Annual meeting: 2013
Fields-Topics: P1 Molecular and Cellular
Type of talk: Fellows Speed Presentation
My research interests relate to the comprehensive understanding of the role of metabolism in microbial adaptation. Predictive biology is of great interest for me since it enables a thorough understanding of microbial adaptation and an efficient prediction of phenotypes via a fusion of concepts from many disciplines, including biology, analytical science, computer science, and applied mathematics. I obtained an MSc in Proteomic, Metabolomics and Structural Biochemistry in 2009 at the Université Paul Sabatier (Toulouse, France), and in 2009 I started a PhD thesis (funded by a CJS fellowship from the INRA, MICA department) in the group of Prof. Jean-Charles Portais (MetaSys, LISBP, Toulouse, France). My PhD project aimed to explore the role of a posttranscriptional regulator, the Csr system, in the metabolic adaptation of Escherichia coli, the most common facultative aerobe in the gut. In 2012, while working as a researcher at UMR LISBP, INRA, I obtained a fellowship from AgreenSkills to join the group of Pedro Mendes (Manchester Centre for Integrative Systems Biology, University of Manchester, UK). During the course of this postdoctoral fellowship, I am developing a detailed, kinetic model of E. coli to understand how metabolic networks and regulatory networks cooperate in the biological response of this bacterium to environmental changes. I got a permanent position as junior researcher at the UMR LISBP in Toulouse in 2014.
One of the outcomes of the genome projects is that we have a catalogue of the functions of all the genes, and yet we are not able to understand the time-dependent behaviour of even simple micro-organisms. To explain and predict how cells respond to their environments, systems biology needs "digital organisms", i.e. dynamic computer models that will enable reasoning and prediction of the function of these cells. To date, a major limit of existing models is they are not able to represent the dynamic behaviour of micro-organisms because they are mainly based on stoichiometric constraints alone. In addition, to become true digital organisms, existing models must integrate not only metabolism but also signalling networks and regulation of gene expression. In that context, my project aims at constructing a whole-cell kinetic model of Escherichia coli that will be able to represent the long-term dynamic response of this model organism to a set of different environmental perturbations. To reach this aim, three specific objectives will be pursued: i) construct a detailed kinetic model of the central metabolism of E. coli, ii) include signalling and gene regulation for specific external perturbations (i.e. environmental changes), and iii) expand this model to genome scale. The whole-cell model is expected to significantly improve our comprehensive, system-level understanding of metabolic adaptation in general, and also to understand how E. coli develops an integrated response to changes in its environment. This project will be a major stepping-stone toward the long-term goal of a complete model of E. coli, and will be of special value in several fields such as biotechnology and biomedicine. We will demonstrate the strategy to achieve it and will resolve some of the methodological problems that lie ahead.
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