{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T17:10:59Z","timestamp":1789665059054,"version":"4.0.1"},"reference-count":86,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:00:00Z","timestamp":1770768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013589","name":"Research England","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013589","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100016270","name":"Global Challenges Research Fund","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100016270","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Rapid and scalable surveillance of antimicrobial resistance (AMR) is urgently needed in resource-constrained countries where routine monitoring is limited. Wastewater-based metagenomics offers a potential solution for early detection and geographic mapping of AMR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective DNA shotgun metagenomic analysis of untreated wastewater collected across Nagpur, India (February\u2013April 2021). A total of 422 grab samples were pooled into 138 composite samples from 10 urban zones and rural catchments. The bacterial microbiota and resistome were profiled, and urban\u2013rural patterns were compared using diversity metrics and correlation analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Across all samples, 871 bacterial genera were detected, dominated by Proteobacteria, with frequent presence of\n                      <jats:italic>Pseudomonas<\/jats:italic>\n                      ,\n                      <jats:italic>Acinetobacter<\/jats:italic>\n                      ,\n                      <jats:italic>Aeromonas<\/jats:italic>\n                      ,\n                      <jats:italic>Acidovorax<\/jats:italic>\n                      and\n                      <jats:italic>Bacteroides<\/jats:italic>\n                      . Beta diversity revealed statistically significant but subtle urban\u2013rural compositional shifts. Of 33 globally important pathogens examined, 13 were detected at generally low relative abundance (&amp;lt;1%).\n                      <jats:italic>Vibrio cholerae<\/jats:italic>\n                      appeared in one sample, while\n                      <jats:italic>Aeromonas<\/jats:italic>\n                      spp. were most prevalent. Seven pathogens occurred in \u226510% of samples, with\n                      <jats:italic>Aeromonas<\/jats:italic>\n                      ,\n                      <jats:italic>Citrobacter<\/jats:italic>\n                      , and\n                      <jats:italic>Enterobacter<\/jats:italic>\n                      differing significantly between locations (\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.05). The resistome comprised 606 unique antimicrobial resistance genes (ARGs), dominated by drug\/biocide efflux determinants, followed by macrolide-lincosamide-streptogramin B genes driven largely by 23S rRNA mutations. Carbapenemases (\n                      <jats:italic>blaNDM<\/jats:italic>\n                      ,\n                      <jats:italic>blaKPC<\/jats:italic>\n                      ) and colistin resistance (\n                      <jats:italic>mcr<\/jats:italic>\n                      ) were detected at lower abundance. Correlation analyses linked\n                      <jats:italic>Pseudomonas<\/jats:italic>\n                      with\n                      <jats:italic>mexEF<\/jats:italic>\n                      \/\n                      <jats:italic>emhABC<\/jats:italic>\n                      efflux and\n                      <jats:italic>copBCDRS<\/jats:italic>\n                      copper resistance operon,\n                      <jats:italic>Acinetobacter<\/jats:italic>\n                      with\n                      <jats:italic>oxa<\/jats:italic>\n                      and\n                      <jats:italic>dfrA<\/jats:italic>\n                      , and\n                      <jats:italic>Aeromonas<\/jats:italic>\n                      with\n                      <jats:italic>ctx<\/jats:italic>\n                      ,\n                      <jats:italic>tetA<\/jats:italic>\n                      ,\n                      <jats:italic>sul1<\/jats:italic>\n                      ,\n                      <jats:italic>dfrB\/F<\/jats:italic>\n                      , and\n                      <jats:italic>gyrA\/parC<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These findings show that wastewater metagenomics sensitively resolved clinically relevant pathogens and ARGs in an Indian urban\u2013rural setting, capturing nuanced geographic structure. Integrating routine DNA metagenomics into One Health environmental surveillance could strengthen AMR early warning and guide interventions in resource-constrained contexts.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmicb.2025.1722229","type":"journal-article","created":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T07:04:15Z","timestamp":1770793455000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Metagenomic insights into the urban\u2013rural variation of antimicrobial resistance and pathogen reservoirs in untreated wastewater from central India"],"prefix":"10.3389","volume":"16","author":[{"given":"Bailey","family":"Secker","sequence":"first","affiliation":[{"name":"School of Veterinary Medicine and Science, University of Nottingham","place":["Leicestershire, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amit","family":"Nayak","sequence":"additional","affiliation":[{"name":"Advanced Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS)","place":["Nagpur, Maharashtra, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aliabbas A.","family":"Husain","sequence":"additional","affiliation":[{"name":"Advanced Research Centre, Dr G.M. Taori Central India Institute of Medical Sciences (CIIMS)","place":["Nagpur, Maharashtra, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sudipti","family":"Arora","sequence":"additional","affiliation":[{"name":"Dr. B. Lal Institute of Biotechnology","place":["Jaipur, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aditi","family":"Nag","sequence":"additional","affiliation":[{"name":"Dr. B. Lal Institute of Biotechnology","place":["Jaipur, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandeep K.","family":"Shrivastava","sequence":"additional","affiliation":[{"name":"Centre for Innovation, Research & Development (CIRD), Dr. B. Lal Clinical Laboratory Pvt., Ltd.","place":["Jaipur, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew C.","family":"Singer","sequence":"additional","affiliation":[{"name":"United Kingdom Centre for Ecology and Hydrology","place":["Wallingford, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel L.","family":"Gomes","sequence":"additional","affiliation":[{"name":"Food Water Waste Research Group, Faculty of Engineering, University of Nottingham","place":["Nottingham, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edward","family":"Acheampong","sequence":"additional","affiliation":[{"name":"Department of Statistics and Actuarial Science, University of Ghana","place":["Legon, Ghana"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saravana B.","family":"Chidambaram","sequence":"additional","affiliation":[{"name":"Department of Pharmacology, JSS College of Pharmacy, JSS Academy of Higher Education & Research","place":["Mysuru, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tarun","family":"Bhatnagar","sequence":"additional","affiliation":[{"name":"ICMR-National Institute of Epidemiology","place":["Chennai, Tamil Nadu, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Umashankar","family":"Vetrivel","sequence":"additional","affiliation":[{"name":"National Institute of Traditional Medicine, Indian Council of Medical Research","place":["Belagavi, India"]},{"name":"Virology and Biotechnology\/Bioinformatics Division, ICMR-National Institute for Research in Tuberculosis","place":["Chennai, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rajpal Singh","family":"Kashyap","sequence":"additional","affiliation":[{"name":"Advanced Research Centre, Dr G.M. 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