Network analysis of human skeletal muscle adaptation under different loading states

As people grow older skeletal muscle gradually becomes smaller and weaker. This progressive muscle weakness results in reduced mobility, independence and quality of life, and increased incidence of frailty-related falls and injury in ageing populations. A commonly observed feature that might contribute to age-related muscle decline is blunted growth responses to exercise training, and a likely impairment in muscular regeneration from individual bouts of activity. Whilst the mechanisms underpinning this phenomenon are poorly understood, failure of exercise-responsive molecular signals are logical candidates for investigation. However, many cross-talking signalling pathways are involved in the post-exercise remodelling process, and systematic evaluation of all associated regulatory molecules and their dysregulation in ageing muscle is not feasible in humans. This project will therefore employ an interdisciplinary approach to predict novel signalling networks regulating exercise-induced metabolic/functional adaptation, and examine the physiological role of these networks directly in ageing people during acute post-exercise muscle remodelling. Bioinformatic predictive modelling will be used to filter candidate network components involved in muscle adaptation to exercise. The relevance of these networks to ageing muscle decline will then be examined using state-of-the-art immunofluorescent imaging techniques, applied to human muscle biopsy samples collected during the acute post-exercise remodelling period. The dynamic temporo-spatial responses of putative regulators of muscle regeneration, overlaid onto the direct functional responses to exercise in humans, will provide new insight into the mechanisms underpinning exercise-mediated muscle adaptation and its deregulation during the ageing process.