An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis

Moraxella catarrhalis is a symbiotic as well as mucosal infection-causing bacterium unique to humans. Currently, it is considered as one of the leading factors of acute middle ear infection in children. As M. catarrhalis is resistant to multiple drugs, the treatment is unsuccessful; therefore, innovative and forward-thinking approaches are required to combat the problem of antimicrobial resistance (AMR). To better comprehend the numerous processes that lead to antibiotic resistance in M. catarrhalis, we have adopted a computational method in this study. From the NCBI-Genome database, we investigated 12 strains of M. catarrhalis. We explored the interaction network comprising 74 antimicrobial-resistant genes found by analyzing M. catarrhalis bacterial strains. Moreover, to elucidate the molecular mechanism of the AMR system, clustering and the functional enrichment analysis were assessed employing AMR gene interactions networks. According to the findings of our assessment, the majority of the genes in the network were involved in antibiotic inactivation; antibiotic target replacement, alteration and antibiotic efflux pump processes. They exhibit resistance to several antibiotics, such as isoniazid, ethionamide, cycloserine, fosfomycin, triclosan, etc. Additionally, rpoB, atpA, fusA, groEL and rpoL have the highest frequency of relevant interactors in the interaction network and are therefore regarded as the hub nodes. These genes can be exploited to create novel medications by serving as possible therapeutic targets. Finally, we believe that our findings could be useful to advance knowledge of the AMR system present in M. catarrhalis.

Automated summary

Moraxella catarrhalis is a unique bacterium in humans, acting as a symbiotic organism while also causing mucosal infections. It is a major contributor to acute middle ear infections in children, and its resistance to multiple drugs poses a challenge in treatment. This study used a computational approach to understand the processes leading to antibiotic resistance in M. catarrhalis by analyzing 12 strains from the NCBI-Genome database. The study found 74 antimicrobial-resistant genes and explored their interaction network, revealing their involvement in antibiotic inactivation, target replacement, alteration, and efflux pump processes. Several genes, such as rpoB, atpA, fusA, groEL, and rpoL, were identified as potential therapeutic targets for novel medications. Overall, this study provides valuable insights into the antimicrobial resistance system of M. catarrhalis.