaceae; Butyricimonas; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Porphyromonadaceae; Odoribacter; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Porphyromonadaceae; Other; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Porphyromonadaceae; Parabacteroides; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Prevotellaceae; Paraprevotella; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Prevotellaceae; Prevotella; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Prevotellaceae; Prevotella; Prevotella copri

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Prevotellaceae; Prevotellamassilia;

Prevotellamassilia timonensis

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Alistipes; Alistipes finegoldii

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Alistipes; Alistipes ihumii

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Alistipes; Alistipes obesi

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Alistipes; Alistipes

onderdonkii

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Alistipes; Alistipes putredinis

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Alistipes; Alistipes shahii

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Alistipes; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Other; Other

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Rikenellaceae; Tidjanibacter; Tidjanibacter

massiliensis

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Tannerellaceae; Parabacteroides; Parabacteroides

distasonis

Bacteria; Bacteroidetes; Bacteroidia; Bacteroidales; Tannerellaceae; Parabacteroides; Parabacteroides

merdae

Bacteria; Bacteroidetes; Other; Other; Other; Other; Other

Bacteria; Bacteroidetes; Sphingobacteriia; Sphingobacteriales; Sphingobacteriaceae; Pedobacter;

Other

Bacteria; Candidatus Saccharibacteria; Saccharibacteria_genera_incertae_sedis; Other; Other; Other; Other

Bacteria; Cyanobacteria/Chloroplast; Chloroplast; Chloroplast; Streptophyta; Other; Other

Bacteria; Firmicutes; Bacilli; Bacillales; Bacillales_Incertae Sedis XI; Gemella; Other

Bacteria; Firmicutes; Bacilli; Bacillales; Other; Gemella; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Carnobacteriaceae; Granulicatella; Granulicatella

adiacens

Bacteria; Firmicutes; Bacilli; Lactobacillales; Carnobacteriaceae; Granulicatella; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Enterococcaceae; Enterococcus; Enterococcus

saccharolyticus

Bacteria; Firmicutes; Bacilli; Lactobacillales; Enterococcaceae; Enterococcus; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Enterococcaceae; Other; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Lactobacillaceae; Lactobacillus; Lactobacillus

rogosae

Bacteria; Firmicutes; Bacilli; Lactobacillales; Lactobacillaceae; Lactobacillus; Lactobacillus sakei

Bacteria; Firmicutes; Bacilli; Lactobacillales; Lactobacillaceae; Lactobacillus; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Lactobacillaceae; Leuconostoc; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Other; Other; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Streptococcaceae; Other; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Streptococcaceae; Streptococcus; Other

Bacteria; Firmicutes; Bacilli; Lactobacillales; Streptococcaceae; Streptococcus; Streptococcus

parasanguinis

Bacteria; Firmicutes; Bacilli; Lactobacillales; Streptococcaceae; Streptococcus; Streptococcus

salivarius

Bacteria; Firmicutes; Bacilli; Lactobacillales; Streptococcaceae; Streptococcus; Streptococcus

sanguinis

Bacteria; Firmicutes; Bacilli; Lactobacillales; Streptococcaceae; Streptococcus; Streptococcus

thermophilus

Bacteria; Firmicutes; Bacilli; Other; Other; Other; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiaceae 1; Clostridium sensu stricto; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiaceae; Clostridium; Clostridium cadaveris

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiaceae; Clostridium; Clostridium

paraputrificum

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiaceae; Clostridium; Clostridium

perfringens

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiaceae; Clostridium; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiaceae; Hungatella; Hungatella effluvii

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiales Family XIII. Incertae

Sedis; Ihubacter; Ihubacter massiliensis

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiales Family XIII. Incertae Sedis; Not

Available; [Eubacterium] sulci

Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiales_Incertae Sedis XI; Parvimonas; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Eubacteriaceae; Anaerofustis; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Eubacteriaceae; Eubacterium; [Eubacterium]

eligens

Bacteria; Firmicutes; Clostridia; Clostridiales; Eubacteriaceae; Eubacterium; Eubacterium

ventriosum

Bacteria; Firmicutes; Clostridia; Clostridiales; Eubacteriaceae; Eubacterium; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Anaerostipes; Anaerostipes

hadrus

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Anaerostipes; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; [Ruminococcus] gnavus

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia caecimuris

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia faecis

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia hominis

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia

hydrogenotrophica

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia luti

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia obeum

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia producta

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia stercoris

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Blautia wexlerae

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Blautia; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Clostridium XIVa; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Coprococcus; Coprococcus catus

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Coprococcus; Coprococcus

comes

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Coprococcus; Coprococcus

eutactus

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Coprococcus; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Dorea; Dorea formicigenerans

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Dorea; Dorea longicatena

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Dorea; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Eisenbergiella; Eisenbergiella

tayi

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Faecalicatena; Faecalicatena

fissicatena

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Faecalimonas; Faecalimonas

umbilicata

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Fusicatenibacter; Fusicatenibacter

saccharivorans

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Fusicatenibacter; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Hungatella; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Lachnoclostridium; [Clostridium]

aldenense

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Lachnoclostridium; [Clostridium]

bolteae

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Lachnoclostridium; [Clostridium]

citroniae

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Lachnoclostridium; [Clostridium]

glycyrrhizinilyticum

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Lachnoclostridium; [Clostridium]

lavalense

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Lachnoclostridium; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Lachnospiracea_incertae_sedis;

Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Not Available; [Eubacterium]

rectale

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Other; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Roseburia; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Roseburia; Roseburia faecis

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Roseburia; Roseburia hominis

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Roseburia; Roseburia intestinalis

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Roseburia; Roseburia

inulinivorans

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Ruminococcus2; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Lachnospiraceae; Tyzzerella; Tyzzerella nexilis

Bacteria; Firmicutes; Clostridia; Clostridiales; Not Available; Colidextribacter; Colidextribacter

massiliensis

Bacteria; Firmicutes; Clostridia; Clostridiales; Not Available; Intestinimonas; Intestinimonas

butyriciproducens

Bacteria; Firmicutes; Clostridia; Clostridiales; Other; Other; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Clostridioides; Clostridioides

difficile

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Clostridium XI; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Intestinibacter;

Intestinibacter bartlettii

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Intestinibacter; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Other; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Peptostreptococcus; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Romboutsia; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Romboutsia; Romboutsia

timonensis

Bacteria; Firmicutes; Clostridia; Clostridiales; Peptostreptococcaceae; Terrisporobacter; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Agathobaculum; Agathobaculum

butyriciproducens

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Anaeromassilibacillus;

Anaeromassilibacillus senegalensis

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Anaerotruncus; Anaerotruncus

colihominis

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Anaerotruncus; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Clostridium IV; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Faecalibacterium; Faecalibacterium

prausnitzii

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Faecalibacterium; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Flavonifractor; Flavonifractor

plautii

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Flavonifractor; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Gemmiger; Gemmiger

formicilis

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Gemmiger; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Intestinimonas; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Negativibacillus; Negativibacillus

massiliensis

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Neglecta; Neglecta timonensis

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Not Available; [Clostridium]

leptum

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Not Available; [Eubacterium]

siraeum

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Oscillibacter; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Other; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Pseudoflavonifractor; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Pseudoflavonifractor;

Pseudoflavonifractor capillosus

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Ruminococcus; Other

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Ruminococcus; Ruminococcus

bromii

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Ruminococcus; Ruminococcus

callidus

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Ruminococcus; Ruminococcus

faecis

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Ruminococcus; Ruminococcus

lactaris

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Ruthenibacterium; Ruthenibacterium

lactatiformans

Bacteria; Firmicutes; Clostridia; Clostridiales; Ruminococcaceae; Subdoligranulum; Other

Bacteria; Firmicutes; Clostridia; Other; Other; Other; Other

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Clostridium

XVIII; Other

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Erysipelatoclostridium;

[Clostridium] innocuum

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Erysipelatoclostridium;

[Clostridium] spiroforme

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Erysipelatoclostridium;

Erysipelatoclostridium ramosum

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Faecalicoccus; Other

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Holdemania; Holdemania

filiformis

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Holdemania; Other

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Massilimicrobiota;

Massilimicrobiota timonensis

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Other; Other

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Solobacterium;

Solobacterium moorei

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Turicibacter; Other

Bacteria; Firmicutes; Erysipelotrichia; Erysipelotrichales; Erysipelotrichaceae; Turicibacter;

Turicibacter sanguinis

Bacteria; Firmicutes; Negativicutes; Acidaminococcales; Acidaminococcaceae; Phascolarctobacterium;

Phascolarctobacterium faecium

Bacteria; Firmicutes; Negativicutes; Selenomonadales; Acidaminococcaceae; Acidaminococcus;

Other

Bacteria; Firmicutes; Negativicutes; Selenomonadales; Acidaminococcaceae; Phascolarctobacterium;

Other

Bacteria; Firmicutes; Negativicutes; Selenomonadales; Veillonellaceae; Dialister; Other

Bacteria; Firmicutes; Negativicutes; Selenomonadales; Veillonellaceae; Other; Other

Bacteria; Firmicutes; Negativicutes; Selenomonadales; Veillonellaceae; Veillonella; Other

Bacteria; Firmicutes; Negativicutes; Veillonellales; Veillonellaceae; Dialister; Dialister invisus

Bacteria; Firmicutes; Negativicutes; Veillonellales; Veillonellaceae; Megasphaera; Megasphaera

micronuciformis

Bacteria; Firmicutes; Negativicutes; Veillonellales; Veillonellaceae; Veillonella; Other

Bacteria; Firmicutes; Negativicutes; Veillonellales; Veillonellaceae; Veillonella; Veillonella

dispar

Bacteria; Firmicutes; Negativicutes; Veillonellales; Veillonellaceae; Veillonella; Veillonella

infantium

Bacteria; Firmicutes; Negativicutes; Veillonellales; Veillonellaceae; Veillonella; Veillonella

parvula

Bacteria; Firmicutes; Other; Other; Other; Other; Other

Bacteria; Firmicutes; Tissierellia; Tissierellales; Peptoniphilaceae; Peptoniphilus; Other

Bacteria; Fusobacteria; Fusobacteriia; Fusobacteriales; Fusobacteriaceae; Fusobacterium;

Fusobacterium nucleatum

Bacteria; Fusobacteria; Fusobacteriia; Fusobacteriales; Fusobacteriaceae; Fusobacterium; Other

Bacteria; Lentisphaerae; Lentisphaeria; Victivallales; Victivallaceae; Victivallis; Other

Bacteria; Other; Other; Other; Other; Other; Other

Bacteria; Proteobacteria; Alphaproteobacteria; Caulobacterales; Caulobacteraceae; Caulobacter;

Caulobacter segnis

Bacteria; Proteobacteria; Alphaproteobacteria; Caulobacterales; Caulobacteraceae; Caulobacter;

Other

Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Phyllobacteriaceae; Phyllobacterium;

Other

Bacteria; Proteobacteria; Alphaproteobacteria; Sphingomonadales; Sphingomonadaceae; Sphingomonas;

Other

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Burkholderiaceae; Burkholderia;

Burkholderia ambifaria

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Burkholderiaceae; Burkholderia;

Burkholderia thailandensis

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Burkholderiaceae; Burkholderia;

Other

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Burkholderiaceae; Other; Other

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Comamonadaceae; Other; Other

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Comamonadaceae; Pelomonas;

Pelomonas aquatica

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Other; Other; Other

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Oxalobacteraceae; Oxalobacter;

Oxalobacter formigenes

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Sutterellaceae; Parasutterella;

Parasutterella excrementihominis

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Sutterellaceae; Sutterella; Other

Bacteria; Proteobacteria; Betaproteobacteria; Burkholderiales; Sutterellaceae; Sutterella; Sutterella

wadsworthensis

Bacteria; Proteobacteria; Betaproteobacteria; Nitrosomonadales; Methylophilaceae; Methylophilus;

Other

Bacteria; Proteobacteria; Betaproteobacteria; Other; Other; Other; Other

Bacteria; Proteobacteria; Deltaproteobacteria; Desulfovibrionales; Desulfovibrionaceae; Bilophila;

Other

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Enterobacteriaceae; Cedecea;

Other

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Enterobacteriaceae; Citrobacter;

Other

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Enterobacteriaceae; Other; Other

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Enterobacteriaceae; Rosenbergiella;

Rosenbergiella collisarenosi

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Enterobacteriaceae; Rosenbergiella;

Rosenbergiella nectarea

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Enterobacteriaceae; Salmonella;

Salmonella enterica

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Enterobacteriaceae; Shigella;

Shigella dysenteriae

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Other; Other; Other

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales; Pectobacteriaceae; Pectobacterium;

Pectobacterium carotovorum

Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacteriales; Enterobacteriaceae; Other; Other

Bacteria; Proteobacteria; Gammaproteobacteria; Other; Other; Other; Other

Bacteria; Proteobacteria; Gammaproteobacteria; Pasteurellales; Pasteurellaceae; Haemophilus;

Haemophilus parainfluenzae

Bacteria; Proteobacteria; Gammaproteobacteria; Pseudomonadales; Pseudomonadaceae; Pseudomonas;

Other

Bacteria; Proteobacteria; Other; Other; Other; Other; Other

Bacteria; Verrucomicrobia; Verrucomicrobiae; Verrucomicrobiales; Akkermansiaceae; Akkermansia;

Akkermansia muciniphila

Bacteria; Verrucomicrobia; Verrucomicrobiae; Verrucomicrobiales; Verrucomicrobiaceae;

Akkermansia; Other

TABLE 20

Proportion of discarded reads and counts of OTUs or ASVs after combined

clustering or denoising of amplicons with different read lengths.

Percentage of discarded reads at each length
ASVs /

16S
Method
100
150
170
200
250
300
350
400
450
O
OTUs
NIS

V1V3
DADA2-
6.43
8.06
9.26
10.01
10.57
11.06
11.59
12.15
13.40
13.75
115,446
18,257

(forward)
DeNovo-ASV

UCLUST-
10.09
17.37
24.14
24.45
25.35
21.14
21.70
18.29
22.51
21.98
18,831
18,257

ClosedRef-0.97

UCLUST-
40.13
56.49
59.89
63.64
66.54
68.03
670.3
71.23
72.96
72.87
9,359
18,257

ClosedRef-1.00

UCLUST-
0
0
0
0
0
0
0
0
0
0
20,020
18,257

DeNovo-0.97

UCLUST-
0
0
0
0
0
0
0
0
0
0
360,329
18,257

DeNovo-1.00

VSEARCH-
0
0
0
0
0
0
0
0
0
0
10,771
18,257

DeNovo-0.97

VSEARCH-
0
10
0
0
0
0
0
0
0
0
13,650
18,257

DeNovo-0.99

VSEARCH-
0
0
0
0
0
0
0
0
0
0
15,668
18,257

DeNovo-1.00

V1V3
DADA2-
4.53
5.74
6.13
6.54
7.25
8.51
10.34
10.84
12.58
13.70
101,887
18,257

(reverse)
DeNovo-ASV

UCLUST-
4.99
5.68
3.95
3.55
5.76
5.81
13.39
11.65
17.72
21.98
23,810
18,257

ClosedRef-0.97

UCLUST-
25.5
35.58
44.04
48.01
57.71
59.43
64.13
65.50
71.62
72.87
11,851
18,257

ClosedRef-1.00
7

UCLUST-
0
0
0
0
0
0
0
0
0
0
27,502
18,257

DeNovo-0.97

UCLUST-
0
0
0
0
0
0
0
0
0
0
668,211
18,257

DeNovo-1.00

VSEARCH-
0
10
0
0
0
0
0
0
0
0
9,451
18,257

DeNovo-0.97

VSEARCH-
0
0
0
0
0
0
0
0
0
0
13,050
18,257

DeNovo-0.99

VSEARCH-
0
0
0
0
0
0
0
0
0
0
15,710
18,257

DeNovo-1.00

V3V5
DADA2-
3.56
5.58
6.00
6.32
6.78
7.48
7.88
8.35
8.75
9.99
97,800
18,269

(forward)
DeNovo-ASV

UCLUST-
1.15
5.05
4.00
4.80
6.26
5.35
5.49
5.30
7.00
12.70
23,460
18,269

ClosedRef-0.97

UCLUST-
37.11
35.89
45.40
46.18
58.54
59.81
66.87
63.24
64.86
74.46
11,354
18,269

ClosedRef-1.00

UCLUST-
0
0
0
0
0
0
0
0
0
0
28,967
18,269

DeNovo-0.97

UCLUST-
0
0
0
0
0
0
0
0
0
0
1,213,787
18,269

DeNovo-1.00

VSEARCH-
0
0
0
0
0
0
0
0
0
0
6,510
18,269

DeNovo-0.97

VSEARCH-
0
0
0
0
0
0
0
0
0
0
10,512
18,269

DeNovo-0.99

VSEARCH-
0
0
0
0
0
0
0
0
0
0
14,081
18,269

DeNovo-1.00

V3V5
DADA2-
3.23
3.95
4.25
4.52
5.06
5.90
6.33
6.94
8.90
10.02
85,124
18,269

(reverse)
DeNovo-ASV

UCLUST-
1.18
1.60
1.26
1.52
1.26
1.94
2.59
2.92
13.41
12.70
23,739
18,269

ClosedRef-0.97

UCLUST-
13.41
34.26
29.83
35.93
38.65
48.93
54.91
62.75
65.73
74.46
12,542
18,269

ClosedRef-1.00

UCLUST-
0
0
0
0
0
0
0
0
0
0
14,924
18,269

DeNovo-0.97

UCLUST-
0
0
0
0
0
0
0
0
0
0
1,010,095
18,269

DeNovo-1.00

VSEARCH-
0
0
0
0
0
0
0
0
0
0
5,518
18,269

DeNovo-0.97

VSEARCH-
0
0
0
0
0
0
0
0
0
0
10,041
18,269

DeNovo-0.99

VSEARCH-
0
0
0
0
0
0
0
0
0
0
14,118
18,269

DeNovo-1.00

V4
DADA2-
3.12
4.11
4.37
4.70
NA
NA
NA
NA
NA
5.26
42,922
19,971

(forward)
DeNovo-ASV

UCLUST-
1.38
2.68
2.08
1.69
NA
NA
NA
NA
NA
3.78
17,463
19,971

ClosedRef-0.97

UCLUST-
30.90
31.06
42.94
37.09
NA
NA
NA
NA
NA
52.47
11,055
19,971

ClosedRef-1.00

UCLUST-
0
0
0
0
NA
NA
NA
NA
NA
0
7,602
19,971

DeNovo-0.97

UCLUST-
0
0
0
0
NA
NA
NA
NA
NA
0
439,029
19,971

DeNovo-1.00

VSEARCH-
0
0
0
0
NA
NA
NA
NA
NA
0
5,471
19,971

DeNovo-0.97

VSEARCH-
0
0
0
0
NA
NA
NA
NA
NA
0
8,981
19,971

DeNovo-0.99

VSEARCH-
0
0
0
0
NA
NA
NA
NA
NA
0
11,695
19,971

DeNovo-1.00

V4
DADA2-
2.51
3.51
4.05
4.47
NA
NA
NA
NA
NA
5.03
50,898
19,971

(reverse)
DeNovo-ASV

UCLUST-
0.65
2.64
1.26
1.78
NA
NA
NA
NA
NA
3.78
18,831
19,971

ClosedRef-0.97

UCLUST-
15.54
37.01
42.90
36.59
NA
NA
NA
NA
NA
52.47
11,459
19,971

ClosedRef-1.00

UCLUST-
0
0
0
0
NA
NA
NA
NA
NA
0
29,066
19,971

DeNovo-0.97

UCLUST-
0
0
0
0
NA
NA
NA
NA
NA
0
1,130,881
19,971

DeNovo-1.00

VSEARCH-
0
0
0
0
NA
NA
NA
NA
NA
0
4,883
19,971

DeNovo-0.97

VSEARCH-
0
0
0
0
NA
NA
NA
NA
NA
0
8,753
19,971

DeNovo-0.99

VSEARCH-
0
0
0
0
NA
NA
NA
NA
NA
0
11,806
19,971

DeNovo-1.00

V6V9
DADA2-
3.95
5.13
5.96
6.36
6.68
7.65
7.93
18.29
8.74
10.64
82,525
14,944

(forward)
DeNovo-ASV

UCLUST-
3.15
5.83
4.29
4.64
5.05
7.36
5.84
5.11
10.99
12.26
19,707
14,944

ClosedRef-0.97

UCLUST-
20.41
33.85
38.87
40.41
52.04
57.23
67.96
62.79
74.13
84.82
10,100
14,944

ClosedRef-1.00

UCLUST-
0
0
0
0
0
0
0
0
0
0
16,744
14,944

DeNovo-0.97

UCLUST-
0
0
0
0
0
0
0
0
0
0
835,026
14,944

DeNovo-1.00

VSEARCH-
0
0
0
0
0
0
0
0
0
0
5,860
14,944

DeNovo-0.97

VSEARCH-
0

00
0
0
0
0
0
0
0
9,191
14,944

DeNovo-0.99

VSEARCH-
0
0
0
0
0
0
0
0
0
0
12,038
14,944

DeNovo-1.00

V6V9
DADA2-
4.55
5.03
5.23
5.46
6.75
7.01
7.60
8.59
8.92
10.64
73,949
14,944

(reverse)
DeNovo-ASV

UCLUST-
5.69
8.87
5.03
4.54
8.49
5.80
7.13
7.15
8.27
12.26
16,825
14,944

ClosedRef-0.97

UCLUST-
28.10
46.15
57.64
54.26
62.61
70.05
73.35
80.74
75.96
84.82
8,035
14,944

ClosedRef-1.00

UCLUST-
0
0
0
0
0
0
0
0
0
0
12,068
14,944

DeNovo-0.97

UCLUST-
0
0
0
0
0
0
0
0
0
0
1,244,549
14,944

DeNovo-1.00

VSEARCH-
0
0
0
0
0
0
0
0
0
0
5,340
14,944

DeNovo-0.97

VSEARCH-
0
0
0
0
0
0
0
0
0
0
8,849
14,944

DeNovo-0.99

VSEARCH-
0
0
0
0
0
0
0
0
0
0
12,008
14,944

DeNovo-1.00

Type of 16S amplicon = 16S; O = Original; Number of ASVs/OTUs = ASVs / OTUs; Number of input strains = NIS; Not Applicable = NA.

TABLE 21

Training and validation cohort information.

Data Order: Dataset ID, Adult training dataset, Internal Process

Code, Category, Geography, Clinical center, Cohort, Time Course,

Data Access, Source of metadata, Groups, Selected patient cases/

subjects, Antibiotic exposure, 16S region, Sequence type,

Sequence orientation, Platform, Publication, Journal

Meta-analysis dataset #1, FALSE, CD_Havard_V4_Paired-end, IBD, North America,

Multiple, Pediatric, Single sampling, PRJNA237362, Supplemental material of paper, “CD,

Not IBD”, 227 CD, Detailed for each subject, V4, Paired-end, Forward & reverse, Illumina,

The Treatment-Naive Microbiome in New-Onset Crohn's Disease, “Cell Host & Microbe,

2014, 15: 382-392.”

Meta-analysis dataset #2, TRUE, CD_Korean_V1V3_Single-end, IBD, South Korea, Single,

Adult, Single sampling, PRJNA240658, NCBI BioSample, “CD, HC”, “11 CD, 10 HC”, No

antibiotics within 3 months, V1-V3, Single-end, Reverse, 454, Does the intestinal microbial

community of Korean Crohn's disease patients differ from that of western patients?, “BMC

Gastroenterology, 2016, 16: 28.”

Meta-analysis dataset #3, TRUE, IBD_Havard_V3V5_Single-end, IBD, United States,

Multiple, Adult, Single sampling, PRJNA82111,

https://web.rniapps.net/iVikodak/refdash/database.php, “CD, UC, HC”, “61 CD, 47 UC, 18

HC”, Not detailed for each subject, V3-V5, Single-end, Reverse, 454, Dysfunction of the

intestinal microbiome in inflammatory bowel disease and treatment, “Genome Biology, 2012,

13: R79.”

Meta-analysis dataset #4, FALSE, IBD_Japan_V3V4_Paired-end, IBD, Japan, Unknown,

Unknown, Single sampling, PRJDB6133, NCBI BioSample, “CD, UC, HC”, “25 CD, 30 UC,

23 HC”, Unknown, V3-V4, Paired-end, Forward & reverse, Illumina, Unknown, Unknown

Meta-analysis dataset #5, TRUE, IBD_Spanish_V4_Single-end, IBD, Spain, Single, Adult,

Longitudinal sampling (follow-up), PRJNA422193, NCBI BioSample, “CD, UC, HC, HR”,

“34 CD, 33 UC, 44 HC, 39 HR”, No antibiotics within 4 weeks, V4, Single-end, Forward,

Illumina, A microbial signature for Crohn's disease, “Gut, 2017, 0: 1-10.”

Meta-analysis dataset #6, TRUE, IBD_Sweden_V4_100 bp_Single-end, IBD, Sweden, Single,

Adult, Longitudinal sampling (follow-up), PRJEB18471, NCBI BioSample, “ICD-r, ICD-nr,

CCD, UC, HC”, “49 CD, 60 UC, 9 HC”, Unknown, V4, Single-end, Forward, Illumina,

Dynamics of the human gut microbiome in inflammatory bowel disease, “Nature

Microbiology, 2017, 2: 17004.”

Meta-analysis dataset #7, TRUE, IBD_Winnipeg_V4_Paired-end, IBD, Canada, Single,

Adult, Longitudinal sampling (follow-up), PRJNA450340, NCBI BioSample, “CD, UC, HC”,

“20 CD, 19 UC, 23 HC”, Unknown, V4, Paired-end, Forward & reverse, Illumina, A

comparative study of the gut microbiota in immune-mediated inflammatory diseases-does a

common dysbiosis exist?, “Microbiome, 2018, 6: 221.”

Meta-analysis dataset #8, TRUE, IBD-IBS_Italy_V1V3_Single-end, IBD, Italy, Single, Adult,

Single sampling, PRJNA391149, NCBI BioSample, “CD, UC, HC”, “6 CD, 24 UC, 40 HC”,

No antibiotics within 3 months, V1-V3, Single-end, Reverse, 454, Fecal and Mucosal

Microbiota Profiling in Irritable Bowel Syndrome and Inflammatory Bowel Disease, “Front.

Microbiol., 2019, 10: 1655.”

Meta-analysis dataset #9, TRUE, UC_Czech_V3V4_Single-end, IBD, Czech, Single, Adult,

Single sampling, PRJNA368966, NCBI BioSample, “UC, HC”, “32 UC, 32 HC”, No

antibiotics within 3 months, V3-V4, Single-end (SRA seq is paired-end merged), Forward,

Illumina, Distinct gut microbiota profiles in patients with primary sclerosing cholangitis and

ulcerative colitis, “World J Gastroenterol 2017, 23(25): 548-4558.”

Meta-analysis dataset #10, TRUE, UC_UCSF_V4_Paired-end, IBD, United States, Single,

Adult, Single sampling, PRJNA313074, NCBI BioSample, “UC, HC”, “30 UC, 13 HC”, No

antibiotics within 2 months, V4, Paired-end, Forward & reverse, Illumina, Disease Severity

and Immune Activity Relate to Distinct interkingdom Gut Microbiome States in Ethnically

Distinct Ulcerative Colitis Patients, “mBio 2016, 7(4): e01072-16.”

Meta-analysis dataset #11, TRUE, IBD-IBS_Italy_V1V3_Single-end, IBS, Italy, Single,

Adult, Single sampling, PRJNA391149, NCBI BioSample, “IBC-C, IBS-D, IBS-M, HC”, “15

IBC-C, 14 IBS-D, 7 IBS-M, 40 HC”, Unknown, V1-V3, Single-end, Reverse, 454, Fecal and

Mucosal Microbiota Profiling in Irritable Bowel Syndrome and Inflammatory Bowel Disease,

“Front. Microbiol., 2019, 10: 1655.”

Meta-analysis dataset #12, TRUE, IBS_Italy_V3V4_Paired-end, IBS, Italy, Single, Adult,

Longitudinal sampling (intervention), PRJNA279031, NCBI BioSample, “Non-constipated

IBS, HC”, “15 Non-constipated IBS, 5 HC”, No antibiotics within 4 weeks, V3-V4, Paired-

end, Forward & reverse, Illumina, Modulation of the gut microbiota composition by rifaximin

in non-constipated irritable bowel syndrome patients: a molecular approach, “Clinical and

Experimental Gastroenterology, 2015, 8: 309-325.”

Meta-analysis dataset #13, TRUE, IBS_Korea_V3V4_Paired-end, IBS, South Korea, Single,

Adult, Single sampling, PRJNA541572, NCBI BioSample, “IBS, HC”, “30

IBS_LowCalprotectin, 19 IBS_HighCalprotectin, 43 HC”, Unknown, V3-V4, Paired-end,

Forward & reverse, Illumina, Unknown, Unknown

Meta-analysis dataset #14, TRUE, IBS_Mexico_V4_Single-end, IBS, Mexico, Single, Adult,

Longitudinal sampling (intervention), PRJNA540064, NCBI BioSample, “IBC-C, IBS-D,

IBS-M”, “16 IBC-C, 5 IBS-D, 19 IBS-M”, Unknown, V4, Single-end, Forward, Illumina,

Unknown, Unknown

Meta-analysis dataset #15, TRUE, IBS_Spanish_V4_Single-end, IBS, Spain, Single, Adult,

Longitudinal sampling (follow-up), PRJNA268708, NCBI BioSample, “IBC-C, IBS-D, IBS-

M (alternating IBS), HC”, “23 IBC-C, 47 IBS-D, 24 IBS-M, 66 HC”, No antibiotics within 3

months, V4, Single-end, Forward, Illumina, Reduction of butyrateand methane-producing

microorganisms in patients with Irritable Bowel Syndrome, “Scientific Reports, 2015,

5: 12693.”

Meta-analysis dataset #16, TRUE, IBS_UCLA_V3V5_Single-end, IBS, United States, Single,

Adult, Single sampling, PRJNA373876, NCBI BioSample, “IBS, HC”, “29 IBS, 23 HC”, No

antibiotics within 3 months, V3-V5, Single-end, Reverse, 454, Differences in gut microbial

composition correlate with regional brain volumes in irritable bowel syndrome, “Microbiome,

2017, 5: 49.”

Meta-analysis dataset #17, TRUE, IBS_Vienna_V1V2_Paired-end, IBS, Italy, Single, Adult,

Single sampling, PRJNA386442, NCBI BioSample, “IBC-C, IBS-D, IBS-M”, “5 IBC-C, 25

IBS-D, 18 IBS-M”, No antibiotics within 1 month, V1-V2, Paired-end, Forward & reverse,

Illumina, A Microbial Signature of Psychological Distress in Irritable Bowel Syndrome,

“Psychosomatic Medicine, 2018, 80: 698-709.”

Meta-analysis dataset #18, TRUE, IBS_SeattleStudy42_V4_Paired-end, IBS, United States,

Single, Adult, Single sampling, Author, Author, “IBC-C, IBS-D, IBS-M”, “25 IBC-C, 46 IBS-

D, 15 IBS-M”, No antibiotics within 2 months, V4, Paired-end, Forward & reverse, Illumina,

“Relationships of microbiome markers with extraintestinal, psychological distress and

gastrointestinal symptoms, and quality of life in women with irritable bowel syndrome”,

“Journal of Clinical Gastroenterology, 2020, 54 (2): 175-183.”

Meta-analysis dataset #19, FALSE, IBS_PHMP_V1V3_V3V5_Single-end, IBS, United

States, Single, Pediatric, Single sampling, PRJNA46339, NCBI BioSample, “IBS/FAP, HC”,

“46 IBS/FAP, 45 HC”, No antibiotics within 6 months, V1-V3, Single-end, Reverse, 454,

Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome,

“Gastroenterology, 2011, 141: 1782-1791.”

Meta-analysis dataset #20, FALSE, IBS_PHMP_V1V3_V3V5_Single-end, IBS, United

States, Single, Pediatric, Single sampling, PRJNA46339, NCBI BioSample, “IBS/FAP, HC”,

“46 IBS/FAP, 45 HC”, No antibiotics within 6 months, V3-V5, Single-end, Reverse, 454,

Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome,

“Gastroenterology, 2011, 141: 1782-1791.”

Meta-analysis dataset #21, FALSE, IBS_TCH_V4_Paired-end, IBS, United States, Single,

Pediatric, Single sampling, Author, Author, “IBS/FAP, HC”, “149 IBS/FAP, 74 HC”,

Unknown, V4, Paired-end, Forward & reverse, Illumina, Unknown, Unknown

Meta-analysis dataset #22, TRUE, CDI_UM_Schloss_V3V5_Single-end, CDI, United States,

Single, Adult, Single sampling, http://www.mothur.org/CDI_MicrobiomeModeling,

http://www.mothur.org/CDI_MicrobiomeModeling, “CDI, HC”, “94 CDI, 155 HC”, Not

detailed for each HC subject within 3 months, V3-V5, Single-end, Reverse, 454, Microbiome

Data Distinguish Patients with Clostridium difficile Infection and Non-C. difficile-Associated

Diarrhea from Healthy Controls, “mBio, 2014, 5(3): e01021-14.”

Meta-analysis dataset #23, TRUE, CDI_UFH_V1V3_Single-end, CDI, United States, Single,

Adult, Single sampling, PRJNA174594, NCBI BioSample, “CDI, HC”, “39 CDI, 40 HC”, Not

detailed for each HC subject within 3 months, V1-V3, Single-end, Reverse, 454, Intestinal

Dysbiosis and Depletion of Butyrogenic Bacteria in Clostridium difficile Infection and

Nosocomial Diarrhea, “Journal of Clinical Microbiology, 2013, 51(9): 2884-2892.”

Meta-analysis dataset #24, TRUE, CDI_Mayo2016_V4_Single-end, CDI, United States,

Single, Adult, Single sampling, PRJNA342347, NCBI BioSample, CDI, 88 CDI, Not

applicable, V4, Paired-end but only forward sequence used, Forward, Illumina, Gut

microbiome predictors of treatment response and recurrence in primary Clostridium difficile

infection, “Aliment Pharmacol Ther, 2016; 44: 715-727.”

Meta-analysis dataset #25, TRUE, CDI_Mayo2018_V4_Paired-end, CDI, United States,

Single, Adult, Single sampling, PRJNA317326, NCBI BioSample, “CDI, HC”, “85 CDI, 110

HC”, Unknown for each HC, V4, Paired-end, Forward & reverse, Illumina, Clostridioides

difficile uses amino acids associated with gut microbial dysbiosis in a subset of patients with

diarrhea, “Sci. Transl. Med., 2018, 10: eaam7019.”

Meta-analysis dataset #26, TRUE, CDI_UM_Young_V4_Paired-end, CDI, United States,

Single, Adult, Longitudinal sampling (follow-up), PRJNA307992, Supplemental material of

paper, CDI, 148 CDI samples, Not applicable, V4, Paired-end, Forward & reverse, Illumina,

Dynamics of the fecal microbiome in patients with recurrent and nonrecurrent Clostridium

difficile infection, “Genome Medicine, 2016, 8: 47.”

Meta-analysis dataset #27, TRUE, Control_UM_Young_V4_Paired-end, Control, United

States, Single, Adult, Single sampling, PRJNA386260, NCBI BioSample, HC, 178 HC, No

antibiotics within 3 months, V4, Paired-end, Forward & reverse, Illumina, Unknown,

Unknown

Validation cohort #1, FALSE, CDI_ChineseAsymCDI, CDI, China, Single, Unknown, Single

sampling, PRJNA488351, NCBI BioSample, CDI, 22 CDI, Not applicable, V3-V4, Paired-

end, Forward & reverse, Illumina, Unknown, Unknown

Validation cohort #2, FALSE, CDI_Netherlands, CDI, Netherlands, Single, Adult, Single

sampling, PRJEB30586, NCBI BioSample, CDI, 41 CDI, Not applicable, V4, Paired-end,

Forward & reverse, Illumina, “The Bacterial Gut Microbiota of Adult Patients Infected,

Colonized or Noncolonized by Clostridioides difficile”, “Microorganisms, 2020, 8, 677.”

Validation cohort #3, FALSE, CDI_Michigan, CDI, US, Single, Adult, Single sampling,

PRJNA729511, NCBI BioSample, CDI, “1, 515 CDI”, Not applicable, V4, Paired-end,

Forward & reverse, Illumina, Unknown, Unknown

Validation cohort #4, FALSE, IBD_Japan_V3V4_Paired-end, IBD, Japan, Unknown,

Unknown, Single sampling, PRJDB6133, NCBI BioSample, “CD, UC, HC”, “25 CD, 30 UC,

23 HC”, Unknown, V3-V4, Paired-end, Forward & reverse, Illumina, Unknown, Unknown

Validation cohort #5, FALSE, IBD_UCC_Canada, IBD, Ireland, Unknown, Adult,

Longitudinal sampling (follow-up), PRJNA414072, Author, “CD, UC, HC”, “186 CD, 144

UC, 79 HC”, Not detailed for each subject, V3-V4 (only use V4 forward seq), Paired-end,

Forward & reverse, Illumina, Ranking microbiome variance in inflammatory bowel disease: a

large longitudinal intercontinental study, “Gut, 2020, 0: 1-12”

Validation cohort #6, FALSE, IBD_UCC_Canada, IBD, Canada, Unknown, Adult,

Longitudinal sampling (follow-up), PRJNA414072, Author, “CD, UC, HC”, “117 CD, 84 UC,

82 HC”, Not detailed for each subject, V3-V4 (only use V4 forward seq), Paired-end, Forward

& reverse, Illumina, Ranking microbiome variance in inflammatory bowel disease: a large

longitudinal intercontinental study, “Gut, 2020, 0: 1-12”

Validation cohort #7, FALSE, AGP-IBD, IBD, US, Not applicable, Adult (main), Single

sampling, PRJEB11419,

https://figshare.com/articles/dataset/Full_American_Gut_Project_mapping_file/6137315,

IBD, 162 IBD (self-reported), No antibiotics within 6 months (majority), V4, Single-end,

Forward, Illumina, American Gut: an Open Platform for Citizen Science Microbiome

Research, mSystems 3: e00031-18

Validation cohort #8, FALSE, IBS_LowFODMAP, IBS, New Zealand, Single, Adult,

Longitudinal sampling (follow-up), PRJNA392762, NCBI BioSample, IBS, 54 IBS samples

(control diet), Unknown, V4, Paired-end, Forward & reverse, Illumina, Long-term irritable

bowel syndrome symptom control with reintroduction of selected FODMAPs, “World J

Gastroenterol, 2017, 23(25): 4632-4643.”

Validation cohort #9, FALSE, IBS_Japan, IBS, Japan, Single, Adult, Single sampling,

PRJNA637763, NCBI SRA, IBS, 85 IBS, No antibiotics within 1 months, V1-V2, Paired-end,

Forward & reverse, Illumina, Usefulness of Machine Learning-Based Gut Microbiome

Analysis for Identifying Patients with Irritable Bowels Syndrome, “J. Clin. Med. 2020, 9(8):

2403.”

Validation cohort #10, FALSE, IBS_Seattle-Study93, IBS, US, Single, Adult, Single

sampling, Author, Author, IBS, 71 IBS, Unknown, V4, Paired-end, Forward & reverse,

Illumina, Unknown, Unknown

Validation cohort #11, FALSE, IBS_Yoga, IBS, Germany, Single, Adult, Longitudinal

sampling (follow-up), PRJEB24421, NCBI BioSample, IBS, 88 IBS samples (yoga group),

Unknown, V3-V4, Paired-end, Forward & reverse, Illumina, Randomised clinical trial: yoga

vs a low-FODMAP diet in patients with irritable bowel syndrome, “Aliment Pharmacol Ther,

2018, 47: 203-211.”

Validation cohort #12, FALSE, AGP-IBS, IBS, US, Not applicable, Adult (main), Single

sampling, PRJEB 11419,

https://figshare.com/articles/dataset/Full_American_Gut_Project_mapping_file/6137315, IBS,

“1, 161 IBS (self-reported)”, No antibiotics within 6 months (majority), V4, Single-end,

Forward, Illumina, American Gut: an Open Platform for Citizen Science Microbiome

Research, mSystems 3: e00031-18

Validation cohort #13, FALSE, LifeLines-IBS, IBS, Netherlands, Not applicable, Adult

(main), Single sampling, EGAD00001003453, https://www.lifelines.nl/ (Need Purchase for

data access), IBS, 115 IBS (self-reported), Not clear at the time of stool sampling, V4, Paired-

end, Forward & reverse, Illumina, Many, Many

TABLE 22

Simulation of 16S rDNA amplicon sequences from NCBI 16S rRNA RefSeq database.

16S Region = 16S; Amplicon size of E. coli 16S template = Amp; Size selection of

amplicons = SSA; Count of sequences (strains) of NCBI 16S rRNA RefSeq = Count; Before

simulation = Before; After simulation = After.

SSA
Count

16S
Forward (5′→3′)
Reverse (5′→3′)
Amp
min.
max.
Before
After

V1-V3
AGAGTTTGAT
CCAGCAGCCGC
490
420
510
20,160
90%

CATGGCTCAG
GGTAAT

input

(SEQ ID NO: 1)
(SEQ ID NO: 2)

V3-V5
CCTACGGGAG
ACTCAAATGAA
551
525
561
20,160
90%

GCAGCAG
TTGACGG

input

(SEQ ID NO: 3)
(SEQ ID NO: 4)

V4
CCAGCAGCCG
ATTAGATACCC
253
248
258
20,160
99%

CGGTAA
TGGTAGTCC

input

(SEQ ID NO: 5)
(SEQ ID NO: 6)

V6
AACGCGAAGA
AAGTCGTAACA
507
477
527
20,160
75%

V9
ACCTTAC
AGGTAACCGTA

input

(SEQ ID NO: 7)
(SEQ ID NO: 8)

Example 3—Determining Optimal Sequence Lengths for Accurate Taxonomic Profiling of 16S Amplicons

Most 16S pipelines trim amplicon reads to equal short sequence lengths after quality control procedures resulting in potential compositional and taxonomic bias (FIG. 1A). Submitting short and long 16S reads for downstream processing can potentially reduce this bias but its analytics represents a bioinformatics challenge. Notably, optimal amplicon length for sequence clustering/denoising and taxonomic resolution needs to be established for each microbial species investigated. To assess the feasibility of such a bioinformatics approach, the inventors simulated 16S amplicon data of variable length and maintained an identical allocated sequence count (randomly assigned from 1 to 50) for benchmarking the accuracy of different sequence clustering/denoising tools. For commonly used 16S variable regions (V1-V3, V3-V5, V4 and V6-V9), closed-reference analysis using UCLUST discarded large proportions of amplicon reads even when a comprehensive reference database (SILVA release 132) was used, and results were strongly biased towards higher sequence identity and longer reads (Table 20). Although the DADA2 pipeline retained more reads in this simulated analysis, it still discarded >2% of sequences, with singleton reads being disproportionally excluded. By contrast, de novo clustering tools retained all sequence reads setting precedent for accurate compositional profiling (Table 20). By performing pairwise Spearman correlations between any two variable lengths (as two independent samples) in OTU/ASV output tables, the inventors found that applying 99% similarity for clustering amplicons in VSEARCH conferred the highest correlation coefficients across wider length ranges in all 16S variable regions tested (data available upon request). Spearman coefficients increased progressively with longer reads, enabling establishment of minimum amplicon length thresholds (Spearman's rho >0.75) and optimal amplicon length ranges for sequence clustering of variable length input data (FIG. 1B and FIGS. 7A-7C).

The above selected amplicon sequence ranges were then applied to assess whether qualified variable read lengths generated from different 16S regions provided accurate taxonomic annotation. Using random and repeat sequences previously reported for benchmarking of taxonomic over-classification by Murali et al. (ref. 10), the inventors found that default settings in BLCA11 did not annotate these sequences whereas other popular taxonomic classifiers, including RDP classifier and SINTAX generated high false positive hits (ref. 10). Because random and repeat sequences do not accurately reflect uncharacterized/unidentified species that could contribute to taxonomical over-classification in a microbiome community, the inventors used simulated amplicon data of unannotated 16S sequences (down to family-rank from the RDP database 11.5) to determine optimal settings in BLCA. The inventors found that taxonomic over-classification is highly dependent on 16S variable region, identity, and coverage of sequence alignment in BLCA (FIG. 8). Over-classification rates were reduced to below 5% (V1-V3, V3-V5, V6-V9) and 10% (V4) when we increased the threshold of sequence identity and coverage to 0.99, without applying bootstrap confidence thresholds for taxonomic selection (FIG. 8). Thus, sequence identity and coverage thresholds of 0.99 were applied in BLCA to conduct the following benchmarking.

The inventors utilized the above threshold settings in BLCA to annotate simulated amplicons of variable length generated from known taxonomic lineages in the NCBI 16S RefSeq database. To calculate taxonomic accuracy, the inventors compared BLCA annotations against input lineage 16S data (ground truth). The inventors then calculated optimal confidence scores and proportions of correctly assigned taxonomic annotations for each qualified sequence length and found that correctly assigned amplicons were significantly increased towards longer read length (FIGS. 1C-1D and FIGS. 9A-9D). Surprisingly, the inventors also observed that confidence scores for incorrect annotations were significantly increased with longer read length, and that misclassification rates were highly dependent on 16S sequence orientation and variable region analyzed (FIGS. 9A-9D). This finding relates to the observation that increasing amplicon length generally improves taxonomic accuracy at species-rank relative to genus-rank, as the latter has more capacity for degeneracy. Because the inventors showed that it is not appropriate to apply universal confidence thresholds to all types of 16S amplicon data, they calculated optimal region-specific confidence thresholds in order to achieve accurate taxonomic annotation for all common types of amplicon data that could be used in a meta-analyses (FIGS. 10A-10B). This conceptual approach formed the basis of a 16S meta-analysis using a new taxonomic binning strategy.

Example 4—Taxa4Meta: A ‘Best Practices’ Taxonomic Profiler for 16S Meta-Analysis

Based on the above described benchmarking results of simulated 16S amplicon data, the inventors designed the bioinformatics pipeline “Taxa4Meta” for accurate taxonomic profiling of 16S rDNA amplicon data generated from different sequencing strategies (FIG. 2A). Taxa4Meta was constructed to maximize the use of clinically archived 16S datasets by adopting a variable sequence length analysis strategy that can be applied to multiple amplicon regions. To obtain accurate taxonomic profiles, we introduced two critical workflow-specific settings: (1) VSEARCH-based de novo sequence clustering with 99% similarity was applied to 16S amplicon data with optimal sequence length range as determined above for each amplicon data type; (2) confident species calls were achieved by using BLCA with stringent sequence alignment (99% identity and 99% coverage), and by applying region-specific confidence scores as determined above. OTUs that were not annotated by BLCA were fed into and classified by the IDTAXA program using its pre-built RDP training set (version 16; curated by program developer). As a last step, Taxa4Meta OTU tables were generated by collapsing taxonomical features down to species-rank without processing for random rarefaction that could result in a biased taxonomic profile.

To test the taxonomic profiling accuracy of Taxa4Meta, the inventors generated complex mock communities with defined and cultivable bacteria as benchmarking input. First, variable length amplicons from diverse 16S sequences representing the NCBI 16S RefSeq database (>20.000 bacterial strains representing >14,000 species from >2.900 genera) were simulated. For benchmarking Taxa4Meta, amplicon length ranges that provide optimal taxonomic annotation for each distinct 16S variable region (FIG. 1B and FIGS. 7A-7C) were selected. Taxa4Meta performance was then critically compared against four state-of-the art 16S pipelines and the input data (ground truth). Because commonly used 16S pipelines rely on different reference databases for taxonomic annotation, taxonomic profiles were interpreted at family rank as this is more consistently represented across databases. Simulated datasets containing defined sequence abundances and taxonomic lineages (ground truth) were used to generate Spearman correlations to compare qualified input data with compositional profiles generated by individual 16S pipelines. Side-by-side comparisons of Taxa4Meta against DADA2. UCLUST and USEARCH pipelines demonstrated the former outperformed the other taxonomic profilers as it generated significantly higher Spearman correlation coefficients across all 16S regions tested (FIG. 2B). Using an independent method of hierarchical clustering, it was further demonstrated that only Taxa4Meta profiles clustered with ground truth input profiles (FIG. 11A), whereas the other taxonomic profilers failed to detect a significant number of families across the four 16S regions tested, i.e., >30% of families were not detected compared with 0.4% omitted by Taxa4Meta (FIG. 11B). The results highlight the utility of Taxa4Meta in generating accurate taxonomic profiles of complex microbiome communities, and this is evident down to species-rank as demonstrated for the detection of C. difficile, a pathogen required for the clinical diagnosis of CDI (FIG. 11C and FIG. 22).

To investigate how Taxa4Meta performed with real-world microbiome datasets, the inventors benchmarked different 16S pipelines using a South Korean cohort of healthy subjects where individual fecal DNA extract underwent comprehensive 16S profiling and shotgun metagenomic sequencing¹². As the inventors observed using complex simulated microbiome communities. Taxa4Meta family-rank profiles clustered together with Kraken2-generated annotations which are regarded as a gold standard reference method because of its high family-rank taxonomic accuracy using metagenomic data¹³(FIG. 2C). By adopting an independent method of pairwise abundance-weighted Jaccard distance calculations. Taxa4Meta profiles further demonstrated the best close distance to Kraken2 profile (FIG. 2D), and this was consistently observed across all 16S data types investigated regardless of sequencing depth (FIGS. 12A-12D). The inventors also evaluated the accuracy of Taxa4Meta species-rank profiles compared with MetaPhlAn2-generated taxonomy as this has higher precision than Kraken2 in avoiding species misclassification¹⁴. Taxa4Meta stringently controls for species misclassification (FIG. 13). Collectively, the findings show that collapsed taxonomic profiles generated by Taxa4Meta are highly accurate and suitable for 16S meta-analysis of amplicon data generated from diverse sequencing strategies.

Example 5—Population-Scale Meta-Analysis to Define the Healthy Human Gut Microbiome

Defining the healthy human gut microbiome remained a major challenge because it is influenced by many individual factors, including age, genetics, diet, environment, lifestyle and transmission². In addition to these influences, discordant analytical methods and small cohort sizes are important determinants in how to reliably chose to characterize the healthy human microbiome. The inventors applied the Taxa4Meta pipeline to perform a meta-analysis of diverse 16S regions and sequencing platforms to identify common microbiome features in over 900 subjects with no documented gastrointestinal disease across North America. Europe. Asia and Australasia (Table 21). The inventors further compared taxonomic profiles of control subjects with over 13.000 participants in the American Gut Project¹⁵and LifeLines cohorts¹⁶. Using Bray-Curtis dissimilarity distance based β-diversity analysis, it was shown that control subjects sequenced across diverse technology platforms shared a similar sample distribution or microbiome variation pattern with American Gut at both genus- and family-rank abundance profiles (FIGS. 14A-14B). Because the inventors identified a significant enterotype bias when comparing American Gut or meta-analysis controls with the European LifeLines cohort, they designed the meta-analysis to include study controls that spanned all the major classical gut enterotypes in order to facilitate accurate downstream disease classification at a population-scale level. Non-Prevotella enterotypes dominated by Bacteroidaceae, Lachnospiracede and Ruminicoccacede represented the healthy gut microbiome in controls from the 16S meta-analysis cohorts (FIGS. 14A-14B). The inventors further identified some outlier controls that were dominated by high abundance of pathobiome, defined as the presence of Enterococcus. Streptococcus, Clostridioides, Escherichia/Shigella, Salmonella, Klebsiella and Pseudomonas (FIGS. 3A-3B). Given that Prevotella and pathobiome-dominated gut microbiota are associated with chronic inflammatory conditions^5,17,18, the results highlight the need for population-scale analyses to consider enterotypes and pathobiome when defining the healthy human microbiome, especially in the context of dysbiosis-associated gastrointestinal disease.

Example 6—Dysbiosis in Chronic Human Diarrheal Disease

Using the Taxa4Meta pipeline, the inventors analyzed fecal microbiome data sequenced over multiple 16S regions on Illumina and 454 pyrosequencing platforms, analyzing over 5,500 matched controls and clinically confirmed diarrheal patients with CDI, IBD, IBS, and non-IBS functional gastrointestinal disorders (FGID) from North America. Europe. Asia and Australasia. α-Diversity indices calculated from Taxa4Meta OTU tables were significantly lower in CDI cases compared with controls or other diarrheal diseases (FIG. 15A), but this was an inconsistent feature among clinical cohorts sequenced across different 16S regions (FIG. 15B). In agreement with prior studies^5,18, the abundance of Enterobacteriaceae and Enterococcacede were significantly elevated in CDI and CD patients compared with matched controls or IBS and UC cases (FIG. 3C and FIG. 16). Collapsed species profiles generated by Taxa4Meta contained classified and unclassified members representing 54% and 46% of total abundance, respectively (FIG. 17), allowing confident assignment of species calls for further data mining. Abundance-weighted Jaccard distance based β-diversity analysis demonstrated a healthy-like microbiome community structure in IBS and UC patients, whereas significant dysbiosis was consistently detected in CDI and CD cases (FIGS. 3A-3B). This observation is in agreement with prior case-control matched studies¹⁹that reported subtle microbiome differences in IBS and FGID patients when compared to healthy controls (FIG. 16). By contrast, the inventors found that CDI and CD patients were readily distinguished from other diarrheal diseases by the abundance of pathobiome (FIGS. 3A-3B), a reflection of gut dysbiosis favoring engraftment and expansion of potential pathogens. Pathobiome-dominated enterotypes found in CD and CDI patients are primarily composed of Enterobacteriaceae and Enterococcaccae, which were shown to occur independently of 16S region, sequencing platforms, age or geography (FIG. 16). Thus, calculation of specific β-diversity distance metrics and pathobiome abundance become useful tools in defining the core microbiome features of specific diarrheal disease types.

Using hierarchical clustering analysis for family abundance profiles the inventors demonstrated that 4 out of 8 UC cohorts were clustered together with control and IBS patients, whereas the remaining UC cohorts and the majority of CD cohorts formed a unique IBD-specific cluster (FIG. 16). This finding was not recapitulated by the microbiome meta-analysis conducted by Duvallet et al.²⁰because UC and CD patients were grouped together for microbiome comparisons against controls. A recent systematic literature review highlighted the significant decrease of Faecalibacterium prausnitzii, an anti-inflammatory gut commensal in both UC and CD patients⁵. The inventors confirmed this finding in their meta-analysis of CD and UC cases (Tables 9-17), but failed to demonstrate significant alterations in Eubacterium rectale and Escherichia abundance in UC patients as previously reported⁵, which could reflect microbiome variations seen in UC cohorts as demonstrated in the meta-analysis. Several novel top ranked disease-associated species were identified including Fusicatenibacter saccharivorans (Control-specific), and Bacteroides xylanisolvens and Romboutsia timonensis (less prevalent in IBD) which have not been reported in previous studies. Other unique findings included decreases in Anaerostipes hadrus and Eubacterium rectale in CDI patients only (Tables 9-17), these features were exploited develop disease-specific classifiers.

Example 7—Pan-Microbiome Profiling Outperforms Individual 16S Region-Specific or Platform-Specific Analysis for Disease Classification

Disease classification is an important emerging application of gut microbiome surveys for biomarker discovery. Because the utility of pan-microbiome profiling had not yet been tested for disease classification, the inventors explored whether this approach improved classifier scores by merging core microbiome communities corrected for demographic and technical bias. In pilot studies using different sequencing modalities, the inventors benchmarked the center HMP cohort of pediatric FGID cases profiled by 16S VIV3 and V3V5 amplicons generated on the 454 pyrosequencing platform²¹. Analysis of β-diversity from collapsed Taxa4Meta taxonomy profiles did not separate FGID cases from healthy controls (FIG. 4A), and not surprisingly a suboptimal classification accuracy (CA<0.85) was evident when profiling individual VIV3 and V3V5 datasets (FIG. 4B). Using feature ranking generated by the random forest algorithm, the inventors selected >85% of genera abundance features that were common to both 16S regions, which identified previously underappreciated Roseburia as a core microbiome genus feature that discriminates between FGID and healthy controls (FIG. 18). Supervised training of pan-microbiome profiles significantly improved the classification accuracy when compared with individual microbiome surveys (FIG. 4B).

In further support, the inventors tested amplicon data generated from multiple CDI cohorts with sequence deposited from different 16S regions and technology platforms (Table 21). Unlike the subtle microbiome community differences observed in FGID cases. CDI patients present with consistent extreme dysbiosis that is evident across multiple sequencing strategies (FIG. 4C). Using a similar approach as above, platform-specific classification models performed well when differentiating CDI from Controls during training procedures, but failed to cross-validate subjects across different sequencing platforms and represents a major limitation for meta-analysis. This classification inaccuracy was eliminated by using pan-microbiome patterns for training (FIG. 4D), as it minimizes the impact of pattern variation and retains common microbiome features to facilitate biomarker discovery.

Example 8—Utility of Pan-Microbiome Features for Diarrheal Disease Classification

Two strategies were employed to generate comprehensive and binary disease classification models based on pan-microbiome profiles (FIG. 5A). Using Taxa4Meta taxonomic profiles, the inventors identified several key features including C. difficile (FIG. 5B) as the top discriminative feature that is pathophysiologically relevant in differentiating CDI from other diarrheal subtypes. This top-ranking feature was not identified as a classifier in two prior microbiome meta-analyses highlighting the technical bias in prior studies^20,22. Notably, the top Taxa4meta collapsed species significantly outperformed discriminative PICRUSt2 pathway features in comprehensive disease classification models (FIGS. 21A-21B). Taxa-based classification models for the five clinical groups investigated (Control. CDI. IBS. IBD UC and IBD CD) demonstrated excellent AUC results, but moderate CA scores indicating that disease classification across all cohort groups is suboptimal (FIG. 6C). This underperformance could be accounted for by the similarity of microbiome features in Control, UC, and IBS subjects, representing a challenge for reliable cross-classification (FIGS. 3A-3C). Nevertheless, in contrast to the multiple-group classification, binary models provided excellent disease classification with improved AUC and CA scores (FIG. 5C). Similar to the comprehensive classification models, binary disease classification using Taxa4meta collapsed species profiles outperformed discriminative functional pathways independent of learning algorithms used (FIGS. 21A-21B). Of note. CDI versus IBD/IBS/Control demonstrated consistently high classification accuracy (>0.9) at both taxonomic and functional levels (FIG. 24). These findings represent a significant advance in diarrheal disease classification, and highlight that compositionally distinct microbiome communities are discernable between infectious colitis (CDI) and IBD/IBS patients.

Example 9—Prototypical Workflow for Clinical Diarrheal Disease Classification

With the urgent need to differentiate common symptoms in CDI. IBD and IBS, the inventors assembled a prototypical workflow to assist in stratifying these patients based on the disclosed Taxa4Meta-generated binary algorithms and/or features (FIG. 6A and Tables 1-17). Diagnosing CDI first was prioritized based on the clinical necessity for rapid treatment and patient contact-isolation. By applying a binary classifier that differentiated CDI from IBD and IBS cases, the inventors demonstrated a classification accuracy of 0.95 (FIG. 6A). A second binary classifier can then be applied that differentiated IBD from IBS cases with an overall classification accuracy of 0.96 (FIG. 6A). To independently validate the diagnostic workflow, the inventors tested 16S data generated from (1) recently published clinical CDI, IBD and IBS microbiome cohorts, and (2) real-world data obtained from self-reported IBD and IBS cases in the American Gut and LifeLines population cohorts. The identified features/classifiers correctly identified 93.6% of CDI patients, with the accuracy of 0.97 in differentiating clinically confirmed IBD versus IBS cases (FIG. 6B). These independent validation cohorts provide strong proof-of-concept data for pan-microbiome based classification in developing companion diagnostic workflows for diarrheal disease stratification.

Example 10—Predictive Functional Analysis Highlights Disease-Specific Biochemical Pathways

PICRUSt2 pathway profiles generated from Taxa4Meta OTU tables were used to characterize disease-specific core microbiome functions compared with healthy controls. Using a combination of LEfSe analysis and feature-scoring by the random forest algorithm, the inventors ranked biochemical pathways that were significantly associated with specific diarrheal disease types (FIGS. 23A-23E and Tables 1-8). The inventors identified a CDI-specific pathway cluster including ECASYN-PWY, PPGPPMET-PWY, PWY0-1338, AST-PWY and THREOCAT-PWY (FIG. 19). Polymyxin resistance (PWY0-1338) represented a strong CDI signature associated with pathobiome abundance, and is typically enriched after antibiotic exposure. Polymyxin is an antibiotic of last resort used to treat multi-drug resistant Gram-negative bacterial infections in patients who are later at high risk of developing CDI. Menaquinone biosynthetic pathways (PWY-7374, PWY-7371 and PWY-6263) were significantly underrepresented in CDI compared with Controls (FIG. 19 and FIGS. 23A-23E), reflecting the decreased abundance of healthy-associated Gram-positive bacteria in CDI, Menaquinones are important vitamin K2 based growth factors for many Gram-positive, obligate anaerobic gut bacteria. By contrast, these biosynthetic pathways were significantly elevated in IBC UC representing unique pathway signatures for IBD subtype classification (FIG. 19). Although beta-diversity distance profiles were not significant differentiated between IBD UC and controls (FIGS. 3A-3B), several other functional pathways were also significantly altered in IBD UC patients (FIG. 23C). Notably, simple saccharide catabolic pathways were highly enriched in IBD UC patients (Tables 1-8), which is supportive of clinical recommendations for IBD patients to avoid simple saccharides. These pathways are associated with increased disease severity in IL-10 deficient mice receiving dietary glucose and fructose. Nitrate reduction pathways were also significantly elevated in IBC UC patients (Tables 1-8), a function known to correlate with colitis risk in patients and IL-10 deficient mice. Dietary and host-derived nitrate also confers growth benefit to pathobiome expansion of Enterobacteriaceae in chemical-induced colitis. In bacteria, nitrate is reduced to nitrite followed by ammonia production, which ultimately serves as substrate for glutamate and glutamine biosynthesis as important carbon and nitrogen sources for gut microbiota. Thus, L-glutamate and L-glutamine biosynthesis (PWY-5505) is an important metabolic pathway for ammonia assimilation and this pathway was elevated in both IBD UC and IBD CD patients (FIG. 19), confirming previous reports linking clinical IBD disease severity with nitrogen reduction and ammonia production. In general, the findings are in agreement with several clinical and mouse models of nitrate metabolism by the IBD microbiota.

The disclosed meta-analysis also identified IBD-specific pathway clusters (FIG. 19 and FIG. 23E). For example, heme biosynthesis (HEMESYN2-PWY) was significantly enriched in IBD UC and IBD CD microbiomes, where heme supplementation is reported to exacerbate colitis in mouse and rat IBD models. Sulfur oxidation (PWY-5304) required by methanogenic archaca for sulfate production was also enriched in IBD-associated microbiome. In addition to the detection of methanogenic archaca retained as a feature for downstream analysis by Taxa4Meta, the IBD-associated microbiome is reported to be enriched in bacterial sulfate reducers, e.g. Desulfovibrio that convert sulfate to pathogenic hydrogen sulfide. Contrasting L-threonine metabolic pathways distinguished CDI from IBD-associated microbiomes, the former being enriched for catabolism (THREOCAT-PWY) whereas the latter facilitated biosynthesis (THRESYN-PWY) (FIG. 19). Increased threonine biosynthesis by IBD-associated microbiota has been implicated in impaired disease recovery, supported by L-threonine supplementation inhibiting mucosal healing in colitis models. Taken together, the utility of predictive metagenome functions based on population-scale microbiome profiles to exploit diarrheal-specific metabolic potential for biomarker discovery and disease classification is demonstrated.

Example 11—Enterotypes Impact Disease Classification Performance

The population-scale meta-analysis described herein demonstrated the existence of different enterotypes that dominate across continents (FIG. 16), with three classical community types formed as previously reported. As demonstrated above, classification models constructed using pan-microbiome profile were expected to minimize enterotype bias. To test this, first a DMM algorithm for clustering all meta-analysis samples was applied, and identified five clusters (FIG. 20A). DMM clusters 1, 2 and 3, commonly observed in Control. IBS and UC (FIG. 20B), were easily distinguished from clusters 4 and 5 with the dominance of Enterobacteriaceae and Prevotellaceae, respectively. Next, the inventors investigated whether enterotype mismatching impacts classification performance. To minimize the classification variation introduced by small sample size, samples of DMM clusters 1, 2 and 3 were combined as one super-cluster, whereas DMM clusters 4 and 5 were combined as another super-cluster. To balance sample size for enterotype-specific comparisons, the inventors applied stratified, random sub-sampling procedure with a total of 10 iterations to sample subjects from two super-clusters to form cluster-specific dataset Sets A and B, and two pan-microbiome Sets C and D for downstream supervised classification analyses (FIG. 20C). While drastic differences in AUC and CA scores for either cluster-specific or pan-microbiome sample datasets were not observed, pan-microbiome disease classifiers demonstrated significantly improved CA scores during independent validation procedure when compared to cluster-specific disease classifiers (FIG. 20D). Although the analysis was not sufficiently powered to perform disease-specific comparisons, the findings are significant as they demonstrate that enterotype-bias represents an important consideration when developing universal microbiome-based disease classification models.

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