Rodents are key reservoirs of zoonotic pathogens and play an important role in disease transmission to humans. Importantly, anthropogenic land-use change has been found to increase the abundance of rodents that thrive in human-built environments (synanthropic rodents), particularly rodent reservoirs of zoonotic disease. Anthropogenic environments also affect the microbiome of synanthropic wildlife, influencing wildlife health and potentially introducing novel pathogens. Our objective was to examine the effect of agricultural development and synanthropic habitat on microbiome diversity and the prevalence of zoonotic bacterial pathogens in wild Peromyscus mice to better understand the role of these rodents in pathogen maintenance and transmission. We conducted 16S amplicon sequencing on fecal samples using long-read Nanopore sequencing technology to characterize the rodent microbiome. We compared microbiome diversity and composition between forest and synanthropic habitats in agricultural and undeveloped landscapes and screened for putative pathogenic bacteria. Microbiome richness, diversity, and evenness were higher in the agricultural landscape and synanthropic habitat compared to undeveloped-forest habitat. Microbiome composition also differed significantly between agricultural and undeveloped landscapes and forest and synanthropic habitat. We detected overall low diversity and abundance of putative pathogenic bacteria, though putative pathogens were more likely to be found in mice from the agricultural landscape. Our findings show that landscape- and habitat-level anthropogenic factors affect Peromyscus microbiomes and suggest that landscape-level agricultural development may be important to predict zoonotic pathogen prevalence. Ultimately, understanding how anthropogenic land-use change and synanthropy affect rodent microbiomes and pathogen prevalence is important to managing transmission of rodent-borne zoonotic diseases to humans.

Peromyscus mice were live-trapped and fecal samples were collected for microbiome analysis. Data was collected during field data collection documenting the date and location of trapped animals, body measurements (body mass, body length), sex, reproductive status, and samples collected. Data was also recorded during the lab processing of the collected fecal samples for DNA extraction, library preparation, and Nanopore sequencing of barcoded libraries.