WO2023128765A1 - Détermination de l'identité de la souche et de la résistance antimicrobienne dans des cultures de sang positives - Google Patents

Détermination de l'identité de la souche et de la résistance antimicrobienne dans des cultures de sang positives Download PDF

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Publication number
WO2023128765A1
WO2023128765A1 PCT/NL2022/050768 NL2022050768W WO2023128765A1 WO 2023128765 A1 WO2023128765 A1 WO 2023128765A1 NL 2022050768 W NL2022050768 W NL 2022050768W WO 2023128765 A1 WO2023128765 A1 WO 2023128765A1
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peptides
resistance
microorganism
proteins
lactamase
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PCT/NL2022/050768
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English (en)
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Wilhelmus Hubertus Franciscus GOESSENS
Theo Marten Luider
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Erasmus University Medical Center Rotterdam
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6848—Methods of protein analysis involving mass spectrometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/195—Assays involving biological materials from specific organisms or of a specific nature from bacteria

Definitions

  • the invention relates to a method for the combined assessment of taxonomic identity and antibiotic resistance of microorganisms.
  • the method relates to high-resolution MS measurement of peptides in a protein digest of a sample comprising microorganisms to provide the identity of the microorganism, combined with high-resolution MS measurement of peptides in the same protein digest originating from antibiotic resistance proteins.
  • the mass spectra acquired provide information on the presence of a drug resistance conferring protein, as well as on the taxonomic identity of the microorganism .
  • Resistant microorganisms such as bacteria and unicellular fungi, but also viruses, may complicate the treatments of infections in critically ill patients, especially in surgery, hemato-oncology and intensive care in general.
  • bacterial isolates have been encountered that have become resistant to “all or nearly all” available antibiotics, including carbapenems, which are typically reserved as the “treatment of last resort” against antibioticresistant bacteria.
  • multi-resistant microorganisms such as Enterobacteriaceae, Pseudomonas aeruginosa, Acinetobacter baumanii calcoaceticus complex, Staphylococcus aureus, Streptococcus pneumoniae, and Candida spp.
  • Enterobacteriaceae Pseudomonas aeruginosa
  • Acinetobacter baumanii calcoaceticus complex Staphylococcus aureus
  • Streptococcus pneumoniae Streptococcus pneumoniae
  • Candida spp. pose serious threats. It is therefore important to have a fast and accurate method to establish whether a microorganism is resistant to a particular antibiotic drug, this is especially the case for antibioticresistant bacteria.
  • a quick and accurate determination of the type of antibiotic to which a microorganism is resistant is vital for choosing a suitable antimicrobial therapy in treatment of infections.
  • aminoglycoside antibiotics primarily inhibitors of protein synthesis
  • resistance to aminoglycoside antibiotics often resides in the presence of efflux pumps, 16S rRNA methylases, or, in particular, in the presence of acquired aminoglycosidemodifying enzymes, including acetyltransferases, adenyltransferases, and phosphotransferases.
  • B-lactam antibiotic family inhibitors of cell wall synthesis, and including penicillins, cephalosporins, carbapenems, monobactams, and B-lactam inhibitors
  • B-lactam inhibitors are commonly, and most importantly, caused by the expression of B-lactamases.
  • the enzymes are subdivided into narrow-, moderate-, broad-, extended-spectrum beta lactamases (ESBLs) and carbapenemases. Mutations in the parent enzymes at critical amino acid sequences important for catalysis have given rise to over 140 currently known ESBL variants.
  • the bacterial cell wall peptidoglycan precursors are targets of glycopeptide antibiotics (vancomycins and teicoplanins). Biosynthesis of cell wall peptidoglycan requires a crosslinking of peptidyl moieties on adjacent glycan strands. While the D-alanine-D-alanine transpeptidase, which catalyzes this crosslinking, is the target of beta-lactam antibiotics, glycopeptides, in contrast, do not inhibit an enzyme, but bind directly to D- alanine-D-alanine substrate and prevent subsequent crosslinking by the transpeptidase. Clinical resistance to vancomycin in enterococcal pathogens has been traced to altered ligases producing D-alanine-D-lactate rather than D-alanine-D-alanine peptidyl moieties.
  • Antibiotic resistance can also be assessed by the use of mass spectrometry. Only a few of these prior art techniques allow detection of mutations in proteins that cause resistance, and even fewer are able to distinguish between different resistance-conferring proteins within a broad class of, for instance, beta-lactamases. In view of the fact that more than 900 different kinds of beta-lactamases are known, it is important to obtain information on the specific beta-lactamase(s) that is(are) present.
  • Mass spectrometry has also been used to identify microorganisms.
  • MALDI-TOF MS has been used to measure protein profiles of microorganism. Mass spectra are acquired and compared to a database of reference mass spectra of microorganisms. The advantage of such a system is the short time in which identifications can be made.
  • many of these identification methods use data on ribosomal proteins, and because resistance is usually not conferred by mutations in ribosomal proteins, there is no establishment of antibiotic resistance possible based on these data.
  • Automated matrix assisted laser desorption/ionization time-of-flight (MALDITOF) MS allow rapid microorganism identification based on distinct protein and peptide mass spectra.
  • MALDITOF Automated matrix assisted laser desorption/ionization time-of-flight
  • identification of microorganisms is performed by using MALDI TOF mass spectrometry, and the detection of (mechanisms of) resistance, or susceptibility to antibiotics, is performed by phenotypic assays such as VITEK® 2 (bioMerieux, Inc.) or BD PhoenixTM (Becton Dickinson Diagnostic Systems) systems. Using these methods, the determination of the susceptibility to various antibiotics may take as long as 18 hours.
  • IRIDICA BAG BSI assay Ibis Biosciences, Abbott Company, Carlsbad, CA; Metzgar, et al., 2016, PLoS ONE 11(7): eO 158186
  • ESI-MS electrospray ionization-MS
  • the system requires extracting DNA from whole blood and amplifying conserved DNA sequences of bacterial or fungal genes, as well as DNA markers for antibiotic resistance genes (e.g., mecA, vanA, vanB, and blaKPC markers).
  • MinlON nanopore sequencing assay (Oxford Nanopore Technologies, Oxford, UK; Tyler et al., 2018, Scientific Reports 8:10931) which generates DNA sequence data from isolated DNA for rapid bacterial identification as well as antibiotic resistance testing. While bacterial species information may be available within as little as 1 h, a complete drug resistance profile may take 12 h, in addition to the DNA extraction and library preparation, which takes up to 5 h prior to sequencing.
  • the present invention now provides a method that allows the combined, that is, essentially simultaneous, detection of protein fragments for bacterial identification as well as detection of pre-defined peptides of antibiotic resistance proteins in a very short time-span.
  • the presently proposed method allows for the combined detection of identity-specific proteins as well as antibiotic resistance-conferring proteins, to thereby facilitate combined determination of taxonomic identity and antibiotic resistance of microorganisms.
  • the present inventors have realized that both the detection of peptides originating from proteins of which the amino acid sequence is unique to a specific taxonomic group of microorganisms (i.e., taxon-specific proteins), as well as the detection of peptides originating from proteins that confer antibiotic resistance, may occur in a single operational run on a mass spectrometer.
  • the method is performed while using a single high resolution mass spectrometry technique, in different data acquisition modes.
  • the method is preferably performed on a sample of a positive blood culture, in which the microorganisms are lysed to provide a crude cell lysate, and digesting the proteins in said crude cell lysate with an endoprotease.
  • the present invention now provides a method for the combined taxonomic identification and determination of antibiotic resistance of a microorganism, proteins of which are present in a test sample, by subjecting the sample to an endoprotease to provide a mixture of peptides, and analyzing the mixture of peptides by high-resolution mass spectrometry using a single high resolution mass spectrometry technique in two separate data acquisition modes that are performed subsequently or in alternation during a single operational run, wherein said data acquisition modes include Data Dependent Acquisition (DDA) mode and Parallel Reaction Monitoring (PRM) mode, and wherein peptides originating from taxonspecific proteins are detected in DDA mode, and wherein peptides originating from proteins that confer antibiotic resistance are detected in PRM mode.
  • DDA mode is used in the first 2-3 minutes of the run, while PRM mode is used in the later part of the measurement run.
  • time during a run not spend in PRM mode is spend in DDA mode.
  • the method comprises a step of digesting a sample comprising proteins of a microorganism with an endoprotease to provide a mixture of peptides as a protein digest, separating the peptides in said mixture by chromatography, preferably liquid chromatography (LC), and acquiring at least a first and second mass spectrum of peptides thus separated by tandem mass spectrometry (MS/MS) at high resolution (preferably at a resolution of 1-10 ppm, more preferably ⁇ 5 ppm), wherein consecutively or alternating in a single operational run, said mass spectra are acquired in DDA mode and in PRM mode.
  • chromatography preferably liquid chromatography (LC)
  • MS/MS tandem mass spectrometry
  • the part of the run wherein the peptides are analysed in DDA mode provides information on peptides (as fragments of proteins) that indicate the presence of a microorganism of a specific taxon.
  • DDA mode shotgun MS proteomic data are acquired, wherein as many peptides as possible are analysed in a short time span of about 1-5, preferably 2-4, preferably about 3 minutes, during a run, with bias towards detecting the peptides that are most abundant in the sample.
  • the mass spectra obtained in DDA mode are used to identify peptides, and the peptides identified are compared to a database of peptides annotated to taxa (such as the UniProt sequence repository) using a software tool (such as Unipept, MetaProteomeAnalyzer (MPA), or ProteoClade) or tailor-made databases.
  • a tailor-made database may for instance be specifically compiled of data for the most common microorganisms that cause blood-stream infections, and such data may include taxon-specific peptide sequences from whole-cell protein digests (proteome data) for, for instance, microorganisms including, but not limited to coagulase-negative staphylococci (including S'. epidermidis, S.
  • the part of the run wherein the peptides are analysed in PRM mode provides information on peptides (as fragments of proteins) that indicate the presence of antibiotic-resistance- conferring proteins.
  • the PRM mode is a targeted workflow performed in a high resolution and high mass accuracy mode on a mass spectrometer, wherein only selected peptides that are surrogates of proteins of interest are measured in a predefined m/z ranges and retention time window during a run.
  • the mass spectra obtained in PRM mode are used to determine the presence or absence of selected, i.e. targeted, peptides originating from antibiotic resistance-conferring proteins.
  • selected, i.e. targeted, peptides originating from antibiotic resistance-conferring proteins One who is skilled in the art will be able to compile a database of selected peptides which must be targeted in PRM mode in order to determine the presence of antibiotic resistanceconferring proteins, preferably from microorganisms that cause infectious disease, including blood infections and urinary tract infection, preferably blood stream infections.
  • Peptides identified in PRM mode may be compared to a database of peptides annotated to antibiotic-resistance-conferring proteins using a software tool.
  • each precursor will require about 30ms for analysis, resulting in a cycle time of about 1 second, and a total scheduled time for PRM of about 1-2 minutes.
  • DDA identification
  • PRM detection of resistance mechanisms
  • DDA measurement is preferably performed during the first 3-minute gradient (x- axis scheduled time 0-3 min), whereas PRM measurement is preferably performed during the remaining 8,5 minutes (x-axis scheduled time 3-11.5 min) (See Figure 1).
  • the information on the peptides as retrieved in both MS modes is preferably used to predict the amino acid sequence of the peptides, and this sequence information may be compared to sequences of proteins in public available or tailor-made databases with known taxonomic annotation and/or known antibiotic-resistance annotation.
  • the information on the peptides as retrieved in both MS modes is preferably used to determine the amino acid sequence of the peptides present in the endoprotease digest of the sample.
  • taxon annotation of preferably as many peptides as possible is achieved in order to increase the reliability of the method.
  • the data acquisition in DDA mode is preferably as short as a 3 minutes LC gradient. It may be as short as 10 seconds.
  • the DDA mode of data acquisition is chosen at any time window that is not used for PRM mode.
  • the DDA mode may be selected to retrieve peptide information for identification before the targeted analysis of the next peptide in PRM mode starts. In this way, machine time is optimally used, and all data can be generated in a very short analysis window of about 10 minutes. It was further found that the PRM data was not compromised by the combined DDA-PRM approach.
  • the present invention now provides a multiplex LC- MS/MS assay able to identify the bacterial species and detect the most important resistance mechanisms with 100% sensitivity and specificity, which correlates very well with phenotypic AST results (SensititreTM, ThermoFisher Scientific).
  • the multiplex LC-MS/MS assay using the methods of the present invention allows for the possibility that more than 25 peptides are measured in the same run, preferably using methods of the present invention up to one hundred peptides are determined in a single run.
  • the peptides to be analysed are about 10-20 amino acids in length, more preferably about 1-12 amino acids.
  • information on the peptides as retrieved in both MS modes is retrieved from a sample comprising proteins of a microorganism, for instance a blood culture, preferably a subsample of a positive blood culture.
  • the sample comprising proteins of a microorganism may also be a urine sample, or a blood sample, or other sample as provided herein.
  • the present invention is an improvement over the prior art methods as described above, as it provides results within 6 hours, preferably within 5, or 4 hours, following the provision of the sample comprising proteins of a microorganism, e.g., a subsample of a positive blood culture.
  • the present invention solves the problem of providing much faster diagnostic results for answering the question which microorganism is present in a clinical sample, and which antibiotic resistance mechanism(s) are present in these particular organisms, thereby providing near- simultaneous taxonomic identification and resistance detection.
  • completion of identification and characterization of mechanisms of resistance may take as little as 4 hours. This allows for reporting of this critical information to the treating physician on the same day, in particular the same office day, which is one day earlier in comparison to the prior art methods.
  • methods of the present invention are significantly faster.
  • methods of the present invention allow for almost complete automation, as they are performed on a single mass spectrometer that can be linked to the blood culture process procedure.
  • Methods of the invention for rapid identification and determination of antimicrobial resistance (AMR) of microbial pathogens in blood from patients with bloodstream infections may be performed on (sub)samples of positive blood cultures.
  • AMR antimicrobial resistance
  • the methods of the present invention may, in one embodiment, comprise a method wherein a sample comprising proteins of a microorganism, such as a subsample of a positive blood culture or a positive blood sample, is digested by an endoprotease, and the resulting peptides are analysed by high-resolution MS in DDA mode to provide the identity of the microorganism, and specific peptides deriving from antibiotic resistance proteins are detected based on their specific retention time in PRM mode, wherein both analyses are performed during a single run, whereby preferably DDA mode is selected to identify the bacteria early in the run, and the remainder of the run is preferably performed in PRM mode to identify the antimicrobial resistance (AMR) profile, preferably using an public existing or tailor made data base to improve the accuracy or reliability of the AMR profile.
  • AMR antimicrobial resistance
  • the present invention now provides a method for the combined taxonomic identification and determination of antimicrobial drug resistance of a microorganism, proteins of which are present in a sample, the method comprising subjecting a sample comprising proteins of a microorganism to an endoprotease to provide a mixture of peptides from said proteins, and analyzing the mixture of peptides by high-resolution mass spectrometry using a single high resolution mass spectrometry technique in two separate data acquisition modes, wherein said modes consist of DDA and PRM, and wherein said two separate data acquisition modes are performed subsequently or in parallel in a single mass spectrometric analysis run.
  • the single mass spectrometric analysis run is a single LC-MS/MS run.
  • a total of 25-100 peptides are monitored in parallel in a single run in PRM mode.
  • PRM mode peptides are identified and compared to a database comprising pre-identified peptides annotated to antimicrobial drug resistanceconferring proteins that indicate specific resistance genes or mutations in genes that are linked to antimicrobial drug resistance.
  • peptides are identified and compared to a database comprising pre-identified peptides annotated to microorganisms of known taxonomic identity.
  • the taxonomic identity is defined at species level, more preferably at strain level.
  • high resolution mass spectrometry technique involves an Orbitrap mass spectrometer, preferably a quadrupole-Orbitrap (q-OT).
  • Orbitrap mass spectrometer preferably a quadrupole-Orbitrap (q-OT).
  • the DDA mode comprises the presence of an existing public database or a tailor-made database.
  • the PRM mode comprises the knowledge of those peptides that overlap within a group of proteins that is associated with antibiotic resistance. Peptides can be chosen in such a way that they are easily detectable in a high-resolution MS. In addition, these peptides can be synthesized with stable isotopes to help in quantitation and reliable identification.
  • the method is completed within 5 hours, more preferably 4 hours, more preferably using automation, following the provision of the sample comprising proteins of a microorganism.
  • Figure 1 is a schematic presentation of the time at which during an LC-MS/MS run in PRM mode, the mass spectrometer is actually occupied with monitoring the various peptide targets (precursors) in a 1-minute and a 2 -minute analysis window. This means that in the remaining time during the same operational run, the mass spectrometer can be used in DDA mode in order to dynamically retrieve peptide data of as many peptides as possible.
  • Figure 2 shows a screenshot of a database sequence similarity search performed in Example 2, which shows that sequence similarity with the peptides identified during DDA mode analysis of isolate nr. 5 identify this microorganism as the taxon Escherichia coli. It is also shown that in the first 3 -minute gradient, sufficient data can be obtained in DDA mode to allow such identification.
  • Figure 3 is an exemplary picture of a clustering of peptide data for E. coli and K. pneumoniae based on DDA analysis, and shows that the DDA analysis provides for sufficient discrimination between the two taxa.
  • Figure 4 shows a screenshot of a the PRM analysis result wherein 13 samples are tested for 7 selected peptides unique to antibiotic-resistance conferring proteins and present in tryptic digests of the crude cell lysate of the test samples as described in Examples 1 and 2.
  • Figure 5 provides the same data as Table 1.
  • Figure 6 provides the same data as Table 2.
  • microorganism refers to bacterium, yeast, fungus, intra- or extracellular parasite, and/or virus and in particular to pathogenic microorganism. In preferred aspects of the present invention, the term refers to pathogenic or opportunistic bacteria. These include both Gram -positive and Gram-negative bacteria and Mycobacteria.
  • Gram-negative bacteria By way of Gram-negative bacteria, mention may be made of bacteria of the following non-limiting list of genera: Pseudomonas, Escherichia, Salmonella, Shigella, Enterobacter , Klebsiella, Serratia, Proteus, Campylobacter, Haemophilus, Morganella, Vibrio, Yersinia, Acinetobacter, Branhamella, Neisseria, Burklwlderia, 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 non-limiting list of 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 non-limiting list of genera: Candida, Cryptococcus, Saccharomyces and Trichosporon.
  • parasites of the following non-limiting list of genera: ectoparasites, endoparasites, intercellular parasites, protozoa, mesoparasite, social parasites, plasmodium, entamoeba, giardia, toxoplasma, pinworm, schistosoma, strongyloides stercolasis, guinea worm, hookworm, tapeworm, sarcoptes scabiei, pediculus humanuss capitis, phtrirus pubis, ticks.
  • genera ectoparasites, endoparasites, intercellular parasites, protozoa, mesoparasite, social parasites, plasmodium, entamoeba, giardia, toxoplasma, pinworm, schistosoma, strongyloides stercolasis, guinea worm, hookworm, tapeworm, sarcoptes scabiei, ped
  • virus when virus is mentioned we mean as a non-limiting list of genera: dsDNA viruses, ssDNA viruses, dsRNA viruses, (+)ssRNA viruses, (-)ssRNA viruses, ssRNA-RT viruses, dsDNA-RT viruses, such as for example polyomavirus, adenovirus, mosaic virus, hepadnavirus, geminivirus, arenavirus, circovirus, retrovirus, metavirus, pseudovirus, caulimovirus, herpesvirus, poxvirus, parvovirus, reovirus, picornavirus, togavirus, orthomyxovirus, rhabdovirus.
  • the genus Mycobacterium consists of a variety of species including species of the M.
  • tuberculosis complex species of the M. avium complex, M. gordonae, M. kansasii, M. simiae, M. leprea, M. bovis, M. smegmatis, M. chelonea, M. fortuitum, and M. abscessus.
  • taxonomic identity and “taxonomic identification” refer to the identification of a microorganisms based on its classification in a biological hierarchical taxonomic system, which system classifies groups of biological organisms based on shared characteristics. Organisms are grouped into taxa (singular: taxon) and these groups are given a taxonomic rank; groups of a given rank can be aggregated to form a more inclusive group of higher rank, thus creating a taxonomic hierarchy. Taxonomic identification in the context of the present invention refers to an approximation of the microorganisms closest or most likely taxonomic position, as based on proteome data.
  • This closest position may be at the level of a genus, preferably a species, and may, in instances where sufficiently discriminatory proteome data are available, be at the level of a subspecies or strain.
  • the determination of the taxonomic identity of a microorganism refers to its taxonomic identification essentially using methods as described herein.
  • an antimicrobial drug refers to any kind of drug that is directed to decrease 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 or complete inhibition of the microorganism.
  • an antimicrobial drug is further intended to include an antibacterial, antiviral, antifungal or antip arasitic drug.
  • antibiotic drugs include penicillins, protease inhibitors, nucleoside analogues, imidazoles, benzoic acids, cephalosporins, aminoglycosides, sulfonamides, macrolides, polymyxins, tetracyclines, lincosamides, quinolones, chloramphenicol, glycopeptides, metronidazole, rifamycins, lipiarmycins, isoniazid, ethambutol, pyrazinamide, spectinomycin, folate inhibitors, sulfamethoxazole, cyclic lipopeptides, glycylcyclines, oxazolidinones, lipiarmycins, myxopyronins and others.
  • Beta-lactam antibiotic is used to designate compounds with antibiotic properties containing a beta-lactam functionality.
  • a betalactam ring (B-lactam) is a cyclic amide comprising a heteroatomic ring structure, consisting of three carbon atoms and one nitrogen atom.
  • Non limiting examples of beta-lactam antibiotics useful in aspects of the invention include penicillins, cephalosporins, cephamycins, penems, carbapenems, and monobactams. Beta-lactam antibiotics are effective (in the absence of resistance) against a wide range of bacterial infections.
  • the term “beta-lactam antibiotic” as used herein is considered to include any antibiotic undergoing mass or structural changes upon inactivation by an antibiotic resistant microorganism, provided said mass or structural change can be detected by mass spectrometry.
  • antiviral drug refers to a class of drugs used specifically for treating viral infections and may include virucides.
  • a virucide is an agent (physical or chemical) that deactivates or destroys viruses.
  • Antiviral drugs may also inhibit the development and/or production of the virus.
  • Non-limiting examples of classes of antiviral drugs are viral entry inhibitors, viral uncoating inhibitors, viral transcription inhibitors, viral integrase inhibitors, viral protease inhibitors, and/or inhibitors of the viral release phase.
  • Non-limiting examples of specific antiviral drugs are zanamivir, oseltamivir, rifampicin, phosphorothioate antisense drug, acyclovir, zidovudine (AZT), lamivudine, saquinavir, ritonavir, indinavir, nelfinavir, amprenavir, boceprevir, telaprevir, tenofovir, adefovir, efavirenz, nevirapine, delavirdine, etravidine, rilpivirine, amantadine, rimantadine, or pleconaril.
  • antifungal drug refers to a class of drugs used to treat fungal infections and/or to pharmaceutical fungicides.
  • Fungal infection are for example but not limited to mycoses, candidiasis, athletes’ food, Dermatophytosis (ringworm), cryptococcal meningitis.
  • Non-limiting examples of classes of antifungal drugs are polyene antifungals, azole antifungals (imidazole, triazole, thiazole), allylamines, or echinocan dins.
  • Non-limiting examples of specific antifungal drugs are Amphotericin B, Candicidin, Filipin, Hamycin, Natamycin, Nystatin, Rimocidin, Bifonazole, Butoconazole, Clotrimazole, Econazole, Fenticonazole, Isoconazole, Ketoconazole, Miconazole, Omoconazole, Oxiconazole, Sertaconazole, Sulconazole, Tioconazole, Albaconazole, Fluconazole, Isavuconazole, Itraconazole, Posaconazole, Ravuconazole, Terconazole, Voriconazole, Abafungin, Amorolfin, Butenafine, Naftifine, Terbinafine, Anidulafungin, Caspofungin, Micafungin, Benzoic acid, Ciclopirox, Flucytosine, Griseofulvin, Haloprogin, Polygodial, Tolnaftate, Und
  • antip ar asitic drug is used for a class of drugs which are indicated for the treatment of parasitic diseases such as nematodes, cestodes, trematodes, infectious protozoa, and amoebas.
  • parasitic diseases such as nematodes, cestodes, trematodes, infectious protozoa, and amoebas.
  • classes of antiparasitic drugs are antinematodes, anticestodes, antitrematodes, antiamoebics, antiprotozoals.
  • Non-limiting examples of specific antiparasitic drugs are mebendazole, pyrantel pamoate, thiabendazole, diethylcarbamazine, ivermectin, niclosamide, praziquantel, albendazole, praziquantel, rifampin, amphotericin B, melarsoprol, eflornithine metronidazole, tinidazole, miltefosine.
  • 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 a certain antimicrobial drug, which concentrations can be attained with normal therapeutic dosage regimes in humans.
  • a resistant strain of a microorganism refers to a strain or (clinical) isolate of a species of a microorganism that does not exhibit decreased viability or inhibited growth or reproduction when exposed to a certain antimicrobial drug, and which antimicrobial drug is known to decrease viability or inhibit the growth or reproduction of susceptible strains of that species. It implies that an infection caused by this resistant strain may not successfully be treated with the antimicrobial drug for which the strain shows resistance.
  • resistance conferring protein refers to any protein that renders a microorganism resistant to an antimicrobial drug.
  • a resistance conferring protein may inactivate or degrade antimicrobial compounds (e.g. beta-lactamase, aminoglycoside modifying proteins), may be an efflux pumps or other changes in the cell wall (e.g. porin alterations) that changes the permeability of the cell wall of the organism, or may be a mutation in target protein of the drug (e.g. ribosomal proteins or penicillin binding proteins (PBPs), reverse transcriptase, and/or protease), a protein that enables bypassing of a metabolic pathway may be a protein that protects the target site (e.g.
  • quinolone resistance may be a target site-modifying protein. It should be understood that the list above is not exhaustive, any kind of drug resistance due to a protein may be detected by the present invention.
  • the term “determination of antimicrobial drug resistance”, as used herein, refers to determination of presence (or absence) of a resistance conferring protein produced by, or present in the proteome of, a (resistant) strain of a microorganism, based on proteome data. This proteotype is an approximation or prediction of the actual phenotype of antimicrobial drug resistance, which phenotype is best determined by cultivation and observing absence or reduced effect of the antimicrobial drug on inhibition of growth or reproduction.
  • mass spectrum refers to a plot having molecular mass or a function thereof (e. g., mass-to-charge ratio (m/z), ion mass, etc.) as the independent variable.
  • the dependent variable is typically a quantitative measure, such as abundance, relative abundance, intensity, concentration, number of ions, number of molecules, number of atoms, counts/millivolt, counts, etc.
  • a mass spectrum typically presents mass-to-charge ratio (m/z) as the independent variable, where m is the mass of the ion species and z is the charge of the ion species, and the dependent variable is most commonly an abundance of each molecular ion and/or its fragment ions.
  • ion means an atom or a group of atoms that has acquired a net electric charge by gaining or losing one or more electrons or gaining or losing one or more protons.
  • An ion can be formed in numerous manners, including by breaking up a molecule of a gas under the action of an electric current, of ultraviolet and certain other rays, and/or of high temperatures.
  • DDA Data Dependent Acquisition
  • MSI tandem mass spectrometry
  • MS2 tandem mass spectrometry
  • a peptide ion is selected for fragmentation from many ions available in the MS 1 data based on its detection intensity in precursor ion scans, and a subsequent MS analysis of the peptide fragments collects the MS/MS spectra for as many peptides as possible.
  • the peptides may then be identified against a proteomics database.
  • DDA can be performed on commercially available mass spectrometers, including ion traps, Q-TOFs, IMS-TOF MS, Orbitraps, FT-MS, LC-MS/MS.
  • the instrument scans all ions but then chooses a subset of those, typically the most abundant ones (MSI spectra), as precursor ions for further fragmentation usually by Collision- Induced Dissociation (CID).
  • the fragmented ions obtained are then acquired to generate MS/MS data (MS2 spectra), which is used to identify peptides by reconstructing the peptide’s amino acid sequence by database searching.
  • MS/MS data MS/MS data
  • DDA selects the most abundant precursor ions for MS/MS analysis. It takes the selection of peptide signals forward for fragmentation and matches them to a predefined database. The method allows for minimal selection of redundant peptide precursors.
  • DDA may include reference to data-independent acquisition (DIA) mode, but preferably the present invention does not include DIA mode for monitoring taxon-specific peptides.
  • DIA data-independent acquisition
  • PRM Parallel Reaction Monitoring
  • HCD collisional dissociation
  • MS/MS spectra MS/MS spectra to be acquired in the Orbitrap analyzer with high mass accuracy and high resolution.
  • HCD is a beam -type collisional dissociation similar to the dissociation achieved in QQQ as well as QTOF mass spectrometers.
  • An advantage of using q-OT is that both the discovery and targeted experiments can be performed on the same instrument, and it is convenient to transfer instrumental parameters such as collision energy, retention time, quadrupole isolation window, etc..
  • PRM is the suitable for an attomole-level detection and quantification of multiple proteins in a complex sample.
  • Orbitrap high-resolution mass spectrometers may be preferred in some embodiments of this invention, also high-resolution mass spectrometers other than Orbitraps may be utilized.
  • sample refers to a substance that contains or is suspected of containing an analyte, such as a microorganism or drug resistance conferring protein 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, body fluid, biopsy sample, or fraction thereof.
  • a sample useful in a method of the invention can be any material that is suspected to contain drug resistance conferring proteins.
  • 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.
  • a microorganism sample may be a lysate of the microorganism, or a cell lysate. It may also comprise a crude lysate of cells or a patient specimen.
  • lysate refers to suspensions or fractions thereof, obtained by disruption or lysing of cells and/or other microorganisms such as viruses.
  • the crude lysate contains all proteins, glycoproteins, polysaccharides, lipids, and nucleic acids.
  • the lysate in aspects of the present invention may comprise whole cells or particles, but will essentially consist of parts of cells or particles or any fraction or mixtures thereof obtained after a lysis step.
  • Lysate solutions can include, without limitation, a solution of lysed cells and/or particles that is treated such that selected molecules are removed or rendered inactive. It follows that this solution remains substantially “crude” with respect to most purified constituents.
  • a cell lysate can be a solution of lysed cells that is treated with an agent that inactivates or removes polymerase inhibitors.
  • a cell lysate can be a solution of lysed cells that is treated with an anti-coagulant. Any method can be used to lyse microorganisms in a sample. For example, osmotic shock, sonication, heating, physical disruption, microwave treatment, and enzymatic and/or alkaline lysis are methods that can be used to lyse microorganisms.
  • quantifying refers to any method for obtaining a quantitative or semi- quantitative measure.
  • quantifying a microorganism can include determining its abundance, relative abundance, intensity, concentration, optical density and/or count, using for instance stable isotope labels or recombinant proteins as a reference.
  • Quantifying an antimicrobial drug resistance conferring protein may encompass determining its expression level, its relative expression level to household proteins, and/or its concentration.
  • the present invention provides a fast and reliable diagnosis for antibiotic drug-resistance in microorganisms. It applies mass spectrometry to identify a resistance conferring protein in the microorganism sample.
  • a well-known resistance conferring protein is e.g., beta-lactamase that degrades or traps a beta-lactam such as penicillin, or aminoglycoside modifying proteins.
  • a particular drug resistance is a resistance against an antibiotic, and especially resistance conferred by the so-called extended spectrum beta lactamases (ESBLs).
  • carbapenems such as for example ceftazidime, cefotaxime, ceftriaxone, cefpodoxime, aztreonam, imipenem, meropenem and ertapenem.
  • Clavulanic acid is a known inhibitor of betalactamases. Some beta lactamases are more sensitive to clavulanic acid then others. Such information is important for the diagnoses and for the subsequent treatment plan.
  • the resistance conferring protein may also be a mutation of a protein normally inhibited by the drug, such as gyrases, reverse transcriptase and/or proteases. The mutation overcomes the inhibition by the drug.
  • the resistance conferring protein may also be a mutation in proteins affecting the activity of efflux pumps and/or content of proteins such that the permeability of the cell membrane is altered.
  • the microorganism may be a bacterium, fungus, virus, or parasite.
  • the microorganism is a bacterium or a virus, more preferably a bacterium.
  • the microorganism is a fungus.
  • the microorganism is a virus.
  • the microorganism is a fungus, or a parasite.
  • the bacterium may be Gram-positive or Gram- negative or acid-fast bacteria (mycobacteria) and is preferably selected from the group consisting of actinobacteria, firmicutes, tenericutes, aquificae, Deinoccos, fibrobacteres, chlorobi, bacteriodetes, fusobacteria, gemmatimonadetes, nitrospireae, planctomycetes, verrumicrobia, chlamydiae, protobacteria, spirochaetes, synergistetes, acidobacteria, chloroflexi, chrysiogenetes, cyanobacteria, deferribacteres, dictyoglomi, thermodesyslfobacteria, and thermotogae.
  • actinobacteria firmicutes, tenericutes, aquificae, Deinoccos, fibrobacteres, chlorobi, bacteriodetes, fusobacteria, gem
  • the microorganism is a pathogenic bacterium, preferably selected from the group consisting of Bordetella, Borrelia, Brucella, Campylobacter, Chlamydia, Chlamydophila, Citrobacter, Clostridium, Corynebacterium, Enterobacter, Enterococcus, Escherichia, Francisella, Haemophilus, Helicobacter, Klebsiella, Legionella, Leptospira, Listeria, Morganella, Mycobactera, Mycoplasma, Neisseria, Proteus, Pseudomonas, Rickettsia, Salmonella, Serratia, Shigella, Staphylococcus, Streptococcus, Treponema, Vibrio, and Yersinia.
  • the microorganism is selected from the group consisting of Bordetella pertussis, Borrelia burgdorferi, Brucella abortus, Brucella canis, Brucella melitensis, Brucella suis, Campylobacter coli, Campylobacter jejuni, Chlamydia pneumoniae, Chlamydia traclwmatis, Chlamydophila psittaci, Citrobacter freundii, Citrobacter koseri, Clostridium botulinum, Clostridium difficile, Clostridium perfringens, Clostridium tetani, Corynebacterium diphtheriae, Enterobacter cloacae, Enterococcus faecalis, Enterococcus faecium, Escherichia coli, Francisella tularensis, Haemophilus influenzae, Haemophil
  • avium complex M. gordonae, M. kansasii, M. simiae, M. leprea, M. bovis, M. smegmatis, M. chelonea, M. fortuitum, M.
  • the microorganism is a fungus.
  • the fungus may be selected from the group consisting of Blastocladiomycota, Chytridiomycota, Glomeromycota, Microsporidia, Neocallimastigomycota, Dikarya (inc.
  • Deuteromycota Deuteromycota
  • Ascomycota Pezizomycotina
  • Saccharomycotina Taphrinomycotina
  • Basidiomycota Agaricomycotina
  • Pucciniomycotina Ustilaginomycotina
  • Subphyla incertae sedis Entomophthoromycotina, Kickxellomycotina, Mucoromycotina, and Zoopagomycotina.
  • the microorganism is a pathogenic fungus, preferably selected from the group consisting of Candida, Aspergillus, Cryptococcus, Histoplasma, Pneumocystis, and Tachybotrys.
  • the microorganism is selected from the group consisting of Candida albicans, Candida glabrata, Candida rugosa, Candida parapsilosis, Candida tropicalis, Candida dubliniensis, Aspergillus fumigatus, Aspergillus flavus, Aspergillus clavatus, Cryptococcus neoformans, Cryptococcus gatti, Histoplasma capsulatum, Pneumocystis jirovecii and Tachybotrys chartarum.
  • the microorganism is a parasite.
  • the parasite may be selected from the group consisting of Flagellates (e.g., Giardia lamblid), Amoeboids (e.g., Entamoeba histolytica), Sporozoans (e.g., Plasmodium knowlesi), Apicomplexa, Myxozoa, Microsporidia, Ciliates (e.g., Balantidium coli), Subphylum Sarcomastigophora, Superclass Mastigophora (includes flagellates), Superclass Sarcodina, Superclass Opalinata, Subphylum Sporozoa (includes apicomplexans), Subphylum Cnidospora , Class Myxosporidea, Class Microsporidea, and Subphylum Ciliophora (includes ciliates).
  • Flagellates e.g., Giardia lamblid
  • Amoeboids e.g., Entamoeba histolytica
  • the microorganism is a pathogenic parasite, preferably a protozoan, preferably selected from the group consisting of Amoebozoa, Excavata, and Chromalveolata.
  • the microorganism is selected from the group consisting of Entamoeba histolytica, Plasmodium (some of which cause malaria), and Giardia lamblia, Trypanosoma brucei, transmitted by the tsetse fly and the cause of African sleeping sickness.
  • the microorganism is a virus.
  • the virus may be selected from the group consisting of Adenoviruses, Herpesviruses, Poxviruses, Parvoviruses, Reoviruses, Picornaviruses, Togaviruses, Orthomyxoviruses, Rhabdoviruses, Retroviruses, and Hepadnaviruses.
  • the microorganism is a pathogenic virus preferably selected from the group consisting of HSV-1, HSV-2, Varicella zoster virus, EBV, CMV, smallpox virus, vaccinia virus, cowpox virus, human adenovirus, adenoassociated virus, erythrovirus, rotavirus, enterovirus, rhinovirus, Hepatitis A virus, Hepatitis B virus, Hepatitis C virus, rubella virus, flaviviruses, influenzavirus, lyssavirus, dengue virus, and HIV.
  • HSV-1 HSV-2
  • Varicella zoster virus EBV
  • CMV smallpox virus
  • vaccinia virus cowpox virus
  • human adenovirus adenoassociated virus
  • erythrovirus rotavirus
  • enterovirus enterovirus
  • rhinovirus Hepatitis A virus
  • Hepatitis B virus Hepatitis C virus
  • rubella virus rubella virus
  • flaviviruses influenzavirus
  • a suitable sample may be a body fluid or body tissue sample of a subject, i.e., a human, or animal subject, suspected of carrying a microorganism of which the drug resistance is to be characterized.
  • Suitable body fluid samples or clinical specimens may be blood, stool, sputa, feces, aspirates or urine sample.
  • the sample may be a culture of a microorganism. Such cultures are preferably pure cultures, but do not need to be pure cultures necessarily. Alternatively, also fractions of culture media or direct clinical materials can be a source of the sample.
  • microorganism sample is a lysate of the microorganism, or a cell lysate.
  • the microorganism is lysed to release the content of the organism.
  • lysis agents are selected from the group comprising lytic enzymes such as lysozyme, lysins, lysostaphin, zymolase, cellulase, mutanolysin, glycanases, proteases, mannase, detergents such as CHAPS, triton X and SDS, beads such as glass, ceramic or steel beads.
  • lysis may be accomplished by sonication by e.g. ultrasound, cell bomb method by e.g. high pressure, cryopulverisation, and high shear mechanical methods such as rotor-stator disruptors, valve-type processors, fixed-geometry processors and fixed orifice and constant pressure processors.
  • the microorganism sample is enriched in drug resistance conferring proteins.
  • Suitable methods of enrichment comprise, purification of proteins by column chromatography, beads or column with antibodies recognizing resistance conferring proteins. Multiplex purification methods, i.e., enriching for more than one protein, is expressly envisioned for the present invention.
  • the digesting step provides a mix of peptides that are suitable for high resolution MS. Different mutations results in different peptides upon digestion, thereby differentiating between mutations in the same protein. Each protein will also render specific peptides upon digestion.
  • Suitable proteases for the present invention and/or embodiments thereof are endoproteases, preferably endoproteases that cleave at a specific or known site of the protein. For the purpose of the present invention with specific or known cleaving site is meant that the protease will cleave at a predetermined location, preferably a location which is known.
  • chymotrypsin preferentially cleaves peptide amide bonds where the carboxyl side of the amide bond is a large hydrophobic amino acid such as tyrosine, tryptophan, and phenylalanine.
  • Proteases that cleave randomly e.g. exoproteasess, are much less suitable for the present invention.
  • Suitable endoproteases for use in aspects of the present invention may include trypsin, chymotrypsin, pepsin, C8, V8, arginase, LysN, and Lys C, preferably trypsin.
  • the cleavage action of the protease is known, and when the amino acid sequence of a protein is known, the cleavage profile may be predicted, including the mass of the peptides.
  • the protease digest may be determined once the amino acid sequence is known and the mass spectrum may be predicted.
  • more than one protease digestion may be used. Each different protease digestion results in different mix of peptides. For each different protease digest a mass spectrum may be acquired. The combined information from the different mass spectra may then determine the antimicrobial drug resistance.
  • the digesting step results in peptides in the range of 5-40 amino acids, more preferably in the range of 7-38 amino acids, more preferably in the range of 10-35 amino acids, more preferably in the range of 12-33 amino acids, more preferably in the range of 15-30 amino acids, more preferably in the range of 18 -27 amino acids, more preferably in the range of 20-25 amino acids.
  • the sensitivity of the MS depends on the m/z ratio of the peptide, if the charge z is high, the mass m may be higher. Peptides with a higher charge may have a higher nominal mass.
  • the digesting step results in peptides having a m/z ratio of 1-20 kDa, more preferably in the range of 1.0-15 kDa, more preferably in the range of 1-10 kDa, more preferably in the range of 1-8 kDa, and more preferably in the range of 1-6 kDa.
  • the resistance conferring protein and/or a mutation of a protein can be measured very accurately by mass spectroscopy.
  • the sample is prepared for mass spectrometry using generic mass spectrometry sample preparation protocols such as protein precipitation with organic solvents, solid-phase extraction (SPE), or liquidliquid extraction (LLE) and affinity related methods.
  • the mass spectrometric sample from the sample is used for the mass spectrometric analysis.
  • the preparation of the mass spectrometric sample from the sample may be performed by methods known per se to one of skill in the art of mass spectrometry.
  • the mass spectrum of the sample is acquired by standard procedures that depend on the type of equipment and MS methods used.
  • the mass spectrum is acquired by high resolution MS.
  • High resolution mass spectrometry (hrMS) provides the sensitivity to detect mutations in proteins.
  • high resolution MS has a resolution of 1-10 ppm, more preferably of 1-5 ppm.
  • Suitable mass spectrometers are Orbitrap, LC-qtrap, FT-ICR and Q-TOF.
  • the MS is not Maldi-TOF, or other MALDI-based MS approach.
  • the present method is especially suited for identifying more than one resistance conferring protein. This provides an enormous advantage as in one measurement, several different types of drug resistance may be determined.
  • a further advantage of the present invention is the ability to quantify the drug resistance, e.g., by quantifying the resistance conferring protein.
  • the microorganism is quantified by quantifying in said samples one or more structural biomolecules derived from said microorganism. This quantification is preferably followed by reference compounds such as stable isotope labeled peptides or proteins.
  • the structural biomolecules or metabolites are selected from the group consisting of nucleic acids, preferably (genomic) DNA. DNA is present as a single molecule inside the cell and can be quantified using for instance PCR- and/or DNA probing mediated technologies.
  • an internal standard is added to the sample of microorganism before the acquisition of the mass spectrum.
  • the internal standard may consist of reference peptides having known amounts.
  • Reference peptides with stable isotope labeled atoms such as the stable isotope, deuterium, 15N, or 13C, are particularly suitable.
  • Stable isotope-labeled (SIL) peptides may be added in known quantities directly to the sample, or at any step during sample preparation for MS analysis.
  • the resistance conferring protein is selected from the group comprising B-lactamase, aminoglycoside modifying protein, gyrase, topoisomerase, rRNA methylase, penicillin binding protein such as PBP2a, or PBP2', dihydrofolate reductase, aminoacyl tRNA synthetase, RNA polymerase, dihydropteroate synthase, catalase-peroxidase, enoylACP reductase, alkyl hydroperoxidase, NADH dehydrogenase II, arabinosyltransferase, pyrazinamidase, reverse transcriptase, and protease.
  • the resistance conferring protein is selected from the group comprising B-lactamase, aminoglycoside modifying protein, gyrase, topoisomerase, rRNA methylase, penicillin binding protein such as PBP2a, or PBP2', dihydrofolate reductase, RNA polymerase, reverse transcriptase, and protease.
  • the invention provides in certain embodiments a method for the rapid diagnosis of microorganisms that comprise proteins conferring resistance to antimicrobial drugs.
  • antibiotics and especially B- lactams including carbapenem antibiotics, aminoglycosides and quinolones are widely used in the empiric therapy for seriously ill patients with infections.
  • Rapid detection of microorganisms resistant to antimicrobial drugs is at present extremely important.
  • By rapid drug resistance detection the patient will be treated with the most appropriate antimicrobial drug therapy from the start.
  • empiric therapy or a wide range therapy is started and is sometimes switched at the moment the results of the susceptibility assays are reported.
  • the methods of the present invention can be used for rapid detection of resistance-conferring proteins.
  • a method of the present invention can be performed using complex samples, including crude lysates or patient specimens. The method allows for the precise assessment of peptides that enables identification of the specific drug resistance conferring protein and/or mutation.
  • a method of the present invention may be used to detect resistance of a microorganism to a specific antimicrobial drug, and determining the taxonomic identity of the microorganism.
  • a method of the invention preferably comprises the step of digesting a sample comprising proteins of a microorganism with an endoprotease.
  • the sample is a crude cell lysate, a blood culture suspected or confirmed of comprising microorganisms, or a patient specimen.
  • the sample contains or is suspected of containing a drug resistance conferring protein.
  • the endoprotease cleaves at a specific site of the protein originating from the microorganism, resulting in a mixture of peptides representing a protein digest.
  • mutations such as amino acid substitutions, insertions or deletions, in the sequence of the protein result in different peptides upon digestion.
  • the different proteins each render specific peptides upon digestion such that when the cleavage action of the protease and the amino acid sequence of a protein are known, the cleavage profile of different peptides in the protein digest including the mass of the different peptides may be predicted.
  • a method of the invention preferably comprises the step of acquiring a mass spectrum of the mix of peptides obtained in the step described above by high resolution mass spectrometry (preferably at a resolution of 1-10 ppm) in DDA mode and PRM mode, wherein in PRM mode said mass spectrum preferably provides information on whether an antimicrobial resistance-conferring protein is present, on the type of drug resistance conferring protein and on amino acid substitutions in the sequence of the drug resistance conferring protein to thereby allow for the precise assessment of peptides and identification of the specific drug resistance conferring protein and/or amino acid substitution mutations therein, and wherein in DDA mode said mass spectrum preferably provides information on the taxonomic identity of the microorganism.
  • a method of the invention preferably comprises the step of identifying from the mass spectra as obtained in DDA mode a multitude of peptide sequences, which sequences are compared to reference sequences of microorganisms of known taxonomic identity, to thereby determine the taxonomic identity of the microorganism.
  • taxon-specific peptides are detected in DDA mode, and comparison with a database of taxon-annotated peptides is performed to identify the taxon of the microorganism.
  • identification may comprise a local alignment of the obtained peptide sequence to the peptide sequences in the taxon-annotated database, and determining the most significant match based on sequence similarity scores (e.g. using the NCBI BLAST program function in combination with the UniProtKB/Swiss-Prot database of EMBL-EBI, of the European Molecular Biology Laboratory).
  • sequence similarity scores e.g. using the NCBI BLAST program function in combination with the UniProtKB/Swiss-Prot database of EMBL-EBI, of the European Molecular Biology Laboratory.
  • at least 5, more preferably at least 10, 20, or 30 taxon-specific peptides are detected in DDA mode and identified by sequence similarity searching (e.g.
  • Taxonomic identification using the shotgun proteomics approach in DDA mode may thus further comprise statistical analysis to determine the most likely taxonomic position of the microorganism when comparing the highest sequence similarity scores for a large number of peptides. In this way, the microorganism can be taxonomically identified with a high level of accuracy of certainty.
  • a method of the invention preferably comprises the step of identifying from the mass spectra as obtained in PRM mode a resistanceconferring protein by identifying selected peptides in a targeted manner.
  • Such peptides comprise an amino acid mutation as present in the resistance-conferring protein, which amino acid mutation is not present in reference peptides from the wild-type reference protein that does not confer resistance.
  • the target peptides that are digested fragments of resistance-conferring proteins preferably include one or more amino acid mutations that are known to be present in resistance-conferring proteins and that distinguish the resistance-conferring protein from their non- resistance conferring variants.
  • the one or more amino acid mutation in peptides that are digested fragments of resistance-conferring proteins may include a substitution, a duplication, insertion, or deletion mutations. Positive detection of the targeted peptide in the test sample indicated the presence therein of the resistance-conferring protein, and determines the resistance of the microorganism in the sample.
  • the step of targeted LC-MS/MS in PRM mode is very suitable for detection of carbapenemases, aminoglycoside-modifying enzymes (AMEs), and 16S rRNA methyltransferases (16S-RMTases).
  • Detection of peptides for these resistance-conferring protein can be performed using, for instance, an Orbitrap (e.g. as described in Foudraine et al. 2019, Front. Microbiol. 10:2760 and Foudraine et al. 2021, J Clin Microbiol 59:e00464-21).
  • the detection of carbapenemases may include detection of KPC, OXA-48-like, NDM and VIM enzymes through specific peptides as indicated in Table 1.
  • the detection of AMEs and 16S-RMTases may include detection of specific peptides as indicated in Table 2.
  • targeted detection in PRM mode includes detection of a combination of at least 2, preferably at least 5, more preferably at least 10, 15, 20, 25, 30, 40 or more peptides unique to endoprotease digested resistance conferring proteins.
  • the resistance conferring protein of which the presence is detected preferably includes a combination, preferably of at least 2 or 3 extended-spectrum B- lactamases (ESBL) selected from a TEM B-lactamase, an SHV B-lactamase, a CTX-M B-lactamase, and an OXA B-lactamase, preferably OXA-48 or OXA- 48-like; preferably at least one AmpC-type B-lactamase; preferably at least 2 or 3 carbapenemases, selected from an IMP-type carbapenemase (metallo-B- lactamase), a VIM (Verona integron-encoded metallo-B-lactamase), an OXA (oxacil
  • ESBL
  • AMEs aminoglycoside-modifying enzymes selected from AAC(3)-Ia, AAC(3)-II, AAC(3)-IV, AAC(3)-VI, AAC(6')-Ib, ANT(2")-I, APH(3')-VI, and AAC(6’)-Ib-cr; at least one, two or three 16S rRNA methyltransferases (16S- RMTases), selected from ArmA, RmtB, RmtC, and RmtF; at least a quinolone resistance mutation in gyrA, gyr
  • One preferred combination of resistance-conferring proteins of which peptides are detected includes the combination of B-lactamases TEM- 1/SHV-l/OXA-l.
  • Another preferred combination of resistance-conferring proteins of which peptides are detected includes the combination of extended spectrum B-lactamases SHV-5/TEM-12/CTX-M. Yet another preferred combination of resistance-conferring proteins of which peptides are detected includes the combination of carbapenemases OXA-48/NDM/KPC/VIM.
  • Yet another preferred combination of resistance-conferring proteins of which peptides are detected includes the combination of AMEs AAC(3)-II/AAC(6')-Ib/AAC(6’)-Ib-cr.
  • Yet another preferred combination of resistance-conferring proteins of which peptides are detected includes the combination gyrA hotspot WT/qnrA.
  • Yet another preferred combination of resistance-conferring proteins of which peptides are detected includes the combination of at least one 16S-RMTase selected from ArmA, RmtB, RmtC, and RmtF.
  • the combination of resistanceconferring proteins of which peptides are detected provides information on the resistance mechanism of the microorganism, in order to select the suitable therapeutic intervention by antibiotics against which the microorganism is resistant or susceptible, and that such information on the resistance mechanism is provided by the least number of targeted peptides detected.
  • One of skill in the art will understand how various combinations of mutations in BALs, EMBLs, carbapenemases, AMEs, quinolone proteins, and/or 16S-RMTases is optimized to provide information on the resistance mechanism of the microorganism. This may depend on the geographic area and the patient populations from which the samples are obtained, and methods according to the present invention allow for easy adaptation to such differences in geographic location and patient populations and also allow for adaptation when new mechanisms of resistance emerge.
  • Preferably 2 peptides are detected for each of SHV, TEM, CTX-M, OXA-1, CMY, AmpC, NDM, VIM, armA, AAC(3)-II, AAC(6’)-Ib, qnrA and qnrB.
  • Preferably 1 peptide is detected for each of AAC(6’)-Ib-cr and gyrA WT.
  • proteins are detected by at least one peptide.
  • Candidate peptides for targeted detection may be selected in silico for each resistance mechanism.
  • reference DNA sequences of the selected AMEs and 16S-RMTases may be obtained from the NCBI nucleotide database (https://www.ncbi.nlm.nih.gov/nucleotide/).
  • BLASTn searches may be performed for reference sequences using the nucleotide collection (nonredundant/nucleotide [nr/nt]) database (https://blast.ncbi.nlm.nih.gov/Blast.cgi).
  • sequences may be put into the correct reading frame by removing one or two nucleotides at the beginning of the sequence if they are incomplete. They may be aligned (e.g. using Clustal X) and translated to peptide sequences (e.g. using the website https://www.bioinformatics.org/sms2/translate.html). The number of available sequences may vary. For instance, one may obtain some 26 sequences for aac(3)-VIa to more than 2,000 sequences for aac(6')-Ib. After translation and alignment of the peptide sequences, all conserved tryptic peptides from 6 to 20 amino acids (preferably 7 to 20 amino acids) may be selected for each mechanism.
  • the number of candidate peptides per resistance mechanism may vary greatly, as some proteins may show more variation in sequences or may contain a low number of lysine and arginine amino acids. Subsequently, all “optimal” peptides without a cysteine, methionine, or ragged end (i.e., RR, RK, KR, or KK) may be selected as candidates for targeted detection. When fewer than six optimal peptides are available, additional “suboptimal” peptides containing a methionine and/or a ragged end may also be selected as candidates.
  • two peptides may be selected as candidates to detect the two key substitutions W102R and D179Y, which distinguish these two groups of enzymes.
  • a search may be performed for all candidate peptides in the NCBI nonredundant protein sequence database using protein BLAST. Searches may also be performed for all variants of peptides with the same mass, i.e., peptides containing leucine instead of isoleucine amino acids and vice versa. Specific attention may be paid to hits with human proteins and hits with pathogenic or commensal bacteria and fungi.
  • peptides specific for the detection of resistance mechanisms may be selected as internal control candidates needed for quality control of sample pretreatment and tryptic digestion.
  • abundant proteins may be selected from the data of a previous untargeted LC-MS/MS experiment.
  • the proteins chaperon protein DNAK, 30S ribosomal protein, and DNA-directed RNA polymerase may be selected as abundant proteins that are present in both E. coli and K. pneumoniae.
  • candidate peptides may be evaluated in a test panel consisting of multiple representative isolates displaying the different mechanisms of resistance. For each resistance mechanism, two isolates may for instance be selected. Internal quality control peptides may be tested in such isolates. Intensity and mass error may be compared for all peptide spectra. Based on such a comparison, one or two peptides may be selected for each resistance mechanism and may be included in a final multiplex panel used for evaluation in a method of the invention. Synthesized stable isotope-labeled (SIL) variants labeled with either lysine 13 Ce, 15 N2 or arginine 13 Ce, 15 N4 may be produced for the selected peptides and may also be included in the multiplex panel.
  • SIL stable isotope-labeled
  • peptides may be considered detected when all of the following criteria are met: mass error, ⁇ 10 ppm; ratio dot product (rdotp), >0.95; presence of all peptide fragments; and ratio to SIL peptide, >0.025.
  • Ratios to SIL peptides may be calculated in Skyline software (MacCoss Lab Software, University of Washington, USA, preferably vl9.1 or later) by dividing signal intensities of the endogenous peptides with signal intensities of the corresponding SIL peptides. Proteins for which one peptide is selected may be considered detected if this single peptide meets the indicated criteria.
  • Proteins for which two peptides are selected may be considered detected if both peptides meet the criteria or if one peptide meets the criteria with a ratio to SIL peptide of >0.1. Ratios of 0.025 and 0.1 may be selected based on the rationale that either carryover or background noise can give a low-intensity signal but not of both peptides and not higher than a ratio of 0.1 to the SIL peptide.
  • the presence of a 16S-RMTase is predicted to result in resistance against all three aminoglycosides gentamicin, tobramycin, and amikacin.
  • the presence of an AME is only predicted to result in resistance against its specific substrates.
  • the presence of only AAC(6')-Ib, for instance, may be predicted not to confer a gentamicin-resistant phenotype.
  • samples comprising microorganisms Prior to LC-MS/MS, samples comprising microorganisms may be pretreated, for instance by concentrating the microorganisms present in the sample through centrifugation. Pellets comprising microorganisms may then be lysed in lysis solution, for instance, comprising or consisting of 5% sodium deoxycholate and 7.5 mM dithiothreitol in water. At this time, SIL variants of selected peptides may be added to the solution in amounts of between 20-1000 fmol/pl. After optional addition of the SIL peptides, samples may for instance be sonicated and/or heated to about 80°C to optimize lysis of the microorganisms.
  • Samples may then optionally be diluted to a suitable protein density upon which the endopeptidase (e.g. trypsin (e.g. at 1 pg/pl)) is added, preferably in a suitable buffer (e.g. Tris buffer, pH 8, for trypsin). Proteins may then be digested at the optimal temperature of the endopeptidase (e.g. 37°C for trypsin) for a duration of about 0.5-2 hrs. Digestion may then be arrested, for instance by addition of trifluoroacetic acid. Digests may then be centrifuged (e.g.
  • Suitable peptide concentrations in the digest include 10-200 ng/pl, preferably around 50 ng/pl.
  • LC-MS/MS For LC-MS/MS analysis, use is preferably made of nano-flow liquid chromatography tandem mass spectrometry or microflow liquid chromatography tandem mass spectrometry (pLC-MS/MS).
  • pLC-MS/MS nano-flow liquid chromatography tandem mass spectrometry or microflow liquid chromatography tandem mass spectrometry
  • LC-MS/MS may be performed using the Evosep One (Evosep, Odense, Denmark) coupled to an Orbitrap mass spectrometer (Q Exactive HF Hybrid Quadrupole-Orbitrap; Thermo Fisher Scientific, Bremen, Germany).
  • LC may then be performed using the manufacturer’s separation method of 11.5 min (100 samples/day) using the corresponding column, gradient, and flow rate as described elsewhere (Bache et al. 2018. Mol Cell Proteomics 17:2284-2296.).
  • the MS system is operated in PRM mode for detection of peptides from antibiotic resistance-conferring proteins.
  • the following settings may suitably be used: a quadrupole isolation window of 0.6 m/z units, an automatic gain control target value of 1 x 10 6 ions, a maximum fill time of 150 ms, and a resolving power of 30,000 at 400 m/z.
  • a normalized collision energy of 27% may be used for all peptides.
  • a retention time window of 2 min may be used for each peptide.
  • the antibiotic resistanceconferring proteins may comprise TEM-l/SHV-l/OXA-1 as examples of B- lactamase enzymes able to confer resistance to small spectrum B-lactams piperacillin/tazobactam and amoxycillin; SHV-5/TEM-12/CTX-M as examples of B-lactamase enzymes able to confer resistance to extended spectrum B-lactams (ESBL) ceftriaxon, cefepime, and ceftazidime; OXA- 48/NDM/KPC/VIM as examples of B-lactamase enzymes/carbapenemases able to confer resistance to small spectrum B-lactams, extended spectrum B- lactams and carbapenems meropenem, imipenem,
  • the antibiotic resistanceconferring protein may further comprise CMY, E. coli chromosomal AmpC, armA, AAC(3)-II, AAC(6’)-Ib, AAC(6’)-Ib-cr, qnrA, and qnrB.
  • the antibiotic resistanceconferring protein is preferably detected by at least 1 peptide, preferably antibiotic resistance-conferring proteins are detected by detecting 2 peptides per protein.
  • Example 1 Determination of resistance mechanism through targeted detection of peptides originating from proteins that confer antibiotic resistance.
  • the antibiotic resistance proteins KPC, OXA-48, NDM, VIM, CTX-M, CMY, armA, rmtB, AAC(3)-II, AAC(6’)-Ib and AAC(6’)-Ib-cr, gyrA hotspot wildtype and qnrA were all measured simultaneously using a single multiplex assay. Criteria for data evaluation were that the retention time of the peptide needed to be the same as the SIL peptide, a ratio dot products (rdotp) > 0.95, a mass error ⁇ 5 ppm, and all fragments present. LC-MS/MS results were compared with AST and WGS results.
  • Example 2 Combined determination of taxonomic identity and resistance mechanism through detection of taxon-specific peptides and targeted detection of peptides of proteins that confer antibiotic resistance
  • the same isolate nr. 5 was subjected to analysis using the methods of the present invention, and using the method for determining the presence of resistance mechanisms essentially as described in Example 1. During the first 3-minutes of the gradient, data were acquired in DDA mode, and as many taxon-specific peptides as possible were identified. PRM measurement was performed in the remaining 8.5 minutes of the same run.
  • ESBL CTX-M
  • AmpC neg
  • Garba neg
  • 16S-RMTase neg
  • AME AAC(3)-II & AAC(6’)-Ib-cr: QRDR: Mutated
  • QNR proteins neg.
  • the resistance phenotype of isolate nr 5 was therefore predicted as susceptible to meropenem and imipenem, and resistant to ampicillin, piperacillin, cefuroxime, ceftriaxone, ceftazidime, gentamicin, tobramycin, and ciprofloxacin. This fully reflected the phenotypic data of Table 4, which were obtained by traditional cultivation techniques.

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Abstract

La présente invention concerne un procédé d'identification taxonomique combinée et de détermination de la résistance aux médicaments antimicrobiens d'un micro-organisme, des protéines de celui-ci étant présentes dans un échantillon, le procédé consistant à soumettre un échantillon comprenant des protéines d'un micro-organisme à une endoprotéase pour fournir un mélange de peptides à partir desdites protéines, et à analyser le mélange de peptides par spectrométrie de masse à haute résolution à l'aide d'une seule technique de spectrométrie de masse à haute résolution dans deux modes d'acquisition de données distincts, lesdits modes étant constitués d'une analyse DDA et d'une surveillance PRM et lesdits deux modes d'acquisition de données distincts étant réalisés par la suite ou en parallèle dans un seul cycle d'analyse par spectrométrie de masse.
PCT/NL2022/050768 2021-12-31 2022-12-30 Détermination de l'identité de la souche et de la résistance antimicrobienne dans des cultures de sang positives WO2023128765A1 (fr)

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WO2021030460A1 (fr) * 2019-08-12 2021-02-18 Baylor College Of Medicine Procédés protéogénomiques de diagnostic du cancer
FR3106414A1 (fr) * 2020-01-17 2021-07-23 Centre National De La Recherche Scientifique (Cnrs) Procédé d’identification et de caractérisation d’une population microbienne par spectrométrie de masse

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Publication number Priority date Publication date Assignee Title
WO2021030460A1 (fr) * 2019-08-12 2021-02-18 Baylor College Of Medicine Procédés protéogénomiques de diagnostic du cancer
FR3106414A1 (fr) * 2020-01-17 2021-07-23 Centre National De La Recherche Scientifique (Cnrs) Procédé d’identification et de caractérisation d’une population microbienne par spectrométrie de masse

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BACHE ET AL., MOL CELL PROTEOMICS, vol. 17, 2018, pages 2284 - 2296
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