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Record W3092635922 · doi:10.1101/2020.10.11.333682

A combination of metagenomic and cultivation approaches reveals hypermutator phenotypes within <i>Vibrio cholerae</i> infected patients

2020· preprint· en· W3092635922 on OpenAlexafffund
Inès Levade, Ashraful Islam Khan, Fahima Chowdhury, Stephen B. Calderwood, Edward T. Ryan, Jason B. Harris, Regina C. LaRocque, Taufiqur Rahman Bhuiyan, Firdausi Qadri, Ana A. Weil, B. Jesse Shapiro

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsMcGill Genome CentreUniversité de MontréalMcGill University
FundersGlobal Affairs CanadaDepartment for International DevelopmentInternational Centre for Diarrhoeal Disease Research, BangladeshStyrelsen för Internationellt Utvecklingssamarbete
KeywordsVibrio choleraeMetagenomicsBiologyNonsynonymous substitutionCholeraGenomeWhole genome sequencingGeneticsAsymptomatic carrierDNA sequencingMicrobiologyGeneAsymptomaticVirologyMedicineBacteria

Abstract

fetched live from OpenAlex

ABSTRACT Vibrio cholerae can cause a range of symptoms, ranging from severe diarrhea to asymptomatic infection. Previous studies using whole genome sequencing (WGS) of multiple bacterial isolates per patient showed that V. cholerae can evolve modest genetic diversity during symptomatic infection. To further explore the extent of V. cholerae within-host diversity, we applied culture-based WGS and metagenomics to a cohort of both symptomatic and asymptomatic cholera patients from Bangladesh. While metagenomics allowed us to detect more mutations in symptomatic patients, WGS of cultured isolates was necessary to detect V. cholerae diversity in asymptomatic carriers, likely due to their low V. cholerae load. Using both metagenomics and isolate WGS, we report three lines of evidence that V. cholerae hypermutators evolve within patients. First, we identified nonsynonymous in V. cholerae DNA repair genes in five out of 11 patient metagenomes sequenced with sufficient coverage of the V. cholerae genome, and in one of three patients with isolate genomes sequenced. Second, mutations in DNA repair genes tended to be accompanied by an excess of intrahost single nucleotide variants (iSNVs). Third, these iSNVs were enriched in transversion mutations, a known hallmark of hypermutator phenotypes. While hypermutators appeared to generate mostly selectively neutral mutations, non-mutators showed signs of convergent mutation across multiple patients, suggesting V. cholerae adaptation within hosts. Our results highlight the power and limitations of metagenomics combined with isolate sequencing to characterize within-patient diversity in acute V. cholerae infections, while providing evidence for hypermutator phenotypes within cholera patients. IMPORTANCE Pathogen evolution within patients can impact phenotypes such as drug resistance and virulence, potentially affecting clinical outcomes. V. cholerae infection can result in life-threatening diarrheal disease, or asymptomatic infection. Here we describe whole-genome sequencing of V. cholerae isolates and culture-free metagenomic sequencing from stool of symptomatic cholera patients and asymptomatic carriers. Despite the typically short duration of cholera, we found evidence for adaptive mutations in the V. cholerae genome that occur independently and repeatedly within multiple symptomatic patients. We also identified V. cholerae hypermutator phenotypes within several patients, which appear to generate mainly neutral or deleterious mutations. Our work sets the stage for future studies of the role of hypermutators and within-patient evolution in explaining the variation from asymptomatic carriage to symptomatic cholera.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.224
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes2
Has abstractyes

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