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mTORC、AMPK 和 SIRT 之间的相互作用:细胞能量平衡和代谢的计算模型。

Interactions among mTORC, AMPK and SIRT: a computational model for cell energy balance and metabolism.

机构信息

Department of Applied Mathematics, University of Waterloo, Waterloo, ON, Canada.

Department of Biology, Cheriton School of Computer Science, and School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.

出版信息

Cell Commun Signal. 2021 May 20;19(1):57. doi: 10.1186/s12964-021-00706-1.

Abstract

BACKGROUND

Cells adapt their metabolism and activities in response to signals from their surroundings, and this ability is essential for their survival in the face of perturbations. In tissues a deficit of these mechanisms is commonly associated with cellular aging and diseases, such as cardiovascular disease, cancer, immune system decline, and neurological pathologies. Several proteins have been identified as being able to respond directly to energy, nutrient, and growth factor levels and stress stimuli in order to mediate adaptations in the cell. In particular, mTOR, AMPK, and sirtuins are known to play an essential role in the management of metabolic stress and energy balance in mammals.

METHODS

To understand the complex interactions of these signalling pathways and environmental signals, and how those interactions may impact lifespan and health-span, we have developed a computational model of metabolic signalling pathways. Specifically, the model includes (i) the insulin/IGF-1 pathway, which couples energy and nutrient abundance to the execution of cell growth and division, (ii) mTORC1 and the amino acid sensors such as sestrin, (iii) the Preiss-Handler and salvage pathways, which regulate the metabolism of NAD+ and the NAD+ -consuming factor SIRT1, (iv) the energy sensor AMPK, and (v) transcription factors FOXO and PGC-1α.

RESULTS

The model simulates the interactions among key regulators such as AKT, mTORC1, AMPK, NAD+ , and SIRT, and predicts their dynamics. Key findings include the clinically important role of PRAS40 and diet in mTORC1 inhibition, and a potential link between SIRT1-activating compounds and premature autophagy. Moreover, the model captures the exquisite interactions of leucine, sestrin2, and arginine, and the resulting signal to the mTORC1 pathway. These results can be leveraged in the development of novel treatment of cancers and other diseases.

CONCLUSIONS

This study presents a state-of-the-art computational model for investigating the interactions among signaling pathways and environmental stimuli in growth, ageing, metabolism, and diseases. The model can be used as an essential component to simulate gene manipulation, therapies (e.g., rapamycin and wortmannin), calorie restrictions, and chronic stress, and assess their functional implications on longevity and ageing-related diseases. Video Abstract.

摘要

背景

细胞通过感知周围环境的信号来调整代谢和活动,这种能力对于它们在面对干扰时的存活至关重要。在组织中,这些机制的缺陷通常与细胞衰老和疾病有关,如心血管疾病、癌症、免疫系统衰退和神经病理学。已经鉴定出几种蛋白质能够直接响应能量、营养和生长因子水平以及应激刺激,从而介导细胞的适应。特别是,mTOR、AMPK 和 sirtuins 被认为在哺乳动物的代谢应激和能量平衡管理中发挥着重要作用。

方法

为了了解这些信号通路和环境信号的复杂相互作用,以及这些相互作用如何影响寿命和健康跨度,我们开发了一种代谢信号通路的计算模型。具体来说,该模型包括(i)胰岛素/IGF-1 通路,它将能量和营养丰度与细胞生长和分裂的执行联系起来,(ii)mTORC1 和氨基酸传感器,如 sestrin,(iii)Preiss-Handler 和补救途径,它们调节 NAD+的代谢和 NAD+消耗因子 SIRT1,(iv)能量传感器 AMPK,以及(v)转录因子 FOXO 和 PGC-1α。

结果

该模型模拟了 AKT、mTORC1、AMPK、NAD+和 SIRT 等关键调节剂之间的相互作用,并预测了它们的动态。主要发现包括 PRAS40 和饮食在 mTORC1 抑制中的临床重要作用,以及 SIRT1 激活化合物和过早自噬之间的潜在联系。此外,该模型还捕捉到了亮氨酸、 sestrin2 和精氨酸之间的精确相互作用,以及它们对 mTORC1 途径的信号。这些结果可用于开发癌症和其他疾病的新治疗方法。

结论

本研究提出了一种用于研究生长、衰老、代谢和疾病中信号通路与环境刺激相互作用的最先进的计算模型。该模型可用于模拟基因操作、治疗方法(如雷帕霉素和渥曼青霉素)、热量限制和慢性应激,并评估它们对寿命和衰老相关疾病的功能影响。视频摘要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8114/8135154/c12fd6f10049/12964_2021_706_Fig1_HTML.jpg

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