Prevalence and Characterization of Shiga Toxin-Producing and Enteropathogenic Escherichia coli in Shellfish-Harvesting Areas and Their Watersheds
Bibliographic record
Abstract
During a two-year study, the presence of Shiga-toxin producing E. coli (STEC) and enteropathogenic E. coli (EPEC) was investigated in shellfish (n=238), seawater (n=12) and surface sediment (n=39) collected from three French coastal shellfish-harvesting areas and freshwaters (n=216) in their watersheds. PCR detection of Shiga toxin- (stx1/stx2) and intimin- (eae) genes following enrichment from these samples revealed the presence of least one of the stx genes in 30.3% of shellfish batches, 85.9% of freshwater, 41.7% of seawater, and 28.2% of sediment samples, while the eae gene was observed in 74.8%, 100%, 100%, and 43.6% of shellfish batches, freshwater, seawater, and sediment samples, respectively. Twenty-eight STEC and 89 EPEC strains were isolated and analyzed in order to determine their serotype, phylogroup, and genetic relatedness and to evaluate the presence of the saa and ehxA genes encoding the STEC autoagglutinating adhesin and the enterohemolysin A, respectively. Finally, the ability to form biofilms and antimicrobial susceptibility were investigated for a selection of strains. Eighteen serotypes were identified among the STEC isolates and 57 among the EPEC isolates. A high diversity was observed within these strains, as 79 different PFGE patterns and 48 distinguishable sequence types were identified. Strains were found to belong mainly to phylogroups B1 and B2 and virulence was observed to be low as more than 85% of the strains possessed only stx1, stx2 or eae genes. One STEC and several EPEC strains belonged to three of the five highly pathogenic serogroups (i.e., O26, O103, and O145). The subset of strains tested for their capacity to form biofilms was mainly strongly to moderately adherent and more strains formed a strong biofilm at 18°C than at 30°C. Finally, more than 85% of analyzed strains were found to be sensitive to the 16 tested antibiotics. These data suggest the low risk of human infection by STEC if shellfish from these shellfish-harvesting areas were consumed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".