Title |
Interaction between signalling pathways involved in skeletal muscle responses to endurance exercise
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Published in |
Pflügers Archiv - European Journal of Physiology, January 2006
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DOI | 10.1007/s00424-005-0030-9 |
Pubmed ID | |
Authors |
Nathalie Koulmann, André-Xavier Bigard |
Abstract |
The purpose of this review is to summarise the latest literature on the signalling pathways involved in transcriptional modulations of genes that encode contractile and metabolic proteins in response to endurance exercise. A special attention has been paid to the cooperation between signalling pathways and coordinated expression of protein families that establish myofibre phenotype. Calcium acts as a second messenger in skeletal muscle during exercise, conveying neuromuscular activity into changes in the transcription of specific genes. Three main calcium-triggered regulatory pathways acting through calcineurin, Ca(2+)-calmodulin-dependent protein kinases (CaMK) and Ca(2+)-dependent protein kinase C, transduce alterations in cytosolic calcium concentration to target genes. Calcineurin signalling, the most important of these Ca(2+)-dependent pathways, stimulates the activation of many slow-fibre gene expression, including genes encoding proteins involved in contractile process, Ca(2+) uptake and energy metabolism. It involves the interaction between multiple transcription factors and the collaboration of other Ca(2+)-dependent CaMKs. Although members of mitogen-activated protein kinase (MAPK) pathways are activated during exercise, their integration into other signalling pathways remains largely unknown. The peroxisome proliferator-activated receptor gamma (PPARgamma) coactivator-1alpha (PGC-1alpha) constitutes a pivotal factor of the circuitry which coordinates mitochondrial biogenesis and which couples to the expression of contractile and metabolic genes with prolonged exercise. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Brazil | 2 | 2% |
Netherlands | 1 | <1% |
Norway | 1 | <1% |
Germany | 1 | <1% |
South Africa | 1 | <1% |
United Kingdom | 1 | <1% |
Canada | 1 | <1% |
Luxembourg | 1 | <1% |
Other | 0 | 0% |
Unknown | 112 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 28 | 23% |
Student > Master | 20 | 16% |
Researcher | 14 | 11% |
Student > Bachelor | 13 | 11% |
Student > Doctoral Student | 10 | 8% |
Other | 25 | 20% |
Unknown | 13 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Sports and Recreations | 38 | 31% |
Agricultural and Biological Sciences | 34 | 28% |
Medicine and Dentistry | 14 | 11% |
Biochemistry, Genetics and Molecular Biology | 11 | 9% |
Neuroscience | 3 | 2% |
Other | 8 | 7% |
Unknown | 15 | 12% |