Decoding the Variance in Intracellular Organization in Human Stem Cells

The Allen Institute for Cell Science is generating a state space of stem cell signatures. The goal is to understand cell organization, identify cell states, and elucidate how cells transition from state to state. We are doing this by conjoining high replicate 3D live cell imaging of cell lines gene-edited with GFP tagged proteins, single cell RNAseq, computational analyses, and visualization. Here we are investigating biological sources of cellular variation to identify the basis functions of a dimensionally-reduced, interpretable parameter space that represents integrated intracellular organization. We used the Allen Cell Structure Segmenter to create accurate 3D segmentations of cells and nuclei in a large, >100k single cell dataset and in multi- hour 3D timelapse movies. We fit extracted cell/nuclear shapes using spherical harmonic functions perform a PCA analysis. We analyzed the contributions of the first 5 primary axes of variation to describing this dimensionally-reduced cell and nuclear shape space. Each shape mode represented a different source of biological variation in hiPS cell colonies and occurred on a distinct timescale. The first two shape modes represented cell growth during the cell cycle and cell colony packing density occurring over several days. The next three axes of variation represent distinct aspects of cell/nuclear shape, such as how elongated these are in the XY plane, which occur over minute timescales due to constant interactions between neighboring cells. We are now applying these analyses to develop biophysical models of cell/nuclear shape and colony dynamics. This general analysis framework will be extended to each of the key intracellular structures in an integrative fashion.