Pegasus Technical Services, Inc., Cincinnati, OH 45219, USA.
Office of Research and Development, United States Environmental Protection Agency, Cincinnati, OH 45268, USA.
Sci Total Environ. 2022 Jul 15;830:154568. doi: 10.1016/j.scitotenv.2022.154568. Epub 2022 Mar 14.
Freshwater harmful cyanobacterial blooms (HCBs) potentially produce excessive cyanotoxins, mainly microcystins (MCs), significantly threatening aquatic ecosystems and public health. Accurately predicting HCBs is thus essential to developing effective HCB mitigation and prevention strategies. We previously developed a novel early-warning system that uses cyanotoxin-encoding genes to predict cyanotoxin production in Harsha Lake, Ohio, USA, in 2015. In this study, we evaluated the efficacy of the early-warning system in forecasting the 2016 HCB in the same lake. We also examined potential HCB drivers and cyanobacterial community composition. Our results revealed that the cyanobacterial community was stable at the phylum level but changed dynamically at the genus level over time. Microcystis and Planktothrix were the major MC-producing genera that thrived in June and July and produced high concentrations of MCs (peak level 10.22 μg·L). The abundances of the MC-encoding gene cluster mcy and its transcript levels significantly correlated with total MC concentrations (before the MC concentrations peaked) and accurately predicted MC production as revealed by logistic equations. When the Microcystis-specific gene mcyG reached approximately 1.5 × 10 copies·mL or when its transcript level reached approximately 2.4 copies·mL, total MC level exceeded 0.3 μg L (a health advisory limit) approximately one week later (weekly sampling scheme). This study suggested that cyanotoxin-encoding genes are promising predictors of MC production in inland freshwater lakes, such as Harsha Lake. The evaluated early-warning system can be a useful tool to assist lake managers in predicting, mitigating, and/or preventing HCBs.
淡水有害蓝藻水华(HCB)可能会产生过量的蓝藻毒素,主要是微囊藻毒素(MCs),这对水生生态系统和公共健康构成了重大威胁。因此,准确预测 HCB 对于制定有效的 HCB 缓解和预防策略至关重要。我们之前开发了一种新的预警系统,该系统使用编码蓝藻毒素的基因来预测 2015 年美国俄亥俄州哈沙湖的蓝藻毒素产生情况。在本研究中,我们评估了该预警系统预测同一湖泊 2016 年 HCB 的效果。我们还研究了潜在的 HCB 驱动因素和蓝藻群落组成。研究结果表明,蓝藻群落在门水平上是稳定的,但随着时间的推移在属水平上发生了动态变化。微囊藻和束丝藻是主要的产 MC 属,在 6 月和 7 月大量繁殖,产生高浓度的 MC(峰值水平为 10.22μg·L)。MC 编码基因簇 mcy 的丰度及其转录水平与总 MC 浓度(在 MC 浓度达到峰值之前)显著相关,并且通过逻辑方程准确预测了 MC 的产生。当微囊藻特异性基因 mcyG 达到约 1.5×10 拷贝·mL-1 或其转录水平达到约 2.4 拷贝·mL-1 时,总 MC 水平约一周后(每周采样方案)超过 0.3μg·L(健康咨询限制)。本研究表明,编码蓝藻毒素的基因是内陆淡水湖泊中 MC 产生的有前途的预测因子,如哈沙湖。评估的预警系统可以成为帮助湖泊管理者预测、减轻和/或预防 HCB 的有用工具。