title: Theoretical basis of the community effect in development.
abstract: BACKGROUND
  Genetically identical cells often show significant variation in gene expression profile and behaviour even in the same physiological condition. Notably, embryonic cells destined to the same tissue maintain a uniform transcriptional regulatory state and form a homogeneous cell group. One mechanism to keep the homogeneity within embryonic tissues is the so-called community effect in animal development. The community effect is an interaction among a group of many nearby precursor cells, and is necessary for them to maintain tissue-specific gene expression and differentiate in a coordinated manner. Although it has been shown that the cell-cell communication by a diffusible factor plays a crucial role, it is not immediately obvious why a community effect needs many cells.
  
  
  RESULTS
  In this work, we propose a model of the community effect in development, which consists in a linear gene cascade and cell-cell communication. We examined the properties of the model theoretically using a combination of stochastic and deterministic modelling methods. We have derived the analytical formula for the threshold size of a cell population that is necessary for a community effect, which is in good agreement with stochastic simulation results.
  
  
  CONCLUSIONS
  Our theoretical analysis indicates that a simple model with a linear gene cascade and cell-cell communication is sufficient to reproduce the community effect in development. The model explains why a community needs many cells. It suggests that the community's long-term behaviour is independent of the initial induction level, although the initiation of a community effect requires a sufficient amount of inducing signal. The mechanism of the community effect revealed by our theoretical analysis is analogous to that of quorum sensing in bacteria. The community effect may underlie the size control in animal development and also the genesis of autosomal dominant diseases including tumorigenesis.
authors.affiliation: Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK. y.saka@abdn.ac.uk
authors.forename: Yasushi
authors.initials: Y
authors.lastname: Saka
authors.forename: Cédric
authors.initials: C
authors.lastname: Lhoussaine
authors.forename: Celine
authors.initials: C
authors.lastname: Kuttler
authors.forename: Ekkehard
authors.initials: E
authors.lastname: Ullner
authors.forename: Marco
authors.initials: M
authors.lastname: Thiel
mesh_terms: D000818:Animals; D002450:Cell Communication; D003198:Computer Simulation; D004058:Diffusion; D051519:Fibroblast Growth Factor 4 / Q000378:metabolism; D020869:Gene Expression Profiling; D018507:Gene Expression Regulation, Developmental; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D013269:Stochastic Processes; D049490:Systems Biology; D014981:Xenopus
chemical_list: C496445:FGF4 protein, human; D051519:Fibroblast Growth Factor 4