Self-organized patterning by diffusible factors: roles of a community effect

Kirill Batmanov, Celine Kuttler, Cédric Lhoussaine, Yasushi Saka

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
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Abstract

For decades, scientists have sought to elucidate self-organized patterning during develop- ment 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 nowthought 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 induc- tion 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 expres- sion pattern with a well-demarcated boundary appears in response to a transient morphogen gradi- ent. Surprisingly, even when the morphogen distribution eventually becomes uniform, the system can maintain the pattern. The regulatory network thus confers memory of morphogen dynamics.
Original languageEnglish
Pages (from-to)419-461
Number of pages44
JournalFundamenta Informaticae
Volume118
Issue number4
DOIs
Publication statusPublished - 2012

Bibliographical note

Acknowledgments.
We wish to thank Ekkehardt Ullner, Alban Edouard, Mathias John, Elahe Radmaneshfar and Cristian Versari for discussions, and Joachim Niehren, Marco Thiel, Ian Stansfield and Stefan Hoppler for critically reading the manuscript.

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