TWO-STEP INFECTION PROCESSES CAN LEAD TO COEVOLUTION BETWEEN FUNCTIONALLY INDEPENDENT INFECTION AND RESISTANCE PATHWAYS

TWO-STEP INFECTION PROCESSES CAN LEAD TO COEVOLUTION BETWEEN FUNCTIONALLY INDEPENDENT INFECTION AND RESISTANCE PATHWAYS
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DOI:
10.1111/j.1558-5646.2012.01578.x
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发表时间:
2012-07-01
期刊:
影响因子:
3.3
通讯作者:
Brockhurst, Michael A.
Brockhurst, Michael A.
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Fenton, Andy;Antonovics, Janis;Brockhurst, Michael A.

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越来越多的证据表明,病原体成功感染宿主需要一系列独立的步骤。然而,多步骤感染过程如何影响宿主病原体共同进化尚不清楚。我们提出了一个共同进化模型,灵感来自一系列宿主-病原体系统的经验观察,其中感染过程包括以下两个步骤:第一步是病原体识别和定位合适的宿主,第二步是利用宿主同时逃避免疫。重要的是,这两个步骤分别符合不同的感染遗传学模型:逆基因换基因(IGFG)和基因换基因(GFG)。我们表明,在这种情况下,共同进化可以导致这两个系统之间的耦合基因频率变化。特别是,选择往往倾向于在第一步(IGFG)中具有传染性的病原体和在第二步(GFG)中具有抗性的宿主。因此,只要存在决定抗性和传染性的多步骤过程,就可能存在功能独立系统之间正选择的信号。这种多步骤感染过程是许多宿主-病原体相互作用的基本但被忽视的特征,并且对我们理解宿主-病原体共同进化具有重要影响。
There is growing evidence that successful infection of hosts by pathogens requires a series of independent steps. However, how multistep infection processes affect hostpathogen coevolution is unclear. We present a coevolutionary model, inspired by empirical observations from a range of hostpathogen systems, where the infection process consists of the following two steps: the first is for the pathogen to recognize and locate a suitable host, and the second is to exploit the host while evading immunity. Importantly, these two steps conform to different models of infection genetics: inverse-gene-for-gene (IGFG) and gene-for-gene (GFG), respectively. We show that coevolution under this scenario can lead to coupled gene frequency changes across these two systems. In particular, selection often favors pathogens that are infective at the first, IGFG, step and hosts that are resistant at the second, GFG, step. Hence, there may be signals of positive selection between functionally independent systems whenever there are multistep processes determining resistance and infectivity. Such multistep infection processes are a fundamental, but overlooked feature of many hostpathogen interactions, and have important consequences for our understanding of hostpathogen coevolution.