Assessing microbial community dynamics and functional shifts due to wastewater discharge using advanced molecular techniques
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».