Szymańska Paulina, Martin Katie R, MacKeigan Jeffrey P, Hlavacek William S, Lipniacki Tomasz
College of Inter-Faculty Individual Studies in Mathematics and Natural Sciences, University of Warsaw, Warsaw, Poland.
Van Andel Institute, Grand Rapids, Michigan, United States of America.
PLoS One. 2015 Mar 11;10(3):e0116550. doi: 10.1371/journal.pone.0116550. eCollection 2015.
We constructed a mechanistic, computational model for regulation of (macro)autophagy and protein synthesis (at the level of translation). The model was formulated to study the system-level consequences of interactions among the following proteins: two key components of MTOR complex 1 (MTORC1), namely the protein kinase MTOR (mechanistic target of rapamycin) and the scaffold protein RPTOR; the autophagy-initiating protein kinase ULK1; and the multimeric energy-sensing AMP-activated protein kinase (AMPK). Inputs of the model include intrinsic AMPK kinase activity, which is taken as an adjustable surrogate parameter for cellular energy level or AMP:ATP ratio, and rapamycin dose, which controls MTORC1 activity. Outputs of the model include the phosphorylation level of the translational repressor EIF4EBP1, a substrate of MTORC1, and the phosphorylation level of AMBRA1 (activating molecule in BECN1-regulated autophagy), a substrate of ULK1 critical for autophagosome formation. The model incorporates reciprocal regulation of mTORC1 and ULK1 by AMPK, mutual inhibition of MTORC1 and ULK1, and ULK1-mediated negative feedback regulation of AMPK. Through analysis of the model, we find that these processes may be responsible, depending on conditions, for graded responses to stress inputs, for bistable switching between autophagy and protein synthesis, or relaxation oscillations, comprising alternating periods of autophagy and protein synthesis. A sensitivity analysis indicates that the prediction of oscillatory behavior is robust to changes of the parameter values of the model. The model provides testable predictions about the behavior of the AMPK-MTORC1-ULK1 network, which plays a central role in maintaining cellular energy and nutrient homeostasis.
我们构建了一个用于调节（巨）自噬和蛋白质合成（翻译水平）的机制性计算模型。该模型旨在研究以下蛋白质之间相互作用的系统级后果：雷帕霉素靶蛋白复合物1（MTORC1）的两个关键组分，即蛋白激酶MTOR（雷帕霉素的机制性靶标）和支架蛋白RPTOR；自噬起始蛋白激酶ULK1；以及多聚体能量感应AMP激活蛋白激酶（AMPK）。模型的输入包括内在的AMPK激酶活性（被用作细胞能量水平或AMP:ATP比值的可调替代参数）和雷帕霉素剂量（用于控制MTORC1活性）。模型的输出包括MTORC1的底物——翻译抑制因子EIF4EBP1的磷酸化水平，以及ULK1的底物——AMBRA1（在BECN1调节的自噬中的激活分子，对自噬体形成至关重要）的磷酸化水平。该模型纳入了AMPK对mTORC1和ULK1的相互调节、MTORC1和ULK1的相互抑制，以及ULK1介导的对AMPK的负反馈调节。通过对模型的分析，我们发现，根据条件不同，这些过程可能导致对应激输入的分级反应、自噬和蛋白质合成之间的双稳态切换，或弛豫振荡（包括自噬和蛋白质合成交替的时期）。敏感性分析表明，振荡行为的预测对模型参数值的变化具有鲁棒性。该模型提供了关于AMPK-MTORC1-ULK1网络行为的可测试预测，该网络在维持细胞能量和营养稳态中起核心作用。
