The Turing mechanism for the production of a broken spatial symmetry in an initially homogeneous system of reacting and diffusing substances has attracted much interest as a potential model for certain aspects of morphogenesis such as pre-patterning in the embryo, and has also served as a model for self-organization in more generic systems. The two features necessary for the formation of Turing patterns are short-range autocatalysis and long-range inhibition which usually only occur when the diffusion rate of the inhibitor is significantly greater than that of the activator. This observation has sometimes been used to cast doubt on applicability of the Turing mechanism to cellular patterning since many messenger molecules that diffuse between cells do so at more-or-less similar rates. Here we show that stationary, symmetry-breaking Turing patterns can form in physiologically realistic systems even when the extracellular diffusion coefficients are equal; the kinetic properties of the 'receiver' and 'transmitter' proteins responsible for signal transduction will be primary factors governing this process.

Orientador: Marcus Aloizio Martinez de Aguiar / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-20T00:25:10Z (GMT). No. of bitstreams: 1 Fernandes_LucasDias_M.pdf: 4124571 bytes, checksum: c9eaf6c1371f1023d813ae1f45f3aa27 (MD5) Previous issue date: 2012 / Resumo: Sistemas de reação-difusão podem apresentar, sob certas condições, formação de padrões espaciais heterogêneos estacionários. Chamados padrões de Turing (ou instabilidades de Turing) devido ao trabalho de Alan Turing, sua formulação matemática é importante para o estudo da formação de padrões em geral e desempenha papel central em muitos campos da biologia, tais como ecologia e morfogênese. No presente estudo, focamos no papel exercido pelos padrões de Turing na descrição de distribuições de abundância de espécies de predadores e presas que habitam ambientes fragmentados com estrutura de rede livre de escala, onde as conexões indicam caminhos de dispersão dessas espécies. Para estudar formação de padrões em cadeias tróficas maiores, nós estendemos o modelo de presa-predador original, proposto por Nakao e Mikhailov (Nature Physics, 2010), incluindo pares de presa-predador adicionais. Mostramos que esses sistemas dinâmicos com mais de dois graus de liberdade apresentam não apenas padrões de Turing, mas também transições entre regimes caóticos, sincronizados e estacionários, dependendo dos parâmetros do sistema. Para o caso dos padrões estacionários em uma cadeia trofica com 6 espécies, identificamos distribuições não triviais das presas nos sítios da rede, dependendo da força de acoplamento entre os pares presa-predador, o que sugere que efeitos de competição aparente são importantes nos padrões observados. Nossos resultados sugerem que diferenças nas distribuições de abundância entre fragmentos podem ser, pelo menos em parte, devidos a padrões de Turing auto-organizados, e não necessariamente a heterogeneidades ambientais intrínsecas / Abstract: Reaction-diffusion systems may lead, under certain conditions, to the formation of steady state heterogeneous spatial patterns. Named Turing patterns (or Turing instabilities) after Alan Turing's work, their mathematical formulation is important for the study of pattern formation in general and play central roles in many elds of biology, such as ecology and morphogenesis. In the present study, we focus on the role of Turing patterns in describing the abundance distribution of species distributed in patches in a scale free network structure, connected by diffusion. In order to study pattern formation in larger trophic food webs, we have extended the original prey-predator model proposed by Nakao and Mikhailov (Nature Physics, 2010) by including additional prey-predator pairs. We observed not only Turing patterns, but also transitions between chaotic, synchronized and stationary regimes, depending on the system parameters. In the case of stationary patterns in trophic webs with 6 species, we identified non trivial prey distributions in the networks nodes, depending on the coupling strength between prey-predator pairs, suggesting that effects of apparent competition are important in the observed patterns. Our results suggest that differences in abundance distribution among patches may be, at least in part, due to self organized Turing patterns, and not necessarily to intrinsic environmental heterogeneities / Mestrado / Física / Mestre em Física

Self-organizing patterns arise in a variety of ways in nature, the complex patterning observed on animal coats is such an example. It is already known that the mechanisms responsible for pattern formation starts at the developmental stage of an embryo. However, the actual process determining cell fate has been, and still is, unknown. The mathematical interest for pattern formation emerged from the theories formulated by the mathematician and computer scientist Alan Turing in 1952. He attempted to explain the mechanisms behind morphogenesis and how the process of spatial cell differentiation from homogeneous cells lead to organisms with different complexities and shapes. Turing formulated a mathematical theory and proposed a reaction-diffusion system where morphogens, a postulated chemically active substance, moderated the whole mechanism. He concluded that this process was stable as long as diffusion was neglected; otherwise this would lead to a diffusion-driven instability, which is the fundamental part of pattern formation. The mathematical theory describing this process consists of solving partial differential equations and Turing considered deterministic reaction-diffusion systems.   This thesis will start with introducing the reader to the problem and then gradually build up the mathematical theory needed to get an understanding of the stochastic reaction-diffusion systems that is the focus of the thesis. This study will to a large extent simulate stochastic systems using numerical computations and in order to be computationally feasible a compartment-based model will be used. Noise is an inherent part of such systems, so the study will also discuss the effects of noise and morphogen kinetics on different geometries with boundaries of different complexities from one-dimensional cases up to three-dimensions.

In this thesis we show how reactive processes can be affected by the presence of different types of spatial constraints, so much so that their nonlinear dynamics can be qualitatively altered or that new and unexpected behaviors can be produced. To understand how this interplay can occur in general terms, we theoretically investigate four very different examples of this situation. <p><p>The first system we study is a reversible trimolecular chemical reaction which is taking place in closed one-dimensional lattices. We show that the low dimensionality may or may not prevent the reaction from reaching its equilibrium state, depending on the microscopic properties of the molecular reactive mechanism. <p><p>The second reactive process we consider is a network of biological interactions between pigment cells on the skin of zebrafish. We show that the combination of short-range and long-range contact-mediated feedbacks can promote a Turing instability which gives rise to stationary patterns in space with intrinsic wavelength, without the need of any kind of motion.<p><p>Then we investigate the behavior of a typical chemical oscillator (the Brusselator) when it is constrained in a finite space. We show that molecular crowding can in such cases promote new nonlinear dynamical behaviors, affect the usual ones or even destroy them. <p><p>Finally we look at the situation where the constraint is given by the presence of a solid porous matrix that can react with a perfect gas in an exothermic way. We show on one hand that the interplay between reaction, heat flux and mass transport can give rise to the propagation of adsorption waves, and on the other hand that the coupling between the chemical reaction and the changes in the structural properties of the matrix can produce sustained chemomechanical oscillations. <p><p>These results show that spatial constraints can affect the kinetics of reactions, and are able to produce otherwise absent nonlinear dynamical behaviors. As a consequence of this, the usual understanding of the nonlinear dynamics of reactive systems can be put into question or even disproved. In order to have a better understanding of these systems we must acknowledge that mechanical and structural feedbacks can be important components of many reactive systems, and that they can be the very source of complex and fascinating phenomena.<p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished