Synthèse de structure de réaction-diffusion à base d’ADN : vers la génération de structure de Turing

Synthesis of reaction-diffusion patterns with DNA : towards Turing patterns

• Auteur / Autrice : Adrian Zambrano Ramirez
• Direction : André Estévez Torres
• Type : Thèse de doctorat
• Discipline(s) : Physique
• Date : Soutenance le 26/09/2016
• Etablissement(s) : Université Paris-Saclay (ComUE)
• Ecole(s) doctorale(s) : École doctorale Electrical, optical, bio : physics and engineering (Orsay, Essonne ; 2015-....)
• Partenaire(s) de recherche : établissement opérateur d'inscription : Université Paris-Sud (1970-2019)
• Partenaire(s) de recherche : Laboratoire : Laboratoire de Photonique et de Nanostructures (Marcoussis, Essonne ; 1984-2016) - Laboratoire Jean Perrin (Paris ; 2009-....)
• Jury : Président / Présidente : Jean-Louis Mergny
• Jury : Examinateurs / Examinatrices : André Estévez Torres, Jean-Louis Mergny, Annette Taylor, Sébastien Michelin, Jean-Christophe Galas
• Jury : Rapporteurs / Rapporteuses : Annette Taylor, Didier Gasparutto

Mots clés

Mots clés contrôlés

Morphogenèse

ADN -- Réplication

Microfluidique

Diffusion (physique)

Mots clés libres

Microfluidique

Formation de motifs

Réseaux de réaction à base d'ADN

Réaction-diffusion

Microfluidics

Pattern formation

Synthetic DNA-Based reaction networks

Reaction-diffusion

Résumé

Cette thèse porte sur la mise en place et le développement d’une approche expérimentale pour l’étude de la dynamique spatio-temporelle de réseaux de réactions à base d’ADN. Nos résultats démontrent la capacité des réseaux d’ADN à se spatialiser sous la forme d’ondes progressives. Nous avons également pu obtenir des motifs stationnaires à base d’ADN et d’assemblages de billes. Ce travail contribue donc à la conception de motifs spatio-temporels de réactions chimiques et de matériaux par le biais de réseaux réactionnels biochimiques programmables. Nous apportons également de nouvelles données sur l’émergence d’ordre spatio-temporel à partir de processus de réaction-diffusion. De ce fait, cette étude contribue à une meilleure compréhension des principes fondamentaux qui régissent l’apparition d’une auto-organisation moléculaire dans un système chimique hors-équilibre. De plus, la combinaison de réseaux synthétiques d’ADN, du contrôle du coefficient de diffusion de plusieurs espèces d’ADN et de la micro-fluidique peut donner lieu à des motifs spatiaux stables, comme par exemple, les fameuses structures de Turing, ce qui tend à confirmer le rôle de celles-ci dans la morphogénèse.

This PhD work is devoted to developing an experimental framework to investigate chemical spatiotemporal organization through mechanisms that could be at play during pattern formation in development. We introduce new tools to increase the versatility of DNA-based networks as pattern-forming systems. The emergence of organization in living systems is a longstanding fundamental question in biology. The two most influential ideas in developmental biology used to explain chemical pattern formation are Wolpert's positional information and Turing's reaction-diffusion self-organization. In the case of positional information, the pattern emerges from a pre-existing morphogen gradient across space that provides positional values as in a coordinate system. Whereas, the Turing mechanism relies on self-organization by driving a system of an initially homogeneous distribution of chemicals into an inhomogeneous pattern of concentration by a process that involves solely reaction and diffusion. Although numerical simulations and mathematical analysis corroborate the incredible potential of reaction-diffusion mechanisms to generate patterns, their experimental implementation is not trivial. And despite of the exceptional achievements in pattern formation with Belousov–Zhabotinsky systems, these are difficult to engineer, thus limiting their experimental implementation to few available mechanisms. In order to engineer reaction-diffusion systems that display spatiotemporal dynamics the following three key elements must be controlled: (i) the topology of the network (how reactions are linked to each other, i.e. in a positive or negative feedback manner), (ii) the reaction rates and (iii) the diffusion coefficients. Recently, using nucleic acids as a substrate to make programmable dynamic chemical systems together with the lessons from synthetic biology and DNA nanotechnology has appeared as an attractive approach due to the simplicity to control reaction rates and network topology by the sequence. Our experimental framework is based on the PEN-DNA toolbox, which involves DNA hybridization and enzymatic reactions that can be maintained out of equilibrium in a closed system for long periods of time. The programmability and biocompatibility of the PEN-DNA toolbox open new perspectives for the engineering of the reaction-diffusion chemical synthesis, in particular in two directions. Firstly, to study biologically-inspired pattern-forming mechanisms in simplified, yet relevant, experimental conditions. Secondly to build new materials that would self-build by a process inspired from embryo morphogenesis. We worked towards the goal of meeting the two requirements of Turing patterning, transferring chemical spatiotemporal behavior into material patterns, and imposing boundary conditions to spatiotemporal patterns. Therefore, the structure of this document is divided into four specific objectives resulting in four chapters. In chapter 1 we worked on testing a DNA-based reaction network with an inhibitor-activator topology. In chapter 2 we focused on developing a strategy to tune the diffusion coefficient of activator DNA strands. In chapter 3 we explored how chemical patterns determine the shape of a material. Finally, in chapter 4 we addressed the issue of controlling the geometry over a DNA-based reaction-diffusion system. Overall, we have expanded the number of available tools to study chemical and material pattern formation and advance towards Turing patterns with DNA.