Human Pathogens and Coastal Ocean Processes

一些人类病原体是海洋微生物群落的天然成员（例如弧菌属），但许多其他病原体，例如原生生物贾第虫，可能通过污水输入和陆地径流进入海水。尽管它们可能对人类健康产生影响，但人们对传统上非海洋人类病原体的发生情况知之甚少，更不用说其流行和分布情况了。各种病原体的生存和持久性肯定受到环境条件的影响，淡水径流、污水和热污染对沿海和河口地区的污染有可能改变当地的环境条件。检查病原体存在和持久性的研究需要与预测模型相结合，以便开始确定病原体在何处和何时传播。 潜在感染的风险，或者仅仅是病原体的存在，是最高的。我们的项目目标是利用分子方法来确定人类病原体（包括贾第鞭毛虫、隐孢子虫、棘阿米巴原虫、耐格里原虫、弧菌和军团菌）的分布和丰度，确定天然存在的海洋阿米巴是否可以作为病原菌的储存库，并在马萨诸塞州霍普山湾受人类活动影响的河口环境中寻找这些关联自然发生的证据。将在空间和时间相关尺度（多个研究中心，多年）收集数据。有关物理化学特征的信息将与生物分布和持久性信息相关联，用于评估海湾的水质/富营养化模型，该模型可用于预测何时何地可以发现病原体。

Some human pathogens are natural members of the marine microbial community (e.g Vibrio species), but many others, such as the protist Giardia, are potentially introduced into seawater from sewage input and terrestrial runoff. Despite the potential for their impact on human health, relatively little is known about the occurrence, much less the prevalence and distribution, of traditionally non-marine human pathogens. The survival and persistence of various pathogens is most certainly influenced by environmental conditions, and the contamination of coastal and estuarine areas through freshwater runoff, sewage and thermal pollution have the potential to alter local environmental conditions. Studies that examine pathogen presence and persistence need to be coupled with predictive models in order to begin to determine where and when the risks of potential infection, or simply the presence of pathogens, are highest. Our project aims are to use molecular methodology to determine the distribution and abundances of the human pathogens (including Giardia, Cryptosporidium, Acanthamoeba, Naegleria, Vibrio and LegioneIla), determine whether naturally occurring marine amoebae can serve as reservoirs for pathogenic bacteria, and look for evidence of natural occurrence of these associations in the anthropogenically impacted estuarine environment of Mount Hope Bay, MA. Data will be collected over spatially and temporally relevant scales (multiple sites, multiple years). Information on the physico-chemical characteristics will be correlated with biological distribution and persistence information for use in evaluating a water quality/eutrophication model for the bay that could be used to predict where and when pathogens could be found.