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)和鱼类消费相关的风险增加。导致蓝藻毒素产生的物理化学因素在与蓝藻生态有关的时间尺度(即几分钟到几小时)上定义不清。急性中毒有很好的记录，但长期接触饮用水中低水平的氰化物毒素却没有。美国的湖泊为服务于数亿人的饮用水处理厂(DWTP)提供水源。支持氰化毒素产生的湖况或免疫学变量与饮用水中氰化毒素的发生有内在联系，因为这些变量也影响DWTP工艺去除氰化毒素的效率。研究人员建议在浮标上使用高分辨率传感器和一种新的自动采样设备，以调查免疫变量与湖泊和饮用水中氰化物存在之间的关系。在这项工作中，密歇根湖分水岭的温尼贝戈湖和一个从湖里取水的污水处理厂将作为模型系统。在目标1中，调查人员将在污水处理厂进水口附近部署一个仪表式浮标和自动取样装置。浮标传感器将测量物理变量和藻类色素，而营养素、群落组成和氰化毒素将在自动采样器收集的保存水样本中进行测量。氰基毒素将用液相色谱-串联质谱仪进行检测，包括肝毒素(微囊藻毒素和柱状精浆)和神经毒素(Anatoxins、SAXITOX和β-N-甲氨基-L-丙氨酸)。此外，斑马鱼化验将用于检测未知毒素和整体水毒性。因此，在蓝藻生长季节(6-10月)期间，将以高分辨率(几分钟到几小时)测量氰化毒素和其他湖沼学变量。这些数据将被用来检验有关湖泊中氰化毒素生产的生理生态的基本假设。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。他们将探索氰化毒素在这些样品中出现的时间动态以及DWTP工艺的去除效率。在目标3中，研究人员将构建湖泊和饮用水中氰化毒素发生的模型。这一最终目标的总体目标是产生氰化毒素水平的预测模型，可供湖泊管理人员和DWTP操作员使用，以防止人类接触氰化毒素。该提案利用了其他正在进行的项目的支持，包括威斯康星大学密尔沃基分校(UWM)的NSF生物学和数学本科研究(UBM)项目，以及由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.