Through the Ecological Looking Glass: Insights into the Wonderland of Antimicrobial Resistance

Dr. Jessica Hite - University of Wisconsin-Madison Drug‑resistant microbes are now documented in hedgehogs, bats, a wide array of non-human primates, and migratory birds, far from areas with any direct antibiotic use. The mere presence of the genes that confer antimicrobial‑resistance (AMR) in the microbiomes of wildlife is not inherently alarming; many of these genes are ancient, widespread components of environmental microbiomes. The emerging concern lies in the degree to which human activities amplify, mobilize, and redistribute these genes across ecosystems, increasing opportunities for transmission among species, habitats, and biogeographic regions. At the same time, natural systems themselves can act as long‑term reservoirs, periodically introducing novel resistance variants into livestock and clinical settings. Discoveries of AMR genes in novel or unexpected hosts and environments often prompt dramatic headlines predicting the collapse of antibiotic efficacy and a return to the pre‑antibiotic era. If such warnings hold even partially true, then understanding, and ultimately interrupting, the processes that spread resistance genes across environmental reservoirs is a critical global priority. Such insights could advance the understanding of the ecological feedbacks that modulate bacterial evolution while also revealing practical opportunities for mitigating and preventing the spread of antimicrobial resistance. Yet, despite considerable research effort, we still lack the integrated data and computational frameworks needed to mechanistically explain why some hosts and habitats consistently function as AMR “hot spots,” while others do not. We also lack a fundamental understanding of how environmental “hot spots” of ARGs and mobile genetic elements (MGEs) translate into public health risks, specifically, the potential for resistant bacteria to spread through direct (host–host) and indirect (environment–host) transmission pathways. To address these gaps in knowledge, we are taking a systems-based approach — spanning natural, agricultural, and clinical settings — to identify the ecological and evolutionary mechanisms underlying bacterial adaptation, including co-selection among resistance genes, MGEs, and pathogens.