Shiyuan Wang, Li Cui, Huifeng Yue
Areas previously fulfilling air quality targets may face increased pressure to reevaluate due to stricter criteria. The gut homeostasis of stray animals may serve as a sensitive indicator of air pollution levels, yet previous research has primarily focused on model organisms. This cross-sectional study employed 16S rRNA sequencing and non-targeted metabolomics to assess changes in gut microbiota and metabolites across stray cat fecal samples from three air pollution zones in a coal-based industrial region in northern China-Polluted Zone 1 (DS), Polluted Zone 2 (WC), and Clean Zone (ZB). Air quality data confirmed significantly higher PM2.5, SO2, CO, and NO2 concentrations in polluted zones. The clean zone exhibited the highest gut microbial α-diversity, while polluted zones showed significantly lower diversity. Fecal metabolomic profiling identified a high-confidence subset of differentially abundant metabolites (DAMs). The transition from clean to polluted zones was associated with more pronounced biological remodeling than between polluted sites, suggesting a potential metabolic threshold effect. Lipids and lipid-like molecules represented the most disrupted superclass, with polluted cohorts showing altered bile acid profiles and accumulation of exogenous chemical remnants. Key neuroactive pathways-specifically retrograde endocannabinoid signaling and glutamatergic synapse-were consistently enriched among DAMs in polluted environments, reflecting localized remodeling of the host metabolic network. These findings suggest that air pollution exposure is associated with potential systemic health effects extending from the gut to the neuroendocrine level. This study provides evidence that environmental pollution gradients are independently associated with alterations in the feline gut microbiome-metabolome axis, highlighting the translational potential of urban stray cats as sentinel species within the One Health framework. Given the observational design, reported associations do not imply causation.