QuaID: Enabling Earlier Detection of Recently Emerged SARS-CoV-2 Variants of Concern in Wastewater.
Journal
medRxiv : the preprint server for health sciences
Titre abrégé: medRxiv
Pays: United States
ID NLM: 101767986
Informations de publication
Date de publication:
04 Aug 2022
04 Aug 2022
Historique:
pubmed:
29
7
2022
medline:
29
7
2022
entrez:
28
7
2022
Statut:
epublish
Résumé
As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variants of concern (VoC) in communities. Multiple recent studies support that wastewater-based SARS-CoV-2 detection of circulating VoC can precede clinical cases by up to two weeks. Furthermore, wastewater based epidemiology enables wide population-based screening and study of viral evolutionary dynamics. However, highly sensitive detection of emerging variants remains a complex task due to the pooled nature of environmental samples and genetic material degradation. In this paper we propose quasi-unique mutations for VoC identification, implemented in a novel bioinformatics tool (QuaID) for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3 week earlier VoC detection compared to existing approaches, (ii) enables more sensitive VoC detection, which is shown to be tolerant of >50% mutation drop-out, and (iii) leverages all mutational signatures, including insertions & deletions.
Identifiants
pubmed: 35898338
doi: 10.1101/2021.09.08.21263279
pmc: PMC9327636
pii:
doi:
Types de publication
Preprint
Langues
eng
Subventions
Organisme : NIAID NIH HHS
ID : P01 AI152999
Pays : United States
Organisme : NIEHS NIH HHS
ID : R01 ES028819
Pays : United States
Commentaires et corrections
Type : UpdateIn
Déclaration de conflit d'intérêts
Competing interests Authors declare no competing interests.
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