EFFECTS OF ANTIMICROBIAL COMPOUNDS ON EARLY LIFE STAGES OF CANADIAN FISH SPECIES
Bibliographic record
Abstract
Antimicrobial compounds are widely used in pharmaceuticals, personal care products, and disinfectants, leading to their continuous release into aquatic environments through wastewater effluents. Despite wastewater treatment, many of these compounds persist in surface waters, where they may pose risks to aquatic organisms, particularly fish. The ecological implications of such exposure remain poorly understood, especially for non-model fish species native to North American freshwater ecosystems. This thesis investigates the lethal and sub-lethal toxicity responses of both legacy (triclosan, TCS) and emerging (chloroxylenol, PCMX; methylisothiazolinone, MIT) antimicrobial compounds to early-life stages (ELS) of three freshwater fish species: rainbow trout (Oncorhynchus mykiss), lake trout (Salvelinus namaycush), and white sucker (Catostomus commersonii). The overarching goal was to characterize species-specific responses to these contaminants and to identify molecular and apical endpoints that can help inform toxicological risk assessments. To achieve this goal, two experimental studies were conducted. In the first study (Chapter 3), rainbow trout embryos were exposed to graded nominal concentrations (0.39-400 µg/L) of TCS, PCMX, and MIT for 28 days (i.e., 2 weeks post-swim-up). Apical endpoints – including mortality, developmental abnormalities, time to swim-up, and histopathological changes – were assessed, alongside transcriptomic profiling using the EcoToxChip RT-qPCR platform after the initial 96 hours of exposure. Exposure to TCS and PCMX resulted in significant mortality and developmental abnormalities, including jaw deformities, yolk sac edema, and spinal curvature. The calculated 28-day LC50 values were 107 µg/L for TCS and 254 µg/L for PCMX based on measured concentrations. MIT exposure did not induce significant apical effects. Transcriptomic analysis revealed 55 and 25 differentially expressed genes (DEGs) in response to TCS and PCMX, respectively, with shared dysregulation of 19 genes linked to endocrine, metabolic, and reproductive pathways. These molecular disruptions aligned with observed phenotypic effects, suggesting similar modes of action for TCS and PCMX. MIT elicited minimal transcriptomic changes, indicating a lower hazard profile under the tested conditions. In the second study (Chapter 4), newly hatched lake trout and white sucker embryos were exposed to TCS and PCMX for 50 and 28 days, respectively. Similar apical endpoints were evaluated to compare interspecies sensitivity. For both species, exposure to TCS resulted in higher mortality and more frequent developmental abnormalities than PCMX. The 50-day LC50 for lake trout exposed to TCS was 25 µg/L, while the 28-day LC50 for white sucker was 37 µg/L (TCS) and 111 µg/L (PCMX), based on measured concentrations. Lake trout exhibited greater sensitivity than white sucker, with significant increases in jaw deformities and yolk sac edema. In contrast, white suckers showed no statistically significant developmental abnormalities, though mortality was observed at higher concentrations. Swim-up delays were noted in both species, particularly with TCS exposure, indicating potential sublethal effects on developmental timing and metabolic status. Overall, this research demonstrated that both TCS and PCMX adversely affected the early-life stage of the freshwater fish species tested, with TCS exhibiting greater toxicity. ELS fish exhibited mortality and developmental abnormalities, and their genes were differentially expressed when exposed to TCS and PCMX. The integration of transcriptomic and apical endpoints provided mechanistic insights into the modes of action of these compounds and supported the use of molecular tools like the EcoToxChip as a new approach method (NAM) to provide insights into the mechanisms of action of these antimicrobials. The minimal effects observed with MIT on ELS rainbow trout suggest it may be a less hazardous alternative, although further research is needed to evaluate its long-term impacts across life stages and species. These findings contribute critical toxicity data for antimicrobials by expanding toxicity testing to non-model species and early developmental stages. Future research should explore chronic and reproductive toxicity of these compounds, expand molecular profiling to additional species, and investigate the combined effects of antimicrobial mixtures to better reflect real-world exposure scenarios and inform more protective environmental guidelines.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".