EP
E. Pavinato Olimpio
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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.
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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.
Living systems, particularly multicellular systems, often seem hopelessly complex. But recent studies have suggested that, beneath this complexity, there may be unifying quantitative principles that are only now starting to unravel. All cells interact with their environments and with other cells. Communication among cells is a primary means for cells to interact with each other. The complexity of these multicellular systems, due to the large numbers of cells and the diversity of intracellular and intercellular interactions, makes understanding multicellular systems a daunting task. To overcome this challenge, we will likely need judicious simplifications and conceptual frameworks, which can reveal design principles that are shared among diverse multicellular systems. Here we review some recent progress toward developing such frameworks.
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Living systems, particularly multicellular systems, often seem hopelessly complex. But recent studies have suggested that, beneath this complexity, there may be unifying quantitative principles that are only now starting to unravel. All cells interact with their environments and with other cells. Communication among cells is a primary means for cells to interact with each other. The complexity of these multicellular systems, due to the large numbers of cells and the diversity of intracellular and intercellular interactions, makes understanding multicellular systems a daunting task. To overcome this challenge, we will likely need judicious simplifications and conceptual frameworks, which can reveal design principles that are shared among diverse multicellular systems. Here we review some recent progress toward developing such frameworks.