CaltechAUTHORS
Published December 29, 2021 | Version public
Discussion Paper Metadata-only

Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission

Creators

  • 1. ROR icon University of California, San Diego
  • 2. ROR icon Scripps Research Institute
  • 3. ROR icon California Department of Public Health
  • 4. ROR icon Rady Children's Hospital-San Diego
  • 5. ROR icon Sharp HealthCare Foundation
  • 6. ROR icon Helix (United States)
  • 7. ROR icon Health and Human Services Agency
  • 8. ROR icon Centers for Disease Control and Prevention
  • 9. ROR icon Sanford Consortium for Regenerative Medicine

Abstract

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Additional Information

Paper in collection COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv. This work has been funded by CDC BAA contracts 75D30121P10258 (Helix) and 75D30120C09795 (G.W.Y., R.K., L.C.L., and K.G.A.), NIH NIAID 3U19AI135995-03S2 (K.G.A.), U19AI135995 (K.G.A.), U01AI151812 (K.G.A.), NIH NCATS UL1TR002550 (K.G.A.), the Conrad Prebys Foundation (K.G.A.), NIH 5T32AI007244-38 (J.I.L.), NIH Pioneer Grant 1DP1AT010885 (R.K), NSF RAPID 2029069 (R.K.), San Diego County Health and Human Services Agency (R.F.M), NIH S10OD026929 (K.J.). The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Use of trade names is for identification only and does not imply endorsement by the Centers for Disease Control and Prevention.

Additional details

Identifiers

PMCID
PMC8996633
Eprint ID
118345
Resolver ID
CaltechAUTHORS:20221215-540121000.6

Related works

Describes
https://resolver.caltech.edu/CaltechAUTHORS:20221215-539953000.2 (URL)

Funding

Centers for Disease Control and Prevention
75D30121P10258
Centers for Disease Control and Prevention
75D30120C09795
NIH
3U19AI135995-03S2
NIH
U19AI135995
NIH
U01AI151812
NIH
UL1TR002550
Conrad Prebys Foundation
NIH Predoctoral Fellowship
5T32AI007244
NIH
1DP1AT010885
NSF
AGS-2029069
San Diego County
NIH
S10OD026929

Dates

Created
2022-12-17
Created from EPrint's datestamp field
Updated
2022-12-17
Created from EPrint's last_modified field

Caltech Custom Metadata

Caltech groups
COVID-19