Patent Application
20240304276
The present invention relates to a method of determining an infection of a patient with at least one microorganism, particularly a bacterial microorganism, potentially resistant to antimicrobial drug treatment, a method of selecting a treatment of a patient suffering from an infection with at least one microorganism, particularly bacterial microorganism, and a method of determining structural changes of the genome of the microorganism, particularly bacterial microorganism, comprising at least one gene, as well as computer program products used in these methods.
Antibiotic resistance is a form of drug resistance whereby a sub-population of a microorganism, e.g. a strain of a bacterial species, can survive and multiply despite exposure to an antibiotic drug. It is a serious health concern for the individual patient as well as a major public health issue. Timely treatment of a bacterial infection requires the analysis of clinical isolates obtained from patients with regard to antibiotic resistance, in order to select an efficacious therapy. Generally, for this purpose an association of the identified resistance with a certain microorganism (i.e. ID) is necessary.
Antibacterial drug resistance (ADR) represents a major health burden. According to the World Health Organization's antimicrobial resistance global report on surveillance, ADR leads to 25,000 deaths per year in Europe and 23,000 deaths per year in the US. In Europe, 2.5 million extra hospital days lead to societal cost of 1.5 billion euro. In the US, the direct cost of 2 million illnesses leads to 20 billion dollar direct cost. The overall cost is estimated to be substantially higher, reducing the gross domestic product (GDP) by up to 1.6%.
In general the mechanisms for resistance of bacteria against antimicrobial treatments rely to a very substantial part on the organism's genetics. The respective genes or molecular mechanisms are either encoded in the genome of the bacteria or on plasmids that can be interchanged between different bacteria. The most common resistance mechanisms include:
1) Efflux pumps are high-affinity reverse transport systems located in the membrane that transports the antibiotic out of the cell, e.g. resistance to tetracycline.
2) Specific enzymes modify the antibiotic in a way that it loses its activity. In the case of streptomycin, the antibiotic is chemically modified so that it will no longer bind to the ribosome to block protein synthesis.
3) An enzyme is produced that degrades the antibiotic, thereby inactivating it. For example, the penicillinases are a group of beta-lactamase enzymes that cleave the beta lactam ring of the penicillin molecule.
In addition, some pathogens show natural resistance against drugs. For example, an organism can lack a transport system for an antibiotic or the target of the antibiotic molecule is not present in the organism.
Pathogens that are in principle susceptible to drugs can become resistant by modification of existing genetic material (e.g. spontaneous mutations for antibiotic resistance, happening in a frequency of one in about 100 mio bacteria in an infection) or the acquisition of new genetic material from another source. One example is horizontal gene transfer, a process where genetic material contained in small packets of DNA can be transferred between individual bacteria of the same species or even between different species. Horizontal gene transfer may happen by transduction, transformation or conjugation.
Generally, testing for susceptibility/resistance to antimicrobial agents is performed by culturing organisms in different concentrations of these agents.
In brief, agar plates are inoculated with patient sample (e.g. urine, sputum, blood, stool) overnight. On the next day individual colonies are used for identification of organisms, either by culturing or using mass spectroscopy. Based on the identity of organisms new plates containing increasing concentration of drugs used for the treatment of these organisms are inoculated and grown for additional 12-24 hours. The lowest drug concentration which inhibits growth (minimal inhibitory concentration-MIC) is used to determine susceptibility/resistance for tested drugs. The process takes at least 2 to 3 working days during which the patient is treated empirically. Automated systems exist from several companies, e.g. Biomeriux (Vitek), Beckman Coulter (Microscan). A significant reduction of time-to-result is needed especially in patients with life-threatening disease and to overcome the widespread misuse of antibiotics.
Recent developments include PCR based test kits for fast bacterial identification (e.g. Biomerieux Biofire Tests, Curetis Unyvero Tests). With these test the detection of selected resistance loci is possible for a very limited number of drugs, but no correlation to culture based AST is given. Mass spectroscopy is increasingly used for identification of pathogens in clinical samples (e.g. Bruker Biotyper), and research is ongoing to establish methods for the detection of susceptibility/resistance against antibiotics.
The use of molecular techniques for direct detection of MRSA has become more commonplace especially for screening purposes. Resistance to methicillin is mediated via the mec operon which is part of the staphylococcal cassette chromosome mec (SCCmec). Recently PCR tests were introduced that are based on the detection of the right extremity sequence of the SCCmec in combination with S. aureus specific marker. Initial reports exist that describe culture based susceptibility reports despite detection of the presence of a resistance conferring gene.
For some drugs such it is known that at least two targets are addressed, e.g. in case of Ciprofloxacin (drug bank ID 00537; http://www.drugbank.ca/drugs/DB00537) targets include DNA Topoisomerase IV, DNA Topoisomerase II and DNA Gyrase. It can be expected that this is also the case for other drugs although the respective secondary targets have not been identified yet. In case of a common regulation, both relevant genetic sites would naturally show a co-correlation or redundancy.
It is known that drug resistance can be associated with genetic polymorphisms. This holds for viruses, where resistance testing is established clinical practice (e.g. HIV genotyping). More recently, it has been shown that resistance has also genetic causes in bacteria and even higher organisms, such as humans where tumors resistance against certain cytostatic agents can be linked to genomic mutations.
Wozniak et al. (BMC Genomics 2012, 13 (Suppl 7):S23) disclose genetic determinants of drug resistance in Staphylococcus aureus based on genotype and phenotype data. Stoesser et al. disclose prediction of antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data (J Antimicrob Chemother 2013; 68: 2234-2244).
Chewapreecha et al (Chewapreecha et al (2014) Comprehensive Identification of single nucleotid polymorphisms associated with beta-lactam resistance within pneumococcal mosaic genes. PLOS Genet 10 (8): e1004547) used a comparable approach to identify mutations in gram-positive Streptococcus Pneumonia.
In recent studies, genetic tests are taken into account that consider variations in the genome of a microorganism, e.g. a bacterial microorganism. In previous works it could be shown that a faster decision for a treatment could be made using changes in single bases. However, this does not necessarily apply to all antimicrobial drugs, e.g. antibiotics, tested.
The fast and accurate detection of infections with microorganisms, particularly microbial species, e.g. Staphylococcus aureus, and the prediction of response to antimicrobial therapy represent a high unmet clinical need.
This need is addressed by the present invention.
The inventors found out that structural variations in the genome that relate to more than one base, particularly at least one gene or more genes in an open reading frame can be related to resistance/susceptibility of microorganisms, particularly bacterial microorganisms, to antimicrobial, e.g. antibiotic, drugs. For example, an efflux pump can be present on a plasmid additionally in a genome. Such efflux pump then can transport a medicine/drug like an antibiotic out of the organism, so that it cannot be effective. Thus, a bacterium having such efflux pump on a plasmid is resistant.
According to a first aspect, the present invention relates to a method of determining structural variations in a genome of a microorganism, particularly a bacterial microorganism, comprising at least a change in the genome comprising more than one base, comprising:
A second aspect of the present invention relates to a diagnostic method of determining an infection of a patient with a microorganism, particularly a bacterial microorganism potentially resistant to antimicrobial drug treatment, comprising the steps of:
A third aspect of the present invention relates to a method of selecting a treatment of a patient suffering from an infection with a potentially resistant microorganism, particularly bacterial microorganism, comprising the steps of:
A fourth aspect of the present invention relates to a method of determining structural variations of a genome of a microorganism for a clinical isolate of the microorganism, particularly a bacterial microorganism, comprising: obtaining or providing at least one gene sequence of the clinical isolate of the microorganism, particularly the bacterial microorganism; and
determining the presence of structural variations in the at least one gene sequence of the clinical isolate of the microorganism, particularly bacterial microorganism, as determined by the method of the first aspect.
In a fifth aspect the present invention relates to one or more computer program products comprising computer executable instructions which, when executed, perform a method according to any one of the first to the fourth aspect of the present invention.
Further aspects and embodiments of the invention are disclosed in the dependent claims and can be taken from the following description, figures and examples, without being limited thereto.
The enclosed drawings should illustrate embodiments of the present invention and convey a further understanding thereof. In connection with the description they serve as explanation of concepts and principles of the invention. Other embodiments and many of the stated advantages can be derived in relation to the drawings. The elements of the drawings are not necessarily to scale towards each other. Identical, functionally equivalent and acting equal features and components are denoted in the figures of the drawings with the same reference numbers, unless noted otherwise.
Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
An “antimicrobial drug” in the present invention refers to a group of drugs that includes antibiotics, antifungals, antiprotozoals, and antivirals. According to certain embodiments, the antimicrobial drug is an antibiotic.
The term “nucleic acid molecule” refers to a polynucleotide molecule having a defined sequence. It comprises DNA molecules, RNA molecules, nucleotide analog molecules and combinations and derivatives thereof, such as DNA molecules or RNA molecules with incorporated nucleotide analogs or cDNA.
The term “nucleic acid sequence information” relates to an information which can be derived from the sequence of a nucleic acid molecule, such as the sequence itself or a variation in the sequence as compared to a reference sequence.
The term “mutation” relates to a variation in the sequence as compared to a reference sequence. Such a reference sequence can be a sequence determined in a predominant wild type organism or a reference organism, e.g. a defined and known bacterial strain or substrain. A mutation is for example a deletion of one or multiple nucleotides, an insertion of one or multiple nucleotides, or substitution of one or multiple nucleotides, duplication of one or a sequence of multiple nucleotides, translocation of one or a sequence of multiple nucleotides, e.g. also a single nucleotide polymorphism (SNP).
In the context of the present invention a “sample” is a sample which comprises at least one nucleic acid molecule from a bacterial microorganism. Examples for samples are: cells, tissue, body fluids, biopsy specimens, blood, urine, saliva, sputum, plasma, serum, cell culture supernatant, swab sample and others. According to certain embodiments, the sample is a patient sample (clinical isolate).
New and highly efficient methods of sequencing nucleic acids referred to as next generation sequencing have opened the possibility of large scale genomic analysis. The term “next generation sequencing” or “high throughput sequencing” refers to high-throughput sequencing technologies that parallelize the sequencing process, producing thousands or millions of sequences at once. Examples include Massively Parallel Signature Sequencing (MPSS), Polony sequencing, 454 pyrosequencing, Illumina (Solexa) sequencing, SOLID sequencing, Ion semiconductor sequencing, DNA nanoball sequencing, Helioscope™ single molecule sequencing, Single Molecule SMRT™ sequencing, Single Molecule real time (RNAP) sequencing, Nanopore DNA sequencing, Sequencing By Hybridization, Amplicon Sequencing, GnuBio.
Within the present description the term “microorganism” comprises the term microbe. The type of microorganism is not particularly restricted, unless noted otherwise or obvious, and, for example, comprises bacteria, viruses, fungi, microscopic algae und protozoa, as well as combinations thereof. According to certain aspects, it refers to one or more bacterial species, being either Gram-negative or Gram-positive, particularly one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species.
A reference to a microorganism or microorganisms in the present description comprises a reference to one microorganism as well a plurality of microorganisms, e.g. two, three, four, five, six or more microorganisms.
A vertebrate within the present invention refers to animals having a vertebrae, which includes mammals-including humans, birds, reptiles, amphibians and fishes. The present invention thus is not only suitable for human medicine, but also for veterinary medicine.
According to certain embodiments, the patient in the present methods is a vertebrate, more preferably a mammal and most preferred a human patient.
Before the invention is described in exemplary detail, it is to be understood that this invention is not limited to the particular component parts of the process steps of the methods described herein as such methods may vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only, and is not intended to be limiting. It must be noted that, as used in the specification and the appended claims, the singular forms “a,” “an” and “the” include singular and/or plural referents unless the context clearly dictates otherwise. For example, the term “a” as used herein can be understood as one single entity or in the meaning of “one or more” entities. It is also to be understood that plural forms include singular and/or plural referents unless the context clearly dictates otherwise. It is moreover to be understood that, in case parameter ranges are given which are delimited by numeric values, the ranges are deemed to include these limitation values.
Regarding the dosage of the antimicrobial, e.g. antibiotic, drugs, it is referred to the established principles of pharmacology in human and veterinary medicine. For example, Forth, Henschler, Rummel “Allgemeine und spezielle Pharmakologie und Toxikologie”, 9th edition, 2005 might be used as a guideline. Regarding the formulation of a ready-to-use medicament, reference is made to “Remington, The Science and Practice of Pharmacy”, 22nd edition, 2013.
Assembling of a gene sequence can be carried out by any known method and is not particularly limited.
According to certain embodiments, mutations that were found using alignments can also be compared or matched with alignment-free methods, e.g. for detecting single base exchanges, for example based on contigs that were found by assemblies. For example, reads obtained from sequencing can be assembled to contigs and the contigs can be compared to each other.
A structural variation comprising a change in the genome comprising more than one base refers to a structural variation wherein at least two bases in a gene sequence of a genome of a microorganism that are adjacent are changed, and can refer to e.g. a deletion of multiple (2 or more) nucleotides, an insertion of multiple (2 or more) nucleotides, a substitution of multiple (2 or more) nucleotides, a duplication of a sequence of multiple (2 or more) nucleotides, or a translocation of a sequence of multiple (2 or more) nucleotide. According to certain embodiments, a structural variation can comprise bigger parts sections of the genome, e.g. at least one whole gene in the genome of the microorganism, or even more genes in an open reading frame.
In the present invention, not specific changes of single nucleotides are determined, but a determination is based on bigger parts of the genome, as above.
In the present invention, a reference sequence is not particularly limited, as long as it is useful as a reference for one or more unknown gene sequences in one or more samples, It can for example be one or more reference genomes, a pan genome or one or more centroids. According to certain embodiments, the reference sequences comprise one or more centroids, wherein a centroid is a representative of a gene group/family/cluster of a genome, e.g. of a microorganism. Centroids can be for example extracted from the database MetaRef (http://metaref.org/), which was used in the present examples, with the extraction from the data base being carried out particularly on Nov. 24, 2014. After the extraction the data from the MetaRef database can be updated continually for further experiments. A list of centroids can be extracted for each organism separately or as a whole. In the present examples a list of centroids was extracted for each organism. The centroid information, e.g. for annotation, can be extracted from databases like IMG (http://img.jgi.doe.gov/), as in the present case, or NCBI.
According to a first aspect, the present invention relates to a method of determining structural variations in a genome of a microorganism, particularly a bacterial microorganism, comprising at least a change in the genome comprising more than one base, comprising:
In this method, as well as the other methods of the invention, the first data set of gene sequences of a plurality of clinical isolates can be provided or obtained in any way, preferably non-invasive, and can be e.g. provided from in vitro samples.
According to certain embodiments, the obtaining or providing of gene sequences of a plurality of clinical isolates in this method—as well as the other methods of the invention—can comprise the following:
A sample of a vertebrate, e.g. a human, e.g. is provided or obtained and nucleic acid sequences, e.g. DNA or RNA sequences, are recorded by a known method for recording nucleic acid, which is not particularly limited. For example, nucleic acid can be recorded by a sequencing method, wherein any sequencing method is appropriate, particularly sequencing methods wherein a multitude of sample components, as e.g. in a blood sample, can be analyzed for nucleic acids and/or nucleic acid fragments and/or parts thereof contained therein in a short period of time, including the nucleic acids and/or nucleic acid fragments and/or parts thereof of at least one microorganism of interest, particularly a bacterial microorganism. For example, sequencing can be carried out using polymerase chain reaction (PCR), particularly multiplex PCR, or high throughput sequencing or next generation sequencing, preferably using high-throughput sequencing. For sequencing, preferably an in vitro sample is used.
The data obtained by the sequencing can be in any format, and can then be used to identify the nucleic acids of the microorganism to be identified, by known methods, e.g. fingerprinting methods, comparing genomes and/or aligning to at least one, or more, reference sequences of one or more species of the microorganism of interest, e.g. a reference genome and/or centroids, etc., forming a third data set of, optionally aligned, genes for a microorganism-discarding additional data from other sources, e.g. the vertebrate. For the present method, also the raw data can be used and/or assemblies, at least in part, can be used for forming the third data set. Thus, according to certain embodiments, at least a part of the gene sequences of the first data set can be assembled, wherein assembly can be carried out by any known method and is not particularly limited. In addition, also data from reference sequences, e.g. centroids and/or genomes of known species, e.g. from bacterial species that are already known, e.g. from databases like MetaRef and/or at the NCBI, can be used in the first data set and/or for evaluation of the first data set.
For some organisms, it might be useful in genome-wide association studies to reference the points of interest, e.g. structural variations, to one constant reference for enhanced standardization. In case of the human with a high consistency of the genome and 99% identical sequences among individuals this is easy and represents the standard, as corresponding reference genomes are available in databases.
In case of organisms that trigger infectious diseases (e.g. bacteria and viruses) this is much more difficult, though, and particularly also genetic variations that are not on genes, particularly known genes, can be missed when aligning sequence data to a reference genome. One possibility to overcome this is to fall back on a virtual pan-genome which contains all sequences of a certain genus or to perform reference free variation calling. A further possibility is the analysis of a huge amount of reference sequences, e.g. from MetaRef, and even all available references, which is much more complex. Therein all n references from a database (e.g. RefSeq) are extracted and compared with the newly sequenced bacterial genomes k. After this, matrices (% of mapped reads, % of covered genome) can be applied and the data can be compared to several reference sequences. In such a case, n×k complete alignments are carried out. Having a big number of references, stable results can be obtained.
In the present method, gene sequence of the first data set can also be assembled, at least in part, according to certain embodiments with known methods, e.g. by de-novo assembly or mapping assembly. The sequence assembly is not particularly limited, and any known genome assembler can be used, e.g. based on Sanger, 454, Solexa, Illumina, SOLid technologies, etc., as well as hybrids/mixtures thereof.
According to certain embodiments, the data of nucleic acids of different origin than the microorganism of interest, e.g. a bacterial microorganism, can be removed after the nucleic acids of interest are identified, e.g. by filtering the data out. Such data can e.g. include nucleic acids of a patient, e.g. the vertebrate, e.g. human, and/or other microorganisms, etc. This can be done by e.g. computational subtraction, as developed by Meyerson et al. 2002. For this, also aligning to the genome of the vertebrate, etc., is possible. For aligning, several alignment-tools are available. This way the original data amount from the sample can be drastically reduced.
After such removal of “excess” data, obtaining the third data set can be carried out for the microorganism, e.g. a bacterial microorganism, as described above.
Using these techniques, structural variations in the genome, e.g. in the gene sequences, of the microorganism of interest, e.g. a bacterial microorganism, can be obtained for various species.
When testing these same species for antimicrobial drug, e.g. antibiotic, susceptibility of a number of antimicrobial drugs, e.g. antibiotics, e.g. using standard culturing methods on dishes with antimicrobial drug, e.g. antibiotic, intake, as e.g. described below, the results of these antimicrobial drug, e.g. antibiotic, susceptibility tests can then be cross-referenced/correlated with the structural variations in the genome of the respective microorganism. Using several, e.g. 50 or more than 50, 100 or more than 100, 200 or more than 200, 400 or more than 400, 800 or more than 800, or 900 or more than 900 different isolates of the same or different species of a microorganism, statistical analysis can be carried out on the obtained cross-referenced data between genetic variations and antimicrobial drug, e.g. antibiotic, susceptibility for these microorganisms, using known methods.
Regarding culturing methods, samples of microorganisms can be e.g. cultured overnight. On the next day individual colonies can be used for identification of organisms, either by culturing or using mass spectroscopy. Based on the identity of organisms new plates containing increasing concentration of antibiotics used for the treatment of these organisms are inoculated and grown for additional 12-24 hours. The lowest drug concentration which inhibits growth (minimal inhibitory concentration-MIC) can be used to determine susceptibility/resistance for tested antibiotics.
Also, resistance testing can be carried out by determining e.g. known resistance genes in the different isolates, like in case of methicillin resistant Staphylococcus aureus (MRSA) and methicillin susceptible Staphylococcus aureus (MSSA). For determining resistances, respectively susceptibility, the data from culturing methods and/or from determining known resistance genes, as well as data obtained in different ways, e.g. based on mass spectrometry (possibly also in connection with culturing) can be used.
Correlation of the genetic variations with antimicrobial drug, e.g. antibiotic, resistance can be carried out in a usual way and is not particularly limited. For example, resistances can be correlated to structural variances in the whole genome of the respective microorganism or only parts thereof, for example only coding parts of the genome. In some cases even only genetic variations in genes, e.g. certain genes, or certain mutations in genes can be determined. After correlation, statistical analysis can be carried out.
According to certain embodiments, the data of the first data set can be filtered prior to a possible annotation to a pan-genome and/or reference genome(s) and the correlation with the resistance/susceptibility data.
For example, to reduce the number of similar annotations they can be filtered and aggregated by one or more of the following:
Also, according to certain embodiments, the following structural variations can be excluded:
For statistical analysis, as in the examples, e.g. Fisher's exact two-sided test can be applied with subsequent p-value adjustment over all phenotypes together using FDR and p-value threshold of 0.01 (1e-2). Additionally, 10 permutation tests can be performed by permuting each phenotype separately and applying Fisher's exact test to the centroid presence matrix and permuted phenotypes. The results then can be further filtered by centroid annotation, i.e.
According to certain embodiments, the structural variations can be annotated to a pan-genome of the microorganism and/or annotated to one or more reference sequences, e.g. centroids, of the microorganism. The construction of a pan-genome is not particularly limited and can be done using known methods.
However, other suitable reference genomes (e.g. used in the Examples, but also for other microorganisms) can be found at publicly available data bases like at the NCBI or from MetaRef.
Statistical analysis of the correlation of the gene mutations with antimicrobial drug, e.g. antibiotic, resistance is not particularly limited and can be carried out, depending on e.g. the amount of data, in different ways, for example using analysis of variance (ANOVA), Student's t-test or Fisher's exact test, for example with a sample size n of 50, 100, 200, 300, 400, 500 or 600, and a level of significance (α-error-level) of e.g. 0.05 or smaller, e.g. 0.05, preferably 0.01 or smaller. A statistical value can be obtained for each structural variation and/or each genetic sequence in the genome as well as for all antibiotics tested, a group of antibiotics or a single antibiotic. The obtained p-values can also be adapted for statistical errors, if needed.
For statistically sound results a multitude of individuals should be sampled, with n=50, 100, 200, 300, 400, 500 or 600, and a level of significance (α-error-level) of e.g. 0.05 or smaller, e.g. 0.05, preferably 0.01 or smaller. According to certain embodiments, particularly significant results can be obtained for n=200, 300, 400, 500 or 600.
For statistically sound results a multitude of individuals should be sampled, with n=50 or more, 100 or more, 200 or more, 300 or more, 400 or more, 500 or more or 600 or more, and a level of significance (α-error-level) of e.g. 0.05 or smaller, e.g. 0.05, preferably 0.01 or smaller. According to certain embodiments, particularly significant results can be obtained for n=200 or more, 300 or more, 400 or more, 500 or more or 600 or more.
After the above procedure has been carried out for the individual strains of bacterial species in the Examples, the data disclosed in Tables 1 to 24 were obtained for the statistically best correlations between structural variations and antimicrobial drug, e.g. antibiotic, resistances. In the tables, tables with an odd number, e.g. 1, 3, 5, represent the top 50 results for the statistical analysis as described above, i.e. the structural variations with the best p-value (denoted best_pv in the tables) for at least one antibiotic, whereas the tables with an even number show the top 50 results regarding p-value with at least one drug class ratio of 1.0, so that the structural variation applies to a multitude of drugs and at least a specific drug class, wherein the following applies:
Drug class ratio=number of significant drugs of that class/number of tested drugs of that class
For example, if two fluoroquinolones were tested but only one has significant p-value, then the drug class ratio for fluoroquinolones is 0.5.
Genetic variations in the gene sequences given in Tables 1 to 24, with regard to the several reference sequences as above, were proven as valid markers for antimicrobial drug, e.g. antibiotic, resistance. According to certain embodiments, structural variations in at least the gene sequences and/or relating to at least the whole sequences between the start coordinate (denoted “Start. Coord” in the tables) and the end coordinate (denoted “End. Coord” in the tables) of the genes, particularly relating to the whole sequence between the start coordinate and the end coordinate, given for consecutive numbers (“No.”) 1 to 50 with the highest p-values, as above, in Tables 1-24 are obtained by the present method.
When referring to the second data set, wherein the second data set e.g. comprises, respectively is, a set of antimicrobial drug, e.g. antibiotic, resistances of a plurality of clinical isolates, this can, within the scope of the invention, also refer to a self-learning data base that, whenever a new sample is analyzed, can take this sample into the second data set and thus expand its data base. The second data set thus does not have to be static and can be expanded, either by external input or by incorporating new data due to self-learning. This is, however, not restricted to the first aspect of the invention, but applies to other aspects of the invention that refer to a second data set, which does not necessarily have to refer to antimicrobial drug resistance. The same applies, where applicable, to the first data set, e.g. in the first aspect.
According to certain embodiments of the first aspect, the structural variations are detected alignment-free. According to certain embodiments, the structural variations are annotated to a pan-genome of the microorganism and/or annotated to one or more reference sequences.
According to certain embodiments, statistical analysis in the present methods is carried can be carried using Fisher's test with p<10−3, preferably p<10−6, further preferably p<10−9.
The method of the first aspect of the present invention, as well as related methods, e.g. according to the 2nd, 3rd and 4th aspect, can, according to certain embodiments, comprise correlating different genetic sites to each other. This way even higher statistical significance can be achieved.
According to certain embodiments of the method of the first aspect and related methods—as above, the second data set can be provided by culturing the clinical isolates of the microorganism on agar plates provided with antimicrobial drugs, e.g. antibiotics, at different concentrations, and the second data can be obtained by taking the minimal concentration of the plates that inhibits growth of the respective microorganism.
According to certain embodiments of the method of the first aspect and related methods, the microorganism is a Gram positive bacterial microorganism, particularly a Staphylococcus species, particularly Staphylococcus aureus, and the antimicrobial drug, e.g. antibiotic drug, is selected from the group consisting of β-lactams, β-lactam inhibitors, quinolines and derivatives thereof, e.g. fluoroquinolones, aminoglycosides, glycopeptides, lincosamides, macrolides, nitrofuranes, oxazolidinones polyketides, respectively tetracyclines, and folate synthesis inhibitors, e.g. benzene derived/sulfonamide antibiotics, preferably from the group consisting of Amoxicillin/Clavulanate, Ampicillin, Ampicillin/Sulbactam, Azithromycin, Cefalothin, Cefazolin, Cefepime, Cefotaxime, Cefoxitin, Ceftriaxone, Cefuroxime, Chloramphenicol, Ciprofloxacin, Clindamycin, Daptomycin, Ertapenem, Erythromycin, Fosfomycin, Fusidic acid, Gentamicin, Imipenem, Levofloxacin, Linezolid, Meropenem, Methicillin, Moxifloxacin, Mupirocin, Nitrofurantoin, Norfloxacin, Ofloxacin, Oxacillin, Penicillin G, Piperacillin/Tazobactam, Quinupristin/Dalfopristin, Rifampicin, Teicoplanin, Tetracycline, Tigecycline, Tobramycin, Trimethoprim/Sulfamethoxazole, and Vancomycin, further preferably from the group consisting of Amoxicillin/Clavulanate, Ampicillin, Ampicillin/Sulbactam, Azithromycin, Cefalothin, Cefazolin, Cefepime, Cefotaxime, Cefoxitin, Ceftriaxone, Cefuroxime, Chloramphenicol, Ciprofloxacin, Clindamycin, Daptomycin, Ertapenem, Erythromycin, Fosfomycin, Fusidic acid, Gentamicin, Imipenem, Levofloxacin, Linezolid, Meropenem, Moxifloxacin, Mupirocin, Nitrofurantoin, Norfloxacin, Ofloxacin, Oxacillin, Penicillin G, Piperacillin/Tazobactam, Quinupristin/Dalfopristin, Rifampicin, Teicoplanin, Tetracycline, Tigecycline, Tobramycin, Trimethoprim/Sulfamethoxazole, and Vancomycin.
According to certain embodiments of the method of the first aspect and related methods, the microorganism is a Gram negative bacterial microorganism, particularly one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, and/or Shigella species, particularly as denoted in the Examples, and the antimicrobial drug, e.g. antibiotic, is at least one selected from the group of β-lactams, β-lactam inhibitors, quinolines and derivatives thereof, aminoglycosides, polyketides, respectively tetracyclines, and folate synthesis inhibitors, preferably from the group consisting of Amoxicillin/K Clavulanate (AUG), Ampicillin (AM), Aztreonam (AZT), Cefazolin (CFZ), Cefepime (CPM), Cefotaxime (CFT), Ceftazidime (CAZ), Ceftriaxone (CAX), Cefuroxime (CRM), Cephalotin (CF), Ciprofloxacin (CP), Ertapenem (ETP), Gentamicin (GM), Imipenem (IMP), Levofloxacin (LVX), Meropenem (MER), Piperacillin/Tazobactam (P/T), Ampicillin/Sulbactam (A/S), Tetracycline (TE), Tobramycin (TO), and Trimethoprim/Sulfamethoxazole (T/S).
According to certain embodiments, structural variations in at least the gene sequences and/or relating to at least the whole sequences between the start coordinate (denoted “Start. Coord” in the tables) and the end coordinate (denoted “End.Coord” in the tables) of the genes, particularly relating to the whole sequence between the start coordinate and the end coordinate, given for consecutive numbers (“No.”) 1 to 50 with the highest p-values, as above, in Tables 1-24 are obtained by the present method, and the antibiotic is at least one chosen from the class of antibiotics in the column designated “sign_phenos_class”, particularly the one in the column designated “best_pheno_class”, preferably wherein the antibiotic is at least one chosen from the ones in the column designated “sign_phenos”, particularly the one in the column designated “best_pheno”.
A second aspect of the present invention relates to a diagnostic method of determining an infection of a patient with a microorganism, particularly a bacterial microorganism potentially resistant to antimicrobial drug treatment, comprising the steps of:
With this method, any mutations in the genome of a microorganism, e.g. the bacterial species given above and below in the Examples, e.g. a clinical isolate with an unknown strain of the microorganism, particularly bacterial microorganism, correlated with antimicrobial drug, e.g. antibiotic, resistance can be determined and a thorough antimicrobial drug, e.g. antibiotic, resistance profile can be established which can add information to a profile which considers only changes in single bases, e.g. single nucleotide polymorphisms (SNPs).
Again, the different steps can herein be carried out as described with regard to the first aspect of the present invention.
According to this aspect, an infection with a microorganism, particularly a bacterial microorganism, in a patient can be determined using sequencing methods, as well as a resistance to antimicrobial drugs, e.g. antibiotics, of the microorganism can be determined in a short amount of time compared to conventional methods.
A third aspect of the present invention relates to a method of selecting a treatment of a patient suffering from an infection with a potentially resistant microorganism, particularly bacterial microorganism, comprising the steps of:
This method can be carried out similarly to the second aspect of the invention and enables a fast was to select a suitable treatment with antibiotics for any infection with an unknown microorganism, particularly bacterial microorganism, e.g. Staphylococcus aureus.
In this method, as well as similar ones, no aligning is necessary, as the unknown sample can be directly correlated, after the genome or genome sequences are produced, with the second data set, and thus genetic variations and antimicrobial drug, e.g. antibiotic, resistances can be determined. The first data set can be assembled, for example, using known techniques.
According to certain embodiments, statistical analysis in the present method is carried out using Fisher's test with p<10−3, preferably p<10−6, preferably p<10−9. Also, according to certain embodiments, the method further comprises correlating different genetic sites to each other.
A fourth aspect of the present invention relates to a method of determining structural variations of a genome of a microorganism for a clinical isolate of the microorganism, particularly a bacterial microorganism, comprising: obtaining or providing at least one gene sequence of the clinical isolate of the microorganism, particularly the bacterial microorganism; and
With this method, antimicrobial drug, e.g. antibiotic, resistances in an unknown isolate of a microorganism, e.g. Staphylococcus aureus, can be determined.
A simple read out concept for a diagnostic test as described in this aspect is shown schematically in
According to
According to certain embodiments, statistical analysis in the present method is carried out using Fisher's test with p<10−3, preferably p<10−6, preferably p<10−9. Also, according to certain embodiments, the method further comprises correlating different genetic sites to each other.
Again, in the third and fourth aspect, the different steps can herein be carried out as described with regard to the first aspect of the present invention.
In a fifth aspect the present invention relates to one or more computer program products comprising computer executable instructions which, when executed, perform a method according to any one of the first to the fourth aspect of the present invention.
In certain embodiments the computer program product is one on which program commands or program codes of a computer program for executing said method are stored. According to certain embodiments the computer program product is a storage medium. As noted above, the computer program products of the present invention can be self-learning, e.g. with respect to the first and second data sets.
In order to obtain the best possible information from the highly complex genetic data and develop an optimum model for diagnostic and therapeutical uses as well as the methods of the present invention—which can be applied stably in clinical routine—a thorough in silico analysis can be necessary. The proposed principle is based on a combination of different approaches, e.g. assembly of the gene sequences and/or genome of the microorganisms, at least in part and optionally annotating the sequences to one or more reference sequences and/or a pan-genome, and/or alignment of the sequence data of the clinical isolate to be determined with one or more reference sequences and/or a pan-genome, and correlation of structural variations found in every sample, e.g. from each patient, respectively an unknown clinical isolate, with all references and drugs, e.g. antibiotics, or only one or some of them, and search for structural variations which occur in one or several drug and one or several strains.
Using the above steps a list of structural variations s with regard to one or more reference sequences and/or a pan-genome is generated. These can be stored in databases and statistical models can be derived from the databases. The statistical models can be based on at least one or more structural variations in at least one or more sequences. Statistical models that can be trained can be combined from structural variations and sequences. Examples of algorithms that can produce such models are association Rules, Support Vector Machines, Decision Trees, Decision Forests, Discriminant-Analysis, Cluster-Methods, and many more.
The goal of the training is to allow a reproducible, standardized application during routine procedures.
For this, for example, gene sequences or parts thereof can be sequenced from a patient to be diagnosed. Afterwards, core characteristics can be derived from the sequence data which can be used to predict resistance. These are the points in the database used for the final model, i.e. at least one structural variation, but also combinations of structural variations, etc.
The corresponding characteristics can be used as input for the statistical model and thus enable a prognosis for new patients. Not only the information regarding all resistances of all microorganisms, against all or only some or one drugs, e.g. antibiotics, can be integrated in a computer decision support tool, but also corresponding directives (e.g. EUCAST) so that only treatment proposals are made that are in line with the directives.
An eighth aspect of the present invention relates to the use of the computer program product according to the fifth aspect, e.g. for determining structural variations of a genome of a microorganism for a clinical isolate of the microorganism in the fourth aspect of the invention and/or for use in the diagnostic method of the second method of the invention and/or for selecting a treatment in the third aspect of the present invention and/or in the method of the first aspect of the present invention.
A sixth aspect of the present invention discloses a diagnostic method of determining an infection of a patient with a microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), potentially resistant to antimicrobial drug, e.g. antibiotic, treatment, comprising the steps of:
As noted above, genetic variations in the gene sequences given in Tables 1 to 24, with regard to the several reference sequences as above, were proven as valid markers for antimicrobial drug, e.g. antibiotic, resistance. According to certain embodiments, structural variations in at least the gene sequences and/or relating to at least the whole sequences between the start coordinate (denoted “Start. Coord” in the tables) and the end coordinate (denoted “End. Coord” in the tables) of the genes, particularly relating to the whole sequence between the start coordinate and the end coordinate, given for consecutive numbers (“No.”) 1 to 50 with the highest p-values, as above, in Tables 1-24 are obtained by the present method.
According to certain embodiments, structural variations in at least the gene sequences and/or relating to at least the whole sequences between the start coordinate (denoted “Start. Coord” in the tables) and the end coordinate (denoted “End. Coord” in the tables) of the genes, particularly relating to the whole sequence between the start coordinate and the end coordinate, given for consecutive numbers (“No.”) 1 to 50 with the highest p-values, as above, in Tables 1-24 are obtained by the present method, and the antibiotic is at least one chosen from the class of antibiotics in the column designated “sign_phenos_class”, particularly the one in the column designated “best_pheno_class”, preferably wherein the antibiotic is at least one chosen from the ones in the column designated “sign_phenos”, particularly the one in the column designated “best_pheno”.
An infection of a patient with a microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), potentially resistant to antimicrobial drug treatment herein means an infection of a patient with a microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), wherein it is unclear if the microorganism, preferably bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), is susceptible to treatment with a specific antimicrobial drug or if it is resistant to the antimicrobial drug.
In step b) above, as well as corresponding steps, at least one structural variation in at least two positions is determined, so that in total at least two structural variations are determined, wherein the two structural variations are in different positions, respectively are different sequences.
In this method, as well as the other methods of the invention, the sample can be provided or obtained in any way, preferably non-invasive, and can be e.g. provided as an in vitro sample or prepared as in vitro sample.
According to certain aspects, structural variations in at least two, three, four, five, six, seven, eight, nine or ten positions, respectively sequences, are determined in any of the methods of the present invention, e.g. in at least two positions, respectively sequences, or in at least three positions, respectively sequences. Instead of testing only single positions, respectively sequences, a combination of several variant positions, respectively sequences, can improve the prediction accuracy and further reduce false positive findings that are influenced by other factors. Therefore, it is in particular preferred to determine the presence of structural variations in 2, 3, 4, 5, 6, 7, 8 or 9 (or more) sequences selected from the respective Table 1-24.
According to certain embodiments, the obtaining or providing a sample containing or suspected of containing at least one microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), from the patient in this method—as well as the other methods of the invention—can comprise the following:
A sample of a vertebrate, e.g. a human, e.g. is provided or obtained and nucleic acid sequences, e.g. DNA or RNA sequences, are recorded by a known method for recording nucleic acid, which is not particularly limited. For example, nucleic acid can be recorded by a sequencing method, wherein any sequencing method is appropriate, particularly sequencing methods wherein a multitude of sample components, as e.g. in a blood sample, can be analyzed for nucleic acids and/or nucleic acid fragments and/or parts thereof contained therein in a short period of time, including the nucleic acids and/or nucleic acid fragments and/or parts thereof of the microorganism. For example, sequencing can be carried out using polymerase chain reaction (PCR), particularly multiplex PCR, or high throughput sequencing or next generation sequencing, preferably using high-throughput sequencing. For sequencing, preferably an in vitro sample is used.
The data obtained by the sequencing can be in any format, and can then be analyzed as described with regard to the first to fourth aspect of the present invention.
In a seventh aspect, the present invention relates to a method of selecting a treatment of a patient suffering from an infection with a potentially resistant microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), comprising the steps of:
In this method, the steps a) of obtaining or providing a sample and b) of determining the presence of at least one structural variation are as in the method of the sixth aspect.
The identification of the at least one or more antimicrobial, e.g. antibiotic, drug in step c) is then based on the results obtained in step b) and corresponds to the antimicrobial, e.g. antibiotic, drug(s) that correlate(s) with the structural variations. Once these antimicrobial drugs, e.g. antibiotics, are ruled out, the remaining antimicrobial drugs, e.g. antibiotic drugs/antibiotics, can be selected in step d) as being suitable for treatment.
In the description, references to the sixth and seventh aspect also apply to the 9th, 10th, 11th and 12th aspect, referring to the same positions, respectively sequences, unless clear from the context that they don't apply.
According to certain embodiments, the microorganism is a Gram positive bacterial microorganism, particularly a Staphylococcus species, particularly Staphylococcus aureus, and the antimicrobial drug, e.g. antibiotic drug, is selected from the group consisting of β-lactams, β-lactam inhibitors, quinolines and derivatives thereof, e.g. fluoroquinolones, aminoglycosides, glycopeptides, lincosamides, macrolides, nitrofuranes, oxazolidinones polyketides, respectively tetracyclines, and folate synthesis inhibitors, e.g. benzene derived/sulfonamide antibiotics, preferably from the group consisting of Amoxicillin/Clavulanate, Ampicillin, Ampicillin/Sulbactam, Azithromycin, Cefalothin, Cefazolin, Cefepime, Cefotaxime, Cefoxitin, Ceftriaxone, Cefuroxime, Chloramphenicol, Ciprofloxacin, Clindamycin, Daptomycin, Ertapenem, Erythromycin, Fosfomycin, Fusidic acid, Gentamicin, Imipenem, Levofloxacin, Linezolid, Meropenem, Methicillin, Moxifloxacin, Mupirocin, Nitrofurantoin, Norfloxacin, Ofloxacin, Oxacillin, Penicillin G, Piperacillin/Tazobactam, Quinupristin/Dalfopristin, Rifampicin, Teicoplanin, Tetracycline, Tigecycline, Tobramycin, Trimethoprim/Sulfamethoxazole, and Vancomycin, further preferably from the group consisting of Amoxicillin/Clavulanate, Ampicillin, Ampicillin/Sulbactam, Azithromycin, Cefalothin, Cefazolin, Cefepime, Cefotaxime, Cefoxitin, Ceftriaxone, Cefuroxime, Chloramphenicol, Ciprofloxacin, Clindamycin, Daptomycin, Ertapenem, Erythromycin, Fosfomycin, Fusidic acid, Gentamicin, Imipenem, Levofloxacin, Linezolid, Meropenem, Moxifloxacin, Mupirocin, Nitrofurantoin, Norfloxacin, Ofloxacin, Oxacillin, Penicillin G, Piperacillin/Tazobactam, Quinupristin/Dalfopristin, Rifampicin, Teicoplanin, Tetracycline, Tigecycline, Tobramycin, Trimethoprim/Sulfamethoxazole, and Vancomycin.
According to certain embodiments, the microorganism is a Gram negative bacterial microorganism, particularly one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, and/or Shigella species, particularly as denoted in the Examples, and the antimicrobial drug, e.g. antibiotic, is at least one selected from the group of β-lactams, β-lactam inhibitors, quinolines and derivatives thereof, aminoglycosides, polyketides, respectively tetracyclines, and folate synthesis inhibitors, preferably from the group consisting of Amoxicillin/K Clavulanate (AUG), Ampicillin (AM), Aztreonam (AZT), Cefazolin (CFZ), Cefepime (CPM), Cefotaxime (CFT), Ceftazidime (CAZ), Ceftriaxone (CAX), Cefuroxime (CRM), Cephalotin (CF), Ciprofloxacin (CP), Ertapenem (ETP), Gentamicin (GM), Imipenem (IMP), Levofloxacin (LVX), Meropenem (MER), Piperacillin/Tazobactam (P/T), Ampicillin/Sulbactam (A/S), Tetracycline (TE), Tobramycin (TO), and Trimethoprim/Sulfamethoxazole (T/S).
In the methods of the invention the resistance of the microorganism, preferably bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), to one or more antimicrobial, e.g. antibiotic, drugs can be determined according to certain embodiments.
According to certain embodiments of the sixth and/or seventh aspect of the invention, the resistance of the microorganism, preferably bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), against 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16, 17, 18, 19, 20 or more antibiotic drugs is determined.
According to certain embodiments of the sixth and/or seventh aspect of the invention, determining the nucleic acid sequence information with the sequences having a structural variation or the presence of a structural variation comprises using a next generation sequencing or high throughput sequencing method. According to preferred embodiments of the sixth and/or seventh aspect of the invention, a partial or entire genome sequence of a microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), is determined by using a next generation sequencing or high throughput sequencing method.
A ninth aspect of the present invention is directed to a method of treating a patient suffering from an antimicrobial drug, e.g. antibiotic, resistant infection with a microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), comprising the steps of:
Herein, steps a) to d) can be carried out as described with respect to the seventh aspect. Step e) can be sufficiently carried out without being restricted and can be done e.g. non-invasively.
A tenth aspect of the present invention discloses a diagnostic method of determining an infection of a patient with a microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), potentially resistant to antimicrobial drug, e.g. antibiotic, treatment, comprising the steps of:
In an eleventh aspect, the present invention relates to a method of selecting a treatment of a patient suffering from an infection with a potentially resistant microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), comprising the steps of:
Again, in the tenth and the eleventh aspect the steps correspond to those in the sixth or seventh aspect, although only a mutation in at least one gene is determined.
A twelfth aspect of the present invention is directed to a method of treating a patient suffering from an antimicrobial drug, e.g. antibiotic, resistant infection with a microorganism, preferably a bacterial microorganism, particularly one as noted above (i.e. one or more of Acinetobacter, Escherichia, e.g. E. coli, Enterobacter, Klebsiella, Proteus, Pseudomonas, Salmonella, Serratia, Shigella and/or Staphylococcus species), comprising the steps of:
Also in the twelfth aspect of the invention, steps a) to d) are analogous to the steps in the method of the ninth aspect of the present invention. Step e) can again be sufficiently carried out without being restricted and can be done e.g. non-invasively.
The present invention will now be described in detail with reference to several examples thereof. However, these examples are illustrative and do not limit the scope of the invention.
Whole genome sequencing was carried out in addition to classical antimicrobial susceptibility testing of the same isolates for a cohort of 448 specimens. This allowed performing genome wide correlation studies to find genetic variants (e.g. point mutations, small insertions and deletion, larger structural variants, plasmid copy number gains, gene dosage effects) in the genome and plasmids that are significantly correlated to the resistance against one or several drugs. The approach also allows for comparing the relevant sites in the genome to each other.
In the approach the different sources of genetic resistance regarding structural variances as well as the different ways of how bacteria can become resistant were covered. By measuring clinical isolates collected in a broad geographical area and across a broad time span of three decades a complete picture going far beyond the rather artificial step of laboratory generated resistance mechanisms was tried to be generated.
To this end, a set of 21 clinically relevant antimicrobial agents with 5 different modes of action was put together, and the minimally inhibitory concentration (MIC) of the 21 drugs for the Acinetobacter isolates was measured.
The detailed procedure is given in the following:
The inventors selected 448 Acinetobacter strains from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
Antimicrobial Susceptibility Testing (AST) Panels Frozen reference AST panels were prepared following Clinical Laboratory Standards Institute (CLSI) recommendations. The following antimicrobial agents (with μg/ml concentrations shown in parentheses) were included in the panels: Amoxicillin/K Clavulanate (0.5/0.25-64/32), Ampicillin (0.25-128), Ampicillin/Sulbactam (0.5/0.25-64/32), Aztreonam (0.25-64), Cefazolin (0.5-32), Cefepime (0.25-64), Cefotaxime (0.25-128), Ceftazidime (0.25-64), Ceftriaxone (0.25-128), Cefuroxime (1-64), Cephalothin (1-64), Ciprofloxacin (0.015-8), Ertepenem (0.12-32), Gentamicin (0.12-32), Imipenem (0.25-32), Levofloxacin (0.25-16), Meropenem (0.12-32), Piperacillin/Tazobactam (0.25/4-256/4), Tetracycline (0.5-64), Tobramycin (0.12-32), and Trimethoprim/Sulfamethoxazole (0.25/4.7-32/608). Prior to use with clinical isolates, AST panels were tested with QC strains. AST panels were considered acceptable for testing with clinical isolates when the QC results met QC ranges described by CLSI16.
Isolates were cultured on trypticase soy agar with 5% sheep blood (BBL, Cockeysville, Md.) and incubated in ambient air at 35±1° C. for 18-24 h. Isolated colonies (4-5 large colonies or 5-10 small colonies) were transferred to a 3 ml Sterile Inoculum Water (Siemens) and emulsified to a final turbidity of a 0.5 McFarland standard. 2 ml of this suspension was added to 25 ml Inoculum Water with Pluronic-F (Siemens). Using the Inoculator (Siemens) specific for frozen AST panels, 5 μl of the cell suspension was transferred to each well of the AST panel. The inoculated AST panels were incubated in ambient air at 35±1° C. for 16-20 h. Panel results were read visually, and minimal inhibitory concentrations (MIC) were determined.
Four streaks of each Gram-negative bacterial isolate cultured on trypticase soy agar containing 5% sheep blood and cell suspensions were made in sterile 1.5 ml collection tubes containing 50 μl Nuclease-Free Water (AM9930, Life Technologies). Bacterial isolate samples were stored at −20° C. until nucleic acid extraction. The Tissue Preparation System (TPS) (096D0382-02_01_B, Siemens) and the VERSANT® Tissue Preparation Reagents (TPR) kit (10632404B, Siemens) were used to extract DNA from these bacterial isolates. Prior to extraction, the bacterial isolates were thawed at room temperature and were pelleted at 2000 G for 5 seconds. The DNA extraction protocol DNAext was used for complete total nucleic acid extraction of 48 isolate samples and eluates, 50 μl each, in 4 hours. The total nucleic acid eluates were then transferred into 96-Well qPCR Detection Plates (401341, Agilent Technologies) for RNase A digestion, DNA quantitation, and plate DNA concentration standardization processes. RNase A (AM2271, Life Technologies) which was diluted in nuclease-free water following manufacturer's instructions was added to 50 μl of the total nucleic acid eluate for a final working concentration of 20 μg/ml. Digestion enzyme and eluate mixture were incubated at 37° C. for 30 minutes using Siemens VERSANT® Amplification and Detection instrument. DNA from the RNase digested eluate was quantitated using the Quant-iT™ PicoGreen dsDNA Assay (P11496, Life Technologies) following the assay kit instruction, and fluorescence was determined on the Siemens VERSANT® Amplification and Detection instrument. Data analysis was performed using Microsoft® Excel 2007. 25 μl of the quantitated DNA eluates were transferred into a new 96-Well PCR plate for plate DNA concentration standardization prior to library preparation. Elution buffer from the TPR kit was used to adjust DNA concentration. The standardized DNA eluate plate was then stored at −80° C. until library preparation.
Prior to library preparation, quality control of isolated bacterial DNA was conducted using a Qubit 2.0 Fluorometer (Qubit dsDNA BR Assay Kit, Life Technologies) and an Agilent 2200 TapeStation (Genomic DNA ScreenTape, Agilent Technologies). NGS libraries were prepared in 96 well format using NexteraXT DNA Sample Preparation Kit and NexteraXT Index Kit for 96 Indexes (Illumina) according to the manufacturer's protocol. The resulting sequencing libraries were quantified in a qPCR-based approach using the KAPA SYBR FAST qPCR MasterMix Kit (Peqlab) on a ViiA 7 real time PCR system (Life Technologies). 96 samples were pooled per lane for paired-end sequencing (2×100 bp) on Illumina Hiseq2000 or Hiseq2500 sequencers using TruSeq PE Cluster v3 and TruSeq SBS v3 sequncing chemistry (Illumina). Basic sequencing quality parameters were determined using the FastQC quality control tool for high throughput sequence data (Babraham Bioinformatics Institute).
For each organism in the examples, a list of centroids was extracted from MetaRef (http://metaref.org/). Herein, centroids were representatives of genes, etc. in a group/family/cluster. Data for information/annotation regarding the centroids was extracted from the database IMG (http://img.jgi.doe.gov/).
For Acinetobacter, 1380 centroids of A. baumannii were used as reference sequences, extracted from MetaRef.
The centroid presence in samples was evaluated as follows: Sequences of centroids were aligned against the de novo assemblies using BLASTn
(http://blast.ncbi.nlm.nih.gov/Blast.cgi).
The following parameters were used:
A centroids was considered as present if the alignment result contained at least one hit with
In the results, a centroid was coded as 0/1 (absent/present)
Association testing and result filtering:
The input data was further filtered as follows to reduce the amount of data:
For statistical analysis, Fisher's exact two-sided test was applied with subsequent p-value adjustment over all phenotypes together using FDR and p-value threshold of 0.01 (1e-2). Additionally, 10 permutation tests were performed by permuting each phenotype separately and applying Fisher's exact test to the centroid presence matrix and permuted phenotypes. The results were further filtered by centroid annotation, i.e.
After the above procedure has been carried out, the data disclosed in Tables 1 and 2 were obtained for the statistically best correlations between structural variations and antimicrobial drug, e.g. antibiotic, resistances. Table 1 (as well as the odd Tables 3, 5, 7, 9, 11, 13, 15, 17, 19, 21 and 23 in Examples 2 to 12) represents the top 50 results for structural variations with the best p-value (denoted best_pv in the tables) for at least one antibiotic, whereas Table 2 (as well as the even Tables 4, 6, 8, 10, 12, 14, 16, 18, 20, 22 and 24 in Examples 2 to 12) shows the top 50 results regarding p-value with at least one drug class ratio of 1.0, so that the structural variation applies to a multitude of drugs and at least a specific drug class, wherein the following applies:
Drug class ratio=number of significant drugs of that class/number of tested drugs of that class
For example, if two fluoroquinolones were tested but only one has significant p-value, then the drug class ratio for fluoroquinolones is 0.5.
In Tables 1 and 2, as well as also the following Tables 3 to 24 in Examples 2 to 12, the columns are designated as follows:
Acinetobacter baumannii 1656-2: CP001921
Acinetobacter sp. 6013113 NZ_ACYR01000063: NZ_ACYR01000063
Acinetobacter baumannii ATCC 17978: NC_009085
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB900: NZ_ABXK01000013
Acinetobacter sp. RUH2624 genomic scaffold supercont1.1: NZ_GG704495
Acinetobacter sp. RUH2624 genomic scaffold supercont1.21: NZ_GG704515
Acinetobacter sp. RUH2624 genomic scaffold supercont1.21: NZ_GG704515
Acinetobacter sp. DR1 chromosome: NC_014259
Acinetobacter calcoaceticus RUH2202 genomic scaffold supercont1.1:
Acinetobacter sp. RUH2624 genomic scaffold supercont1.21: NZ_GG704515
Acinetobacter calcoaceticus PHEA-2: CP002177
Acinetobacter sp. RUH2624 genomic scaffold supercont1.21: NZ_GG704515
Acinetobacter sp. RUH2624 genomic scaffold supercont1.1: NZ_GG704495
Acinetobacter sp. ADP1: NC_005966
Acinetobacter sp. RUH2624 genomic scaffold supercont1.21: NZ_GG704515
Acinetobacter baumannii A3307-0294: NC_011595
Acinetobacter baumannii TCDC-AB0715: CP002522
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter sp. DR1 chromosome: NC_014259
Acinetobacter lwoffii SH145 genomic scaffold supercont1.39: NZ_GG705093
Acinetobacter sp. 6013150 NZ_ACYQ01000024: NZ_ACYQ01000024
Acinetobacter sp. RUH2624 genomic scaffold supercont1.38: NZ_GG704532
Acinetobacter sp. 6014059 NZ_ACYS01000159: NZ_ACYS01000159
Acinetobacter baumannii ACICU: NC_010611
Acinetobacter sp. SH024 genomic scaffold supercont1.2: NZ_GG753601
Acinetobacter baumannii TCDC-AB0715: CP002522
Acinetobacter johnsonii SH046 genomic scaffold supercont1.16: NZ_GG704979
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii ACICU: NC_010611
Acinetobacter baumannii TCDC-AB0715: CP002522
Acinetobacter baumannii AB900: NZ_ABXK01000021
Acinetobacter baumannii 1656-2: CP001921
Acinetobacter sp. 6013150 NZ_ACYQ01000067: NZ_ACYQ01000067
Acinetobacter baumannii ATCC 19606 genomic scaffold supercont1.8:
Acinetobacter baumannii ACICU: NC_010611
Acinetobacter haemolyticus ATCC 19194 contig00185: NZ_ADMT01000124
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter calcoaceticus PHEA-2: CP002177
Acinetobacter baumannii ATCC 19606 genomic scaffold supercont1.8:
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter sp. RUH2624 genomic scaffold supercont1.5: NZ_GG704499
Acinetobacter baumannii TCDC-AB0715: CP002522
Acinetobacter baumanii (continued)
Acinetobacter baumannii 1656-2: CP001921
Acinetobacter sp. 6013113 NZ_ACYR01000063:
Acinetobacter baumannii ATCC 17978: NC_009085
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB900: NZ_ABXK01000013
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter sp. DR1 chromosome: NC_014259
Acinetobacter calcoaceticus RUH2202 genomic
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter calcoaceticus PHEA-2: CP002177
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter sp. ADP1: NC_005966
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii TCDC-AB0715: CP002522
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter sp. DR1 chromosome: NC_014259
Acinetobacter lwoffii SH145 genomic scaffold
Acinetobacter sp. 6013150 NZ_ACYQ01000024:
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter sp. 6014059 NZ_ACYS01000159:
Acinetobacter baumannii ACICU: NC_010611
Acinetobacter sp. SH024 genomic scaffold
Acinetobacter baumannii TCDC-AB0715: CP002522
Acinetobacter johnsonii SH046 genomic scaffold
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter baumannii ACICU: NC_010611
Acinetobacter baumannii TCDC-AB0715: CP002522
Acinetobacter baumannii AB900: NZ_ABXK01000021
Acinetobacter baumannii 1656-2: CP001921
Acinetobacter sp. 6013150 NZ_ACYQ01000067:
Acinetobacter baumannii ATCC 19606 genomic
Acinetobacter baumannii ACICU: NC_010611
Acinetobacter haemolyticus ATCC 19194
Acinetobacter baumannii AB0057: NC_011586
Acinetobacter calcoaceticus PHEA-2: CP002177
Acinetobacter baumannii ATCC 19606 genomic
Acinetobacter baumannii AB307-0294: NC_011595
Acinetobacter sp. RUH2624 genomic scaffold
Acinetobacter baumannii TCDC-AB0715: CP002522
The procedure was carried out as in Example 1, except that the following microorganisms were used: +
The inventors selected 695 Enterobacter strains, particularly 298 for Enterobacter aerogenes and 397 for Enterobacter cloacae, from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 5220 centroids of E. aerogenes were used as reference sequences for E. aerogenes, and 4734 centroids of E. cloacae were used as reference sequences for E. cloacae.
The results for Enterobacter aerogenes are shown in Tables 3 (corresponding to Table 1) and 4 (corresponding to Table 2), and the results for Enterobacter cloacae are shown in Tables 5 (corresponding to Table 1) and 6 (corresponding to Table 2).
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2:
Escherichia coli MS 198-1 E_coli198-1-1.0_Cont45.1:
Klebsiella pneumoniae subsp. whinoscleromatis ATCC
Escherichia coli MS 198-1 E_coli198-1-1.0_Cont45.1;
Escherichia coli MS 198-1 E_coli198-1-1.0_Cont45.1:
Escherichia coli BL21(DE3) : AM946981
Klebsiella sp. 1_1_55 genomic scaffold supercont1.3:
Enterobacter aerogenes (continued)
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter sakazakii ATCC BAA-894: NC_009778
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Escherichia coli MS 198-1 E_coli198-1-1.0_Cont45.1:
Escherichia coli MS 198-1 E_coli198-1-1.0_Cont45.1:
Escherichia coli MS 198-1 E_coli198-1-1.0_Cont45.1:
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Enterobacter aerogenes (continued)
Edwardsiella tarda EIB202 plasmid pEIB202: NC_013509
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Escherichia coli APEC O1 plasmid pAPEC-O1-R: NC_009838
Escherichia coli APEC O1 plasmid pAPEC-O1-R: NC_009838
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Citrobacter sp. 30_2 genomic scaffold supercont1.5:
Citrobacter sp. 30_2 genomic scaffold supercont1.5:
Escherichia coli APEC O1 plasmid pAPEC-O1-R: NC_009838
Enterobacter sakazakii ATCC BAA-894: NC_009778
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Escherichia coli MS 196-1 E_coli196-1-1.0_Cont1482.1:
Enterobacter cloacae subsp. cloacae ATCC 13047
Salmonella enterica subsp. enterica serovar Virchow str.
Shigella flexneri 2a str. 2457T: NC_004741
Enterobacter cloacae subsp. cloacae ATCC 13047
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont398.10:
Enterobacter cloacae subsp. cloacae ATCC 13047
Shigella flexneri 2002017: CP001383
Escherichia coli DH1: CP001637
Escherichia coli MS 124-1 E_coliMS124-1-1.0.1_Cont5.1:
Escherichia coli MS 21-1 E_coli21-1-1.0_Cont669.1:
Enterobacter cloacae subsp. cloacae ATCC 13047
Escherichia coli E22, unfinished sequence:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter hormaechei ATCC 49162 contig00043:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter hormaechei ATCC 49162 contig00073:
Enterobacter hormaechei ATCC 49162 contig00073:
Enterobacter hormaechei ATCC 49162 contig00034:
Enterobacter hormaechei ATCC 49162 contig00073:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter hormaechei ATCC 49162 contig00062:
Enterobacter cloacae SCF1 chromosome: NC_014618
Enterobacter cloacae SCF1 chromosome: NC_014618
Enterobacter cancerogenus ATCC 35316, unfinished
Enterobacter cloacae subsp. cloacae ATCC 13047
Citrobacter sp. 30_2 genomic scaffold supercont1.5:
Enterobacter cloacae SCF1 chromosome: NC_014618
Enterobacter hormaechei ATCC 49162 contig00015:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae (continued)
Enterobacter cloacae (continued)
Enterobacter cloacae (continued)
Edwardsiella tarda EIB202 plasmid pEIB202: NC_013509
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Escherichia coli APEC O1 plasmid pAPEC-O1-R: NC_009838
Escherichia coli APEC O1 plasmid pAPEC-O1-R: NC_009838
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Citrobacter sp. 30_2 genomic scaffold supercont1.5:
Citrobacter sp. 30_2 genomic scaffold supercont1.5:
Escherichia coli APEC O1 plasmid pAPEC-O1-R: NC_009838
Enterobacter sakazakii ATCC BAA-894: NC_009778
Enterobacter cloacae subsp. cloacae ATCC 13047 plasmid
Escherichia coli MS 196-1 E_coli196-1-1.0_Cont1482.1:
Enterobacter cloacae subsp. cloacae ATCC 13047
Salmonella enterica subsp. enterica serovar Virchow
Shigella flexneri 2a str. 2457T: NC_004741
Enterobacter cloacae subsp. cloacae ATCC 13047
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont398.10:
Enterobacter cloacae subsp. cloacae ATCC 13047
Shigella flexneri 2002017: CP001383
Escherichia coli DH1: CP001637
Escherichia coli MS 124-1 E_coliMS124-1.1.0.1_Cont5.1:
Escherichia coli MS 21-1 E_coli21-1-1.0_Cont669.1:
Enterobacter cloacae subsp. cloacae ATCC 13047
Escherichia coli E22, unfinished sequence:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter hormaechei ATCC 49162 contig00043:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter hormaechei ATCC 49162 contig00073:
Enterobacter hormaechei ATCC 49162 contig00073:
Enterobacter hormaechei ATCC 49162 contig00034:
Enterobacter hormaechei ATCC 49162 contig00073:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter hormaechei ATCC 49162 contig00062:
Enterobacter cloacae SCF1 chromosome: NC_014618
Enterobacter cloacae SCF1 chromosome: NC_014618
Enterobacter cancerogenus ATCC 35316, unfinished
Enterobacter cloacae subsp. cloacae ATCC 13047
Citrobacter sp. 30_2 genomic scaffold supercont1.5:
Enterobacter cloacae SCF1 chromosome: NC_014618
Enterobacter hormaechei ATCC 49162 contig00015:
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae subsp. cloacae NCTC 9394 draft
Enterobacter cloacae (continued)
Enterobacter cloacae (continued)
Enterobacter cloacae (continued)
The procedure was carried out as in Example 1, except that the following microorganisms were used: Bacterial Strains
The inventors selected 1144 E. coli strains from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 318 centroids of E. coli were used as reference sequences.
The results for E. coli are shown in Tables 7 (corresponding to Table 1) and 8 (corresponding to Table 2).
Salmonella enterica subsp. enterica serovar Heidelberg str.
Escherichia coli B7A, unfinished sequence: NZ_AAJT01000012
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont44.1:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid
Escherichia coli MS 175-1 E_coli175-1-1.0_Cont542.3:
Salmonella enterica subsp. enterica serovar Schwarzengrund
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont55.1:
Escherichia coli B171, unfinished sequence: NZ_AAJX01000089
Escherichia fergusonii ATCC 35469 plasmid pEFER: NC_011743
Edwardsiella tarda EIB202 plasmid pEIB202: NC_013509
Escherichia coli FVEC1412 genomic scaffold supercont1.13:
Edwardsiella tarda EIB202 plasmid pEIB202: NC_013509
Escherichia coli FVEC1412 genomic scaffold supercont1.13:
Citrobacter rodentium ICC168 plasmid pCROD1: NC_013717
Citrobacter rodentium ICC168 plasmid pCROD1: NC_013717
Escherichia coli MS 145-7 E_coliMS145-7-1.0.1_Cont88.1:
Escherichia coli UMN026: NC_011751
Escherichia coli UMN026: NC_011751
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont55.1:
Escherichia coli SECEC SMS-3-5 plasmid pSMS35_130: NC_010488
Escherichia coli MS 182-1 E_coli182-1-1.0_Cont460.3:
Escherichia coli MS 145-7 E_coliMS145-7-1.0.1_Cont94.1:
Escherichia coli MS 182-1 E_coli182-1-1.0_Cont460.3:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont16.1:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid
Escherichia sp. 1_1_43 genomic scaffold supercont1.1:
Escherichia coli MS 115-1 E_coli115-1-1.0_Cont158.2:
Salmonella enterica subsp. enterica serovar Typhimurium str.
Klebsiella pneumoniae 342 plasmid pKP187: NC_011282
Escherichia coli O157:H7 str. EC4401, unfinished sequence:
Escherichia coli SECEC SMS-3-5 plasmid pSMS35_130: NC_010488
Klebsiella sp. MS 92-3 K_spMS92-3-l.0_Cont24.1:
Escherichia coli NA114: CP002797
Escherichia coli O157:H7 str. EC4206, unfinished sequence:
Citrobacter sp. 30_2 genomic scaffold supercont1.1:
Escherichia coli O157:H7 str. EC4115: NC_011353
Citrobacter youngae ATCC 29220 C_sp-1.0_Cont2.3:
Escherichia coli SE15 DNA: AP009378
Escherichia coli O157:H7 str. FRIK966: NZ_ACXN01000074
Shigella sonnei Ss046: NC_007384
Citrobacter youngae ATCC 29220 C_sp-1.0_Cont2.3:
Escherichia coli MS 115-1 E_coli115-1-1.0_Cont264.1:
Escherichia coli W3110 DNA: AC_000091
Escherichia coli MS 196-1 E_colil96-1-1.0_Cont1482.1:
Salmonella enterica subsp. enterica serovar Heidelberg str.
Shigella flexneri 2002017: CP001383
Escherichia coli MS 21-1 E_coli21-1-1.0_Cont296.1:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid
Shigella flexneri 2a str. 301 plasmid pCP301: NC_004851
Salmonella enterica subsp. enterica serovar Heidelberg
Escherichia coli B7A, unfinished sequence: NZ_AAJT01000012
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont44.1:
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont55.1:
Escherichia coli B171, unfinished sequence:
Escherichia fergusonii ATCC 35469 plasmid pEFER: NC_011743
Escherichia coli FVEC1412 genomic scaffold supercont1.13:
Escherichia coli FVEC1412 genomic scaffold supercont1.13:
Escherichia coli MS 145-7 E_coliMS145-7-1.0.1_Cont88.1:
Escherichia coli UMN026: NC_011751
Escherichia coli UMN026: NC_011751
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont55.1:
Escherichia coli SECEC SMS-3-plasmid pSMS35_130:
Escherichia coli MS 182-1 E_coli182-1-1.0_Cont460.3:
Escherichia coli MS 145-7 E_coliMS145-7-1.0.1_Cont94.1:
Escherichia coli MS 182-1 E_coli182-1-1.0_Cont460.3:
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont16.1:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid
Escherichia sp. 1_1_43 genomic scaffold supercont1.1:
Escherichia coli MS 115-1 E_coli115-1-1.0_Cont158.2:
Salmonella enterica subsp. enterica serovar Typhimurium
Escherichia coli C157:H7 str. EC4401, unfinished sequence:
Escherichia coli SECEC SMS-3-plasmid pSMS35_130:
Escherichia coli NA114: CP002797
Escherichia coli 0157:H7 str. EC4206, unfinished sequence:
Citrobacter sp. 30_2 genomic scaffold supercont1.1;
Escherichia coli C157:H7 str. EC4115: NC_011353
Escherichia coli SE15 DNA: AP009378
Escherichia coli C157:H7 str. FRIK966: NZ_ACXN01000074
Escherichia coli MS 115-1 E_coli115-1-1.0_Cont264.1:
Escherichia coli W3110 DNA: AC_000091
Escherichia coli MS 196-1 E_coli196-1-1.0_Cont1482.1:
Salmonella enterica subsp. enterica serovar Heidelberg
Escherichia coli MS 21-1 E_coli21-1-1.0_Cont296.1:
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid
Escherichia coli MS 115-1 E_coli115-1-1.0_Cont677.5:
The procedure was carried out as in Example 1, except that the following microorganisms were used: Bacterial Strains
The inventors selected 1568 Klebsiella strains, particularly 1179 for Klebsiella pneumonia and 389 for Klebsiella oxytoca, from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 1640 centroids of Klebsiella species were used as reference sequences for K. oxytoca, and 1641 centroids of K. pneumoniae were uses as reference sequences of K. pneumoniae.
The results for K. oxytoca are shown in Tables 9 (corresponding to Table 1) and 10 (corresponding to Table 2), and the results for K. pneumonia are shown in Tables 11 (corresponding to Table 1) and 12 (corresponding to Table 2).
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1:
Klebsiella pneumoniae subsp. rhinoscleromatis AICC 13884
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.5:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1;
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2:
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont1649.3:
Klebsiella pneumoniae 342: NC_011283
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1: NZ_GG745508
Enterobacter aerogenes KCTC 2190 chromosome: NC_015663
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2: NZ_GG745509
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1: NZ_GG745508
Klebsiella pneumoniae 342: NC_011283
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella sp. 1_1_55 genomic scaffold supercont1.5: NZ_GG745512
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1: NZ_GG745508
Klebsiella pneumoniae subsp. pneumoniae MGH 78578: NC_009648
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
pneumoniae NTUH-K2044: NC_012731
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1: NZ_GG745508
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1: NZ_GG745508
Klebsiella sp. 1_1_55 genomic scaffold supercont1.1: NZ_GG745508
Klebsiella
pneumoniae NTUH-32044: NC_012731
Klebsiella
pneumoniae KCTC 2242: CP002910
Klebsiella
pneumoniae 342: NC_011283
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont988.13:
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2: NZ_GG745509
Klebsiella sp. 1_1_55 genomic scaffold supercont1.2: NZ_GG745509
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella pneumoniae subsp. pneumoniae MGH 78578: NC_009648
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont1649.3:
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella
variicola At-22 chromosome: NC_013850
Klebsiella pneumoniae subsp. pneumoniae MGH 78578: NC_009648
Klebsiella
pneumoniae 342: NC_011283
Klebsiella
pneumoniae 342: NC_011283
Shigella sonnei Ss046: NC_007384
Salmonella enterica subsp. enterica serovar Heidelberg str. SL476:
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont44.1:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN5:
Salmonella enterica subsp. enterica serovar Virchow str. SL491,
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella pneumoniae 342 plasmid pKP187: NC_011282
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Escherichia coli MS 69-1 E_coli69-1-1.0_Cont630.1: NZ_ADTP01000323
Citrobacter koseri ATCC BAA-895 plasmid pCKO3: NC_009793
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella sp. 1_1_55 genomic scaffold supercont1.8: NZ_GG745515
Escherichia coli B171, unfinished sequence: NZ_AAJX01000089
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella sp. MS 92-3 K_spMS92-3-l.0_Cont91.1: NZ_AFBO01000042
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN3:
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN3:
Klebsiella sp. MS 92-3 K_spMS92-3-l.0_Cont91.1: NZ_AFBO01000042
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN3:
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Enterobacter cloacae subsp. cloacae ATCC 13047 chromosome:
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella sp. 1_1_55 genomic scaffold supercont1.5: NZ_GG745512
Salmonella enterica subsp. enterica serovar Typhi str. E98-3139,
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Enterobacter cloacae subsp. cloacae ATCC 13047 chromosome:
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont1175.2: NZ_AFBO01000625
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Klebsiella variicola At-22 chromosome: NC_013850
Dickeya zeae Ech1591: NC_012912
Edwardsiella tarda EIB202 plasmid pEIB202: NC_013509
Salmonella enterica subsp. enterica serovar Typhimurium str.
Salmonella enterica subsp. enterica serovar Choleraesuis str. SC-
Salmonella enterica subsp. enterica serovar Typhimurium str.
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont505.1: NZ_AFBO01000232
Salmonella enterica subsp. enterica serovar Typhi Ty2: NC_004631
Klebsiella pneumoniae NTUH-K2044 plasmid pK2044: NC_006625
Shigella sonnei Ss046: NC_007384
Salmonella enterica subsp. enterica serovar Heidelberg str. SL476:
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont44.1:
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN5:
Salmonella enterica subsp. enterica serovar Virchow str. SL491,
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella variicola At-22 chromosome: NC_013850
Klebsiella pneumoniae 342 plasmid pKP187: NC_011282
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Escherichia coli MS 69-1 E_coli69-1-1.0_Cont630.1: NZ_ADTP01000323
Citrobacter koseri ATCC BAA-895 plasmid pCKO3: NC_009793
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella sp. 1_1_55 genomic scaffold supercont1.8: NZ_GG745515
Escherichia coli B171, unfinished sequence: NZ_AAJX01000089
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella sp. MS 92-3 K_spMS92-3-l.0_Cont91.1: NZ_AFBO01000042
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN3:
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN3:
Klebsiella sp. MS 92-3 K_spMS92-3-l.0_Cont91.1: NZ_AFBO01000042
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN3:
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Enterobacter cloacae subsp. cloacae ATCC 13047 chromosome:
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella sp. 1_1_55 genomic scaffold supercont1.5: NZ_GG745512
Salmonella enterica subsp. enterica serovar Typhi str. E98-3139,
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae KCTC 2242: CP002910
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Enterobacter cloacae subsp. cloacae ATCC 13047 chromosome:
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont1175.2: NZ_AFBO01000625
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Klebsiella variicola At-22 chromosome: NC_013850
Dickeya zeae Ech1591: NC_012912
Edwardsiella tarda EIB202 plasmid pEIB202: NC_013509
Salmonella enterica subsp. enterica serovar Typhimurium str.
Salmonella enterica subsp. enterica serovar Choleraesuis str. SC-
Salmonella enterica subsp. enterica serovar Typhimurium str.
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont505.1: NZ_AFBO01000232
Salmonella enterica subsp. enterica serovar Typhi Ty2: NC_004631
Klebsiella pneumoniae NTUH-K2044 plasmid pK2044: NC_006625
The procedure was carried out as in Example 1, except that the following microorganisms were used: Bacterial Strains
The inventors selected 582 Proteus strains from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 2318 centroids of Proteus species were used as reference sequences.
The results for Proteus are shown in Tables 13 (corresponding to Table 1) and 14 (corresponding to Table 2).
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont338: NZ_ABVP01000020
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont6.1: NZ_ABVP01000019
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont356: NZ_ABVP01000021
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont350: NZ_ABVP01000014
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus mirabilis ATCC 29906 contig00088: NZ_ACLE01000064
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont356: NZ_ABVP01000021
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont338: NZ_ABVP01000020
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont334: NZ_ABVP01000024
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont6.1: NZ_ABVP01000019
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont6.1: NZ_ABVP01000019
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont338: NZ_ABVP01000020
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont356: NZ_ABVP01000021
Proteus mirabilis ATCC 29906 contig00105: NZ_ACLE01000079
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont338: NZ_ABVP01000020
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont6.1: NZ_ABVP01000019
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont356: NZ_ABVP01000021
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont350: NZ_ABVP01000014
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus mirabilis ATCC 29906 contig00088: NZ_ACLE01000064
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont356: NZ_ABVP01000021
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont338: NZ_ABVP01000020
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont341: NZ_ABVP01000022
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont334: NZ_ABVP01000024
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont6.1: NZ_ABVP01000019
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont6.1: NZ_ABVP01000019
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont338: NZ_ABVP01000020
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont348: NZ_ABVP01000026
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont344: NZ_ABVP01000025
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont356: NZ_ABVP01000021
Proteus mirabilis ATCC 29906 contig00105: NZ_ACLE01000079
Proteus mirabilis HI4320: NC_010554
Proteus penneri ATCC 35198 P_penneri-1.1.1_Cont336: NZ_ABVP01000023
The procedure was carried out as in Example 1, except that the following microorganisms were used: Bacterial Strains
The inventors selected 1042 Pseudomonas strains, particularly Pseudomonas aeruginosa, from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 640 centroids of Pseudomonas aeruginosa were used as reference sequences.
The results for P. aeruginosa are shown in Tables 15 (corresponding to Table 1) and 16 (corresponding to Table 2).
The procedure was carried out as in Example 1, except that the following microorganisms were used: Bacterial Strains
The inventors selected 634 Salmonella strains, particularly from Salmonella_choleraesuis, Salmonella_dublin, Salmonella_enterica_ssp_arizonae, Salmonella_enterica_ssp_diarizoniae, Salmonella_enteritidis, Salmonella_gallinarum, Salmonella_Group_A, Salmonella_Group_B, Salmonella_Group_C, Salmonella_Group_D, Salmonella_heidelberg, Salmonella_miami, Salmonella_newport, Salmonella_panama, Salmonella_parahaemolyticus_A, Salmonella_paratyphi_A, Salmonella_paratyphi_B, Salmonella_pullorum, Salmonella_senfienberg, Salmonella_species, Salmonella_species_Lac_−−,_ONPG_+, Salmonella_species_Lac_+,_ONPG_+, Salmonella_subgenus_I, Salmonella_subgenus_II, Salmonella_subgenus_IV, Salmonella_subgroup_I_Suc+, Salmonella_tennessee, and Salmonella_typhi, from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 713 centroids of Salmonella species were used as reference sequences.
The results for Salmonella species are shown in Tables 17 (corresponding to Table 1) and 18 (corresponding to Table 2).
Salmonella enterica subsp. enterica serovar Heidelberg str. SL476:
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Escherichia coli MS 175-1 E_coli175-1-1.0_Cont542.3: NZ_ADUB01000261
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid pKPN5:
Salmonella enterica subsp. enterica serovar Virchow str. SL491,
Escherichia fergusonii ATCC 35469 plasmid pEFER: NC_011743
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont44.1:
Escherichia coli B171, unfinished sequence: NZ_AAJX01000089
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont1175.2: NZ_AFBO01000625
Escherichia coli MS 182-1 E_coli182-1-1.0_Cont460.3: NZ_ADTM01000311
Escherichia coli MS 196-1 E_coli196-1-1.0_Cont1482.1:
Salmonella enterica subsp. enterica serovar Virchow str. SL491,
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid pKPN4:
Salmonella enterica subsp. enterica serovar Virchow str. SL491,
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont16.1:
Escherichia coli MS 124-1 E_coliMS124-1-1.0.1_Cont151.1:
Salmonella enterica subsp. enterica serovar Heidelberg str. SL476
Salmonella enterica subsp. enterica serovar Typhimurium str. T000240
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid pKPN4:
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Escherichia albertii TW07627, unfinished sequence: NZ_ABKX01000001
Salmonella enterica subsp. enterica serovar Typhimurium str. 4/74
Salmonella enterica subsp. enterica serovar Paratyphi C strain
Salmonella typhimurium LT2 plasmid pSLT: NC_003277
Salmonella enterica subsp. enterica serovar Typhimurium str. 14028S
Escherichia albertii TW07627, unfinished sequence: NZ_ABXX01000001
Salmonella enterica subsp. enterica serovar Paratyphi C strain
Salmonella enterica subsp. enterica serovar Paratyphi C strain
Salmonella enterica subsp. enterica serovar Typhimurium str. 4/74:
Salmonella enterica subsp. enterica serovar Heidelberg str. SL486,
Salmonella enterica subsp. enterica serovar Paratyphi C strain
Salmonella enterica subsp. enterica serovar Paratyphi C strain
Salmonella typhimurium LT2: NC_003197
Salmonella enterica subsp. enterica serovar Typhimurium str. 4/74
Salmonella enterica subsp. enterica serovar Saintpaul str. SARA23,
Salmonella enterica subsp. enterica serovar Paratyphi B str. SPB7;
Salmonella enterica subsp. enterica serovar Typhimurium str. T000240
Salmonella enterica subsp. arizonae serovar 62:z4,z23:--: NC_010067
Salmonella enterica subsp. arizonae serovar 62:z4,z23:--: NC_010067
Salmonella bongori NCTC 12419: NC_015761
Salmonella enterica subsp. enterica serovar Heidelberg str. SL486,
Salmonella enterica subsp. enterica serovar Paratyphi C strain
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Salmonella enterica subsp. enterica serovar Heidelberg str. SL476:
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Escherichia coli MS 175-1 E_coli175-1-1.0_Cont542.3: NZ_ADU301000261
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid pKPN5;
Salmonella enterica subsp. enterica serovar Virchow str. SI491,
Escherichia fergusonii ATCC 35469 plasmid pEFER: NC_011743
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont44.1: NZ_ADWV01000045
Escherichia coli B171, unfinished sequence: NZ_AAJX01000089
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont1175.2: NZ_AFBO01000625
Escherichia coli MS 182-1 E_coli182-1-1.0_Cont460.3: NZ_ADTM01000311
Escherichia coli MS 196-1 E_coli196-1-1.0_Cont1482.1: NZ_ADUD01000537
Salmonella enterica subsp. enterica serovar Virchow str. SI491,
Klebsiella pneumoniae subsp. pneumoniae MGH 78578 plasmid pKPN4:
Salmonella enterica subsp. enterica serovar Virchow str. SL491,
Escherichia coli MS 107-1 E_coliMS107-1-1.0.1_Cont16.1: NZ_ADWV01000017
Escherichia coli MS 124-1 E_coliMS124-1-1.0.1_Cont151.1:
Salmonella enterica subsp. enterica serovar Heidelberg str. SL476
Salmonella enterica subsp. enterica serovar Typhimurium str. T000240
Klebsiella pneumoniae subsp. pneumoniae MCH 78578 plasmid pKPN4:
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Escherichia albertii TW07627, unfinished sequence: NZ_ABXX01000001
Salmonella enterica subsp. enterica serovar Typhimurium str. 4/74
Salmonella enterica subsp. enterica serovar Paratyphi C strain RKS4594
Salmonella typhimurium LT2 plasmid pSLT: NC_003277
Salmonella enterica subsp. enterica serovar Typhimurium str. 14028S
Escherichia albertii TW07627, unfinished sequence: NZ_ABXX01000001
Salmonella enterica subsp. enterica serovar Paratyphi C strain RKS4594
Salmonella enterica subsp. enterica serovar Paratyphi C strain RKS4594:
Salmonella enterica subsp. enterica serovar Typhimurium str. 4/74:
Salmonella enterica subsp. enterica serovar Heidelberg str. SL486,
Salmonella enterica subsp. enterica serovar Paratyphi C strain RKS4594
Salmonella enterica subsp. enterica serovar Paratyphi C strain RKS4594;
Salmonella typhimurium LT2: NC_003197
Salmonella enterica subsp. enterica serovar Typhimurium str. 4/74
Salmonella enterica subsp. enterica serovar Saintpaul str. SARA23,
Salmonella enterica subsp. enterica serovar Paratyphi B str. SPB7:
Salmonella enterica subsp. enterica serovar Typhimurium str. T000240
Salmonella enterica subsp. arizonae serovar 62:z4,z23:--: NC_010067
Salmonella enterica subsp. arizonae serovar 62:z4,z23:--: NC_010067
Salmonella bongori NCTC 12419: NC_015761
Salmonella enterica subsp. enterica serovar Heidelberg str. SL486,
Salmonella enterica subsp. enterica serovar Paratyphi C strain RKS4594:
Salmonella enterica subsp. enterica serovar Schwarzengrund str. SL480,
The procedure was carried out as in Example 1, except that the following microorganisms were used: Bacterial Strains
The inventors selected 437 Serratia strains from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 1671 centroids of Serratia species were used as reference sequences.
The results for Serratia are shown in Tables 19 (corresponding to Table 1) and 20 (corresponding to Table 2).
Citrobacter sp. 30_2 genomic scaffold supercont1.9: NZ_GG657374
Pantoea sp. At-9b chromosome: NC_014837
Citrobacter sp. 30_2 genomic scaffold supercont1.9: NZ_GG657374
The procedure was carried out as in Example 1, except that the following microorganisms were used: Bacterial Strains
The inventors selected 442 Shigella strains, particularly Shigella boydii, Shigella dysenteriae, Shigella flexneri, Shigella sonnei and other Shigella species, from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing.
From MetaRef, 730 centroids of Shigella species were used as reference sequences.
The results for Shigella species are shown in Tables 21 (corresponding to Table 1) and 22 (corresponding to Table 2).
Escherichia coli MS 175-1 E_coli175-1-1.0_Cont166.1: NZ_ADU301000093
Escherichia coli MS 196-1 E_coli196-1-1.0_Cont1343.1: NZ_ADUD01000475
Escherichia coli MS 124-1 E_coliMS124-1-1.0.1_Cont5.1: NZ_ADWT01000006
Salmonella enterica subsp. enterica serovar Typhimurium str. T000240
Escherichia coli MS 175-1 E_coli175-1-1.0_Cont422.2: NZ_ADUB01000227
Escherichia coli MS 175-1 E_coli175-1-1.0_Cont823.2: NZ_ADUB01000365
Escherichia coli MS 175-1 E_coli175-1-1.0_Cont100.1: NZ_ADUB01000054
Escherichia albertii TW07627, unfinished sequence: NZ_ABXX01000001
Escherichia albertii TW07627, unfinished sequence: NZ_ABKX01000001
Escherichia coli MS 21-1 E_coli21-1-1.0_Cont744.1: NZ_ADTR01000390
Salmonella enterica subsp. enterica serovar Choleraesuis str. SC-367
Escherichia coli ED1a: NC_011745
Escherichia coli C157:H7 str. TW14588, unfinished sequence;
Escherichia coli UMNK88: CP002729
Escherichia coli S88: NC_011742
Salmonella enterica subsp. enterica serovar Kentucky str. CVM29188,
Escherichia coli C157:H7 str. EC4486, unfinished sequence:
Escherichia coli BW2952: NC_012759
Escherichia coli MS 196-1 E_coli196-1-1.0_Cont2124.2: NZ_ADUD01000718
Escherichia coli C157:H7 EDL933: NC_002655
Escherichia coli BL21(DE3): CP001509
Enterobacter cloacae subsp. cloacae NCTC 9394 draft genome.: FP929040
Klebsiella sp. MS 92-3 K_spMS92-3-1.0_Cont773.2: NZ_AFBC01000392
Escherichia coli MS 187-1 E_coli187-1-1.0_Cont287.1: NZ_ADTQ01000190
Klebsiella pneumoniae subsp. rhinoscleromatis ATCC 13884 contig00015:
Salmonella enterica subsp. enterica serovar Typhi str. E98-3139,
Escherichia coli 042: FN554766
Escherichia coli MS 115-1 E_coli115-1-1.0_Cont569.1: NZ_ADTL01000219
Escherichia coli C157:H7 str. EC4024, unfinished sequence:
Escherichia coli E22, unfinished secuence: NZ_AAJV01000016
Salmonellentericaenterica
—
EscherichcoliO157—
Escherichia coli MS 175-1 E—coli175-1-1.0_Cont166.1:
Escherichia coli MS 196-1 E—coli196-1-1.0_Cont1343.1:
Escherichia coli MS 124-1 E—coliMS124-1-1.0.1_Cont5.1:
Salmonella enterica subsp. enterica serovar Typhimurium
Shigella flexneri 2002017: CP001383
Shigella dysenteriae 1012, unfinished sequence:
Escherichia coli MS 175-1 E—coli175-1-1.0_Cont422.2:
Shigella dysenteriae 1012, unfinished sequence:
Shigella flexneri 2002017: CP001383
Escherichia coli MS 175-1 E—coli175-1-1.0_Cont823.2:
Escherichia coli MS 175-1 E—coli175-1-1.0_Cont100.1:
Shigella flexneri 2002017: CP001383
Edwardsiella tarda EI3202 plasmid pEIB202: NC_013509
Escherichia albertii TW07627, unfinished sequence:
Shigella sonnei Ss046: NC_007384
Shigella flexneri 2002017: CP001383
Escherichia albertii TW07627, unfinished sequence:
Escherichia fergusonii ATCC 35469 plasmid pEFER: NC_011743
Shigella dysenteriae 1617 gss1617.assembly.53:
Escherichia coli ED1a: NC_011745
Escherichia coli C157:H7 str. TW14588, unfinished sequence:
Escherichia coli S88: NC_011742
Edwardsiella tarda EI3202 plasmid pEIB202: NC_013509
Escherichia coli E22, unfinished sequence: NZ_AAJV01000016
Klebsiella pneumoniae NTUH-K2044: NC_012731
Escherichia fergusonii ATCC 35469: NC_011740
Escherichia fergusonii ATCC 35469: NC_011740
Escherichia coli B354 genomic scaffold supercont1.2:
Escherichia coli MS 69-1 E—coli69-1-1.0_Cont727.1:
Shigella flexneri 5 str. 8401: NC_008258
Shigella flexneri 5 str. 8401: NC_008258
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Citrobacter youngae ATCC 29220 C_sp-1.0_Cont0.2:
Escherichia fergusonii ATCC 35469: NC_011740
Shigella dysenteriae 1617 gss1617.assembly.21:
Shigella boydii CDC 3083-94: NC_010658
Escherichia fergusonii ATCC 35469: NC_011740
Salmonella enterica subsp. enterica serovar Schwarzengrund str.
Shigella sonnei Ss046 plasmid pSS046_spA: NC_009345
Escherichia fergusonii ATCC 35469: NC_011740
Escherichia albertii TW07627, unfinished sequence:
Escherichia coli ABU 83972: CP001671
Escherichia coli DH1: CP001637
Shigella flexneri 2a str. 2457T: NC_004741
Escherichia coli 53638, unfinished sequence:
Escherichia coli 2362-75 gec2362.assembly.47:
Escherichia albertii TW07627, unfinished sequence:
Escherichia coli MS 21-1 E—coli21-1-1.0_Cont515.2:
Shigella boydii CDC 3083-94: NC_010658
Citrobacter sp. 30_2 genomic scaffold supercont1.1:
Senteenterica_010100025269
The procedure was carried out as in Example 1, except for the following changes:
The inventors selected 1001 specimens of S. aureus from the microbiology strain collection at Siemens Healthcare Diagnostics (West Sacramento, CA) for susceptibility testing and whole genome sequencing, of which 985 had an assembly, a unique Kiel NGS ID (NGS data and assembly ID, a unique resistance profile (no different resistance profiles with different outcomes, and at least one drug with non-missing resistance value, so that these were further analyzed.
From MetaRef, 754 centroids of S. aureus were used as reference sequences.
Resistance/susceptibility was determined for the following antibiotics as described below:
Amoxicillin/Clavulanate, Ampicillin, Ampicillin/Sulbactam, Azithromycin, Cefalothin, Cefazolin, Cefepime, Cefotaxime, Cefoxitin, Ceftriaxone, Cefuroxime, Chloramphenicol, Ciprofloxacin, Clindamycin, Daptomycin, Ertapenem, Erythromycin, Fosfomycin, Fusidic acid, Gentamicin, Imipenem, Levofloxacin, Linezolid, Meropenem, Moxifloxacin, Mupirocin, Nitrofurantoin, Norfloxacin, Ofloxacin, Oxacillin, Penicillin G, Piperacillin/Tazobactam, Quinupristin/Dalfopristin, Rifampicin, Teicoplanin, Tetracycline, Tigecycline, Tobramycin, Trimethoprim/Sulfamethoxazole, and Vancomycin.
For testing, standard procedures were used, i.e. VITEK 2 system and AST cards (Biomerieux), Microscan system and AST panels (Beckmann Coulter).
DNA extraction and purification was carried out using the MagAttract HMW DNA Kit (Qiagen) procedure with the following changes. After up to 2×109 bacteria (1 ml culture) were centrifuged in a 2 ml tube (10 min, 5000×g) and the supernatant was discharged, it was again centrifuged 1 min and the sample was taken. The resulting pellet was dispersed in 160 μl P1, 20 μl lysozyme (100 mg/ml) and 4 μl lysostaphin were added and mixed, and the suspension was incubated at 37° C. at 900 rpm for 30 mins in a thermal mixer. Afterwards 300 μl lysis buffer and proteinase K (30 μl) (both from the blood kit for Maxwell of Promega) were added and the whole again incubated for 30 mins at 56° C. and 900 rpm. The samples as a whole (˜510 μl) were then transferred to the Maxwell cartridges for further processing, using the Tissue LEV Total RNA Kit AS1220 or the XAS1220 Custom Kit (Promega).
Next generation sequencing and data analysis was carried out as in Example 1.
The results for S. aureus are shown in Tables 23 (corresponding to Table 1) and 24 (corresponding to Table 2).
Staphylococcus epidermidis W23144:
Staphylococcus epidermidis M23864: W2(grey)
Staphylococcus epidermidis M23864: W2(grey)
Staphylococcus aureus subsp. aureus EMRSA16
Staphylococcus epidermidis 3CM-HMP0060:
Staphylococcus aureus A9719: NZ_ACKJ01000008
Staphylococcus
aureus subsp. aureus TW20:
Staphylococcus
aureus subsp. aureus TW20:
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A6300: NZ_ACKF01000035
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis M23864: W2(grey)
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A6300: NZ_ACKF01000007
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A8796 cont1.31:
Staphylococcus aureus subsp. aureus N315:
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus subsp. aureus TCH70:
Staphylococcus aureus A5937: NZ_ACKC01000026
Staphylococcus aureus A5937: NZ_ACKC01000026
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus subsp. aureus ECT-R 2:
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus RF122: NC_007622
Staphylococcus aureus subsp. aureus JH1:
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A8117 cont1.32:
Staphylococcus aureus subsp. aureus ECT-R 2:
Staphylococcus aureus subsp. aureus TCH130:
Staphylococcus aureus A6224: NZ_ACKE01000012
Staphylococcus aureus subsp. aureus JKD6159:
Staphylococcus aureus subsp. aureus C101
Staphylococcus aureus A6300: NZ_ACKF01000014
Staphylococcus aureus A9763: NZ_ACKK01000039
Staphylococcus aureus A6224: NZ_ACKE01000008
Staphylococcus aureus A8115: NZ_ACKG01000031
Staphylococcus aureus subsp. aureus JH1:
Staphylococcus aureus A8117 cont1.3:
Staphylococcus aureus subsp. aureus ECT-R 2
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus A8819 cont1.20:
Staphylococcus hominis subsp. hominis C80
Staphylococcus epidermidis W23144: NZ_ACJC01000132
Staphylococcus epidermidis M23864: W2 (grey)
Staphylococcus epidermidis M23864: W2 (grey)
Staphylococcus aureus subsp. aureus EMRSA16 genomic
Staphylococcus epidermidis 3CM-HMP0060: NZ_ACHE01000064
Staphylococcus aureus A9719: NZ_ACKJ01000008
Staphylococcus aureus subsp. aureus TW20: FN433596
Staphylococcus aureus subsp. aureus TW20: FN433596
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A6300: NZ_ACK301000035
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis M23864: W2 (grey)
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A6300: NZ_ACK301000007
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A8796 cont1.31: NZ_ADJJ01000031
Staphylococcus aureus subsp. aureus N315: NC_002745
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus subsp. aureus TCH70: NZ_ACHH01000128
Staphylococcus aureus A5937: NZ_ACKC01000026
Staphylococcus aureus A5937: NZ_ACKC01000026
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus subsp. aureus ECT-R 2: FR714927
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus RF122: NC_007622
Staphylococcus aureus subsp. aureus JH1: NC_009632
Staphylococcus epidermidis RP62A: NC_002976
Staphylococcus aureus A8117 cont1.32: NZ_ACY001000032
Staphylococcus aureus subsp. aureus ECT-R 2: FR714927
Staphylococcus aureus subsp. aureus TCH130: NZ_ACHO01000273
Staphylococcus aureus A6224: NZ_ACK301000012
Staphylococcus aureus subsp. aureus JK06159: CP002114
Staphylococcus aureus subsp. aureus C101 genomic scaffold
Staphylococcus aureus A6300: NZ_ACK301000014
Staphylococcus aureus A9763: NZ_ACKK01000039
Staphylococcus aureus A6224: NZ_ACK301000008
Staphylococcus aureus A8115: NZ_ACKG01000031
Staphylococcus aureus subsp. aureus JH1: NC_009632
Staphylococcus aureus A8117 cont1.3: NZ_ACYC01000003
Staphylococcus aureus subsp. aureus ECT-R 2 plasmid pLUH02:
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus 04-02981: CP001844
Staphylococcus aureus A8819 cont1.20: NZ_ADJK01000020
Staphylococcus hominis subsp. hominis C80 genomic scaffold
For examples 1-12, as well as further testes microorganisms, a consolidated List of the centroids that were found is given in the following Table 25.
Acinetobacter baumannii
Citrobacter koseri
Enterobacter aerogenes
Enterobacter cloacae
Escherichia coli
Klebsiella oxytoca
Klebsiella pneumoniae
Morganella morganii
Proteus
Pseudomonas aeruginosa
Salmonella
Shigella
Serratia marcescens
Stenotrophomonas maltophilia
Staphylococcus aureus
Staphylococcus aureus
Acinetobacter baumannii
Citrobacter koseri
Enterobacter aerogenes
Enterobacter cloacae
Escherichia coli
Klebsiella oxytoca
Klebsiella pneumoniae
Morganella morganii
Proteus
Pseudomonas aeruginosa
Salmonella
Shigella
Serratia marcescens
Stenotrophomonas maltophilia
Staphylococcus aureus
Staphylococcus aureus
In Table 25 herein the number of significant centroids (with the respective p-values) found by the present method before and after the above filtering process is given. This shows that, while the best 50 gene sequences are given for the Examples in the odd Tables (Tables 1, 3, 5, etc.), more than those 50 gene sequences were actually found for all the examples after filtering, e.g. 810 for Acinetobacter baumannii.
As noted above, for the even Tables (Tables 2, 4, 6, etc.) the data are further processed.
As can be seen from the Examples, similarities in gene sequences can be found over all the bacterial species, showing that they form clusters, which can also be seen in the fact that for several bacteria centroids from other bacterial species are found as suitable, e.g. from E. coli.
A genetic test for the combined pathogen identification and antimicrobial susceptibility testing direct from the patient sample can reduce the time—to actionable result significantly from several days to hours, thereby enabling targeted treatment. Furthermore, this approach will not be restricted to central labs, but point of care devices can be developed that allow for respective tests. Such technology along with the present methods and computer program products could revolutionize the care, e.g. in intense care units or for admissions to hospitals in general. Furthermore, even applications like real time outbreak monitoring can be achieved using the present methods.
Compared to approaches using MALDI-TOF MS, the present approach has the advantage that it covers almost the complete genome and thus enables us to identify the potential genomic structural changes that might be related to resistance. While MALDI-TOF MS can also be used to identify point mutations in bacterial proteins, this technology only detects a subset of proteins and of these not all are equally well covered. In addition, the identification and differentiation of certain related strains is not always feasible.
The present method allows computing a best breakpoint for the separation of isolates into resistant and susceptible groups. The inventors designed a flexible software tool that allows to consider-besides the best breakpoints—also values defined by different guidelines (e.g. European and US guidelines), preparing for an application of the GAST in different countries.
The current approach enables
The current method is faster than classical culture-based predictions and has the potential to be faster than tests based on single bases, e.g. SNPs. Most remarkably the current method can help improve the accuracy of novel genetic tests.
With the present methods, structural variations can be detected, which particularly also include copy-number variations that can lead to gene dosage effects.
| Number | Date | Country | Kind |
|---|---|---|---|
| 15180042.2 | Aug 2015 | EP | regional |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15749384 | Jan 2018 | US |
| Child | 18440585 | US |
