Linking Limnology to Cyanotoxins in Drinking Water Using Buoy Sensors and Auto-Sa

描述（由申请人提供） 由于土地利用和气候的变化，美国支持有毒蓝藻积累的湖泊数量正在增加。因此，与湖泊娱乐活动（如游泳、划船）和鱼类消费有关的风险越来越大。导致蓝藻毒素生产的物理化学因素在与蓝藻生态相关的时间尺度（即分钟至小时）上定义不清。 急性中毒是有据可查的，但长期接触饮用水中低水平的蓝藻毒素则没有。美国的湖泊为饮用水处理厂（DWTP）提供水源，为数亿人提供服务。 湖泊条件，或免疫学变量，支持蓝藻毒素生产的发生在饮用水中的蓝藻毒素有着内在的联系，因为这些变量也影响蓝藻毒素去除效率的DWTP过程。 研究人员建议使用浮标上的高分辨率传感器和一种新的自动采样装置来调查免疫学变量与湖泊和饮用水中蓝藻毒素存在之间的关系。在这项工作中，密歇根湖流域的温尼贝戈湖和从该湖取水的DWTP将作为模型系统。 在目标1中，调查人员将在DWTP进水口附近部署一个仪表浮标和自动采样装置。浮标传感器将测量物理变量和藻类色素，而营养物质，群落组成和蓝藻毒素将在保存的水样自动采样器收集测量。氰毒素将通过液相色谱串联质谱法进行测量，包括肝毒素（微囊藻毒素和柱精子蛋白）和神经毒素（类毒素、蛤蚌毒素和β-N-甲基氨基-L-丙氨酸）。 此外，斑马鱼试验将用于检测未知毒素和总体水毒性。 因此，蓝藻毒素和其他湖沼变量将在高分辨率（分钟至小时）的蓝藻生长季节（6月至10月）的持续时间进行测量。这些数据将被用来测试的生理生态的蓝藻毒素生产在湖泊中的基本假设。 在目标2中，调查人员将在DWTP部署自动采样器，每天采集两次样本。 他们将探讨这些样品中出现的蓝藻毒素的时间动态以及DWTP过程的去除效率。 在目标3中，研究者将建立蓝藻毒素在湖泊和饮用水中出现的模型。 最终目标的总体目标是产生可供湖泊管理者和DWTP运营商使用的蓝藻毒素水平预测模型，以防止人类暴露于蓝藻毒素。该提案利用了其他正在进行的项目的支持，包括威斯康星州，密尔沃基（UWM）的大学生物学和数学（UBM）计划的NSF本科研究，以及全球湖泊生态观测网络和UWM儿童环境健康科学核心中心提供的资源，设施和服务。

DESCRIPTION (provided by applicant) The number of lakes supporting accumulations of toxic cyanobacteria in the United States is rising due to changes in land use and climate. As a result there is increasing risk associated with lake recreational activities (e.g. swimming, boating), and consumption of fish. Physicochemical factors leading to cyanotoxin production are ill-defined at time-scales relevant to cyanobacterial ecology (i.e. minutes to hours). Acute poisonings are well-documented, but chronic exposure to low levels of cyanotoxins in drinking water is not. Lakes in the U.S. provide source water for drinking water treatment plants (DWTP) serving hundreds of millions of people. Lake conditions, or immunological variables, that support cyanotoxin production are intrinsically linked to the occurrence of cyanotoxins in drinking water because these variables also influence cyanotoxin removal efficiency by DWTP processes. The investigators propose to use high-resolution sensors on buoys and a new automated sampling device to investigate relationships between immunological variables and the presence of cyanotoxins in lakes and drinking water. For this work, Lake Winnebago in the Lake Michigan watershed and a DWTP drawing water from the lake will serve as a model system. In aim 1 the investigators will deploy an instrumented buoy and automated sampling device near the DWTP intake. Buoy sensors will measure physical variables and algal pigments while nutrients, community composition, and cyanotoxins will be measured in preserved water samples collected by the automated sampler. Cyanotoxins will be measured by liquid chromatography tandem mass spectrometry and include hepatotoxins (microcystins and cylindrospermopsin) and neurotoxins (anatoxins, saxitoxin, and beta-N-methylamino-L-alanine). In addition, a zebrafish assay will be used to detect unknown toxins and overall water toxicity. Thus, cyanotoxins and other limnological variables will be measured at high resolution (minutes to hours) for the duration of the cyanobacterial growth season (June-October). This data will be used to test fundamental hypotheses about the physiological ecology of cyanotoxin production in lakes. In aim 2, the investigators will deploy automated samplers at a DWTP, collecting samples twice daily. They will explore temporal dynamics of cyanotoxin occurrence in these samples as well as removal efficiency by DWTP processes. In aim 3 the investigators will construct models of cyanotoxin occurrence in lakes and drinking water. The overall goal of this final aim is to produce predictive models of cyanotoxin levels that can be used by lake managers and DWTP operators to prevent human exposure to cyanotoxins. This proposal leverages the support of other ongoing projects including the NSF Undergraduate Research in Biology and Mathematics (UBM) program at the University of Wisconsin, Milwaukee (UWM), and resources, facilities, and services provided by the Global Lake Ecological Observatory Network and the Children's Environmental Health Sciences Core Center at UWM.