The development of therapies and other products based on pluripotent stem cells requires control of the pluripotent and differentiated states of cells in culture. Pluripotent cells need to be expanded in culture without differentiation, and when appropriate, cells need to be differentiated into appropriate lineages. The efficiency of expansion and the completeness of differentiation is important to both efficient manufacturing and to product safety. Time-lapse microscopy of living cells allows the quantification of changes in dynamic activity of individual cells over time. We have shown that such data can provide information about fluctuations in promoter activity and can be used to predict rates of state change in cell populations. Applying these techniques to induced pluripotent stem cell (iPSC) colonies will provide a better understanding of cellular mechanics and efficiency of differentiation, and will allow systematic quantitative assessment of how conditions such as extracellular matrix and other agents can influence differentiation. Research challenges could include creating iPSC lines with reporter constructs, designing live cell imaging experiments to assess cell response, and developing quantitative image analysis methods.

References

Sisan D.R., et al. (2012) Predicting rates of cell state change due to stochastic fluctuations using a data-driven landscape model. PNAS 109, 19262-19267

Bhadriraju K, et al. (2016) Large-scale time-lapse microscopy of Oct4 expression in human embryonic stem cell colonies. Stem Cell Research (17): 122-129

Halter et al. (2011) Cell cycle dependent TN-C promoter activity determined by live cell imaging.  Cytometry Part A. 3A: 192-202. 

key words

Quantitative biology; Stem cell; Pluripotency; Differentiation; Live cell microscopy; Image analysis; Biological variation; Predictive models;

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants