{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T13:54:07Z","timestamp":1791467647703,"version":"4.3.4"},"reference-count":51,"publisher":"American Society for Microbiology","license":[{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.asm.org\/non-commercial-tdm-license"}],"content-domain":{"domain":["journals.asm.org"],"crossmark-restriction":true},"short-container-title":["mSphere"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title\/>\n                    <jats:p>Urban public transport systems, particularly metro networks, serve as key hubs for microbial transmission, yet the urban microbiome in densely populated regions like India remains poorly characterized. Understanding these environments is crucial for public health, especially in light of the COVID-19 pandemic and growing concerns about antimicrobial resistance (AMR). This study is the first of its kind to investigate the microbial communities and the presence of AMR genes in the Chennai Metro system. We collected 96 surface swabs from 12 metro stations across two lines, focusing on surfaces that people frequently touch, such as handrails, kiosks, banisters, and ticket counters. Of the collected samples, 47 met quality control standards and were subjected to shotgun metagenomic sequencing, and 41 samples with more than 1 million reads were included in our analysis. Our findings indicate that surface type significantly influences microbial community structure, with kiosks exhibiting the highest microbial diversity. Comparative analysis with global urban data sets revealed unique microbial patterns specific to Chennai, including nine species that were notably more prevalent in our samples than in other urban transit systems worldwide. Furthermore, through pangenome analysis, we generated high-quality metagenome-assembled genomes that elucidated the adaptive strategies of dominant microbial species in this urban environment. Despite their relatively low abundance, several AMR families were widely distributed across the data set, with over 80% of samples containing at least one associated AMR gene, including families linked to rifamycins, multidrug resistance, and sulfonamides. This study lays a foundation for understanding the urban microbiome in India, emphasizing distinct regional characteristics and underscoring the need for sustained monitoring to mitigate disease transmission risks in high-density transit settings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>IMPORTANCE<\/jats:title>\n                    <jats:p>Densely populated urban transit systems are critical hubs for microbial exchange, yet the mass transit microbiomes of Indian cities remain largely uncharacterized, representing a significant gap in global surveillance. Our study provides the first comprehensive metagenomic analysis of the Chennai Metro, a high-traffic transit network serving millions. Our findings highlight the unique environmental drivers shaping urban microbiota in India. Chennai, with over 12 million residents and a metro system serving over 105 million passengers annually, is an ideal yet uncharacterized environment for studying microbial dynamics, surface\u2013microbe interactions, and environmental antimicrobial resistance reservoirs.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1128\/msphere.00433-26","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T13:00:31Z","timestamp":1791464431000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":0,"title":["Microbial communities on station and train surfaces in Chennai Metro: insights into urban transit microbiome"],"prefix":"10.1128","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7846-2561","authenticated-orcid":true,"given":"Vijaya Yuvaram","family":"Singh","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras","place":["Chennai, India"]},{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Centre for Integrative Biology and Systems Medicine, Wadhwani School of Data Science and Artificial Intelligence, IIT Madras","place":["Chennai, India"]},{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Wadhwani School of Data Science and Artificial Intelligence, IIT Madras","place":["Chennai, India"]},{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Data Science and Artificial Intelligence, Wadhwani School of Data Science and Artificial Intelligence, IIT Madras","place":["Chennai, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Veerendra P.","family":"Gadekar","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Centre for Integrative Biology and Systems Medicine, Wadhwani School of Data Science and Artificial Intelligence, IIT Madras","place":["Chennai, India"]},{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Wadhwani School of Data Science and Artificial Intelligence, IIT Madras","place":["Chennai, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Srijith","family":"Sasikumar","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, IIT Madras","place":["Chennai, India"]},{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Centre for Integrative Biology and Systems Medicine, Wadhwani School of Data Science and Artificial Intelligence, IIT Madras","place":["Chennai, India"]},{"id":[{"id":"https:\/\/ror.org\/03v0r5n49","id-type":"ROR","asserted-by":"publisher"}],"name":"Wadhwani School of Data Science and Artificial Intelligence, IIT Madras","place":["Chennai, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R. 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