Analysis of Cyanobacteria and its Abundance in the Turkey Lakes Watershed using Molecular Techniques
Notice bibliographique
Résumé
Toxic cyanobacterial blooms continue to pose a threat to the quality and safety of drinking water globally by producing toxins and forming dense surface blooms. Forested watersheds naturally provide high quality drinking water to various communities but are threatened by bloom events that are increasing due to warming climates and anthropogenic land use. Monitoring programs utilized in drinking water sources are required to adapt to the changing intensity and frequency of these blooms where observation of cyanobacterial composition and abundance may vary based on sampling efforts. However, due to the variation and adaptability of these organisms spatially and temporally, cyanobacteria are often overlooked if surface blooms are not visualized, where these organisms may be present and abundant throughout the water column at different depths and vary throughout the day. The undetected organisms may release potent toxins that are threats to drinking water security if left untreated. The harmful toxic blooms comprise of cyclic hepatotoxins, involved in causing severe liver damage and affecting human and aquatic health. The aim of this study was to identify and quantify the cyanobacterial community composition and abundance of potential toxin producing genes in an oligotrophic northern forested watershed (Turkey Lakes Watershed, Ontario, Canada). \n\tTo evaluate the composition and abundance, water samples were collected from Little Turkey Lake in May, June, July, and August 2022 at integrated and varying depths to determine variability over a summer season and at different timepoints in a single day. Microbial DNA was extracted from the water samples for 16S rRNA gene sequencing where data was obtained for bioinformatic and phylogenetic analyses. Extracted samples underwent quantitative PCR analysis for identification of gene copy numbers of cyanobacteria and potential microcystin producing organisms. With the extension of the ice-free season through warmer temperatures, and changes in environmental parameters, cyanobacteria and potential cyanotoxin producers appeared as early as May in this oligotrophic lake system. Peak abundances of cyanobacterial and potential cyanotoxin producing gene copy numbers were observed in the months of July and August, without visible blooms during sampling. Cyanobacterial composition had variability between the months, days, and timepoints when sampling, demonstrating the importance of consisting monitoring and sampling efforts due to the changing composition and abundance. Variation was observed among the depths within the water column, where integrated sampling provided a snapshot of the water system and can be useful for efficient analysis of the system, but multiple depth sampling is more representative of the community composition and abundance of cyanobacteria. This illustrates that monitoring protocols for drinking water sources require evaluation for the appropriate sampling protocol, timepoints, and location of the water column as each water system is unique. \n\tThis research provides insight into cyanobacterial emergence in earlier summer months in an oligotrophic water system. It is applicable for the development of monitoring and drinking water treatment protocols for toxin-producing cyanobacteria, where analysis of the full water column is required with consistent sampling and integrated sampling is efficient, especially when there is an absence of a visible surface bloom. The inclusion of molecular characterization (amplicon sequencing and qPCR) is a valuable tool that can be cost efficient and effective ways to analyze samples. This research can then be expanded to other toxins and secondary metabolites produced by cyanobacteria.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».