Tissue engineering combines cells, soluble stimuli (e.g., growth factors), and/or a matrix (biomaterial scaffold) to guide regeneration. This paradigm has proven to be powerful and has transformed our understanding of the cell and its interactions with its environment. Yet progress in organ regeneration has fallen far short of expectation, with current scaffolds failing to provide cells with the c
ues necessary to initiate regeneration. A seemingly bewildering array of environmental stimuli are known to influence cell behavior, including matrix stiffness, induced cell shape, cell-cell interactions, nano- and micro-scale matrix topography, and the concentration, identity, and time-dependent presentation of biochemical signals. When this external complexity is overlaid on the truly awesome complexity of the cell and the way it translates signals, being able to rationally design scaffold environments to guide cell behavior can seem like a pipe-dream. However, in the absence of rational design, we are left with trial-and-error evaluation of scaffolds, with rapid advances in tissue engineering limited to serendipity or singular flashes of genius. But, what if the aspects of cell behavior critical to the regeneration of a particular organ could be captured more simply, and the seemingly overwhelming complexity of the cell could be pared down to a fundamental core? The overarching hypothesis governing my work is that there is a subset of external and internal signals which dominate cellular regeneration of a given tissue and that discovery of these stimuli, and the key intracellular mechanisms through which they actuate cell behavior, will allow us to predict, and therefore dictate, cell behavior. In essence, my work is attempting to do for tissue engineering what Newton did for the physics – generate a consistent framework of primary effects governing the behavior of cells in specific contexts (in Newton’s case, the motion of objects with speeds less than that of light), bringing what now appears unpredictable within our control. In asking these questions, we combine cells with a highly tunable scaffold environment, which allows us to simultaneously apply what are believed to be “mixed” messages to the cells, e.g., one signal should, based on current understanding, tell the cells to “go”, one should tell the cells to “stop”, and another should tell the cells to “reverse”. We then probe the “direction” the cells chose in face of these conflicting signals to gain key insight into the relative effects of various stimuli. Our work will one day allow us to identify the minimal information that needs to be encoded into the cellular environment to coax cells to regenerate a particular organ, transforming regenerative medicine.
