Identification and Mechanism of Evolution of New Alleles Coding for the AIDA-I Autotransporter of Porcine Pathogenic Escherichia coli
Bibliographic record
Abstract
Autotransporters are a large family of virulence factors of Gram-negative bacterial pathogens. The autotransporter adhesin involved in diffuse adherence (AIDA-I) is an outer membrane protein of Escherichia coli, which allows binding to epithelial cells as well as the autoaggregation of bacteria. AIDA-I is glycosylated by a specific heptosyltransferase encoded by the aah gene that forms an operon with the aidA gene. aidA is highly prevalent in strains that cause disease in pigs. Nevertheless, there are only two published whole-length sequences for this gene. In this study, we sequenced the aah and aidA genes of 24 aidA-positive porcine strains harboring distinct virulence factor profiles. We compared the obtained sequences and performed phylogenetic and pulsed-field electrophoresis analyses. Our results suggest that there are at least 3 different alleles for aidA, which are associated with distinct virulence factor profiles. The genes are found on high-molecular-weight plasmids and seem to evolve via shuffling mechanisms, with one of the sequences showing evidence of genetic recombination. Our work suggests that genetic plasticity allows the evolution of aah-aidA alleles that are selected during pathogenesis.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".