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Metagenomics-Based Microbial Ecological Community Threshold and Indicators of Anthropogenic Disturbances in Estuarine Sediments.
Bao, Yingyu; Ruan, Yuefei; Wu, Jiaxue; Wang, Wen-Xiong; Leung, Kenneth M Y; Lee, Patrick K H.
Afiliação
  • Bao Y; School of Energy and Environment and State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong SAR, China.
  • Ruan Y; State Key Laboratory of Marine Pollution and Department of Chemistry, City University of Hong Kong, Hong Kong SAR, China.
  • Wu J; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China.
  • Wang WX; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519000, China.
  • Leung KMY; School of Energy and Environment and State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong SAR, China.
  • Lee PKH; Research Centre for the Oceans and Human Health, City University of Hong Kong Shenzhen Research Institute, Shenzhen 518057, China.
Environ Sci Technol ; 58(1): 780-794, 2024 Jan 09.
Article em En | MEDLINE | ID: mdl-38118133
ABSTRACT
Assessing the impacts of cumulative anthropogenic disturbances on estuarine ecosystem health is challenging. Using spatially distributed sediments from the Pearl River Estuary (PRE) in southern China, which are significantly influenced by anthropogenic activities, we demonstrated that metagenomics-based surveillance of benthic microbial communities is a robust approach to assess anthropogenic impacts on estuarine benthic ecosystems. Correlational and threshold analyses between microbial compositions and environmental conditions indicated that anthropogenic disturbances in the PRE sediments drove the taxonomic and functional variations in the benthic microbial communities. An ecological community threshold of anthropogenic disturbances was identified, which delineated the PRE sediments into two groups (H and L) with distinct taxa and functional traits. Group H, located nearshore and subjected to a higher level of anthropogenic disturbances, was enriched with pollutant degraders, putative human pathogens, fecal pollution indicators, and functional traits related to stress tolerance. In contrast, Group L, located offshore and subjected to a lower level of anthropogenic disturbances, was enriched with halotolerant and oligotrophic taxa and functional traits related to growth and resource acquisition. The machine learning random forest model identified a number of taxonomic and functional indicators that could differentiate PRE sediments between Groups H and L. The identified ecological community threshold and microbial indicators highlight the utility of metagenomics-based microbial surveillance in assessing the adverse impacts of anthropogenic disturbances in estuarine sediments, which can assist environmental management to better protect ecosystem health.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Microbiota Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Microbiota Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article