Novel Aspects in Pattern Formation Arise from Coupling Turing Reaction–Diffusion and Chemotaxis

• Published in: Bulletin of mathematical biology Vol. 86; no. 1; p. 4
• Main Authors: Fraga Delfino Kunz, Camile, Gerisch, Alf, Glover, James, Headon, Denis, Painter, Kevin John, Matthäus, Franziska
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2024; Springer Nature B.V
• Subjects: Cell Biology; Chemotaxis; Coupling; Diffusion; Dynamic stability; Life Sciences; Mathematical and Computational Biology; Mathematical Concepts; Mathematical models; Mathematics; Mathematics and Statistics; Models, Biological; Models, Theoretical; Morphogenesis; Numerical analysis; Original; Original Article; Parameters; Pattern analysis; Pattern formation; Patterning; Regularity; Robustness (mathematics); Stability analysis; Morphogenesis; Biological development; Chemotaxis; Reaction–diffusion
• ISSN: 0092-8240; 1522-9602
• DOI: 10.1007/s11538-023-01225-5

Recent experimental studies on primary hair follicle formation and feather bud morphogenesis indicate a coupling between Turing-type diffusion driven instability and chemotactic patterning. Inspired by these findings we develop and analyse a mathematical model that couples chemotaxis to a reaction–diffusion system exhibiting diffusion–driven (Turing) instability. While both systems, reaction–diffusion systems and chemotaxis, can independently generate spatial patterns, we were interested in how the coupling impacts the stability of the system, parameter region for patterning, pattern geometry, as well as the dynamics of pattern formation. We conduct a classical linear stability analysis for different model structures, and confirm our results by numerical analysis of the system. Our results show that the coupling generally increases the robustness of the patterning process by enlarging the pattern region in the parameter space. Concerning time scale and pattern regularity, we find that an increase in the chemosensitivity can speed up the patterning process for parameters inside and outside of the Turing space, but generally reduces spatial regularity of the pattern. Interestingly, our analysis indicates that pattern formation can also occur when neither the Turing nor the chemotaxis system can independently generate pattern. On the other hand, for some parameter settings, the coupling of the two processes can extinguish the pattern formation, rather than reinforce it. These theoretical findings can be used to corroborate the biological findings on morphogenesis and guide future experimental studies. From a mathematical point of view, this work sheds a light on coupling classical pattern formation systems from the parameter space perspective.