Fourteen-Genome Comparison Identifies DNA Markers for Severe-Disease-Associated Strains of Clostridium difficile
Bibliographic record
Abstract
Clostridium difficile is a common cause of infectious diarrhea in hospitalized patients. A severe and increased incidence of C. difficile infection (CDI) is associated predominantly with the NAP1 strain; however, the existence of other severe-disease-associated (SDA) strains and the extensive genetic diversity across C. difficile complicate reliable detection and diagnosis. Comparative genome analysis of 14 sequenced genomes, including those of a subset of NAP1 isolates, allowed the assessment of genetic diversity within and between strain types to identify DNA markers that are associated with severe disease. Comparative genome analysis of 14 isolates, including five publicly available strains, revealed that C. difficile has a core genome of 3.4 Mb, comprising ∼ 3,000 genes. Analysis of the core genome identified candidate DNA markers that were subsequently evaluated using a multistrain panel of 177 isolates, representing more than 50 pulsovars and 8 toxinotypes. A subset of 117 isolates from the panel had associated patient data that allowed assessment of an association between the DNA markers and severe CDI. We identified 20 candidate DNA markers for species-wide detection and 10,683 single nucleotide polymorphisms (SNPs) associated with the predominant SDA strain (NAP1). A species-wide detection candidate marker, the sspA gene, was found to be the same across 177 sequenced isolates and lacked significant similarity to those of other species. Candidate SNPs in genes CD1269 and CD1265 were found to associate more closely with disease severity than currently used diagnostic markers, as they were also present in the toxin A-negative and B-positive (A-B+) strain types. The genetic markers identified illustrate the potential of comparative genomics for the discovery of diagnostic DNA-based targets that are species specific or associated with multiple SDA strains.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".