Universite Paul Sabatier
CNRS-Laboratoire de Microbiologie et Genetique Moleculaires
118, route de Narbonne
31062 Toulouse CEDEX 9, France
Systematic sequencing genome projects generate large amounts of data that must be annotated for their biological exploitation. If the first annotation step may allow the identification of single genes/gene products, a complementary level of annotation consists in taking into account interactions of the proteins involved in the same supra-molecular system and/or biological process. These interactions can be stable, or transient, and either physical or functional. The cellular functions that emerge from these complex systems are not only an addition of the individual protein properties but result also from the interactions between the proteins. Biological systems result also from a complex evolutionary history, in a sense that partners and/or relationships between them can have been added, removed or replaced along the evolutionary history, with two extreme consequences, the loss or the duplication of systems in a phylogenetic clade. In general, duplicated systems do not conserve the same cellular function. Such a complex evolutionary scenario occurs when partners are encoded by multigenic families. In this framework, our group has focused its activity on two main research axes: i) development of strategies in order to identify, reconstruct and classify, from the genomic sequences, functional supra-molecular assemblies whose members belong to multigenic families and ii) phylogenomics analyses involving also the development of approaches to identify orthologous genes/proteins. ABC systems were initially chosen as a model because they form one of the largest ubiquitous families of paralogous systems that have arisen early in evolution and are involved in many essential physiological processes. The developed strategies lead to the creation and maintenance of a public database dedicated to ABC systems (ABCdb). Since then, we have extended our expertise in phylogenomics analyses on different gene families and systems through collaborations. To address the dynamics of the interaction between biological entities, we started to implement systems biology approaches focused on the modeling of the regulatory pathway of natural genetic transformation in streptococcal species.