Multiscale models of skeletal muscle reveal the complex effects of muscular dystrophy on tissue mechanics and damage susceptibility

Abstract

Computational models have been increasingly used to study the tissue-level constitutive properties of muscle microstructure; however, these models were not created to study or incorporate the influence of disease-associated modifications in muscle. The purpose of this paper was to develop a novel multiscale muscle modelling framework to elucidate the relationship between microstructural disease adaptations and modifications in both mechanical properties of muscle and strain in the cell membrane. We used an agent-based model to randomly generate new muscle fibre geometries and mapped them into a finite-element model representing a cross section of a muscle fascicle. The framework enabled us to explore variability in the shape and arrangement of fibres, as well as to incorporate disease-related changes. We applied this method to reveal the trade-offs between mechanical properties and damage susceptibility in Duchenne muscular dystrophy (DMD). DMD is a fatal genetic disease caused by a lack of the transmembrane protein dystrophin, leading to muscle wasting and death due to cardiac or pulmonary complications. The most prevalent microstructural variations in DMD include: lack of transmembrane proteins, fibrosis, fatty infiltration and variation in fibre cross-sectional area. A parameter analysis of these variations and case study of DMD revealed that the nature of fibrosis and density of transmembrane proteins strongly affected the stiffness of the muscle and susceptibility to membrane damage.

Computational Modeling of Muscle Regeneration and Adaptation to Advance Muscle Tissue Regeneration Strategies

“…For example, simulation of cell-seeded scaffolds, such as the tissue-engineered muscle repair technology [Machingal et al, 2011;Corona et al, 2012], could provide valuable predictions on how various combinations of cells might influence the regenerative response of an engineered implant. Second, improving predictive power through linking the ABMs with micro- [Virgilio et al, 2015] and/or macromechanical [Fiorentino et al, 2014] computational models of muscle could provide mechanistic information about how biomechanical influences affect (and are affected by) biochemical influences (i.e. mechanisms of feedback between biochemical and biomechanical signals).…”

“…Computational and mathematical models are used to predict muscle force generation at multiple biological scales, including cross-bridge dynamics [Huxley, 1969;Eisenberg et al, 1980], sarcomere and half sarcomere dynamics [Razumova et al, 1999;Campbell, 2009], muscle fiber excitation/contraction coupling [Wakeling et al, 2012], multifiber and muscle tissue dynamics [Sharafi and Blemker, 2010;Virgilio et al, 2015], whole muscle dynamics [Fiorentino et al, 2014], as well as limb and body locomotion [Delp et al, 2007]. These models revealed important relationships between force production and skeletal muscle structure at different length scales.…”

Towards a unified approach in the modeling of fibrosis: A review with research perspectives

“…Further agent-based models where the role of fibrosis is taken into account can be found in [116,117]. The reader interested in a detailed description of other agent-based models for fibrosis-related diseases is referred to papers [118][119][120][121][122][123][124][125][126] and the references cited therein.…”

In Vivo Multiscale and Spatially-Dependent Biomechanics Reveals Differential Strain Transfer Hierarchy in Skeletal Muscle

“…Computational research has thoroughly investigated how continuum mechanics, molecular mechanics, or a combination of both can explain the multiscale force transfer and downstream chemical pathway activation in soft tissues (e.g. skeletal muscle 6–8 , cardiovascular system 9,10 and articular cartilage 11,12 ). Experimental paradigms have used isolated single cell mechanics, tissue equivalents, or in situ studies to probe multiscale strain transfer and mechanotransduction mechanisms in the ECM, cell, and nucleus 13,14 .…”