The occurrence of subtilase-cytotoxin-encoding genes in environmental <i>Escherichia coli</i> isolated from a Northern California estuary
Bibliographic record
Abstract
The presence of subtilase-cytotoxin-encoding genes was determined in 397 environmental Escherichia coli strains isolated from water, suspended solids, and sediments sampled from different hydrological and environmental conditions in a California estuary. A total of 7 strains (1.76%) were found to harbor subtilase-cytotoxin-encoding genes. Using primers targeting subA only, we generated PCR amplicons from 2 strains; while using primers targeting the 3' end of SubA downstream to the 5' end of SubB, amplicons of 232 bp were generated from 5 additional strains. The 556 bp subA sequences were almost identical to that in the subtilase-cytotoxin-positive strain ED 591 (98%), while subAB sequences of 2 non-Shiga-toxigenic strains revealed 100% similarity with the Shiga-toxigenic E. coli O113:H21 strain 98NK2 that was isolated from an outbreak of hemolytic uremic syndrome. Additionally, the serogroup O113:H21 was present in this collection of environmental E. coli, and it was found to harbor stx2d, hra1 that encodes the heat resistant agglutinin 1, and a subAB sequence similar to that in the non-Shiga-toxigenic E. coli subtilase cytotoxin strain ED 591. To further understand potential health risks posed by strains encoding SubAB, future epidemiological studies should consider screening isolates for subAB regardless of the presence of Shiga-toxin-encoding genes.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".