Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, P.O. Box 94240, 1090 GE, Amsterdam, The Netherlands; Waardenburg Ecology, Varkensmarkt 9, 4101 CK, Culemborg, The Netherlands.
Department of Freshwater and Marine Ecology, Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, P.O. Box 94240, 1090 GE, Amsterdam, The Netherlands.
Harmful Algae. 2024 Sep;138:102683. doi: 10.1016/j.hal.2024.102683. Epub 2024 Jun 22.
Toxic cyanobacterial blooms impose a health risk to recreational users, and monitoring of cyanobacteria and associated toxins is required to assess this risk. Traditionally, monitoring for risk assessment is based on cyanobacterial biomass, which assumes that all cyanobacteria potentially produce toxins. While these methods may be cost effective, relatively fast, and more widely accessible, they often lead to an overestimation of the health risk induced by cyanotoxins. Monitoring methods that more directly target toxins, or toxin producing genes, may provide a better risk assessment, yet these methods may be more costly, usually take longer, or are not widely accessible. In this study, we compared six monitoring methods (fluorometry, microscopy, qPCR of 16S and mcyE, ELISA assays, and LC-MS/MS), of which the last three focussed on the most abundant cyanotoxin microcystins, across 11 lakes in the Netherlands during the bathing water season (May-October) of 2019. Results of all monitoring methods significantly correlated with LC-MS/MS obtained microcystin levels (the assumed 'golden standard'), with stronger correlations for methods targeting microcystins (ELISA) and microcystin genes (mcyE). The estimated risk levels differed substantially between methods, with 78 % and 56 % of alert level exceedances in the total number of collected samples for fluorometry and microscopy-based methods, respectively, while this was only 16 % and 6 % when the risk assessment was based on ELISA and LC-MS/MS obtained toxin concentrations, respectively. Integrating our results with earlier findings confirmed a strong association between microcystin concentration and the biovolume of potential microcystin-producing genera. Moreover, using an extended database consisting of 4265 observations from 461 locations across the Netherlands in the bathing water seasons of 2015 - 2019, we showed a strong association between fluorescence and the biovolume of potentially toxin-producing genera. Our results indicate that a two-tiered approach may be an effective risk assessment strategy, with first a biomass-based method (fluorometry, biovolume) until the first alert level is exceeded, after which the risk level can be confirmed or adjusted based on follow-up toxin or toxin gene analyses.
有毒蓝藻水华会对娱乐用水者的健康构成威胁，因此需要监测蓝藻并评估相关毒素，以评估这种风险。传统上，风险评估监测基于蓝藻生物量，这意味着假设所有蓝藻都可能产生毒素。虽然这些方法可能具有成本效益、相对快速且更广泛适用，但它们往往会高估蓝藻毒素引起的健康风险。更直接针对毒素或产毒基因的监测方法可能提供更好的风险评估，但这些方法可能成本更高、耗时更长或不广泛适用。在这项研究中，我们比较了六种监测方法（荧光法、显微镜法、16S 和 mcyE 的 qPCR、ELISA 测定和 LC-MS/MS），其中后三种方法主要针对最丰富的蓝藻毒素微囊藻毒素，在 2019 年 5 月至 10 月的游泳水季节期间，在荷兰的 11 个湖泊中进行了研究。所有监测方法的结果与通过 LC-MS/MS 获得的微囊藻毒素水平（假设的“金标准”）显著相关，与针对微囊藻毒素的方法（ELISA）和微囊藻毒素基因（mcyE）的相关性更强。不同方法的估计风险水平差异很大，荧光法和显微镜法基础方法采集的样本总数中，分别有 78%和 56%超过警戒水平，而基于 ELISA 和 LC-MS/MS 获得的毒素浓度进行风险评估时，这一比例分别为 16%和 6%。将我们的结果与早期研究结果相结合，证实了微囊藻毒素浓度与潜在产微囊藻毒素属的生物量之间存在很强的关联。此外，我们使用了一个扩展的数据库，该数据库由 2015 年至 2019 年游泳水季节在荷兰 461 个地点采集的 4265 个观测结果组成，结果表明荧光与潜在产毒属的生物量之间存在很强的关联。我们的研究结果表明，两级方法可能是一种有效的风险评估策略，首先采用基于生物量的方法（荧光法、生物量），直到超过第一个警戒水平，然后根据后续的毒素或毒素基因分析确认或调整风险水平。
