Chronic wounds are a major threat to public health and the economy and present as a comorbid complication with major diseases in humans. Although the proper healing of cutaneous wounds requires collective and coordinated behaviors of multiple cell types, the rate-determining step is the recruitment and function of dermal fibroblasts, which are directed to invade the wound by a gradient in the concentration of platelet-derived growth factor (PDGF). A great deal is known about the signal transduction pathways activated by PDGF receptors and other receptor tyrosine kinases;yet mechanistic insights about how those pathways are spatially organized to bias the dynamics of the actin cytoskeleton and the directionality of cell migration are still emerging. A still larger fundamental gap lies inthe integration of molecular, supramolecular, cellular, and tissue-level dynamics of wound healing, which span disparate time (seconds to weeks) and spatial (nm to cm) scales. To advance this field, novel approaches are needed to fuse experimental and observational scales that are relatively data-rich (signaling, cytoskeletal dynamics) and data-poor (in vivo dynamics). To that end, we propose to develop a predictive, multiscale model of the proliferative phase of wound healing, incorporating 1) receptor-mediated signal transduction (molecular scale), 2) self-assembly of contractile actomyosin structures (supramolecular scale), 3) morphodynamics and statistics of cell migration (cellular scale), and 4) collective cell behavior in vivo (tissue scal). Our partnership combines expertise in experimental cell biology and biophysical modeling, and model development will be guided by new, quantitative measurements at every scale of biological abstraction.
Chronic wounds in people suffering from diseases, such as diabetes and obesity, present a significant threat to public health in the United States. Proper healing of cutaneous wounds requires collective and coordinated cellular behavior that spans multiple length and time scales. To achieve a systems-level understanding of wound healing requires novel approaches to fuse observational scales that are relatively data-rich (signaling, cytoskeletal dynamics) with those that are data-poor (in vivo dynamics). To that end, we propose to develop a predictive, multiscale model of the proliferative phase of wound healing.
