Correspondence between Signaling and Developmental Patterns by Competing Cells: A Computational Perspective

Abstract

Arrangement of variant phenotypes in ordered spatial assemblies during division of stem cells is essential for the self-organization of cell tissues. The cellular patterns of phenotypes competing for space and resources against one another are mostly driven by secreted diffusible chemical signaling clues. This complex process is carried out within a chronological framework of interplaying intracellular and intercellular events. This includes receiving external stimulants-whether secreted by other individuals or provided by the environment-interpreting these environmental signals and incorporating the information to designate cell fate. An enhanced understanding of the building blocks of this framework would be of help to set the scene for promising regenerative therapies. In this study, by proposing a designative computational map, we show that there is a correspondence between signaling and developmental patterns that are produced by competing cells. That is, the model provides an appropriate prediction for the final structure of the differentiated cells in a competitive environment. Besides, given that the final state of the cellular organization is known, the corresponding regressive signaling patterns are partly predictable following the proposed map. Author SummaryMulticellular organisms are made of repeated divisions of single cells and aggregation of their offspring together. However, the aggregated formations are not colony-like accumulations of piled-up cells. Instead, they are "emergent" spatiotemporal structures of developmentally differentiated cell types. The functionally integrated structures remain relatively constant throughout the life of the organisms, despite the death and production of new cells. The question is: How differentiated cells are capable of making variant patterns without any predefined templates? It is shown that with a variety of differentiated cell types, emergence of complex patterns is feasible through the interplay of intercellular interactions and intracellular decision-making switches. Such conceptual understanding has the potential to generate a multitude of novel and precisely controlled cellular behaviors.