Potential health risk assessment of cyanobacteria across global lakes
Cyanobacterial blooms pose environmental and health risks due to their production of toxic secondary metabolites. While current methods for assessing these risks have focused primarily on bloom frequency and intensity, the lack of comprehensive and comparable data on cyanotoxins makes it challenging...
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Veröffentlicht in: | Applied and environmental microbiology 2024-11, Vol.90 (11), p.e0193624 |
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creator | Hu, Hang Zhang, Zhenyan Chen, Bingfeng Zhang, Qi Xu, Nuohan Paerl, Hans W Wang, Tingzhang Hong, Wenjie Penuelas, Josep Qian, Haifeng |
description | Cyanobacterial blooms pose environmental and health risks due to their production of toxic secondary metabolites. While current methods for assessing these risks have focused primarily on bloom frequency and intensity, the lack of comprehensive and comparable data on cyanotoxins makes it challenging to rigorously evaluate these health risks. In this study, we examined 750 metagenomic data sets collected from 103 lakes worldwide. Our analysis unveiled the diverse distributions of cyanobacterial communities and the genes responsible for cyanotoxin production across the globe. Our approach involved the integration of cyanobacterial biomass, the biosynthetic potential of cyanotoxin, and the potential effects of these toxins to establish potential cyanobacterial health risks. Our findings revealed that nearly half of the lakes assessed posed medium to high health risks associated with cyanobacteria. The regions of greatest concern were East Asia and South Asia, particularly in developing countries experiencing rapid industrialization and urbanization. Using machine learning techniques, we mapped potential cyanobacterial health risks in lakes worldwide. The model results revealed a positive correlation between potential cyanobacterial health risks and factors such as temperature, N
O emissions, and the human influence index. These findings underscore the influence of these variables on the proliferation of cyanobacterial blooms and associated risks. By introducing a novel quantitative method for monitoring potential cyanobacterial health risks on a global scale, our study contributes to the assessment and management of one of the most pressing threats to both aquatic ecosystems and human health.
Our research introduces a novel and comprehensive approach to potential cyanobacterial health risk assessment, offering insights into risk from a toxicity perspective. The distinct geographical variations in cyanobacterial communities coupled with the intricate interplay of environmental factors underscore the complexity of managing cyanobacterial blooms at a global scale. Our systematic and targeted cyanobacterial surveillance enables a worldwide assessment of cyanobacteria-based potential health risks, providing an early warning system. |
doi_str_mv | 10.1128/aem.01936-24 |
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O emissions, and the human influence index. These findings underscore the influence of these variables on the proliferation of cyanobacterial blooms and associated risks. By introducing a novel quantitative method for monitoring potential cyanobacterial health risks on a global scale, our study contributes to the assessment and management of one of the most pressing threats to both aquatic ecosystems and human health.
Our research introduces a novel and comprehensive approach to potential cyanobacterial health risk assessment, offering insights into risk from a toxicity perspective. The distinct geographical variations in cyanobacterial communities coupled with the intricate interplay of environmental factors underscore the complexity of managing cyanobacterial blooms at a global scale. Our systematic and targeted cyanobacterial surveillance enables a worldwide assessment of cyanobacteria-based potential health risks, providing an early warning system.</description><identifier>ISSN: 0099-2240</identifier><identifier>ISSN: 1098-5336</identifier><identifier>EISSN: 1098-5336</identifier><identifier>DOI: 10.1128/aem.01936-24</identifier><identifier>PMID: 39494896</identifier><language>eng</language><publisher>United States: American Society for Microbiology</publisher><subject>Aquatic ecosystems ; Cyanobacteria ; Developing countries ; Ecosystem management ; Environmental Microbiology ; Health risk assessment ; Health risks ; Human influences ; Lakes ; LDCs ; Machine learning ; Metabolites ; Metagenomics ; Monitoring methods ; Nitrous oxide ; Risk assessment ; Secondary metabolites ; Threat evaluation ; Toxins ; Urbanization</subject><ispartof>Applied and environmental microbiology, 2024-11, Vol.90 (11), p.e0193624</ispartof><rights>Copyright © 2024 American Society for Microbiology.</rights><rights>Copyright American Society for Microbiology Nov 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a240t-eb48c5322949e137f3bbbf8fddca707393dc0ded44660283c6102bfc448d36f63</cites><orcidid>0009-0002-4090-7224 ; 0000-0003-0807-9991</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.asm.org/doi/pdf/10.1128/aem.01936-24$$EPDF$$P50$$Gasm2$$H</linktopdf><linktohtml>$$Uhttps://journals.asm.org/doi/full/10.1128/aem.01936-24$$EHTML$$P50$$Gasm2$$H</linktohtml><link.rule.ids>314,780,784,3187,27923,27924,52750,52751,52752</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39494896$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Spear, John R.</contributor><creatorcontrib>Hu, Hang</creatorcontrib><creatorcontrib>Zhang, Zhenyan</creatorcontrib><creatorcontrib>Chen, Bingfeng</creatorcontrib><creatorcontrib>Zhang, Qi</creatorcontrib><creatorcontrib>Xu, Nuohan</creatorcontrib><creatorcontrib>Paerl, Hans W</creatorcontrib><creatorcontrib>Wang, Tingzhang</creatorcontrib><creatorcontrib>Hong, Wenjie</creatorcontrib><creatorcontrib>Penuelas, Josep</creatorcontrib><creatorcontrib>Qian, Haifeng</creatorcontrib><title>Potential health risk assessment of cyanobacteria across global lakes</title><title>Applied and environmental microbiology</title><addtitle>Appl Environ Microbiol</addtitle><addtitle>Appl Environ Microbiol</addtitle><description>Cyanobacterial blooms pose environmental and health risks due to their production of toxic secondary metabolites. While current methods for assessing these risks have focused primarily on bloom frequency and intensity, the lack of comprehensive and comparable data on cyanotoxins makes it challenging to rigorously evaluate these health risks. In this study, we examined 750 metagenomic data sets collected from 103 lakes worldwide. Our analysis unveiled the diverse distributions of cyanobacterial communities and the genes responsible for cyanotoxin production across the globe. Our approach involved the integration of cyanobacterial biomass, the biosynthetic potential of cyanotoxin, and the potential effects of these toxins to establish potential cyanobacterial health risks. Our findings revealed that nearly half of the lakes assessed posed medium to high health risks associated with cyanobacteria. The regions of greatest concern were East Asia and South Asia, particularly in developing countries experiencing rapid industrialization and urbanization. Using machine learning techniques, we mapped potential cyanobacterial health risks in lakes worldwide. The model results revealed a positive correlation between potential cyanobacterial health risks and factors such as temperature, N
O emissions, and the human influence index. These findings underscore the influence of these variables on the proliferation of cyanobacterial blooms and associated risks. By introducing a novel quantitative method for monitoring potential cyanobacterial health risks on a global scale, our study contributes to the assessment and management of one of the most pressing threats to both aquatic ecosystems and human health.
Our research introduces a novel and comprehensive approach to potential cyanobacterial health risk assessment, offering insights into risk from a toxicity perspective. The distinct geographical variations in cyanobacterial communities coupled with the intricate interplay of environmental factors underscore the complexity of managing cyanobacterial blooms at a global scale. Our systematic and targeted cyanobacterial surveillance enables a worldwide assessment of cyanobacteria-based potential health risks, providing an early warning system.</description><subject>Aquatic ecosystems</subject><subject>Cyanobacteria</subject><subject>Developing countries</subject><subject>Ecosystem management</subject><subject>Environmental Microbiology</subject><subject>Health risk assessment</subject><subject>Health risks</subject><subject>Human influences</subject><subject>Lakes</subject><subject>LDCs</subject><subject>Machine learning</subject><subject>Metabolites</subject><subject>Metagenomics</subject><subject>Monitoring methods</subject><subject>Nitrous oxide</subject><subject>Risk assessment</subject><subject>Secondary metabolites</subject><subject>Threat evaluation</subject><subject>Toxins</subject><subject>Urbanization</subject><issn>0099-2240</issn><issn>1098-5336</issn><issn>1098-5336</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kM1LwzAYh4Mobk5vniXgRcHONx9Lk6OM-QEDPeg5pGnquqXtbNrD_nvjNhUET4E3D7_39z4InRMYE0LlrXHVGIhiIqH8AA0JKJlMGBOHaAigVEIphwE6CWEJAByEPEYDprjiUokhmr00nau70ni8cMZ3C9yWYYVNCC6EKv7gpsB2Y-omM7ZzbWmwsW0TAn73ceSxNysXTtFRYXxwZ_t3hN7uZ6_Tx2T-_PA0vZsnJpboEpdxaSeM0rjeEZYWLMuyQhZ5bk0KKVMst5C7nHMhgEpmBQGaFZZzmTNRCDZCV7vcddt89C50uiqDdd6b2jV90IxQJkEokUb08g-6bPq2ju0ixRUVksMkUjc7antT6wq9bsvKtBtNQH_p1VGv3urVlEf8eoebUNHfwH_Yi32BPqtc_hP87Z59AkUfgfg</recordid><startdate>20241120</startdate><enddate>20241120</enddate><creator>Hu, Hang</creator><creator>Zhang, Zhenyan</creator><creator>Chen, Bingfeng</creator><creator>Zhang, Qi</creator><creator>Xu, Nuohan</creator><creator>Paerl, Hans W</creator><creator>Wang, Tingzhang</creator><creator>Hong, Wenjie</creator><creator>Penuelas, Josep</creator><creator>Qian, Haifeng</creator><general>American Society for Microbiology</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QO</scope><scope>7SN</scope><scope>7SS</scope><scope>7ST</scope><scope>7T7</scope><scope>7TM</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>SOI</scope><scope>7X8</scope><orcidid>https://orcid.org/0009-0002-4090-7224</orcidid><orcidid>https://orcid.org/0000-0003-0807-9991</orcidid></search><sort><creationdate>20241120</creationdate><title>Potential health risk assessment of cyanobacteria across global lakes</title><author>Hu, Hang ; Zhang, Zhenyan ; Chen, Bingfeng ; Zhang, Qi ; Xu, Nuohan ; Paerl, Hans W ; Wang, Tingzhang ; Hong, Wenjie ; Penuelas, Josep ; Qian, Haifeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a240t-eb48c5322949e137f3bbbf8fddca707393dc0ded44660283c6102bfc448d36f63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aquatic ecosystems</topic><topic>Cyanobacteria</topic><topic>Developing countries</topic><topic>Ecosystem management</topic><topic>Environmental Microbiology</topic><topic>Health risk assessment</topic><topic>Health risks</topic><topic>Human influences</topic><topic>Lakes</topic><topic>LDCs</topic><topic>Machine learning</topic><topic>Metabolites</topic><topic>Metagenomics</topic><topic>Monitoring methods</topic><topic>Nitrous oxide</topic><topic>Risk assessment</topic><topic>Secondary metabolites</topic><topic>Threat evaluation</topic><topic>Toxins</topic><topic>Urbanization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Hang</creatorcontrib><creatorcontrib>Zhang, Zhenyan</creatorcontrib><creatorcontrib>Chen, Bingfeng</creatorcontrib><creatorcontrib>Zhang, Qi</creatorcontrib><creatorcontrib>Xu, Nuohan</creatorcontrib><creatorcontrib>Paerl, Hans W</creatorcontrib><creatorcontrib>Wang, Tingzhang</creatorcontrib><creatorcontrib>Hong, Wenjie</creatorcontrib><creatorcontrib>Penuelas, Josep</creatorcontrib><creatorcontrib>Qian, Haifeng</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Applied and environmental microbiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Hang</au><au>Zhang, Zhenyan</au><au>Chen, Bingfeng</au><au>Zhang, Qi</au><au>Xu, Nuohan</au><au>Paerl, Hans W</au><au>Wang, Tingzhang</au><au>Hong, Wenjie</au><au>Penuelas, Josep</au><au>Qian, Haifeng</au><au>Spear, John R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Potential health risk assessment of cyanobacteria across global lakes</atitle><jtitle>Applied and environmental microbiology</jtitle><stitle>Appl Environ Microbiol</stitle><addtitle>Appl Environ Microbiol</addtitle><date>2024-11-20</date><risdate>2024</risdate><volume>90</volume><issue>11</issue><spage>e0193624</spage><pages>e0193624-</pages><issn>0099-2240</issn><issn>1098-5336</issn><eissn>1098-5336</eissn><abstract>Cyanobacterial blooms pose environmental and health risks due to their production of toxic secondary metabolites. While current methods for assessing these risks have focused primarily on bloom frequency and intensity, the lack of comprehensive and comparable data on cyanotoxins makes it challenging to rigorously evaluate these health risks. In this study, we examined 750 metagenomic data sets collected from 103 lakes worldwide. Our analysis unveiled the diverse distributions of cyanobacterial communities and the genes responsible for cyanotoxin production across the globe. Our approach involved the integration of cyanobacterial biomass, the biosynthetic potential of cyanotoxin, and the potential effects of these toxins to establish potential cyanobacterial health risks. Our findings revealed that nearly half of the lakes assessed posed medium to high health risks associated with cyanobacteria. The regions of greatest concern were East Asia and South Asia, particularly in developing countries experiencing rapid industrialization and urbanization. Using machine learning techniques, we mapped potential cyanobacterial health risks in lakes worldwide. The model results revealed a positive correlation between potential cyanobacterial health risks and factors such as temperature, N
O emissions, and the human influence index. These findings underscore the influence of these variables on the proliferation of cyanobacterial blooms and associated risks. By introducing a novel quantitative method for monitoring potential cyanobacterial health risks on a global scale, our study contributes to the assessment and management of one of the most pressing threats to both aquatic ecosystems and human health.
Our research introduces a novel and comprehensive approach to potential cyanobacterial health risk assessment, offering insights into risk from a toxicity perspective. The distinct geographical variations in cyanobacterial communities coupled with the intricate interplay of environmental factors underscore the complexity of managing cyanobacterial blooms at a global scale. Our systematic and targeted cyanobacterial surveillance enables a worldwide assessment of cyanobacteria-based potential health risks, providing an early warning system.</abstract><cop>United States</cop><pub>American Society for Microbiology</pub><pmid>39494896</pmid><doi>10.1128/aem.01936-24</doi><tpages>17</tpages><orcidid>https://orcid.org/0009-0002-4090-7224</orcidid><orcidid>https://orcid.org/0000-0003-0807-9991</orcidid></addata></record> |
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subjects | Aquatic ecosystems Cyanobacteria Developing countries Ecosystem management Environmental Microbiology Health risk assessment Health risks Human influences Lakes LDCs Machine learning Metabolites Metagenomics Monitoring methods Nitrous oxide Risk assessment Secondary metabolites Threat evaluation Toxins Urbanization |
title | Potential health risk assessment of cyanobacteria across global lakes |
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