Institut für Integrative Biologie, ETH, Universitätstrasse 16, Zürich, Switzerland.
J Evol Biol. 2009 May;22(5):1123-32. doi: 10.1111/j.1420-9101.2009.01726.x.
The evolution of infectious diseases is known to affect epidemiological dynamics, but, for some viruses and bacteria, this evolution also takes place inside a host during the course of an infection. I develop an original approach to study intrahost evolutionary dynamics of quantitative disease traits. This approach can be expressed mathematically using the ‘Price equation’ framework recently developed in evolutionary epidemiology. This framework combines population genetics and within-host population dynamics models to identify trade-offs that affect disease intrahost evolution and to predict short-term evolutionary dynamics of life-history traits. I show that this can be applied to study the evolution of viruses competing for host cells or to study the coevolution between parasites and the immune system of the host. This framework can also easily incorporate experimental data. Studying intrahost evolutionary dynamics provides insight at the within-host level, because it allows us to better understand the course of chronic infections, and at the epidemiological level, because it helps to study multi-scale evolutionary processes. This framework can be used to address important biological issues, from immune escape to disease evolutionary response to treatments.
传染病的进化过程已知会影响流行病学动态，但对于某些病毒和细菌而言，这种进化也会在感染过程中发生在宿主内部。我开发了一种研究定量疾病特征的宿主内进化动态的新方法。这种方法可以使用最近在进化流行病学中发展起来的“Price 方程”框架进行数学表达。该框架将群体遗传学和宿主内种群动态模型结合起来，以确定影响疾病宿主内进化的权衡，并预测生活史特征的短期进化动态。我表明，这可应用于研究争夺宿主细胞的病毒的进化，或研究寄生虫与宿主免疫系统之间的共同进化。该框架还可以轻松纳入实验数据。研究宿主内进化动态可以提供在宿主内水平的洞察力，因为它可以帮助我们更好地了解慢性感染的过程，并且可以在流行病学水平上进行研究，因为它有助于研究多尺度进化过程。该框架可用于解决重要的生物学问题，从免疫逃避到疾病对治疗的进化反应。
