Patent Application
20230183818
The present disclosure relates to microorganisms and related biology as well as to diagnosis and treatment of related conditions in individuals. In particular, the present disclosure relates to antibiotic susceptibility of microorganisms and related markers, compositions, methods and systems.
Antibiotic susceptibility is an important feature of the biology of various microorganisms, which can be used in identifying approaches to treat or prevent bacterial infections.
Ideal antibiotic therapy is based on determination of the etiological agent for a particular condition and determination of the antibiotic sensitivity of the identified agent. In particular, the effectiveness of individual antibiotics varies with various factors including the ability of the microorganism to resist or inactivate the antibiotic.
Despite progress in identifying methods and systems to test antibiotic susceptibility for various microorganisms, as well as the identification of related markers, determination of antibiotic susceptibility can still be challenging. In particular, determination of antibiotic susceptibility when a rapid and accurate detection is desired for microorganisms such as Neisseria gonorrhoeae which are slow growing and lack the classic transcriptional SOS response to DNA damage.
Provided herein are RNA markers of antibiotic (sometimes abbreviated as ABX) susceptibility of microorganisms and related compositions, methods and systems that can be used for their identification and/or use. In particular described herein are RNA markers and related methods and systems to test antibiotic susceptibility of microorganisms as well as RNA markers and related methods and systems for the diagnosis and/or treatment of related infections in individuals.
According to a first aspect, a method is described to identify a RNA marker of antibiotic susceptibility in a microorganism. The method comprises providing a susceptible isolate or specimen comprising a strain of the microorganism susceptible to the antibiotic and a resistant isolate or specimen comprising a strain of the microorganism resistant to the antibiotic.
The method further comprises providing a susceptible (Cs:Ts) value for a candidate marker gene in the susceptible isolate or specimen, wherein Cs is a control susceptible gene expression value Cs for a candidate marker in a control susceptible sample not treated with the antibiotic and Ts is a treated susceptible gene expression for the candidate marker in a treated susceptible sample treated with the antibiotic.
The method also comprises providing a resistant (Cr:Tr) value for a candidate marker gene in the resistant isolate or specimen, wherein Cr is a control resistant gene expression value for the candidate marker in a control resistant sample not treated with the antibiotic and Tr is a treated resistant gene expression for the candidate marker in a treated resistant sample treated with the antibiotic. The method additionally comprises selecting the candidate marker gene when Cs:Ts in the susceptible isolate or specimen is different from Cr:Tr in the resistant isolate or specimen to provide a selected marker gene expressing the RNA marker of antibiotic susceptibility of the microorganism. In particular the selected marker gene is therefore differentially expressed in the treated samples of the susceptible isolate or specimen compared with the resistant isolate or specimen as will be understood by a skilled person.
According to a second aspect, an RNA marker of antibiotic susceptibility in a microorganism, a corresponding marker gene and/or a corresponding cDNA are described, which can be obtained by the method to identify an RNA marker of antibiotic susceptibility herein described.
In some embodiments the RNA marker can be selected from a transcript encoding for a ribosomal protein of the microorganism. In some of those embodiments the RNA marker can be selected from a transcript encoding for a 30S ribosomal protein and 50S ribosomal protein. In some embodiments, the RNA marker can be selected from: a transcript of N. gonorrhoeae gene having locus tag NGO0340, a transcript of N. gonorrhoeae gene having locus tag NGO1837, a transcript of N. gonorrhoeae gene having locus tag NGO1843, a transcript of N. gonorrhoeae gene having locus tag having locus tag NGO2024, a transcript of N. gonorrhoeae gene having locus tag NGO1845, a transcript of N. gonorrhoeae gene having locus tag NGO1677, a transcript of N. gonorrhoeae gene having locus tag NGO1844, a transcript of N. gonorrhoeae gene having locus tag NGO0171, a transcript of N. gonorrhoeae gene having locus tag NGO1834, a transcript of N. gonorrhoeae gene having locus tag NGO0172, a transcript of N. gonorrhoeae gene having locus tag NGO1835, a transcript of N. gonorrhoeae gene having locus tag NGO1673, a transcript of N. gonorrhoeae gene having locus tag NGO1833, a transcript of N. gonorrhoeae gene having locus tag NGO2173, a transcript of N. gonorrhoeae gene having locus tag NGO0604, a transcript of N. gonorrhoeae gene having locus tag NGO0016, a transcript of N. gonorrhoeae gene having locus tag NGO1676, a transcript of N. gonorrhoeae gene having locus tag NGO1679, a transcript of N. gene having locus tag NGO1658 and encoding hypothetical protein, a transcript of N. gonorrhoeae gene having locus tag NGO1440, a transcript of N. gonorrhoeae gene having locus tag NGO0174, a transcript of N. gonorrhoeae gene having locus tag NGO0173, a transcript of N. gonorrhoeae gene having locus tag NGO0592, a transcript of N. gonorrhoeae gene having locus tag NGO1680, a transcript of N. gonorrhoeae gene having locus tag NGO0620, a transcript of N. gonorrhoeae gene having locus tag NGO1659, a transcript of N. gonorrhoeae gene having locus tag NGO1291, a transcript of N. gonorrhoeae gene having locus tag NGO0648, a transcript of N. gonorrhoeae gene having locus tag NGO0593, a transcript of N. gonorrhoeae gene having locus tag NGO1804, a transcript of N. gonorrhoeae gene having locus tag NGO0618, a transcript of N. gonorrhoeae gene having locus tag NGO0619, a transcript of N. gonorrhoeae gene having locus tag NGO1812, a transcript of N. gonorrhoeae gene having locus tag NGO1890, a transcript of N. gonorrhoeae gene having locus tag NGO2098, a transcript of N. gonorrhoeae gene having locus tag NGO2100 and a transcript tRNA having GeneID A9Y61_RS02445 or NGO_t12, a tRNA transcript having GeneID A9Y61_RS04515 or NGO_t15, a transcript tRNA having GeneID A9Y61_RS04510 or NGO_t14, a transcript tRNA having GeneID A9Y61_RS09170 or NGO_t37, or a transcript tRNA having GeneID A9Y61_RS00075 or NGO_t01. The locus tags and GeneIDs of the transcripts of N. gonorrhoeae gene are the locus tags and GeneIDs of the registry of locus_tag prefixes of databases of the International Nucleotide Sequence Database Collaboration (INSDC) at the filing date of the present disclosure.
According to a third aspect, a method is described to detect a transcript of an N. gonorrhoeae. The method comprises quantitatively detecting in the N. gonorrhoeae a transcript expression value of an RNA marker of N. gonorrhoeae selected from any one of the RNA markers of N. gonorrhoeae herein described, following contacting of the N. gonorrhoeae with an antibiotic to obtain an antibiotic treated transcript expression value for the RNA marker of N. gonorrhoeae
According to a fourth aspect, a method to perform an antibiotic susceptibility test for N. gonorrhoeae is described. The method comprises detecting susceptibility to an antibiotic of an N. gonorrhoeae, by quantitatively detecting in a sample comprising the N. gonorrhoeae a transcript expression value of an RNA marker of N. gonorrhoeae selected from the RNA markers of an N. gonorrhoeae herein described following contacting the sample with the antibiotic.
According to a fifth aspect a method is described to detect an RNA marker of susceptibility to an antibiotic in N. gonorrhoeae in a sample comprising the N. gonorrhoeae. The method comprises contacting the sample with the antibiotic to obtain an antibiotic treated sample and quantitatively detecting in the antibiotic treated sample one or more of the RNA marker of N. gonorrhoeae herein described.
According to a sixth aspect, a method to diagnose susceptibility to an antibiotic of a N. gonorrhoeae infection in an individual is described. The method comprises contacting with the antibiotic a sample from the individual comprising N. gonorrhoeae; and quantitatively detecting expression by the N. gonorrhoeae in the sample of a marker of antibiotic susceptibility in N. gonorrhoeae selected from any one of the transcripts of N. gonorrhoeae genes herein described. In the method, the quantitatively detecting is performed following or upon contacting the sample with the antibiotic. The method further comprises detecting whether there is a downshift of the transcript presence quantitatively detected in the antibiotic treated sample with respect to the transcript presence in a sample from the individual not treated with antibiotic and comprising N. gonorrhoeae to diagnose the antibiotic susceptibility of the N. gonorrhoeae infection in the individual.
According to a seventh aspect, a method is described to detect antibiotic susceptibility of an N. gonorrhoeae bacterium and treat N. gonorrhoeae in an individual. The method comprises contacting a sample from the individual with an antibiotic, and quantitatively detecting in the sample, expression by the N. gonorrhoeae bacteria of a marker of antibiotic susceptibility selected from any one of the transcripts of N. gonorrhoeae genes herein described. In the method, the quantitatively detecting is performed following contacting the sample with the antibiotic. The method further comprises diagnosing antibiotic susceptibility of N. gonorrhoeae infection in the individual when a downshift in expression of at least one of the detected markers in the sample is detected in comparison with a control untreated sample of the individual. The method also comprises administering an effective amount of the antibiotic to the diagnosed individual.
According to an eighth aspect, a system is described for performing at least one of the methods herein described to detect an N. gonorrhoeae transcript, to detect antibiotic susceptibility of an N. gonorrhoeae bacteria, to perform an antibiotic susceptibility test for an N gonorrhoeae, and/or to diagnose and/or treat an N. gonorrhoeae in an individual. The system comprises at least one probe specific for a transcript selected from any one of the transcripts of N. gonorrhoeae genes herein described or for a polynucleotide complementary thereof, and reagents for detecting the at least one probe.
In additional aspects, methods and systems are described, in which RNA markers and related marker genes and cDNAs of a microorganism other than N. gonorrhoeae in accordance with the second aspect of the disclosure, are used in place of N. gonorrhoeae RNA markers and related genes and cDNA to: i) detect a transcript of the another microorganism, ii) perform an antibiotic susceptibility test for the another microorganism, detect an RNA marker of susceptibility to an antibiotic in the another microorganism, diagnose susceptibility to an antibiotic of the another microorganism infection in an individual, and/or detect antibiotic susceptibility of the another microorganism and treat the another microorganism in an individual, the methods and systems comprising the features according to the third to the eighth aspect of the instant disclosure. In some of these embodiments the another microorganism is N. meningitidis.
RNA markers and related compositions methods and systems herein described allow in several embodiments to elicit in a microorganism, (e.g. N gonorrhoeae) phenotypic responses to antibiotics that are faster and greater in magnitude compared to responses in DNA markers. Therefore, in several embodiments RNA markers and related compositions methods and systems herein described allow phenotypic measurements of antibiotic susceptibility and resistance of a microorganism (e.g. N gonorrhoeae).
RNA markers and related compositions methods and systems herein described allow in several embodiments to identify as markers of antibiotic susceptibility responsive transcripts with the highest abundance and fold changes, as well as validated gene expression.
RNA markers and related compositions methods and systems herein described allow in several embodiments to perform an accurate and rapid antibiotic susceptibility test for N. gonorrhoeae based on RNA signatures.
RNA markers and related compositions methods and systems herein described allow in several embodiments to compensate for errors in sample splitting between treated and control samples and to compensate for errors in sample preparation.
RNA markers and related compositions methods and systems herein described can be used in connection with various applications wherein identification and/or detection of antibiotic susceptibility for a microorganism is desired, in particular when the microorganism is N gonorrhoeae. For example, RNA markers and related compositions methods and systems herein described can be used in drug research and to develop diagnostic and therapeutic approaches and tools to counteract infections, in particular for N gonorrhoeae. Additional exemplary applications include uses of the RNA markers and related compositions methods and systems herein described in several fields including basic biology research, applied biology, bio-engineering, aetiology, medical research, medical diagnostics, therapeutics, and in additional fields identifiable by a skilled person upon reading of the present disclosure.
The details of one or more embodiments of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.
The accompanying drawings, which are incorporated into and constitute a part of this specification, illustrate one or more embodiments of the present disclosure and, together with the detailed description and example sections, serve to explain the principles and implementations of the disclosure. Exemplary embodiments of the present disclosure will become more fully understood from the detailed description and the accompanying drawings, wherein:
The accompanying ANNEX A provides exemplary 16S rRNA and 23S rRNA sequences (SEQ ID NO: 1-9 and 13-27) that can be used as control transcript for normalization. ANNEX B provides exemplary marker genes (SEQ ID NO: 28-153 and 228-230) differentially expressed by an exemplary microorganism (N. gonorrhoeae) in an untreated sample and in a sample treated with an antibiotic. ANNEX C provides exemplary marker genes (SEQ ID NO: 154-159) expected to be differentially expressed by an exemplary microorganism (N. meningitidis) in an untreated sample and in a sample treated with an antibiotic. ANNEX D provides sequences of an exemplary marker of antibiotic susceptibility (porB) in 50 clinical isolates from the Center of Disease Control and Prevention (CDC) bank (SEQ ID NO: 178-227). ANNEX E provides a list of exemplary RNAs reported in Table 1 (SEQ ID NO: 231-344 and SEQ ID NO: 10-12) with a log2 fold change less than 0.32 (corresponding to <25% change) that can be used as control transcripts. ANNEX A to E which are incorporated into and constitute a part of this specification, together with the detailed description section, serve to explain the principles and implementations of the disclosure. Other features, objects, and advantages will be apparent from the entire description and drawings, and from the claims.
Provided herein are RNA markers of antibiotic susceptibility of microorganisms and related compositions, methods and systems for their identification and/or use.
The term “RNA” or “Ribonucleic acid” as used herein indicates a polynucleotide composed of our of ribonucleotide bases: or an analog thereof linked to form an organic polymer. The term “ribonucleotide” refers to any compounds that consist of a ribose (ribonucleotide) sugar joined to a purine or pyrimidine base and to a phosphate group, and that are the basic structural units of a ribonucleic acid, typically adenine (A), cytosine (C), guanine (G), and uracil (U). In an RNA adjacent ribose nucleotide bases are chemically attached to one another in a chain typically via phosphodiester bonds. The term “ribonucleotide analog” refers to a ribonucleotide in which one or more individual atoms have been replaced with a different atom with a different functional group. For example, ribonucleotide analogues include chemically modified ribonucleotides, such as methylation hydroxymethylation glycosylation and additional modifications identifiable by a skilled person. Examples of chemical modifications of RNA comprise dynamic modifications to RNA identified in the transcriptome, including N6-methyladenosine (m6A), inosine (I), 5-methylcytosine (m5C), pseudouridine (Ψ), 5-hydroxymethylcytosine (hm5C), and N1-methyladenosine (m1A), and related epitranscriptome which are described in Song and Yi 2017,. [1] Additional chemical modifications of transfer RNA (tRNA) are described in Jackman and Alfonzo 2013 [2] (Accordingly, the term RNA includes ribonucleic acids of any length including analogs or fragments thereof.
The term “marker” as used herein refers to a category of characteristics that are objectively measured and evaluated as an indicator of biological processes, pathogenic processes, or pharmacologic response to a therapeutic intervention or an environmental exposure. A marker can be any molecule associated with the process and/or response of interest and that can be used as an identifier to detect the process and/or response of interest, such as certain characteristics in a microorganism and/or its response to a therapeutic intervention or an environmental exposure including exposure to antibiotics.
The term “antibiotic” sometimes abbreviated as ABX, as used herein refers to a type of antimicrobial used in the treatment and prevention of bacterial infection. Some antibiotics can either kill or inhibit the growth of bacteria. Others can be effective against fungi and protozoans. The term “antibiotic” can be used to refer to any substance used against microbes. Antibiotics are commonly classified based on their mechanism of action, chemical structure, or spectrum of activity. Most antibiotics target bacterial functions or growth processes. Antibiotics having bactericidal activities target the bacterial cell wall, such as penicillins and cephalosporins, or target the cell membrane, such as polymyxins, or interfere with essential bacterial enzymes, such as rifamycins, lipiarmycins, quinolones and sulfonamides. Antibiotics having bacteriostatic properties target protein synthesis, such as macrolides, lincosamides and tetracyclines. Antibiotics can be further categorized based on their target specificity. “Narrow-spectrum” antibacterial antibiotics target specific types of bacteria, such as Gram-negative or Gram-positive bacteria. “Broad-spectrum” antibiotics affect a wide range of bacteria. Exemplary antibiotics comprise topoisomerase inhibitors which are chemical compounds capable of blocking the action of a topoisomerase such as topoisomerase I and II (a type of enzyme that controls the changes in DNA structure by catalyzing the breaking and rejoining of the phosphodiester backbone of DNA strands during the normal cell cycle) and fluoroquinolones which are quinolones containing a fluorine atom in their chemical structure and are effective against both Gram-negative and Gram-positive bacteria. A quinolone antibiotic indicates any member of a large group of broad-spectrum bactericides that share a bicyclic core structure related to the compound 4-quinolone. Exemplary fluoroquinolones include ciprofloxacin (Cipro), gemifloxacin (Factive), levofloxacin (Levaquin), moxifloxacin (Avelox), norfloxacin (Noroxin), and ofloxacin (Floxin).
The wording “antibiotic susceptibility” or “antibiotic sensitivity” as used herein indicates the susceptibility of bacteria to antibiotics and the antibiotic susceptibility can vary within a species. Antibiotic susceptibility testing (AST) can be carried out to predict the clinical response to treatment and guide the selection of antibiotics as will be understood by a person skilled in the art. In some embodiments, AST categorizes organisms as susceptible, resistant, or intermediate to a certain antibiotic.
Microorganisms can be classified as susceptible (sensitive), intermediate or resistant based on breakpoint minimum inhibitory concentration (MIC) values that are arbitrarily defined and reflect the achievable levels of the antibiotic, the distribution of MICs for the organism and their correlation with clinical outcome. MIC value of a microorganism is the lowest concentration of an antibiotic that will inhibit its growth. Methods that can be used to measure the MIC of a microorganism comprise broth dilution, agar dilution and gradient diffusion (the ‘E test’), where twofold serial dilutions of antibiotic are incorporated into tubes of broth, agar plates or on a paper strip, respectively, as will be understood by a person skilled in the art. The disk diffusion method defines an organism as susceptible or resistant based on the extent of its growth around an antibiotic-containing disk. MIC values are influenced by several laboratory factors.
Laboratories follow standard for parameters such as incubation temperature, incubation environment, growth media, as well as inoculum and quality control parameters. In the U.S., standards for performing AST as well as breakpoint MIC values for various bacteria can be found in Clinical & Laboratory Standards Institute (CLSI) publications (see the web page https://clsi.org/standards/products/microbiology/documents/m100/ at the date of filing of the present disclosure). An example of standards for performing an Antibiotic Susceptibility Test (AST) as well as breakpoint MIC values for various bacteria which can be used in embodiments of the present disclosure is provided in Example 16. In Europe, standards for performing AST as well as breakpoint MIC values for bacteria can be found in European Committee on Antimicrobial Susceptibility Testing (EUCAST) see http://www.eucast.org/clinical_breakpoints/ at the time of filing of the instant disclosure) as will be understood by the skilled person.
The term “microorganism”, or “microbe” as used herein indicates a microscopic organism, which may exist in its single-celled form or in a colony of cells, such as prokaryotes and in particular bacteria.
The term “prokaryotic” is used herein interchangeably with the terms “cell” and refers to a microbial species which contains no nucleus or other organelles in the cell. Exemplary prokaryotic cells include bacteria.
The term “bacteria” or “bacterial cell”, used herein interchangeably with the terms “cell” indicates a large domain of prokaryotic microorganisms. Typically a few micrometers in length, bacteria have a number of shapes, ranging from spheres to rods and spirals, and are present in several habitats, such as soil, water, acidic hot springs, radioactive waste, the deep portions of Earth’s crust, as well as in symbiotic and parasitic relationships with plants and animals. Bacteria in the sense of the disclosure refers to several prokaryotic microbial species which comprise Gram-negative bacteria Gram-positive bacteria, Proteobacteria, Cyanobacteria, Spirochetes and related species, Planctomyces, Bacteroides, Flavobacteria, Chlamydia, Green sulfur bacteria, Green non-sulfur bacteria including anaerobic phototrophs, Radioresistant micrococci and related species, Thermotoga and Thermosipho thermophiles as would be understood by a skilled person. More specifically, the wording “Gram positive bacteria” refers to cocci, nonsporulating rods and sporulating rods, such as, for example, Actinomyces, Bacillus, Clostridium, Corynebacterium, Erysipelothrix, Lactobacillus, Listeria, Mycobacterium, Myxococcus, Nocardia, Staphylococcus, Streptococcus and Streptomyces.
The term “proteobacteria” as used herein refers to a major phylum of Gram-negative bacteria. Many move about using flagella, but some are nonmotile or rely on bacterial gliding. As understood by skilled persons, taxonomic classification as proteobacteria is determined primarily in terms of ribosomal RNA (rRNA) sequences. The Proteobacteria are divided into six classes, referred to by the Greek letters alpha through epsilon and the Acidithiobacillia and Oligoflexia, including alphaproteobacteria, betaproteobacteria and gammaproteobacteria as will be understood by a skilled person. Proteobacteria comprise the species: N. gonorrhoeae and N meningitidis within the class of Betaproteobacteria, the order: Neisseriales the Family of Neisseriaceae and the Genus of Neisseria.
In embodiments of the instant disclosure, RNA markers are described and related methods and systems to test antibiotic susceptibility of microorganisms as well as for the diagnosis and/or treatment of related infections in individuals.
In particular, in some embodiments described herein is a method to identify an RNA marker of antibiotic susceptibility in a microorganism. The method herein described is based on the use of a susceptible isolate or specimen comprising a strain of the microorganism susceptible to the antibiotic and of a resistant isolate or specimen comprising a strain of the microorganism resistant to the antibiotic.
The term “isolate” as used herein indicates a portion of matter resulting from a separation of a strain of a microorganism from a natural, usually mixed population of living microbes, as present in a natural or experimental environment, for example in water or soil flora, or from living beings with skin flora, oral flora or gut flora.
The word “specimen” as used herein indicates a portion of matter from an environment for use in testing, examination, or study. The environment can comprise living beings and in particular human beings. In these instances a specimen can include portion of tissues, organs or other biological material from the living being such as urethra, urine, cervix, vagina, rectum, oropharynges, conjunctiva, or any body fluids.
In some embodiments, the isolates can be obtained from isolate banks such as CDC and FDA AR Isolate Bank which provide curated collections of susceptible and resistant organisms. In particular in embodiments wherein the microorganism is N. gonorrhoeae, the susceptible and resistant isolates are obtained from the N. gonorrhoeae panel of the CDC Antimicrobial Resistance Isolate Bank, which as of Aug. 1, 2018 contained 50 total isolates.
In methods to identify such an RNA marker of antibiotic susceptibility in a microorganism herein described, the selected RNA marker of antibiotic susceptibility identified by the method is a transcript of a gene which is differentially expressed in a sample of the susceptible isolate or specimen treated with the antibiotic and in sample of the resistant isolate or specimen treated with the antibiotic.
The term “sample” as used herein indicates a limited quantity of something that is indicative of a larger quantity of that something, including but not limited to fluids from an isolate or a specimen such as biological environment, cultures, tissues, commercial recombinant proteins, synthetic compounds or portions thereof. In particular biological sample can comprise one or more cells of any biological lineage, as being representative of the total population of similar cells in the sampled individual. Exemplary biological samples comprise the following: cheek tissue, whole blood, dried blood spots, organ tissue, plasma, urine, mucus, mucosal secretions, vaginal fluids and secretions, urethral fluids and secretions, feces, skin, hair, or tumor cells, among others identifiable by a skilled person. Biological samples can be obtained using sterile techniques or non-sterile techniques, as appropriate for the sample type, as identifiable by persons skilled in the art. Some biological samples can be obtained by contacting a swab with a surface on a human body and removing some material from said surface, examples include throat swab, urethral swab, oropharyngeal swab, cervical swab, vaginal swab, genital swab, anal swab. Depending on the type of biological sample and the intended analysis, biological samples can be used freshly for sample preparation and analysis, or can be fixed using fixative. Preferably, in methods and systems herein described the sample comprises live cells.
The wording “differentially expressed” as used herein with respect to a gene indicates a difference in the expression of the gene by a cell under different experimental, environmental and/or biological conditions. Accordingly, differential expression of a gene can be detected in a microorganism following a different in one or more of these conditions as will be understood by a skilled person. For example, the wording “differentially expressed” can reference to a difference in the expression of a gene in a microorganism: i) with or without drug treatment, ii) on a same sample or different samples, and/or iii) at different times. Accordingly, differential expression analysis requires that gene expression values detected under the different conditions be compared and therefore that the expression of the genes be quantitatively detected.
In particular, detection of a differential expression of a gene in a susceptible or resistant isolate or specimen according to methods herein described can be performed by quantitatively detecting the expression of the gene in samples of the susceptible and resistant isolate or specimen.
The terms “detect” or “detection” as used herein indicates the determination of the existence, presence or fact of a target in a limited portion of space, including but not limited to a sample, a reaction mixture, a molecular complex and a substrate. The “detect” or “detection” as used herein can comprise determination of chemical and/or biological properties of the target, including but not limited to ability to interact, and in particular bind, other compounds, ability to activate another compound and additional properties identifiable by a skilled person upon reading of the present disclosure. The detection can be quantitative or qualitative. A detection is “quantitative” when it refers, relates to, or involves the measurement of quantity or amount of the target or signal (also referred as quantitation), which includes but is not limited to any analysis designed to determine the amounts or proportions of the target or signal. A detection is “qualitative” when it refers, relates to, or involves identification of a quality or kind of the target or signal in terms of relative abundance to another target or signal, which is not quantified.
An exemplary way to quantitatively detect differential expression is the fold change approach which can be used as a criterion to select differentially expressed genes as will be understood by a person skilled in the art. In the fold-change approach, a gene is considered to be differentially expressed if the ratio of the normalized marker expression level, possibly normalized, between the antibiotic treated and untreated conditions exceeds a certain threshold
In methods herein described, quantitative detection of expression of a gene can be performed with various techniques such as by RNA-seq, qPCR, digital PCR, and isothermal techniques such as LAMP or digital isothermal, microarrays signals, Nanostring as well high throughput RNA sequencing as reads per kilobase per million reads (RPKM) or transcripts per million (TPM) for RNA-seq data and additional nucleic acid quantification techniques identifiable to a skilled person. It should be understood that in such methods quantitative detection of expression of a gene is commonly combined with a reverse transcription step to convert the RNA sequence into a cDNA sequence which can be quantified by methods described herein and/or identifiable by a skilled person. Either sequence-specific or sequence-non-specific primers can be used to initiate reverse transcription of a target gene as will be understood by a skilled person.
In some embodiments, detecting specific gene expression can be performed at the transcription level by performing RNA-seq and calculating RNA expression values based on the sequence data.
In some embodiments, the RNA expression values can be detected and provided as transcripts per million (TPM) as will be understood by a person skilled in the art. In particular, to calculate TPM, read counts are first divided by the length of each gene in kilobases, which gives reads per kilobase (RPK). RPKs for all genes are added and the sum is divided by 1,000,000. This gives the “per million” scaling factor. Finally, the RPK value for each genes is divided by the “per million” scaling factor to give TPM. [3]
In particular, in method to identify an RNA marker of antibiotic susceptibility herein described, quantitatively detecting the expression of a gene is performed in treated samples of the susceptible and resistant isolate or specimen following treatment of the samples with the antibiotic and in control samples of the susceptible and resistant isolate or specimen without treatment with the antibiotic.
In some of these embodiments, providing a treated sample and a control sample of the susceptible and/or resistant isolate or specimen can comprise contacting a first sample of the susceptible and/or resistant isolate or specimen with a treatment media to obtain the susceptible and/or resistant control samples respectively and contacting a second sample of the susceptible and/or resistant isolate or specimen from the same source or host with the same treatment media and an antibiotic to obtain a susceptible and/or resistant antibiotic treated sample respectively. The contacting time (referring to the duration of the contact) with the treatment media is preferably substantially the same for the control sample and the treated sample. The wording “substantially the same” when referred to two or more times indicates times differing one from another of an amount up to 30%, Accordingly, for example two contacting times are substantially the same in the sense of the disclosure, if they are within approximately 30% of each other, 20% of each other, 10% of each other, 5% of each other. For example, the two contacting times can be within 2 minutes of each other, or within 1 minute of each other.
In some particular embodiments, treatment of a sample with a treatment media is performed to create a controlled environment that would minimize the impact of biochemical parameters of a sample, such as pH or salt concentration or presence of molecules other than RNA or cells (human cells or other microorganisms other than target microorganism from which gene expression is to be detected)) on the gene expression and RNA response of the target microorganism to an external stimulus such as a antibiotic treatment and/or quantitative detection of gene expression. Treatment media can be used to create a more controlled environment for obtaining a more reliable gene expression. For example, treatment media can be composed of commercially available broths designed for the cultivation of microorganisms (such as Fastidious Broth from Hardy Diagnostics) or prepared using chemically defined components. In some cases, commercial broths can be diluted to create the desired treatment environment. For example, a specific osmolarity (for example in the range 0.0 - 0.5 osmols) or pH (for example in the range 5 - 9). Treatment media can be modified to contain specific factors to increase or decrease the metabolism of the target microorganism (such as carbon source or specific anions or cations). Gentle or vigorous mixing can be performed at specific time intervals after the addition of microorganisms to the treatment media in order to maintain homogeneity and reliable gene expression.
In some embodiments, a control sample and/or treated sample of the susceptible and/or resistant isolate or specimen can preferably be pretreated to enrich said sample with RNA or with the target microorganism, and/or to remove human RNA or RNA of other microorganisms. The removal of human RNA can be performed via hybridization to beads or columns with probes specific for human RNA. The removal of human RNA can also be performed via selective lysis of human cells and degradation of released human RNA. The sample may also be pretreated to enrich or deplete, as desired, tRNA via size selection.
In some embodiments, treatment or exposure with antibiotic can be performed by adding antibiotics to the microorganism and incubating the sample under certain condition preferably following and/or upon contacting the sample with a treatment media.
Treatment media used in connection with antibiotic exposure in accordance to methods herein described can be designed to support physiological processes of the target microorganism, enable or accelerate DNA replication and translation, maintain cellular uniformity and homogeneity in suspension, and promote interaction of the microorganism and antibiotic. Accordingly, the treatment media can be selected to include a source of energy and nourishment specific for the target microorganism, such as carbon, hydrogen, oxygen, nitrogen phosphorus, Sulphur, potassium, magnesium, calcium, iron, trace elements and organic growth factors which can be provided as organic sources such as simple sugars e.g. glucose, acetate or pyruvate, amino acids, nitrogenous bases or extracts such as peptone, tryptone, yeast extract and additional identifiable by a skilled person., Inorganic sources such as ; carbon dioxide (CO2) or hydrogen carbonate salts (HCO3)NH4CI, (NH4)2S04, KNO3, and for dinitrogen fixers N2, KH2PO4, Na2HPO4, Na2SO4, H2S, KCI, K2HPO4, MgCI2, MgSO4, CaCI2, Ca(HC03)2, NaCI, FeCI3, Fe(NH4)(SO4)2, Fe-chelates1), CoCI2, ZnCI2, Na2MoO4, CuCI2, MnSO4, NiCI2, Na2SeO4, Na2WO4, Na2VO4, as well as Vitamins, amino acids, purines, pyrimidines (see the website https://www.sigmaaldrich.com/technical-documents/articles/microbiology/microbiology-introduction.html at the filing date of the present disclosure). Additional parameters considered to select the proper treatment media for a target microorganism comprise osmotic pressure, pH, oxygen content, water content, carbon dioxide content as will be understood by a skilled person to support physiological processes of the target microorganism, enable or accelerate DNA replication and translation, maintain cellular uniformity and homogeneity in suspension, and promote interaction of the microorganism and antibiotic. For example in the experiments described herein with reference to N. gonorrhoeae the treatment media used was Fastidious Broth from Hardy Diagnostics (cat no. K31) which comprise pancreatic Digest of Casein , Yeast Extract, Dextrose, Peptic Digest of Animal Tissue, Sodium Chloride, Brain Heart Infusion, TRIS , Pancreatic Digest of Gelatin, Agarose, L-Cysteine HCl, Magnesium Sulfate, Ferrous Sulfate , Hematin, NAD, Pyridoxal and Tween® 80 (see https://catalog.hardydiagnostics.com/cp_prod/content/hugo/fbbroth.htm at the filing date of the present disclosure) Additional treatment media suitable to support physiological processes of N. gonorrhoeae, to enable or accelerate DNA replication and translation, maintain cellular uniformity and homogeneity in suspension, and promote interaction of the N. gonorrhoeae and the antibiotic are identifiable by a skilled person.
In methods herein described, incubation of a sample with an antibiotic can be performed at a temperature such that a physiological response to the antibiotic is generated in the target microorganism (often the microorganisms optimal growth temperature, for example 37° C. or at a temperature ± 0.5 degrees, ± 1 degree, ± 2 degrees, ± 3° C. therefrom). Also, adding the antibiotics can be performed throughout incubation or at set intervals during incubation to increase or decrease the physiological response of the microorganism to the antibiotic.
In particular in some embodiments, the antibiotic for treating the sample herein described can be provided at a concentration equal to or above the breakpoint MIC for the susceptible isolate or specimen to the antibiotic. In particular, the antibiotic for treating the sample herein described can be provided at a concentration lower than the breakpoint MIC for the resistant isolate or specimen to the antibiotic, for example 1.5 times (or 1.5X) lower, 2 times (or 2X) lower, 3 times (or 3X) lower, 4 times (or 4X) lower, 8 times (or 8X) lower, or 16 times (or 16X) lower than the breakpoint MIC for a resistant isolate. In some embodiments, the antibiotic for treating the sample herein described is provided at a concentration higher than the breakpoint MIC for the resistant isolate or specimen to the antibiotic, for example 1.5 times (or 1.5X) higher, 2 times (or 2X) higher, 3 times (or 3X) higher, or 4 times (or 4X) higher, 8 times higher (8X), 16 times higher (or 16X) than then breakpoint MIC. The breakpoint MIC of the antibiotic can be obtained from the Clinical & Laboratory Standards Institute (CLSI) guidelines, European Committee of Antimicrobial Susceptibility Testing (EUCAST) or other sources identifiable to a skilled person. In some embodiments, samples can be treated at several concentrations of the antibiotics for example, to measure the MIC of an organism before identifying the marker of antibiotic susceptibility as will be understood by a skilled person.
In some embodiments, antibiotic treatment or exposure can be performed for a set time period (e.g. up to 5 minutes, 10 minutes, 15 minutes or 20 minutes or any other time between 0-20 minutes or longer).
In some embodiments of the methods of the instant disclosure, the time period of contacting the sample with an antibiotic is shorter than the doubling time of the target organism. For example, the time of contacting could be less than 1x doubling time, less than 0.75X doubling time, less than 0.5 doubling time, less than 0.35 doubling time, less than 0.25 doubling time, less than 0.2 doubling time, less than 0.15 doubling time, less than 0.1 doubling time, less than 0.075 doubling time, less than 0.05 doubling time.
During the incubation, the sample can be collected at different time interval for further analysis (see Example 1). In addition to collecting samples during the incubation with antibiotics, samples can be collected for analysis before treatment or exposure. Such samples can be used as controls in analysis. Detection of response of the microorganism to the antibiotic can be performed one or more times at any time after antibiotic treatment or exposure. In some embodiments, rapid detection, for example detection completed within 10 minutes, 15 minutes, 20 minutes, 30 minutes, 40 minutes after exposure.
In some of embodiments of the method to identify an RNA marker of antibiotic susceptibility herein described, providing a treated sample and a control sample of the susceptible and/or resistant isolate or specimen can comprise enriching a first sample and a second sample of the susceptible and/or resistant isolate or specimen from the same source or host with the microorganism to obtain the susceptible and/or resistant control samples respectively, and contacting the second sample with an antibiotic to obtain a susceptible and/or resistant antibiotic treated sample respectively.
In embodiments of the method to identify an RNA marker of antibiotic susceptibility herein described,, providing a treated sample and a control sample of the susceptible and/or resistant isolate or specimen can comprise enriching a first sample and a second sample of the susceptible and/or resistant isolate or specimen from the same source or host with the microorganism, contacting the first sample with a treatment media following the enriching to obtain the susceptible and/or resistant control samples respectively and contacting the second sample of the susceptible and/or resistant isolate or specimen from the same source or host with the same treatment media and an antibiotic to obtain a susceptible and/or resistant antibiotic treated sample respectively.
In methods herein described, enriching a sample with the microorganisms can be performed between sample collection (and optionally elution from a collection tool such as a swab) and exposure. In particular enriching a sample with microorganisms and in particular bacteria (such as Neisseria gonorrhoeae) can be performed by capturing the microorganism using a solid support (e.g. a membrane, a filtration membrane, an affinity membrane, an affinity column) or a suspension of a solid reagent (e.g. microspheres, beads). Capture of a target microorganism can improve the assay and the response to antibiotic. Capture can be used to enrich/concentrate low-concentration samples. Capture followed by washing can be used to remove inhibitors or components that may interfere with the method described here. Capture followed by washing may be used to remove inhibitors of nucleic acid amplification or inhibitors of other quantitative detection assays. Enrichment can also be performed using lysis-filtration techniques to lyse host cells and dissolve protein and/or salt precipitates while maintaining bacterial cell integrity then capturing target bacteria on filters (e.g. mixed cellulose ester membranes, polypropylene and polysulfone membranes). Enrichment can also be performed by binding target bacteria to membranes of microspheres, optionally coated with an affinity reagent (e.g. an antibody, an aptamer) specific to the target bacteria’s cell envelope. When microspheres or beads are used for capture, they can be filtered, centrifuged, or collected using a magnet to enrich bacteria. AST in the format described here can then be performed directly on captured bacteria, or the bacteria can be released before performing the method.
Accordingly, in methods to identify an RNA marker of antibiotic susceptibility, quantitative detection of a marker gene is performed to provide for each of the detected genes a control gene expression value C in a control sample not treated with the antibiotic and a corresponding treated gene expression value T in a treated sample treated with the antibiotic in each of the susceptible and resistant isolate or specimen.
In particular, quantitative detection of the expression of one or more genes in method herein described to identify an RNA marker of antibiotic susceptibility is performed to provide
More particularly in methods to identify an RNA marker of antibiotic quantitative detection of the expression of one or more genes is performed to provide a susceptible (Cs:Ts) value for a candidate marker gene in the susceptible isolate or specimen, and a resistant (Cr:Tr) value for a candidate marker gene in the resistance isolate or specimen.
In particular providing a susceptible (Cs:Ts) value for the candidate marker gene in the susceptible isolate or specimen can be performed by
Additionally, providing a resistant (Cr:Tr) value for the candidate marker gene in the at least one resistant isolate or specimen can be performed by.
In methods to identify an RNA marker of antibiotic susceptibility, the RNA is identified by selecting the candidate marker gene when Cs:Ts is different from Cr:Tr to provide a selected marker gene differentially expressed in the treated susceptible sample and in the treated resistant sample.
In some embodiments, the Cs:Ts ratio and the Cr:Tr ratios are provided by gene expressionin TPM in the control sample divided by the gene expression in TPM in the treated sample.
In some embodiments, the Cs:Ts ratio and the Cr:Tr ratios can be provided by RPKM (reads per kilobase per million mapped reads). The use of RPKM and comparison to TPM is described for example in Wagner et al 2012 [3]. In some embodiments the Cs:Ts ratio and the Cr:Tr ratios are provided by FPKM (fragments per kilobase per million), the use of FPKM is described for example in Conesa, Ana, et al. 2016 [4]. These units normalize for sequencing depth and transcript length. In some embodiments RPM (reads per million mapped reads; RPM does not normalize for transcript length) or raw sequencing read counts can be used. Typically, to calculate RPM (reads per million), the total reads from a sample are divided by 1,000,000 to obtain the “per million scaling factor”. The read counts for each gene are then divided by the “per million scaling factor” to give RPM. Also typically to calculate RPKM (for single-end RNA-seq), the RPM values are divided by the gene length in kilobases. FPKM (for paired-end RNA-seq), is calculated the same way as RPKM, taking into account that with paired-end RNA-seq, two reads can correspond to a single fragment, or, if one read in the pair did not map, one read can correspond to a single fragment as will be understood by a skilled person.
In some embodiments, the Cs:Ts ratio and the Cr:Tr ratio can be plotted as -log2(C:T) against the -log2(expression in TPM) for all genes (
In some embodiments, to qualify for a marker gene differentially expressed in the treated sample of the susceptible isolate or specimen and in the treated sample of the resistant isolate or specimen, the difference between the (Cs:Ts) value and resistant (Cr:Tr) value is statistically significant.
In preferred embodiments, to qualify for a marker gene differentially expressed in the treated sample of the susceptible isolate or specimen and in the treated sample of the resistant isolate or specimen, the difference between the (Cs:Ts) value and resistant (Cr:Tr) value is statistically significant over the related biological variability (variability due to physiologic differences among a biological unit of a same microorganism such as between different strains of the microorganism and/or between different individual microorganism of a same strains) and/or technical variability (variability due to performance of different measurements of a same biological unit), more preferably over both biological and technical variability.
To measure technical variability a Cs:Ts or a Cr:Tr ratio is measured from a given sample multiple times with the method of choice (e.g. at least 3 or more times, or 5 or more times depending on the variability of the methods chosen for measurement as will be understood by a skilled person) and statistical analysis is performed on the resulting distribution (e.g. standard error of the mean, or standard distribution depending on the number of samples used as will be understood by a skilled person). Technical variability would depend on the measurement method chosen, as different methods have different accuracy, upper quantitative limits and more importantly lower quantitative limits as will be understood by a skilled person. For example RNA sequencing and reverse transcription digital PCR are methods with low technical variability.
To measure biological variability, a Cs:Ts or a Cr:Tr ratio is measured from multiple samples (in particular one can use three resistant and three susceptible samples, or preferably at least 5 resistant and 5 susceptible samples) with a method that has minimal technical variability such as RNA sequencing or others identifiable by a skilled person upon of reading of the present disclosure.
Statistical significance can be defined using a desired percent confidence. A common choice would be a 95% confidence interval or a 99% confidence interval (for relevant descriptions see Devore 2017 [5]. Additional description of statistical analysis used in single-molecule (digital) measurements to resolve differences between two distributions is provided in Kreutz et al 2011. [6]
In preferred embodiments, to qualify for a marker gene differentially expressed in the treated sample of the susceptible isolate or specimen and in the treated sample of the resistant isolate or specimen, the difference between the (Cs:Ts) value and resistant (Cr:Tr) value is adjusted to reduce the impact of biological variability and/or technical variability, more preferably of both biological and technical variability. Accordingly, in some embodiments, the method to identify a marker, further comprises normalizing the susceptible (Cs:Ts) value and the resistant (Cr:Tr) value prior to selecting a marker gene differentially expressed in the treated samples.
The wording “normalizing” and “normalization” as used herein refer to adjustments of a value related to a quantified amount to account for variations. In particular normalization of a value can be performed to account for a variation in a parameter associated with the detection of the quantified amount, such as variations in an amount of starting material, variations in an amount of sample, variations in bacterial concentration of sample, variations due to biological variability and variations due to technical variability.
Normalizing the susceptible (Cs:Ts) value and the resistant (Cr:Tr) value is performed with a reference measurement of RNA, DNA or cell number, the number of samples, the volume of sample used, the concentration of sample used, the effective amount of sample used and/or a related ratio in a control and in a treated sample. Effective amount of sample can be calculated by for example measuring the volumes and concentration of the sample used. Normalizing the susceptible (Cs:Ts) value can be performed by dividing the control susceptible gene expression by a reference measurement in the control susceptible sample and dividing the treated susceptible gene expression by the reference measurement in the treated susceptible sample. Normalizing the resistant (Cr:Tr) value can be performed by dividing the control resistant gene expression by a reference measurement in the control resistant sample and dividing the treated resistant gene expression by the reference measurement in the treated resistant sample. In addition, the normalization ratio for susceptible sample can be calculated by dividing the control susceptible reference measurement by the treated susceptible reference measurement. Normalizing the susceptible (Cs:Ts) value can be performed by dividing the (Cs:Ts) value by a susceptible normalization ratio. The normalization ratio for resistant sample can be calculated by dividing the control resistant reference measurement by the treated resistant reference measurement. Normalizing the resistant (Cr:Tr) value can be performed by dividing the (Cs:Ts) value by a resistant normalization ratio.
In some embodiments, normalization can be performed with reference measurement of cells such as cell number and/or a related ratio (
In some embodiments of these embodiments, the reference measurement is a measurement that reflects the number of target cells. For example, prior to the calculation of a CT ratio, the RNA expression in the untreated control sample and the RNA expression in the treated sample would be divided by a cell normalization ratio between number of target cells in the treated sample and number of target cells in the control sample which can be calculated from other measurements such as optical density, turbidity, increase in intensity of a colorimetric, fluorogenic, or luminescent metabolic indicator or a live/dead indicator, colony counting after plating, amount of pathogen-specific DNA and amount of pathogen-specific RNA as will be understood by a skilled person,.
In some embodiments, normalization can be performed with reference measurement of DNA and/or a related normalization ratio.
In some of these embodiments, the reference measurement is a measurement that reflects the amount of DNA of the target pathogen. For example, the amount of DNA of the target pathogen present could be measured using real time polymerase chain reaction, digital polymerase chain reaction, digital isothermal amplification, real time isothermal amplification, and/or other nucleic acid quantification techniques described herein. One or more DNA target sequences from the genome of the target pathogen can be used for estimating the amount of DNA of the target pathogen. Preferably, DNA sequences conserved within this organism are used.
For example, prior to the calculation of the CT ratio, the RNA expression in the untreated control sample would be divided by the amount of DNA of the target pathogen measured to be present in the control sample, and the RNA expression in the treated sample would be divided by the amount of DNA of the target pathogen measured to be present in the treated sample. In addition or in the alternative prior to the calculation of the CT ratio, a DNA normalization ratio can be provided by dividing the amount of DNA of the target pathogen measured to be present in the control sample and the amount of DNA of the target pathogen measured to be present in the treated sample. The RNA expression in the untreated control sample and the RNA expression in the treated sample can then be divided by the DNA normalization ratio to normalize the related value.
In some embodiments, normalization can be performed with reference to an RNA measurement and/or a related ratio. In particular, in those embodiments, the normalization can be performed using the expression value of a reference RNA, preferably selected among RNA expressed by the microorganism with low variability among strains of the microorganism.
In some of these embodiments, prior to the calculation of a CT ratio, the RNA expression value of a marker in the treated and/or in the untreated control sample would be divided by the expression value of the reference RNA in the treated and/or untreated control sample respectively. In addition or in the alternative, prior to the calculation of a CT ratio, the RNA expression in the untreated control sample and the RNA expression in the treated sample can be divided by a RNA normalization ratio provided by the expression value of the reference RNA in the untreated control sample divided by the expression of the reference RNA in the treated sample. The expression value the reference RNA can be detected by detecting the RNA and/or the corresponding cDNA in the microorganism.
In some embodiments, also the susceptible (Cs:Ts) value and the resistant (Cr:Tr) value can be normalized with respect to a reference parameter and/or a related ratio.
For example, normalization of the susceptible (Cs:Ts) value can be performed by dividing the susceptible (Cs:Ts) value of a target transcript in an untreated control sample by the expression of a control transcript such as 16S rRNA and/or 23S rRNA in the untreated control sample, and by dividing the susceptible (Cs:Ts) value of the target transcript in the treated sample by the expression of the same control transcript (e.g. 16S rRNA and/or 23S rRNA) in the treated sample. In addition or in the alternative normalizing the susceptible (Cs:Ts) value can be performed by dividing the susceptible (Cs:Ts) value by a susceptible control (Csc:Tsc) value of a control transcript (e.g. 16S rRNA or 23S rRNA) wherein the susceptible control (Csc:Tsc) value is calculated by dividing a gene expression value of the control transcript (e.g. 16S rRNA or 23S rRNA) in the control susceptible sample by a gene expression value of the control transcript (e.g. 16S rRNA or 23S rRNA) in the treated susceptible sample. In some embodiments, the control transcript can be ribosomal rRNA such as 16S rRNA or 23S rRNA.
Normalization of the resistant (Cr:Tr) value can be performed by dividing the resistant (Cr:Tr) value of a target transcript in an untreated control sample by the expression of 16S rRNA and/or 23S rRNA in the untreated control sample, and by dividing the resistant (Cr:Tr) value of the target transcript in the treated sample by the expression of 16S rRNA and/or 23S rRNA in the treated sample. In addition or in the alternative Normalizing the resistant (Cr:Tr) value can be performed by dividing the resistant (C:T) value by a resistant control (Crc:Trc) value of a control transcript (16S rRNA or 23S rRNA) wherein the resistant control (Crc:Trc) value is calculated by dividing a gene expression value of the control transcript (16S rRNA or 23S rRNA) in the control resistant sample by a gene expression value of the control transcript (16S rRNA or 23S rRNA) in the treated resistant sample.
The term “control transcript” refers to a transcript with a fold change in gene expression between control and treated samples (C:T ratio) that is substantially the same in the resistant and susceptible samples. In some embodiments, the CT ratio of the control transcript is within a 0.1-10 range, preferably within 0.5 to 2.0 range, more preferably within 0.75 and 1.25 range.
In preferred embodiments, a control transcript is selected so that the percentage change from control to treated gene expression is less than 25%, more preferably less than 10%. For example, in some embodiments control transcripts are selected so this C:T ratio is close to 1.0 in both resistant and susceptible samples. Preferably, control transcripts are selected so this C:T ratio has low technical and biological variability, for example described by standard deviation with value of less than 0.5, less than 0.4, less than 0.3, less than 0.2, less than 0.1. In some embodiments, high-abundance transcripts (for example, transcripts in the top 10% of most expressed transcripts) are used to achieve low technical variability. Preferably, control transcripts are selected so this C:T ratio has low biological variability. Transcripts with high expression and low biological variability which are not affected by the antibiotic treatment are good candidates for control transcripts.
Exemplary RNAs with a log2 fold change less than 0.32 (corresponding to <25% change) that can be used as control transcripts is reported in Table 1 below. The fold change is calculated as the average over the six (three susceptible and three resistant) isolates sequenced. The expression guidelines follow the same as in markers.
In Table 1, the GeneID and Gene Name columns are respectively the identification or reference and name or description of the control transcript gene from NCBI FA1090. Susc. Fold Change column represents the average Log2 C:T ratio for the three susceptible isolates sequenced and Susc. Control column represents the average TPM for the three susceptible isolates sequenced.
In some embodiments, the control transcript can be a ribosomal RNA, including 23S rRNA, 16S rRNA, 5S rRNA and other RNA component of ribosome.
In some embodiments, 16S rRNA or 23 rRNA are used as control transcripts for normalization. Exemplary control transcripts are listed in Table 2:
In some embodiments, control transcript according to the instant disclosure can have a sequence identity of at least 80%, or 90%, up to 100% of the markers listed in Table 1 and 2. In particular markers of the instant disclosure can be have sequence identity of 93%, 94%, 95%, 96%, 97%, 98%, or 99% of the sequences indicated in Tables 1 and 2.
The Gene IDs listed above as well as their sequences can be retrieved from NCBI database (https://www.ncbi.nlm.nih.gov/nuccore/1036099588) as will be understood by a person skilled in the art.
For example, in some embodiments, a specific region (such as a gene) of the DNA can be measured in in the control and treated sample and used as normalization DNA measurement, as will be understood by a skilled person. In some embodiments DNA normalization methods can be performed by PCR or dPCR. In some embodiments, a fluorescence dye that quantitatively stains DNA can be used as a normalization method. Additional methods to perform normalization DNA measurements are identifiable by a skilled person upon reading of the present disclosure.
In some embodiments, quantitatively detecting Cs Ts and Cr and Tr can be performed on a treated sample and corresponding control sample under several sets of conditions (e.g. varying treatment times, different experimental settings and/or using a plurality of isolates or specimen and/or a plurality of related control and/or treated sample) to provide a gene expression pattern for the candidate marker gene formed by the gene expression values detected in each treated and corresponding control samples under each set of conditions. In those embodiments, the differential expression of the candidate gene marker is detected with respect to the corresponding gene expression pattern according to approaches identifiable by a skilled person upon reading of the present disclosure.
In some embodiments, the candidate gene marker is a plurality of candidate gene markers. In those embodiments the quantitative detection of the related expression can be performed by detecting global gene expression, or patterns of gene expression, in the samples of the susceptible and resistant isolate or specimen.
The wording “global gene expression” as used herein indicates an expression level of a population of RNA molecules in cells and tissues. In particular, global gene expression can be performed to detect a transcriptome which is the set of all RNA molecules in one cell or a population of cells. Global gene expression is an approach typically used to investigate a transcriptional behavior of a biological system in connection with various biological phenomenon, as global genes expression can provide quantitative information about the population of RNA species in cells and tissues. The wording “Pattern of gene expression” refers to gene expression of multiple markers, or gene expression of the same marker over multiple conditions.
In embodiments herein described detecting global gene expression and pattern of gene expression can be performed using DNA microarrays, Nanostring, RNA-Seq, digital PCR, bulk qPCR, isothermal techniques such as LAMP or digital isothermal amplification techniques, and other nucleic acid quantification techniques described herein to measure the levels of RNA species in biological systems.
In those embodiments, providing a susceptible (Cs:Ts) value for the candidate marker gene in the susceptible isolate or specimen and providing a resistant (Cr:Tr) value for the candidate marker gene in the resistant isolate or specimen can be performed by
In those embodiments, the method further comprises selecting a set of maker genes differentially expressed in the treated sample of the susceptible isolate or specimen and in the treated sample of the resistant isolate or specimen by identifying the genes with the susceptible (Cs:Ts) value different from the corresponding resistant (Cs:Ts) value.
In some embodiments, to qualify for a marker gene differentially expressed in the treated sample of the susceptible isolate or specimen and in the treated sample of the resistant isolate or specimen, the difference between the susceptible (C:T) value and resistant (C:T) value is larger than a threshold.
In some embodiments, the method further comprises selecting the candidate gene markers having a Cs:Ts and/or Cr:Tr above or below a threshold of significance respectively. In some embodiments, an individual threshold is established for each of the plurality of markers in accordance with approaches of the present disclosure. In particular the threshold can be based on the knowledge of a distribution of a parameter indicative of the expression of one or more transcripts, to include transcripts differentially expressed in treated vs control sample across the distribution. For example to establish the threshold for each marker, C:T measurements are performed on a plurality of resistant and susceptible isolates, optionally including isolates with intermediate resistance. Threshold values can then be chosen to maximally separate C:T ratios for resistant and susceptible isolates. If a plurality of markers is used to determine antibiotic susceptibility of an organism, a number of algorithms can be used to interpret such information to make the determination. For example, weighted average or weighted sum of C:T ratios of the markers can be compared to the weighted average or weighted sum of the thresholds. Machine learning and pattern-recognition algorithms can be used. Measured fold-changes can be multiplied and compared to multiplied thresholds for multiple markers.
In detections when there is overlap between C:T ratios of resistant and susceptible isolates, various classification models can be used to map the C:T ratios between the susceptible and resistant groups. For example, receiver operating characteristic (ROC curve) can be analyzed and used to set optimal threshold. (see https://en.wikipedia.org/wiki/Receiver_operating_characteristic at the filing date of the present disclosure). ROC curve can be used to select optimal balance of analytical specificity and sensitivity of the test. In particular, the wording “analytical sensitivity” indicates the method’s ability to detect the target molecule at low levels in a sample. This is defined as the lowest concentration of RNA in a sample that can be detected >95% of the time. The wording “analytical specificity” indicates the method’s ability to detect the intended target in a complex sample. This refers to the ability of the method to differentiate between the intended target and similar targets from other bacterial species and the ability of the method to overcome inhibitors from the sample. When tested with clinical samples, ROC curve can be used to select optimal balance of clinical specificity and sensitivity of the test. Furthermore, prevalence data can be incorporated to provide a further refinement or predicted specificity and sensitivity of the test.
Additionally, in those embodiments detection where there is overlap between C:T ratios of resistant and susceptible isolates, the threshold can be also set in view of the severity of one type of error versus another, to reduce or minimize major errors even if this requires an increase of minor errors. For example, in case of overlaps between C:T ratios of resistant and susceptible isolates the threshold can be set to reduce up to minimize false susceptible (considered a more problematic error in terms of resulting treatment) increasing the expected percentage of false resistant. In some embodiments, the method can be performed with a plurality of susceptible and/or resistant isolates having genetic variability.
The wording “genetic variability” refers to either the presence of, or the generation of, genetic differences in a microorganism. The term “genetic variability” is defined as the formation of individuals differing in genotype, or the presence of genotypically different individuals. Therefore, Genetic variability refers to the difference in genotype between specific organisms while biological variability refers to the phenotypic differences between specific organisms, in this case RNA response to an antibiotic given for a specified amount of time.
Accordingly, a genetic variant indicates a genetic difference from a reference genome. The genetic variant can be used to describe an alteration (such as insertions, deletions, and /or replacement of nucleotides) that can be a result of mutations, recombination as will be understood by a person skilled in the art. Exemplary genetic variants comprise single base-pair substitution, also known as single nucleotide polymorphism (SNP), insertion or deletion of a single stretch of DNA sequence that can range for example from two to hundreds of base-pairs in length, and structural variation including copy number variation and chromosomal rearrangement events. The structural variation typically include deletion, insertion, inversion, duplication and copy number variation of the individual nucleic acids as will be understood by a person skilled in the art.
In particular in some embodiments, the susceptible and resistant isolates or specimen used herein for identifying a marker of antibiotic susceptibility comprise at least three different susceptible isolates or specimen and at least three different resistant isolates or specimen, preferably at least five different susceptible isolates or specimen and at least five different resistant isolates.
In preferred embodiments, the susceptible and resistant isolates or specimen used herein for identifying a marker of antibiotic susceptibility are selected to differ in genotypes and in biological responses to antibiotic administration to maximize genetic and biological variability of the isolates or specimen used for identifying a marker.
In some embodiments, selection of susceptible and resistant isolates or specimen used for identifying a marker of antibiotic susceptibility to increase or maximize genetic variability can be performed by sequencing the genomes of multiple isolates and selecting genetically different isolates or by obtaining isolates from different clusters from an isolate depository such as the CDC isolate bank or others entities identifiable by a skilled person. Hierarchical clustering based on genetic distance can be performed by first generating a SNP profile for each isolate against a reference genome (NCBI FA1090). Then a maximum-likelihood based inference method for phylogenetic tree generation can be performed to cluster isolates by genetic variability using tools such as RAxML or Garli and additional tools identifiable by a skilled person. Isolates can then be chosen from a plurality of clusters after hierarchical phylogenetic clustering.
In some embodiments, selection of susceptible and resistant isolates or specimen used for identifying a marker of antibiotic susceptibility to increase or maximize biological variability in RNA expression can be performed on a full transcriptome scale, (e.g. by detecting the transctiptome through RNA sequencing or on a gene specific scale (e.g. by detecting the specific gene expression through PCR based methods) following administration of an antibiotic and then calculating the related C:T ratio. Reference is made in this connection to the resistant isolates in
In preferred embodiments, selection of susceptible and resistant isolates or specimen used herein for identifying a marker of antibiotic susceptibility to select isolates having a high prevalence in a target region (area where the marker is intended to be used, such a city a county, a state, a country or larger regions formed by groups of countries or the entire world) based on surveys or other epidemiological data on the strains of a certain microorganism in the target region. In particular, one or more isolates can be selected that cluster together with strains accounting for at least 75% more preferably at least 85% even more preferably at least 90% or most preferably at least 95% of the strains infecting individuals in the target region.
In preferred embodiments selection of susceptible and resistant isolates or specimen used for identifying a marker of antibiotic susceptibility is performed by selecting at least 3 to 5 isolates maximizing genetic variability, biological variability while selecting the isolates with a prevalence of at least 75% more preferably at least 85% even more preferably at least 90% or most preferably at least 95% of the strains infecting individuals in a target region.
Following selection of a plurality of isolates preferably maximizing genetic and biological variability and prevalence in a target region, candidate markers can be tested with methods herein described.
In some embodiments, detecting expression of a candidate gene marker in a plurality of the selected susceptible isolates and in a plurality of the selected resistant isolates (at least three preferably at least 5) gene expression upon antibiotic exposure is performed by detecting expression a plurality of candidate gene markers (e.g. at least 2, at least 5, at least 10, at least 50 or, at least 100 or 300 or more depending on the genome size and the candidate markers selected and the detection technique selected). In those embodiments, detecting expression a plurality of candidate gene markers can be performed by detecting patterns of gene expression and/or global gene expression upon antibiotic exposure in a control sample and in a treated sample of each of the plurality of the selected susceptible isolates and in each of the plurality of the selected resistance isolates.
In some embodiments wherein quantitatively detecting expression of a candidate marker genes is performed by quantitatively detecting a plurality of candidate marker gene, and/or by quantitatively detecting expression of a candidate marker gene in a plurality of resistant and/or susceptible isolate, the method to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure can further comprises selecting the candidate gene marker with a transcript having a high fold change in expression upon antibiotic exposure.
A high fold change is defined as at least two folder change or higher. In particular, in some embodiments, a significant shift of fold change (larger than 4) in transcript levels can be observed within 5 min of antibiotic exposure. In some typically more infrequent instances genes can respond to antibiotic exposure with changes as large as 6-fold within 5 min.
The term “transcript” as used herein refers to any ribonucleic acid sequence provided in the microorganism without limitation to any specific type, function or length. Transcripts include messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA) of any length.
In some embodiments, the method to identify an RNA marker of antibiotic susceptibility further comprises validating the candidate markers by determining whether the candidate markers respond consistently across a large pool of isolates with genetic variability.
The validation of candidate markers can be performed by selecting the candidate markers with the highest abundance and fold change and using these selected candidate markers to determine the susceptibility of clinical isolates with known susceptibility/resistance. The clinical isolates can be obtained from the Centers for Disease Control (CDC) Antimicrobial Resistance Isolate Bank (see Example 10) and preferably represent a large degree of genetic variation or difference.
Validate markers are identified as markers showing consistency in their ability to correctly determine susceptibility or resistant of the clinical isolates.
In some embodiments, wherein quantitatively detecting expression of a candidate marker genes is performed by quantitatively detecting a plurality of candidate marker gene, and/or by quantitatively detecting expression of a candidate marker gene in a plurality of resistant and/or susceptible isolates or specimen, the method to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure further comprises selecting a candidate gene marker having transcripts representative of different biochemical pathways.
The term “biochemical pathways” refer to a sequence of chemical or biochemical reactions catalyzed by enzymes in which a product of one enzyme acts as the substrate for the next.
In some embodiments of the method to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure, the microorganism is a slow growing microorganism, a microorganism with a transcriptome which is not characterized and/or a microorganism that lacks a transcriptional SOS response to DNA damage.
The term “slow growing” as used herein indicates an organism with a doubling time longer than 30 minutes.
In some embodiments of the method to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure, the antibiotic is a fluoroquinolone. The term “fluoroquinolone” as used herein indicates a group of antibiotics containing a fluorine atom in their chemical structure. Fluoroquinolones are usually effective against both Gram-negative and Gram-positive bacteria. Exemplary fluoroquinolone include levofloxacin, ofloxacin, gatifloxacin, moxifloxacin, and norfloxacin.
In some of these embodiments, the antibiotic for treating the sample herein described, the concentration of the antibiotic can be provided at a concentration between 0.015 microgram/mL and 16.0 microgram/mL.
In some of these embodiments, the fluoroquinolones is ciprofloxacin. In some of these embodiments, the concentration of antibiotic used during exposure or treatment can be any concentration between the susceptible and resistant MIC breakpoints of the target organism. For example, for exposure or treatment of Ng with ciprofloxacin, the concentration of antibiotic used could any concentration ≥ 0.06 microgram/mL (the susceptible MIC breakpoint for ciprofloxacin for Neisseria gonorrhoeae) and ≤ 1.00 microgram/mL (the resistant MIC breakpoint for ciprofloxacin for Neisseria gonorrhoeae). In some embodiments, for example when faster responses are desired, higher than breakpoint concentrations can be used.
In some embodiments of the method to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure the antibiotic is an antibiotic inhibiting the enzymes topoisomerase II (DNA gyrase) and topoisomerase IV, thereby inhibiting cell division. Examples include Aminocoumarin antibiotics such as Novobiocin, Albamycin Coumermycin, Clorobiocin, and their derivatives, Simocyclinones and derivatives, moxifloxacin, ciprofloxacin, azithromycin, tetracycline, and ceftriaxone.
Additional examples of such antibiotics comprise novel bacterial topoisomerase inhibitors (NBTIs) and in particular Type I NBTIs such as gepotidacin and its analogues, GSK945237, AM-8722, 1,5-naphthyridine oxabicyclooctane linked NBTIs, and type II NBTIs, such as quinolone pyrimidone trione-1 (QPT-1) Zoliflodacin (AZD0914), isothiazolone analogue REDX04957 and its two enantiomer forms, REDX05967 and REDX05990,. Further examples comprise nalidixic acid, oxolinic acid, norfloxacin, iprofloxacin, levofloxacin, moxifloxacin, Gemifloxacin, EDX04139, REDX05604, REDX05931, kibdelomycin thiosemicarbazide; 4,5-dibromo-N-(thiazol-2-yl)-1H-pyrrole-2-carboxamide, cyclothialidine; pyrazolopyridone, 4-(4-(3,4-dichloro-5-methyl-1H-pyrrole-2carboxamido), piperidin-1-yl)-4-oxobutanoic acid, trans-4-(4,5-dibromo1H-pyrrole-2-carboxamide)cyclohexyl)glycine, pyrazolopyridones, cyclothialidines and their analogues, GR122222X, cinodine, albicidin, clerocidin, microcin B17, CcdB, an pentapeptide repeat proteins Qnr and MfpA, as well as additional antibiotics identifiable by a skilled person (see e.g. Badshah and Ullah 2018 [7] and Collin et al. 2018 [8]).
In the instant disclosure, an RNA marker of antibiotic susceptibility in a microorganism is described, as well as a corresponding marker gene and/or a corresponding cDNA are described, which can be obtained by the method to identify an RNA marker of antibiotic susceptibility
In some embodiments, the RNA markers comprise RNA markers encoding a ribosomal protein. The term “ribosomal protein” is the protein component of ribosome that in conjunction with rRNA make up the ribosomal subunits involved in the cellular process of translation. Prokaryotic bacteria and archaea have a 30S small subunit and a 50S large subunit. Accordingly, some of these mRNA markers disclosed herein comprise mRNA markers encoding 50S ribosomal proteins and mRNA markers encoding 30S ribosomal proteins.
Exemplary mRNA markers encoding ribosomal proteins include mRNA encoding 50S L4, 50S L13, 30S S12, 50S L27, 50S L19, 30S S19, 50S L2, 50S L22, 50S L32, 30S S1, 50S L21, 50S L33, 30S S16, 50S L28.
An additional list of exemplary mRNA markers of N. gonorrhoeae encoding ribosomal proteins is also shown in Table 5 of the instant application including rplD, rplM, rpsL, rpmA, rplS, rpsS, rplB, rplV, rpmF, rpsA, rplU, rpmG, rpsP, and rpmB.In some embodiments of the method herein described to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure, the microorganism is N. gonorrhoeae.
Neisseria gonorrhoeae is one type of proteobacteria that causes the sexually transmitted genitourinary infection gonorrhea as well as other forms of gonococcal disease including disseminated gonococcemia, septic arthritis, and gonococcal ophthalmia neonatorum. The term “Neisseria gonorrhea” includes all strains of N. gonorrhoeae identifiable by a person skilled in the art. Neisseria gonorrhea also includes genetic variants of different strains. One may determine whether the target organism is N. gonorrhoeae by a number of accepted methods, including sequencing of the 16S ribosomal RNA (rRNA) gene, as described in Chakravorty et al (2007) for N. gonorrhoeae. [9]
In some embodiments of the method herein described to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure, the microorganism is Neisseria meningitidis. Neisseria meningitidis, often referred to as meningococcus, is a Gram-negative bacterium that can cause meningitis and other forms of meningococcal disease such as meningococcemia, a life-threatening sepsis.
In some embodiments of the method herein described to identify a marker of antibiotic susceptibility in a microorganism of the instant disclosure, the RNA marker is not a direct target of the antibiotic. For example in some embodiments where the antibiotic is a quinolone and in particular ciprofloxacin, the selected markers are not identified target of gyrA, parC and/or recA identified as target for ciprofloxacin.
In some embodiments of the instant disclosure wherein the microorganism is N. gonorrhoeae, the markers can be selected from: a transcript of N. gonorrhoeae gene having locus tag NGO0340, a transcript of N. gonorrhoeae gene having locus tag NGO1837, a transcript of N. gonorrhoeae gene having locus tag NGO1843, a transcript of N. gonorrhoeae gene having locus tag having locus tag NGO2024, a transcript of N. gonorrhoeae gene having locus tag NGO1845, a transcript of N. gonorrhoeae gene having locus tag NGO1677, a transcript of N. gonorrhoeae gene having locus tag NGO1844, a transcript of N. gonorrhoeae gene having locus tag NGO0171, a transcript of N. gonorrhoeae gene having locus tag NGO1834, a transcript of N. gonorrhoeae gene having locus tag NGO0172, a transcript of N. gonorrhoeae gene having locus tag NGO1835, a transcript of N. gonorrhoeae gene having locus tag NGO1673, a transcript of N. gonorrhoeae gene having locus tag NGO1833, a transcript of N. gonorrhoeae gene having locus tag NGO2173, a transcript of N. gonorrhoeae gene having locus tag NGO0604, a transcript of N. gonorrhoeae gene having locus tag NGO0016, a transcript of N. gonorrhoeae gene having locus tag NGO1676, a transcript of N. gonorrhoeae gene having locus tag NGO1679, a transcript of N. gonorrhoeae gene having locus tag NGO1658, a transcript of N. gonorrhoeae gene having locus tag NGO1440, a transcript of N. gonorrhoeae gene having locus tag NGO0174, a transcript of N. gonorrhoeae gene having locus tag NGO0173, a transcript of N. gonorrhoeae gene having locus tag NGO0592, a transcript of N. gonorrhoeae gene having locus tag NGO1680, a transcript of N. gonorrhoeae gene having locus tag NGO0620, a transcript of N. gonorrhoeae gene having locus tag NGO1659, a transcript of N. gonorrhoeae gene having locus tag NGO1291, a transcript of N. gonorrhoeae gene having locus tag NGO0648, a transcript of N. gonorrhoeae gene having locus tag NGO0593, a transcript of N. gonorrhoeae gene having locus tag NGO1804, a transcript of N. gonorrhoeae gene having locus tag NGO0618, a transcript of N. gonorrhoeae gene having locus tag NGO0619, a transcript of N. gonorrhoeae gene having locus tag NGO1812, a transcript of N. gonorrhoeae gene having locus tag NGO1890, a transcript of N. gonorrhoeae gene having locus tag NGO2098, a transcript of N. gonorrhoeae gene having locus tag NGO2100, a transcript tRNA having GeneID A9Y61_RS02445 or NGO_t12, a transcript tRNA having GeneID A9Y61_RS04515 or NGO_t15, a transcript tRNA having GeneID A9Y61_RS04510 or NGO_t14, a transcript tRNA having GeneID A9Y61_RS09170 or NGO_t37, and a transcript tRNA having GeneID A9Y61_RS00075 or NGO_t01. The sequences of these transcripts can be retrieved from the public databases in compliance with the International Nucleotide Sequence Database Collaboration at the date of filing of the present disclosure as will be understood by a person skilled in the art. In particular, the sequences of these transcript can be identified by entering the locus tag or the GenID, alone or in combination with additional information provided in the present disclosure, in databases such as National Center for Biotechnology Information (NCBI) the European Bioinformatics Institute (EMBL-EBI) and DNA Data Bank of Japan (DDBJ) at the date of filing of the present disclosure.
In some embodiments the cDNAs of N. gonorrhoeae can have a sequence that can be shorter or longer than the sequences in the databases as will be understood by a skilled person. In particular, the transcript can include a re be up to 30 bp, 40 bp, 50 bp, 60 bp, 70 bp, 80 bp, 90 bp, 100 bp, 150 bp, 200 bp, 250 bp, 300 bp, 400 bp, 500 bp, 750 bp, 1000 bp, 1500 bp, 2000 bp, 2500 bp , or up to 3000 bp, shorter or longer of the sequence in the database as will be understood by a skilled person. Exemplary sequences for the above markers are provided in Table 3 below.
In some embodiments, markers according to the instant disclosure can have a sequence identity of at least 80%, or 90%, up to 100% of the markers listed in Table 3. In particular, markers of the instant disclosure can have sequence identity of 93%, 94%, 95%, 96%, 97%, 98%, or 99% of the sequences indicated in Table 3.
The term “sequence identity” refers to a quantitative measurement of the identity between sequences of a polypeptide or a polynucleotide and, in particular, indicates the amount of characters that match between two different sequences. Commonly used similarity searching programs, such as BLAST, PSI-BLAST [10] [11] [12] [13], SSEARCH [14] [15] FASTA[16] and the HMMER3 9 [17] can produce accurate statistical estimates, ensuring that protein sequences that share significant similarity also have similar structures.
The identity between sequences is typically measured by a process that comprises the steps of aligning the two polypeptide or polynucleotide sequences to form aligned sequences, then detecting the number of matched characters, i.e. characters identical between the two aligned sequences, and calculating the total number of matched characters divided by the total number of aligned characters in each polypeptide or polynucleotide sequence, including gaps. The identity result is expressed as a percentage of identity.
Biomarker’s features of the RNA markers of Table 3, such as resistant CT ratios and values, susceptible CT ratio values, abundance and threshold values, are further illustrated in
In the illustration of Table 4, for each marker, the range of possible threshold C:T ratios is calculated as a range between the mean Cr:Tr ratios for resistant and the mean Cs:Ts ratios for susceptible isolates, and narrowed down further to account for variability of the Cr:Tr ratios for resistant and the Cs:Ts ratios of susceptible isolates.
In some embodiments, after the marker is selected, when testing a sample with bacteria of unknown susceptibility to an antibiotic, the C:T ratio for this marker obtained from this sample is compared with Cs:Ts and Cr:Tr ratios. In some embodiments the C:T ratio thus obtained can be assigned as belonging to susceptible or resistant organism based on a threshold value.
For example, for a marker downregulated in the susceptible bacteria, the Cr:Tr values will be smaller than Cs:Ts values and a threshold value can be set above Cr:Tr value(s) and below Cs:Ts value(s). If a detected C:T is below threshold, we call it resistant and if CT is above threshold we call susceptible. In particular the threshold value can be set based on the knowledge of a distribution of a parameter indicative of the expression of one or more transcripts, to include transcripts differentially expressed in treated vs control sample across the distribution. In particular the threshold value for a C:T ratio can be set based on the knowledge of Cs:Ts and Cr:Tr distributions of a given transcript. In some embodiments, the threshold value is set at the average between the means of Cs:Ts and Cr:Tr distributions. In some embodiments, especially when the Cs:Ts and Cr:Tr distributions have unequal variance, the threshold value is set to between the means of Cs:Ts and Cr:Tr distributions at a value where the overlap between Cs:Ts and Cr:Tr distributions is zero or minimized.
In some embodiments, the threshold value can be selected among any one of the value within the following ranges 0.931-1.946, 0.964-1.698, 0.892-1.964., 0.944-1.792, 0.902-1.898, 1.003-2.360, 0.849-2.033, 0.933-1.977, 0.947-2.038., 0.923-1.686, 0.952-1.939, 0.936-2.026, 0.953-2.054, 0.981-2.379, 0.918-2.290, 0.980-2.708, 1.001-2.536, 0.944-2.721, 0.942-2.866, 1.026-2.933, 1.015-2.587, 0.981-2.818, 0.925-2.534, 1.021-2.618, 0.982-4.037, 0.983-4.091, 1.028-3.420, 1.015-3.876, 1.059-3.941, 1.284-3.219, 0.969-3.875, 0.991-3.290, 0.937-3.878, 0.934-4.327, 0.924-4.523, 0.851-3.326, 0.999-5.053, 0.845-5.897, 1.227-4.222 as will be understood by a skilled person upon reading of the present disclosure.
In some embodiments the RNA markers of N. gonorrhoeae herein described can have the following sequences indicated properties indicated in Table 5.
In preferred embodiments, the transcript can comprise at least one of a transcript of N. gonorrhoeae gene having locus tag NGO1812, a transcript of N. gonorrhoeae gene having locus tag NGO1680), a transcript of N. gonorrhoeae gene having locus tag NGO1291, a transcript of N. gonorrhoeae gene having locus tag NGO1673, a transcript of a transcript of N. gonorrhoeae gene having locus tag NGO0592 and a transcript of N. gonorrhoeae gene having locus tag NGO0340.
In more preferred embodiments, the transcript comprises or is at least one of a transcript N. gonorrhoeae gene having locus tag NGO1812 and possibly and putatively encoding major outer membrane protein (porB), and N. gonorrhoeae gene having locus tag NGO1680 and possibly and putatively encoding 50S ribosomal protein L28 (rpmB).
In some embodiments of the instant disclosure a method is described to detect in an N. gonorrhoeae bacteria, a N. gonorrhoeae transcript, which comprises
In some embodiments, the method further comprises detecting whether there is a downshift in the transcript expression value of the RNA marker of N. gonorrhoeae following and/or upon the contacting of the N. gonorrhoeae with the antibiotic by comparing the antibiotic treated transcript expression value with an untreated marker expression valuean untreated marker expression value indicating of the expression of the RNA marker of N. gonorrhoeae in N. gonorrhoeae in absence of antibiotic treatment.
In some embodiments, the reference expression value of the RNA marker of N. gonorrhoeae in absence of antibiotic treatment is a control transcript expression value obtained by quantitatively detecting the RNA of N. gonorrhoeae in a control sample not treated with the antibiotic. In some embodiments, the reference transcript expression value of the RNA marker of N. gonorrhoeae is a transcript expression value obtained by quantitatively detecting the RNA of N. gonorrhoeae in the same sample prior to treatment with the antibiotic. In some embodiments, the reference transcript expression value of the RNA marker of N. gonorrhoeae is a transcript expression value obtained by quantitatively detecting the RNA of N. gonorrhoeae at time zero of the RNA expression of the transcript.
Accordingly, in some embodiments, the method to detect in an N. gonorrhoeae bacteria an N. gonorrhoeae transcripts can be performed by
In some embodiments an untreated marker expression value indicative of the expression of the RNA marker of N. gonorrhoeae in N. gonorrhoeae in absence of antibiotic treatment is a control transcript expression value obtained by
In some embodiments, the RNA markers of N. gonorrhoeae herein described can be used in a method to perform an antibiotic susceptibility test for N. gonorrhoeae. The method comprises detecting susceptibility to an antibiotic of an N. gonorrhoeae, by quantitatively detecting in a sample comprising the N. gonorrhoeae a transcript expression value of an RNA marker of N. gonorrhoeae selected from the RNA markers of an N. gonorrhoeae herein described following and/or upon contacting the sample with the antibiotic.
In the method to perform an antibiotic susceptibility test for N. gonorrhoeae the quantitatively detecting is performed to obtain an antibiotic treated transcript expression value for the RNA marker of N. gonorrhoeae suitable to detect susceptibility to the antibiotic of the N. gonorrhoeae in the sample.
In some embodiments, the method to perform an antibiotic susceptibility test for N. gonorrhoeae further comprises detecting whether there is a downshift of the transcript expression value with respect to the expression of the transcript in an untreated sample of the same specimen by comparing the detected antibiotic transcript expression value with an untreated marker expression value indicative of the transcript expression in the sample in absence of antibiotic treatment.
In some embodiments, the RNA markers of N. gonorrhoeae herein described can be used in a method to detect an RNA marker of susceptibility to an antibiotic in N. gonorrhoeae in a sample comprising the N. gonorrhoeae. The method comprises contacting the sample with the antibiotic to obtain an antibiotic treated sample and quantitatively detecting in the antibiotic treated sample one or more of the RNA markers of N. gonorrhoeae herein described.
In some embodiments, the method to detect an RNA marker of susceptibility to an antibiotic in N. gonorrhoeae further comprises detecting a downshift of an RNA marker selected from any one of the transcripts of N. gonorrhoeae genes herein described with respect to an untreated marker expression value indicative of the expression of the RNA marker of N. gonorrhoeae in N. gonorrhoeae in absence of antibiotic treatment.
The RNA markers of N. gonorrhoeae herein described can be used in a method to diagnose susceptibility to an antibiotic of a N. gonorrhoeae infection in an individual. The method comprises contacting a sample from the individual with the antibiotic; and quantitatively detecting expression by the N. gonorrhoeae in the sample of a marker of antibiotic susceptibility in N. gonorrhoeae selected from any one of the transcripts of N. gonorrhoeae genes herein described. In the method, the quantitatively detecting is performed following contacting the sample with the antibiotic. The method further comprises detecting whether there is a downshift of the detected transcript presence in the antibiotic sample with respect to an untreated marker expression value indicative of the expression of the marker of antibiotic susceptibility in N. gonorrhoeae to diagnose the antibiotic susceptibility of the N. gonorrhoeae infection in the individual.
The RNA markers of N. gonorrhoeae herein described can be used in a method to detect antibiotic susceptibility of an N. gonorrhoeae bacterium and treat N. gonorrhoeae in an individual. The method comprises contacting a sample from the individual with an antibiotic, and quantitatively detecting in the sample expression by the N. gonorrhoeae bacteria of a marker of antibiotic susceptibility selected from any one of the transcripts of N. gonorrhoeae genes herein described. In the method, the quantitatively detecting is performed following and/or upon contacting the sample with the antibiotic.
The method further comprises diagnosing antibiotic susceptibility of N. gonorrhoeae infection in the individual when a downshift in expression of at least one of the detected markers in the sample is detected in comparison with an untreated marker expression value indicative of the expression of the at least one of the detected markers in the sample from the individual in absence of antibiotic treatment.
The method also comprises administering an effective amount of the antibiotic to the diagnosed individual.
The term “individual” as used herein in the context of treatment includes a single biological organism, including but not limited to, animals and in particular higher animals and in particular vertebrates such as mammals and in particular human beings
In embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, contacting the N. gonorrhea can be performed by adding antibiotics to the microorganism and incubating the sample under certain condition
In particular in some embodiments, the antibiotic for treating the sample herein described can be provided in a sample comprising N. gonorrhoeae at a concentration equal to or the breakpoint MIC for the N. gonorrhoeae, to the antibiotic. In particular, the antibiotic for treating the sample herein described can be provided at a concentration lower than the breakpoint MIC for the N. gonorrhoeae strain in the sample, for example 1.5 times (or 1.5X) lower, 2 times (or 2X) lower, 3 times (or 3X) lower, 4 times (or 4X) lower, 8 times (or 8X) lower, or 16 times (or 16X) lower than the breakpoint MIC for a resistant isolate.. In some embodiments, the antibiotic for treating the sample herein described can be provided at a concentration higher than the breakpoint MIC for the N. gonorrhoeae strain in the sample, for example 1.5 times (or 1.5X) higher, 2 times (or 2X) higher, 3 times (or 3X) higher, or 4 times (or 4X) higher, or 8 times higher (8X) or 16 times higher (or 16X) than the breakpoint MIC for a resistant isolate. The breakpoint MIC of the antibiotic for the N. gonorrhoeae strain in the sample, can be obtained from the Clinical & Laboratory Standards Institute (CLSI) guidelines, European Committee of Antimicrobial Susceptibility Testing (EUCAST) or other sources identifiable to a skilled person.
In some embodiments, samples may be treated at several concentrations of the antibiotic to measure MIC of an organism and/or to determine if a sample contains bacteria with intermediate susceptibility, susceptible bacteria, or resistant bacteria to the antibiotic of interest. In order to determine the MIC using the described method, samples can be treated at multiple concentrations of antibiotic. These concentrations would include multiple dilutions below the susceptible MIC breakpoint, dilutions between the susceptible and resistant MIC breakpoints (including intermediate breakpoint concentrations), as well as a dilution above the resistant MIC breakpoint (see Example 13) To determine, degree of susceptibility, the sample would be exposed to three concentrations of antibiotic: a concentration equal to the susceptible MIC breakpoint, a concentration equal to the concentration of the resistant MIC breakpoint, and a concentration equal to the average of the maximum and minimum of the intermediate MIC breakpoint range. Susceptibility would then be determined , for example, by measuring the slope obtained by fitting a curve or line to the three points on the C:T ratio vs treatment concentration plot, and/or by comparing the relative difference in C:T ratio between the low and intermediate concentration of antibiotic and the difference in CT ratio between the intermediate and high concentration, and/or by comparing the magnitude of the value relative to a pre-defined threshold, or a combination of these analyses (see Example 14).
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the time period of contacting the sample with an antibiotic can be up to 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes up to 60 up to 90 up to 120 or higher, inclusive of any value therebetween or fraction thereof.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the time period of contacting the sample with an antibiotic is shorter than the doubling time of the N. gonorrhoeae strain in the sample. For example, for conditions with N. gonorrhoeae doubling time of 45 minutes, 1 hour, 1.5 hours, or 2 hours, antibiotic exposure contacting time could be less than the time indicated in Table 6 below
In methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, incubation of a sample with an antibiotic can be performed at a temperature such that a physiological response to the antibiotic is generated in N. gonorrhoeae. The contacting is performed typically in an incubation temperature at 37° C., in an incubation temperature within the range of 36-38° °C, in an incubation temperature within the range of 35-39° °C.
In methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the contacting can be performed by adding antibiotics to the microorganism and incubating the sample under certain condition preferably following and/or upon contacting the sample with a treatment media designed to support physiological processes of N. gonorrhoeae, enable or accelerate DNA replication and translation, maintain cellular uniformity and homogeneity in suspension, and promote interaction of the N. gonorrhoeae and antibiotic herein described.
In methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, quantitatively detecting an antibiotic treated transcript expression value in the treated sample can be performed following and/or upon contacting the sample with an antibiotic for a time period up to 20 minutes.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, quantitatively detecting transcript expression value can be performed by RNA-seq, qPCR, digital PCR, isothermal techniques such as LAMP, digital isothermal amplification methods, or using probes specifically targeting any one of the differentially expressed transcripts herein described. Additional techniques include microarrays and nanostringtm as will be understood by a person skilled in the art.
In some embodiments, detecting specific gene expression can be performed at the transcription level by performing RNA sequencing (RNA-seq) and calculating RNA expression values based on the sequence data.
In some embodiments, the RNA expression values can be calculated as transcripts per million (TPM) as will be understood by a person skilled in the art. To calculate TPM, read counts are first divided by the length of each gene in kilobases, which gives reads per kilobase (RPK). RPKs for all genes are added and the sum is divided by 1,000,000. This gives the “per million” scaling factor. Finally, the RPK value for each genes is divided by the “per million” scaling factor to give TPM. [3]
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, quantitatively detecting a treated gene expression pattern of the transcript can be performed using probes specifically targeting any one of the differentially expressed transcripts herein described.
The term “probe” as described herein indicates a molecule or computer support tool capable of specifically detect a target molecule such as one of the markers herein described. The wording “specific” “specifically” or “specificity” as used herein with reference to the binding of a first molecule to second molecule refers to the recognition, contact and formation of a stable complex between the first molecule and the second molecule, together with substantially less to no recognition, contact and formation of a stable complex between each of the first molecule and the second molecule with other molecules that may be present. Exemplary specific bindings are antibody-antigen interaction, cellular receptor-ligand interactions, polynucleotide hybridization, enzyme substrate interactions and additional interactions identifiable by a skilled person. The wording “specific” “specifically” or “specificity” as used herein with reference to a computer supported tool, such as a software indicates a tool capable of identifying a target sequence (such as the one of a marker herein described) among a group of sequences e.g. within a database following alignment of the target sequence with the sequences of the database. Exemplary software configured to specifically detect target sequences comprise Primer-3, PerlPrimer and PrimerBlast.
In methods of the instant disclosure using any one of the N. gonorrhoeae transcripts herein described, treatment of the N. gonorrhoeae bacteria with a probe and/or antibiotic or with any other reagents functional to perform the related step is performed on samples.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the probe specific for the transcript is selected from a primer having a sequence specific for the marker, or an antibody specific for the marker.
In particular, probes usable in methods herein described can include primers for nucleic acid amplification reactions (such as PCR, LAMP, HAD, RPA, NASBA, RCA, SDA, NEAR, and additional reactions identifiable by a skilled person), including digital single molecule versions of these reactions and including real-time versions of these reactions, molecular beacons that include dyes, quenchers, or combinations of dyes and quenchers.
Nucleic acid probes preferably have sequences that complementarily bind to the DNA and/or RNA sequences of the markers described herein, and can be used to target RNA molecules directly, or DNA molecules that result, for example, from reverse transcription of the target RNA molecules (such molecules may be referred to as cDNA). In embodiments of the present disclosure when two polynucleotide strands, sequences or segments are noted to be binding to each other through complementarily binding or complementarily bind to each other, this indicate that a sufficient number of bases pairs forms between the two strands, sequences or segments to form a thermodynamically stable double-stranded duplex, although the duplex can contain mismatches, bulges and/or wobble base pairs as will be understood by a skilled person.
The term “thermodynamic stability” as used herein indicates a lowest energy state of a chemical system. Thermodynamic stability can be used in connection with description of two chemical entities (e.g. two molecules or portions thereof) to compare the relative energies of the chemical entities. For example, when a chemical entity is a polynucleotide, thermodynamic stability can be used in absolute terms to indicate a conformation that is at a lowest energy state, or in relative terms to describe conformations of the polynucleotide or portions thereof to identify the prevailing conformation as a result of the prevailing conformation being in a lower energy state. Thermodynamic stability can be detected using methods and techniques identifiable by a skilled person. For example, for polynucleotides thermodynamic stability can be determined based on measurement of melting temperature Tm, among other methods, wherein a higher Tm can be associated with a more thermodynamically stable chemical entity as will be understood by a skilled person. Contributors to thermodynamic stability can include, but are not limited to, chemical compositions, base compositions, neighboring chemical compositions, and geometry of the chemical entity.
In embodiments herein described, primer and/or other nucleic acid probes can be designed to complementarily bind the target marker herein described with methods described in [13].
Probes usable in methods herein described include probes used in guiding CRISPR-based detection of nucleic acids. e.g. CRISPR-associated protein-9 nuclease; CRISPR-associated nucleases. An example of a CRISPR-based method is described in references [18] [19] [20]. Such probes can be synthesized using naturally occurring nucleotides including deoxyInosine, or include unnatural nucleotides such as locked nucleic acid (LNA). Probes can comprise dyes, quenchers, or combinations of dyes and quenchers attached to the probe. Hybridization probes, including those used in fluorescent in situ hybridization and hybridization chain reaction. Probes can also comprise electrochemically active redox molecules attached to the probe. Probes can be provided in a dry state. Probes can also include probes bound to beads, such beads may be fluorescently labeled. Probes can also include probes bound to nanoparticles, such nanoparticles may include gold nanoparticles. Probes can include probes disposed in arrays of wells with volumes less than 50 microliters, and/or wells within plastic substrates. Exemplary probes suitable to be used in methods using any one of the N. gonorrhoeae markers herein described comprise probes provided with the commercially available technology such as the technology of any of the companies GenProbe, Nanosphere, Luminex, Biofire and additional companies identifiable by a skilled person.
In some embodiments, quantitative detection of the marker/transcript is performed by one or more methods including Northern blotting, Nuclease Protection Assays (NPAs) in situ hybridization, reverse transcription polymerase chain reaction, and qPCR.
In some embodiments, of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, quantitatively detecting of a marker can be performed by detecting a detectable portion thereof. Exemplary detectable portions comprise to regions of at least 14 base pair, at least 16 base pair, at least 18 base pair, at least 19 base pair, at least 20 base pair, at least 21 base pair, at least 22 base pair, at least 23 base pair, at least 24 base pair, at least 30 base pair, at least 40 base pair, at least 50 base pair, at least 60 base pair, at least 70 base pair, at least 80 base pair, at least 90 base pair, or at least 100 base pair, The specific portion can be identified by a skilled person based on the length of the transcript to be detected as will be understood by a skilled person.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, quantitatively detecting individual tRNA markers can be performed with quantification methods comparable with method used for detection of other RNA markers above. The secondary structure and multitude of base modifications prevalent on tRNA often makes reverse transcription inefficient and thus a variety of modified reverse transcription steps can be used. These can involve more flexible reverse transcriptases (RTs) like group II intron reverse transcriptase[21] [22].
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the methods comprise detecting whether there is a shift in the transcript expression of the markers, in a sample treated with an antibiotic with respect to a sample not treated with antibiotic.
In particular, in embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the methods comprise detecting whether there is a downshift of a detected presence in N. gonorrhoeae of a N. gonorrhoeae marker following treatment with antibiotic with respect to an untreated marker expression value indicative of the expression in N. gonorrhoeae of the one or more N. gonorrhoeae marker in absence of antibiotic treatment.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers, the reference expression value is a control transcript expression value of the RNA marker of N. gonorrhoeae detected in a control sample of the specimen, and detecting whether there is a downshift can be performed by comparing the antibiotic treated transcript expression value with respect to the control transcript expression value of the RNA marker of N. gonorrhoeae in a control sample of the specimen.
Therefore, in some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers, the reference expression value indicative of the expression of the RNA marker of N. gonorrhoeae in absence of antibiotic treatment is a control transcript expression value obtained by quantitatively detecting the RNA of N. gonorrhoeae marker in a control sample not treated with the antibiotic.
A shift in the expression of the markers can be determined by calculating differential gene expression levels (C:T ratios) as described above in connection with methods to identify a marker of antibiotic susceptibility.
In particular in methods of the instant disclosure using any one of the N. gonorrhoeae markers, the methods can comprise for a specimen comprising N. gonorrhoeae (e.g. from an individual).
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the marker comprises more than one marker.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the N. gonorrhoeae bacteria is selected from any strain of N. gonorrhoeae including its genetic variants.
In some embodiments, the C:T ratio can be provided by RPKM (reads per kilobase per million mapped reads). The use of RPKM and comparison to TPM is described for example in Wagner et al 2012 [3]. In some embodiments the C:T ratio is provided by FPKM (fragments per kilobase per million), the use of FPKM is described for example in Conesa et al. 2016 [4]. These units normalize for sequencing depth and transcript length. In some embodiments RPM (reads per million mapped reads; RPM does not normalize for transcript length) or raw sequencing read counts can be used. The related methods are identifiable by a skilled person upon reading of the present disclosure.
In methods of the instant disclosure using any one of the N. gonorrhoeae markers, the differential expression of the N. gonorrhoeae marker can be expressed in accordance with a fold change approach in view of the C:T ratios identifiable by a skilled person upon reading of the present disclosure. In particular in the fold-change approach, a gene is considered to be differentially expressed if the ratio of the marker expression level between the antibiotic treated and untreated conditions exceeds a certain threshold, for example, 1.5-fold, twofold or threefold, or 4-fold or 5-fold change.
Accordingly, in some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers at least 1.2-fold magnitude of fold change is considered as a shift. In some embodiments, contacting the sample with an antibiotic results the markers a 1.5 fold change or 2-fold or 4-fold change up to 6-fold change within the first 5 minutes of contact. Increasing the antibiotic exposure time can further shift the fold-change value.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers, the downshift of the transcript presence is at least 2-fold, 4-fold or is 6-fold or higher.
In preferred embodiments, the (C:T) value of an N. gonorrhoeae marker can be adjusted to reduce the impact of biological variability and/or technical variability in the C:T detection, more preferably of both biological and technical variability.
Accordingly, in some embodiments, any one of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described can further comprise normalizing the antibiotic treated transcript expression value, the control transcript expression value and/or the related ratio, before detecting whether there is a downshift in antibiotic treated sample with respect to the untreated sample.
In particular, in some embodiments, at least one of the antibiotic treated transcript expression value and the control transcript expression value are normalized before providing a C:T ratio. In some embodiments, the C:T ratio of the antibiotic treated transcript expression value and the control transcript expression value is normalized using reference measurements.
The normalization can be performed by dividing the antibiotic treated transcript expression value, the control transcript expression value and/or the related ratio, by a reference measurement of RNA, DNA, cell number, number of samples, effective amount of sample used and/or a related ratio in a control and in a treated sample, according to approaches indicated for methods to identify markers of antibiotic susceptibility of the disclosure.
In particular, in some of these embodiments, the quantitatively detecting can be performed at a plurality of times following and/or upon contacting the sample, and/or under several conditions following and/or upon contacting the sample. For example in some of these embodiments, the antibiotic can be added at different concentrations. Also, in some of those embodiments adding the antibiotic can be performed in the treated N. gonorrhoeae sample throughout incubation or at set intervals during incubation to increase or decrease the physiological response of the N. gonorrhoeae to the antibiotic. Also in some of those embodiments, the quantitatively detecting can be performed at various times including time zero (for example, immediately prior or immediately after antibiotic treatment) of the transcript expression in the sample. In some of those embodiments, the quantitatively detecting can be performed at various temperatures and/or in multiple samples. In these embodiments, normalization can be performed by dividing the detected expression value and/or the related ratio between treated and control samples by the volume of samples or other reference measurements, such as the expression value of a reference RNA, level of DNA, cell numbers, as well as other reference parameters.
The control transcripts and related method of identification described in the method to identify markers of the present disclosure apply to the instant methods as will be understood by a skilled person.
Preferably, control transcripts are selected so this C:T ratio has low technical and biological variability, for example described by standard deviation with value of less than 0.5, less than 0.4, less than 0.3, less than 0.2, less than 0.1. In some embodiments, high-abundance transcripts (for example, transcripts in the top 10% of most expressed transcripts) are used to achieve low technical variability. Preferably, control transcripts are selected so this C:T ratio has low biological variability. Transcripts with high expression not affected by the antibiotic treatment are good candidates for control transcripts with low biological variability. For mRNA high expression level is obtained with more than 10 copies per cell or equivalent parameter in view of the method of measurement (for example RNAseq can have preferred expression levels for detection are TPM > 100 for any transcript and “high expression” being TPM > 100,000 (greater than 3000 copies/cell).
In some embodiments, a control transcript can be selected by providing a pool of isolates with known susceptibility; for each of these isolates, measuring a CT ratio of each transcript; and selecting as the control transcripts the transcripts with a CT ratio that is substantially the same in the pool of isolates between the susceptible isolates and the resistant isolates. The pool of isolates can be obtained from CDC Antimicrobial Resistance Isolate Bank. and/or from clinical collections of isolates.
Alternatively, the control transcript can be selected by measuring a CT ratio of each transcript in a strain subject to the antibiotic susceptibility test, i.e. with unknown susceptibility, and selecting as the control transcript the transcript with a CT ratio close to one, i.e. transcripts with expression not affected by the antibiotic treatment. Preferably, the control transcripts have a high expression level (e.g. with a TPM >10,000). Exemplary control transcripts comprise the transcript listed in Table 1.
In some embodiments, the control transcript can be a ribosomal RNA, including 23S rRNA, 16S rRNA, 5S rRNA and other RNA component of ribosome.
In some embodiments, 16S rRNA or 23 rRNA are used as reference RNA for normalization (see e.g. Table 2 of the instant disclosure).
In some embodiments of the fold-change approach, a gene is considered to be differentially expressed if the ratio of the normalized marker expression level between the antibiotic treated and untreated conditions exceeds a certain threshold, for example, 1.5 fold, twofold or threefold, or 4-fold or 5-fold change, wherein normalization can be performed with any of the methods herein described.
In some embodiments of any one of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, detecting whether there is a downshift can be performed by comparing the antibiotic treated transcript expression value of the RNA marker of N. gonorrhoeae with the expression value in the treated sample of a biomarker of the expression of the RNA marker of N. gonorrhoeae to detect the downshift. In particular, a biomarker of the expression can be any molecule and in particular a transcript, whose expression, under control conditions, has been previously shown to be correlated with the expression of the RNA marker of N. gonorrhoeae, preferably for a plurality of strains. In some embodiments, a downshift of expression of the RNA marker is detected when the ratio of expression of this marker to the expression of the biomarker of the expression in the treated sample is statistically significantly different than the range of ratios expected based on the analysis correlation of expression of these two markers under control conditions.
In some embodiments any one of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the N. gonorrhoeae marker is a plurality of N. gonorrhoeae markers. In those embodiments the quantitative detection of the related expression can be performed by detecting global gene expression, or patterns of gene expression, in the tested samples for the plurality of the N. gonorrhoeae markers, as will be understood by a skilled person.
In methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the sample can be provided from urine, swab, genital swab, throat swab, urethral swab, cervical swab, vaginal swab, oropharyngeal swab, throat swab, and rectal swabs. For urine sample, the preferable amount is between 1 ul and 10 ml. If the sample is provided as in swabs, the swab can be placed in an elution buffer to elute bacterial target cells from the swab. Samples can also include bacterial culture samples, for example, those grown on solid media such as chocolate agar, or grown in liquid culture such as Hardy Fastidious Broth (HFB).
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the sample can be pretreated to enrich RNA or a N. gonorrhoeae by removal of human RNA or RNA of other microorganisms. The removal of human RNA can be performed via hybridization to beads or columns with probes specific for human RNA. The removal of human RNA can also be performed via selective lysis of human cells and degradation of released human RNA. The sample may also be pretreated to enrich tRNA via size selection.
In general, in embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, enriching a sample can be performed with methods and approaches described for the methods to identify an antibiotic susceptibility marker of the disclosure.
In some embodiments of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the sample can be stored until sample preparation and analysis, for example at room temperature, 4° C., -20° C., or -80° C., as appropriate, identifiable by those skilled in the art. When biological specimens are stored, ideally they remain equivalent to freshly-collected specimens for the purposes of analysis. In some embodiments, of the methods of the instant disclosure using any one of the N. gonorrhoeae markers herein described, the sample can be pre-incubated with growth media for a short period of time to increase the number of viable bacterial cells or to increase the level of RNA expression in such cells. The temperature and media for such pre-incubation can be performed as described herein for incubation. The duration of such pre-incubation can range, for example, from 5 minutes to 20 minutes to 1 hour to 2 hours.
In some embodiments of the instant disclosure wherein the microorganism is N. meningitidis, markers are expected to be selected from a transcript of a N. meningitidis gene based on the fact that Neisseria meningitidis also lacks the SOS response [23] ([24] (and [25] or a corresponding cDNA.
In particular, markers are expected to be selected from a transcript of a N. meningitidis gene comprise the ones listed in Table 7
In some embodiments, markers according to the instant disclosure can have a sequence identity of at least 80%, or 90%, up to 100% of the markers listed in Table 7. In particular markers of the instant disclosure can have sequence identity of 93%, 94%, 95%, 96%, 97%, 98%, or 99% of the sequences indicated in Table 7.
The RNA marker of N. meningitidis and/or corresponding cDNA can be used to detect a transcript of N. meningitidis., perform an antibiotic susceptibility test for N. meningitidis, detect an RNA marker of susceptibility to an antibiotic in N. meningitidis, diagnose susceptibility to an antibiotic of a N. meningitidis infection in an individual, and/or detect antibiotic susceptibility of an N. meningitidis bacterium and treat N. meningitidis in an individual, with methods and systems comprising the features indicated in any one of the third to the eighth aspect of the summary section and related portion of the detailed description of the instant disclosure in connection with N. gonorrhoeae transcripts and/or corresponding cDNA and their use in methods and systems related to the N. gonorrhoeae microorganism.
Methods of the present disclosure using any one of the N. gonorrhoeae transcripts and/or N. meningitidis herein described, can be performed with a corresponding system comprising at least one probe specific for a transcript herein described and/or or probe specific for cDNA a transcript herein described, and reagents for detecting the at least one probe. The at least one probe and reagents are included in the system for simultaneous combined or sequential use in any one of the methods of the present disclosure using any one of the N. gonorrhoeae transcripts herein described.
In particular, in the instant disclosure a system is described for performing at least one of the methods herein described to detect an N. gonorrhoeae transcript, to detect antibiotic susceptibility of N. gonorrhoeae bacteria, to perform an antibiotic susceptibility test for an N gonorrhoeae, and/or to diagnose and/or treat N. gonorrhoeae in an individual. The system comprises at least one probe specific for a transcript selected from any one of the transcripts of N. gonorrhoeae genes herein described, and/or a probe specific for cDNA a transcript herein described, and reagents for detecting the at least one probe.
In some embodiments of the system herein described the system comprises at least one probe specific for a transcript, and/or probe specific for a corresponding cDNA of said transcript, selected from at least one of a transcript of N. gonorrhoeae gene having locus tag NGO1812 and encoding major outer membrane protein (porB), a transcript of N. gonorrhoeae gene having locus tag NGO1680 and encoding 50S ribosomal protein L28 (rpmB), a transcript of N. gonorrhoeae gene having locus tag NGO1291 and encoding transcriptional regulator (yebC)a transcript of N. gonorrhoeae gene having locus tag NGO1673 and encoding type IV pilus assembly protein(pilB), a transcript of a transcript of N. gonorrhoeae gene having locus tag NGO0592 and encoding trigger factor (tig) and a transcript of N. gonorrhoeae gene having locus tag NGO0340 and encoding cysteine synthase A (cysK).
In some embodiments of the system herein described the system comprises at least one probe specific for a transcript and/or a corresponding cDNA, which comprises or is at least one of a transcript N. gonorrhoeae gene having locus tag NGO1812 and annotated as encoding major outer membrane protein (porB), and/or a corresponding cDNA and N. gonorrhoeae gene having locus tag NGO1680 and annotated as encoding 50S ribosomal protein L28 (rpmB) and/or a corresponding cDNA.
In some embodiments of the system herein described the system comprises primers configured to specifically hybridizes with the transcript and/or a corresponding cDNA. In some of these embodiments the system comprises a probe specific for a transcript of N. gonorrhoeae gene having locus tag NGO1812, the probe comprises a pair of primers having sequence GCTACGATTCTCCCGAATTTGCC (SEQ ID NO: 160) (CCGCCKACCAAACGGTGAAC (SEQ ID NO: 161), a probe specific for a transcript of N. gonorrhoeae gene having locus tag NGO1680 the probe comprises a pair of primers having sequence TTGCCCAACTTGCAATCACG (SEQ ID NO: 162) and AGCACGCAAATCAGCCAATAC (SEQ ID NO: 163). a probe specific for a transcript of N. gonorrhoeae gene having locus tag NGO1291 the probe comprises a pair of primers having sequence GCTTTGGAAAAAGCAGCCG (SEQ ID NO: 164) and GGTTTTGTTGTCGGTCAGGC (SEQ ID NO: 165), a probe specific for a transcript of N. gonorrhoeae gene having locus tag NGO1673, the probe comprises a pair of primers having sequence GACTTTTGCCGCTGCTTTG (SEQ ID NO: 166) and GCGCATTATTCGTGTGCAG (SEQ ID NO: 167), a probe specific for a transcript of N. gonorrhoeae gene having locus tag NGO0592 the probe comprises a pair of primers having sequence AAAGCCTTGGGTATTGCGG (SEQ ID NO: 168) and TGACCAAAGCAACCGGAAC (SEQ ID NO: 169). and/or a probe specific for a transcript of N. gonorrhoeae gene having locus tag NGO0340 the probe comprises a pair of primers having sequence GAGGCTTCCCCCGTATTGAG (SEQ ID NO: 170) and TTCAAAAGCCGCTTCGTTCG (SEQ ID NO: 171).
In some embodiments, the systems of the disclosure to be used in connection with methods herein described using any one of the N. gonorrhoeae transcripts herein described, the system further comprises a probe specific for a reference RNA and/or a corresponding cDNA. In some of these embodiments, the reference RNA is N. gonorrhoeae 16S rRNA the and the probe comprises a pair of primers having sequence the probe comprises a pair of primers having sequence ACTGCGTTCTGAACTGGGTG (SEQ ID NO: 172) and GGCGGTCAATTTCACGCG (SEQ ID NO: 173). In some of these embodiments, the control transcript is N. gonorrhoeae 23S rRNA and the probe comprises a pair of primers having sequence the probe comprises a pair of primers having sequence GCATCTAAGCGCGAAACTCG (SEQ ID NO: 174), and CCCCACCTATCAACGTCCTG (SEQ ID NO: 175).
In some embodiments, the systems of the disclosure to be used in connection with methods herein described using any one of the N. gonorrhoeae transcripts herein described or cDNA of any one of the N. gonorrhoeae transcripts herein described the system can further comprise an antibiotic formulated for administration to a sample in combination with the at least one probe.
In some embodiments, the systems of the disclosure to be used in connection with methods herein described using any one of the N. gonorrhoeae transcripts herein described and/or cDNA of any one of the N. gonorrhoeae transcripts herein described, the system further comprises an antibiotic formulated for administration to an individual in an effective amount to treat an N. gonorrhoeae infection in the individual.
In some embodiments, the systems of the disclosure to be used in connection with methods herein described using any one of the N. gonorrhoeae transcripts herein described, the reagents comprise RNA extraction kit and amplification mix. The system may also include one or more antibiotics and/or exposure media with or without the antibiotics. The system can also include reagents required for preparing the sample, such as one or more of buffers e.g. lysis, stabilization, binding, elution buffers for sample preparation, enzyme for removal of DNA e.g. DNase I, and solid phase extraction material for sample preparation., reagents required for quantitative detection such as intercalating dye, reverse-transcription enzyme, polymerase enzyme, nuclease enzyme (e.g. restriction enzymes; CRISPR-associated protein-9 nuclease; CRISPR-associated nucleases as described herein) and reaction buffer. Sample preparation materials and reagents may include reagents for preparation of RNA and DNA from samples, including commercially available reagents for example from Zymo Research, Qiagen or other sample preparations identifiable by a skilled person. The system can also include means for performing RNA quantification such as one or more of: container to define reaction volume, droplet generator for digital quantification, chip for digital detection, chip or device for multiplexed nucleic acid quantification or semiquantification, and optionally equipment for temperature control and detection, including optical detection, fluorescent detection, electrochemical detection.
In some embodiments, the system can comprise a device combining all aspects required for an antibiotic susceptibility test.
The systems herein disclosed can be provided in the form of kits of parts. In kit of parts for performing any one of the methods herein described, the probes and the reagents for the related detection can be included in the kit alone or in the presence of one or more antibiotic as well as any one of the RNA markers, corresponding cDNA and/or probes for one or more reference RNAs and/or corresponding cDNAs. In kit of parts for the treatment of an individual the probes and reagents for the related detection can be comprised together with the antibiotic formulated for administration to the individual as well as additional components identifiable by a skilled person.
In a kit of parts, the probes and the reagents for the related detection, antibiotics, RNA markers, and/or reference RNA and additional reagents identifiable by a skilled person are comprised in the kit independently possibly included in a composition together with suitable vehicle carrier or auxiliary agents. For example, one or more probes can be included in one or more compositions together with reagents for detection also in one or more suitable compositions.
Additional components can include labeled polynucleotides, labeled antibodies, labels, microfluidic chip, reference standards, and additional components identifiable by a skilled person upon reading of the present disclosure.
The terms “label” and “labeled molecule” as used herein refer to a molecule capable of detection, including but not limited to radioactive isotopes, fluorophores, chemiluminescent dyes, chromophores, enzymes, enzymes substrates, enzyme cofactors, enzyme inhibitors, dyes, metal ions, nanoparticles, metal sols, ligands (such as biotin, avidin, streptavidin or haptens) and the like. The term “fluorophore” refers to a substance or a portion thereof which is capable of exhibiting fluorescence in a detectable image. As a consequence, the wording “labeling signal” as used herein indicates the signal emitted from the label that allows detection of the label, including but not limited to radioactivity, fluorescence, chemoluminescence, production of a compound in outcome of an enzymatic reaction and the like.
In embodiments herein described, the components of the kit can be provided, with suitable instructions and other necessary reagents, in order to perform the methods here disclosed. The kit will normally contain the compositions in separate containers. Instructions, for example written or audio instructions, on paper or electronic support such as tapes, CD-ROMs, flash drives, or by indication of a Uniform Resource Locator (URL), which contains a pdf copy of the instructions for carrying out the assay, will usually be included in the kit. The kit can also contain, depending on the particular method used, other packaged reagents and materials (i.e. wash buffers and the like).
Further details concerning the identification of the suitable carrier agent or auxiliary agent of the compositions, and generally manufacturing and packaging of the kit, can be identified by the person skilled in the art upon reading of the present disclosure.
The methods and system herein disclosed are further illustrated in the following examples, which are provided by way of illustration and are not intended to be limiting.
Antibiotic susceptible and resistant clinical isolates were obtained from the University of California, Los Angeles, Clinical Microbiology Laboratory.
Isolates were plated from glycerol stocks onto Chocolate Agar plates and grown in static incubation overnight (37° C., 5% CO2). Cells were re-suspended in Hardy Fastidious Broth (HFB) and incubated for 45 min (37° C., 5% CO2) with shaking (800 rpm) to an OD600 between 1 and 5. Cultures were diluted (5X) into HFB. Each isolate culture was split into “treated” and “control” tubes.
Ciprofloxacin was added to the “treated” tubes (final concentration of 0.5 µg/mL) and water was added to the “control” tubes; cultures were incubated (static; 37° C., 5% CO2) for 15 min. During incubation, samples were collected for RNA sequencing at 5, 10, and 15 min (300 µL aliquot of sample was mixed into 600 µL of Qiagen RNA Protect Reagent (Qiagen, Hilden, Germany) for immediate RNA stabilization).
In addition, a sample was collected for RNA sequencing immediately before ciprofloxacin was added.
To quantify CFU, the sample at t = 15 min was serially diluted (10x), plated on a Chocolate Agar plate, and incubated overnight (37° C., 5% CO2).
Antibiotic susceptible and resistant clinical isolates were obtained from the N. gonorrhoeae panel of the CDC Antimicrobial Resistance Isolate Bank. Isolates were plated from glycerol stocks onto Chocolate Agar plates and grown in static incubation overnight (37° C., 5% CO2). Cells were re-suspended in pre-warmed HFB + 5 mM sodium bicarbonate and incubated for 30 min (37° C., 5% CO2) with shaking (800 rpm) to an OD600 between 1 and 5. Cultures were diluted (100X) into HFB + 5 mM sodium bicarbonate.
Each isolate culture was split into treated (0.5 µg/mL final concentration of ciprofloxacin) and control (water instead of antibiotic) samples. Samples were incubated at 37° C. for 10 min on a static hot plate. A 90 µLaliquot of each sample was placed into 180 µLof Qiagen RNA Protect Reagent for immediate RNA stabilization. A 5 µLaliquot of each sample was plated onto a Chocolate Agar plate and incubated overnight (37° C., 5% CO2) as a control for the exposure experiments. If the expected growth phenotypes (i.e. resistant = growth; susceptible = no growth) were not observed for any single sample in the plating control, the exposure experiment was repeated for the set of samples.
From the 50 total isolates available from the N. gonorrhoeae panel of the CDC Antimicrobial Resistance Isolate Bank, 49 were used in this study. One isolate was excluded from this study because it is suspected that it had been contaminated; N. gonorrhoeae porB primer amplification was not detected using qPCR.
RNA was extracted using the Enzymatic Lysis of Bacteria protocol of the Qiagen RNeasy Mini Kit and processed according to the manufacturer’s protocol. DNA digestion was performed during extraction using the Qiagen RNase-Free DNase Set.
The quality of extracted RNA was measured using an Agilent 2200 TapeStation (Agilent, Santa Clara, CA, USA). Extracted RNA samples were prepared for sequencing using the NEBNext Ultra RNA Library Prep Kit for Illumina (New England Biolabs, Ipswitch, MA, USA) and the NEBNExt Multiplex Oligos for Illumina. Libraries were sequenced at 50 single base pair reads and a sequencing depth of 10 million reads on an Illumina HiSeq 2500 System (Illumina, San Diego, CA, USA) at the Millard and Muriel Jacobs Genetics and Genomics Laboratory, California Institute of Technology. Raw reads from the sequenced libraries were subjected to quality control to filter out low-quality reads and trim the adaptor sequences using Trimmomatic (version 0.35).
The reads were aligned to the FA 1090 strain of N. gonorrhoeae (NCBI Reference Sequence: NC_002946.2) using Bowtie2 (version 2.2.5) and quantified using the Subread package (version 1.5.0-p1). A pseudocount of 1 was added to the gene quantification; gene expression was defined in transcripts per million (TPM).
For each gene, the C:T ratio was defined as the gene expression (TPM) in the control sample divided by the gene expression (in TPM) in the treated sample. The -log2(C:T) was plotted against the -log2(expression in TPM) for all genes. To identify genes that were differentially expressed between control and treated samples, a threshold of significance was defined.
The threshold of significance was calculated from the C:T ratios at t = 0 for the biological replicates that were sequenced (three susceptible and three resistant isolates). For each of the six gene expression datasets (one for each isolate), a negative exponential curve was fit to the outer edge of each plot and then the curves were averaged from all six datasets.
Finally, a 90% confidence interval was added to the average curve by assuming a Gaussian fit for the error distribution, which is the threshold of significance. Genes with a -log2(C:T) value above or below the upper and lower thresholds were identified as differentially expressed. Genes that were differentially expressed consistently (either always above or always below the thresholds) among the three susceptible isolates and were not differentially expressed among the three resistant isolates were defined as candidate markers.
To measure copies per cell using RNA sequencing data, 2uL of (1/1000 dilution) ERCC RNA Spike-In Mix (Thermo Fisher Scientific, Waltham, MA, USA) was added to the lysis buffer in the RNeasy Mini Kit to each individual sample. The number of copies of each ERCC transcript in the sample was calculated, by accounting for dilution and multiplying by Avogadro’s number (manufacturer’s concentrations were reported in attomoles/µL). The relationship between log2(ERCC copies added) against log2(gene expression in TPM) was plotted and a linear regression in the region of linearity was performed. The linear regression was used to convert TPM values to total RNA copies in each sample. Finally, using the CFU measured for each sample from plating (described in the “Antibiotic exposure for RNA sequencing” section), the total RNA copies were converted to copies per cell.
Primers were designed for candidate markers using Primer-BLAST[13] and primer alignments were verified using SnapGene. Expression of candidate markers was quantified using the Bio-Rad QX200 droplet dPCR system (Bio-Rad Laboratories, Hercules, CA, USA). The concentration of the components in the dPCR mix used in this study were as follows: 1× EvaGreen Droplet Generation Mix (Bio-Rad), 150U/mL WarmStart RTx Reverse Transcriptase, 800U/mL RiboGaurd RNase Inhibitor, 500 nM forward primer, and 500 nM reverse primer. The RNA extraction comprised 5% of the final volume in the dPCR mix.
For each isolate, candidate marker expression was quantified in the control and treated samples and the fold-change difference (C:T ratio) was calculated. To account for potential differences between the control and treated samples that could arise from experimental variability and extraction efficiency, ribosomal RNA (rRNA) was used as an internal control.
From the sequencing data, it was found that rRNA was not affected by antibiotic exposure in the time frame of this study and showed very low variability. The 16S rRNA in the control was therefore also quantified, samples were treated by dPCR and an rRNA C:T ratio was calculated. The C:T ratio of each marker was normalized with the rRNA C:T ratio. All dPCR C:T ratios reported in the example section of the disclosure are the normalized C:T ratios.
RNA-seq was used to study the transcriptome response of susceptible and resistant isolates of N. gonorrhoeae after 5, 10, and 15 min of ciprofloxacin exposure (
Genes that demonstrated significant fold-change differences between the susceptible and resistant isolates were identified as differentially expressed. To account for biological variability, three pairs of susceptible and resistant isolates were used in this study to identify markers. Candidate markers were selected from the pool of differentially expressed genes and were validated using droplet dPCR (see Examples 4 and 6).
Global shifts were observed in RNA expression in susceptible isolates in as early as 5 min after antibiotic exposure (
To identify genes that were differentially expressed between control and treated samples, a threshold of significance was defined (
The curves were then averaged from all six datasets and added a 90% confidence interval to the average curve by assuming a Gaussian fit for the error distribution, which was defined as the threshold of significance. Genes with a -log2(C:T ratio) value above or below the upper and lower thresholds were identified as differentially expressed. Downregulated genes (fold changes below the significance threshold) appeared as early as 5 min after antibiotic exposure (blue dots,
A key aim of this study was to identify RNA markers that would yield a measurable response after only a short antibiotic exposure (less or equal to 15 min) to ensure this approach can fit within the required timescale for a rapid AST. It is possible that longer exposure times could provide additional insight into the biological response of N. gonorrhoeae to ciprofloxacin, but this was not the focus of this study. Furthermore, the short exposure times potentially introduce a bias toward transcripts present at low abundance when evaluating fold change.
For transcripts present at high abundance to display the same fold change, a substantially higher number of mRNA molecules must be transcribed, which would require longer timescales. As an example, a 4-fold change from 1 to 4 transcripts requires 3 additional mRNA to be produced, whereas a 4-fold change from 20 to 80 requires 60 mRNA to be transcribed. This bias also holds true in downregulation, where mRNA continues to be transcribed in the control samples, whereas transcript levels drop in treated samples due to degradation of RNA, and/or a reduction in rate of transcription.
RNA expression in response to antibiotics can be heterogeneous among different isolates of the same species[26]; thus, it is important to select candidate markers from differentially expressed genes that respond consistently across isolates of N. gonorrhoeae.
To identify these markers, three different pairs of susceptible isolates (minimum inhibitory concentrations (MICs) <= 0.015microg/mL) and resistant isolates (MICs 2.0 microgram/mL, 4.0 microgram/mL, and 16.0 microgram/mL) were exposed to ciprofloxacin for 15 min and extracted RNA for sequencing (see workflow in
The nature of the transcriptional response of N. gonorrhoeae to antibiotic exposure was a global downregulation in transcript levels. In particular, 181, 41, and 410 differentially expressed genes were found in susceptible isolates 1, 2, and 3, respectively (
Among the differentially expressed genes, 38 genes responded consistently across the three pairs of susceptible and resistant isolates (i.e. responses overlapped in all three susceptible isolates and were not responsive in all three resistant isolates) (see
Among the 38 candidate markers, 15 were ribosomal proteins (including one of the top markers, rpmB), which play a prominent role in assembly and function of the ribosomes and are essential for cell growth. Mutations in ribosomal proteins have been reported to confer resistance to different classes of antibiotics[27].
These 38 genes spanned a variety of biochemical functions in the cell. Six candidate transcript markers were selected for further analysis based on the following criteria: (1) high fold change; (2) high expression levels (>75 transcripts per million, TPM); and (3) representative of different biochemical pathways.
The selected candidate markers were: porB (membrane protein), rpmB (ribosomal protein), tig (molecular chaperone), yebC (transcriptional regulator), pilB (pilus assembly ATPase), and cysK (cysteine synthase). Among the candidate marks, all exhibited downregulation in response to ciprofloxacin.
The candidate marker with the highest abundance and largest fold change upon antibiotic exposure was porB, which is a membrane channel forming protein and the site of antibiotic influx into the cell[28]. porB is a porin protein responsible for uptake of small nutrients and the site of antibiotic influx into the cell. The expression of porins is highly regulated in response to environmental stimuli[29]. Reducing permeability to decrease intracellular antibiotic concentration is a known mechanism for bacteria to confer antibiotic resistance[27]. The downregulation of porB observed in this study can be attributed to a halt in growth processes caused by ciprofloxacin damage and possibly an attempt to reduce influx of antibiotic.
A high level of gene expression was one of the criteria for selection of candidate markers from the sequencing data. High expression of candidate markers is not only important for sensitivity and limits of detection, as has been previously demonstrated in AST methods based on quantification of DNA replication[30], but is particularly important for clinical samples with low numbers of pathogen cells. One of the advantages of RNA compared with DNA as a nucleic acid marker is its natural abundance in the cell. Because the gene expression values obtained from sequencing are relative values, the next step was to quantify the absolute copies per cell for the candidate markers. In the quantification approach, clinical isolate samples were plated after 15 min of ciprofloxacin exposure to obtain cell numbers in colony forming units (CFU/mL). Primers were designed for the candidate markers (see Example 6 and
Additionally, the RNA sequencing data was used to obtain transcriptome-wide estimates of transcript copies per cell. In the sequencing approach, external RNA control consortium (ERCC) spike-ins was added to the lysis buffer step of the extraction protocol in order to capture any loss of RNA throughout the extraction steps. By linear regression the relationship between ERCC copies added to the samples and ERCC quantified by sequencing was captured. Using the linear regression, gene expression values were converted from RNA sequencing (in TPM) to approximate copy numbers per cell (see Example 5). The transcript copies per cell estimated for the candidate markers using the sequencing approach were within the same order of magnitude as the absolute copies per cell measured by digital PCR (
It is noted that gyrA and parC, which are known genotypic markers for resistance to ciprofloxacin, were not found to be differentially expressed. recA, which is one of the prominent genes in the SOS response, was also not found to have an increased transcript level because N. gonorrhoeae does not have a true SOS system[31, 32]. Whereas recA is a specific cellular response to overcome DNA damage, the global downregulation that was observed suggests a general shift away from growth and cell proliferation
To determine how the relative changes observed through RNA-seq compare to direct gene expression measurements by dPCR, dPCR assays were designed for candidate markers, which involved measuring the expression of the candidate marker in both control and treated samples, and calculating the C:T ratio.
In this assay, the 16S rRNA was also measured and used to normalize the C:T ratio of the candidate markers. In the three susceptible isolates that were sequenced we found that rRNA consistently showed the smallest fold change (< 1.06) in response to ciprofloxacin compared with all other genes in N. gonorrhoeae. Therefore, to account for experimental variations in the antibiotic exposure and RNA extraction steps between control and treated samples, the 16S rRNA was used as an intracellular control for normalizing the C:T ratios (see Example 6). It was found that the C:T ratios measured by the dPCR assay agreed with the C:T ratios obtained through sequencing (
To determine whether candidate markers respond consistently across a large pool of isolates with genetic variability, the two candidate markers with the highest abundance and fold change (porB and rpmB) were chosen to determine the susceptibility of 49 clinical isolates, with a wide range of MIC values (see
The MIC values were representative of the population-wide distribution values reported by the European Committee on Antimicrobial Susceptibility Testing[34]. Each clinical isolate was exposed to ciprofloxacin for 10 min and the fold change was measured in expression of the two candidate markers between the control and treated sample using dPCR (
In particular, both markers were consistent in their ability to correctly determine susceptibility or resistance of all 49 clinical isolates. porB demonstrated C:T ratios between 2.5 to 7 and rpmB demonstrated C:T ratios between 2 and 6 after 10 min of antibiotic exposure in the nine susceptible clinical isolates. The large fold changes highlight the significance of using RNA response as an AST marker compared with quantification of DNA replication. The previous work using dPCR quantification of DNA replication demonstrated C:T ratios between 1.2 and 2.4 for 15 min of antibiotic exposure in susceptible E. coli[30], which has a doubling time approximately 3 times shorter than N. gonorrhoeae.
An alignment search of porB was performed against other prokaryotes and porB was found to be specific to the Neisseria genus. AST markers should be specific to the pathogen of interest because additional bacterial species are likely to be present in clinical samples.
Antibiotic susceptible and resistant clinical isolates plated from glycerol stocks onto Chocolate Agar plates and grown in static incubation overnight (37° C., 5% CO2). Cells were re-suspended in Hardy Fastidious Broth (HFB) and incubated for 45 min (37° C., 5% CO2) with shaking (800 rpm) to an OD600 between 1 and 5. Cultures were diluted (5X) into HFB. Each isolate culture was split into “treated” and “control” tubes. Ciprofloxacin was added to the “treated” tubes (final concentration of 0.5 µg/mL) and water was added to the “control” tubes; cultures were incubated (static; 37° C., 5% CO2) for 15 min. Samples for DNA quantification were extracted at 0 and 15 min using the Epicentre QuickExtract DNA Extraction Solution according to the manufacturer’s protocol. 10 uL of sample is placed into 90 uL extraction buffer and incubated at 65° C. for 6 min, followed by 98° C. for 4 min. t0 samples were left at 65° C. during treatment. DNA quantification was performed by digital droplet PCR. The concentrations of the components in the dPCR mix was as follows: 1× QX200 ddPCR EvaGreen Supermix (Bio-Rad), 500 nM forward primer GTTTCAGCGGCAGCATTCA (SEQ ID NO: 176), and 500 nM reverse primer CCGGAACTGGTTTCATCTGATT (SEQ ID NO: 177). Primers that target the 16S or 23S gene of N. gonorrhoeae can be used for dPCR amplification.
In order to understand the variability of the porB gene among the 50 CDC clinical isolates, a clustal omega alignment was performed to determine the smallest percent identity between the FA 1090 sequence and the 50 CDC sequences. The percent identity was shown to be 94.94%. porB is known to be more variable than rpmB and therefore it is likely that percent identity will be higher for rpmB. The porB sequences for the 50 clinical isolates from the CDC bank are listed in ANNEX D (SEQ ID NO: 178-227).
An antibiotic MIC in a targeted organism can be determined in connection with any one of the methods herein described.
For example, when determining ciprofloxacin MIC in Neisseria gonorrhoeae, in some embodiments samples would be treated at 0.015, 0.030, 0.060, 0.125, 0.25, 0.5, 1.0, 2.0, and 4.0 microgram/mL. The C:T ratios measured at each concentration would then be used to determine the sample’s MIC. MIC could be determined, for example, by fitting a curve to the C:T ratios obtained at each concentration of antibiotic plotted vs the concentration of antibiotic used for treatment, and determining the concentration at which the maximum slope of the curve occurs.
This concentration of antibiotic would then correlate to a particular MIC, determined from performing this method on samples with known MICs. MIC could also be determined by the value at which the fit curve crosses a pre-defined threshold or from the lowest antibiotic concentration that gives a CT response larger than a pre-defined threshold. MIC could also be determined from matching the shape of single curve (or multiple curves) fit to the CT ratios to a pre-constructed library of curves determined by performing the method on isolates with known MICs. An exemplary curve fitting antibiotic concentrations and C:T ratios is reported in
In order to determine if a sample contains bacteria with intermediate susceptibility, susceptible bacteria, or resistant bacteria to the antibiotic of interest, the sample can be exposed to three concentrations of antibiotic: a concentration equal to the susceptible MIC breakpoint, a concentration equal to the concentration of the resistant MIC breakpoint, and a concentration equal to the average of the maximum and minimum of the intermediate MIC breakpoint range. Susceptibility would then be determined , for example, by measuring the slope obtained by fitting a curve or line to the three points on the C:T ratio vs treatment concentration plot, and/or by comparing the relative difference in C:T ratio between the low and intermediate concentration of antibiotic and the difference in CT ratio between the intermediate and high concentration, and/or by comparing the magnitude of the value relative to a pre-defined threshold, or a combination of these analyses. For example, for exposure or treatment of Neisseria gonorrhoeae to ciprofloxacin the sample would be exposed to 0.06, 0.25, and 1.0 ug/mL ciprofloxacin.
This example follows the procedure used in [30] Schoepp, N.G., et al., Rapid pathogen-specific phenotypic antibiotic susceptibility testing using digital LAMP quantification in clinical samples. Sci Transl Med, 2017. 9(410)). Urine containing or suspected of containing Neisseria gonorrhoeae is obtained from a patient. Urine is then mixed and incubated in exposure media with and without antibiotics. After incubation in exposure media, nucleic acids are extracted and the target Neisseria gonorrhoeae RNA marker is quantified using digital loop-mediated isothermal amplification (dLAMP). The marker concentration in the control sample (sample without antibiotics) is divided by the concentration in the treated sample (sample with antibiotics) to generate a control-treated ratio (C:T ratio).
If the C:T ratio is above the threshold, Neisseria gonorrhoeae bacteria from this patient sample are called susceptible. If the C:T ratio is below the threshold, Neisseria gonorrhoeae bacteria from this patient sample are called resistant. If the C:T ratio is at the threshold, or within 0.05 of the threshold, Neisseria gonorrhoeae bacteria from this patient sample are called indeterminate.
The following description is taken from Clinical Laboratory Standards Institute (CISI) as an example for performing an Antibiotic Susceptibility Test (AST) as well as breakpoint MIC values for various bacteria according to the CLSI standard. More detailed description and updates for CLSI documents can be further found at https://clsi.org/standards-development/documentcorrection-notices/ as will be understood by a person skilled in the art.
General Comments include:
The examples set forth above are provided to give those of ordinary skill in the art a complete disclosure and description of how to make and use the embodiments of the materials, compositions, systems and methods of the disclosure, and are not intended to limit the scope of what the inventors regard as their disclosure. Those skilled in the art will recognize how to adapt the features of the exemplified methods and systems based on the RNA markers identified herein for detection of susceptibility and resistance against various antibiotics in antimicrobial-resistance bacteria according to various embodiments and scope of the claims.
All patents and publications mentioned in the specification are indicative of the levels of skill of those skilled in the art to which the disclosure pertains.
The entire disclosure of each document cited (including webpages patents, patent applications, journal articles, abstracts, laboratory manuals, books, or other disclosures) in the Background, Summary, Detailed Description, and Examples is hereby incorporated herein by reference. All references cited in this disclosure, including references cited in any one of the Appendices, are incorporated by reference to the same extent as if each reference had been incorporated by reference in its entirety individually. However, if any inconsistency arises between a cited reference and the present disclosure, the present disclosure takes precedence. Furthermore, the computer readable form of the sequence listing of the ASCII text file named “P2255-US-2021-08-23-Sq-List-ST25”, created on Aug. 23, 2021, and having a file size (not “size on disk”) of 425 kilobytes measured on Windows Server 2016 Standard ver. 1607, is incorporated herein by reference in its entirety.
The terms and expressions which have been employed herein are used as terms of description and not of limitation, and there is no intention in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the disclosure claimed. Thus, it should be understood that although the disclosure has been specifically disclosed by embodiments, exemplary embodiments and optional features, modification and variation of the concepts herein disclosed can be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this disclosure as defined by the appended claims.
It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the content clearly dictates otherwise. The term “plurality” includes two or more referents unless the content clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the disclosure pertains.
When a Markush group or other grouping is used herein, all individual members of the group and all combinations and possible subcombinations of the group are intended to be individually included in the disclosure. Every combination of components or materials described or exemplified herein can be used to practice the disclosure, unless otherwise stated. One of ordinary skill in the art will appreciate that methods, device elements, and materials other than those specifically exemplified may be employed in the practice of the disclosure without resort to undue experimentation. All art-known functional equivalents, of any such methods, device elements, and materials are intended to be included in this disclosure. Whenever a range is given in the specification, for example, a temperature range, a frequency range, a time range, or a composition range, all intermediate ranges and all subranges, as well as, all individual values included in the ranges given are intended to be included in the disclosure. Any one or more individual members of a range or group disclosed herein may be excluded from a claim of this disclosure. The disclosure illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is not specifically disclosed herein.
A number of embodiments of the disclosure have been described. The specific embodiments provided herein are examples of useful embodiments of the invention and it will be apparent to one skilled in the art that the disclosure can be carried out using a large number of variations of the devices, device components, methods steps set forth in the present description. As will be obvious to one of skill in the art, methods and devices useful for the present methods may include a large number of optional composition and processing elements and steps.
In particular, it will be understood that various modifications may be made without departing from the spirit and scope of the present disclosure. Accordingly, other embodiments are within the scope of the following claims.
Appendix D: List of 16S ribosomal RNA and 23S ribosomal RNA used for normalization
> A9Y61_06450: 23S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1190505-1193403 - Is on the negative strand DNA (- strand): SEQ ID NO: 1
cDNA: SEQ ID NO: 2
RNA: SEQ ID NO: 3
> A9Y61_06465: 16S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1194001-1195552 - Is on the negative strand DNA (- strand): SEQ ID NO: 4
cDNA: SEQ ID NO: 5
RNA: SEQ ID NO: 6
> A9Y61_07175: 23S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1325810-1328708 - Is on the negative strand DNA (- strand): SEQ ID NO: 7
cDNA: SEQ ID NO: 8
RNA: SEQ ID NO: 9
> A9Y61_RS07190: 16S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1329306-1330857 - Is on the negative strand DNA (+ strand): SEQ ID NO: 13
cDNA: SEQ ID NO: 14
RNA: SEQ ID NO: 15
> A9Y61_09315: 23S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1718894-1721792 - Is on the negative strand DNA (- strand): SEQ ID NO: 16
cDNA: SEQ ID NO: 17
RNA: SEQ ID NO: 18
> A9Y61_09330: 16S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1722390-17239411721792 — Is on the negative strand DNA (- strand): SEQ ID NO: 19
cDNA: SEQ ID NO: 20
RNA: SEQ ID NO: 21
> A9Y61_10490: 23S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1941315-1944213 - Is on the negative strand DNA (- strand): SEQ ID NO: 22
cDNA: SEQ ID NO: 23
RNA: SEQ ID NO: 24
> A9Y61_10505: 16S ribosomal RNA (1 of 4 copies) NZ_CP016017.1:1944811-1946362- Is on the negative strand DNA (- strand): SEQ ID NO: 25
cDNA: SEQ ID NO: 26
RNA: SEQ ID NO: 27
Sequences for the exemplary marker genes differentially expressed between an untreated sample and a sample treated with antibiotics
DNA (+ strand): SEQ ID NO: 28
cDNA: SEQ ID NO: 29
RNA: SEQ ID NO: 30
DNA (- strand): SEQ ID NO: 31
cDNA: SEQ ID NO: 32
RNA: SEQ ID NO: 33
DNA (- strand): SEQ ID NO: 34
cDNA: SEQ ID NO: 35
RNA: SEQ ID NO: 36
DNA (- strand): SEQ ID NO: 37
cDNA: SEQ ID NO: 38
RNA: SEQ ID NO: 39
DNA (- strand): SEQ ID NO: 40
cDNA: SEQ ID NO: 41
RNA: SEQ ID NO: 42
DNA (- strand): SEQ ID NO: 43
cDNA: SEQ ID NO: 44
RNA: SEQ ID NO: 45
DNA (- strand): SEQ ID NO: 46
cDNA: SEQ ID NO: 47
RNA: SEQ ID NO: 48
DNA (+ strand): SEQ ID NO: 49
cDNA: SEQ ID NO: 50
RNA: SEQ ID NO 51
DNA (+ strand): SEQ ID NO: 52
cDNA: SEQ ID NO: 53
RNA: SEQ ID NO: 54
DNA (+ strand): SEQ ID NO: 55
cDNA: SEQ ID NO: 56
RNA: SEQ ID NO: 57
DNA (- strand): SEQ ID NO: 58
cDNA: SEQ ID NO: 59
RNA: SEQ ID NO: 60
DNA (- strand): SEQ ID NO: 61
cDNA: SEQ ID NO: 62
RNA: SEQ ID NO: 63
DNA (- strand): SEQ ID NO: 64
cDNA: SEQ ID NO: 65
RNA: SEQ ID NO: 66
DNA (- strand): SEQ ID NO: 67
cDNA: SEQ ID NO: 68
RNA: SEQ ID NO: 69
DNA (+ strand): SEQ ID NO: 70
cDNA: SEQ ID NO: 71
RNA: SEQ ID NO: 72
DNA (+ strand): SEQ ID NO: 73
cDNA: SEQ ID NO: 74
RNA: SEQ ID NO: 75
DNA (- strand): SEQ ID NO: 76
cDNA: SEQ ID NO: 77
RNA: SEQ ID NO: 78
DNA (- strand): SEQ ID NO: 79
cDNA: SEQ ID NO: 80
RNA: SEQ ID NO: 81
DNA (- strand): SEQ ID NO: 82
cDNA: SEQ ID NO: 83
RNA: SEQ ID NO: 84
DNA (- strand): SEQ ID NO: 85
cDNA: SEQ ID NO: 86
RNA: SEQ ID NO: 87
DNA (+ strand): SEQ ID NO: 88
cDNA: SEQ ID NO: 89
RNA: SEQ ID NO: 90
DNA (+ strand): SEQ ID NO: 91
cDNA: SEQ ID NO: 92
RNA: SEQ ID NO: 93
DNA (- strand): SEQ ID NO: 94
cDNA: SEQ ID NO: 95
RNA: SEQ ID NO: 96
DNA (+ strand): SEQ ID NO: 97
cDNA: SEQ ID NO: 98
RNA: SEQ ID NO: 99
DNA (- strand): SEQ ID NO: 100
cDNA: SEQ ID NO: 101
RNA: SEQ ID NO: 102
DNA (- strand): SEQ ID NO: 103
cDNA: SEQ ID NO: 104
RNA: SEQ ID NO: 105
DNA (- strand): SEQ ID NO: 106
cDNA: SEQ ID NO: 107
RNA: SEQ ID NO: 108
DNA (- strand): SEQ ID NO: 109
cDNA: SEQ ID NO: 110
RNA: SEQ ID NO: 111
DNA (- strand): SEQ ID NO: 112
cDNA: SEQ ID NO: 113
RNA: SEQ ID NO: 114
DNA (- strand): SEQ ID NO: 115
cDNA: SEQ ID NO: 116
RNA: SEQ ID NO: 117
DNA (- strand): SEQ ID NO: 118
cDNA: SEQ ID NO: 119
RNA: SEQ ID NO: 120
DNA (- strand): SEQ ID NO: 121
cDNA: SEQ ID NO: 122
RNA: SEQ ID NO: 123
DNA (+ strand): SEQ ID NO: 124
cDNA: SEQ ID NO: 125
RNA: SEQ ID NO: 126
DNA (- strand): SEQ ID NO: 127
cDNA: SEQ ID NO: 128
RNA: SEQ ID NO: 129
DNA (+ strand): SEQ ID NO: 130
cDNA: SEQ ID NO: 131
RNA: SEQ ID NO: 132
DNA (- strand): SEQ ID NO: 133
cDNA: SEQ ID NO: 134
RNA: SEQ ID NO: 135
DNA (- strand): SEQ ID NO: 136
cDNA: SEQ ID NO: 137
RNA: SEQ ID NO: 138
DNA (- strand): SEQ ID NO: 139
cDNA: SEQ ID NO: 140
RNA: SEQ ID NO: 141
DNA (- strand): SEQ ID NO: 142
cDNA: SEQ ID NO: 143
RNA: SEQ ID NO: 144
DNA (+ strand): SEQ ID NO: 145
cDNA: SEQ ID NO: 146
RNA: SEQ ID NO: 147
DNA (+ strand): SEQ ID NO: 148
cDNA: SEQ ID NO: 149
RNA: SEQ ID NO: 150
DNA (+ strand): SEQ ID NO: 151
cDNA: SEQ ID NO: 152
RNA: SEQ ID NO: 153
DNA (- strand): SEQ ID NO: 228
cDNA: SEQ ID NO: 229
RNA: SEQ ID NO: 230
DNA(+)strand: SEQ ID NO: 154
cDNA: SEQ ID NO: 155
RNA: SEQ ID NO: 156
DNA (+)strand SEQ ID NO: 157
Cdna SEQ ID NO: 158
RNA SEQ ID NO: 159
>ng_165_porB SEQ ID NO: 178
>ng_166_porB SEQ ID NO: 179
>ng_167_porB SEQ ID NO: 180
>ng_168_porB SEQ ID NO: 181
>ng_169_porB SEQ ID NO: 182
>ng_170_porB SEQ ID NO: 183
>ng_171_porB SEQ ID NO: 184
>ng_172_porB SEQ ID NO: 185
>ng_173_porB SEQ ID NO: 186
>ng_174_porB SEQ ID NO: 187
>ng_175_porB SEQ ID NO: 188
>ng_176_porB SEQ ID NO: 189
>ng_177_porB SEQ ID NO: 190
>ng_178_porB SEQ ID NO: 191
>ng_179_porB SEQ ID NO: 192
>ng_180_porB SEQ ID NO: 193
>ng_181_porB SEQ ID NO: 194
>ng_182_porB SEQ ID NO: 195
>ng_183_porB SEQ ID NO: 196
>ng_184_porB SEQ ID NO: 197
>ng_185_porB SEQ ID NO: 198
>ng_186_porB SEQ ID NO: 199
>ng_187_porB SEQ ID NO: 200
>ng_188_porB SEQ ID NO: 201
>ng_189_porB SEQ ID NO: 202
>ng_190_porB SEQ ID NO: 203
>ng_191_porB SEQ ID NO: 204
>ng_192_porB SEQ ID NO: 205
>ng_193_porB SEQ ID NO: 206
>ng_194_porB SEQ ID NO: 207
>ng_195_porB SEQ ID NO: 208
>ng_196_porB SEQ ID NO: 209
>ng_197_porB SEQ ID NO: 210
>ng_198_porB SEQ ID NO: 211
>ng_199_porB SEQ ID NO: 212
>ng_200_porB SEQ ID NO: 213
>ng_201_porB SEQ ID NO: 214
>ng_202_porB SEQ ID NO: 215
>ng_203_porB SEQ ID NO: 216
>ng_204_porB SEQ ID NO: 217
>ng_205_porB SEQ ID NO: 218
>ng_206_porB SEQ ID NO: 219
>ng_207_porB SEQ ID NO: 220
>ng_208_porB SEQ ID NO: 221
>ng_209_porB SEQ ID NO: 222
>ng_210_porB SEQ ID NO: 223
>ng_211_porB SEQ ID NO: 224
>ng_212_porB SEQ ID NO: 225
>ng_213_porB SEQ ID NO: 226
>ng_214_porB SEQ ID NO: 227
DNA (- strand): SEQ ID NO: 231
RNA SEQ ID NO: 232
cDNA: SEQ ID NO: 233
DNA (- strand): SEQ ID NO: 234
RNA: SEQ ID NO: 235
cDNA: SEQ ID NO: 236
DNA (+ strand): SEQ ID NO: 237
RNA SEQ ID NO: 238
cDNA: SEQ ID NO: 239
DNA (+ strand): SEQ ID NO: 240
RNA SEQ ID NO: 241
cDNA: SEQ ID NO: 242
DNA (- strand): SEQ ID NO: 243
RNA SEQ ID NO: 244
cDNA: SEQ ID NO: 245
DNA (+ strand): SEQ ID NO: 246
RNA SEQ ID NO: 247
cDNA: SEQ ID NO: 248
DNA (+ strand): SEQ ID NO: 249
RNA: SEQ ID NO: 250
cDNA: SEQ ID NO: 251
DNA (- strand): SEQ ID NO: 252
RNA: SEQ ID NO: 253
cDNA: SEQ ID NO: 254
DNA (- strand): SEQ ID NO: 255
RNA SEQ ID NO: 256
cDNA: SEQ ID NO: 257
DNA (- strand): SEQ ID NO: 258
RNA SEQ ID NO: 259
cDNA: SEQ ID NO: 260
DNA (- strand): SEQ ID NO: 261
RNA: SEQ ID NO: 262
cDNA: SEQ ID NO: 263
DNA (- strand): SEQ ID NO: 264
RNA: SEQ ID NO: 265
cDNA: SEQ ID NO: 266
DNA (+ strand): SEQ ID NO: 267
RNA: SEQ ID NO: 268
cDNA: SEQ ID NO: 269
DNA (- strand): SEQ ID NO: 270
RNA: SEQ ID NO: 271
cDNA: SEQ ID NO: 272
DNA (+ strand): SEQ ID NO: 273
RNA: SEQ ID NO: 274
cDNA: SEQ ID NO: 275
DNA (- strand): SEQ ID NO: 276
RNA: SEQ ID NO: 277
cDNA: SEQ ID NO: 278
DNA (+ strand): SEQ ID NO: 279
RNA: SEQ ID NO: 280
cDNA: SEQ ID NO: 281
DNA (+ strand): SEQ ID NO: 282
RNA: SEQ ID NO: 283
cDNA: SEQ ID NO: 284
DNA (+ strand): SEQ ID NO: 285
RNA: SEQ ID NO: 286
cDNA: SEQ ID NO: 287
DNA (+ strand): SEQ ID NO: 288
RNA: SEQ ID NO: 289
cDNA: SEQ ID NO: 290
DNA (- strand): SEQ ID NO: 291
RNA: SEQ ID NO: 292
cDNA: SEQ ID NO: 293
DNA (- strand): SEQ ID NO: 294
RNA: SEQ ID NO: 295
cDNA: SEQ ID NO: 296
DNA (+ strand): SEQ ID NO: 297
RNA: SEQ ID NO: 298
cDNA: SEQ ID NO: 299
DNA (- strand): SEQ ID NO: 300
RNA: SEQ ID NO: 301
cDNA: SEQ ID NO: 302
DNA (- strand): SEQ ID NO: 303
RNA: SEQ ID NO: 304
cDNA: SEQ ID NO: 305
DNA (+ strand): SEQ ID NO: 306
RNA: SEQ ID NO: 307
cDNA: SEQ ID NO: 308
DNA (- strand): SEQ ID NO: 309
RNA: SEQ ID NO: 310
cDNA: SEQ ID NO: 311
DNA (+ strand): SEQ ID NO: 312
RNA: SEQ ID NO: 313
cDNA: SEQ ID NO: 314
DNA (+ strand): SEQ ID NO: 315
RNA: SEQ ID NO: 316
cDNA: SEQ ID NO: 317
DNA (- strand): SEQ ID NO: 318
RNA: SEQ ID NO: 319
cDNA: SEQ ID NO: 320
DNA (- strand) SEQ ID NO: 321
RNA: SEQ ID NO: 322
cDNA: SEQ ID NO: 323
DNA (- strand): SEQ ID NO: 324
RNA: SEQ ID NO: 325
cDNA: SEQ ID NO: 326
DNA (- strand): SEQ ID NO: 327
RNA: SEQ ID NO: 328
cDNA: SEQ ID NO: 329
DNA (- strand): SEQ ID NO: 330
RNA: SEQ ID NO: 331
cDNA: SEQ ID NO: 332
DNA (- strand): SEQ ID NO: 333
RNA: SEQ ID NO: 334
cDNA: SEQ ID NO: 335
DNA (- strand): SEQ ID NO: 336
RNA: SEQ ID NO: 337
cDNA: SEQ ID NO: 338
DNA (- strand): SEQ ID NO: 339
RNA: SEQ ID NO: 340
cDNA: SEQ ID NO: 341
DNA (- strand): SEQ ID NO: 342
RNA: SEQ ID NO: 343
cDNA: SEQ ID NO: 344
DNA (- strand): SEQ ID NO: 10
RNA: SEQ ID NO: 11
cDNA: SEQ ID NO: 12
The present application is the U.S. National Stage of International Patent Application No. PCT/US2019/044748, entitled “Antibiotic Susceptibility of Microorganisms and Related Markers, Compositions, methods and Systems,” filed on Aug. 1, 2019 which claims priority to U.S. Provisional Application No. 62/713,412, entitled “Antibiotic Susceptibility of Microorganisms and Related Markers, Compositions, methods and Systems” filed on Aug. 1, 2018 with docket number P2255-USP, the content of which is incorporated herein by reference in its entirety.
This invention was made with government support under Federal Award No. IDSEP160030-02awarded by the Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR) and the Wellcome Trust under the CARB-X program. The government has certain rights in the invention.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2019/044748 | 8/1/2019 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 62713412 | Aug 2018 | US |
