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植物免疫网络中细胞表面模式识别的演变格局。

The evolving landscape of cell surface pattern recognition across plant immune networks.

机构信息

Department of Biology, University of Washington, Seattle WA 98195, USA; Washington Research Foundation, Seattle, WA 98102, USA.

出版信息

Curr Opin Plant Biol. 2020 Aug;56:135-146. doi: 10.1016/j.pbi.2020.05.001. Epub 2020 Jun 29.

Abstract

To recognize diverse threats, plants monitor extracellular molecular patterns and transduce intracellular immune signaling through receptor complexes at the plasma membrane. Pattern recognition occurs through a prototypical network of interacting proteins, comprising A) receptors that recognize inputs associated with a growing number of pest and pathogen classes (bacteria, fungi, oomycetes, caterpillars), B) co-receptor kinases that participate in binding and signaling, and C) cytoplasmic kinases that mediate first stages of immune output. While this framework has been elucidated in reference accessions of model organisms, network components are part of gene families with widespread variation, potentially tuning immunocompetence for specific contexts. Most dramatically, variation in receptor repertoires determines the range of ligands acting as immunogenic inputs for a given plant. Diversification of receptor kinase (RK) and related receptor-like protein (RLP) repertoires may tune responses even within a species. Comparative genomics at pangenome scale will reveal patterns and features of immune network variation.

摘要

为了识别各种威胁,植物通过质膜上的受体复合物监测细胞外分子模式并转导细胞内免疫信号。模式识别通过一个相互作用蛋白的典型网络来实现,该网络包括 A)识别与越来越多的害虫和病原体类群(细菌、真菌、卵菌、毛毛虫)相关输入的受体,B)参与结合和信号转导的共受体激酶,以及 C)介导免疫输出初始阶段的细胞质激酶。虽然这个框架已经在模式生物的参考品系中阐明,但网络组件是具有广泛变异的基因家族的一部分,可能为特定的环境调整免疫能力。最显著的是,受体库的变异决定了作为给定植物免疫原性输入的配体范围。受体激酶(RK)和相关受体样蛋白(RLP)库的多样化甚至可以调节物种内的反应。泛基因组规模的比较基因组学将揭示免疫网络变异的模式和特征。

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