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生物医学干预逃逸的进化动力学

Evolutionary dynamics of escape from biomedical intervention.

作者信息

Iwasa Yoh, Michor Franziska, Nowak Martin A

机构信息

Department of Biology, Kyushu University, Fukuoka 812-8581, Japan.

出版信息

Proc Biol Sci. 2003 Dec 22;270(1533):2573-8. doi: 10.1098/rspb.2003.2539.

Abstract

Viruses, bacteria, eukaryotic parasites, cancer cells, agricultural pests and other inconvenient animates have an unfortunate tendency to escape from selection pressures that are meant to control them. Chemotherapy, anti-viral drugs or antibiotics fail because their targets do not hold still, but evolve resistance. A major problem in developing vaccines is that microbes evolve and escape from immune responses. The fundamental question is the following: if a genetically diverse population of replicating organisms is challenged with a selection pressure that has the potential to eradicate it, what is the probability that this population will produce escape mutants? Here, we use multi-type branching processes to describe the accumulation of mutants in independent lineages. We calculate escape dynamics for arbitrary mutation networks and fitness landscapes. Our theory shows how to estimate the probability of success or failure of biomedical intervention, such as drug treatment and vaccination, against rapidly evolving organisms.

摘要

病毒、细菌、真核寄生虫、癌细胞、农业害虫以及其他令人头疼的生物具有一种不幸的倾向,即它们会逃避旨在控制它们的选择压力。化疗、抗病毒药物或抗生素失效,是因为它们的靶点并不稳定,而是会产生抗性。开发疫苗的一个主要问题是微生物会进化并逃避免疫反应。根本问题如下:如果一个具有遗传多样性的复制生物群体受到一种有可能根除它的选择压力的挑战,那么这个群体产生逃逸突变体的概率是多少?在这里,我们使用多类型分支过程来描述独立谱系中突变体的积累。我们计算任意突变网络和适应度景观的逃逸动态。我们的理论展示了如何估计针对快速进化生物的生物医学干预(如药物治疗和疫苗接种)成功或失败的概率。

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