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Summary
As we develop methods for engineering biology, we are faced with the dilemma of the very large numbers of different molecular species and reactions in cells. Without a functional context, we don’t know which molecular biomarkers are the best indicators of biological fate.
Description
Cell-based therapies require efficient manufacturing processes, as well as assurance of the safety and the stability of cellular products. However, our ability to predict the response of cells to environmental conditions is far from perfect. To move beyond empirical approaches, we are using quantitative live cell imaging to help us develop a theoretical framework for predictive modeling of cell response.
Oct4, Sox2 and Nanog are promoter effector molecules that are thought to control pluripotency and differentiation. Their interdependent relationships are complex, as are their influences on other cellular molecules and pathways. Cell lines that allow us to follow each of these biomarkers in live cells will make it possible to map their dynamic interdependence, and their mutual dependence on determining pluripotency and differentiation. This information will allow better measurements, and better interpretation of measurements, that will inform biomanufacturing and product safety.
Since each cell in a population reflects a potential response to conditions, the aggregate population data can provide us with a measure of the dynamic behavior of cells as they transition from one state of gene expression to another. This work will lead to quantitative predictions of transitions between pluripotency and differentiation.