Assessing microbial community dynamics and functional shifts due to wastewater discharge using advanced molecular techniques
Bibliographic record
Abstract
Microbial communities play important roles in freshwater biodiversity, which is increasingly at risk from human activities. Wastewater discharges are particularly concerning, as they introduce pollutants, nutrients, and exogenous microorganisms that can alter natural microbial populations. However, the effects of wastewater treatment plant (WWTP) effluents on these communities remain poorly understood. This thesis investigates the effects of WWTP effluents and agricultural runoff on microbial communities in southern Saskatchewan, Canada, integrating molecular and environmental analyses to provide a comprehensive assessment of these impacts. During the first field season (2021), the effects of effluents from five WWTPs on microbial taxonomic diversity and community composition were analyzed using DNA metabarcoding, alongside assessments of nutrient and pollutant levels. The comparison across streams revealed that microbial community composition varied more significantly among different streams than between upstream and downstream sites within the same stream, except for Wascana Creek. This suggests that local environmental factors, such as stream size, flow dynamics, and land use, exert a greater influence on shaping microbial communities than proximity to WWTP discharge alone. Despite these differences in overall community composition, there were similar patterns in downstream communities across all streams such as the decline of sulfur-oxidizing bacteria, indicating disruptions to sulfur cycling. Furthermore, certain microbial taxa emerged as consistent indicators of WWTP-related pollution, demonstrating potential utility as bioindicators. Among the studied streams, Wascana Creek exhibited the most pronounced impacts, with downstream sites showing high nutrient and pollutant loads, reduced biodiversity, the occurrence of cyanotoxins, and the dominance of taxa associated with anthropogenic pollution and eutrophication. To further explore these patterns, a detailed follow-up study was conducted in Wascana Creek during the second field season (2022). This study combined DNA metabarcoding and GeoChip microarray analyses with evaluations of nutrient concentrations, greenhouse gas (GHG) saturation, and pollutant levels. Agricultural runoff in the upper reaches led to increased phosphorus levels, leading to anoxic conditions, cyanobacterial blooms, and fish mortality. Furthermore, methane (CH4) and carbon dioxide (CO2) saturations increased, along with methanogenic microorganisms and sulfate-reducing bacteria, highlighting the effects of low-oxygen conditions. Downstream of the Regina WWTP, effluent exposure led to increased nitrogen concentrations and nitrous oxide (N₂O) saturation, which correlated with significant shifts in nitrogen cycling pathways. GeoChip analysis revealed increases in genes associated with nitrogen metabolism, including those linked to N₂O reduction. Additionally, functional gene analysis showed increased abundances of antimicrobial resistance genes, and genes involved in contaminant degradation and metal detoxification, underscoring the introduction of effluent-derived stressors. A notable increase in viral marker genes, particularly those targeting eukaryotic hosts, further indicated significant shifts in viral community composition. Across both field seasons, consistent patterns emerged, including the dominance of pollutant-tolerant taxa and the presence of cyanotoxins downstream of the Regina WWTP. These shifts not only indicate changes in microbial diversity but also signify functional transformations with profound implications for ecosystem processes, including nutrient cycling and GHG emissions. This thesis highlights the dual role of microbial communities as indicators and mediators of environmental health. By integrating taxonomic and functional assessments, it provides a holistic understanding of how microbial communities adapt and respond to pollution. The findings underscore the potential of microbial taxa as bioindicators and offer a foundation for future research into microbial dynamics and their application in environmental monitoring and ecosystem 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".