CN113308467A - Novel penA resistance gene of beta-lactam antibiotics and application thereof - Google Patents
Novel penA resistance gene of beta-lactam antibiotics and application thereof Download PDFInfo
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- CN113308467A CN113308467A CN202110800058.4A CN202110800058A CN113308467A CN 113308467 A CN113308467 A CN 113308467A CN 202110800058 A CN202110800058 A CN 202110800058A CN 113308467 A CN113308467 A CN 113308467A
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Abstract
The invention relates to a resistance gene of beta-lactam antibiotics and application thereof, and particularly discloses a novel resistance gene penA _ like of beta-lactam antibiotics and application thereof, wherein the sequence of the penA _ like gene is shown as SEQ ID No. 1. Through sequence similarity alignment, no known resistance gene is found on the genome. The invention also discloses a detection method of the gene. The invention provides help for understanding the drug resistance mechanism of the beta-lactam antibiotics and supplementing a drug resistance database, provides theoretical support for later resistance to the beta-lactam antibiotics, provides a target for solving the problem of the drug resistance of the beta-lactam antibiotics and lays a foundation for research on the resistance to bacteria.
Description
Technical Field
The invention relates to the technical field of biology, in particular to a resistance gene of beta-lactam antibiotics and application thereof.
Background
The beta-lactam antibiotics have a typical beta-lactam ring in chemical structure, and mainly comprise cephalosporins, penicillins, penems, oxapenems, monocyclic beta-lactam antibiotics and the like. The action mechanisms of various beta-lactam antibiotics are similar, cell wall mucopeptide synthesis can be hindered by inhibiting cell wall mucopeptide synthetase, and thalli are cracked and die due to cell wall defect. The major resistance mechanisms include: beta-lactamase hydrolyzes antibiotics, beta-lactamase binds to antibiotics, target proteins have reduced affinity for antibiotics, cell wall or outer membrane permeability changes, and the like.
Hidden Markov Models (HMM) based on probability can determine implicit parameters of the process from observable parameters, are often used for supplementing gene annotation and gene prediction in the field of research of Antibiotic Resistance Genes (ARGs), and have potential for developing potential novel genes. Traditional gene annotation is usually set by means of a threshold value of sequence similarity, but the method limits the discovery of novel genes and has certain limitation on the annotation of ARGs. The HMM model-based database widely applied at home and abroad comprises Pfam, TIGERFAM, Resfam and the like, and plays a vital role in comprehensively analyzing and mining the ARGs.
The ARGs-OAP is an online ARGs analysis platform, can realize the rapid annotation and quantification of the ARGs of metagenome data, and the database (Structured biological Resistance genes, SARG) contained in the ARGs-OAP integrates two large ARGs databases, namely ARDB and CARD, and lays a solid foundation for the comprehensive analysis of the ARGs by classifying and annotating the ARGs sequences step by step. On the basis of an SARG database, the platform establishes a database SARGfam based on model comparison by applying an HMM model construction method, and can be used for developing potential novel resistance genes.
Disclosure of Invention
Aiming at the background technology, the invention aims to provide a resistance gene of beta-lactam antibiotics and application thereof, and the invention discovers a novel resistance gene penA _ like of the beta-lactam antibiotics from a strain of Labrys (without corresponding Chinese name), supplements a database of beta-lactam antibiotic resistance and lays a solid foundation for deep research on bacterial resistance.
In order to achieve the purpose, the invention adopts the technical scheme that:
the first aspect of the invention provides a resistance gene of beta-lactam antibiotics, the gene sequence of which is shown in SEQ ID No.1 and is named as penA _ like gene.
The second aspect of the invention provides the use of a penA-like gene inhibitor for the manufacture of a product for reducing resistance of a subject to a beta-lactam antibiotic.
The third aspect of the invention provides the application of the reagent for detecting the SEQ ID No.1 sequence in the preparation of a kit for detecting the drug resistance of the beta-lactam antibiotics, and further, the reagent for detecting the SEQ ID No.1 sequence is constructed by qualitatively or quantitatively detecting the SEQ ID No.1 sequence by using a PCR method.
The fourth aspect of the present invention is to provide the use of a penA _ like gene as a target gene for increasing the sensitivity of a subject to a beta-lactam antibiotic.
The fifth aspect of the invention is to provide a method for detecting beta-lactam antibiotic drug resistance, further, detecting beta-lactam antibiotic drug resistance based on SEQ ID No.1 sequence information, wherein the method is not used for diagnosis.
In the technical scheme of the invention, the beta-lactam antibiotics comprise cephalosporin antibiotics, penicillin antibiotics, penem antibiotics, oxapenem antibiotics and monocyclic beta-lactam antibiotics.
The technical scheme has the following advantages or beneficial effects:
the invention provides a novel resistance gene penA _ like of beta-lactam antibiotics and application thereof, wherein the sequence of the penA _ like gene is shown as SEQ ID No. 1. Through sequence similarity alignment, no known resistance gene is found on the genome. The invention provides help for understanding the drug resistance mechanism of the beta-lactam antibiotics and supplementing a drug resistance database, provides theoretical support for later resistance to the beta-lactam antibiotics, provides a target for solving the problem of the drug resistance of the beta-lactam antibiotics and lays a foundation for research on the resistance to bacteria.
Drawings
FIG. 1 is a phylogenetic tree diagram between the penA _ like gene and a known reference gene sequence in example 1, which is used to describe the degree of difference between the penA _ like gene sequence and the known reference sequence.
Detailed Description
The following examples are only a part of the present invention, and not all of them. Thus, the detailed description of the embodiments of the present invention provided below is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the invention without making creative efforts, belong to the protection scope of the invention.
Example 1:
1. prediction of Open Reading Frame (ORF) of genome
And (3) applying prodigal software to perform ORF prediction on the pure bacterial genome obtained by subpackaging to obtain an ORF file of the genome.
2. HMM-based model alignment
And (3) comparing the ORF file obtained in the step (1) with a SARGfam database by using a hmmmscan function in HMMER software (parameter setting: -cut _ ga-tblout) to obtain an ORF annotation result based on model comparison. The alignment results are shown in Table 1.
TABLE 1
| Target name | Query id | E-value | sore | Bias |
| beta_lactam__penA_train_msa | 1_4089 | 1.9e-12 | 420.1 | 0.0 |
3. Sequence similarity based alignment
And (3) comparing the ORF file obtained in the step (1) with a SARG database by using blastp (parameter setting: evalue 1e-10-max _ target _ seqs 1), and obtaining an ORF annotation result based on sequence similarity. The alignment results are shown in Table 2.
TABLE 2
4. Identification of potentially novel resistance genes
(ii) defining as true the annotation result for the ORF with sequence similarity higher than 70% and coverage higher than 65% in the result of step 3, i.e. known ARGs, whereas an ORF not meeting the threshold is defined as a potential novel gene if there is an annotation result in step 2; if an ORF is not annotated as ARG after alignment based on sequence similarity, but is annotated as ARG in the alignment results of HMM model, the ORF is also considered as a potential novel gene. Through screening, the pure bacterial genome is found to have a potential novel beta-lactam antibiotic resistance gene penA _ like. The method comprises the steps of carrying out multiple sequence comparison on a reference sequence corresponding to a penA gene in an SARG database and a penA _ like gene sequence by utilizing ClustalW, constructing a maximum likelihood phylogenetic tree by using MEGA, resampling 1000 times by using a bootstrap method to evaluate a topological structure of the tree, and further determining the difference degree between the potential novel gene penA _ like and a known reference gene sequence (as shown in figure 1).
Example 2
After a strain containing the penA-like gene is purified and separated, and the minimum inhibitory concentration MIC value of the strain to the beta-lactam antibiotic is detected, the MIC value of the strain to the beta-lactam antibiotic is up to 100mg/L, which indicates that the penA-like gene enables the strain to have resistance to the beta-lactam antibiotic, and the penA-like gene is the drug resistance gene of the beta-lactam antibiotic.
The above description is only for the preferred embodiment of the present invention and is not intended to limit the scope of the present invention, and all equivalent modifications made by the contents of the present specification and the drawings, or applied directly or indirectly to other related technical fields, are included in the scope of the present invention.
SEQUENCE LISTING
<110> Shenzhen International institute for graduate of Qinghua university
Novel penA resistance gene of <120> beta-lactam antibiotics and application thereof
<130> CP121010588C
<160> 1
<170> PatentIn version 3.3
<210> 1
<211> 2214
<212> DNA
<213> Labrys
<400> 1
atgaccgagt tcaagaatcc ccagcaacaa ctgcagacgt ttcatctgcg gatcacagcg 60
gctgcatttt tcgtgctgat ctgctttggc ctgctcggcg tacgcttcgt ctacctgcag 120
gtcttccgcc ataaccagta cgcgctgcaa gccgacgaga atcgcgtctc gctcgcgccg 180
atcgtgccca accggggcgt gatcatggat cgcaacggcg tggtgctcgc gcgcaattat 240
tccgcttaca cgctggaaat cacgccgtcg aagatcggcc gtccgctgga agatctcatc 300
accgatctgt ccgacgtgat cgagatcacg ccgcgcgacc gcgcccgctt caagaagctc 360
atggacgaca gcaagagctt cgagagcctg ccgatccgca cgcgcctgac cgacgaggaa 420
gtcgcgcgct tcaccgcgca gcgcttccgc tttcccggcg tggatgtgca cgcgcggctc 480
ttccgtcagt acccgctggg cgagaccgcc gcgcacgtga tcggctacat cggccggatc 540
tcgcagcgcg atcgccagcg gatcgaggcg atgagcgaag agaacgacag cgacagcgcc 600
aagtacgaca tccgccgcga cgtcaacaac tacaagggca ccgattacat cggcaagatc 660
ggcgtcgagc agagctacga gacgcagctc cacggcatca ccggtttcga ggaaatcgaa 720
gtcaccgccg gtggccgccc ggtgcgcacg atctcgcgca ccccggccac gcccggcgac 780
aatctggtgc tgtcgctcga catcaagctc cagcaagtgg ccgagcaagc gttcgccggg 840
cggcgcggcg ccgtcgtggc gatcgagccg aagacgggcg acgtgctggc gttcgtctcg 900
gcaccgagct tcgatccgaa catgttcgtc gaagggatcg accagcaaaa ctgggacgcc 960
ctgaacaatt cgcccgaccg gcctttgctc aaccgcccct tgcgcggcac ctatccgatc 1020
ggctcgacgt acaagccgtt catggcgctc gccgcgctcg aactgggcaa gcgcaccacg 1080
agctggggct tccaggacac gggcgcgttc acactcggga accatacgtt ccgcaacgac 1140
gttcgcaacg gccagggctg gatcgacatg taccgttcga tcgtggtgtc gaacgacacg 1200
tattactaca tgctcgcgca cgatctcggc gtgaacgcca ttcacgactt catggcgccg 1260
ctcggcttcg gtcagctgac gggcatcgac atcgaaggcg aggcgcgcgg cattctgccg 1320
tcgaccgaat ggaagcgcaa ggcgtacaag aagcccgcgc agcagaagtg gtacgacggc 1380
gagacggtca gtctgggcat cgggcaaggc tacaactcgt tcacgatcct gcaacttgcg 1440
cacgcgacgg ccacgctggc caacaacggc gtagtgatga agcctcacct ggtgaaggcc 1500
atcgaagatc ccgtcacgca cgcacgccag ctcaccgtgc cgcacgaaag cgcgcggctg 1560
ccctacaagc aggcgaacat cgatttcgtc aaacgcgcga tggtcggggt gatcaaggaa 1620
ggcaccggcc gtcaggcatt cgcgggcgcg ccgtacgagg ccggtggcaa gaccggcacg 1680
gcgcaggtct actcgctcgg caagaacgaa aagtacaacc acaacgccat ccccgaattc 1740
aaacgcgatc atgccttgtt catcgctttc gcccccgccg acgatccgaa gatcgccgtc 1800
gcgctgatcg tcgagaacgc gggatggggc gccgcacaag ccggtccggt cgcgcgtcgt 1860
ctgctcgact actacctcat cgacgagccg aaggagcgcg ccgccgaagc ggcggcgttg 1920
caagcggccg cttcggctcc gggggcggca tcgggcgtct cggccgtgtc cgccacaccg 1980
gatgccgccc ccgccagcgc cgccgaactg agcgggcgca cgaccgtggc acgcgtcgcc 2040
ccggtcgcgt ccaacgcgac ggcgagcgta tcgcgtaccg ccgacggcaa ggcttccgct 2100
gccggtgcac cgaagcccgc cccggtgccg catcgtcagc cggctgtgag tccgaccgtc 2160
gccgacgaag ctcgccatcg cgcggccatt cgcgcgcaag gaggaacgcc atga 2214
Claims (10)
1. The resistance gene of beta-lactam antibiotics is characterized in that the gene sequence is shown in SEQ ID No.1 and is named as penA _ like gene.
2. The gene of claim 1, wherein the beta-lactam antibiotic comprises a cephalosporin antibiotic, a penicillin antibiotic, a penem antibiotic, an oxapenem antibiotic, or a monobactam antibiotic.
Use of a inhibitor of penA-like gene expression for the preparation of a product for reducing the resistance of a subject to a beta-lactam antibiotic.
4. The application of the reagent for detecting the SEQ ID No.1 sequence in the preparation of the kit for detecting the drug resistance of the beta-lactam antibiotics.
5. The use according to claim 4, wherein the reagent for detecting the sequence of SEQ ID No.1 is a reagent constructed by qualitative or quantitative detection of the sequence of SEQ ID No.1 by a PCR method or a QPCR method.
Use of a penA-like gene as a target gene for increasing the sensitivity of a subject to a beta-lactam antibiotic.
7. The use according to any one of claims 3 to 6, wherein the beta-lactam antibiotic comprises a cephalosporin antibiotic, a penicillin antibiotic, a penem antibiotic, an oxapenem antibiotic, a monobactam antibiotic.
8. A method for detecting drug resistance of beta-lactam antibiotics is characterized in that the drug resistance of the beta-lactam antibiotics is detected based on SEQ ID No.1 sequence information.
9. The method of claim 8, wherein the method is not for diagnostic purposes.
10. The method of claim 8, wherein the beta-lactam antibiotic comprises a cephalosporin antibiotic, a penicillin antibiotic, a penem antibiotic, an oxapenem antibiotic, a monobactam antibiotic.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643758A (en) * | 2021-09-22 | 2021-11-12 | 华南农业大学 | Prediction method for obtaining beta-lactam drug resistance resistant gene facing enterobacter |
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| US20110245105A1 (en) * | 2008-12-08 | 2011-10-06 | Yissum Research Development Company Of The Hebrew University Of Jerusalem | Methods and Kits for Direct Detection and Susceptibility Profiling of Beta-Lactam Resistant Bacteria |
| US20120071336A1 (en) * | 2010-06-02 | 2012-03-22 | Medical Diagnostic Laboratories, Llc | Antibiotic resistance profile for Neisseria gonorrhoeae and use of same in diagnosis and treatment of gonorrhea |
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2021
- 2021-07-13 CN CN202110800058.4A patent/CN113308467A/en active Pending
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|---|---|---|---|---|
| US20110245105A1 (en) * | 2008-12-08 | 2011-10-06 | Yissum Research Development Company Of The Hebrew University Of Jerusalem | Methods and Kits for Direct Detection and Susceptibility Profiling of Beta-Lactam Resistant Bacteria |
| US20120071336A1 (en) * | 2010-06-02 | 2012-03-22 | Medical Diagnostic Laboratories, Llc | Antibiotic resistance profile for Neisseria gonorrhoeae and use of same in diagnosis and treatment of gonorrhea |
| CN103645273A (en) * | 2013-12-12 | 2014-03-19 | 佟雪梅 | Method and system for detecting drug resistance of beta-lactam antibiotics and application of beta-lactam antibiotics |
| CN108491692A (en) * | 2018-03-09 | 2018-09-04 | 中国科学院生态环境研究中心 | A method of structure antibiotics resistance gene database |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113643758A (en) * | 2021-09-22 | 2021-11-12 | 华南农业大学 | Prediction method for obtaining beta-lactam drug resistance resistant gene facing enterobacter |
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