Molecular networks in skeletal muscle plasticity
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Updated: Mar 26, 2026

Author Spotlight: Isolation of Long Muscle Fibers from Mouse Hindlimb Muscles for Studying Excitation-Contraction Coupling Across Fiber Types
Published on: December 1, 2023
1Emeritus Department of Anatomy, University of Bern, Baltzerstrasse 2, Bern 9 CH-3000, Switzerland hoppeler@ana.unibe.ch.
Abstract:
The skeletal muscle phenotype is subject to considerable malleability depending on use as well as internal and external cues. In humans, low-load endurance-type exercise leads to qualitative changes of muscle tissue characterized by an increase in structures supporting oxygen delivery and consumption, such as capillaries and mitochondria. High-load strength-type exercise leads to growth of muscle fibers dominated by an increase in contractile proteins. In endurance exercise, stress-induced signaling leads to transcriptional upregulation of genes, with Ca(2+) signaling and the energy status of the muscle cells sensed through AMPK being major input determinants. Several interrelated signaling pathways converge on the transcriptional co-activator PGC-1α, perceived to be the coordinator of much of the transcriptional and post-transcriptional processes. Strength training is dominated by a translational upregulation controlled by mTORC1. mTORC1 is mainly regulated by an insulin- and/or growth-factor-dependent signaling cascade as well as mechanical and nutritional cues. Muscle growth is further supported by DNA recruitment through activation and incorporation of satellite cells. In addition, there are several negative regulators of muscle mass. We currently have a good descriptive understanding of the molecular mechanisms controlling the muscle phenotype. The topology of signaling networks seems highly conserved among species, with the signaling outcome being dependent on the particular way individual species make use of the options offered by the multi-nodal networks. As a consequence, muscle structural and functional modifications can be achieved by an almost unlimited combination of inputs and downstream signaling events.
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