Bacterial diversity and resistome analysis of drinking water stored in cisterns from two First Nations communities in Manitoba, Canada
Bibliographic record
Abstract
The microbiological content of water is an ongoing concern in First Nations communities in Canada. Many communities lack water treatment plants and continue to be under drinking water advisories. However, lack of access to treatment plants is only a part of the problem as poor water distribution systems also contribute to the failure to provide safe drinking water. Here, we studied the microbial diversity and antibiotic resistome from water stored in cisterns from two First Nations communities in Manitoba, Canada. We found that the cistern water contained a high number of bacteria and showed the presence of diverse antimicrobial resistance genes. Interestingly, the bacterial diversity and antimicrobial resistance genes varied considerably from that of the untreated source water, indicating that the origin of contamination in the cistern water came from within the treatment plant or along the delivery route to the homes. Our study highlights the importance of proper maintenance of the water distribution system in addition to access to water treatment facilities to ensure a supply of safe water to First Nations communities in Canada.IMPORTANCEThe work described addresses a critical issue in First Nations communities in Canada-the microbiological content of water. Many of these communities lack access to water treatment plants and frequently experience drinking water advisories. This study focused on the microbial diversity and antibiotic resistome in water stored in cisterns within two First Nations communities in Manitoba, Canada. These findings reveal that cistern water, a common source of drinking water in these communities, contains a high number of bacteria and a wide range of antimicrobial resistance genes. This highlights a serious health risk as exposure to such water can lead to the spread of drug-resistant infections, posing a threat to the well-being of the residents.
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) | 0.001 | 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 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".