Your browser doesn't support javascript.
loading
Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques.
Baaijens, Jasmijn A; Zulli, Alessandro; Ott, Isabel M; Nika, Ioanna; van der Lugt, Mart J; Petrone, Mary E; Alpert, Tara; Fauver, Joseph R; Kalinich, Chaney C; Vogels, Chantal B F; Breban, Mallery I; Duvallet, Claire; McElroy, Kyle A; Ghaeli, Newsha; Imakaev, Maxim; Mckenzie-Bennett, Malaika F; Robison, Keith; Plocik, Alex; Schilling, Rebecca; Pierson, Martha; Littlefield, Rebecca; Spencer, Michelle L; Simen, Birgitte B; Hanage, William P; Grubaugh, Nathan D; Peccia, Jordan; Baym, Michael.
Affiliation
  • Baaijens JA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. j.a.baaijens@tudelft.nl.
  • Zulli A; Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands. j.a.baaijens@tudelft.nl.
  • Ott IM; Department of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA.
  • Nika I; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • van der Lugt MJ; Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands.
  • Petrone ME; Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands.
  • Alpert T; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • Fauver JR; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • Kalinich CC; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • Vogels CBF; Department of Epidemiology, University of Nebraska Medical Center, Omaha, NE, USA.
  • Breban MI; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • Duvallet C; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • McElroy KA; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
  • Ghaeli N; Biobot Analytics, Inc., Cambridge, MA, USA.
  • Imakaev M; Biobot Analytics, Inc., Cambridge, MA, USA.
  • Mckenzie-Bennett MF; Biobot Analytics, Inc., Cambridge, MA, USA.
  • Robison K; Biobot Analytics, Inc., Cambridge, MA, USA.
  • Plocik A; Ginkgo Bioworks, Inc., Boston, MA, USA.
  • Schilling R; Ginkgo Bioworks, Inc., Boston, MA, USA.
  • Pierson M; Ginkgo Bioworks, Inc., Boston, MA, USA.
  • Littlefield R; Ginkgo Bioworks, Inc., Boston, MA, USA.
  • Spencer ML; Ginkgo Bioworks, Inc., Boston, MA, USA.
  • Simen BB; Ginkgo Bioworks, Inc., Boston, MA, USA.
  • Hanage WP; Ginkgo Bioworks, Inc., Boston, MA, USA.
  • Peccia J; Center for Communicable Disease Dynamics and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Baym M; Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Genome Biol ; 23(1): 236, 2022 11 08.
Article in En | MEDLINE | ID: mdl-36348471
ABSTRACT
Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable.
Subject(s)
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Risk_factors_studies Limits: Humans Language: En Journal: Genome Biol Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2022 Type: Article Affiliation country: United States
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Risk_factors_studies Limits: Humans Language: En Journal: Genome Biol Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2022 Type: Article Affiliation country: United States