Evolution and Transmission of Influenza Virus in Natural Human Infection

季节性流感流行会导致显著的发病率和死亡率，而疫苗的有效性是 低得令人失望。流感病毒的快速进化是有效疫苗的主要障碍，如新的 具有不同抗原性的菌株在一个非常大的种群中不断产生 受感染的宿主。NIAID最近的流感战略计划和PA-18-859强调了这一问题， 突出了关于流感病毒在个体中的进化及其传播的关键知识差距 在他们之间。这项研究的长期目标是阐明进化和流行病学动态。 在自然感染的人类宿主中的流感病毒。这个项目的目标是使用最先进的 用分子方法定义流感宿主水平的进化并确定传染性和 变速箱。该项目将结合密集的病毒采样、匹配的血清和来自 自然感染的个人及其接触者，这将使对流感演变的有力分析成为可能， 传播，传播。已公布的初步数据支持了这种方法的可行性，这些数据表明 序列抽样可以用来刻画流感病毒在自然界中的进化动态 感染者；(2)下一代测序(NGS)可用于识别传播对和估计 在个人之间传播的独特病毒变异的数量；(Iii)关于病毒载量的时间数据和在- 宿主遗传多样性可以为传播的数学模型提供信息。流感演变的详细分析 而传输将通过三个目标来实现。(目标1)确定出现的抗原变异体 与宿主一起肯定地选择了。将使用连续采样的宿主内病毒种群的NGS来识别 宿主内正选择条件下的血凝素和神经氨酸酶变异及其与宿主的关系 免疫状态。这些突变对病毒抗原性的影响将使用登记的血清进行评估。 个人。(目标2)确定传播瓶颈和传播的遗传变异。NGS of 将使用来自索引病例和家庭接触者的连续样本来定义家庭传播链， 传输瓶颈的大小，以及在主机变体内传输的内容。(目标3)识别病毒和 与宿主易感性、传染性和传播性相关的宿主因素。一个特定品系的家庭 综合分子和流行病学数据的传播模型将被用于估计感染的危险 来自社区和每个受感染家庭的接触。这项工作具有创新性，因为它利用了 现有生产团队的专业知识，将最先进的病毒测序技术和 研究流感病毒在自然感染中的进化和传播的复杂建模方法。这个 拟议的研究意义重大，因为它将在一定程度上定义流感病毒的进化动力学。 社区环境中的单个主持人。

Seasonal influenza epidemics result in significant morbidity and mortality, and vaccine effectiveness is disappointingly low. The rapid evolution of influenza viruses is a major barrier to effective vaccines, as new strains with different antigenic properties are continuously generated within a remarkably large population of infected hosts. This problem was highlighted in the recent NIAID strategic plan for influenza and in PA-18-859, which highlight key knowledge gaps with respect to influenza virus evolution in individuals and its transmission between them. The long-term goal of this research is to elucidate the evolutionary and epidemiological dynamics of influenza viruses in naturally infected human hosts. The objectives of this project are to use state-of-the-art molecular approaches to define the host-level evolution of influenza and to identify correlates of infectivity and transmission. This project will combine intensive sampling of viruses, matched sera, and clinical data from naturally infected individuals and their contacts, which will allow for robust analyses of influenza evolution, transmission, and spread. The feasibility of this approach is supported by published preliminary data, which show that (i) serial sampling can be used to characterize the evolutionary dynamics of influenza viruses within naturally infected people; (ii) next generation sequencing (NGS) can be used to identify transmission pairs and to estimate the number of unique viral variants transmitted between individuals; (iii) temporal data on viral load and within- host genetic diversity can inform mathematical models of transmission. Detailed analyses of influenza evolution and transmission will be accomplished in three aims. (Aim 1) Identify the emergent antigenic variants that are positively selected with hosts. NGS of serially sampled within-host viral populations will be used to identify hemagglutinin and neuraminidase variants under positive selection within hosts and their relationship to host immune status. The impact of these mutations on viral antigenicity will be evaluated using sera from enrolled individuals. (Aim 2) Define the transmission bottleneck and the genetic variants that are transmitted. NGS of serial samples from index cases and household contacts will be used to define household transmission chains, the size of the transmission bottleneck, and which within host variants are transmitted. (Aim 3) Identify viral and host factors associated with host susceptibility, infectivity, and transmission. A strain-specific household transmission model, integrating molecular and epidemiologic data, will be used to estimate hazards of infection from the community and each infected household contact. This work is innovative, because it leverages the expertise of an existing productive team to combine state-of-the-art technologies for viral sequencing and sophisticated modeling approaches to study influenza virus evolution and transmission in natural infection. The proposed research is significant, because it will define the evolutionary dynamics of influenza viruses at the level of individual hosts in a community setting.