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The resistome analysis revealed high abundances of genes known to confer resistance against sulfonamides (\n                      <jats:italic toggle=\"yes\">sul1<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">sul2<\/jats:italic>\n                      ), aminoglycosides (\n                      <jats:italic toggle=\"yes\">aadS<\/jats:italic>\n                      ), and macrolides\/streptogramins (\n                      <jats:italic toggle=\"yes\">msrE<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">mphE<\/jats:italic>\n                      ). High-risk resistance genes were also detected, including those known to confer resistance to \u03b2-lactams (\n                      <jats:italic toggle=\"yes\">bla<\/jats:italic>\n                      <jats:sub>OXA<\/jats:sub>\n                      ,\n                      <jats:italic toggle=\"yes\">bla<\/jats:italic>\n                      <jats:sub>TEM<\/jats:sub>\n                      ,\n                      <jats:italic toggle=\"yes\">bla<\/jats:italic>\n                      <jats:sub>GES<\/jats:sub>\n                      ,\n                      <jats:italic toggle=\"yes\">bla<\/jats:italic>\n                      <jats:sub>NDM<\/jats:sub>\n                      ,\n                      <jats:italic toggle=\"yes\">bla<\/jats:italic>\n                      <jats:sub>KPC<\/jats:sub>\n                      ), colistins (\n                      <jats:italic toggle=\"yes\">mcr-5<\/jats:italic>\n                      ), and tetracyclines [\n                      <jats:italic toggle=\"yes\">tet(C)<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">tet(A)<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">tet(L)<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">tet(M)<\/jats:italic>\n                      ]. Comparisons with hospital wastewater resistome profiles from regional neighbors and other lower-and-middle-income countries indicated broadly similar relative abundances of dominant resistance genes, with differences largely driven by low-abundance resistance genes. The bacterial community was dominated by the phylum Pseudomonadota, with high relative abundances of the genera\n                      <jats:italic toggle=\"yes\">Stenotrophomonas<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">Rhodococcus<\/jats:italic>\n                      , and\n                      <jats:italic toggle=\"yes\">Pseudomonas<\/jats:italic>\n                      , while ESKAPEE pathogens were detected at lower levels. A diverse array of mobile genetic elements\u2014many known to be associated with resistance to multiple drug classes and disinfectants\u2014was also observed. Overall, this study provides a valuable preliminary evidence base for future antimicrobial resistance and epidemiological surveillance efforts in the Philippines, particularly those employing wastewater-based approaches.\n                    <\/jats:p>\n                    <jats:sec>\n                      <jats:title>IMPORTANCE<\/jats:title>\n                      <jats:p>Antimicrobial resistance (AMR) is a growing public health threat caused by pathogenic bacteria that are no longer controlled by commonly used treatments. Infections caused by these resistant bacteria may lead to prolonged illness, more severe symptoms, or even death. Hospitals are critical hotspots for the emergence and spread of AMR. Their wastewater, which contains antibiotics, medical and human waste, and diverse microbial communities, can support the persistence and dissemination of resistant bacteria. The significance of this research lies in identifying and characterizing these bacterial communities and the resistance genes they carry. Such information can provide an indication of the resistance burden faced by patients and serve as an early warning system to strengthen infection prevention and control measures, support national surveillance efforts, and inform the development of more effective treatment and management strategies in healthcare settings.<\/jats:p>\n                    <\/jats:sec>\n                  <\/jats:sec>","DOI":"10.1128\/spectrum.03963-25","type":"journal-article","created":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T13:59:26Z","timestamp":1774879166000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":1,"title":["Investigating the resistome, taxonomic composition, and mobilome of bacterial communities in hospital wastewaters of Metro Manila using a shotgun metagenomics approach"],"prefix":"10.1128","volume":"14","author":[{"given":"Jiaan Carlo E.","family":"Santos","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Biology, College of Science, De La Salle University","place":["Manila, Philippines"]},{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Systems & Computational Biology Unit, Center for Natural Sciences and Environmental Research, De La Salle University","place":["Manila, Philippines"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daphne Janelyn L.","family":"Go","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Systems & Computational Biology Unit, Center for Natural Sciences and Environmental Research, De La Salle University","place":["Manila, Philippines"]},{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Software Technology, College of Computer Studies, De La Salle University","place":["Manila, Philippines"]},{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Bioinformatics Laboratory, Advanced Research Institute for Informatics, Computing, and Networking, De La Salle University","place":["Manila, Philippines"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert D.","family":"Unciano","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Systems & Computational Biology Unit, Center for Natural Sciences and Environmental Research, De La Salle University","place":["Manila, Philippines"]},{"name":"Institute of Arts and Sciences, Far Eastern University","place":["Manila, Philippines"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7848-5050","authenticated-orcid":true,"given":"Paul K.","family":"Yu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04p491231","id-type":"ROR","asserted-by":"publisher"}],"name":"Bioinformatics and Genomics Program, Pennsylvania State University College of Medicine","place":["Hershey, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3028-9610","authenticated-orcid":true,"given":"Angelyn R.","family":"Lao","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Systems & Computational Biology Unit, Center for Natural Sciences and Environmental Research, De La Salle University","place":["Manila, Philippines"]},{"id":[{"id":"https:\/\/ror.org\/04xftk194","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Mathematics and Statistics, College of Science, De La Salle University","place":["Manila, Philippines"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4542-3627","authenticated-orcid":true,"given":"Ma. 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