Antibiogram profile prediction of selected bacterial strains by in silico determination of acquired antimicrobial resistance genes from their whole-genome sequence

  • Babatunde O
  • Okiti A
  • Bayode M
  • et al.
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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 reproduc-ibility of results thereby reducing the cost and time utilized.

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Babatunde, O. J., Okiti, A. F., Bayode, M. T., Babatunde, S. O., & Olaniran, A. M. (2022). 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, 46(1). https://doi.org/10.1186/s42269-022-00922-w

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