scispace - formally typeset
Open AccessJournal ArticleDOI

Genome Sequencing of Sewage Detects Regionally Prevalent SARS-CoV-2 Variants.

Reads0
Chats0
TLDR
In this paper, the authors used a pipeline for single nucleotide variant calling in a metagenomic context, characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California.
Abstract
Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and nearly complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the United States or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside California, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Evaluation of Sampling, Analysis, and Normalization Methods for SARS-CoV-2 Concentrations in Wastewater to Assess COVID-19 Burdens in Wisconsin Communities

TL;DR: The differences in the strength of SARS-CoV-2 relationships to COVID-19 incidence and the effect of normalization on these data among communities demonstrate that rigorous validation should be performed at individual sites where wastewater surveillance programs are implemented.
Journal ArticleDOI

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission

Smruthi Karthikeyan, +117 more
- 07 Jul 2022 - 
TL;DR: In this paper , a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission was proposed, in the controlled environment of a large university campus and the broader context of the surrounding county.
Journal ArticleDOI

Evaluating recovery, cost, and throughput of different concentration methods for SARS-CoV-2 wastewater-based epidemiology.

TL;DR: In this article, the authors evaluated the recovery, cost, and throughput of five different concentration methods for quantifying SARS-CoV-2 virus RNA in wastewater samples and evaluated the use of a bovine coronavirus vaccine as a process control and pepper mild mottle virus as a normalization factor.
References
More filters
Journal ArticleDOI

Fast gapped-read alignment with Bowtie 2

TL;DR: Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
Journal ArticleDOI

An interactive web-based dashboard to track COVID-19 in real time.

TL;DR: The outbreak of the 2019 novel coronavirus disease (COVID-19) has induced a considerable degree of fear, emotional stress and anxiety among individuals around the world.
Journal ArticleDOI

SciPy 1.0: fundamental algorithms for scientific computing in Python.

TL;DR: SciPy as discussed by the authors is an open-source scientific computing library for the Python programming language, which has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year.
Journal ArticleDOI

Data, disease and diplomacy: GISAID's innovative contribution to global health

TL;DR: The article finds that the Global Initiative on Sharing All Influenza Data contributes to global health in at least five ways: collating the most complete repository of high‐quality influenza data in the world; facilitating the rapid sharing of potentially pandemic virus information during recent outbreaks; supporting the World Health Organization's biannual seasonal flu vaccine strain selection process; developing informal mechanisms for conflict resolution around the sharing of virus data.
Related Papers (5)