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How do anthropogenic changes affect wildlife microbiomes? [1]

['Katherine M. Lagerstrom', 'Department Of Ecology', 'Evolutionary Biology', 'Princeton University', 'Princeton', 'New Jersey', 'United States Of America', 'Andrew P. Dobson', 'Shane Campbell-Staton', 'Andrew H. Moeller']

Date: 2026-09 

Some of the most ubiquitous effects that humans have on wildlife and their associated microbiota are mediated by environmental pollution [11]. In this section, we consider pollution by chemical and material contaminants, including heavy metals, pesticides, antibiotics, pharmaceutical effluent, and other toxicants, rather than biological inputs involving the direct introduction of live microbes. Some sources of pollution, such as wastewater or domestic animal waste, can also alter microbial source pools and facilitate microbial transmission; we treat those effects as interactions between pollution and altered host contact networks.

Exposure to chemical and material pollutants can reshape the structure, stability, and physiology of host-associated microbiota [12], which in turn influences how hosts process and respond to pollutants, including through microbial biotransformation and effects on host detoxification pathways. Thus, microbiota responses to pollutants may be beneficial, harmful, or context-dependent for hosts, but the consequences of these responses remain unclear for most wildlife species. Recent evidence shows that pollution can drive both loss of beneficial microbial taxa and adaptive changes via directional selection within wildlife microbiota, with potentially profound consequences for host health, resilience, and fitness (S1 Table). Together, these findings suggest that pollution not only reshapes microbiota composition but may also erode key symbiotic relationships that support host health.

Antibiotics constitute another class of widespread pollutants that can erode co-evolved symbioses. These pollutants enter ecosystems through industrial and pharmaceutical effluent, wastewater discharge, and agricultural runoff, and are inefficiently removed by standard treatment methods, often becoming concentrated downstream [ 36 ]. Laboratory studies show that exposure of the microbiota to antibiotics drives sharp declines in taxonomic diversity as well as persistent shifts in metabolic potential and colonization resistance [ 37 – 40 ]. Laboratory zebrafish exposed to environmentally realistic levels of sulfamethoxazole and oxytetracycline display altered gut communities, increased inflammation, reduced immune enzyme activity, and impaired resistance to the pathogen Aeromonas hydrophila [ 41 ]. Tadpoles in an artificial freshwater system with antibiotic pollution experience turnover in microbiota composition, resulting in disrupted metabolism and reduced fitness [ 42 ]. Parallel findings are emerging from studies of wildlife: human disturbance alters gut microbiota structure and function in golden snub-nosed monkeys (Rhinopithecus roxellana), with disproportionate effects on Firmicutes (often associated with fiber metabolism) and little discernible impact on Proteobacteria, which can increase under conditions of host metabolic stress [ 43 ]. Similarly, wild goitered gazelles (Gazella subgutturosa) inhabiting antibiotic-contaminated areas in the Qaidam Basin exhibit reduced microbial diversity and significant compositional shifts, which may simultaneously buffer metabolic stress and heighten inflammatory risks [ 44 ].

Numerous laboratory studies demonstrate that pesticide exposure reshapes gut microbiota composition, increases gut permeability and low-grade inflammation, and can even affect host behavior through microbially derived metabolites, such as short-chain fatty acids, which influence appetite [ 25 – 29 ]. In wildlife, pesticide exposure risk is not confined to agricultural ‘hot-spots’: free-living small mammals show widespread contamination by both legacy and currently used pesticides, often at high concentrations [ 30 ]. Across host taxa, pesticide exposure perturbs microbiota [ 31 ], driving the loss of microbial diversity or turnover in microbiota composition. For instance, experimental exposure to the herbicide glyphosate at environmental concentrations drives decreases in the abundance of dominant gut bacteria in bees [ 32 ]. Pesticide-induced losses of microbiota may contribute to deleterious effects on host digestion, immunity, and development. For example, the widely used organophosphate chlorpyrifos promotes obesity and insulin resistance in mice via microbiota interactions [ 33 ]. Yet, effects may not be uniformly negative: in some contexts, altered microbiota may enhance host resilience by contributing to pesticide detoxification [ 34 ]. Moreover, the neonicotinoid imidacloprid reduces bee survival without altering microbiota [ 35 ], indicating that negative health impacts of pesticides can occur independently of microbial disruption.

Mining, nuclear accidents, and related industrial activities are major sources of environmental metal and radionuclide contamination that can alter wildlife microbiota. Tree sparrow nestlings show decreased gut microbiota diversity (alpha diversity) and increased inter-individual variation (beta diversity) in metal-polluted areas, alongside increased relative abundances of functional pathways associated with metal toxicity resistance [ 20 ]. Earthworms inhabiting arsenic-contaminated soils lose several bacterial taxa [ 21 ], and exposure to environmental concentrations of cadmium also alters earthworm gut microbiota, increasing the relative abundance of heavy-metal-resistant bacteria [ 22 ]. Similarly, wild Apodemus mice exposed to radionuclide contamination experience shifts in community composition in both general and host-specific ways, despite unchanged alpha diversity [ 23 ], suggesting pollutant-mediated loss and replacement of endogenous microbial taxa. Conversely, free-living bank voles (Myodes glareolus) exhibit higher gut microbiota diversity as well as altered community composition in metal-contaminated environments; this observation could suggest greater resistance to environmental perturbations and pathogen invasion, or reflect reduced stability or increased richness of opportunistic pathogens [ 24 ].

A wide range of environmental pollutants, including heavy metals, pesticides, and antibiotics, can alter the selective landscape experienced by microbiota within hosts, potentially driving the loss of microbiota constituents that have persisted for millions of years ( Box 1 ). These changes may reflect declines in the relative abundance of sensitive taxa or shifts in community evenness, but they may also be underlain by local extinction of symbionts from host individuals or populations, a hypothesis that warrants further study. Erosion of co-evolved symbioses critical for digestion, immunity, or development may weaken host resilience to environmental stress and reduce fitness. Reductions in microbial diversity within individual hosts, for example, can decrease colonization resistance to pathogen invasion [ 13 , 14 ]. The risks of microbiota erosion may be particularly acute in insects, where symbionts are often obligate, less diverse, and provide direct protection against pathogens and parasites [ 15 , 16 ]. In bees, for example, microbiota disruption is implicated in colony collapse disorder [ 17 ], a phenomenon with severe consequences for agriculture. Although pollutant-induced losses of microbiota are often deleterious for hosts, in some cases, they may open ecological niche space for taxa that aid pollutant detoxification ( Box 1 ). For instance, parasitic helminths that interact with the microbiota in host guts significantly reduce the concentration of environmental contaminants [ 18 , 19 ]. A major direction for future work will therefore be field- and laboratory-based tests of the phenotypic consequences of pollution-mediated reductions in microbiota diversity.

Selection for antimicrobial resistance

In addition to disrupting beneficial symbioses, antibiotic pollutants can directly select for AMR, while pesticides and heavy metals can promote AMR through co-selection mechanisms in environmental and host-associated microbial communities. Wildlife in polluted landscapes, especially near wastewater effluent, livestock operations, or urban centers, often harbor bacteria carrying clinically relevant antimicrobial resistance genes (ARGs), effectively transforming wildlife into reservoirs or amplifiers of AMR [45–47]. In these settings, pollution can influence AMR through at least two non-exclusive processes: chemical selection, in which antibiotics, heavy metals, pesticides, or other contaminants favor resistant bacteria or resistance genes; and microbial input, in which wastewater, livestock waste, or other sources introduce resistant bacteria and mobile genetic elements into environmental reservoirs encountered by wildlife. Although environmental concentrations of antibiotic pollutants are lower than those used in clinical or agricultural settings, sub-inhibitory levels can in some cases select for resistance more rapidly than full dosages [48]. Non-antibiotic pollutants can also promote AMR through co-selection, including: co-resistance, in which genes conferring resistance to antibiotics and metals or biocides are physically linked on plasmids, transposons, integrons, or other mobile genetic elements; cross-resistance, in which a single mechanism, such as a multidrug efflux pump, or reduced membrane permeability, confers tolerance to multiple compounds; and co-regulation, in which exposure to one agent triggers regulatory responses that increase tolerance to others [49]. In one in vitro study, Escherichia coli evolved resistance up to 100,000 times faster when exposed to an antibiotic–herbicide combination compared to the antibiotic alone [50]. These co-selection processes may be amplified when mobile genetic elements carrying ARGs spread among bacterial taxa through horizontal gene transfer (HGT) [51]. Together, these processes position polluted landscapes to function as interfaces where anthropogenic selection acts across wildlife microbiota and environmental reservoirs to shape the emergence, persistence, and spread of clinically relevant resistance.

Wildlife are increasingly recognized as potential reservoirs and disseminators of clinically relevant resistance [43,52–56]. The prevalence of ARGs in wildlife microbiota is strongly associated with human antibiotic use and the resulting environmental contamination, with higher frequencies typically observed near human development [57]. Viruses, including those that infect bacteria (bacteriophages), are a key reservoir of AMR in the environment [58], and their diversity and abundance are directly driven by the selection pressure of their environment (or host) [59,60]. This suggests that wildlife microbiota not only reflect anthropogenic pressures but may also serve as early indicators of ecological disturbance and human health risk. Temporal studies demonstrate the value of wildlife as sentinels: shotgun metagenomic analysis of dental calculus from wild Swedish brown bears spanning the pre- and post-antibiotic eras showed that AMR levels tracked national antibiotic use over decades, with a decline following control policies [61]. Such evidence underscores the idea that interventions can meaningfully reduce the prevalence of resistance. However, recent findings complicate this narrative. For example, >30% of E. coli isolates from wild birds and mammals were resistant to colistin (a last-resort antibiotic), yet the prevalence of resistance did not reflect the level of human impact at sampling sites [62]. Indeed, clinically relevant ARGs have been detected in animals from remote regions, including the Arctic [63] and the Gobi Desert [64]. Such results could reflect several non-exclusive processes: natural background resistance maintained by microbial competition, widespread anthropogenic contamination that masks local gradients, or long-distance dispersal of resistant bacteria, ARGs, and selective agents via wind, water, or animal movement. Migratory birds, in particular, have been highlighted as major vectors for the dissemination of resistance across large geographic scales [65], with urban proximity linked to higher AMR incidence in wild bird populations [66]. A major unresolved challenge is therefore to distinguish natural resistome variation from pollutant-driven proliferation of ARGs in wildlife microbiota. Addressing this challenge will require replicated sampling across anthropogenic exposure gradients, paired measurements of pollutants and microbial source pools, and approaches that distinguish background resistance from ARGs bearing signatures of anthropogenic influence, such as clinical relevance, mobility, or recent acquisition. Strain-resolved metagenomics, reconstruction of ARG genomic context, mobile-element tracking, absolute-abundance measurements, and phylogenetic comparisons with human-, livestock-, and environment-associated bacteria would help identify when ARGs in wildlife reflect natural microbial ecology versus recent anthropogenic selection or transmission.

By favoring resistant bacteria and resistance-bearing mobile genetic elements, pollution exposure may increase the emergence, persistence, and spread of clinically relevant AMR in wildlife-associated and environmental microbial communities. For antibiotic pollutants, measured environmental concentrations can be sufficient to select for resistance in clinically relevant bacteria [67]. However, major knowledge gaps remain regarding how resistance enters, persists, and evolves in wildlife microbiota. Most research emphasizes screening for ARGs, with far less attention to the mechanisms by which resistance enters and persists in wildlife microbiota, or to the downstream ecological and evolutionary consequences. Even less is known about the effects of complex pollutant mixtures, which represent the most realistic exposure scenarios. Mixture effects can be additive, synergistic, or antagonistic, depending on the pollutants and bacterial taxa involved [49]. Conceptually, increasing concentrations of antibiotics and pesticides are expected to increase rates of AMR evolution, with potential synergistic effects when both are present (Fig 2A). Most studies to date rely on indirect comparisons of 16S rRNA profiles and ARG distributions across environmental samples [69,70], controlled in vitro assays [50], or experiments using simplified microbial consortia and limited chemical combinations [71,72]. Recent advances in strain-resolved, low-cost metagenomics [8,73] and the use of germ-free animal models [74,75] now make it possible to trace how complex pollutant mixtures shape resistance at the strain level in vivo. Because causal links between AMR, pollutant exposure, and wildlife health are often ethically and logistically constrained, future work should combine observational, longitudinal, and experimental approaches to examine how pollutants interact with other anthropogenic pressures, including habitat transformation and cross-species microbiota transmission, to shape host outcomes.

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[1] Url: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3003939

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