Investigating the role of residual antibiotics on the promotion of antimicrobial resistance in multi-species drinking water biofilms
Bibliographic record
Abstract
Antimicrobial resistance (AMR) is one of our top global public health threats, necessitating research on identifying factors that are contributing to its development and spread. This thesis identifies the residual levels of antibiotics detected in tap water interacting with drinking water biofilms, as a potential factor. To investigate this, a series of controlled experiments were conducted using a novel, bench-top drinking water reactor (BWDR). The BWDR was composed of looping polyvinyl chloride (PVC) pipe as found in premise plumbing, and simulated the chemical, biological, and hydraulic conditions found in drinking water systems. The BWDRs were used to grow multi-species biofilms with bacteria native to Lake Ontario for the experiments. The most commonly reported antibiotics in drinking water, ciprofloxacin and sulfamethoxazole, were investigated at environmentally relevant, residual concentrations to examine their persistence, as well as whether they could promote and subsequently disseminate bacteria harbouring antibiotic resistance genes (ARGs) to consumers at the tap. The experimental results produced new insights on: (1) the degradation kinetics of the aforementioned antibiotics, which showed a decreased, but detectable concentration after 12 days of exposure to the biofilms and a PVC-only control; (2) the baseline abundance and expression of ARGs in biofilms and tap water bacteria sourced from Lake Ontario, which were found to actively express intI1, sul1, and sul2; (3) the AMR effects of each antibiotic, where ciprofloxacin induced an increase in biomass, whereas sulfamethoxazole was found to correlate with ARG abundance and expression; and (4) the genera in the biofilm that were associated with ARG promotion. The research results are the first to assess the expression ARGs in drinking water biofilms and provide evidence to warrant the attention of public health officials and municipal management.
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 | 0.000 |
| 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 | 0.001 | 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".