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Dose Response Relationship in Anti-Stress Gene Regulatory Networks

机译:抗应激基因调控网络中的剂量反应关系

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To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on the level of local gains, presence of gain-changing events, and degree of feedforward gene activation, this region can appear as superlinear, sublinear, or even J-shaped. The general dose response transition proposed here was further examined in a complex anti-electrophilic stress pathway, which involves multiple genes, enzymes, and metabolic reactions. This work would help biologists and especially toxicologists to better assess and predict the cellular impact brought about by biological stressors.
机译:为了维持稳定的细胞内环境,细胞利用复杂而专门的防御系统来抵抗各种外部扰动,例如亲电子应激,热休克和缺氧等。不管应激的类型如何,许多导致细胞稳态的适应性机制似乎通过基因调控网络运作,这些网络被组织成负面反馈回路。通常,首先通过专门的传感器分子检测诸如亲电试剂,错误折叠的蛋白质和O2等受控变量的偏离程度,然后将信号转导至特定的转录因子。转录因子可以调节一系列抗应激基因的表达,其中许多抗应激基因编码的酶具有抵消干扰变量的作用。这项研究的目的是使用控制理论和计算方法,探索在这些基因调控中细胞应激源与细胞内生化物种(控制变量,转录因子和基因产物)之间稳态剂量反应关系的理论基础。网络。我们的工作表明剂量响应曲线(线性,超线性或亚线性)的形状取决于分布在反馈回路中的局部响应系数(增益)的特定值的变化。抗应激酶和转录因子多聚化为同型二聚体,同型三聚体,甚至更高阶的多聚体,在维持稳固的体内平衡方面起着重要作用。此外,我们的仿真结果表明,随着应激源水平的提高,受控变量的剂量响应曲线可以依次经历四个不同的阶段:初始超线性(控制较少),超线性(高度受控),线性非受控以及亚线性。每个阶段都依赖于特定的增益变化事件,这些事件随着压力源水平的提高而发挥作用。低剂量区域本质上是非线性的,并且取决于局部增益的水平,增益变化事件的存在以及前馈基因激活的程度,该区域可能显示为超线性,亚线性甚至J形。本文提出的一般剂量反应转变在复杂的抗亲电应激途径中进行了进一步研究,该途径涉及多个基因,酶和代谢反应。这项工作将帮助生物学家,尤其是毒理学家更好地评估和预测生物应激物对细胞的影响。

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