Multi-scale mechanobiological model for skeletal muscle hypertrophy

Area of Science:

• Biomechanics
• Molecular Biology
• Computational Modeling

Background:

• Skeletal muscle adaptation to exercise involves complex signaling pathways, notably the IGF1-AKT pathway regulating protein synthesis and degradation.
• Existing computational models often focus separately on biochemical signaling or organ-scale mechanical function.
• Understanding the interplay between muscle geometry and protein synthesis is crucial for modeling muscle adaptation.

Purpose of the Study:

• To develop a computational model integrating the IGF1-AKT signaling pathway with a continuum-mechanical muscle model.
• To investigate the impact of adaptive muscle geometry on protein synthesis at the fiber scale.
• To explore how mechanical responses influence signaling pathways in muscle adaptation.

Main Methods:

• Developed a dynamical model of the IGF1-AKT signaling pathway.
• Linked this to a continuum-mechanical model of muscle active and passive response.
• Introduced a growth tensor to connect signaling to mechanical response and protein synthesis rate to mechanical response.

Main Results:

• The model accurately predicted the increase in cross-sectional area (CSA) following an 8-week training protocol, aligning with experimental data.
• Demonstrated that muscle growth rate diminishes when the correlation between protein synthesis and CSA is negative.
• Highlighted the significant influence of adaptive geometry on protein synthesis rates.

Conclusions:

• Multi-scale computational models coupling mechanical properties and molecular functions offer a promising approach for understanding muscle adaptation.
• This integrated model can enhance the development of targeted muscular therapies and optimized training protocols.
• The findings underscore the importance of considering the bidirectional relationship between mechanical factors and molecular signaling in skeletal muscle.