Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence
Abstract Background The continuous increase in the resistance of pathogenic bacteria to antimicrobial agents elicits a source of concern for public health. Developing a method that allows for swift evaluation of the antibiotic sensitivity profile of bacteria is a major leap in antimicrobial research...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-08-01
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| Series: | Bulletin of the National Research Centre |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42269-022-00922-w |
| _version_ | 1798042571436457984 |
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| author | Olamide Joshua Babatunde Ayomide Faith Okiti Michael Tosin Bayode Samson Oloruntola Babatunde Ayo Mercy Olaniran |
| author_facet | Olamide Joshua Babatunde Ayomide Faith Okiti Michael Tosin Bayode Samson Oloruntola Babatunde Ayo Mercy Olaniran |
| author_sort | Olamide Joshua Babatunde |
| collection | DOAJ |
| description | Abstract Background The continuous increase in the resistance of pathogenic bacteria to antimicrobial agents elicits a source of concern for public health. Developing a method that allows for swift evaluation of the antibiotic sensitivity profile of bacteria is a major leap in antimicrobial research and could be one of the deciding factors in providing a lasting solution to antimicrobial resistance. The gradual and continuous reduction in the cost and turnaround time of whole-genome sequencing (WGS) has enabled scientists to develop WGS-based antimicrobial susceptibility testing using computational methods. The genes present on the ResFinder database were blasted against the WGS of the bacterial isolates obtained from NCBI database, and the best-matching genes were automatically generated by the system. Results Antimicrobial resistance genes were detected from the strains tested though not innate, thereby suggesting that they must have been acquired through horizontal gene transfer. Additionally, it was revealed that specific genes confer resistance to specific group of antibiotics. Conclusion The in silico method of antimicrobial resistance research provides for easy interpretation and reproducibility of results thereby reducing the cost and time utilized. |
| first_indexed | 2024-04-11T22:37:22Z |
| format | Article |
| id | doaj.art-08d05f5fe66840a3ba31b5d46b5090f5 |
| institution | Directory Open Access Journal |
| issn | 2522-8307 |
| language | English |
| last_indexed | 2024-04-11T22:37:22Z |
| publishDate | 2022-08-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Bulletin of the National Research Centre |
| spelling | doaj.art-08d05f5fe66840a3ba31b5d46b5090f52022-12-22T03:59:11ZengSpringerOpenBulletin of the National Research Centre2522-83072022-08-014611710.1186/s42269-022-00922-wAntibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequenceOlamide Joshua Babatunde0Ayomide Faith Okiti1Michael Tosin Bayode2Samson Oloruntola Babatunde3Ayo Mercy Olaniran4Department of Microbiology, Federal University of TechnologyDepartment of Microbiology, Federal University of TechnologyDepartment of Microbiology, Federal University of TechnologyDepartment of Biochemistry, Federal University of TechnologyDepartment of Microbiology, Federal University of TechnologyAbstract Background The continuous increase in the resistance of pathogenic bacteria to antimicrobial agents elicits a source of concern for public health. Developing a method that allows for swift evaluation of the antibiotic sensitivity profile of bacteria is a major leap in antimicrobial research and could be one of the deciding factors in providing a lasting solution to antimicrobial resistance. The gradual and continuous reduction in the cost and turnaround time of whole-genome sequencing (WGS) has enabled scientists to develop WGS-based antimicrobial susceptibility testing using computational methods. The genes present on the ResFinder database were blasted against the WGS of the bacterial isolates obtained from NCBI database, and the best-matching genes were automatically generated by the system. Results Antimicrobial resistance genes were detected from the strains tested though not innate, thereby suggesting that they must have been acquired through horizontal gene transfer. Additionally, it was revealed that specific genes confer resistance to specific group of antibiotics. Conclusion The in silico method of antimicrobial resistance research provides for easy interpretation and reproducibility of results thereby reducing the cost and time utilized.https://doi.org/10.1186/s42269-022-00922-wAntimicrobial resistanceWhole-genome sequenceResistance genesResFinderResistance database |
| spellingShingle | Olamide Joshua Babatunde Ayomide Faith Okiti Michael Tosin Bayode Samson Oloruntola Babatunde Ayo Mercy Olaniran Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence Bulletin of the National Research Centre Antimicrobial resistance Whole-genome sequence Resistance genes ResFinder Resistance database |
| title | Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence |
| title_full | Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence |
| title_fullStr | Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence |
| title_full_unstemmed | Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence |
| title_short | Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence |
| title_sort | antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole genome sequence |
| topic | Antimicrobial resistance Whole-genome sequence Resistance genes ResFinder Resistance database |
| url | https://doi.org/10.1186/s42269-022-00922-w |
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