Effects of climate change on prevalence and environmental niches of clinically important vibrios in the Chesapeake Bay

极端天气事件的频率、强度和持续时间的变化可能会影响切萨皮克湾（Chesapeake Bay）的致病性弧菌生态。切萨皮克湾是美国最大的河口，目前海平面上升速度是全球平均速度的两倍。与弧菌相关的人类健康风险主要与食用受污染的海产品或在水上娱乐活动中接触病原体有关。由于弧菌无法从切萨皮克湾根除，基于有利于其在海洋环境中生存的条件开发预测模型将为决策者提供信息，以制定保护公众健康的政策。通过完成这个项目，研究小组将对极端事件对切萨皮克湾相关水域、浮游生物和牡蛎中病原体流行的影响进行全面评估，考虑到调节这些关系的环境和地球物理过程。这项研究的结果通过各种渠道（网站、新闻媒体和卫生保健机构）传播，将有助于关键决策，以尽量减少切萨皮克湾地区与弧菌相互作用的公共卫生风险。该结果可能对美国和其他国家的其他地区有用，以帮助预防疾病的爆发，因为已知弧菌在水生环境中自然发生。该项目由美国国家科学基金会和国家环境健康科学研究所（NIEHS）联合支持。以往的研究清楚地表明，弧菌的出现频率受环境因素的影响，在一定的条件下，这些细菌会进入一种可存活但不可培养（VBNC）的状态。检测致病性弧菌（包括VBNC细胞）的存在是至关重要的，因为丧失培养能力并不保证丧失毒力。本研究将通过对该地区（水中、浮游生物和牡蛎）病原体（霍乱弧菌、创伤弧菌和副溶血性弧菌）的生态理论（可培养和VBNC）结合卫星遥感启发的模拟和预测风险模型，通过彻底取样，提高对该海湾临床重要弧菌的发生率和丰度的了解。该研究的三个目标是：(i)利用最近开发的检测方法表征这些可培养弧菌和VBNC弧菌在切萨皮克湾水域、浮游生物和牡蛎中的流行程度；（ii）调查极端高温事件、极端降水事件和其他关键环境和地球物理因素（如浮游生物大量繁殖、海面高度、盐度）对切萨皮克湾致病性弧菌流行率的影响，并进一步调查这种关联在可培养状态和VBNC状态之间的差异；（iii）为切萨皮克湾地区弧菌爆发开发基于卫星的预测风险模型，为公共卫生准备提供信息。观测数据分析和建模的结合将用于实现目标，检验假设，并探索替代机制。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Changes in the frequency, intensity, and duration of extreme weather events is likely to affect the ecology of pathogenic Vibrio bacteria in the Chesapeake Bay, the largest estuary in the U.S., which is already experiencing twice the global average rate of sea-level rise. Human health risks associated with vibrios are primarily related to the consumption of contaminated seafood or exposure to pathogens during water-based recreational activities. Since vibrios cannot be eradicated from the Chesapeake Bay, the development of predictive models based on conditions favoring their survival in the marine environment will inform decision makers to devise policies to protect public health. Through the completion of this project the research team will produce a comprehensive assessment of the impact of extreme events on the prevalence of pathogens in the Chesapeake Bay associated water, plankton, and oysters, considering the environmental and geophysical processes that modulate these relations. The outcomes of this research, disseminated through various channels (websites, news media and healthcare agencies), will assist in critical decision making to minimize public health risk of interaction with vibrios in the Chesapeake Bay area. The results may be useful to other locations in the United States and other countries to help prevent an outbreak of disease as the vibrios are known to occur naturally in the aquatic environment. The project is jointly supported by NSF and by the National Institute for Environmental Health Sciences (NIEHS).Prior studies clearly indicate that the frequency of Vibrio spp. occurrences are influenced by environmental factors, and under certain conditions, these bacteria enter into a viable but nonculturable (VBNC) state. Detecting the presence of pathogenic vibrios, including VBNC cells, is critical because loss of culturability does not guarantee loss of virulence. This research will enhance knowledge on understanding of occurrence and abundance of clinically important vibrios in the Bay using a fundamentally transformational approach - a satellite remote sensing inspired simulation and prediction risk model integrating ecological theory (culturable and VBNC) of pathogens (V. cholerae, V. vulnificus and V. parahaemolyticus) through exhaustive sampling (in water, plankton and oysters) in the region. Three objectives of the study are to (i) characterize the prevalence of these culturable and VBNC vibrios using recently developed detection method in the Chesapeake Bay water, plankton and oysters; (ii) Investigate the impact of extreme heat events, extreme precipitation events and other key environmental and geophysical factors (e.g. plankton blooms, sea surface height, salinity) on the prevalence of pathogenic Vibrio spp.in Chesapeake Bay and further investigate how this association differs between culturable versus VBNC states and (iii) develop satellite- based predictive risk models for vibriosis outbreaks in the Chesapeake Bay area to inform public health preparedness. A combination of observational data analysis and modeling will be used to accomplish the goals, test hypotheses, and explore alternate mechanisms.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.