Model-driven discovery of calcium-related protein-phosphatase inhibition in plant guard cell signaling
Model-driven discovery of calcium-related protein-phosphatase inhibition in plant guard cell signaling
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DOI：
10.1371/journal.pcbi.1007429
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发表时间：
2019-10-01
影响因子：
4.3
通讯作者：
Albert, Reka
中科院分区：
文献类型：
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作者：
Maheshwari, Parul;Du, Hao;Albert, Reka
植物激素脱落酸（阿坝）通过多种细胞信号级联促进气孔关闭。我们以前的气孔关闭网络的全面重建导致了一个81节点的网络与153条边。利用该网络的离散动态建模再现了75%以上的实验观察结果，但一些实验支持的结果没有概括。在这里，我们确定的预测，提高模型和实验之间的协议。我们进行了动态保持网络约简，得到了一个浓缩的49个节点和113个边缘的气孔关闭网络，保留了所有的动态决定网络图案，并再现了原始模型的预测。然后，我们利用减少网络探索的情况下，在没有阿坝的实验激活内部节点引起气孔关闭在湿台实验，但不是在我们的计算机模型。我们的模拟结果表明，除了一个单一的边缘，这使得间接抑制任何一个的三个PP 2C蛋白磷酸酶（ABI 2，PP 2CA，HAB 1）的胞质Ca 2+升高，解决了大多数的差异。与这一假设相一致，我们的实验表明，在生理浓度的细胞裂解液中的Ca 2+应用抑制PP 2C活性。这个新的边缘增强的模型提供了新的见解胞质Ca 2+振荡在气孔关闭中的作用，揭示了胞质Ca 2+浓度的反复增加和信号网络内部的自我维持反馈电路之间的相互加强。这些结果说明了模型和实验之间的迭代如何提高高度复杂的细胞dynamics.Author总结预测我们建立在一个全面的离散动态模型的基础上的植物信号网络，管理关闭的微观气孔表面上的叶子。该网络收集了绝大多数关于响应一种特定信号-激素脱落酸-而关闭气孔的实验观察结果，脱落酸在干旱期间促使气孔关闭，从而促进植物水分保持。在这里，我们确定了一个知识差距，在理解实验观察到的气孔关闭响应网络中的内部节点的激活。与这些节点可能沿着沿着线性路径定位的期望相反，我们发现，通过加强反馈丰富的子网络可以填补知识缺口。具体来说，我们预测，胞浆钙升高可以抑制一个或多个2C型蛋白磷酸酶，并证实了这一预测实验。这个新的信息增强的模型概括了内部节点激活的实验观察，通过一种可能推广到其他生物网络的机制。这种机制的关键是两个反馈回路之间的相互强化，一个产生重复的活动模式，另一个保持持续的活动模式。
The plant hormone abscisic acid (ABA) promotes stomatal closure via multifarious cellular signaling cascades. Our previous comprehensive reconstruction of the stomatal closure network resulted in an 81-node network with 153 edges. Discrete dynamic modeling utilizing this network reproduced over 75% of experimental observations but a few experimentally supported results were not recapitulated. Here we identify predictions that improve the agreement between model and experiment. We performed dynamics-preserving network reduction, resulting in a condensed 49 node and 113 edge stomatal closure network that preserved all dynamics-determining network motifs and reproduced the predictions of the original model. We then utilized the reduced network to explore cases in which experimental activation of internal nodes in the absence of ABA elicited stomatal closure in wet bench experiments, but not in our in silico model. Our simulations revealed that addition of a single edge, which allows indirect inhibition of any one of three PP2C protein phosphatases (ABI2, PP2CA, HAB1) by cytosolic Ca2+ elevation, resolves the majority of the discrepancies. Consistent with this hypothesis, we experimentally show that Ca2+ application to cellular lysates at physiological concentrations inhibits PP2C activity. The model augmented with this new edge provides new insights into the role of cytosolic Ca2+ oscillations in stomatal closure, revealing a mutual reinforcement between repeated increases in cytosolic Ca2+ concentration and a self-sustaining feedback circuit inside the signaling network. These results illustrate how iteration between model and experiment can improve predictions of highly complex cellular dynamics.Author summary We build on the foundation of a comprehensive discrete dynamic model of a plant signaling network that governs the closing of microscopic stomatal pores on the surface of leaves. That network captured the vast majority of experimental observations regarding closure in response to a specific signal, the hormone abscisic acid, which elicits stomatal closure during drought, thereby promoting plant water conservation. Here, we identify a knowledge gap in understanding experimentally observed stomatal closure in response to activation of internal nodes in the network. In contrast to the expectation that these nodes might be positioned along a linear pathway, we find that the knowledge gap can be filled by reinforcement of a feedback-rich subnetwork. Specifically, we predict that cytosolic calcium elevation can inhibit one or more of three 2C-type protein phosphatases, and confirm this prediction experimentally. The model augmented with this new information recapitulates experimental observations on internal node activation, via a mechanism that is potentially generalizable to other biological networks. Key to this mechanism is a mutual reinforcement between two feedback loops, one that generates a repetitive activity pattern, and another that preserves a sustained activity pattern.