Spatial pattern dynamics of 3D stem cell loss of pluripotency via rules-based computational modeling.
Spatial pattern dynamics of 3D stem cell loss of pluripotency via rules-based computational modeling.
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DOI：
10.1371/journal.pcbi.1002952
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发表时间：
2013
影响因子：
4.3
通讯作者：
Kemp ML
中科院分区：
文献类型：
--
作者：
White DE;Kinney MA;McDevitt TC;Kemp ML
Pluripotent embryonic stem cells (ESCs) have the unique ability to differentiate into cells from all germ lineages, making them a potentially robust cell source for regenerative medicine therapies, but difficulties in predicting and controlling ESC differentiation currently limit the development of therapies and applications from such cells. A common approach to induce the differentiation of ESCs in vitro is via the formation of multicellular aggregates known as embryoid bodies (EBs), yet cell fate specification within EBs is generally considered an ill-defined and poorly controlled process. Thus, the objective of this study was to use rules-based cellular modeling to provide insight into which processes influence initial cell fate transitions in 3-dimensional microenvironments. Mouse embryonic stem cells (D3 cell line) were differentiated to examine the temporal and spatial patterns associated with loss of pluripotency as measured through Oct4 expression. Global properties of the multicellular aggregates were accurately recapitulated by a physics-based aggregation simulation when compared to experimentally measured physical parameters of EBs. Oct4 expression patterns were analyzed by confocal microscopy over time and compared to simulated trajectories of EB patterns. The simulations demonstrated that loss of Oct4 can be modeled as a binary process, and that associated patterns can be explained by a set of simple rules that combine baseline stochasticity with intercellular communication. Competing influences between Oct4+ and Oct4− neighbors result in the observed patterns of pluripotency loss within EBs, establishing the utility of rules-based modeling for hypothesis generation of underlying ESC differentiation processes. Importantly, the results indicate that the rules dominate the emergence of patterns independent of EB structure, size, or cell division. In combination with strategies to engineer cellular microenvironments, this type of modeling approach is a powerful tool to predict stem cell behavior under a number of culture conditions that emulate characteristics of 3D stem cell niches. Pluripotent embryonic stem cells can differentiate into all cell types making up the adult body; however, this process occurs in a complex three dimensional environment with many different parameters present that are capable of influencing cell fate decisions. A model that can accurately predict the strengths of factors influencing cell fate would allow examination of spatial and temporal patterns of cell phenotype. For this study, we focused on the earliest fate transition that occurs in 3D clusters of embryonic stem cells by monitoring the presence of a transcription factor (Oct4) associated with stem cell pluripotency. After experimentally classifying patterns that arise en route to a fully differentiated aggregate in vitro, we constructed a computational model to deduce how stem cells integrate cues from their surrounding environment to give rise spatial patterns. We used a rules-based modeling approach in which information exchanged by cells with their nearest neighbors regulated cell fate decisions. This parsimonious model captured the spatial dynamics of early cell lineage commitment in a 3D multicellular structure. In combination with strategies to modulate cellular environments, our model provides a flexible tool for elucidating the extra- and intercellular interactions regulating spatially organized differentiation of stem cells in 3D.
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