Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea
The excessive input of nutrients into rivers can lead to contamination and eutrophication, which poses a threat to the health of aquatic ecosystems. It is crucial to identify the sources of contaminants to develop effective management plans for eutrophication. However, traditional methods for identi...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Microbiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1111297/full |
| _version_ | 1797840533339504640 |
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| author | Jie Ma Qiuying Lai Fei He Xuhan Zhang Jian Shui Minghui Yu Geng Wei Weixin Li |
| author_facet | Jie Ma Qiuying Lai Fei He Xuhan Zhang Jian Shui Minghui Yu Geng Wei Weixin Li |
| author_sort | Jie Ma |
| collection | DOAJ |
| description | The excessive input of nutrients into rivers can lead to contamination and eutrophication, which poses a threat to the health of aquatic ecosystems. It is crucial to identify the sources of contaminants to develop effective management plans for eutrophication. However, traditional methods for identifying pollution sources have been insufficient, making it difficult to manage river health effectively. High-throughput sequencing offers a novel method for microbial community source tracking, which can help identify dominant pollution sources in rivers. The Wanggang River was selected for study, as it has suffered accelerated eutrophication due to considerable nutrient input from riparian pollutants. The present study identified the dominant microbial communities in the Wanggang River basin, including Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Verrucomicrobia, and Firmicutes. The Source Tracker machine-learning classification system was used to create source-specific microbial community fingerprints to determine the primary sources of contaminants in the basin, with agricultural fertilizer being identified as the main pollutant source. By identifying the microbial communities of potential pollution sources, the study determined the contributing pollutant sources in several major sections of the Wanggang River, including industry, urban land, pond culture, and livestock land. These findings can be used to improve the identification of pollution sources in specific environments and develop effective pollution management plans for polluted river water. |
| first_indexed | 2024-04-09T16:16:54Z |
| format | Article |
| id | doaj.art-4ead70ecc9b74442820f617e47a60a3a |
| institution | Directory Open Access Journal |
| issn | 1664-302X |
| language | English |
| last_indexed | 2024-04-09T16:16:54Z |
| publishDate | 2023-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Microbiology |
| spelling | doaj.art-4ead70ecc9b74442820f617e47a60a3a2023-04-24T04:35:27ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2023-04-011410.3389/fmicb.2023.11112971111297Microbial source tracking identifies sources of contamination for a river flowing into the Yellow SeaJie Ma0Qiuying Lai1Fei He2Xuhan Zhang3Jian Shui4Minghui Yu5Geng Wei6Weixin Li7Nanjing Institute of Environment Sciences, Ministry of Ecology and Environment, Nanjing, ChinaNanjing Institute of Environment Sciences, Ministry of Ecology and Environment, Nanjing, ChinaNanjing Institute of Environment Sciences, Ministry of Ecology and Environment, Nanjing, ChinaCollege of Hydrology and Water Resources, Hohai University, Nanjing, ChinaCollege of Hydrology and Water Resources, Hohai University, Nanjing, ChinaCollege of Hydrology and Water Resources, Hohai University, Nanjing, ChinaCollege of Hydrology and Water Resources, Hohai University, Nanjing, ChinaNanjing Institute of Environment Sciences, Ministry of Ecology and Environment, Nanjing, ChinaThe excessive input of nutrients into rivers can lead to contamination and eutrophication, which poses a threat to the health of aquatic ecosystems. It is crucial to identify the sources of contaminants to develop effective management plans for eutrophication. However, traditional methods for identifying pollution sources have been insufficient, making it difficult to manage river health effectively. High-throughput sequencing offers a novel method for microbial community source tracking, which can help identify dominant pollution sources in rivers. The Wanggang River was selected for study, as it has suffered accelerated eutrophication due to considerable nutrient input from riparian pollutants. The present study identified the dominant microbial communities in the Wanggang River basin, including Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Verrucomicrobia, and Firmicutes. The Source Tracker machine-learning classification system was used to create source-specific microbial community fingerprints to determine the primary sources of contaminants in the basin, with agricultural fertilizer being identified as the main pollutant source. By identifying the microbial communities of potential pollution sources, the study determined the contributing pollutant sources in several major sections of the Wanggang River, including industry, urban land, pond culture, and livestock land. These findings can be used to improve the identification of pollution sources in specific environments and develop effective pollution management plans for polluted river water.https://www.frontiersin.org/articles/10.3389/fmicb.2023.1111297/fullrivermicrobial communitythe Source Trackereutrophicationpollution sources |
| spellingShingle | Jie Ma Qiuying Lai Fei He Xuhan Zhang Jian Shui Minghui Yu Geng Wei Weixin Li Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea Frontiers in Microbiology river microbial community the Source Tracker eutrophication pollution sources |
| title | Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea |
| title_full | Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea |
| title_fullStr | Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea |
| title_full_unstemmed | Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea |
| title_short | Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea |
| title_sort | microbial source tracking identifies sources of contamination for a river flowing into the yellow sea |
| topic | river microbial community the Source Tracker eutrophication pollution sources |
| url | https://www.frontiersin.org/articles/10.3389/fmicb.2023.1111297/full |
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