Predictive Models of Cell Alignment and Scar Formation under Mechanical Loading

Following injury to many different tissues in the body – including heart, tendons and ligaments, spinal cord, and skin – the body builds scar tissue through a complex wound healing process. The structural and mechanical properties of the resultant scar are critical in determining the overall function of the repaired tissue, particularly for tissues that are under high mechanical load. In the case of healing after myocardial infarction in the heart, our lab has found that longitudinally reinforcing the damaged region can significantly improve cardiac output and pump function, suggesting that manipulating the healing process to generate longitudinally aligned collagen could represent a novel therapeutic approach. In tendons and ligaments, collagen in the scar tissue that forms following injury is generally less aligned and mechanically weaker than native tissue, again suggesting that controlling collagen alignment in healing scar could be an important therapeutic advance. Currently, the exact determinants of scar structure are not understood well enough to design protocols to achieve a desired outcome.

Fibroblasts are the primary drivers of collagen deposition and scar formation. These cells align in response to cues from their environment and synthesize, assemble, remodel, and cross-link collagen within the developing scar, mediating the development of scar mechanical properties. In both healthy and scar tissue, fibroblasts are typically found aligned with local collagen fibers, suggesting that fibroblast alignment and collagen organization are mechanistically related. While we know that the mechanical environment plays a key role in driving cellular behaviors and scar formation, a more complete understanding of how the mechanical environment influences cell and collagen alignment may enable us to develop better interventions for healing scar tissue. The overall goal of this dissertation was to develop predictive models of fibroblast alignment and scar formation during wound healing. The overall approach of this dissertation was to first experimentally test the effect of the mechanical environment on cell alignment across a broad range of mechanical conditions. We then used this data to develop a computational model of cell alignment and incorporated that validated cellular model into a multiscale computational framework to predict scar formation in the healing tendon.

Fibroblasts, endothelial cells, mesenchymal stem cells, and osteoblasts all orient perpendicular to an applied cyclic stretch when plated on stretchable elastic substrates, suggesting a common underlying mechanism. Yet many of these same cells orient parallel to stretch in vivo and in 3D culture, and a compelling explanation for the different orientation responses in 2D and 3D has remained elusive. Here, we employed a novel experimental system to conduct a series of experiments designed specifically to test the hypothesis that differences in strains transverse to the primary loading direction give rise to the different alignment patterns observed in 2D and 3D cyclic stretch experiments (“strain avoidance”). We found that in static or low-frequency stretch conditions, cell alignment in fibroblast-populated collagen gels correlated with the presence or absence of a restraining boundary condition, rather than with compaction strains. Cyclic stretch could induce perpendicular alignment in 3D culture, but only at frequencies an order of magnitude greater than reported to induce perpendicular alignment in 2D. We modified a published model of stress fiber dynamics and were able to reproduce our experimental findings across all conditions tested, as well as published data from 2D cyclic stretch experiments. These experimental and model results suggest a new explanation for the apparently contradictory alignment responses of cells subjected to cyclic stretch on 2D membranes and in 3D gels.

Next, we used this knowledge about cell alignment and applied it to make predictions about scar formation within the healing tendon. Mechanical stimulation of the healing tendon is thought to regulate scar anisotropy and strength and is relatively easy to modulate through physical therapy. However, in vivo studies of various loading protocols in animal models have produced mixed results. To integrate and better understand the available data, we developed a multiscale model of rat Achilles tendon healing that incorporates the effect of changes in the mechanical environment on fibroblast behavior, collagen deposition, and scar formation. We modified an OpenSim model of the rat right hindlimb to estimate physiologic strains in the lateral/medial gastrocnemius and soleus musculo-tendon units during loading and unloading conditions. We used the tendon strains as inputs to a thermodynamic model of stress fiber dynamics that predicts fibroblast alignment, and to determine local collagen synthesis rates according to a response curve derived from in vitro studies. We then used an agent-based model (ABM) of scar formation to integrate these cell-level responses and predict tissue-level collagen alignment and content. We compared our model predictions to experimental data from ten different studies. We found that a single set of cellular response curves can explain features of observed tendon healing across a wide array of reported experiments in rats – including the paradoxical finding that repairing transected tendon reverses the effect of loading on alignment – without fitting model parameters to any data from those experiments. The key to these successful predictions was simulating the specific loading and surgical protocols to predict tissue-level strains, which then guided cellular behaviors according to response curves based on in vitro experiments. Our model results provide a potential explanation for the highly variable responses to mechanical loading reported in the tendon healing literature and may be useful in guiding the design of future experiments and interventions.