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病毒免疫协同进化的抗原波。

Antigenic waves of virus-immune coevolution.

机构信息

Laboratoire de Physique de l'École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, 75005 Paris, France.

Institute for Biological Physics, University of Cologne, 50937 Cologne, Germany.

出版信息

Proc Natl Acad Sci U S A. 2021 Jul 6;118(27). doi: 10.1073/pnas.2103398118.

Abstract

The evolution of many microbes and pathogens, including circulating viruses such as seasonal influenza, is driven by immune pressure from the host population. In turn, the immune systems of infected populations get updated, chasing viruses even farther away. Quantitatively understanding how these dynamics result in observed patterns of rapid pathogen and immune adaptation is instrumental to epidemiological and evolutionary forecasting. Here we present a mathematical theory of coevolution between immune systems and viruses in a finite-dimensional antigenic space, which describes the cross-reactivity of viral strains and immune systems primed by previous infections. We show the emergence of an antigenic wave that is pushed forward and canalized by cross-reactivity. We obtain analytical results for shape, speed, and angular diffusion of the wave. In particular, we show that viral-immune coevolution generates an emergent timescale, the persistence time of the wave's direction in antigenic space, which can be much longer than the coalescence time of the viral population. We compare these dynamics to the observed antigenic turnover of influenza strains, and we discuss how the dimensionality of antigenic space impacts the predictability of the evolutionary dynamics. Our results provide a concrete and tractable framework to describe pathogen-host coevolution.

摘要

许多微生物和病原体的进化,包括季节性流感等循环病毒,都是由宿主群体的免疫压力驱动的。反过来,受感染人群的免疫系统也会得到更新,从而更深入地追踪病毒。从定量上理解这些动态如何导致观察到的病原体和免疫适应性的快速变化,对于流行病学和进化预测至关重要。在这里,我们提出了一种在有限维抗原空间中免疫系统和病毒之间共同进化的数学理论,该理论描述了病毒株和由先前感染引发的免疫系统之间的交叉反应性。我们展示了由交叉反应推动和引导的抗原波的出现。我们获得了波的形状、速度和角扩散的解析结果。特别是,我们表明病毒-免疫共同进化产生了一个新的时间尺度,即抗原空间中波的方向持续时间,它可能比病毒群体的合并时间长得多。我们将这些动态与流感株的观察到的抗原转换进行了比较,并讨论了抗原空间的维度如何影响进化动态的可预测性。我们的结果为描述病原体-宿主共同进化提供了一个具体且易于处理的框架。

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