Reaction-diffusion Dynamics and Biological Pattern Formation

2017 ◽  
Vol 6 (4) ◽  
pp. 547-564 ◽  
Author(s):  
Kishore Dutta
Keyword(s):  
Pattern Formation ◽  
Reaction Diffusion ◽  
Diffusion Dynamics ◽  
Biological Pattern Formation

scholarly journals Synchrony and pattern formation of coupled genetic oscillators on a chip of artificial cells

2017 ◽  
Vol 114 (44) ◽  
pp. 11609-11614 ◽  
Author(s):  
Alexandra M. Tayar ◽  
Eyal Karzbrun ◽  
Vincent Noireaux ◽  
Roy H. Bar-Ziv
Keyword(s):  
Pattern Formation ◽  
Large Scale ◽  
Reaction Diffusion ◽  
Biochemical Networks ◽  
Artificial Cells ◽  
Diffusion Dynamics ◽  
Oscillatory Reactions ◽  
Potential Applications ◽  
On Chip ◽  
Genetic Oscillators

Understanding how biochemical networks lead to large-scale nonequilibrium self-organization and pattern formation in life is a major challenge, with important implications for the design of programmable synthetic systems. Here, we assembled cell-free genetic oscillators in a spatially distributed system of on-chip DNA compartments as artificial cells, and measured reaction–diffusion dynamics at the single-cell level up to the multicell scale. Using a cell-free gene network we programmed molecular interactions that control the frequency of oscillations, population variability, and dynamical stability. We observed frequency entrainment, synchronized oscillatory reactions and pattern formation in space, as manifestation of collective behavior. The transition to synchrony occurs as the local coupling between compartments strengthens. Spatiotemporal oscillations are induced either by a concentration gradient of a diffusible signal, or by spontaneous symmetry breaking close to a transition from oscillatory to nonoscillatory dynamics. This work offers design principles for programmable biochemical reactions with potential applications to autonomous sensing, distributed computing, and biomedical diagnostics.

scholarly journals Pattern formation in reaction–diffusion system on membrane with mechanochemical feedback

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Naoki Tamemoto ◽  
Hiroshi Noguchi
Keyword(s):  
Pattern Formation ◽  
Plasma Membranes ◽  
Reaction Diffusion ◽  
Living Cells ◽  
Nonequilibrium Dynamics ◽  
Membrane Deformation ◽  
Brusselator Model ◽  
Diffusion Dynamics ◽  
Curved Membranes ◽  
Membrane Shape

Abstract Shapes of biological membranes are dynamically regulated in living cells. Although membrane shape deformation by proteins at thermal equilibrium has been extensively studied, nonequilibrium dynamics have been much less explored. Recently, chemical reaction propagation has been experimentally observed in plasma membranes. Thus, it is important to understand how the reaction–diffusion dynamics are modified on deformable curved membranes. Here, we investigated nonequilibrium pattern formation on vesicles induced by mechanochemical feedback between membrane deformation and chemical reactions, using dynamically triangulated membrane simulations combined with the Brusselator model. We found that membrane deformation changes stable patterns relative to those that occur on a non-deformable curved surface, as determined by linear stability analysis. We further found that budding and multi-spindle shapes are induced by Turing patterns, and we also observed the transition from oscillation patterns to stable spot patterns. Our results demonstrate the importance of mechanochemical feedback in pattern formation on deforming membranes.

scholarly journals Spatio-temporal Brusselator Model and Biological Pattern Formation

2021 ◽  
pp. 88-99
Author(s):  
Zakir Hossine ◽  
Oishi Khanam ◽  
Md. Mashih Ibn Yasin Adan ◽  
Md. Kamrujjaman
Keyword(s):  
Pattern Formation ◽  
Diffusion Model ◽  
Initial Conditions ◽  
Neumann Boundary ◽  
Reaction Diffusion ◽  
Two Dimensions ◽  
Brusselator Model ◽  
Reaction Diffusion Model ◽  
Biological Pattern Formation ◽  
Spatio Temporal

This paper explores a two-species non-homogeneous reaction-diffusion model for the study of pattern formation with the Brusselator model. We scrutinize the pattern formation with initial conditions and Neumann boundary conditions in a spatially heterogeneous environment. In the whole investigation, we assume the case for random diffusion strategy. The dynamics of model behaviors show that the nature of pattern formation with varying parameters and initial conditions thoroughly. The model also studies in the absence of diffusion terms. The theoretical and numerical observations explain pattern formation using the reaction-diffusion model in both one and two dimensions.

scholarly journals Non-linear Analysis of Models for Biological Pattern Formation: Application to Ocular Dominance Stripes

2021 ◽  
Author(s):  
Michael J Lyons
Keyword(s):  
Pattern Formation ◽  
Adiabatic Approximation ◽  
Striate Cortex ◽  
Ocular Dominance ◽  
Reaction Diffusion ◽  
Linear Analysis ◽  
Non Linear ◽  
Biological Pattern Formation ◽  
Model Equations ◽  
Linear Property

We present a technique for the analysis of pattern formation by a class of models for the formation of ocular dominance stripes in the striate cortex of some mammals. The method, which employs the adiabatic approximation to derive a set of ordinary differential equations for patterning modes, has been successfully applied to reaction-diffusion models for striped patterns. Models of ocular dominance stripes have been studied by computation, or by linearization of the model equations. These techniques do not provide a rationale for the origin of the stripes. We show here that stripe formation is a non-linear property of the models. Our analysis indicates that stripe selection is closely linked to a property in the dynamics of the models which arises from a symmetry between ipsilateral and contralateral synapses to the visual cortex of a given hemisphere.

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