Ojosnegros Samuel, Beerenwinkel Niko
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Immunome Res. 2010 Nov 3;6 Suppl 2(Suppl 2):S5. doi: 10.1186/1745-7580-6-S2-S5.
Viruses are fast evolving pathogens that continuously adapt to the highly variable environments they live and reproduce in. Strategies devoted to inhibit virus replication and to control their spread among hosts need to cope with these extremely heterogeneous populations and with their potential to avoid medical interventions. Computational techniques such as phylogenetic methods have broadened our picture of viral evolution both in time and space, and mathematical modeling has contributed substantially to our progress in unraveling the dynamics of virus replication, fitness, and virulence. Integration of multiple computational and mathematical approaches with experimental data can help to predict the behavior of viral pathogens and to anticipate their escape dynamics. This piece of information plays a critical role in some aspects of vaccine development, such as viral strain selection for vaccinations or rational attenuation of viruses. Here we review several aspects of viral evolution that can be addressed quantitatively, and we discuss computational methods that have the potential to improve vaccine design.
病毒是快速进化的病原体,它们不断适应其生存和繁殖的高度可变环境。致力于抑制病毒复制并控制其在宿主间传播的策略需要应对这些极其异质的群体及其规避医学干预的潜力。诸如系统发育方法等计算技术拓宽了我们对病毒在时间和空间上进化的认识,数学建模也为我们在揭示病毒复制、适应性和毒力动态方面取得的进展做出了重大贡献。将多种计算和数学方法与实验数据相结合有助于预测病毒病原体的行为并预测其逃逸动态。这条信息在疫苗开发的某些方面起着关键作用,例如疫苗接种的病毒株选择或病毒的合理减毒。在这里,我们回顾了病毒进化中可以定量解决的几个方面,并讨论了有可能改进疫苗设计的计算方法。