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通过鉴定钙信号的解码机制来预测植物免疫基因的表达。

Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures.

机构信息

Department of Biosciences, Durham University, South Road, Durham, DH1 3LE, UK.

出版信息

New Phytol. 2018 Mar;217(4):1598-1609. doi: 10.1111/nph.14924. Epub 2017 Dec 8.

DOI:10.1111/nph.14924
PMID:29218709
Abstract

Calcium plays a key role in determining the specificity of a vast array of signalling pathways in plants. Cellular calcium elevations with different characteristics (calcium signatures) carry information on the identity of the primary stimulus, ensuring appropriate downstream responses. However, the mechanism for decoding calcium signatures is unknown. To determine this, decoding of the salicylic acid (SA)-mediated plant immunity signalling network controlling gene expression was examined. A dynamic mathematical model of the SA-mediated plant immunity network was developed. This model was used to predict responses to different calcium signatures; these were validated empirically using quantitative real-time PCR to measure gene expression. The mechanism for decoding calcium signatures to control expression of plant immunity genes enhanced disease susceptibility 1 (EDS1) and isochorismate synthase 1 (ICS1) was identified. Calcium, calmodulin, calmodulin-binding transcription activators (CAMTA)3 and calmodulin binding protein 60g (CBP60g) together amplify each calcium signature into three active signals, simultaneously regulating expression. The time required for calcium to return to steady-state level also quantitatively regulates gene expression. Decoding of calcium signatures occurs via nonlinear interactions between these active signals, producing a unique response in each case. Key properties of the calcium signatures are not intuitive, exemplifying the importance of mathematical modelling approaches. This approach can be applied to identifying the decoding mechanisms of other plant calcium signalling pathways.

摘要

钙在决定植物中大量信号通路的特异性方面起着关键作用。具有不同特征的细胞钙升高(钙信号)携带关于原始刺激物身份的信息,确保适当的下游反应。然而,解码钙信号的机制尚不清楚。为了确定这一点,研究了解码水杨酸(SA)介导的植物免疫信号网络控制基因表达的机制。开发了一个 SA 介导的植物免疫网络的动态数学模型。该模型用于预测对不同钙信号的反应;这些反应使用定量实时 PCR 进行了经验验证,以测量基因表达。解码钙信号以控制植物免疫基因增强疾病易感性 1(EDS1)和异分支酸合酶 1(ICS1)表达的机制已被确定。钙、钙调蛋白、钙调蛋白结合转录激活因子(CAMTA)3 和钙调蛋白结合蛋白 60g(CBP60g)一起将每个钙信号放大为三个活性信号,同时调节表达。钙恢复到稳定水平所需的时间也定量调节基因表达。钙信号的解码是通过这些活性信号之间的非线性相互作用发生的,在每种情况下产生独特的反应。钙信号的关键特性不是直观的,这证明了数学建模方法的重要性。这种方法可用于确定其他植物钙信号通路的解码机制。

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