Our live cell image program supports the advancement of iPSC technology in three ways:
1) Identification of process control measurements: A critical component to the translation of iPSCs into therapeutic applications is to design principles for predictably and reproducibly culturing cells and efficiently differentiating them into cell types of interest. Live cell imaging provides ‘high-resolution’ measurements in the sense that we collect time-dependent data from large numbers of individual cells. We then use this data to discover lower resolution measurements, such as the activity of a biomarker at a single point in time, that can serve as critical process control points during processing of pluripotent stem cells.
2) Interpreting biomarkers: Cells are stochastic and dynamic and may interconvert between states and the expression of biomarkers can change over time. The predictive power of a biomarker or a set of biomarkers the indicate the differentiated state of a cell can be evaluated by examining the history of that cell by tracking forward and backward in time through a time lapse image set.
3) Predictive modeling: We have shown that fluctuations in promoter activity can be used in combination with appropriate models to predict rates of state change in cell populations. Similar mathematical models that can inform bioprocessing decisions during scale-up will be critical to obtaining iPSC populations with a desired set of characteristics.
Over the past several years, we have developed tools for measuring parameters related to size, shape and intensity from single cells over time (Halter Cytometry 2011). We have also developed modeling tools for using the temporal information to model the stochastic and deterministic components of gene expression (Sisan PNAS 2012; Lund Phys Chem B 2014).
We are now applying these live cell imaging tools to the study of stem cell pluripotency and differentiation (Bhadriraju Stem Cell Research 2016). Induced pluripotent stem cell technologies are a powerful new tool for biomedical research and have the potential to revolutionize medicine.