Characteristic gene combination, kit and sequencing method for predicting antibiotic susceptibility phenotype of Acinetobacter baumannii

Abstract

The present invention discloses a characteristic gene combination, a kit and a sequencing method for predicting the antibiotic susceptibility phenotype of Acinetobacter baumannii, and determines the susceptibility phenotype of Acinetobacter baumannii to imipenem, ceftazidime, cefepime and ciprofloxacin by detecting the presence or absence of genes or mutations in the characteristic combination. The characteristic combination provided by the present invention has a high accuracy rate in predicting the susceptibility phenotype, which is conducive to the clinical development of precise treatment of Acinetobacter baumannii-related infections.

Description

Technical Field

[0001] The present invention relates to gene sequencing technology, in particular to a characteristic gene combination, a kit and a sequencing method for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii. Background Art

[0002] Acinetobacter baumannii is one of the common clinical conditional pathogens, with the fifth highest clinical isolation rate in my country (CHINET data in 2021). It can cause respiratory tract infections, meningitis, urinary tract infections, sepsis, etc. In recent years, due to the irrational use of clinical interventional treatments and broad-spectrum antibiotics, the inherent drug resistance and acquired drug resistance of Acinetobacter baumannii have gradually increased, and the drug resistance rate has increased year by year. In particular, the emergence of multidrug-resistant Acinetobacter baumannii, led by carbapenem resistance, has brought great difficulties to clinical treatment. Clinical precision treatment requires the selection of antimicrobial drugs based on the results of drug sensitivity tests and related enzyme type tests. Therefore, it is very important to establish an accurate and rapid detection method to predict the drug sensitivity phenotype of Acinetobacter baumannii to guide clinical treatment.

[0003] The resistance of Acinetobacter baumannii to various antibiotics can be mediated by the production of various enzymes (such as β-lactams), target changes (such as quinolones), active efflux and other mechanisms. For example, the resistance mechanism of Acinetobacter baumannii to β-lactams is mainly the production of β-lactamases, including penicillinase, extended-spectrum β-lactamase, cephalosporinase, carbapenemase, etc. This type of enzyme can hydrolyze β-lactam antibiotics such as cephalosporins and carbapenems, and some of them can lead to high-level resistance. Common β-lactamase families in Acinetobacter baumannii include OXA family, ADC family, NDM family, TEM family, CTX-M, etc. Different enzyme types in the family have great differences in their ability to hydrolyze β-lactam drugs. The resistance mechanism of Acinetobacter baumannii to quinolones is mainly the target of quinolone drugs, such as mutations in the topoisomerase gyrA or parC gene. In addition, studies have shown that the AdeABC efflux pump system is also associated with quinolone resistance. However, for different antibiotics, there are dozens to hundreds of resistance-related genes reported in the literature, some of which are not related to the resistance phenotype or have little contribution, which misleads the judgment of drug sensitivity phenotype. Studies have confirmed that the accuracy of predicting resistance phenotypes by using resistance genes included in the existing authoritative resistance gene databases Resfinder and CARD is only 66% and 52% (doi: 10.1093 / jac / dkaa257).

[0004] At present, the drug resistance detection for Acinetobacter baumannii can be divided into phenotypic detection and genotypic detection methods. In terms of phenotypic detection, the main clinical method is microbial culture + drug sensitivity test. This method has limitations such as long culture time and low culture positive rate, and cannot fully meet the needs of clinical precision treatment. In terms of genetic testing, it is mainly aimed at detecting specific and limited drug resistance genes. The content of this test is relatively simple and cannot reflect the true drug sensitivity results. Therefore, it is urgent to find a method that is fast, independent of culture, and highly accurate to detect the drug sensitivity phenotype of commonly used clinical antibiotics to guide clinical precision treatment. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a characteristic gene combination, a kit and a sequencing method for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii, which can analyze the resistance of four antibiotics, imipenem, ceftazidime, cefepime and ciprofloxacin, at one time, with good accuracy, sensitivity and specificity.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a characteristic gene combination for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii, wherein the antibiotic is one or a combination of imipenem, ceftazidime, cefepime, and ciprofloxacin,

[0007] The characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to imipenem includes OXA-23, ADC-33, OXA-72, ADC-56, and OXA-24. If all the genes are tested simultaneously, if the test results are negative, it is presumed to be sensitive; if any gene test result is positive, it is presumed to be resistant; and / or

[0008] The characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to ceftazidime includes OXA-23, ADC-30, ADC-79, ADC-162, and PER-1. If the test results of all genes are negative, it is presumed to be sensitive; if the test result of any gene is positive, it is presumed to be resistant; and / or

[0009] The characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to cefepime includes OXA-23, ADC-30, ADC-162, and ADC-56. If the genes are tested simultaneously, if the test results are all negative, it is presumed to be sensitive; if the test result of any gene is positive, it is presumed to be resistant; and / or

[0010] The characteristic gene mutation sites of the predicted drug-susceptibility phenotype of Acinetobacter baumannii to ciprofloxacin include gyrA:242 (C->T). If the test results are all negative, it is presumed to be sensitive; if the test results are positive, it is presumed to be resistant.

[0011] Preferably, the characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to imipenem also includes ADC-223, ADC-222, ampC, NDM-1, ADC-215, ADC-226, ADC-219, ADC-74, ADC-214, ADC-233, OXA-20, OXA-237, OXA-253, OXA-542, and IMP-16 genes.

[0012] Preferably, the characteristic gene combination for predicting the ceftazidime susceptibility phenotype of Acinetobacter baumannii also includes ADC-73, ADC-212, ADC-33, ADC-25, ADC-176, ADC-56, ADC-240, PER-7, ADC-191, NDM-1, ADC-215, ADC-100, ADC-96, GES-11, ADC-219, CTX-M-15, CMY-30, ADC-74, ADC-140, ADC-214, ADC-218, OXA-253, OXA-20, OXA-533, VEB-1, and IMP-16 genes.

[0013] Preferably, the characteristic gene combination for predicting the cefepime susceptibility phenotype of Acinetobacter baumannii also includes ADC-73, ADC-212, ADC-223, PER-1, ADC-25, ADC-176, NDM-1, PER-7, ADC-100, ADC-11, ADC-215, ADC-191, GES-11, ADC-218, ADC-214, CTX-M-15, ADC-96, CMY-30, OXA-253, and OXA-20 genes.

[0014] Preferably, the characteristic gene mutation sites for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to ciprofloxacin also include gyrB:1437 (A->C) and parC:251 (C->T).

[0015] A kit containing the above-mentioned characteristic gene combination detection reagent for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii.

[0016] The sequencing method for predicting the drug sensitivity phenotype of Acinetobacter baumannii using the above kit adopts a whole genome sequencing method or a metagenomic sequencing method.

[0017] The beneficial effects of the present invention are as follows: the present invention is a method for detecting drug resistance based on nucleic acid molecules, which is independent of bacterial culture and can directly detect a small amount of Acinetobacter baumannii genomic nucleic acid obtained from clinical specimens or other methods, and predict its drug sensitivity phenotype based on the characteristic gene combination provided by the present invention. Compared with traditional methods, it has the characteristics of short detection cycle and high detection sensitivity. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a diagram showing the detection results of characteristic genes used for imipenem susceptibility phenotype prediction in Acinetobacter baumannii strains downloaded from a public database (left half) and the corresponding relationship between the actual susceptibility phenotype results and the predicted susceptibility phenotype results (right half).

[0019] Figure 2 This is a diagram showing the detection results of characteristic genes used for ceftazidime drug sensitivity phenotype prediction in Acinetobacter baumannii strains downloaded from a public database (left half) and the corresponding relationship between the actual drug sensitivity phenotype results and the predicted drug sensitivity phenotype results (right half).

[0020] Figure 3 This is a diagram showing the detection results of characteristic genes used for predicting cefepime drug sensitivity phenotype in Acinetobacter baumannii strains downloaded from a public database (left half) and the corresponding relationship between the actual drug sensitivity phenotype results and the predicted drug sensitivity phenotype results (right half).

[0021] Figure 4 This is a diagram showing the detection results of characteristic gene mutation sites used for ciprofloxacin susceptibility phenotype prediction in Acinetobacter baumannii strains downloaded from a public database (left half) and the corresponding relationship between the actual susceptibility phenotype results and the predicted susceptibility phenotype results (right half). DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention; it is obvious that the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments, and all other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making creative work are within the scope of protection of the present invention.

[0023] The present invention provides a characteristic gene combination for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii, wherein the antibiotic is one or a combination of imipenem, ceftazidime, cefepime and ciprofloxacin.

[0024] The characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to imipenem includes OXA-23, ADC-33, OXA-72, ADC-56, and OXA-24. If all the genes are tested simultaneously, if the test results are negative, it is presumed to be sensitive; if any gene test result is positive, it is presumed to be resistant; and / or

[0025] The characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to ceftazidime includes OXA-23, ADC-30, ADC-79, ADC-162, and PER-1. If the test results of all genes are negative, it is presumed to be sensitive; if the test result of any gene is positive, it is presumed to be resistant; and / or

[0026] The characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to cefepime includes OXA-23, ADC-30, ADC-162, and ADC-56. If the genes are tested simultaneously, if the test results are all negative, it is presumed to be sensitive; if the test result of any gene is positive, it is presumed to be resistant; and / or

[0027] The characteristic gene mutation sites of the predicted drug-susceptibility phenotype of Acinetobacter baumannii to ciprofloxacin include gyrA:242 (C->T). If the test results are all negative, it is presumed to be sensitive; if the test results are positive, it is presumed to be resistant.

[0028] Preferably, the characteristic gene combination for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to imipenem also includes ADC-223, ADC-222, ampC, NDM-1, ADC-215, ADC-226, ADC-219, ADC-74, ADC-214, ADC-233, OXA-20, OXA-237, OXA-253, OXA-542, and IMP-16 genes.

[0029] Preferably, the characteristic gene combination for predicting the ceftazidime susceptibility phenotype of Acinetobacter baumannii also includes ADC-73, ADC-212, ADC-33, ADC-25, ADC-176, ADC-56, ADC-240, PER-7, ADC-191, NDM-1, ADC-215, ADC-100, ADC-96, GES-11, ADC-219, CTX-M-15, CMY-30, ADC-74, ADC-140, ADC-214, ADC-218, OXA-253, OXA-20, OXA-533, VEB-1, and IMP-16 genes.

[0030] Preferably, the characteristic gene combination for predicting the cefepime susceptibility phenotype of Acinetobacter baumannii also includes ADC-73, ADC-212, ADC-223, PER-1, ADC-25, ADC-176, NDM-1, PER-7, ADC-100, ADC-11, ADC-215, ADC-191, GES-11, ADC-218, ADC-214, CTX-M-15, ADC-96, CMY-30, OXA-253, and OXA-20 genes.

[0031] Preferably, the characteristic gene mutation sites for predicting the drug-susceptibility phenotype of Acinetobacter baumannii to ciprofloxacin also include gyrB:1437 (A->C) and parC:251 (C->T).

[0032] A kit containing the above-mentioned characteristic gene combination detection reagent for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii.

[0033] The kit is used to sequence the drug sensitivity phenotype of Acinetobacter baumannii, using a whole genome sequencing method or a metagenomic sequencing method.

[0034] The present invention is described in detail below in conjunction with specific detection methods and effect comparisons:

[0035] Example 1 Prediction of drug susceptibility phenotypes of Acinetobacter baumannii in public databases using feature combinations

[0036] 1.1 Data collection: The genome information of 1557 strains of Acinetobacter baumannii and their corresponding antibiotic susceptibility phenotype data were downloaded from public databases (NCBI NDARO database and PATRIC database). Among them, 736 strains were resistant to imipenem (English abbreviation imipenem), 675 strains were sensitive, 980 strains were resistant to ceftazidime (English abbreviation ceftazidime), 205 strains were sensitive, 532 strains were resistant to cefepime (English abbreviation cefepime), 137 strains were sensitive, and 1165 strains were resistant to ciprofloxacin (English abbreviation ciprofloxacin), 186 strains were sensitive.

[0037] 1.2 Detection of drug-resistant genes and mutations: The assembled genome sequence was aligned with the drug-resistant database using ncbi-blast (v2.9.0+) software (parameters: -evalue 1e-5 -outfmt 0 -num_alignments 10000) to detect the above-mentioned drug-resistant genes and mutation sites. For the presence or absence of gene characteristics, if the alignment consistency rate with the reference sequence of the drug-resistant gene is higher than 90% and the coverage rate is higher than 60%, the drug-resistant gene is considered to be detected. For gene mutation characteristics, if the sequence of the drug-resistant gene supports the mutation site, the mutation is considered to be detected.

[0038] 1.3 Statistics on the detection of drug-resistant genes and mutations in each strain of Acinetobacter baumannii.

[0039] 1.4 Prediction of drug sensitivity results: For the drug sensitivity prediction of any antibiotic of a certain strain of bacteria, if any one of the characteristics in the feature combination is detected, the strain is considered to be phenotypically resistant to the antibiotic; otherwise, it is judged to be sensitive. Figure 1-Figure 4As shown in Table 1, in the four models of imipenem, ceftazidime, cefepime, and ciprofloxacin, the drug sensitivity results predicted by the detected features in each strain are highly consistent with the actual drug sensitivity phenotype. The prediction performance is shown in Table 1. The accuracy of the feature combination in predicting the drug sensitivity phenotype of imipenem, ceftazidime, cefepime, and ciprofloxacin is 0.918, 0.949, 0.933, and 0.996, respectively, and the specificity and sensitivity are also at a high level. The number of feature detection samples, the number of phenotypic resistance samples, and the positive predictive value (positive predictive value = number of phenotypic resistance samples / number of feature detection samples) of each resistance feature are shown in Table 2. The above results show that the above feature combination has a good effect on distinguishing phenotypic resistance and phenotypic sensitivity of Acinetobacter baumannii.

[0040]

[0041]

[0042]

[0043]

[0044] Example 2 Prediction of drug susceptibility phenotype of Acinetobacter baumannii isolated from clinical specimens using feature combination

[0045] 2.1 Sample collection: 385 cases of Acinetobacter baumannii isolated from clinical specimens were collected from a hospital, and the corresponding drug sensitivity results were collected. Among them, 175 strains were resistant to imipenem and 171 strains were sensitive; 213 strains were resistant to ceftazidime and 74 strains were sensitive; 131 strains were resistant to cefepime and 53 strains were sensitive; 252 strains were resistant to ciprofloxacin and 71 strains were sensitive.

[0046] 2.2 Whole genome sequencing of samples: nucleic acid was extracted from the samples, and after Qubit detection, it was confirmed that the DNA could meet the requirements of subsequent sequencing. The extracted nucleic acid was sequenced and subjected to high-throughput sequencing (Illumina Novaseq 6000PE150).

[0047] 2.3 Sequencing data quality control: fastp (v0.19.5) software was used to filter the obtained raw fastq sequence data (parameter setting: -q 15 -u 40 -l read_length*0.67) to remove low-quality and short sequences; at the same time, komplexity (v0.3.6) software was used to calculate the sequence information complexity (parameter setting: -F -t 0.4) and filter out low-complexity sequences.

[0048] 2.4 Drug-resistant gene detection: Use blastn (version 2.9.0+) software to compare read sequences with drug-resistant gene reference sequences. For gene presence or absence characteristics, if there are more than one read with a consistency rate of more than 90% with the reference sequence, the drug-resistant gene is considered to be detected. For gene mutation characteristics, for a certain mutation site, if the proportion of reads supporting the mutation site is greater than 0.2, the mutation is considered to be detected.

[0049] 2.5 Prediction of drug sensitivity phenotype: For the prediction of drug sensitivity of a certain strain of bacteria to any antibiotic, if any one of the features in the feature combination is detected, the strain is considered to be resistant to the antibiotic phenotype; otherwise, it is judged to be sensitive. According to the feature detection results, compared with the drug sensitivity results obtained by the hospital laboratory, the accuracy, sensitivity and specificity are all above 0.9. The detection results are summarized in Table 3. The above results show that for the actual collected Acinetobacter baumannii isolated from clinical specimens, the corresponding feature combination also has a high accuracy, sensitivity and specificity, indicating that the present invention has a high practical value.

[0050]

[0051] Example 3 Prediction of drug susceptibility phenotypes of Acinetobacter baumannii in public databases using a preferred combination of important features

[0052] 3.1 Based on the detection frequency, positive predictive value and common detection relationship between the features of each feature in Example 1, the presence or absence of OXA-23, ADC-33, OXA-72, ADC-56, and OXA-24 genes were selected as the important feature combination of imipenem, the presence or absence of OXA-23, ADC-30, ADC-79, ADC-162, and PER-1 genes were selected as the important feature combination of ceftazidime, the presence or absence of OXA-23, ADC-30, ADC-162, and ADC-56 genes were selected as the important feature combination of ceftazidime, and the gyrA:242 (C->T) mutation was selected as the important feature of ciprofloxacin.

[0053] 3.2 For the Acinetobacter baumannii strain downloaded in Example 1, statistics were performed on the preferred features described in 3.1 based on the feature detection results obtained in 1.2.

[0054] 3.3 If any of the features in the preferred feature combination is detected, the strain is considered to be resistant to the antibiotic phenotype; otherwise, it is judged to be sensitive. As shown in Table 4, the use of the preferred resistance features to predict the drug sensitivity phenotype has a good accuracy, sensitivity and specificity. It can be seen that the use of the preferred feature combination can also better predict the drug sensitivity phenotype of Acinetobacter baumannii downloaded from the public database.

[0055]

[0056] Example 4 Prediction of drug susceptibility phenotype of Acinetobacter baumannii in clinical specimens using a preferred combination of important features

[0057] 4.1 For the Acinetobacter baumannii strains collected from the hospital in Example 2, statistics were performed on the important features selected in 3.1 according to the feature detection results obtained in 2.4.

[0058] 4.2 If any of the features in the preferred feature combination is detected, the strain is considered to be resistant to the antibiotic phenotype; otherwise, it is judged to be sensitive. As shown in Table 5, the use of the preferred resistance features to predict the drug sensitivity phenotype has a good accuracy, sensitivity and specificity. It can be seen that the use of the preferred feature combination can also better predict the drug sensitivity phenotype of Acinetobacter baumannii isolated from clinical specimens.

[0059]

[0060] Example 5 Prediction of drug susceptibility phenotype of Acinetobacter baumannii in clinical specimens using a preferred combination of important features

[0061] 5.1 Sample collection: A total of 115 clinical specimens with positive culture results for Acinetobacter baumannii and drug sensitivity tests were collected from a hospital, including sputum, bronchoalveolar lavage fluid, ascites, and drainage fluid.

[0062] 5.2 High-throughput sequencing of samples: DNA was extracted from the samples and tested by Qubit to confirm that the DNA quality could meet the requirements of subsequent sequencing. The extracted DNA was subjected to library construction and high-throughput sequencing (Illumina Nextseq 550SE75).

[0063] 5.3 Sequencing data analysis: fastp (v0.19.5) software was used to filter the raw fastq sequence data (parameter settings: -q 15 -u 40 -l read_length*0.67) to remove low-quality sequences and sequences that were too short. Komplexity (v0.3.6) software was used to calculate the sequence information complexity (parameter settings: -F -t 0.4) and filter out low-complexity sequences.

[0064] 5.4 Removal of human sequences: The clean sequences obtained by quality control filtering were aligned with the human reference genome sequence (human_38) using bowtie2 (v2.3.4.3) software (parameter settings: --mm --very-sensitive -k1) to filter out human sequences.

[0065] 5.5 Species annotation: Minimap2 software (v2.17) was used to align the Illumina read sequences with the target pathogen reference genome sequence library (derived from the NCBI genome database) set above (alignment parameters: -x sr-a--secondary=no-L), and the LCA algorithm was used for species annotation statistics. Finally, the number of sequences and genome coverage of Acinetobacter baumannii detected were counted.

[0066] 5.6 Drug resistance feature detection: Use blastn (version 2.9.0+) software to compare read sequences with drug resistance gene reference sequences. For gene presence or absence features, if there are more than one read with a consistency rate of more than 90% with the reference sequence, the drug resistance gene is considered to be detected. For drug resistance gene mutation features, for a certain mutation site, if the proportion of reads supporting the mutation site is greater than 0.2, the mutation is considered to be detected.

[0067] 5.7 Prediction of drug sensitivity phenotype: The drug sensitivity phenotype of Acinetobacter baumannii to each antibiotic in clinical specimens is predicted using the combination of important features of each antibiotic described in 3.1. For a certain antibiotic, if any important feature is detected, Acinetobacter baumannii is considered to be resistant to the antibiotic; otherwise, Acinetobacter baumannii is sensitive to the drug. When the detected genome coverage is less than a certain proportion and no resistance feature is detected, it is impossible to make a prediction because it is uncertain whether the feature exists (the feature may exist in an uncovered area). Table 6 shows the statistical results of some clinical specimens.

[0068]

[0069]

[0070] “ / ” indicates that the drug sensitivity phenotype cannot be predicted at the current genome coverage.

[0071] The genome coverage represents the ratio of the number of bases in the reference genome and the number of bases in the reference genome in the data obtained by metagenomic sequencing. As shown in Table 7, by using the metagenomic sequencing method and the above-mentioned preferred feature combination, the drug sensitivity phenotype of Acinetobacter baumannii in most clinical specimens to four antibiotics can be predicted with high accuracy, indicating that the present invention has a high application value in assisting the treatment of Acinetobacter baumannii infection.

[0072]

[0073] The embodiments described above are only used to illustrate the technical ideas and features of the present invention, and their purpose is to enable those skilled in the art to understand the contents of the present invention and implement them accordingly. The patent scope of the present invention cannot be limited only by this embodiment, that is, any equivalent changes or modifications made to the spirit disclosed by the present invention still fall within the patent scope of the present invention.

Claims

1. A characteristic gene combination for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii, the characteristic gene combination comprising OXA-23, OXA-20, OXA-253, and ADC-215, characterized in that: Drug sensitivity prediction includes drug resistance prediction and sensitivity prediction. All characteristic genes of the combination are tested at the same time. If the test results are all negative, it is presumed to be sensitive; if any gene test result is positive, it is presumed to be resistant. The drug sensitivity is to one of imipenem, ceftazidime and cefepime; When targeting imipenem, the characteristic gene combination also includes one or more of ADC-33, OXA-72, ADC-56, OXA-24, ADC-223, ADC-222, ampC, NDM-1, ADC-226, ADC-219, ADC-74, ADC-214, ADC-233, OXA-237, OXA-542, and IMP-16; When targeting ceftazidime, the characteristic gene combination also includes one or more of ADC-30, ADC-79, ADC-162, PER-1, ADC-73, ADC-212, ADC-33, ADC-25, ADC-176, ADC-56, ADC-240, PER-7, ADC-191, NDM-1, ADC-215, ADC-100, ADC-96, GES-11, ADC-219, CTX-M-15, CMY-30, ADC-74, ADC-140, ADC-214, ADC-218, OXA-533, VEB-1, and IMP-16; When targeting cefepime, the characteristic gene combination also includes one or more of ADC-30, ADC-162, ADC-56, ADC-73, ADC-212, ADC-223, PER-1, ADC-25, ADC-176, NDM-1, PER-7, ADC-100, ADC-11, ADC-191, GES-11, ADC-218, ADC-214, CTX-M-15, ADC-96, and CMY-30.

2. A kit containing the characteristic gene combination detection reagent for predicting the antibiotic sensitivity phenotype of Acinetobacter baumannii according to claim 1.

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