Statistical Dynamics of Spatial-Order Formation by Communicating Cells

Journal Article (2018)
Author(s)

E. Pavinato Olimpio (TU Delft - OLD BN/Hyun Youk Lab, Kavli institute of nanoscience Delft)

Y. Dang (TU Delft - OLD BN/Hyun Youk Lab)

H.O. Youk (TU Delft - OLD BN/Hyun Youk Lab, TU Delft - BN/Bionanoscience)

Research Group
OLD BN/Hyun Youk Lab
Copyright
© 2018 E. Pavinato Olimpio, Y. Dang, H.O. Youk
DOI related publication
https://doi.org/10.1016/j.isci.2018.03.013
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 E. Pavinato Olimpio, Y. Dang, H.O. Youk
Related content
Research Group
OLD BN/Hyun Youk Lab
Issue number
2
Volume number
1
Pages (from-to)
27-40
Reuse Rights

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Abstract

Communicating cells can coordinate their gene expressions to form spatial patterns, generating order from disorder. Ubiquitous “secrete-and-sense cells” secrete and sense the same molecule to do so. Here we present a modeling framework—based on cellular automata and mimicking approaches of statistical mechanics—for understanding how secrete-and-sense cells with bistable gene expression, from disordered beginnings, can become spatially ordered by communicating through rapidly diffusing molecules. Classifying lattices of cells by two “macrostate” variables—“spatial index,” measuring degree of order, and average gene-expression level—reveals a conceptual picture: a group of cells behaves as a single particle, in an abstract space, that rolls down on an adhesive “pseudo-energy landscape” whose shape is determined by cell-cell communication and an intracellular gene-regulatory circuit. Particles rolling down the landscape represent cells becoming more spatially ordered. We show how to extend this framework to more complex forms of cellular communication.