Background: Mass transit environments, such as the metro, can facilitate the spread of bacteria between humans and their surroundings. These environments are particularly important for human health due to their potential for spreading pathogens and their impact on large populations. To gain a deeper understanding of bacterial distribution in subways, it is essential to identify variables that affect bacterial composition and microorganisms that are probably harmful to human heath.
Methods: We conducted high-throughput 16S rRNA gene sequencing on surface samples from 5 subway stations in Shanghai, China, during the warm(summer), cold(winter) and transition(autumn) seasons. Bacteria community features across the three seasons were distinguished using random forest classification analyses, followed by in-depth diversity analyses.
Results: Significant differences were observed in surface bacterial communities across seasons. Highly abundant bacterial groups were generally ubiquitous. Among these highly abundant families and genera, some were unique to surface samples. Notably, the phyla Firmicutes, Proteobacteria, and Actinobacteria were predominant, with total abundances of 32.87 %, 29.41 %, and 16.31 %, respectively. Alpha diversity indices were statistically significant (P < 0.05) among different seasons, with autumn exhibiting significantly higher alpha diversity metrics compared to summer and winter. Beta diversity analysis revealed significant compositional dissimilarities and distinct clustering patterns among the three seasons (P < 0.05). An analysis of similarities (ANOSIM) test results indicated significant differences in bacterial patterns at the phylum, class, order, family, genus levels among the seasons (P < 0.05). Random forest classification analyses identified the top 24 bacterial taxa at the genus level across seasons in the metro system.
Conclusions: We provided a direct comparison of surface bacterial microbiomes, and a comprehensive survey of seasonal variation in subways using culture-independent methods. Our findings reveal differences in both diversity and abundance of certain taxa across seasons, with 24 top indicator bacterial genera identified. This work serves as a reference for understanding the composition and dynamics of bacterial communities and for biomarker screening in subways, a crucial public space in our increasingly urbanized and interconnected world.
Keywords: 16S rRNA gene sequencing; Amplicon sequencing; Seasonal variation; Subway microbiome; Surface.
© 2025 Published by Elsevier B.V.
