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Molecular Mechanisms of Muscle Plasticity with Exercise

骨骼肌 下调和上调 信号转导 细胞生物学 生物 转录因子 细胞信号 安普克 内分泌学 基因 磷酸化 遗传学 蛋白激酶A
作者
Hans Hoppeler,Oliver Baum,Glenn J. Lurman,Matthias Mueller
出处
期刊:Comprehensive Physiology 卷期号:: 1383-1412 被引量:100
标识
DOI:10.1002/cphy.c100042
摘要

Abstract The skeletal muscle phenotype is subject to considerable malleability depending on use. Low‐intensity endurance type exercise leads to qualitative changes of muscle tissue characterized mainly by an increase in structures supporting oxygen delivery and consumption. High‐load strength‐type exercise leads to growth of muscle fibers dominated by an increase in contractile proteins. In low‐intensity exercise, stress‐induced signaling leads to transcriptional upregulation of a multitude of genes with Ca 2+ signaling and the energy status of the muscle cells sensed through AMPK being major input determinants. Several parallel signaling pathways converge on the transcriptional co‐activator PGC‐1α, perceived as being the coordinator of much of the transcriptional and posttranscriptional processes. High‐load training is dominated by a translational upregulation controlled by mTOR mainly influenced by an insulin/growth factor‐dependent signaling cascade as well as mechanical and nutritional cues. Exercise‐induced muscle growth is further supported by DNA recruitment through activation and incorporation of satellite cells. Crucial nodes of strength and endurance exercise signaling networks are shared making these training modes interdependent. Robustness of exercise‐related signaling is the consequence of signaling being multiple parallel with feed‐back and feed‐forward control over single and multiple signaling levels. We currently have a good descriptive understanding of the molecular mechanisms controlling muscle phenotypic plasticity. We lack understanding of the precise interactions among partners of signaling networks and accordingly models to predict signaling outcome of entire networks. A major current challenge is to verify and apply available knowledge gained in model systems to predict human phenotypic plasticity. © 2011 American Physiological Society. Compr Physiol 1:1383‐1412, 2011.

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