Metagenomic insights into the resistome, mobilome, and virulome of dogs with diverse lifestyles.

Background: Dogs-whether pets, rural, or stray-exhibit distinct living styles that influence their fecal microbiota and resistomes, yet these dynamics remain underexplored. This study aimed to analyze and compare the fecal microbiota and resistomes of three groups of dogs (37 pets, 20 rural, and 25 stray dogs) in Shanghai, China.

Results: Metagenomic analysis revealed substantial differences in fecal microbial composition and metabolic activities among the dog groups. Pet dogs displayed the lowest microbial diversity. Using Shapley Additive Explanations (SHAP), an interpretable machine learning approach, Ligilactobacillus emerged as the most diverse genus, with significantly higher SHAP values in stray dogs, suggesting enhanced adaptability to more variable and less controlled environments. Across all samples, 587 antibiotic resistance genes (ARGs) were identified, conferring resistance to 14 antibiotic classes. A striking observation was the detection of mcr-1 in one pet dog, indicating a potential public health risk. The floR gene was identified as a key differentiator in resistance profiles, particularly in pet and rural dogs, likely due to antibiotic exposure in their environments.

Conclusion: This study provides the first comprehensive assessment of fecal microbiota and resistome variations among dogs with different lifestyles, revealing a less resilient microbiome and heightened antimicrobial resistance in pet dogs, which could have public health implications.