Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts 02139, USA.
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Nat Commun. 2016 May 23;7:11660. doi: 10.1038/ncomms11660.
Human immunodeficiency virus (HIV) evolves within infected persons to escape being destroyed by the host immune system, thereby preventing effective immune control of infection. Here, we combine methods from evolutionary dynamics and statistical physics to simulate in vivo HIV sequence evolution, predicting the relative rate of escape and the location of escape mutations in response to T-cell-mediated immune pressure in a cohort of 17 persons with acute HIV infection. Predicted and clinically observed times to escape immune responses agree well, and we show that the mutational pathways to escape depend on the viral sequence background due to epistatic interactions. The ability to predict escape pathways and the duration over which control is maintained by specific immune responses open the door to rational design of immunotherapeutic strategies that might enable long-term control of HIV infection. Our approach enables intra-host evolution of a human pathogen to be predicted in a probabilistic framework.
人类免疫缺陷病毒（HIV）在感染者体内进化，以逃避宿主免疫系统的破坏，从而阻止对感染的有效免疫控制。在这里，我们结合进化动力学和统计物理的方法来模拟体内 HIV 序列进化，预测在 17 名急性 HIV 感染患者的队列中，针对 T 细胞介导的免疫压力，逃避和逃避突变的相对速率。预测和临床观察到的逃避免疫反应的时间非常吻合，我们表明，由于上位性相互作用，逃避的突变途径取决于病毒序列背景。预测逃避途径的能力以及特定免疫反应维持控制的持续时间，为合理设计免疫治疗策略打开了大门，这些策略可能使 HIV 感染得到长期控制。我们的方法能够在概率框架内预测人体病原体的宿主内进化。
