Novel Methods for Interrogating Cryptic Heterogeneity in Pluripotent Stem Cells

Human embryonic stem cells display several features of heterogeneity in culture. This heterogeneity is poorly understood and may impair differentiation protocol efficiency. There is increasing evidence that stem cell heterogeneity is dynamic and affects lineage fate decisions whilst cells are still pluripotent. The aim of this project was to develop new approaches for understanding the heterogeneity of cells within the pluripotent stem cell compartment that influences stem cell fate decisions. Understanding the rules governing stem cell heterogeneity would open up opportunities to manipulate these features for the improved application of differentiation protocols or within regular cell culture maintenance.

Two novel methods for the interrogation of pluripotent stem cell heterogeneity have been developed in this thesis. The first approach examines pluripotent stem cell dynamics by modelling the population fluctuations of the sensitive pluripotency marker SSEA3 of a pluripotent Embryonal Carcinoma (EC) cell line, NTera2. The model generated explained the heterogeneity dynamics of SSEA3 within NTera2 and in a predictive manner that also revealed candidate substate populations.

The second approach developed was the application of Raman spectroscopy for the non-invasive assessment of heterogeneity within and between stem cell populations according to biochemical signatures. These studies showed that a hyperspectral, grid based, approach proved sensitive for examination of cell biochemistry and furthermore, this approach was used to address biological questions. Raman Spectroscopy proved sensitive enough to notice differences between cell lines, between differentiated and undifferentiated cells, between intracellular compartments, and could discriminate between different pluripotent cells associated with differing lineage biases.

This work therefore represents a development in both our understanding of pluripotent stem cell dynamics and the potential for using both modelling and Raman spectroscopy to analyse this phenomenon.