Signatures of Immunity on the Antigenic Diversity of Pathogens

描述(申请人提供)：许多人类病原体表现出广泛的抗原性多样性。对感染一种抗原变体的免疫力通常部分地防止感染另一种抗原变体，导致抗原性相似的菌株之间对敏感宿主的竞争。了解这种竞争背后的免疫学机制是预测菌株动态的重要一步，包括新的抗原变异体是否会导致居民灭绝，以及针对一些菌株的疫苗接种将如何影响非靶标的竞争菌株。品系竞争的经典模型预测，由持久的品系特异性免疫驱动的负频率相关选择。虽然这些简单的模型有时是一个有用的近似值，但它们并没有解释其他已知的免疫机制如何解释相关病原体抗原多样性模式的细微差异。这个项目的目标是检验不同种类的免疫在病原体多样性中塑造种群水平模式的一般假设。第一个目的是评估先天免疫和基于抗体的免疫在两种常见细菌病原体-肺炎链球菌(肺炎球菌)和脑膜炎奈瑟菌(脑膜炎球菌)-产生抗原多样性模式中的作用。通过将观察到的主要抗原类型的流行情况与基于个体的模型的结果进行比较，评估每种免疫的各自贡献，在该模型中，异种免疫的强度、广度和持续时间根据每种免疫类型的不同而不同。第二个目的是使用同样的三个因素来推断先天免疫、细胞免疫和体液免疫对流感和副流感这两种病毒动态的影响。这三个因素将通过将常微分方程模型与每个主要抗原型(副流感血清型1-3和A型(H3N2型)、A型(H1N1)和B型)病例的时间序列进行拟合来直接估计。第三个目的是探索不同寄主之间的差异会在多大程度上影响菌株竞争的结果。这些差异可能有遗传根源，如宿主的MHC I和II等位基因，或源于宿主特定的感染史；初步工作表明，对特定表位的高度偏见反应促进了抗原类型的共存。为了衡量异质性反应的影响，基于个体的模型将被用来在异质性和同质性的假设下比较平衡和非平衡多样性水平。这项为期三年的博士后研究培训计划将提高研究人员对传染病免疫学、不同免疫机制如何影响宿主-病原体动态以及哪些建模方法适合不同情况的理解。加上一系列不同的专业培训机会，这一经历将使调查员为独立研究职位做好准备。这一知识最终将对研究人员和其他寻求开发竞争病原体菌株动态预测模型的科学家有用。

DESCRIPTION (provided by applicant): Many human pathogens show extensive antigenic diversity. Immunity from infection with one antigenic variant is often partially protective against infection with another antigenic variant, resulting in competition between antigenically similar strains for susceptible hosts. Understanding the immunological mechanisms underlying this competition is an important step in predicting strain dynamics, including such questions as whether a new antigenic variant will drive residents extinct, and how vaccination against some strains will affect competing strains that aren't targeted. Classic models of strain competition predict negative frequency-dependent selection driven by long-lasting, strain-specific immunity. Though sometimes a useful approximation, these simple models shed little light on how other known mechanisms of immunity might explain subtle differences in patterns of antigenic diversity of related pathogens. The goal of this project is to test the general hypothesis that different kinds of immunity shape population-level patterns in pathogen diversity. The first aim is to assess the roles of innate and antibody-based immunity in generating the patterns of antigenic diversity in two common bacterial pathogens, Streptococcus pneumoniae (pneumococcus) and Neisseria meningitidis (meningococcus). The respective contributions of each kind of immunity will be evaluated by comparing the observed prevalence of major antigenic types with results from an individual-based model in which the strength, breadth, and duration of heterologous immunity are varied in accordance with each type of immunity. The second aim uses the same three factors to infer the contributions of innate, cellular, and humoral immunity to the dynamics of two viruses, influenza and parainfluenza. The three factors will be estimated directly by fitting models of ordinary differential equations to time series of cases of each major antigenic type (serotypes 1-3 of parainfluenza and type A (subtype H3N2), A (H1N1), and B of influenza). The third aim explores to what extent differences between individual hosts might influence the outcomes of strain competition. These differences might have a genetic origin, such as hosts' MHC type I and II alleles, or derive from hosts' specific infection histories; preliminary work suggests highly biased responses to particular epitopes promote coexistence of antigenic types. To measure the effects of heterogeneous responses, individual-based models will be used to compare equilibrium and nonequilibrium diversity levels under assumptions of heterogeneity and homogeneity. This three-year postdoctoral research training plan will improve the investigator's understanding of the immunology of infectious diseases, the ways in which different immune mechanisms can affect host-pathogen dynamics, and which modeling approaches are appropriate in different situations. Augmented by a diverse set of professional training opportunities, this experience will prepare the investigator for an independent research position. This knowledge will ultimately be useful to the investigator and other scientists seeking to develop predictive models of the dynamics of competing pathogen strains.