Coupling Experimental and Multi-Scale Modeling Approaches to Elucidate Mechanisms of Muscle Regeneration: The Role of Estrogen and Microenvironmental Dynamics 131 views

Skeletal muscle regeneration is a crucial process for maintaining daily functionality, influenced by a variety of muscle injury types that range from minor, self-healing eccentric contractions to severe injuries necessitating strategic intervention. The complex microenvironment of muscle recovery involves numerous biochemical interactions and cellular behaviors that are both temporally and spatially dependent. Notably, there are sex differences in muscle regeneration, with estrogen playing a significant role in driving many cellular processes. However, the sensitivity of key regenerative cell types to estrogen fluctuations is often overlooked when treating muscle injuries. This dissertation explores how the tissue microenvironment, estrogen levels, and injury type impact the muscle regeneration cascade and recovery outcomes. An agent-based model (ABM) of muscle regeneration was developed which focused on spatial cellular and cytokine dynamics alongside microvascular adaptations. The ABM identified that combined cytokine delivery could enhance regeneration outcomes more effectively than individual cytokine delivery. Subsequently, the model was extended to incorporate estrogen-driven alterations in cellular behaviors, using literature data and conducting in vivo experiments to fill gaps. This combined approach elucidated threshold-dependent estrogen mechanisms in satellite stem cell (SSC) and inflammatory cell behaviors. Model perturbations revealed that both the temporal nature and recovery outcomes vary in treatment response based on E2 levels. The model was further applied to study the modulation of cellular mechanisms by different injury types, simulating various injuries to help explain the variability in recovery observed across different studies. The ABM elucidated which cellular behaviors are most critical for fiber recovery, and a random forest regression model was developed to further investigate how specific regeneration metrics at various time points can predict recovery outcomes. Ultimately, this work provides new insights into cellular interactions and microenvironmental changes influenced by estrogen levels and injury types. It underscores the importance of considering estrogen levels in injury treatment across different life stages. Additionally, the model serves as a valuable tool to explore the diverse cellular responses and regeneration outcomes resulting from varying injuries and estrogen levels. Future model developments could facilitate in silico treatment optimization, accounting for cyclic estrogen levels and incorporating broader sex differences.

PHD (Doctor of Philosophy)

Skeletal muscle regeneration; Estrogen; Sex differences; Agent-based model; Cytokine dynamics; Treatment optimization; Muscle injury types

English

2024-08-26