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Patterning Bioactive Proteins or Peptides on Hydrogel Using Photochemistry for Biological Applications
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Beyond Turing: mechanochemical pattern formation in biological tissues.

Moritz Mercker1, Felix Brinkmann2,3, Anna Marciniak-Czochra2

  • 1Institute of Applied Mathematics, BioQuant and Interdisciplinary Center of Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany. mmercker_bioscience@gmx.de.

Biology Direct
|May 6, 2016
PubMed
Summary

Mechanochemical feedback loops, not just chemical morphogens, drive tissue self-organization during embryogenesis. This study reveals how mechanical cues like strain and stress can spontaneously generate complex biological patterns.

Keywords:
DevelopmentLong-range inhibitionMechanochemistryMechanotransductionMorphogensPattern formationReaction-diffusionTissue mechanicsTissue morphogenesis

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Area of Science:

  • Developmental Biology
  • Biophysics
  • Computational Biology

Background:

  • Embryogenesis involves self-organized chemical (morphogen) and mechanical patterning.
  • Turing's reaction-diffusion model, focusing on chemical interactions, has long been the paradigm for tissue patterning.
  • Emerging evidence highlights the significant role of tissue mechanics alongside morphogens.

Purpose of the Study:

  • To investigate mechanochemical processes where morphogen dynamics and tissue mechanics are coupled.
  • To explore the influence of mechanical cues (strain, stress, compression) on pattern formation.
  • To demonstrate that simple mechanochemical interactions can generate de novo patterns.

Main Methods:

  • Combined continuous finite strain with discrete cellular tissue models.
  • Developed and numerically investigated coupled mechanochemical feedback loops.
  • Modeled feedback loops involving strain, stress, and compression.

Main Results:

  • Identified three distinct feedback loops driven by mechanical cues (strain, stress, compression).
  • Demonstrated spontaneous and robust mechanochemical pattern formation.
  • Showed that simple mechanochemical interactions suffice for de novo pattern generation, contrasting with Turing-type models.

Conclusions:

  • Mechanochemical processes are strong candidates for controlling various embryogenesis stages.
  • The findings motivate further experimental research into living tissue mechanisms.
  • Predictive in silico experiments are provided to guide future investigations.