Heterogeneous structure of stem cells dynamics: statistical models and quantitative predictions.
Understanding stem cell (SC) population dynamics is essential for developing models that can be used in basic science and medicine, to aid in predicting cells fate. These models can be used as tools e.g. in studying patho-physiological events at the cellular and tissue level, predicting (mal)functions along the developmental course, and personalized regenerative medicine. Using time-lapsed imaging and statistical tools, we show that the dynamics of SC populations involve a heterogeneous structure consisting of multiple sub-population behaviors. Using non-Gaussian statistical approaches, we identify the co-existence of fast and slow dividing subpopulations, and quiescent cells, in stem cells from three species. The mathematical analysis also shows that, instead of developing independently, SCs exhibit a time-dependent fractal behavior as they interact with each other through molecular and tactile signals. These findings suggest that more sophisticated models of SC dynamics should view SC populations as a collective and avoid the simplifying homogeneity assumption by accounting for the presence of more than one dividing sub-population, and their multi-fractal characteristics.
1] Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089-2560, USA [2].
Paul
P
Bogdan
1] CellStock, Pittsburgh, PA 15237, USA [2] McGowan Institute of Regenerative Medicine of UPMC and Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA [3].
Bridget M
BM
Deasy
1] Institute for Complex Engineered Systems, Carnegie Mellon University, Pittsburgh, PA15213, USA [2] Stem Cell Research Center (SCRC), University of Pittsburgh, Pittsburgh, PA 15219, USA [3].
Burhan
B
Gharaibeh
McGowan Institute of Regenerative Medicine of UPMC and Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Timo
T
Roehrs
Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Radu
R
Marculescu
D000818:Animals; D002455:Cell Division; D049109:Cell Proliferation; D006801:Humans; D051379:Mice; D008954:Models, Biological; D015233:Models, Statistical; D051381:Rats; D013234:Stem Cells / Q000166:cytology* / Q000502:physiology*; D059008:Time-Lapse Imaging