Investigation of the presence and impact of environmentally-adapted Escherichia coli in private well water in southeastern Ontario
Bibliographic record
Abstract
The fecal contamination of drinking water causing acute gastrointestinal illness remains a threat to public health in Canada, including Ontario, particularly in rural regions reliant on private well water. To determine potability, water is assessed for the presence of fecal indicator bacteria (FIB) to indicate contamination with harmful fecal pathogens. Escherichia coli remains the most frequently employed FIB, given it is a natural inhabitant of the gastrointestinal tract (GIT) of warm-blooded animals. However, the use of E. coli as a FIB has been questioned in recent years with the identification of populations of environmentally-adapted E. coli capable of survival and growth outside of the GIT, including in water and soil. Environmentally-adapted E. coli do not represent a recent fecal contamination event and thus challenge the current dogma that the presence of E. coli in water always reflects recent contamination from a fecal source and the potential presence of fecal pathogens. This study hypothesizes that environmentally-adapted E. coli populations are present in private well water in southeastern Ontario. Environmentally-adapted populations were characterized by comparing the genetic signature and phylogenetic origin of E. coli isolates obtained directly from feces of a variety of hosts to that obtained from domestic private well water samples, both collected from southeastern Ontario. Quantitative polymerase chain reaction and accessory gene fingerprinting were employed to facilitate identifying genetic fingerprints unique to well water and, in combination with phylogroup analysis, this revealed the presence of environmentally-adapted E. coli populations in 66% of the 76 E. coli positive wells analyzed. All isolates sampled from 37% of E. coli positive wells were exclusively of environmentally-adapted populations. These findings show that environmentally-adapted E. coli are widespread in domestic private well water in southeastern Ontario. This is the first study to investigate and report the presence of environmentally-adapted E. coli in private well water. As a result, the reassessment of E. coli as the principle FIB is required, as well as a review of current water quality testing methodology and interpretation. These findings may inform future drinking water quality guidelines, policy, and public health risk assessment.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".