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Enregistrement W2563602559

Microbial ecology of ammonia oxidation in the Grand River

2014· dissertation· en· W2563602559 sur OpenAlexaboutno aff
Puntipar Sonthiphand

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2014
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueWastewater Treatment and Nitrogen Removal
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEcologyAmmoniaMicrobial ecologyEnvironmental scienceEnvironmental chemistryChemistryBiologyBacteria
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The Grand River is the largest catchment in Southern Ontario and is heavily impacted by the results of human activities, including wastewater effluent and agricultural and urban runoff. Ammonia oxidation is an important biogeochemical process for maintaining ecosystem health in impacted rivers because high ammonium concentrations are toxic to aquatic life and affect drinking water quality. In this thesis, I focus on the microorganisms involved in aerobic and anaerobic ammonia oxidation within a freshwater context. Aerobic ammonia oxidizing bacteria (AOB) and archaea (AOA) oxidize ammonium to nitrite under oxic conditions, whereas anaerobic ammonia-oxidizing (anammox) bacteria oxidize ammonium and reduce nitrite to produce N2 gas under anoxic conditions. Anammox bacteria play an important role in removing fixed N from both engineered and natural ecosystems, yet broad scale distributions of anammox bacterial have not yet been summarized. Chapter 2 investigates global distributions and diversity of anammox bacteria and explores factors that influence their biogeography. Combined bioinformatics and multivariate analyses demonstrates that an important factor influencing anammox bacterial distributions was salinity, in addition to selection based on natural and engineered ecosystems. In Chapter 3, I address a limitation of anammox surveys, which is the specificity of primers used to study environmental distributions of anammox bacteria. The published primers commonly used in anammox surveys were verified for their specificity and tested by multiple molecular approaches, including denaturing gradient gel electrophoresis (DGGE), quantitative PCR (qPCR), and cloning. The A438f/A684r primer set was specific for anammox bacterial detection in freshwater environments. Because anammox bacteria are not the only microorganisms capable of ammonia oxidation, Chapter 4 investigates the oxidation of ammonium to nitrite by AOB and AOA under different environmental conditions. Both sediment and water column samples were studied to assess the impact of anthropogenic inputs on in-river microbial communities, identifying key players removing ammonium from the Grand River. DGGE demonstrated that wastewater effluent impacted the in-river microbial community downstream. Together, qPCR and RT-qPCR indicated that AOB and anammox are important within river sediments, reflecting a possible nitrification-anammox coupled process. However, only AOB were implicated in water column ammonia oxidation. This study also demonstrates the importance of combined molecular and activity-based studies for disentangling molecular signatures of wastewater effluent from autochthonous prokaryotic communities. In order to confirm that molecular signals corresponded to metabolic activity, the differential nitrification inhibitors (ATU and PTIO) were used in Chapter 5 to confirm AOB activity within the Grand River, for both sediment and water column samples. Urea hydrolysis was tested in parallel to nitrification activity, examining this alternative source of ammonium for fuelling ammonia oxidation within the river. The results confirmed the dominant activity of AOB in both sediment and water column samples collected downstream in waters receiving wastewater effluent. Water column AOB likely hydrolyzed urea and used the resulting ammonium as an energy source. In Chapter 6, the full length of the Grand River was sampled to identify the composition of bacterial taxa, as revealed by next-generation sequencing and bioinformatics. The major bacterial taxa detected along the river were Proteobacteria, Bacteroidetes, and Actinobacteria. The wastewater effluents harbored unique taxa, including TM6 and GN02; these two were poorly represented in the river itself. Distance-specific relationships, from the head to the mouth of the river, including hydrodynamics (i.e., lake and dam effects), were key factors correlating with measured in-river microbial communities. Water chemistry (i.e., pH, DOC, NO3-) showed weak correlations with in-river bacterial distributions. Together, my research demonstrates the biogeography of anammox bacteria and niche partitioning of AOB, AOA, and anammox bacteria within the heterogeneous microbial community background of the Grand River. This thesis represents an important step forward toward understanding the roles of microbial nitrogen cycling within aquatic habitats, especially those impacted by anthropogenic activities.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,754
Score d'incertitude au seuil0,965

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,006
Tête enseignante GPT0,178
Écart entre enseignants0,172 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2014
Routes d'admission1
Résumé présentoui

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