Self-organized Patterning by Diffusible Factors: Roles of a Community Effect

Abstract

For decades, scientists have sought to elucidate self-organized patterning during development of higher organisms. It has been shown that cell interaction plays a key role in this process. One example is the community effect, an interaction among undifferentiated cells. The community effect allows cell population to forge a common identity, that is, coordinated and sustained tissue-specific gene expression. The community effect was originally observed in muscle differentiation in Xenopus embryos, and is now thought to be a widespread phenomenon. From a modelling point of view, the community effect is the existence of a threshold size of cell populations, above which the probability of tissue-specific gene expression for a sustained period increases significantly. Below this threshold size, the cell population fails to maintain tissue-specific gene expression after the initial induction. In this work, we examine the dynamics of a community effect in space and investigate its roles in two other processes of self-organized patterning by diffusible factors: Turing's reaction-diffusion system and embryonic induction by morphogens. Our major results are the following. First, we show that, starting from a one-dimensional space model with the simplest possible feedback loop, a community effect spreads in an unlimited manner in space. Second, this unrestricted expansion of a community effect can be avoided by additional negative feedback. In Turing's reaction-diffusion system with a built-in community effect, if induction is localized, sustained activation also remains localized. Third, when a simple cross-repression gene circuitry is combined with a community effect loop, the system self-organizes. A gene expression pattern with a well-demarcated boundary appears in response to a transient morphogen gradient. Surprisingly, even when the morphogen distribution eventually becomes uniform, the system can maintain the pattern. The regulatory network thus confers memory of morphogen dynamics.