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Fibroblasts play an important role in tissue growth and wound healing by generating contractile force or tension within collagen network. As a result, fibroblast-populated collagen lattices have become a common tissue model for studying the biology and biomechanics of wound healing. However, it is challenging to estimate the amplitudes of the cellular tension in the engineered tissue in normal and wound healing conditions. In this study, we engineered the tissue that is made up mainly of human dermal fibroblasts and type I collagen. We used the Optical Coherence Tomography to image and quantify the development and reorganization of the collagen network driven by fibroblast cells. We also probed the mechanical tension in the tissue by introducing a circular dissection on the tissue and quantifying the ensuing wound expansion. Finite element models were created to simulate the wound expansion and estimate the magnitude of the associated tension. Quantifying how mechanical forces regulate the tissue generation will help us understand the biophysical mechanisms behind wound healing.

biochemistry is computationally predictable. Partial Order Optimum Likelihood (POOL) is a machine learning method developed by us to predict residues important for function, using the 3D structure of the query protein. The input features to POOL are based on computed electrostatic and chemical properties from THEMATICS. These input features are effectively measures of the strength of coupling between protonation events. POOL is used to predict the residues important for catalysis and ligand binding. Typical predicted catalytic sites are characterized by networks of strongly coupled protonation states; these networks impart the necessary electrostatic and proton-transfer properties to the active residues in the first layer around the reacting substrate molecule(s). Most often these networks include first-, second-, and sometimes third-layer residues. POOL-predicted, multi-layer active sites with significant participation by distal residues have been verified experimentally by single-point sitedirected mutagenesis and kinetics assays for multiple examples, including human phosphoglucose isomerase, human PARK2 (an E3 ubiquitin ligase), and E. coli ornithine transcarbamoylase. Mechanisms for the effects of diseaseassociated mutations, and implications for personalized medicine, are discussed.

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Elastin fibers assemble in the extracellular matrix from the precursor protein tropoelastin and provide the flexibility and spontaneous recoil required for arterial function. Unlike many proteins, a structure-function mechanism for elastin has been elusive. We have performed detailed NMR relaxation studies of the dynamics of the minielastin 24x′ in solution and of purified bovine elastin fibers in the presence and absence of mechanical stress. The low sequence complexity of 24x′ enables us to determine dynamical timescales and degrees of local ordering with residue-specific resolution in the cross-link and hydrophobic modules using NMR relaxation. We find an extremely high degree of disorder, with order parameters for the entirety of the hydrophobic domains near zero, resembling that of simple chemical polymers and less than the order parameters that have been observed in other intrinsically disordered proteins. We find that backbone order parameters in natural, purified elastin fibers are comparable to those found in 24x′ in solution. The difference in dynamics, compared to 24x′, is that backbone correlation times are significantly slowed in purified elastin. Moreover, when elastin is mechanically stretched, the high chain disorder in purified elastin is retained - showing that any change in local ordering is below that detectable in our experiment. Combined with our previous finding of a 10-fold increase in the ordering of water when fully hydrated elastin fibers are stretched by 50%, these results support the hypothesis that stretch induced solvent ordering, i.e. the hydrophobic effect, is a key player in the elastic recoil of elastin.