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Information content and optimization of self-organized developmental systems.

David B Brückner1, Gašper Tkačik1

  • 1Institute of Science and Technology Austria, AT-3400 Klosterneuburg, Austria.

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This study introduces an information-theoretic measure to quantify how developmental systems reliably organize cell fates. The framework helps classify self-organizing biological systems using a common information language.

Keywords:
developmentinformation theoryself-organizationsignaling networks

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Area of Science:

  • Developmental biology
  • Systems biology
  • Information theory

Background:

  • Biological systems self-organize spatial patterns of distinct cell fates for proper function.
  • Reproducibility in pattern formation requires controlling intrinsic and extrinsic fluctuations.
  • A principled framework is lacking to quantify the performance of stochastic self-organizing systems.

Purpose of the Study:

  • Introduce an information-theoretic measure to quantify self-organized fate specification in embryonic development.
  • Provide a normative theory for developmental circuits by optimizing this measure.
  • Develop a common information-theoretic language for classifying developmental systems.

Main Methods:

  • Developed an information-theoretic measure for self-organized fate specification.
  • Decomposed information content into positional and correlational contributions.
  • Applied the measure to models of lateral inhibition, cell type proportioning, and reaction-diffusion systems.

Main Results:

  • The proposed measure quantifies the total information content of cell fate patterns.
  • The measure successfully decomposes information into positional and correlational components.
  • Optimization of the measure provides insights into the performance of developmental circuits.

Conclusions:

  • The information-theoretic framework offers a quantitative approach to understanding stochastic self-organization in development.
  • This approach facilitates the classification of diverse developmental systems.
  • It provides a unified language to organize signaling processes in developmental biology.