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Abstract
Anthropogenic environments have been implicated in enrichment and exchange of antibiotic resistance genes and bacteria. Here we study the impact of confined and controlled swine farm environments on temporal changes in the gut microbiome and resistome of veterinary students with occupational exposure for 3 months. By analyzing 16S rRNA and whole metagenome shotgun sequencing data in tandem with culture-based methods, we show that farm exposure shapes the gut microbiome of students, resulting in enrichment of potentially pathogenic taxa and antimicrobial resistance genes. Comparison of students’ gut microbiomes and resistomes to farm workers’ and environmental samples revealed extensive sharing of resistance genes and bacteria following exposure and after three months of their visit. Notably, antibiotic resistance genes were found in similar genetic contexts in student samples and farm environmental samples. Dynamic Bayesian network modeling predicted that the observed changes partially reverse over a 4-6 month period. Our results indicate that acute changes in a human’s living environment can persistently shape their gut microbiota and antibiotic resistome.
Environments where antibiotics are used indiscriminately exhibit microbial communities that can represent hot-spots of resistance gene enrichment, which in turn could spread to humans. Here, the authors characterize how exposure to swine farms environment lead to temporal changes in the gut microbiome and resistome of healthy veterinary students.
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1 South China Agricultural University, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, Guangzhou, China (GRID:grid.20561.30) (ISNI:0000 0000 9546 5767); Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China (GRID:grid.20561.30)
2 Washington University in St. Louis School of Medicine, The Edison Family Center for Genome Sciences and Systems Biology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002)
3 South China Agricultural University, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, Guangzhou, China (GRID:grid.20561.30) (ISNI:0000 0000 9546 5767); Shenzhen Puensum Genetech Institute, Shenzhen, China (GRID:grid.20561.30)
4 Consejo Superior de Investigaciones Científicas, Centro Nacional de Biotecnología, Calle Darwin, Spain (GRID:grid.4711.3) (ISNI:0000 0001 2183 4846)
5 South China Agricultural University, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, Guangzhou, China (GRID:grid.20561.30) (ISNI:0000 0000 9546 5767); Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China (GRID:grid.20561.30); South China Agricultural University, Guangdong Provincial Key Laboratory of Veterinary Pharmaceutics Development and Safety Evaluation, Guangzhou, China (GRID:grid.20561.30) (ISNI:0000 0000 9546 5767)
6 Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, China (GRID:grid.20561.30)
7 Shenzhen Puensum Genetech Institute, Shenzhen, China (GRID:grid.20561.30)
8 Washington University in St. Louis School of Medicine, The Edison Family Center for Genome Sciences and Systems Biology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002); Washington University in St. Louis School of Medicine, Department of Pathology & Immunology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002); Washington University in St. Louis, Department of Biomedical Engineering, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002); Washington University in St. Louis School of Medicine, Department of Molecular Microbiology, St. Louis, USA (GRID:grid.4367.6) (ISNI:0000 0001 2355 7002)