Detection of Antibiotic Resistance Genes in Source and Drinking Water Samples from a First Nations Community in Canada
Bibliographic record
Abstract
UNLABELLED: Access to safe drinking water is now recognized as a human right by the United Nations. In developed countries like Canada, access to clean water is generally not a matter of concern. However, one in every five First Nations reserves is under a drinking water advisory, often due to unacceptable microbiological quality. In this study, we analyzed source and potable water from a First Nations community for the presence of coliform bacteria as well as various antibiotic resistance genes. Samples, including those from drinking water sources, were found to be positive for various antibiotic resistance genes, namely, ampC, tet(A), mecA, β-lactamase genes (SHV-type, TEM-type, CTX-M-type, OXA-1, and CMY-2-type), and carbapenemase genes (KPC, IMP, VIM, NDM, GES, and OXA-48 genes). Not surprisingly, substantial numbers of total coliforms, including Escherichia coli, were recovered from these samples, and this result was also confirmed using Illumina sequencing of the 16S rRNA gene. These findings deserve further attention, as the presence of coliforms and antibiotic resistance genes potentially puts the health of the community members at risk. IMPORTANCE: In this study, we highlight the poor microbiological quality of drinking water in a First Nations community in Canada. We examined the coliform load as well as the presence of antibiotic resistance genes in these samples. This study examined the presence of antibiotic-resistant genes in drinking water samples from a First Nations Community in Canada. We believe that our findings are of considerable significance, since the issue of poor water quality in First Nations communities in Canada is often ignored, and our findings will help shed some light on this important issue.
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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".