Uncoupling between core genome and virulome in extraintestinal pathogenic <i>Escherichia coli</i>
Bibliographic record
Abstract
Extraintestinal pathogenic Escherichia coli (ExPEC) are among the most frequently isolated bacterial pathogens in hospitals. They are considered opportunistic pathogens and are found mostly in urinary and bloodstream infections. They are genetically diverse, and many studies have sought associations between genotypes or virulence genes and infection site, severity, or outcome, with varied, often contradictory, results. To understand these difficulties, we have analyzed the diversity patterns in the core genomes and virulomes of more than 500 ExPEC isolates from 5 different collections. The core genome was analyzed using a multilocus sequence type-based single-nucleotide polymorphism (SNP) pyrosequencing approach, while the virulence gene content (the virulome) was studied by polymerase chain reaction detection of 25 representative genes. SNP typing showed a similar population structure in the different collections: half of the isolates belong to a few sequence types (5 to 8), while the other half is composed of a large diversity of sequence types that are found once or twice. Sampling analysis by rarefaction plots of SNP profiles showed saturation curves indicative of a limited diversity. Contrary to this, the virulome shows an extremely high diversity, with almost as many gene profiles as isolates, and linear, nonsaturating, rarefaction plots, even within sequence types. These data show that genetic exchange rates are very heterogeneous along the chromosome, being much higher in the virulome fraction of the genome than in the core genome.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".