Morphogene adsorption as a Turing instability regulator: Theoretical analysis and possible applications in multicellular embryonic systems

PLoS One. 2017 Feb 7;12(2):e0171212. doi: 10.1371/journal.pone.0171212. eCollection 2017.


The Turing instability in the reaction-diffusion system is a widely recognized mechanism of the morphogen gradient self-organization during the embryonic development. One of the essential conditions for such self-organization is sharp difference in the diffusion rates of the reacting substances (morphogens). In classical models this condition is satisfied only for significantly different values of diffusion coefficients which cannot hold for morphogens of similar molecular size. One of the most realistic explanations of the difference in diffusion rate is the difference between adsorption of morphogens to the extracellular matrix (ECM). Basing on this assumption we develop a novel mathematical model and demonstrate its effectiveness in describing several well-known examples of biological patterning. Our model consisting of three reaction-diffusion equations has the Turing-type instability and includes two elements with equal diffusivity and immobile binding sites as the third reaction substance. The model is an extension of the classical Gierer-Meinhardt two-components model and can be reduced to it under certain conditions. Incorporation of ECM in the model system allows us to validate the model for available experimental parameters. According to our model introduction of binding sites gradient, which is frequently observed in embryonic tissues, allows one to generate more types of different spatial patterns than can be obtained with two-components models. Thus, besides providing an essential condition for the Turing instability for the system of morphogen with close values of the diffusion coefficients, the morphogen adsorption on ECM may be important as a factor that increases the variability of self-organizing structures.

MeSH terms

  • Adsorption*
  • Algorithms
  • Animals
  • Computer Simulation
  • Diffusion*
  • Embryo, Nonmammalian / metabolism
  • Embryonic Development*
  • Models, Biological
  • Models, Theoretical*

Grant support

This work was supported by the Russian Science Foundation (Grant: 14-14-00557, to AGZ. Particularly, the work on computational scheme was supported the Russian Foundation for Basic Research (Grant: 14-01-00196, to MBK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.