Evidence map›Paper›PMID 38806450›Full record

ArticleNature communications2024

Crykey: Rapid identification of SARS-CoV-2 cryptic mutations in wastewater.

Yunxi Liu, Nicolae Sapoval, Pilar Gallego-García, Laura Tomás, David Posada, Todd J Treangen, Lauren B Stadler

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Review
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  5. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Yunxi LiuDepartment of Computer Science, Rice University, Houston, TX, 77005, USA.ORCID http://orcid.org/0000-0003-2657-1816
Nicolae SapovalDepartment of Computer Science, Rice University, Houston, TX, 77005, USA.
Pilar Gallego-GarcíaCINBIO, Universidade de Vigo, 36310, Vigo, Spain.ORCID http://orcid.org/0000-0001-8531-9851
Laura TomásCINBIO, Universidade de Vigo, 36310, Vigo, Spain.ORCID http://orcid.org/0000-0001-9848-002X
David PosadaCINBIO, Universidade de Vigo, 36310, Vigo, Spain.ORCID http://orcid.org/0000-0003-1407-3406
Todd J TreangenDepartment of Computer Science, Rice University, Houston, TX, 77005, USA. treangen@rice.edu.ORCID http://orcid.org/0000-0002-3760-564X
Lauren B StadlerDepartment of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA. lauren.stadler@rice.edu.ORCID http://orcid.org/0000-0001-7469-1981

Funding

Project 3: Functional Microbiome and Host Signatures in Transition from Commensal to pathogenP01AI152999 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HAAG, ANTHONY · 2020 to 2025
$12.0M
National Science Foundation (NSF) CNS-1338099National Science Foundation (NSF) IIS-2239114NIAID NIH HHS P01 AI152999U.S. Department of Health & Human Services | Centers for Disease Control and Prevention (CDC) 75D30121C11180
6 · The paper itself

Abstract

Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2.

Indexed as

COVID-19Genome, ViralMutationSARS-CoV-2WastewaterComputational BiologyHumansWastewater

Identifiers

PMID38806450
PMCPMC11133379

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.