Crossing scales to predict and prevent bat virus zoonoses in a Madagascar ecosystem

跨尺度预测和预防马达加斯加生态系统中的蝙蝠病毒人畜共患病

• 批准号: 10509070
• 负责人: Cara Brook
• 金额: $ 46.06万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-05 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10509070
• 关键词: 2019-nCoV; Address; African; Animals; Anti-Inflammatory Agents; Biology; Blood Circulation; COVID-19 pandemic effects; Canis familiaris; Case Fatality Rates; Cell Line; Chicago; Chiroptera; Clinical; Collaborations; Communicable Diseases; Communities; Consumption; Coronavirus; Coupled; Data; Discipline; Disease; Doctor of Philosophy; Ebola; Ecology; Ecosystem; Evolution; Exhibits; Exposure to; Filovirus; Food; Fruit; Future; Goals; Hendra Virus; Henipavirus; Henipavirus Infections; Human; Immune; Immune system; Immunity; Immunologics; Infection; Infection Control; Innate Immune Response; Intervention; Island; Jamaican; Laboratories; Learning; Link; Literature; Madagascar; Mammals; Marburgvirus; Measles; Middle East Respiratory Syndrome; Middle East Respiratory Syndrome Coronavirus; Modeling; Molecular; Molecular Computations; Molecular Immunology; Monitor; Nature; Nutritional; Paramyxovirus; Pathology; Pattern; Periodicity; Physiologic pulse; Physiological; Physiology; Population; Population Sizes; Population Study; Postdoctoral Fellow; Prevention; Process; Public Health; Rabies virus; Recommendation; Recrudescences; Regimen; Research; Resources; SARS coronavirus; Sampling; Seasonal Variations; Series; Serology; Severe Acute Respiratory Syndrome; Shapes; Source; Stress; System; Techniques; Testing; Time; United States National Institutes of Health; Universities; Ursidae Family; Vaccinated; Vaccination; Vaccines; Viral; Viral Load result; Virulent; Virus; Virus Diseases; Virus Shedding; Work; Zoonoses; antiviral immunity; bat-borne; betacoronavirus; chronic infection; cost effective; cross-species transmission; design; experience; exposed human population; field study; health economics; immunopathology; infectious disease model; innovation; interest; mathematical model; molecular modeling; novel; pandemic preparedness; pathogen; post-doctoral training; prevent; professor; reproductive; spillover event; stressor; therapy design; tool; transmission process; vaccine distribution; viral transmission; willingness; zoonotic spillover

The wide-reaching impacts of the COVID-19 pandemic highlight the extreme threat posed by the cross-species emergence of zoonotic pathogens. Bats (order: Chiroptera) are the natural reservoir hosts for the majority of the world’s most virulent zoonotic viruses, including Hendra and Nipah henipaviruses, Ebola and Marburg filoviruses, and SARS, MERS, and now SARS-CoV-2 coronaviruses. Remarkably, bats exhibit little demonstrable disease upon infection with viruses that cause extreme pathology in other mammals, likely in part due to their unique anti-inflammatory molecular adaptations, which are thought to have evolved to mitigate the accumulation of physiological damage accrued during flight. Surprisingly, isolated island bat communities around the world support the endemic circulation of numerous viruses in populations below the critical community size required for persistence of related pathogens in other hosts. Since cross-species spillover of several bat-borne viruses bears a distinctive seasonal signature, coincident with the timing of reproductive and nutritional stress for the bat hosts in question, disentangling the mechanisms governing the transmission, circulation, and persistence of these viruses in wild bat populations is of critical public health interest. In part with the research initiatives proposed here, we will use molecular and serological tools to develop a longitudinal time series of immunological and infection data for henipaviruses and coronaviruses circulating in wild fruit bats in Madagascar, leveraging samples collected in our longterm wildlife surveillance effort. Bats are widely consumed as a source of human food in Madagascar, and preliminary data from our research group demonstrates serological signatures of prior human exposure to these zoonotic viruses across the island. We propose to fit disparate dynamical models to the resulting population-level data in order to distinguish mechanisms underpinning seasonal viral shedding pulses and concomitant transmission in these bat hosts. In addition to population-level studies, we will also construct within-host models of viral control in a single bat immune system, which we will fit to experimental infection data from Betacoronavirus-challenged bats in the laboratory, with the aim of deciphering the mechanisms which motivate viral shedding. Our project aims to simultaneously develop molecular tools of bat cell lines and viruses with which to support within-host studies in our own Madagascar system. Finally, we will build on population-level and within-host studies to model and implement a vaccine intervention designed to eradicate circulating henipavirus from a test-population of Madagascar fruit bats. Broadly, our project aims to use a uniquely integrative combination of field, molecular, and modeling tools to enable the prediction and prevention of bat virus spillover events before they occur.

COVID-19大流行的广泛影响凸显了跨物种的极端威胁 人畜共患病病原体的出现。蝙蝠（目的：翼手目）是大多数的天然水库主机 世界上最致命的人畜共患病毒，包括亨德拉和尼帕亨尼帕病毒、埃博拉和马尔堡病毒 丝状病毒，SARS，MERS，现在是SARS-CoV-2冠状病毒值得注意的是，蝙蝠很少表现出 感染病毒后可证实的疾病，在其他哺乳动物中引起极端病理，可能在 部分原因是它们独特的抗炎分子适应性，这被认为是为了减轻 飞行过程中生理损伤的累积。令人惊讶的是，孤立的岛屿蝙蝠群落 世界各地支持许多病毒在低于临界值的人群中流行 相关病原体在其他宿主中持续存在所需的群落规模。由于跨物种溢出， 几种蝙蝠传播的病毒具有独特的季节性特征，与繁殖时间一致， 研究蝙蝠宿主的营养压力，解开控制传播的机制， 这些病毒在野生蝙蝠种群中的传播和持续存在是至关重要的公共卫生利益。部分 随着这里提出的研究倡议，我们将使用分子和血清学工具来开发一个 流行的亨尼帕病毒和冠状病毒的免疫学和感染数据的纵向时间序列 马达加斯加的野生果蝠，利用我们长期野生动物监测工作中收集的样本。蝙蝠是 在马达加斯加作为人类食物的来源被广泛消费，我们研究小组的初步数据显示， 显示了全岛人类先前接触这些人畜共患病毒的血清学特征。我们 建议将不同的动态模型拟合到所产生的人口水平数据，以区分 这些蝙蝠宿主中的季节性病毒脱落脉冲和伴随的传播机制。在 除了群体水平的研究，我们还将在单个蝙蝠中构建病毒控制的宿主内模型 免疫系统，我们将适合实验感染数据从β冠状病毒挑战蝙蝠在 实验室，目的是破译机制，促使病毒脱落。我们的项目旨在 同时开发蝙蝠细胞系和病毒分子工具，以支持宿主内研究， 我们自己的马达加斯加系统最后，我们将在人群水平和宿主内研究的基础上建立模型， 实施疫苗干预，旨在根除试验人群中的循环亨尼帕病毒， 马达加斯加果蝠。从广义上讲，我们的项目旨在使用一个独特的领域，分子， 和建模工具，以便能够在蝙蝠病毒溢出事件发生之前预测和预防它们。