Modeling of Emergent Patterning within Pluripotent Colonies

Elena S. Dimitrova, PhD, Melissa L. Kemp, PhD, Daniel A. Cruz, PhD, Eunbi Park, Jack Toppen

The differentiation of stem cell colonies into specified tissue types is possible through local and long-distance intercellular communication; however, it is unclear which local mechanisms take priority in context-specific situations as the fates of cell colonies are established. In this project, we consider human induced pluripotent stem cells (hiPSCs) whose therapeutic potential arises from their ability to differentiate into all germ layers. Prior work in the literature suggests that both cell-autonomous and non-autonomous (e.g. positional) mechanisms determine cell fate during the differentiation of hiSPCs, producing patterns and other system-level features in the process. Informed by experimental data, we have focused our work on three interrelated endeavors: i) the development of a general-use, computational pipeline to quantitatively examine the multicellular organization and pattern formation of hiPSC colonies using topological data analysis; ii) the development of an agent-based model (ABM) of early hiPSC differentiation, and iii) the generalization of a mathematical framework which formalizes ABMs for the purpose of estimating long-term behavior (e.g. changes in agent population densities over time) of biologically-inspired ABMs without simulations.



D.A. Cruz, M.L Kemp. Hybrid computational modeling methods for systems biology. Progress in Biomedical Engineering 4 (2021) 012002. DOI: 10.1088/2516-1091/ac2cdf

D.A. Cruz, J. Toppen, E. Park, M.L. Kemp, E.S. Dimitrova. Estimating the long-term behavior of biologically inspired agent-based models. In preparation (2023); preprint:

I. Hartsock, E. Park, J. Toppen, E.S. Dimitrova, M.L. Kemp, P. Bubenik, D.A. Cruz. Topological data analysis of pattern formation of human induced pluripotent stem cell colonies. In preparation (2023).

E. Park, D.A. Cruz, J. Toppen, E.S. Dimitrova, M.L. Kemp. Extraction of transcriptional network within human induced pluripotent colonies via Boolean logic. In preparation (2023).


National Science Foundation DMS1764406 and Simons Foundation/SFARI 594594 (Joint grant for the NSF-Simons Southeast Center for Mathematics and Biology)