{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T18:09:36Z","timestamp":1788977376396,"version":"build-2803163510"},"reference-count":49,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000030","name":"Centers for Disease Control and Prevention","doi-asserted-by":"publisher","award":["CK-19-1904"],"award-info":[{"award-number":["CK-19-1904"]}],"id":[{"id":"10.13039\/100000030","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Wastewater surveillance is a valuable tool for monitoring SARS-CoV-2 at the community level. As the virus diversified into many variants and subvariants that share overlapping mutations, resolving them accurately from wastewater becomes a key bioinformatic challenge.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Objectives and aims<\/jats:title>\n                    <jats:p>This study evaluated two distinct bioinformatic approaches, multilocus sequence typing (MLST) and Freyja, for identifying SARS-CoV-2 variants and subvariants in Oregon wastewater samples collected from February 2021 to February 2022.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The MLST approach identified SARS-CoV-2 variants using unique mutations curated from clinical samples. In contrast, the Freyja approach resolved variant and subvariant abundances using genome wide mutation profiles weighted by sequencing depth. In this study, the variant and subvariants relative abundances produced by both approaches were compared against those observed in clinical surveillance data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Both approaches identified SARS-CoV-2 variants at relative abundances that agreed closely with those observed in clinical surveillance data. However, only the Freyja approach identified over 200 Delta subvariants, divided into three clades (21A, 21I and 21J) and two levels (Level 1 and 2) based on Pango subvariants. Delta subvariants showed strong agreement at Level 1 subvariants (r\n                      <jats:sub>s<\/jats:sub>\n                      \u2009=\u20090.892\u20130.944), while agreement at Level 2 subvariants was inconsistent (r\n                      <jats:sub>s<\/jats:sub>\n                      \u2009=\u20090.324\u20130.903).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec005\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The Freyja approach provided enhanced resolution of SARS-CoV-2 variants and subvariants in wastewater, at abundances that agreed with clinical surveillance. This added resolution is a critical advantage for public health surveillance as SARS-CoV-2 continues to evolve and share mutations across variants and subvariants.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0357591","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T17:43:46Z","timestamp":1788975826000},"page":"e0357591","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Correlation assessment of SARS-CoV-2 variants and their subvariants present in clinical and wastewater samples in Oregon, USA (February 7, 2021 - February 26, 2022) using the Freyja bioinformatics approach"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-8626-5651","authenticated-orcid":true,"given":"Anirudh","family":"Bhatia","sequence":"first","affiliation":[{"name":"School of Chemical, Biological and Environmental Engineering, Oregon State University","place":["Corvallis, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justin","family":"Elser","sequence":"additional","affiliation":[{"name":"Center for Quantitative Life Sciences, Oregon State University","place":["Corvallis, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3243-2601","authenticated-orcid":true,"given":"Steven J.","family":"Carrell","sequence":"additional","affiliation":[{"name":"Center for Quantitative Life Sciences, Oregon State University","place":["Corvallis, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brent","family":"Kronmiller","sequence":"additional","affiliation":[{"name":"Center for Quantitative Life Sciences, Oregon State University","place":["Corvallis, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melissa","family":"Sutton","sequence":"additional","affiliation":[{"name":"Oregon Health Authority","place":["Portland, Oregon, United States of America"],"department":["Public Health Division"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christine","family":"Kelly","sequence":"additional","affiliation":[{"name":"School of Chemical, Biological and Environmental Engineering, Oregon State University","place":["Corvallis, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5295-3562","authenticated-orcid":true,"given":"Tyler S.","family":"Radniecki","sequence":"additional","affiliation":[{"name":"School of Chemical, Biological and Environmental Engineering, Oregon State University","place":["Corvallis, Oregon, United States of America"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,9,9]]},"reference":[{"issue":"5","key":"pone.0357591.ref001","doi-asserted-by":"crossref","first-page":"2919","DOI":"10.1128\/AEM.69.5.2919-2927.2003","article-title":"Environmental surveillance system to track wild poliovirus transmission","volume":"69","author":"JM Deshpande","year":"2003","journal-title":"Appl Environ Microbiol"},{"key":"pone.0357591.ref002","doi-asserted-by":"crossref","first-page":"156724","DOI":"10.1016\/j.scitotenv.2022.156724","article-title":"Surveillance of omicron variants through wastewater epidemiology: Latest developments in environmental monitoring of pandemic","volume":"843","author":"V Soni","year":"2022","journal-title":"Sci Total Environ"},{"issue":"3","key":"pone.0357591.ref003","doi-asserted-by":"crossref","first-page":"434","DOI":"10.2166\/wh.2011.019","article-title":"Surveillance of influenza A and the pandemic influenza A (H1N1) 2009 in sewage and surface water in the Netherlands","volume":"9","author":"L Heijnen","year":"2011","journal-title":"J Water Health"},{"issue":"2","key":"pone.0357591.ref004","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1021\/acs.estlett.1c00963","article-title":"Respiratory Syncytial Virus (RSV) RNA in Wastewater Settled Solids Reflects RSV Clinical Positivity Rates","volume":"9","author":"B Hughes","year":"2022","journal-title":"Environmental Science & Technology Letters"},{"issue":"2","key":"pone.0357591.ref005","doi-asserted-by":"crossref","first-page":"16","DOI":"10.15585\/mmwr.mm7502a1","article-title":"Notes from the Field: Retrospective Analysis of Wild-Type Measles Virus in Wastewater During a Measles Outbreak - 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