• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Biotechnology Progress >A dynamic mathematical model to clarify signaling circuitry underlying programmed cell death control in Arabidopsis disease resistance [Review]
【24h】

A dynamic mathematical model to clarify signaling circuitry underlying programmed cell death control in Arabidopsis disease resistance [Review]

机译：阐明拟南芥抗病性中编程性细胞死亡控制基础的信号传导电路的动态数学模型[综述]

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Plant cells undergo programmed cell death in response to invading pathogens. This cell death limits the spread of the infection and triggers whole plant antimicrobial and immune responses. The signaling network connecting molecular recognition of pathogens to these responses is a prime target for manipulation in genetic engineering strategies designed to improve crop plant disease resistance. Moreover, as alterations to metabolism can be misinterpreted as pathogen infection, successful plant metabolic engineering will ultimately depend on controlling these signaling pathways to avoid inadvertent activation of cell death. Programmed cell death resulting from infection of Arabidopsis thaliana with Pseudomonas syringae bacterial pathogens was chosen as a model system. Signaling circuitry hypotheses in this model system were tested by construction of a differential-equations-based mathematical model. Model-based simulations of time evolution of signaling components matched experimental measurements of programmed cell death and associated signaling components obtained in a companion study. Simulation of systems-level consequences of mutations used in laboratory studies led to two major improvements in understanding of signaling circuitry: (1) Simulations supported experimental evidence that a negative feedback loop in salicylic acid biosynthesis postulated by others does not exist. (2) Simulations showed that a second negative regulatory circuit for which there was strong experimental support did not affect one of two pathways leading to programmed cell death. Simulations also generated testable predictions to guide future experiments. Additional testable hypotheses were generated by results of individually varying each model parameter over 2 orders of magnitude that predicted biologically important changes to system dynamics. These predictions will be tested in future laboratory studies designed to further elucidate the signaling network control structure.
机译：植物细胞响应入侵的病原体而经历程序性细胞死亡。这种细胞死亡限制了感染的传播，并引发了整个植物的抗微生物和免疫反应。将病原体的分子识别与这些反应联系起来的信号网络是旨在改善农作物抗病性的基因工程策略中操纵的主要目标。此外，由于新陈代谢的改变可能被误解为病原体感染，成功的植物代谢工程最终将取决于控制这些信号传导途径，以避免细胞死亡的意外激活。选择由拟南芥丁香假单胞菌细菌病原体感染引起的拟南芥程序性细胞死亡作为模型系统。通过建立基于微分方程的数学模型，测试了该模型系统中的信号电路假设。基于模型的信号组分时间演变模拟模拟了在伴随研究中获得的程序性细胞死亡和相关信号组分的实验测量结果。对实验室研究中使用的突变的系统级后果进行模拟，导致对信号传导电路的理解有了两个重大改进：（1）模拟支持实验证据，表明其他人没有提出水杨酸生物合成中的负反馈回路。 （2）模拟表明，第二个负调节电路具有强大的实验支持，并不影响导致程序性细胞死亡的两条途径之一。模拟还生成了可测试的预测，以指导将来的实验。通过将每个模型参数分别改变2个数量级以上的结果来生成其他可检验的假设，这些参数预测了系统动力学的生物学重要变化。这些预测将在未来的实验室研究中进行测试，以进一步阐明信令网络的控制结构。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号