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(如弧菌)，但许多其他病原体，如原生贾第鞭毛虫，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知之甚少，更不用说流行和分布了。各种病原体的生存和持久性肯定会受到环境条件的影响，而淡水径流、污水和热污染对沿海和河口地区的污染可能会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，以便开始确定何时何地发生 潜在感染的风险最高，或者只是病原体的存在。我们的项目旨在利用分子方法学来确定人类病原体(包括贾第鞭毛虫、隐孢子虫、棘阿米巴、奈格勒虫、弧菌和军团Ila)的分布和丰度，确定自然存在的海洋阿米巴是否可以作为病原体的宿主，并在马萨诸塞州希望山湾受人类影响的河口环境中寻找这些联系自然存在的证据。数据将在空间和时间上相关的尺度(多个地点，多年)上收集。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.