Metabolomics for biomonitoring: an evaluation of the metabolome as an indicator of aquatic ecosystem health
Notice bibliographique
Résumé
Global degradation of aquatic ecosystems has initiated widespread use of biomonitoring to inform management. Current biomonitoring programs typically apply biomarkers (e.g., vitellogenin) and (or) measurements of community composition (e.g., algae or benthic macroinvertebrates) as indicators to assess ecosystem condition. However, independently these indicators may fail to provide either ecologically significant (a limitation of biomarkers) or early warning (a limitation of population and community measures) information to aquatic managers. Environmental metabolomics studies the relationship between an organism’s environment and its metabolome (i.e., description of the state of molecules produced or consumed during an organism’s metabolic processes, e.g., amino acids). Shifts in the metabolome occur because of stress-driven changes in resource allocation and are often indicative of changes in organism fitness. The metabolome of target species may thus be an effective bioindicator; however, it has not been evaluated for use in aquatic biomonitoring. Our objectives were threefold: introduce and describe metabolomics, evaluate the metabolome as a bioindicator, and provide recommendations for integration of metabolomics into biomonitoring. We conclude that the metabolome meets many bioindicator criteria and the potential to meet the remaining criteria following further research. Specifically, we concluded the metabolome is grounded in sound ecological theory while also having the potential to be a priori predictive and to assess ecological functions. Although the reliability of the metabolome to detect change needs further study, there is growing evidence that the metabolome can detect changes in human impact and discriminate between stressors. We provide an example of this capability with a case study assessment of municipal wastewater. Practically, the metabolome can be readily integrated into existing biomonitoring protocols. However, the ability of agencies to adopt metabolomics-based biomonitoring may be impeded by a lack of understanding of metabolomics within institutions and difficulty of communication with stakeholders. We suggest training or hiring of appropriate personnel and the generation of a common metabolomics language as mechanisms for overcoming this impediment. We conclude that background knowledge for metabolomics-based monitoring is sufficient for agency-based pilot projects aimed at assessing ecological status of aquatic ecosystems. However, continued development may ultimately provide early warning and diagnostic assessments of aquatic impacts.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 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) | 0,007 | 0,001 |
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 tête enseignante, 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 ».