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WO2025096569A1 - Procédés et compositions pour profilage de résistance antimicrobienne en temps réel - Google Patents

Procédés et compositions pour profilage de résistance antimicrobienne en temps réel Download PDF

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WO2025096569A1
WO2025096569A1 PCT/US2024/053600 US2024053600W WO2025096569A1 WO 2025096569 A1 WO2025096569 A1 WO 2025096569A1 US 2024053600 W US2024053600 W US 2024053600W WO 2025096569 A1 WO2025096569 A1 WO 2025096569A1
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primer
sequencing
microbiome
sample
gene
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Erika GANDA RICOTTA
Jasna KOVAC
Sophia M. KENNEY
Emily P. VAN SYOC
Taejung CHUNG
Asha MILES
Stephanie CLOUSER
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Penn State Research Foundation
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6844—Nucleic acid amplification reactions
    • C12Q1/6853—Nucleic acid amplification reactions using modified primers or templates
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
    • C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria

Definitions

  • AMR antimicrobial resistance
  • AMR antimicrobial resistance genes
  • AMR antimicrobial resistance genes
  • AMR antimicrobial resistance genes
  • the rapid detection and characterization of resistant bacteria is a major component of the CDC’s Solutions Initiative that invests in national infrastructure to detect, respond, contain, and prevent resistant infections across healthcare settings, food, and communities. Increasing the frequency of isolate testing is effective to identify outbreaks faster and improve health outcomes. Still, this approach is limited in its ability to capture metagenomic resistance trends reflected in resistomes (i.e., collections of all ARG in a sample). The most comprehensive characterization of resistomes can be achieved with shotgun metagenomics.
  • resistome characterization efforts could therefore enable informed development of effective interventions to mitigate transmission and enrichment of ARG through the interconnected environment, animal, and human systems in a one health context.
  • shotgun metagenomics the currently used techniques for surveillance and tracking of ARG mostly rely on culturing bacteria from samples. A subset of isolates is then tested for antimicrobial susceptibility using time-consuming phenotypic assays (e.g., standard broth microdilution).
  • NGS next-generation sequencing
  • WGS whole-genome sequencing
  • Characterization of resistomes using culture independent methods can provide insight into the ARG status of a given sample without biases introduced by bacterial isolation.
  • the state-of-the-art culture-independent resistome characterization methods rely on untargeted shotgun sequencing (Raghavendra 2018), which has advantages as well as limitations discussed above.
  • ARG noyes 2017
  • Low relative abundance of ARG in the context of host genome therefore requires large and expensive sequencing depths to ensure the detection of ARG.
  • the resistome characterization challenge therefore needs to be addressed.
  • Noyes et al. developed an ARG enrichment method based on bait-capture. Their method increased the percentage of reads mapping to ARG in metagenomes from 0.1% to 11% (up to 1400 ARG detected), on average (Noyes 2017). However, this method is very costly. It also results in approximately 90% of the data being discarded as it does not map to ARG. Furthermore, the method application requires relatively high technical expertise. Another approach to enrichment is via target amplification.
  • CleanPlex has recently been applied to detect SARS-CoV-2 variants (Truong 2021; Alteri 2021; Shen 2021; Fernandez-Cadena 2021), however it is not available for resistome characterization. CleanPlex was not deemed feasible for resistome characterization in complex samples with thousands of different species. Like CleanPlex technology, a self-avoiding molecular recognition system (SAMRS) and novel hot- start polymerases have improved the specificity of multiplexed PCR reactions. However, these technologies have not yet been developed to a point where they could be applied to amplify thousands of targets, which is needed for comprehensive resistome characterization (Sharma 2014; Yang 2020). What is needed in the art are cost-effective and comprehensive methods to effectively implement ARG and pathogen surveillance.
  • SAMRS self-avoiding molecular recognition system
  • novel hot- start polymerases have improved the specificity of multiplexed PCR reactions.
  • these technologies have not yet been developed to a point where they could be applied to amplify thousands of targets
  • the present invention relates to a method of detecting two or more antimicrobial resistance (AMR) genes in a biological sample, the method comprising: (a) providing a reaction mixture comprising (i) two or more oligonucleotide primer pairs, wherein each primer pair is specific for an AMR gene target (the gene or a variant thereof), and further wherein each primer has a cleavage domain positioned 5' of a blocking group and 3' of a position of hybridization with a target nucleic acid, wherein the blocking group is linked at or near the end of the 3 '-end of the oligonucleotide primer, wherein the blocking group prevents primer extension and/or inhibits the primer from serving as a template for DNA synthesis, (ii) a biological sample comprising two or more target nucleic acids, (iii) a cleaving enzyme, and (iv) a polymerase; (b) exposing the two or more oligonucleotide primer pairs to the biological sample,
  • FIG.1A-G shows rhPCR methodology.
  • Each individual sample undergoes a 2-step PCR where a) custom rhPrimers anneal to target sequences, b) RNAse H2 recognizes RNA base and cleaves blocking moiety, allowing c) DNA polymerase to amplify target sequence.
  • Amplicons from PCR undergo a second indexing PCR where d) uniquely barcoded primers identify samples before e) sequencing adapters are attached to final amplicon.
  • FIG.2 shows the feasibility of rhPCR-based antimicrobial resistance gene amplification (rhAMR amplification). Amplicons were sequenced using Illumina MiSeq with ⁇ 15,000 reads per sample.
  • FIG.3A-D shows rhAMR results. Selected results from proof-of-concept experiments in (A) mock microbiome; (B) turkey cloacal swabs; and (C) human fecal samples. Limit of Detection (D) of genes specific to serial diluted spike-in sample.
  • FIG.4 shows workflow of LOD analysis using a human fecal sample and S. sonnei.
  • FIG.5 shows gene counts of each unique ARG present in S. sonnei at 1:100, 1:1,000, and 1:10,000 dilutions, but absent in the fecal sample resistome as determined by whole genome sequencing.
  • FIG.6A-B shows correlation between log relative abundance of ARG counts and dilution factor of S. sonnei DNA inoculated into human fecal sample DNA. ARGs with counts ⁇ 25 are shown in (A) and ARGs with counts ⁇ 25 are shown in (B).
  • FIG.7 shows regression coefficient (R 2 ) distributions characterizing the correlation between ARGs and inoculated S. sonnei dilution.
  • FIG. 8A-B shows Illumina-sequencing based experiments (A) and illumina versus nanopore comparison (B).
  • the stepwise workflow includes 1) selecting antimicrobial resistance genes (ARGs) associated with AMR phenotypes from MEGARes v2.0 database, then 2) collecting samples from at least three sources (mock microbiome, human, turkey), then 3a) whole-genome sequencing of samples; 3b) serially diluting spike-ins of individual bacterial isolates that have unique ARGs to a microbial community without said gene; and 4) amplifying and analyzing for the presence of ARGs.
  • Figure 9 shows a subset pool PCA (annotated).
  • Figure 10 shows rhAMR workflow.
  • Figure 11A-B shows compositional rhAMR vs. WGS mock microbiome.
  • FIG. 12A-C shows composition rhAMR versus shotgun in human samples.
  • (A) shows metagenome (all detected);
  • (B) shows metagenome in rhAMR only; and
  • (C) shows rhAMR.
  • Figure 13A-C shows a composition rhAMR versus shotgun in turkey samples.
  • (A) shows metagenome (all detected);
  • (B) shows metagenome in rhAMR only; and
  • C) shows rhAMR.
  • Figure 14 shows rhAMR paired with nanopore sequencing.
  • Figure 15A-B shows individual primer performance under serial dilutions of gene targets.
  • (A) shows specific genes and (B) shows antimicrobials.
  • Figure 16 shows EC-K12 ROC curve.
  • Figure 17A-B shows rhAMR FP/TP/FN/TN in mock microbiome pools.
  • DETAILED DESCRIPTION Definitions Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. In case of conflict, the present document, including definitions, will control. Preferred methods and materials are described below, although methods and materials similar or equivalent to those described herein can be used in practice or testing of the present invention.
  • the terms “antibiotic” and “antimicrobial compound” are used interchangeably herein and are used herein to describe a compound or composition which decreases the viability of a microorganism, or which inhibits the growth or reproduction of a microorganism.
  • “Inhibits the growth or reproduction” means increasing the generation cycle time by at least 2-fold, preferably at least 10-fold, more preferably at least 100-fold, and most preferably indefinitely, as in total cell death.
  • an antibiotic is further intended to include an antibacterial, bacteriostatic, or bactericidal agent.
  • Non-limiting examples of antibiotics useful in aspect of the invention include penicillins, cephalosporins, aminoglycosides, sulfonamides, macrolides, tetracyclins, lincosamides, quinolones, chloramphenicol, glycopeptides, metronidazole, rifampin, isoniazid, spectinomycin, folate inhibitors, sulfamethoxazole, and others.
  • resistant and “resistance”, as used herein, refer to the phenomenon that a microorganism does not exhibit decreased viability or inhibited growth or reproduction when exposed to concentrations of the antimicrobial agent that can be attained with normal therapeutic dosage regimes in humans.
  • microorganism refers in particular to pathogenic microorganisms, such as bacteria, yeast, fungi and intra- or extra-cellular parasites. In preferred aspects of the present invention, the term refers to pathogenic or opportunistic bacteria. These include both Gram-positive and Gram-negative bacteria.
  • Gram-negative bacteria By way of Gram-negative bacteria, mention may be made of bacteria of the following genera: Pseudomonas, Escherichia, Salmonella, Shigella, Enterobacter, Klebsiella, Serratia, Proteus, Campylobacter, Haemophilus, Morganella, Vibrio, Yersinia, Acinetobacter, Branhamella, Neisseria, Burkholderia, Citrobacter, Hafnia, Edwardsiella, Aeromonas, Moraxella, Pasteurella, Providencia, Actinobacillus, Alcaligenes, Bordetella, Cedecea, Erwinia, Pantoea, Ralstonia, Stenotrophomonas, Xanthomonas and Legionella.
  • Gram-positive bacteria By way of Gram-positive bacteria, mention may be made of bacteria of the following genera: Enterococcus, Streptococcus, Staphylococcus, Bacillus, Listeria, Clostridium, Gardnerella, Kocuria, Lactococcus, Leuconostoc, Micrococcus, Mycobacteria and Corynebacteria.
  • yeasts and fungi mention may be made of yeasts of the following genera: Candida, Cryptococcus, Saccharomyces and Trichosporon.
  • sample refers to a substance that contains or is suspected of containing an analyte, such as a microorganism to be characterized.
  • a sample useful in a method of the invention can be a liquid or solid, can be dissolved or suspended in a liquid, can be in an emulsion or gel, and can be bound to or absorbed onto a material.
  • a sample can be a biological sample, environmental sample, experimental sample, diagnostic sample, or any other type of sample that contains or is suspected to contain the analyte of interest.
  • a sample can be, or can contain, an organism, organ, tissue, cell, bodily fluid, biopsy sample, environmental sample (such as water, wastewater, or swab), soil, animal bedding, or fraction thereof.
  • a sample can include biological fluids, whole organisms, organs, tissues, cells, microorganisms, culture supernatants, subcellular organelles, protein complexes, individual proteins, recombinant proteins, fusion proteins, viruses, viral particles, peptides and amino acids.
  • quantifying refers to any method for obtaining a quantitative measure. For example, quantifying a microorganism can include determining its abundance, relative abundance, intensity, concentration, and/or count, etc.
  • “Complement” or “complementary” as used herein means a nucleic acid, and can mean Watson-Crick (e.g., A-T/U and C-G) or Hoogsteen base pairing between nucleotides or nucleotide analogs of nucleic acid molecules.
  • “Fluorophore” or “fluorescent label” refers to compounds with a fluorescent emission maximum between about 350 and 900 nm.
  • “Hybridization” as used herein, refers to the formation of a duplex structure by two single-stranded nucleic acids due to complementary base pairing. Hybridization can occur between fully complementary nucleic acid strands or between "substantially complementary” nucleic acid strands that contain minor regions of mismatch.
  • “Identical” sequences refers to sequences of the exact same sequence or sequences similar enough to act in the same manner for the purpose of signal generation or hybridizing to complementary nucleic acid sequences.
  • “Primer dimers” refers to the hybridization of two oligonucleotide primers.
  • “Stringent hybridization conditions” as used herein means conditions under which hybridization of fully complementary nucleic acid strands is strongly preferred. Under stringent hybridization conditions, a first nucleic acid sequence (for example, a primer) will hybridize to a second nucleic acid sequence (for example, a target sequence), such as in a complex mixture of nucleic acids. Stringent conditions are sequence-dependent and will be different in different circumstances.
  • Stringent conditions can be selected to be about 5-10°C lower than the thermal melting point (Tm) for the specific sequence at a defined ionic strength pH.
  • Tm can be the temperature (under defined ionic strength, pH, and nucleic concentration) at which 50% of an oligonucleotide complementary to a target hybridize to the target sequence at equilibrium (as the target sequences are present in excess, at Tm, 50% of the probes are occupied at equilibrium).
  • Stringent conditions can be those in which the salt concentration is less than about 1.0 M sodium ion, such as about 0.01-1.0 M sodium ion concentration (or other salts) at pH 7.0 to 8.3 and the temperature is at least about 30°C for short probes (e.g., about 10-50 nucleotides) and at least about 60°C for long probes (e.g., greater than about 50 nucleotides). Stringent conditions can also be achieved with the addition of destabilizing agents such as formamide. For selective or specific hybridization, a positive signal can be at least 2 to 10 times background hybridization.
  • Exemplary stringent hybridization conditions include the following: 50% formamide, 5x SSC, and 1% SDS, incubating at 42°C, or, 5x SSC, 1% SDS, incubating at 65°C, with wash in 0.2x SSC, and 0.1% SDS at 65°C.
  • the terms "nucleic acid,” “oligonucleotide,” or “polynucleotide,” as used herein, refer to at least two nucleotides covalently linked together.
  • the depiction of a single strand also defines the sequence of the complementary strand.
  • a nucleic acid also encompasses the complementary strand of a depicted single strand.
  • nucleic acid can be used for the same purpose as a given nucleic acid.
  • a nucleic acid also encompasses substantially identical nucleic acids and complements thereof.
  • a single strand provides a probe that can hybridize to a target sequence under stringent hybridization conditions.
  • a nucleic acid also encompasses a probe that hybridizes under stringent hybridization conditions.
  • Nucleic acids can be single stranded or double stranded, or can contain portions of both double stranded and single stranded sequences.
  • the nucleic acid can be DNA, both genomic and cDNA, RNA, or a hybrid, where the nucleic acid can contain combinations of deoxyribo- and ribonucleotides, and combinations of bases including uracil, adenine, thymine, cytosine, guanine, inosine, xanthine hypoxanthine, isocytosine and isoguanine.
  • Nucleic acids can be obtained by chemical synthesis methods or by recombinant methods.
  • a particular nucleic acid sequence can encompass conservatively modified variants thereof (e.g., codon substitutions), alleles, orthologs, single nucleotide polymorphisms (SNPs), and complementary sequences as well as the sequence explicitly indicated.
  • PCR Polymerase Chain Reaction
  • the reaction typically involves the use of two synthetic oligonucleotide primers, which are complementary to nucleotide sequences in the substrate DNA which are separated by a short distance of a few hundred to a few thousand base pairs, and the use of a thermostable DNA polymerase.
  • the chain reaction consists of a series of 10 to 40 cycles. In each cycle, the substrate DNA is first denatured at high temperature. After cooling down, synthetic primers which are present in vast excess, hybridize to the substrate DNA to form double- stranded structures along complementary nucleotide sequences.
  • Primer-substrate DNA complexes will then serve as initiation sites for a DNA synthesis reaction catalyzed by a DNA polymerase, resulting in the synthesis of a new DNA strand complementary to the substrate DNA strand.
  • the synthesis process is repeated with each additional cycle, creating an amplified product of the substrate DNA.
  • "Primer,” as used herein, refers to an oligonucleotide capable of acting as a point of initiation for DNA synthesis under suitable conditions.
  • Suitable conditions include those in which hybridization of the oligonucleotide to a template nucleic acid occurs, and synthesis or amplification of the target sequence occurs, in the presence of four different nucleoside triphosphates and an agent for extension (e.g., a DNA polymerase) in an appropriate buffer and at a suitable temperature.
  • Probe and “fluorescent generation probe” are synonymous and refer to either a) a sequence-specific oligonucleotide having an attached fluorophore and/or a quencher, and optionally a minor groove binder or b) a DNA binding reagent, such as, but not limited to, SYBR® Green dye.
  • Quencher refers to a molecule or part of a compound, which is capable of reducing the emission from a fluorescent donor when attached to or in proximity to the donor. Quenching may occur by any of several mechanisms including fluorescence resonance energy transfer, photo-induced electron transfer, paramagnetic enhancement of intersystem crossing, Dexter exchange coupling, and exciton coupling such as the formation of dark complexes.
  • RNase H PCR rhPCR
  • “Blocked” primers contain at least one chemical moiety (such as, but not limited to, a ribonucleic acid residue) bound to the primer or other oligonucleotide, such that hybridization of the blocked primer to the template nucleic acid occurs, without amplification of the nucleic acid by the DNA polymerase.
  • the chemical moiety is removed by cleavage by an RNase H enzyme, which is activated at a high temperature (e.g., 50°C or greater). Following RNase H cleavage, amplification of the target DNA can occur.
  • the 3' end of a blocked primer can comprise the moiety rDDDDMx, wherein relative to the target nucleic acid sequence, "r” is an RNA residue, “D” is a complementary DNA residue, “M” is a mismatched DNA residue, and “x” is a C3 spacer.
  • a C3 spacer is a short 3-carbon chain attached to the terminal 3' hydroxyl group of the oligonucleotide, which further inhibits the DNA polymerase from binding before cleavage of the RNA residue.
  • a primer is “specific,” for a target sequence if, when used in an amplification reaction under sufficiently stringent conditions, the primer hybridizes primarily to the target nucleic acid.
  • a primer is specific for a target sequence if the primer-target duplex stability is greater than the stability of a duplex formed between the primer and any other sequence found in the sample.
  • factors such as salt conditions as well as base composition of the primer and the location of the mismatches, will affect the specificity of the primer, and that routine experimental confirmation of the primer specificity will be needed in many cases.
  • Hybridization conditions can be chosen under which the primer can form stable duplexes only with a target sequence.
  • target-specific primers under suitably stringent amplification conditions enables the selective amplification of those target sequences which contain the target primer binding sites.
  • non-specific amplification refers to the amplification of nucleic acid sequences other than the target sequence which results from primers hybridizing to sequences other than the target sequence and then serving as a substrate for primer extension.
  • the hybridization of a primer to a non-target sequence is referred to as “non-specific hybridization” and is apt to occur especially during the lower temperature, reduced stringency, pre-amplification conditions, or in situations where there is a variant allele in the sample having a very closely related sequence to the true target as in the case of a single nucleotide polymorphism (SNP).
  • SNP single nucleotide polymorphism
  • primer dimer refers to a template-independent non-specific amplification product, which is believed to result from primer extensions wherein another primer serves as a template. Although primer dimers frequently appear to be a concatamer of two primers, i.e., a dimer, concatamers of more than two primers also occur.
  • primer dimer is used herein generically to encompass a template-independent non-specific amplification product.
  • reaction mixture refers to a solution containing reagents necessary to carry out a given reaction.
  • a “PCR reaction mixture” typically contains oligonucleotide primers, a DNA polymerase (most typically a thermostable DNA polymerase), dNTP's, and a divalent metal cation in a suitable buffer.
  • a reaction mixture is referred to as complete if it contains all reagents necessary to enable the reaction, and incomplete if it contains only a subset of the necessary reagents.
  • reaction components are routinely stored as separate solutions, each containing a subset of the total components, for reasons of convenience, storage stability, or to allow for application-dependent adjustment of the component concentrations, and that reaction components are combined prior to the reaction to create a complete reaction mixture.
  • reaction components are packaged separately for commercialization and that useful commercial kits may contain any subset of the reaction components which includes the blocked primers of the invention.
  • non-activated refers to a primer or other oligonucleotide that is incapable of participating in a primer extension reaction or a ligation reaction because either DNA polymerase or DNA ligase cannot interact with the oligonucleotide for their intended purposes.
  • the non-activated state occurs because the primer is blocked at or near the 3′-end so as to prevent primer extension.
  • specific groups are bound at or near the 3′-end of the primer, DNA polymerase cannot bind to the primer and extension cannot occur.
  • a non-activated primer is, however, capable of hybridizing to a substantially complementary nucleotide sequence.
  • the term “activated,” as used herein, refers to a primer or other oligonucleotide that is capable of participating in a reaction with DNA polymerase or DNA ligase.
  • a primer or other oligonucleotide becomes activated after it hybridizes to a substantially complementary nucleic acid sequence and is cleaved to generate a functional 3′- or 5′-end so that it can interact with a DNA polymerase or a DNA ligase.
  • a 3′-blocking group can be removed from the primer by, for example, a cleaving enzyme such that DNA polymerase can bind to the 3′ end of the primer and promote primer extension.
  • cleavage domain or “cleaving domain,” as used herein, are synonymous and refer to a region located between the 5′ and 3′ end of a primer or other oligonucleotide that is recognized by a cleavage compound, for example a cleavage enzyme, that will cleave the primer or other oligonucleotide.
  • the cleavage domain is designed such that the primer or other oligonucleotide is cleaved only when it is hybridized to a complementary nucleic acid sequence, but will not be cleaved when it is single-stranded.
  • the cleavage domain or sequences flanking it may include a moiety that a) prevents or inhibits the extension or ligation of a primer or other oligonucleotide by a polymerase or a ligase, b) enhances discrimination to detect variant alleles, or c) suppresses undesired cleavage reactions.
  • One or more such moieties may be included in the cleavage domain or the sequences flanking it.
  • RNase H cleavage domain is a type of cleavage domain that contains one or more ribonucleic acid residue or an alternative analog which provides a substrate for an RNase H.
  • An RNase H cleavage domain can be located anywhere within a primer or oligonucleotide, and is preferably located at or near the 3′-end or the 5′-end of the molecule.
  • cleavage compound or “cleaving agent” as used herein, refers to any compound that can recognize a cleavage domain within a primer or other oligonucleotide, and selectively cleave the oligonucleotide based on the presence of the cleavage domain.
  • the cleavage compounds utilized in the invention selectively cleave the primer or other oligonucleotide comprising the cleavage domain only when it is hybridized to a substantially complementary nucleic acid sequence, but will not cleave the primer or other oligonucleotide when it is single stranded.
  • the cleavage compound cleaves the primer or other oligonucleotide within or adjacent to the cleavage domain.
  • the term “adjacent,” as used herein, means that the cleavage compound cleaves the primer or other oligonucleotide at either the 5′-end or the 3′ end of the cleavage domain.
  • the cleavage compound is a “cleaving enzyme.”
  • a cleaving enzyme is a protein or a ribozyme that is capable of recognizing the cleaving domain when a primer or other nucleotide is hybridized to a substantially complementary nucleic acid sequence, but that will not cleave the complementary nucleic acid sequence (i.e., it provides a single strand break in the duplex).
  • the cleaving enzyme will also not cleave the primer or other oligonucleotide comprising the cleavage domain when it is single stranded.
  • cleaving enzymes examples include RNase H enzymes and other nicking enzymes.
  • blocking group refers to a chemical moiety that is bound to the primer or other oligonucleotide such that an amplification reaction does not occur. For example, primer extension and/or DNA ligation does not occur. Once the blocking group is removed from the primer or other oligonucleotide, the oligonucleotide is capable of participating in the assay for which it was designed (PCR, ligation, sequencing, etc).
  • the “blocking group” can be any chemical moiety that inhibits recognition by a polymerase or DNA ligase.
  • the blocking group may be incorporated into the cleavage domain but is generally located on either the 5′- or 3′-side of the cleavage domain.
  • the blocking group can be comprised of more than one chemical moiety.
  • the “blocking group” is typically removed after hybridization of the oligonucleotide to its target sequence.
  • AMR antimicrobial resistance
  • Short read (SR) targets are used because the rhPCR technology has been optimized for Illumina SR sequencing, however, Oxford Nanopore Technologies® (ONT) platforms have also been successfully used, thus there is novelty in applying ONT for real-time data acquisition.
  • rhPCR panels are used to profile ARGs in microbiomes and wastewater samples and the panel is expanded to include the detection of SARS-CoV-2 variants, foodborne pathogens of interest and high-resolution subtyping of select foodborne bacteria.
  • a novel resistome characterization method providing the resolution of shotgun sequencing with the cost-effectiveness of targeted PCR. Real-time results can be obtained, for example, using a portable Nanopore MinION sequencer.
  • Figure 14 shows the application of highly parallel multiplexed amplicon generation (to enrich for ARGs from complex samples) and real-time sequencing with the pocket-sized sequencer Nanopore MinION Mk1C.
  • This method is based on a dual-enzyme approach that uses rhPCR technology (Dobosy 2011) with rhPrimers which contain a 3’ blocking group and a single RNA base.
  • This DNA-RNA junction is recognized and cleaved by RNase H2 (Fresnedo-Ramirez 2019). Only after cleaving, extension by DNA polymerases becomes possible (Dobosy 2011, herein incorporated by reference in its entirety).
  • This approach reduces off-target amplification and mitigates primer dimer creation, allowing for massive multiplexing (Fresnedo-Ramirez 2019) with high specificity and real-time sequencing.
  • rhPCR also referred to as RNAse H-dependent PCR
  • RNAse H-dependent PCR can be used (U.S. Patent Application No. US2019/0218611, herein incorporated by reference in its entirety for its teaching concerning rhPCR).
  • rhPCR is drawn to a method of utilizing blocked-cleavable rhPCR primers (see U.S. Patent Application Publication No. US 2009/0325169 A1, incorporated by reference herein in its entirety) and a DNA polymerase with high levels of mismatch discrimination. This is illustrated in Figure 1A-C. This can be accomplished using primers which are specifically designed to target AMR genes (see Example 1, for instance).
  • the methods described herein can be performed using any suitable RNase H enzyme that is derived or obtained from any organism.
  • RNase H-dependent PCR reactions are performed using an RNase H enzyme obtained or derived from the hyperthermophilic archaeon Pyrococcus abyssi such as RNase H2.
  • the RNase H enzyme employed in the methods described herein desirably is obtained or derived from Pyrococcus abyssi, preferably an RNase H2 obtained or derived from Pyrococcus abyssi.
  • the RNase H enzyme employed in the methods described herein can be obtained or derived from other species, for example, Pyrococcus furiosis, Pyrococcus horikoshii, Thermococcus kodakarensis, or Thermococcus litoralis.
  • the amplicons can be fitted with barcoded adapters which allow for the individual amplicons to be identified. They can then be pooled and sequenced. Methods of barcoding sequences which are compliant with the sequencing methods disclosed herein are known to those of skill in the art. For example, U.S. Patent Application US 2018/0087050 and PCT Application WO2022/067019 (both incorporated by reference herein), teach methods of barcoding nucleic acid which can be used with the present invention.
  • Oxford Nanopore Technologies relies on a nanoscale protein pore, or ‘nanopore’, that serves as a biosensor and is embedded in an electrically resistant polymer membrane.
  • a constant voltage is applied to produce an ionic current through the nanopore such that negatively charged single-stranded DNA or RNA molecules are driven through the nanopore from the negatively charged ‘cis’ side to the positively charged ‘trans’ side.
  • Translocation speed is controlled by a motor protein that ratchets the nucleic acid molecule through the nanopore in a step-wise manner. Changes in the ionic current during translocation correspond to the nucleotide sequence present in the sensing region and are decoded using computational algorithms, allowing real-time sequencing of single molecules.
  • this invention can be used with any sequencing technology which allows for high-speed, high- throughput sequencing of a large amount of nucleic acid.
  • a method of detecting two or more antimicrobial resistance (AMR) gene targets in a biological sample comprising: (a) providing a reaction mixture comprising (i) two or more oligonucleotide primer pairs, wherein each primer pair is specific for an AMR gene target, and further wherein each primer has a cleavage domain positioned 5' of a blocking group and 3' of a position of hybridization with a target nucleic acid, wherein the blocking group is linked at or near the end of the 3'-end of the oligonucleotide primer, wherein the blocking group prevents primer extension and/or inhibits the primer from serving as a template for DNA synthesis, (ii) a biological sample comprising two or more target nucleic acids, (iii) a cleaving enzyme, and (iv) a polymerase; (b) exposing the two or more oligonucleotide primer pairs to the biological sample, wherein if one or more target nucleic
  • AMR gene targets are well characterized, and an example list can be found below in Table 1.
  • the primers disclosed herein can be used to detect any AMR gene target from any organism, including pathogenic and non-pathogenic microorganisms, such as bacteria and fungi.
  • a “gene target” can mean a nucleic acid sequence within a gene which is the target of detection efforts.
  • the method disclosed herein can be used to carry out multiplex detection, so that 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, or more gene targets can be detected at the same time.
  • 3’ end” or “5’ end” is meant the terminal nucleotide in a nucleic acid, such as a primer.
  • primer pair is meant a pair of primers which is suitable for amplification of a gene target, such as a forward and reverse primer (one of each per pair).
  • an adaptor also referred to herein as a “barcode” which can allow for the sequencing of the amplified product. This can be done using a variety of methods known in the art, such as with nanopore technology described above.
  • the method may comprise detecting the presence, absence or amount of a target polynucleotide by detecting a signal output. The signal may be characteristic of an attached barcode.
  • EXAMPLE 1 HIGHLY MULTIPLEXED AMPLICON SEQUENCING WITH NANOPORE FOR DETECTION OF PATHOGENS AND ARG TARGETS Overview
  • An ARG primer panel has been successfully designed in collaboration with bioinformaticians at IDT using the MEGARes2.0 database.
  • the primer panel contains 2,451 pairs of primers that have been tested in silico and found to detect 7,364 ARG targets in 2 separate reactions.
  • a subset of this panel has been tested in vitro with mock microbiomes and human fecal samples using both short read sequencing (SRS) and Oxford Nanopore Technology (ONT) sequencing.
  • SRS short read sequencing
  • ONT Oxford Nanopore Technology
  • Short read targets are used because the rhPCR technology has been optimized for Illumina short read sequencing, however, success has been proven in obtaining data from ONT platforms, therefore ONT can be applied for real-time data acquisition.
  • This panel is then combined to primer panels targeting SARS-CoV-2 variants of concern. Primers are developed to target major foodborne pathogens of concern in the US.
  • the rhPCR primer panel is designed for compatibility for multiplexing in as few reactions as possible and for subsequent subtyping based on amplicon sequences.
  • a (i) primer panel based on MLST schemes for bacterial pathogens of interest is designed and (ii) the panel performance is evaluated using mock microbiomes and spiked wastewater samples. High resolution subtyping of foodborne bacteria is also conducted.
  • Genomic regions of high discriminatory ability for subtyping of foodborne pathogens is carried out in Salmonella and E. coli.
  • Diagnostic SNPs are identified and used to develop a large scale MLST scheme that are used for (ii) primer panel design and testing using mock microbiomes and spiked wastewater samples. This process yields (i) optimized ARG rhPCR panel, (ii) rhPCR primer panel for detection of SARS-CoV-2 variants of concern, (iii) a foodborne pathogen detection rhPCR panel, and (iv) a high-resolution foodborne bacteria subtyping rhPCR panel.
  • Technical Details Design of comprehensive rhPCR primer panels ARG primer panels were successfully designed using the MEGARes2.0 3 database.
  • Strains were selected to be included in the mock microbiome based on their ARG profiles identified using WGS. Detected ARG (a total of 96) were used as the “ground truth” to evaluate the performance of the rhPCR primer panel. This primer panel was also applied on DNA from human fecal samples inoculated with DNA from bacteria containing unique ARGs in serial dilutions to demonstrate the feasibility of amplification of the target genes in a complex sample, and assess primer efficiency, and limit of detection. Shotgun sequencing of human fecal samples was used to determine bacteria for inoculation and as ground truth. This experiment has been repeated with ONT sequencing technology with similar results. This can also be done with fecal samples from any animals, including poultry such as turkeys.
  • the methods disclosed herein are a better- performing alternative to shotgun sequencing for resistome, SARS-CoV-2, and foodborne pathogen profiling due to improved sensitivity, and reduced cost and time-to-results.
  • Primers are designed and validated in silico followed by validation using mock microbiomes comprised of a well-characterized panel of pathogens and wastewater and clinical samples spiked with various strains. Using well-defined mock microbiomes allows for initial sensitivity, specificity, limit of detection, and primer efficiency assessment, while the use of environmental and clinical samples demonstrate the feasibility for application on complex samples (clinical samples, wastewater).
  • rhPCR can detect targets present in a mock microbiome with a high >80% sensitivity and specificity. Furthermore, rhPCR can detect targets present in a strain inoculated into a complex sample (wastewater, clinical samples) at low concentrations (e.g., 1:100,000) demonstrating good limit of detection.
  • the CDC’s enteric diversity panel from Antibiotic Resistance Isolate Bank is used to assemble a mock microbiome and to spike samples. Strains are grown in appropriate media, DNA is extracted, quantified, and mixed in equal ratios based on genome equivalents which is used for amplification with the rhPCR panel and sequencing as described in Figure 1.
  • Whole genome sequencing data for isolates is used as ground truth data for tests using mock microbiomes. Samples are profiled and diluted at different concentrations to estimate the method's limit of detection. Samples’ ARGs are characterized prior to inoculation using shotgun metagenomics (at ⁇ 60 M reads/sample) and with the rhPCR panel to assess the proportion of targets that were detected using both methods. Additionally, rhPCR amplicons are sequenced both with ONT and Illumina as the gold standard for rhPCR-based sequencing. The generated data is used to optimize and evaluate the performance of rhPCR for AMR characterization of different sample types.
  • Primer design and in-silico testing rhPCR ARG primers were designed to target over 7,800 ARG targets included in the recently updated MEGARes 2 database (Doster 2020). Primer design and in silico testing was performed by IDT scientists based on the MEGARes v2.0 database using their proprietary software. IDT has provided primer sequences to the Ganda lab in FASTA and BAM formats as well as assay IDs for primer purchase. Based on initial results, individual primers are purchased in 96-well plate format to allow for mix-and-match optimization of the panel. Preparation of mock microbiomes and spiked samples: The CDC’s Enteric Diversity Panel (EDP) is used for preparation of mock microbiomes that are used in the sensitivity, specificity, and primer efficiency evaluation.
  • EDP Enteric Diversity Panel
  • the EDP panel includes 30 strains for which WGS are available and ARG are known. Strains are selected that harbor 3 or more unique ARG each to include in a mock microbiome for the initial sensitivity and specificity evaluation in a well- defined and controlled system. Subsequently, all 30 strains are used in the limit of detection (LOD) and primer efficiency assessments. Nucleic acid extraction: DNA is isolated from 1.5 ml of each culture using the MagMAX Microbiome Ultra Nucleic Acid Isolation Kits (ThermoFisher, MA), according to the manufacturer's instructions. DNA concentration and quality are assessed with a Qubit and Nanodrop, respectively. rhPCR, library preparation, nanopore sequencing, and data processing.
  • Extracted genomic DNA undergoes dual-PCR rhPCR library preparation ( Figure 1) following manufacturer’s instructions. Briefly, extracted DNA is combined with rhPCR primers and rhAmpSeq library mix to amplify targets of interest. The rhPCR amplicons from step 1 are prepared for sequencing with the Oxford Nanopore Rapid Barcoding Kit. After barcoding, the samples are pooled into one library and loaded into the R9 flow cell. Sequencing is run for up to 40 hours, and data is processed with EPI2ME using the standard Fastq Antimicrobial Resistance Workflow. Assay controls. Nucleic acid extractions, rhPCR and rhPCR library preparation is each carried out as described above with reagents only (no sample DNA added) and is included in sequencing runs as negative controls.
  • Paired-end reads are merged in FLASH with max overlap of 150 and converted to fasta format with seqkit (Shen 2016).
  • a BLAST database is constructed from the entire MEGARes database (v2.0) (Doster 2020) and a local alignment performed and filtered to 100% identity.
  • the AmrPlusPlus workflow (Doster 2020; Lakin 2017) is used instead of BLAST where applicable.
  • Top hits are identified as present ARG.
  • Gene counts are constructed from the summed number of local alignments per sample, and relative abundances calculated.
  • Sensitivity and specificity Mock microbiomes are prepared with a leave-one-out design to assess the sensitivity and specificity for detection of genes that are unique to a given strain or variant that is left out in each experiment.
  • Mock microbiomes are used to determine the sensitivity and specificity of rhPCR to detect the unique targets of a total of targets present in the selected strains.
  • the WGS data of strains are used as gold standard for calculation of sensitivity (true positive rate) and specificity (true negative rate).
  • Limit of detection and primer efficiency Mock microbiomes are prepared comprised of strains that do not carry a specific gene or variant (e.g. gene “X”) and inoculate them with a “spike strain” that carries the gene or variant.
  • the strains are grown in appropriate conditions and extracted nucleic acids are mixed in equal ratios to form a mock microbiome.
  • the spike strain is inoculated into the mock microbiome in different concentrations (at 1:1, 1:10, 1:100, 1:1,000, 1:10,000, 1:100,000 and 1:1,000,000 ratio).
  • concentration of a spiked strain an increasing relative abundance of the gene that is uniquely present in the spiked strain is used.
  • the proposed dilutions were selected based on data that showed that the target ARGs can be detected even at 1:10,000 dilution.
  • the primer efficiency is measured by calculating the regression coefficient for a linear regression model describing the relationship between the target gene read count and the dilution of the strain carrying the target gene. Once the performance of the primer panel is satisfactory, the primer panel is applied to characterize wastewater samples.
  • Target counts are determined from the summed number of local alignments per sample, and relative abundances are calculated. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) are calculated according to Dohoo (Dohoo 2009).
  • a database is developed containing publicly available SARS-CoV-2 variants of concern (Zhou 2021; Korber 2020; Volz 2021) and other coronavirus genomes. Alignments are performed to identify regions of greatest diversity among closely and distantly related viruses, and diagnostic single nucleotide polymorphisms (SNPs) are identified. These regions and SNPs are used for panel design in collaboration with IDT as described above.
  • RNA extraction is performed from inactivated pure cultures of SARS-CoV-2 variants of concern with an established protocol using a KingFisher (ThermoFisher Scientific) with the MagMAX Viral/Pathogen extraction kit (ThermoFisher Scientific), and reverse transcriptase is performed to produce cDNA which is used for variant detection tests.
  • Target regions are selected based on previously published and evaluated primer targets (e.g., MLST genes) and are used to design rhPCR primers .
  • Primers are designed for selected targets. The primer design is guided by in silico testing to ensure efficient amplification in a multiplexed reaction. Evaluate the performance of the panel using a mock microbiome and spiked wastewater: Stocks of microorganisms are obtained from the CDC or other culture collections (e.g., Penn State, ATCC). Primer efficiency is assessed by rhPCR using dilutions of DNA extracted from each pathogen.
  • the primer panel is assessed on a mock microbiome comprised of all targets represented in equal concentrations to assess the performance of primers in a multiplexed reaction.
  • mock microbiomes are prepared using a leave-one-out approach to assess the specificity of primers.
  • microbiomes are prepared by inoculating individual target microorganisms in decreasing concentrations to estimate the method's limit of detection. This also allows for the assessment of primer amplification efficiency. The primer efficiency is measured by calculating the regression coefficient for a linear regression model describing the relationship between the target gene read count and the dilution of the strain carrying the target gene. Wastewater samples are also sequenced using shotgun metagenomic sequencing and results are compared with those obtained using rhPCR with the pathogen detection primer panel.
  • Identify diagnostic SNPs in genomes of Salmonella and E. coli A database is developed containing genomes of pathogens of interest (e.g., E. coli O157:H7). Alignments are performed to identify regions of greatest diversity among closely and distantly related organisms, with an emphasis on genes associated with disease potential including O antigens and virulence genes. Databases of all known E. coli and Salmonella O antigen diagnostic gene targets are publicly available ( Diagnostic single nucleotide polymorphisms (SNPs) will be identified and a large-scale MLST scheme will be developed targeting hundreds of regions per genome.
  • SNPs single nucleotide polymorphisms
  • the library is prepared for sequencing according to the protocol for the Oxford Nanopore Rapid Barcoding Kit. These barcode-specific adapters are attached to each of the samples run in order to identify them in the output data. After barcoding, the samples are pooled into one library, which was used for sequencing. The flow cell is properly primed, library added, and sequencing is run for 40 hours. Upon completion of sequencing, nanopore sequencing data is processed with EPI2ME using the Fastq Antimicrobial Resistance Workflow. The sequencing results demonstrated successful detection of AMR genes in the samples from 7,725 reads. Results are shown in Table 2. Table 2. Results of MinION real-time sequencing data analysis in EPI2ME demonstrating detectable genes using IDT’s rhPCR amplification protocol.
  • boot sock swabs are an acceptable sampling method, providing evidence and guidance for designing future studies evaluating the effect of feed additives on the microbiome of birds in production settings.
  • a study was carried out to longitudinally describe the microbial profile of birds fed two antibiotic-free feed additives. Briefly, day-old Cobb 500 male chicks were purchased at a local hatchery, transported to PERC and randomly allocated into cages of 10 birds each where they were grown for 21 days.
  • Cages were randomly allocated to receive a control diet (no additive), a diet supplemented with an essential oil blend, a probiotic at an inclusion of 3 x 10 5 CFU per gram of feed (Calsporin, QTI), or antibiotic at an inclusion of 50g/ton as a positive control (BMD, bacitracin methylene disalicylate, Zoetis).
  • Eight replicates (8 cages, 80 birds) per treatment were carried out, with a total of 320 birds. Fecal samples of each cage were collected by laying a sterile collection paper under the cage for one hour.
  • Baseline diet is fed and referred to as a negative control; a positive control diet is formulated with bacitracin methylene disalicylate (BMD) – Zoetis which is approved for prevention and control of necrotic enteritis in commercial poultry (50 grams/ton).
  • BMD bacitracin methylene disalicylate
  • Zoetis which is approved for prevention and control of necrotic enteritis in commercial poultry (50 grams/ton).
  • Samples are collected at baseline (1-day old chick data is gathered from chick paper that lines the boxes in which chicks are shipped from the hatchery to the grower farms, representing the baseline microbiome and resistome of each flock). In addition to chick paper, samples are collected every other week. Sampling is performed as described in Thompson et al. (2016) and sanitized boots are covered by a sterile moistened boot sock. Study personnel circumnavigate each pen and make multiple crosses over the center to collect a representative sample of the environmental mi- crobiome. Each pair of boot socks are stored in a plastic bag on ice until processing.
  • EXAMPLE 4 NANOPORE SEQUENCING OF ANTIMICROBIAL RESISTANT GENE TARGETS Materials and Methods Assay targets and primer design
  • the MEGARes 2.0 database Doster 2020 was chosen as it is currently the most comprehensive antimicrobial resistance gene (AMRg) database.
  • AMRg antimicrobial resistance gene
  • IDT Integrated DNA Technologies
  • primers were designed along the database sequences, accounting for target insert size and off-target effects. Primers were scored on in silico sensitivity and specificity, both individually and as a panel.
  • Additional quality thresholds dictated that primers were designed to have under 70% GC content and no more than one ambiguous base in a 25- base pair sliding window.
  • raw sequence reads were downloaded from SRA using SRR accession IDs. Reads were processed through the AMRPlusPlus Bioinformatic Pipeline (v2.0.2) (Doster 2020) using default parameters. In brief, raw reads were processed with Trimmomatic (Bolger 2014), removing low quality bases (Q score ⁇ 48) from 5’ and 3’ ends, and along a 4-base sliding window. Reads shorter than 36 base pairs were also removed. Host reads were filtered and removed using the reference Homo sapiens genome, GRCh38 (NCBI RefSeq; GCF_000001405.26).
  • the resultant count matrices from both studies were filtered to remove gene groups requiring SNP confirmation to be AMR-conferring.
  • the counts for all variants within a group were summed.
  • reads-per-million (RPM) was calculated using the gene counts and trimmed, host- decontaminated sample read counts.
  • RPM reads-per-million
  • genomic DNA was extracted from broth cultures and Campylobacter colonies using the MagMAX Microbiome Ultra (Applied Biosystems, CA, USA) extraction kit on the KingFisher Flex (Thermo Fisher Scientific, CA, USA) platform. DNA was quantified and diluted according to calculated genome equivalents such that, when pooling strain DNA to create mock microbiome pools, no strain would be overrepresented. Sample pools were then created according to aforementioned pool designs. For mock microbiome pools without spike-ins, DNA was pooled 1:1 by volume. For complex samples without spike-ins, no additional DNA was added. For mock microbiome and complex sample pools with spike-ins, spike-in strain DNA was serially diluted into the pools by volume.
  • rhAmpSeq PCR, library preparation, and sequencing rhAmpSeq PCR and library preparation was performed according to IDT’s “rhAmpSeq Library Preparation For Targeted Amplicon Sequencing” protocol using the rhAmpSeq Library Kit (Cat. No.10000066; Integrated DNA Technologies) and Agencourt AMPure XP purification beads for amplicon and library clean-up (Beckman Coulter, CA, USA).
  • the RPM threshold of 23 was then applied to create a presence-absence binary wherein AMRg with RPM ⁇ 23 were considered absent. AMRg above this threshold were considered present. For all samples, AMRg were denoted as true or false positives or negatives based on if genes were 1) detected based on the RPM threshold, 2) in the rhAMR primer panel used, and 3) expected in a sample’s AMRg profile. Sensitivity, specificity, and accuracy were calculated by primer panel, sample pool, and combinations thereof.
  • the final assay design included three panels (p1-3) covering 7,371 of the original 7,885 sequence accessions in MEGARes 2.0. Specifically, p1, p2, and p3 panels account for 6,196, 3,596, and 7 accessions each, covering 1,258, 335, and 5 AMRg groups, respectively. There is no AMRg target redundancy across panels; however, as some targets cover different lengths of same accession, some AMRg accessions and AMRg groups are covered in multiple panels.
  • rhAMR product sequence evaluation Forty samples (8.9%) failed sequencing. All were products from the smallest panel, p3, and thirty-seven of them were metagenomic pool variations. Ten additional p3 panel products, while they did not fail sequencing, had insufficient reads to be processed through the AMRPlusPlus Bioinformatic Pipeline. Of the original 447 samples, 397 were used for downstream analysis.
  • sequencing reads averaged 155,128 per sample, ranging from 2-2,552,250 reads (Table 4).
  • primer panel (p1-3) sequencing reads averaged 352,320, 57,531, and 548, respectively.
  • mock microbiome samples averaged 338,632 reads/sample
  • turkey-associated complex samples averaged 82,227 reads/sample
  • human- associated complex samples averaged 87,914 reads/sample (Table 4).
  • the single strain E. coli K12 control averaged 829,325 reads. Overall, 92.2% of raw reads, averaging 142,986 reads per sample, were successfully mapped to the MEGARes v2.0 database (Table 4).
  • rhAMR distinguishes mock microbiome communities with high specificity and accuracy rhAMR performance was assessed using sensitivity, specificity, and accuracy wherein gene detection was defined by an RPM greater than the calculated threshold of 23 RPM, and a gene had to be in both 1) the primer panel used and 2) in the pool’s aggregated whole-genome sequence AMRg profile to be considered expected. Based on these definitions of expected and detected, the overall false positive rate among mock microbiome samples was 7.7% while the overall false negative rate was 6.1%. Specific incidence of true and false positive and negatives by gene group within pool from panel 1 are available in Figure 17.
  • rhAMR accuracy ranged from 77.4-87.4%, specificity from 83.4-90.4%, and sensitivity from 59.7-85.5%.
  • Performance with p2 and p3 panels are detailed in Table 9.
  • sensitivity, specificity, and accuracy were 98.0%, 94.1%, 95.2%, respectively.
  • rhAMR allowed for differentiation of the subset mock microbiome pools MM2-MM5 ( Figure 11) with MM1 and MM5, the pools accounting for the most diverse strain subsets, being most central to all other pool clusters ( Figure 11A).
  • Mapped Reads Raw Reads Maps
  • Mapped Reads Min Mean Median Max Min Mean Median Max T6 2 80110 23968 634165 2 80049 23962.0 634099 T7 6 150630 13750 1287115 4 150030 13721.0 1286939 T8 2 53119 7934 447026 2 52877 7263.0 446983 Table 5.
  • FastQC a quality control tool for high throughput sequence data. (2010). Bolger, A. M., Lohse, M., Usadel, B. Trimmomatic: A flexible trimmer for Illumina Se- quence Data. Bioinformatics (2014). Shen, W., Le, S., Li, Y. & Hu, F. SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation. PLOS ONE 11, e0163962 (2016). Lakin, S. M. et al. MEGARes: an antimicrobial resistance database for high throughput sequencing. Database issue Published online 45, (2017). Dohoo, I. R., Martin, W., & Stryhn, H. E.
  • RNase H-dependent PCR (rhPCR): improved specificity and single nucleotide polymorphism detection using blocked cleavable primers.
  • Tan X Chung T, Chen Y, Macarisin D, LaBorde L, Kovac J.2019.
  • the occurrence of Listeria monocyto-genes is associated with built environment microbiota in three tree fruit processing facilities. Microbiome 7:115. Chung T, Weller DL, Kovac J.2020.
  • Appl Environ Microbiol 83 Miller RA, Jian J, Beno SM, Wiedmann M, Kovac J.2018. Intraclade Variability in Toxin Production and Cytotoxicity of Bacillus cereus Group Type Strains and Dairy-Associated Isolates.
  • Appl Environ Microbiol 84 Goodman LB, Lawton MR, Franklin-Guild RJ, Anderson RR, Schaan L, Thachil AJ, Wiedmann M, Miller CB, Alcaine SD, Kovac J.2017. Lactococcus petauri sp. nov., isolated from an abscess of a sugar glider. Int J Syst Evol Microbiol 67:4397–4404.
  • SeqKit A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipula-tion. PLOS ONE 11:e0163962. Mago ⁇ T, Salzberg SL.2011. FLASH: fast length adjustment of short reads to improve genome assem-blies. Bioinformatics 27:2957–2963. Dohoo I, Martin S, Stryhn H.2009. Veterinary Epidemiologic Research. undefined. Zaheer R, Noyes N, Ortega Polo R, Cook SR, Marinier E, Van Domselaar G, Belk KE, Morley PS, McAllis-ter TA.2018. Impact of sequencing depth on the characterization of the microbiome and resistome.1. Sci Rep 8:5890.
  • the antibiotic resistome gene flow in environments, animals and human beings. Frontiers of Medicine (2017) doi:10.1007/s11684-017-0531-x. Perry, J., Waglechner, N. & Wright, G. The prehistory of antibiotic resistance. Cold Spring Harb. Perspect. Med. (2016) doi:10.1101/cshperspect.a025197. Zou, C. et al. Haplotyping the Vitis collinear core genome with rhAmpSeq improves marker transferability in a diverse genus. Nat. Commun.11, (2020). Williams, M. S. et al. Targeted nanopore sequencing for the identification of ABCB1 promoter translocations in cancer. BMC Cancer 20, (2020). Eus Mein, P.
  • Antimicrobial Agents and Chemotherapy 64 (2020). McArthur, A. G. et al. The comprehensive antibiotic resistance database. Antimicrobial Agents and Chemotherapy 57, 3348–3357 (2013). Gupta, S. K. et al. ARG-annot, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrobial Agents and Chemotherapy 58, 212–220 (2014). Feldgarden, M. et al. Validating the AMRFINder tool and resistance gene database by using antimicrobial resistance genotype-phenotype correlations in a collection of isolates. Antimicrobial Agents and Chemotherapy 63, (2019). Zankari, E. et al.
  • Mohebodini H., Jazi, V., Ashayerizadeh, A., Toghyani, M. & Tellez-Isaias, G.
  • Productive parameters cecal microflora, nutrient digestibility, antioxidant status, and thigh muscle fatty acid profile in broiler chickens fed with Eucalyptus globulus essential oil.
  • Temporal genomic phylogeny reconstruction indicates a geospatial transmission path of Salmonella cerro in the United States and a clade-specific loss of hydrogen sulfide production.

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Abstract

Il est important de déterminer l'existence de gènes de résistance aux antimicrobiens (AMR) dans les micro-organismes du microbiome. De manière à permettre un traitement ciblé des personnes porteuses de ces micro-organismes et à mieux comprendre comment ils apparaissent et comment on peut les prévenir. La présente invention concerne des procédés et des compositions qui aident à la détection des AMR dans le microbiome qui peuvent être utilisés pour la prise de décision en matière de traitement dans des contextes cliniques.
PCT/US2024/053600 2023-10-30 2024-10-30 Procédés et compositions pour profilage de résistance antimicrobienne en temps réel Pending WO2025096569A1 (fr)

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WO2022067019A1 (fr) * 2020-09-26 2022-03-31 The Regents Of The University Of California Protocoles hybrides et schémas de codage à barres pour technologies de séquençage multiples
US20220136046A1 (en) * 2019-03-04 2022-05-05 St George's Hospital Medical School Detection and antibiotic resistance profiling of microorganisms
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US20090325169A1 (en) * 2008-04-30 2009-12-31 Integrated Dna Technologies, Inc. Rnase h-based assays utilizing modified rna monomers
US20180327806A1 (en) * 2015-11-04 2018-11-15 The Broad Institute, Inc. Multiplex high-resolution detection of micro-organism strains, related kits, diagnostics methods and screening assays
US20190218611A1 (en) * 2015-11-25 2019-07-18 Integrated Dna Technologies, Inc. Methods for variant detection
US20220145375A1 (en) * 2016-03-14 2022-05-12 The Translational Genomics Research Institute Methods and kits to identify klebsiella strains
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