Laboratoire Matière et Systèmes Complexes

Thèse de Zoran Marinkovic effectuée sous la direction de Pascal Hersen et Ariel B Lindner.

Soutenance le jeudi 30 novembre 2017 à 10h00.

Lieu : bâtiment Condorcet, Amphithéâtre Pierre-Gilles de Gennes (niveau -1). La soutenance sera suivie d’un pot dans l’espace convivalité du 6ème étage.

Self-organization of Saccharomyces cerevisiae colonies

Abstract :

The natural environment of yeast is often a community of cells but researchers prefer to study them in simpler homogeneous environments like single cell or bulk liquid cultures, losing insight into complex spatiotemporal growth, differentiation and self-organization and how those features are intertwined and shaped through evolution and ecology. I developed a multi-layered microfluidic device that allows us to grow yeast colonies in spatially controlled dynamically structured changing environments from a monolayer of single yeast cells to a multi-layered colony. Colony growth, as a whole and at specific locations, is a result of the nutrient gradient formation within a colony through interplay of nutrient diffusion rates, nutrient uptake rates by the cells and starting nutrient concentrations. Once a limiting nutrient (e.g. glucose or amino acids) is depleted at a specific distance from the nutrients source the cells within a colony stop to grow. I was able to modulate this specific distance by changing the starting nutrient concentrations and uptake rates of cells. Colony gene expression patterns gave us information on specific micro environments formation and consequential development, differentiation and self-organization. I quantified the patterns of expression of seven glucose transporter genes (HXT1-7), each of them specifically expressed depending on the glucose concentration. This enabled us to reconstruct glucose gradients formation in a colony. I further followed the expression of fermentation and respiration specific genes and observed differentiation between two subpopulations. I also mapped other genes specific for different parts of carbohydrate metabolism, followed and quantified the spatiotemporal dynamics of growth and gene expression, and finally modelled the colony growth and nutrient gradient formation. For the first time, we were able to observe growth, differentiation and self-organization of S. cerevisiae colony with such an unprecedented spatiotemporal resolution.