Bacterial metatranscriptomes in wastewater can differentiate virally infected human populations

Year: 2022

Type: preprint

Abstract: Monitoring wastewater samples at building-level resolution screens large populations for SARS-CoV-2, prioritizing testing and isolation efforts. Here we perform untargeted metatranscriptomics on virally-enriched wastewater samples from 10 locations on the UC San Diego campus, demonstrating that resulting bacterial taxonomic and functional profiles discriminate SARS-CoV-2 status even without direct detection of viral transcripts. Our proof-of-principle reveals emergent threats through changes in the human microbiome, suggesting new approaches for untargeted wastewater-based epidemiology.

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.1101/2022.02.23.481658

Institutions: University of California San Diego, IBM Research - Almaden, IBM (United States), IBM Research - Thomas J. Watson Research Center

Language: English

Topic: SARS-CoV-2 detection and testing

Subfield: Infectious Diseases

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Clean water and sanitation

Open Access status: green

Funders: National Science Foundation, Emerald Foundation, National Institutes of Health, University of California, San Diego

Award: RAPID: Improving QIIME 2 and UniFrac for Viruses to Respond to COVID-19

OpenAlex ID: W4214686964