antimicrobial resistance
Definition
Antimicrobial resistance (AMR) is the ability of microorganisms—bacteria, viruses, fungi, and parasites—to survive exposure to antimicrobial agents that would normally kill them or inhibit their growth. This phenomenon arises through genetic mutations or acquisition of resistance genes via horizontal gene transfer. AMR represents a critical global health threat, rendering standard treatments ineffective and leading to persistent infections, increased mortality, and healthcare costs. Key mechanisms include enzymatic drug inactivation, altered drug targets, reduced membrane permeability, and efflux pump overexpression. Understanding AMR requires analyzing complex interactions between resistance genes, regulatory pathways, environmental factors, and microbial evolution. The emergence and spread of multidrug-resistant organisms necessitates systems-level approaches to identify novel therapeutic targets and develop alternative treatment strategies.
Visualize antimicrobial resistance in Nodes Bio
Researchers can map AMR gene networks showing relationships between resistance determinants, mobile genetic elements, and host bacterial species. Visualize regulatory pathways controlling resistance gene expression, identify critical nodes in horizontal gene transfer networks, and analyze co-occurrence patterns of resistance genes across clinical isolates. Network analysis reveals potential targets for combination therapies and predicts resistance emergence pathways.
Visualization Ideas:
- Resistance gene co-occurrence networks across bacterial strains
- Regulatory networks controlling efflux pump and resistance gene expression
- Horizontal gene transfer networks showing plasmid-mediated resistance spread
Example Use Case
A research team investigating carbapenem-resistant Enterobacteriaceae constructs a network linking carbapenemase genes (blaKPC, blaNDM, blaOXA-48) with their plasmid vectors, transposable elements, and regulatory proteins. By integrating clinical surveillance data across hospitals, they identify key transmission hubs and high-risk plasmid types. Network centrality analysis reveals that targeting specific transcriptional regulators could simultaneously suppress multiple resistance mechanisms, guiding development of adjuvant therapies that restore antibiotic susceptibility.