CN115305292B - Characteristic gene combination, kit and sequencing method for predicting antibiotic drug sensitivity phenotype of staphylococcus aureus - Google Patents
Characteristic gene combination, kit and sequencing method for predicting antibiotic drug sensitivity phenotype of staphylococcus aureus Download PDFInfo
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Abstract
The invention discloses a characteristic gene combination, a kit and a sequencing method for predicting the drug sensitivity phenotype of staphylococcus aureus to antibiotics, which are used for judging the drug sensitivity phenotype of staphylococcus aureus to cefoxitin, clindamycin, erythromycin, methicillin, oxacillin, ciprofloxacin and penicillin by detecting the existence of genes or mutation in the characteristic combination. The feature combination provided by the invention has high accuracy in predicting the drug-sensitive phenotype, and is beneficial to clinically developing accurate treatment on staphylococcus aureus related infection.
Description
Technical Field
The invention relates to a gene sequencing technology, in particular to a characteristic gene combination, a kit and a sequencing method for predicting antibiotic drug sensitive phenotype of staphylococcus aureus.
Background
Staphylococcus aureus is one of the main pathogens of hospital and community infection, and has high clinical isolation rate in China (CHINET data in 2021), and can cause various infectious diseases, such as skin and soft tissue infection, endocarditis, osteomyelitis, bacteremia and fatal pneumonia. Staphylococcus aureus can be classified into methicillin-sensitive staphylococcus aureus (MSSA) and methicillin-resistant staphylococcus aureus (MRSA) according to sensitivity to antibiotics. In recent decades, due to bacterial evolution and antibiotic abuse, staphylococcus aureus resistance has increased worldwide, MRSA infection has also increased, and clinical anti-infective therapy against MRSA has become more difficult. There is growing evidence that the mechanism of resistance to staphylococcus aureus is very complex, especially for MRSA, which is resistant to multiple antibiotics. Therefore, establishing an accurate and rapid detection method for predicting the drug sensitivity phenotype of staphylococcus aureus is very important for guiding clinical treatment.
MRSA resistance is produced by a gene encoding penicillin binding protein 2a or 2 '(PBP 2a or PBP 2') (mecA). In addition, MRSA has rapidly become the most common drug resistant pathogen found in many parts of the world, including europe, the united states, north africa, the middle east and east asia. In China, the proportion of hospital-acquired MRSA has reached 50.4%. The endogenous drug resistance mechanism of staphylococcus aureus mainly comprises three aspects. (1) outer membrane permeability. When cell membrane permeability is reduced, energy metabolism of bacteria is affected, and thus drug absorption is reduced, resulting in drug resistance. For example, resistance to aminoglycosides by staphylococcus aureus is caused by a decrease in membrane permeability, ultimately resulting in a decrease in drug intake. (2) an evacuation system. There are three types of multi-drug pump proteins on the staphylococcus aureus cell membrane: qacA, norA and Smr. (3) overproduction of beta-lactamase. Excessive secretion of beta-lactamase by MRSA reduces the action of antibiotics mainly by hydrolysis and pinching mechanisms, which results in MRSA resistance.
The current detection of resistance to staphylococcus aureus can be categorized into phenotypic detection and genotypic detection methods. In the aspect of phenotype detection, the main clinical method is a microorganism culture and drug sensitivity experiment, and the method has the limitations of long culture time, low culture positive rate and the like, so that the requirement of clinical accurate treatment cannot be completely met. In the aspect of gene detection, the detection is mainly carried out on specific and limited drug-resistant genes, the detection content is single, and the real drug-sensitive results cannot be reflected. Therefore, there is a need to find a method for rapidly, independent of culture, and with high accuracy, detecting the drug-sensitive phenotype of clinically usual antibiotics to guide clinically accurate treatment.
Disclosure of Invention
The invention aims to solve the technical problem of providing a characteristic gene combination, a kit and a sequencing method for predicting the drug sensitivity phenotype of staphylococcus aureus to antibiotics, which can analyze the drug resistance condition of 7 antibiotics of cefoxitin, clindamycin, erythromycin, methicillin, oxacillin, ciprofloxacin and penicillin at one time, and has better accuracy, sensitivity and specificity.
In order to solve the technical problems, the invention adopts the following technical scheme: a characteristic gene combination for predicting drug sensitivity phenotype of staphylococcus aureus to antibiotics, wherein the antibiotics are one or a combination of more of cefoxitin, clindamycin, erythromycin, methicillin, oxacillin and penicillin,
the characteristic gene combination of the staphylococcus aureus on the phenotype of the cefoxitin Ding Yaomin is predicted to comprise mecA and mecI, the genes are detected simultaneously, and if the detection results are negative, the sensitivity is presumed; if any gene detection result is positive, the medicine resistance is presumed; and/or
The characteristic gene combination for predicting the drug sensitivity phenotype of staphylococcus aureus to clindamycin comprises ErmA, ermC, ermB, detecting genes simultaneously, and if the detection results are negative, presuming that the detection results are sensitive; if any gene detection result is positive, the medicine resistance is presumed; and/or
The characteristic gene combination for predicting the erythromycin drug sensitivity phenotype of staphylococcus aureus comprises ErmA, ermC, msrA, ermB, ermT, detecting genes simultaneously, and if the detection results are negative, presuming that the staphylococcus aureus is sensitive; if any gene detection result is positive, the medicine resistance is presumed; and/or
Predicting that the characteristic gene of staphylococcus aureus on the phenotype of methicillin Lin Yaomin is mecA, and if the detection results are negative, presuming that the staphylococcus aureus is sensitive; if the detection result is positive, the medicine resistance is presumed;
predicting that the characteristic gene of staphylococcus aureus on the phenotype of oxaziclomex Lin Yaomin is mecA, and if the detection results are negative, presuming that the staphylococcus aureus is sensitive; if the detection result is positive, the medicine resistance is presumed;
the characteristic gene mutation site combination for predicting the phenotype of staphylococcus aureus on cyclopropyl Sha Xingyao is Sta_parC 239 (C- > T), sta_parC 239 (C- > A), sta_gyrA 251 (C- > T) and Sta_gyrA 250 (T- > G), and if the detection results are negative, the detection results are presumed to be sensitive; if the detection result is positive, the medicine resistance is presumed; and/or
The characteristic genes of the staphylococcus aureus for predicting the penicillin drug sensitivity phenotype are blaZ and mecA, and if the detection results are negative, the detection results are presumed to be sensitive; if the detection result is positive, the drug resistance is presumed.
A kit comprising the above-described gene combination assay reagent for predicting the antibiotic susceptibility phenotype of staphylococcus aureus.
The sequencing method for carrying out drug sensitive phenotype prediction on staphylococcus aureus by adopting the kit adopts a whole genome sequencing method or a metagenome sequencing method.
The beneficial effects of the invention are as follows: the invention is a method for detecting drug resistance based on nucleic acid molecules, can directly detect a small amount of staphylococcus aureus genome nucleic acid obtained by a clinical specimen or other modes without depending on bacterial culture, and predicts the drug sensitive phenotype according to the characteristic gene combination provided by the invention.
Drawings
FIG. 1 is a graph of the correspondence between the detected results (left half) of the signature genes for the phenotype prediction of cefoxitin Ding Yaomin in the staphylococcus aureus strains downloaded in the public database and the actual and predicted drug-sensitive phenotype results (right half).
FIG. 2 is a graph of the correspondence between the detected results (left half) of the signature genes for clindamycin drug susceptibility phenotype prediction in staphylococcus aureus strains downloaded in the public database and the actual drug susceptibility phenotype results and predicted drug susceptibility phenotype results (right half).
FIG. 3 is a graph of the correspondence between the detected results (left half) of the signature genes for erythromycin drug susceptibility phenotype prediction in the staphylococcus aureus strains downloaded in the public database and the actual drug susceptibility phenotype results and predicted drug susceptibility phenotype results (right half).
FIG. 4 is a graph of the correspondence between the detected results (left half) of the signature gene mutation sites for the methicillin Lin Yaomin phenotype prediction in staphylococcus aureus strains downloaded in the public database (right half) and the actual and predicted drug sensitive phenotype results.
FIG. 5 is a graph of the correspondence between the detected results (left half) of the signature gene mutation sites for the benzoimidazole Lin Yaomin phenotype prediction in the staphylococcus aureus strains downloaded in the public database (right half) and the actual drug sensitive phenotype results and the predicted drug sensitive phenotype results.
FIG. 6 is a graph of the correspondence between the detected results (left half) of the signature gene mutation sites for the prediction of the cyclopropane Sha Xingyao-sensitive phenotype in staphylococcus aureus strains downloaded in the public database (right half) and the actual and predicted drug-sensitive phenotype results.
FIG. 7 is a graph showing the correspondence (left half) between the detected results (left half) of the characteristic gene mutation sites for penicillin drug susceptibility phenotype prediction in Staphylococcus aureus strains downloaded in the public database, and the actual drug susceptibility phenotype results and predicted drug susceptibility phenotype results.
Detailed Description
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 apparent that the described embodiments are only some embodiments of the present invention, not all embodiments, and that all other embodiments obtained by persons of ordinary skill in the art without making creative efforts based on the embodiments in the present invention are within the protection scope of the present invention.
The invention relates to a characteristic gene combination for predicting drug sensitivity phenotype of staphylococcus aureus to antibiotics, wherein the antibiotics are one or a combination of more of cefoxitin, clindamycin, erythromycin, methicillin, oxacillin, ciprofloxacin and penicillin,
the characteristic gene combination of the staphylococcus aureus on the phenotype of the cefoxitin Ding Yaomin is predicted to comprise mecA and mecI, the genes are detected simultaneously, and if the detection results are negative, the sensitivity is presumed; if any gene detection result is positive, the medicine resistance is presumed; and/or
The characteristic gene combination for predicting the drug sensitivity phenotype of staphylococcus aureus to clindamycin comprises ErmA, ermC, ermB, detecting genes simultaneously, and if the detection results are negative, presuming that the detection results are sensitive; if any gene detection result is positive, the medicine resistance is presumed; and/or
The characteristic gene combination for predicting the erythromycin drug sensitivity phenotype of staphylococcus aureus comprises ErmA, ermC, msrA, ermB, ermT, detecting genes simultaneously, and if the detection results are negative, presuming that the staphylococcus aureus is sensitive; if any gene detection result is positive, the medicine resistance is presumed; and/or
Predicting that the characteristic gene of staphylococcus aureus on the phenotype of methicillin Lin Yaomin is mecA, and if the detection results are negative, presuming that the staphylococcus aureus is sensitive; if the detection result is positive, the medicine resistance is presumed;
predicting that the characteristic gene of staphylococcus aureus on the phenotype of oxaziclomex Lin Yaomin is mecA, and if the detection results are negative, presuming that the staphylococcus aureus is sensitive; if the detection result is positive, the medicine resistance is presumed;
the characteristic gene mutation site combination for predicting the phenotype of staphylococcus aureus on cyclopropyl Sha Xingyao is Sta_parC 239 (C- > T), sta_parC 239 (C- > A), sta_gyrA 251 (C- > T) and Sta_gyrA 250 (T- > G), and if the detection results are negative, the detection results are presumed to be sensitive; if the detection result is positive, the medicine resistance is presumed; and/or
The characteristic genes of the staphylococcus aureus for predicting the penicillin drug sensitivity phenotype are blaZ and mecA, and if the detection results are negative, the detection results are presumed to be sensitive; if the detection result is positive, the drug resistance is presumed.
A kit comprising the above-described gene combination assay reagent for predicting the antibiotic susceptibility phenotype of staphylococcus aureus.
The kit is used for carrying out drug sensitive phenotype sequencing on staphylococcus aureus, and a whole genome sequencing method or a metagenome sequencing method is adopted.
The invention is described in detail below in connection with specific detection methods and effect comparisons:
example 1 prediction of the drug susceptibility phenotype of Staphylococcus aureus in public databases Using feature combinations
1.1 data collection: the 2946 strain staphylococcus aureus genome information and the corresponding antibiotic susceptibility phenotype data are downloaded from public databases (NCBI NDARO database and PATRIC database). Wherein, cefoxitin (English abbreviation cefoxitin) drug-resistant strain 702 and sensitive strain 201; clindamycin (English abbreviation clindamycin) resistant strain 333 and sensitive strain 555; erythromycin (english abbreviation erythromycin) resistant strain 726, susceptible strain 1283; methicillin (english abbreviation methicillin) resistant strain 949, susceptible strain 694; oxacillin (english abbreviation oxacilin) resistant strain 75, sensitive strain 368; ciprofloxacin (english abbreviation ciprofloxacin) resistant strain 764, sensitive strain 958; penicillin (penicillin) resistant strain 900 and sensitive strain 138.
1.2 drug resistance gene and mutation detection: the assembled genomic sequence was aligned with the drug resistance database using ncbi-blast (v2.9.0+) software (parameters: -value 1e-5-outfmt 0-num_alignments 10000) and the drug resistance gene and mutation site detection described above were performed. The presence or absence of a gene is considered to be detected if the alignment agreement with the reference sequence of the drug-resistant gene is higher than 90% and the coverage is higher than 60%. For the characteristics of a mutation in a gene, the mutation is considered to be detected if the sequence of the drug-resistant gene is aligned to support the mutation site.
1.3 counting the detection of drug resistance genes and mutations in each strain of Staphylococcus aureus.
1.4 prediction of drug sensitivity results: for the drug sensitivity prediction of any antibiotic of a strain, detecting any characteristic in the characteristic combination, and considering that the strain is resistant to the phenotype of the antibiotic; otherwise, judging as sensitive. As shown in fig. 1-7, in seven models of cefoxitin, clindamycin, erythromycin, methicillin, oxacillin, ciprofloxacin and penicillin, the drug susceptibility results predicted by the detected characteristics in each strain are highly consistent with the actual drug susceptibility phenotype. The predicted performance is shown in table 1, the drug sensitive phenotype accuracies of the characteristic combination predicted cefoxitin, clindamycin, erythromycin, methicillin, oxacillin, ciprofloxacin and penicillin are respectively 0.999, 0.976, 0.985, 0.990, 0.977, 0.990 and 0.982, and the specificity and the sensitivity are also at higher levels. The number of feature-detected samples, the number of phenotype-resistant samples, and the positive predictive value (positive predictive value=number of phenotype-resistant samples/number of feature-detected samples) of each drug-resistant feature are shown in table 2. The results show that the combination of the characteristics has better distinguishing effect on the phenotypic drug resistance and the phenotypic sensitivity of staphylococcus aureus.
TABLE 1 prediction of the performance of drug sensitive phenotypes of public database derived strains
TABLE 2 detection frequency of signature genes and mutations in public database derived strains
Example 2 prediction of the drug susceptibility phenotype of isolated Staphylococcus aureus in clinical specimens Using a combination of features
2.1 sample collection: 459 cases of staphylococcus aureus isolated from clinical specimens were collected from a hospital and corresponding drug sensitive results were collected. Wherein, the cefoxitin has drug resistance of 39 strains and sensitivity of 38 strains; clindamycin resistant 51 strain and sensitive 25 strain; erythromycin drug resistance 53 strains, sensitive 23 strains; oxacillin resistant 38 strains, sensitive 38 strains; ciprofloxacin resistant 15 strains and sensitive 62 strains; penicillin resistant 75 strains and sensitive 2 strains.
2.2 sample whole genome sequencing: and (3) extracting nucleic acid from the sample, after Qubit detection, confirming that the DNA can meet the subsequent sequencing requirement, and carrying out sequencing library construction and high-throughput sequencing (Illumina Novaseq 6000 PE 150) on the extracted nucleic acid.
2.3 quality control of sequencing data: the resulting raw fastq sequence data was filtered (parameter settings: -q 15-u 40-l read_length 0.67) using fastp (v0.19.5) software, removing low quality and short sequences; at the same time, the sequence information complexity (parameter settings: -F-t 0.4) was calculated using komplity (v0.3.6) software and the low complexity sequences were filtered out.
2.4 drug resistance gene detection: the reads sequence was aligned to the drug resistance gene reference sequence using blastn (version 2.9.0 +) software. For the presence or absence of the characteristic of the gene, if the reads with the alignment consistency ratio of the reference sequence higher than 90% are larger than 1, the drug-resistant gene is considered to be detected. For a gene mutation feature, if the ratio of reads supporting a mutation site is greater than 0.2 for that mutation site, the mutation is considered to be detected.
2.5 drug sensitive phenotype prediction: for the drug sensitivity prediction of any antibiotic of a strain, detecting any characteristic in the characteristic combination, and considering that the strain is resistant to the phenotype of the antibiotic; otherwise, judging as sensitive. According to the feature detection result, compared with the drug sensitivity result obtained by the clinical laboratory of the hospital, the accuracy, sensitivity and specificity are all above 0.9. The detection results are summarized in table 3. The results show that the staphylococcus aureus separated from the clinical specimens actually collected has higher accuracy, sensitivity and specificity by utilizing the corresponding characteristic combination, and the invention has higher practical value.
TABLE 3 prediction of the performance of drug sensitive phenotypes of Hospital-collected strains
Example 3 drug sensitive phenotype prediction of Staphylococcus aureus in clinical specimens Using feature combinations
3.1 sample collection: 22 clinical specimens, which were positive for Staphylococcus aureus and tested for drug sensitivity, were collected from a hospital, including sputum, alveolar lavage fluid, ascites fluid, drainage fluid, puncture fluid, secretions, and pus.
3.2 sample high throughput sequencing: DNA extraction is carried out on the sample, the quality of the DNA can meet the subsequent sequencing requirement through Qubit detection, and library construction and high-throughput sequencing (Illumina Next seq 550 SE75) are carried out on the extracted DNA.
3.3 sequencing data fingering: the resulting raw fastq sequence data was filtered (parameter settings: -q 15-u 40-l read_length 0.67) using fastp (v0.19.5) software, removing low quality sequences and too short sequences; at the same time, the sequence information complexity (parameter settings: -F-t 0.4) was calculated using komplity (v0.3.6) software and the low complexity sequences were filtered out.
3.4 human sequence removal: the clear sequence obtained by quality control filtration is compared with the ginseng genome sequence (human_38) by using bowtie2 (v2.3.4.3) software (parameter setting: minus mm- -ver-active-k 1) to filter out the human sequence.
3.5 species annotation: the Illumina reads sequence was aligned with the target pathogen reference genome sequence library set forth above (derived from NCBI genome database) using minimal ap2 software (v 2.17) (alignment parameters: -xr-a-second=no-L)), and species annotation statistics were performed using LCA algorithm, and finally the number of sequences and genome coverage of staphylococcus aureus were statistically detected.
3.6 drug resistance feature detection: the reads sequence was aligned to the drug resistance gene reference sequence using blastn (version 2.9.0 +) software. For the presence or absence of the characteristic of the gene, if the reads with the alignment consistency ratio of the reference sequence higher than 90% are larger than 1, the drug-resistant gene is considered to be detected. For the mutation characteristics of the drug-resistant gene, if the ratio of reads supporting a mutation site is greater than 0.2 for the mutation site, the mutation is considered to be detected.
3.7 drug sensitive phenotype prediction: the drug susceptibility phenotype of staphylococcus aureus in clinical specimens to each antibiotic was predicted using the feature combinations of each antibiotic described in 2.1. For one antibiotic, if any important characteristic is detected, the staphylococcus aureus is considered to be resistant to the antibiotic; otherwise, staphylococcus aureus is sensitive to the drug. When the detected genome coverage is less than a certain proportion and no drug resistant feature is detected, no prediction can be given because it is not possible to determine whether the feature is present (the feature may be present in an uncovered area). Table 4 shows the statistical results of the partial clinical specimens:
TABLE 4 detection information of partial clinical specimens
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"/" indicates that no prediction of drug-sensitive phenotype is possible with current genome coverage.
Genome coverage represents the ratio of the number of bases of the reference genome to the number of total bases of the reference genome in the data obtained by metagenome sequencing, which is attributed to the reads alignment of staphylococcus aureus. As can be seen from Table 5, by using the above preferred feature combinations, the drug-sensitive phenotype of Staphylococcus aureus in most clinical specimens to seven antibiotics can be predicted by using the metagenomic sequencing method, and the accuracy is high, which indicates that the invention has higher application value in assisting the treatment of Staphylococcus aureus infection.
TABLE 5 prediction of the performance of drug sensitive phenotypes of Staphylococcus aureus in clinical specimens using a preferred combination of features
The above-described embodiments are only for illustrating the technical spirit and features of the present invention, and it is intended to enable those skilled in the art to understand the content of the present invention and to implement it accordingly, and the scope of the present invention is not limited to the embodiments, i.e. equivalent changes or modifications to the spirit of the present invention are still within the scope of the present invention.
Claims (2)
1. Use of a reagent for detecting a characteristic gene combination consisting of mecA and mecI in the preparation of a kit for predicting the drug resistance and sensitivity of staphylococcus aureus to cefoxitin Ding Nai; simultaneously detecting all the characteristic genes of the combination, and if the detection results are negative, presuming that the combination is sensitive; if any characteristic gene detection result is positive, the medicine is presumed to be drug-resistant.
2. Use of a reagent for detecting a characteristic gene combination consisting of mecA and blaZ for the preparation of a kit for predicting resistance and sensitivity of staphylococcus aureus to penicillin; simultaneously detecting all the characteristic genes of the combination, and if the detection results are negative, presuming that the combination is sensitive; if any characteristic gene detection result is positive, the medicine is presumed to be drug-resistant.
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| 91株金黄色葡萄球菌毒力基因和耐药基因分布研究;王冬梅;刘传桂;梁晓静;欧阳德宏;;检验医学与临床(第14期);摘要 * |
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