Effect of Non-Antibiotic Pollution in Farmland Soil on the Risk of Antibiotic Resistance Gene Transfer

The widespread use of antibiotics, combined with pervasive exposure to diverse environmental media, has intensified the global challenge of antibiotic resistance. Accumulating evidence reveals that beyond direct antibiotic pressure, residual non-antibiotic chemicals—despite lacking intrinsic antibacterial activity—can significantly promote the enrichment and spread of antibiotic resistance genes (ARGs) in farmland soils through indirect mechanisms such as inducing oxidative stress, altering microbial community structure, and enhancing both vertical and horizontal gene transfer. To address this issue, the present study investigates the influence of representative non-antibiotic contaminants commonly detected in agricultural environments—including pesticides (e.g., Omethoate, imidacloprid, and atrazine), industrial pollutants (e.g., PCB138, BDE47, benzo [a] pyrene, 2,3,7,8-tetrachlorodibenzo-p-dioxin [TCDD], and benzene), plastic-associated compounds (e.g., Polyethylene trimer, phthalates, and tributyl acetylcitrate), and ingredients from personal care products (e.g., triclosan and bisphenol A)—on ARG transmission dynamics. Leveraging bioinformatics resources such as the CARD database, PDB, AlphaFold, and molecular sequence analysis tools, we identified relevant small-molecule ligands and macromolecular receptors to construct a simulation system modeling ARG transfer pathways. Molecular docking and molecular dynamics (MD) simulations were then implemented, guided by a Plackett–Burman experimental design, to systematically evaluate the impact of individual and co-occurring pollutants. The resulting data were processed using advanced analytical tools, and MD trajectories were interpreted at the molecular level across three scenarios: an unperturbed (blank) system, single-pollutant exposures, and dual-pollutant combinations. By integrating computational simulations with machine learning approaches, this work uncovers the “co-selection” effect exerted by non-antibiotic chemical residues in shaping the environmental resistome, thereby providing a mechanistic and scientific basis for comprehensive risk assessment of agricultural non-point source pollution and the development of effective soil health management and antimicrobial resistance containment strategies.