Computational Analysis of Acquired Antimicrobial Resistance Genes in Mycobacterium Plasmid

Abstract

Mycobacterium species are becoming an increasing health challenge worldwide due to antimicrobial resistance (AMR). Although chromosomal mutations are well characterized, not much is known about the contribution of acquired AMR genes acquired via plasmids in this genus. In this study, a computational pipeline was used to examine acquired AMR genes in plasmids in both pathogenic Mycobacterium species. Out of 195 species, 51 species were identified to be pathogenic; 18 of which harbored a total of 301 plasmids that were obtained in NCBI nucleotide database. The acquired AMR genes in all plasmids were screened with ResFinder 4.0, which was designed to screen 15 antibiotic classes. The resistance hits of plasmids were additionally analysed with KmerResistance and ResFinderFG, and such basic genomic characteristics as size and GC content were analysed. The detection of acquired AMR genes was done by comparative sequence analysis with the help of BLAST and MEGA X by detecting three plasmids, which were parts of the Mycobacterium abscessus complex, and contained a total of 15 resistance genes. These plasmids contained a high GC content (64.25-64.3 percent), which was quite similar to that of their host genome, hence indicating adaptation. Comparison of sequences showed that there was close relatedness between the resistance plasmids, which was in line with recent divergence and horizontal gene transfer in the complex. Even though a small proportion of Mycobacterium plasmids already harbor acquired AMR genes, the genes are in clinically relevant, hard-to-treat species, and thus, genomic surveillance and wise antibiotic intake are still necessary.