Network-Based Co-Resistance Analysis Across Six Foodborne Bacterial Pathogens: Hub Gene Identification, Horizontal Gene Transfer Potential, and Multi-Criteria Drug Target Prioritisation

Abstract

Background: Antimicrobial resistance (AMR) poses an escalating global health threat, with foodborne pathogens serving as critical vectors for multi-drug resistance (MDR) dissemination across the One Health continuum. Although individual resistance mechanisms have been extensively characterised, the systems-level architecture of cross-species AMR gene co-occurrence networks remains poorly defined.

Methods: A binary presence/absence matrix of 47 AMR genes spanning 11 drug classes was assembled from six priority foodborne pathogens that include Campylobacter jejuni, Enterococcus faecium, Escherichia coli, Listeria monocytogenes, Salmonella enterica, and Staphylococcus aureus based on a comprehensive primary literature synthesis. Jaccard similarity-based co-occurrence statistics with Bonferroni correction were applied to construct an undirected co-resistance network. Network topology metrics (degree, betweenness, closeness, and eigenvector centrality; composite hub score) were computed alongside pairwise horizontal gene transfer (HGT) potential scores. A four-component weighted algorithm incorporating hub score, pathogen breadth, chromosomal stability, and essentiality was applied for drug target prioritisation.

Results: The network comprised 47 nodes and 205 statistically significant co-occurrence edges (density = 0.190; average clustering coefficient = 0.727). Three hub genes aac6_ib_cr, acrAB, and blaSHV achieved maximal hub scores (0.238 each). The E. coli–S. enterica dyad exhibited the highest inter-species HGT potential (score = 0.692), sharing 18 mobile AMR genes including colistin resistance determinants (mcr1, mcr4) and extended-spectrum beta-lactamases. Drug target prioritisation ranked topoisomerase subunits parC and parE highest (composite score = 0.590), followed by gyrA (0.562), gyrB (0.557), and the efflux pump regulator acrAB (0.547).

Conclusion: Network-based AMR analysis identifies discrete hub genes and critical inter-species HGT axes that are obscured by species-centric approaches. The E. coli–S. enterica axis warrants priority One Health surveillance, and efflux pump inhibition combined with novel-binding-mode topoisomerase inhibitor development represents a network-informed therapeutic strategy with broad cross-pathogen applicability.

Keywords: antimicrobial resistance; co-resistance network; horizontal gene transfer; foodborne pathogens; drug target prioritisation; One Health; multi-drug resistance; network biology