A Computational Systems Biology Approach for the Identification of Antimicrobial Resistance Genes in Staphylococcus aureus

Md Imran Hasan

Document Type

Conference Proceeding

Publication Date

2024

Abstract

Staphylococcus aureus is a formidable pathogen that poses a significant threat in both community and hospitals, causing substantial illness and fatalities. Its capacity to colonize various hosts, as well as its ability to develop antibiotic resistance, makes it a persistent concern in healthcare. To gain a deeper understanding of the mechanisms underlying antibiotic resistance in S. aureus, we constructed an interaction network involving 378 antimicrobial-resistant genes across diverse strains. To elucidate the molecular intricacies of antimicrobial resistance, we employed hub gene analysis and functional enrichment assessments in Antimicrobial Resistance (AMR) gene networks. We find that a majority of the hub genes within the network were associated with antibiotic inactivation, efflux pumps, and resistance to common antibiotics like Tetracycline and Vancomycin. Our findings contribute to the understanding of antimicrobial resistance in S. aureus, potentially informing the development of new drugs to address this evolving public health concern.

Comments

Studies in Biology
BLH 262

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