Predictive comparative antibiotic resistance (AMR) profiles of rhizobacteria genes using CARD: a bioinformatics approach

  • Micheal A
  • Catherine O
  • Adenike A
  • et al.
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Abstract

Members of the Plant Growth Promoting Rhizobacteria (PGPR) have been severally implicated as excellent growth enhancers, yield promoters as well as bio-fertilizers. A study on antibiotics surveillance of PGPR is urgently needed as caution towards its continued usage in Bio-science and Agro-allied. Antimicrobial resistance has become a great concern in agriculture and public health. The detection and characterization of antimicrobial resistance move from targeted culture and enzyme-based reaction to high-throughput metagenomics; acceptable resources for the analysis of large-scale information area unit as an expected rescue. The excellent bioinformatics tool newly curated for Antibiotic Resistance information (CARD; https://card.mcmaster.ca) could be a curated hub and resource-providing-referenced server for deoxyribonucleic acid and protein sequences as well as detection models on the molecular radar for antimicrobial resistance. This study employed CARD as pathogenomics repertoires for high-quality reference information on retrieving antibiotics resistance information on twenty-two carefully-selected members of Rhizobacter from NCBI. NCBI and CARD on-line platform were employed in polishing of antiobitics resistance info of selected PGPR genera such as Leguminosarum, Azotobacter, Azospirillum, Erwinia, Mesorhizobium, Flavobacterium Paenibacillus Polymyxa, Bacilli mycoides, B. subtilis, and Burkholderia pseudomallei among others. The data generated showed evidence that these rhizobacteria could be resistant to certain drug classes under a different Antimicrobial Resistance (AMR) Gene families using different phyto-pathogenic genes (ARO terms) using different resistance mechanisms. This distinctive platform provides bioinformatics tool that bridges antibiotic resistance considerations, which could be a fallback for policies in healthcare, agriculture and the environment.

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APA

Micheal, A. O., Catherine, O. A., Adenike, A. K., Adeola, A. O., Adedamola, A. B., & Ademola, A. D. (2020). Predictive comparative antibiotic resistance (AMR) profiles of rhizobacteria genes using CARD: a bioinformatics approach. Highlights in BioScience. https://doi.org/10.36462/h.biosci.20223

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