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Record W3115199828 · doi:10.1371/journal.ppat.1009181

Phylogenomics of 8,839 Clostridioides difficile genomes reveals recombination-driven evolution and diversification of toxin A and B

2020· article· en· W3115199828 on OpenAlexafffund
Michael J. Mansfield, Benjamin J.-M. Tremblay, Ji Zeng, Xin Wei, Harold Hodgins, Jay Worley, Lynn Bry, Min Dong, Andrew C. Doxey

Bibliographic record

VenuePLoS Pathogens · 2020
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of Waterloo
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentU.S. National Library of MedicineNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthBurroughs Wellcome FundUniversity of WaterlooNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaHarvard Digestive Diseases Center, Harvard UniversityOkinawa Institute of Science and Technology Graduate UniversityJapan Society for the Promotion of ScienceGovernment of OntarioIntellectual and Developmental Disabilities Research CenterBrigham and Women's Hospital
KeywordsClostridium difficile toxin BBiologyClostridium difficile toxin AHomologous recombinationSubtypingGeneticsGenomeClostridium difficilePhylogenomicsGenePhylogeneticsVirologyAntibiotics

Abstract

fetched live from OpenAlex

Clostridioides difficile is the major worldwide cause of antibiotic-associated gastrointestinal infection. A pathogenicity locus (PaLoc) encoding one or two homologous toxins, toxin A (TcdA) and toxin B (TcdB), is essential for C. difficile pathogenicity. However, toxin sequence variation poses major challenges for the development of diagnostic assays, therapeutics, and vaccines. Here, we present a comprehensive phylogenomic analysis of 8,839 C. difficile strains and their toxins including 6,492 genomes that we assembled from the NCBI short read archive. A total of 5,175 tcdA and 8,022 tcdB genes clustered into 7 (A1-A7) and 12 (B1-B12) distinct subtypes, which form the basis of a new method for toxin-based subtyping of C. difficile. We developed a haplotype coloring algorithm to visualize amino acid variation across all toxin sequences, which revealed that TcdB has diversified through extensive homologous recombination throughout its entire sequence, and formed new subtypes through distinct recombination events. In contrast, TcdA varies mainly in the number of repeats in its C-terminal repetitive region, suggesting that recombination-mediated diversification of TcdB provides a selective advantage in C. difficile evolution. The application of toxin subtyping is then validated by classifying 351 C. difficile clinical isolates from Brigham and Women's Hospital in Boston, demonstrating its clinical utility. Subtyping partitions TcdB into binary functional and antigenic groups generated by intragenic recombinations, including two distinct cell-rounding phenotypes, whether recognizing frizzled proteins as receptors, and whether it can be efficiently neutralized by monoclonal antibody bezlotoxumab, the only FDA-approved therapeutic antibody. Our analysis also identifies eight universally conserved surface patches across the TcdB structure, representing ideal targets for developing broad-spectrum therapeutics. Finally, we established an open online database (DiffBase) as a central hub for collection and classification of C. difficile toxins, which will help clinicians decide on therapeutic strategies targeting specific toxin variants, and allow researchers to monitor the ongoing evolution and diversification of C. difficile.

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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.257
Teacher spread0.218 · 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".

Quick stats

Citations80
Published2020
Admission routes2
Has abstractyes

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