Occurrence of Diarrheagenic Virulence Genes and Genetic Diversity in <i>Escherichia coli</i> Isolates from Fecal Material of Various Avian Hosts in British Columbia, Canada
Bibliographic record
Abstract
Contamination of surface water by fecal microorganisms originating from human and nonhuman sources is a public health concern. In the present study, Escherichia coli isolates (n = 412) from the feces of various avian host sources were screened for various virulence genes: stx1 and stx2 (Shiga toxin-producing E. coli [STEC]), eae (enteropathogenic E. coli [EPEC]), est-h, est-p, and elt (encoding heat-stable toxin [ST] variants STh and STp and heat-labile toxin [LT], respectively) (enterotoxigenic E. coli [ETEC]), and ipaH (enteroinvasive E. coli [EIEC]). None of the isolates were found to be positive for stx1, while 23% (n = 93) were positive for only stx2, representing STEC, and 15% (n = 63) were positive for only eae, representing EPEC. In addition, five strains obtained from pheasant were positive for both stx2 and eae and were confirmed as non-O157 by using an E. coli O157 rfb (rfbO157) TaqMan assay. Isolates positive for the virulence genes associated with ETEC and EIEC were not detected in any of the hosts. The repetitive element palindromic PCR (rep-PCR) fingerprint analysis identified 143 unique fingerprints, with an overall Shannon diversity index of 2.36. Multivariate analysis of variance (MANOVA) showed that the majority of the STEC and EPEC isolates were genotypically distinct from nonpathogenic E. coli and clustered independently. MANOVA analysis also revealed spatial variation among the E. coli isolates, since the majority of the isolates clustered according to the sampling locations. Although the presence of virulence genes alone cannot be used to determine the pathogenicity of strains, results from this study show that potentially pathogenic STEC and EPEC strains can be found in some of the avian hosts studied and may contaminate surface water and potentially impact human health.
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 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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".