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

Abstract

Skeletal muscle has an exceptional ability to regenerate and adapt following injury. Tissue engineering approaches (e.g. cell therapy, scaffolds, and pharmaceutics) aimed at enhancing or promoting muscle regeneration from severe injuries are a promising and active field of research. Computational models are beginning to advance the field by providing insight into regeneration mechanisms and therapies. In this paper, we summarize the contributions computational models have made to understanding muscle remodeling and the functional implications thereof. Next, we describe a new agent-based computational model of skeletal muscle inflammation and regeneration following acute muscle injury. Our computational model simulates the recruitment and cellular behaviors of key inflammatory cells (e.g. neutrophils and M1 and M2 macrophages) and their interactions with native muscle cells (muscle fibers, satellite stem cells, and fibroblasts) that result in the clearance of necrotic tissue and muscle fiber regeneration. We demonstrate the ability of the model to track key regeneration metrics during both unencumbered regeneration and in the case of impaired macrophage function. We also use the model to simulate regeneration enhancement when muscle is primed with inflammatory cells prior to injury, which is a putative therapeutic intervention that has not yet been investigated experimentally. Computational modeling of muscle regeneration, pursued in combination with experimental analyses, provides a quantitative framework for evaluating and predicting muscle regeneration and enables the rational design of therapeutic strategies for muscle recovery.

Multiscale Coupling of an Agent-Based Model of Tissue Fibrosis and a Logic-Based Model of Intracellular Signaling

“…For example, previous computational models have demonstrated that simultaneous targeting of multiple cells types rather than fibroblasts alone can enhance the efficacy of therapies for pulmonary fibrosis (Warsinske et al, 2016). Inflammatory cells, including macrophages and neutrophils, will be incorporated into a model of post-MI wound healing as the primary source and modulators of inflammatory cytokines and TGFβ input, as has been demonstrated previously in simulations of skeletal muscle and lung fibrosis (Martin et al, 2016;Warsinske et al, 2016;Virgilio et al, 2018). This will add another layer of complexity to the spatial heterogeneity of the coupled model by representing cytokine production from individual cells, diffusion of soluble cytokines and growth factors, and migration that is driven by chemokine gradients.…”

Applying Optimization Algorithms to Tuberculosis Antibiotic Treatment Regimens

“…Systems biology has been used to study a wide array of topics 52 including systems pharmacology, 4,10,20 vascular and muscle growth, 34 or cancer development and therapy. 7,14,53 Computational modeling and systems biology approaches can help integrate large sets of data and provide additional biological insights, e.g.…”

Agent-based model illustrates the role of the microenvironment in regeneration in healthy and mdx skeletal muscle

“…Inflammatory cell ordinary differential equation. The inflammatory cell dynamics were defined based on previous work by Martin et al (49,50). Our goal was to reduce the computational cost of the ABM but still retain the dynamic behaviors of the inflammatory cells that were previously established.…”