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寄生虫回避行为的基因型变异和其他传播的机制性、非线性成分。

Genotypic variation in parasite avoidance behaviour and other mechanistic, nonlinear components of transmission.

机构信息

Department of Biology, Indiana University, Bloomington, IN 47401, USA.

Department of Biology, Emory University, Atlanta, GA 30322, USA.

出版信息

Proc Biol Sci. 2019 Nov 20;286(1915):20192164. doi: 10.1098/rspb.2019.2164.

Abstract

Traditional epidemiological models assume that transmission increases proportionally to the density of parasites. However, empirical data frequently contradict this assumption. General yet mechanistic models can explain why transmission depends nonlinearly on parasite density and thereby identify potential defensive strategies of hosts. For example, hosts could decrease their exposure rates at higher parasite densities (via behavioural avoidance) decrease their per-parasite susceptibility when encountering more parasites (e.g. via stronger immune responses). To illustrate, we fitted mechanistic transmission models to 19 genotypes of hosts over gradients of the trophically acquired parasite, . Exposure rate (foraging, ) frequently decreased with parasite density (), and per-parasite susceptibility () frequently decreased with parasite encounters (). Consequently, infection rates () often peaked at intermediate parasite densities. Moreover, host genotypes varied substantially in these responses. Exposure rates remained constant for some genotypes but decreased sensitively with parasite density for others (up to 78%). Furthermore, genotypes with more sensitive foraging/exposure also foraged faster in the absence of parasites (suggesting 'fast and sensitive' versus 'slow and steady' strategies). These relationships suggest that high densities of parasites can inhibit transmission by decreasing exposure rates and/or per-parasite susceptibility, and identify several intriguing axes for the evolution of host defence.

摘要

传统的流行病学模型假设,传播与寄生虫密度成正比增加。然而,经验数据经常与这一假设相矛盾。一般但机械的模型可以解释为什么传播与寄生虫密度呈非线性关系,从而确定宿主的潜在防御策略。例如,宿主可以在寄生虫密度较高时降低其暴露率(通过行为回避);在遇到更多寄生虫时降低每只寄生虫的易感性(例如通过更强的免疫反应)。例如,我们根据 营养获得的寄生虫 的梯度拟合了 19 种 宿主的机械传播模型。暴露率(觅食,)经常随寄生虫密度()下降,每只寄生虫的易感性()经常随寄生虫的遭遇()下降。因此,感染率()经常在中间寄生虫密度处达到峰值。此外,宿主基因型在这些反应中差异很大。对于某些基因型,暴露率保持不变,但对于其他基因型,暴露率随寄生虫密度敏感下降(高达 78%)。此外,觅食/暴露更敏感的基因型在没有寄生虫的情况下也更快地觅食(表明“快速而敏感”与“缓慢而稳定”的策略)。这些关系表明,寄生虫的高密度可以通过降低暴露率和/或每只寄生虫的易感性来抑制传播,并确定了宿主防御进化的几个有趣的轴。

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