The highly buffered Arabidopsis immune signaling network conceals the functions of its components.
The highly buffered Arabidopsis immune signaling network conceals the functions of its components.
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DOI：
10.1371/journal.pgen.1006639
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发表时间：
2017-05
期刊：
影响因子：
4.5
通讯作者：
Katagiri F
中科院分区：
文献类型：
--
作者：
Hillmer RA;Tsuda K;Rallapalli G;Asai S;Truman W;Papke MD;Sakakibara H;Jones JDG;Myers CL;Katagiri F
植物免疫保护植物免受许多潜在致病微生物的侵害。控制植物诱导免疫的生物网络必须有效地发挥作用，即使网络成分被病原体效应物靶向或禁用。网络缓冲可以通过允许网络的不同部分补偿彼此功能的损失来赋予这种弹性。丰富的缓冲网络依赖于网络内部的相互作用，但这些机制很难通过简单的遗传手段来研究。通过网络重组策略，我们分解并逐步重组介导模式触发免疫的植物免疫网络，我们已经解决了拟南芥转录组对免疫刺激物鞭毛蛋白22 （flg22）反应的系统水平调节机制。这些机制显示了flg22应答转录组中主要子网络（我们称之为扇区）之间相互作用的广泛证据。这些交互中的许多都会导致网络缓冲。已解决的调控机制揭示了茉莉酸盐（JA）、乙烯（ET）、植物抗毒素缺陷4 （PAD4）和水杨酸盐（SA）信号传导部门如何控制flg22的转录反应。我们证明，我们解决的许多调控机制是无法检测到传统的单基因零突变分析的遗传方法。与潜在的致病扰动类似，免疫信号的零突变效应可以被网络缓冲。为了保护自己免受病原体的侵害，植物检测到病原体的攻击，并通过激活各种免疫反应的信号网络发送这一信息。病原体分泌的效应物使免疫信号网络的成分失效。因此，植物免疫信号网络的功能必须很好地缓冲效应扰动。关于这种网络缓冲是如何实现的，我们所知不多。这在一定程度上是因为单个网络组件的突变影响也被网络很好地缓冲了。为了克服单基因突变分析的这一缺点，我们采用了网络重构策略，首先禁用四个主要信号部门，然后逐一恢复，以确定信号部门的功能及其相互作用。我们收集并分析了细菌鞭毛蛋白免疫刺激后所有可能的网络重构状态的转录组和激素谱。我们发现神经网络不是独立路径的集合；相反，部门之间的相互作用主导了转录组反应的网络调节，这解释了观察到的广泛的网络缓冲。因此，基于单基因突变分析推断的表观网络机制往往与潜在机制不同。
Plant immunity protects plants from numerous potentially pathogenic microbes. The biological network that controls plant inducible immunity must function effectively even when network components are targeted and disabled by pathogen effectors. Network buffering could confer this resilience by allowing different parts of the network to compensate for loss of one another’s functions. Networks rich in buffering rely on interactions within the network, but these mechanisms are difficult to study by simple genetic means. Through a network reconstitution strategy, in which we disassemble and stepwise reassemble the plant immune network that mediates Pattern-Triggered-Immunity, we have resolved systems-level regulatory mechanisms underlying the Arabidopsis transcriptome response to the immune stimulant flagellin-22 (flg22). These mechanisms show widespread evidence of interactions among major sub-networks—we call these sectors—in the flg22-responsive transcriptome. Many of these interactions result in network buffering. Resolved regulatory mechanisms show unexpected patterns for how the jasmonate (JA), ethylene (ET), phytoalexin-deficient 4 (PAD4), and salicylate (SA) signaling sectors control the transcriptional response to flg22. We demonstrate that many of the regulatory mechanisms we resolved are not detectable by the traditional genetic approach of single-gene null-mutant analysis. Similar to potential pathogenic perturbations, null-mutant effects on immune signaling can be buffered by the network. To protect themselves from pathogens, plants detect pathogen attack and send this information through a signaling network that activates various immune responses. Pathogens secrete effectors that disable components of the immune signaling network. Thus, the function of the plant immune signaling network must be well buffered from effector perturbations. Not much is known about how such network buffering is achieved. This is partly because the effects of mutations in single network components are also well buffered by the network. To overcome this shortcoming of single-gene mutant analysis, we employed a network reconstitution strategy, in which four major signaling sectors were first disabled and then restored one by one to determine the functions of the signaling sectors and their interactions. We collected and analyzed transcriptome and hormone profiles from all possible states of network reconstitution along time courses after immune stimulation with bacterial flagellin. We discovered that the network is not a collection of independent pathways; rather, interactions among the sectors dominate network regulation of the transcriptome response, which explains the extensive network buffering observed. Consequently, apparent network mechanisms inferred based on single-gene mutant analysis were often different from the underlying mechanisms.