文献类型：期刊文献

英文题名：Potential health risk assessment of cyanobacteria across global lakes

作者：Hu, Hang[1];Zhang, Zhenyan[1];Chen, Bingfeng[1];Zhang, Qi[2,3];Xu, Nuohan[2,3];Paerl, Hans W.[4];Wang, Tingzhang[5];Hong, Wenjie[5];Penuelas, Josep[6,7];Qian, Haifeng[1]

机构：[1]Zhejiang Univ Technol, Coll Environm, Hangzhou, Zhejiang, Peoples R China;[2]Shaoxing Univ, Inst Adv Studies, Shaoxing, Peoples R China;[3]Shaoxing Univ, Coll Chem & Chem Engn, Shaoxing, Peoples R China;[4]Univ North Carolina Chapel Hill, Inst Marine Sci, Morehead City, NC USA;[5]Key Lab Microbial Technol & Bioinformat Zhejiang P, Hangzhou, Peoples R China;[6]UAB, CSIC, CREAF, Global Ecol Unit, Barcelona, Catalonia, Spain;[7]Campus Univ Autonoma Barcelona, CREAF, Barcelona, Catalonia, Spain

年份：2024

卷号：90

期号：11

外文期刊名：APPLIED AND ENVIRONMENTAL MICROBIOLOGY

收录：SCI-EXPANDED(收录号：WOS:001349446000003)、、EI(收录号：20244817419135)、Scopus(收录号：2-s2.0-85209741526)、WOS

基金：H.F.Q., Q.Z., H.W.P., and J.P. acquired funding for this project. This work was financially supported by the National Natural Science Foundation of China (21976161, 21777144, 42307158, and 22376187), the Zhejiang Provincial Natural Science Foundation of China (Grant No. LZ23B070001), the China Postdoctoral Science Foundation (2023M743100), the Zhejiang Provincial Postdoctoral Science Foundation (ZJ2023058), and the Key Scientific and Technological Program of Hangzhou (2023SZD0058). H.P. was supported by the US National Science Foundation (1831096, 1803697, 2108917) and the National Institutes of Health (1P01ES028939-01). J.P.'s research was supported by the Spanish Government grant TED2021-132627B-I00 funded by MCIN, AEI/10.13039/501100011033, and the European Union NextGenerationEU/PRTr; the Fundacion Ramon Areces grant CIVP20A6621; and the Catalan Government grant SGR2021-1333.

语种：英文

外文关键词：lake; metagenome; cyanobacterial bloom; cyanotoxins; risk assessment; machine learning

外文摘要：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, N2O 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.