Molecular mechanisms of muscle plasticity with exercise

Hoppeler, Hans-Heinrich; Baum, Oliver; Lurman, Glenn; Müller, Matthias (2011). Molecular mechanisms of muscle plasticity with exercise. COMPREHENSIVE PHYSIOLOGY, 1(3), pp. 1383-1412. Wiley 10.1002/cphy.c100042

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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 Ca2+ 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.

Item Type:	Journal Article (Review Article)
Division/Institute:	04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Anatomy
UniBE Contributor:	Hoppeler, Hans-Heinrich, Baum, Oliver, Lurman, Glenn, Müller, Matthias
Subjects:	600 Technology > 610 Medicine & health
ISSN:	2040-4603
ISBN:	9780470650714
Publisher:	Wiley
Language:	English
Submitter:	Factscience Import
Date Deposited:	04 Oct 2013 14:19
Last Modified:	05 Dec 2022 14:05
Publisher DOI:	10.1002/cphy.c100042
PubMed ID:	23733647
Web of Science ID:	000208632800012
URI:	https://boris.unibe.ch/id/eprint/6352 (FactScience: 211297)