PhD thesis defense of Laurie FAVRE
Laurie FAVRE, PhD student at MAPIEM lab, under the supervision of:
will defend her PhD thesis in Biochemistry, on the topic:
on March 28th, 2017, at 09:00 AM, in the Amphitheatre of Building M, SEATECH, University of Toulon,
before a jury composed of :
- Mrs PRADO Soizic, Professor, Museum National d’Histoire Naturelle
- M GROVEL Olivier, Associate Professor, University of Nantes
- Mrs BONIN Patricia, Research Director, CNRS (Aix-Marseille University)
- M MARTIN Jean-Charles, Research Director, INRA (Aix-Marseille University)
- M PEREZ Thierry, Research Director, CNRS (Aix-Marseille University)
- M GANDOLFO Robert, Project manager, Pôle Mer Méditerranée
- M CULIOLI Gérald, Associate Professor, University of Toulon
- Mrs ORTALO-MAGNE Annick, Assistant Professor, University of Toulon
Abstract:
In the marine environment, all immersed surfaces are subjected to colonization pressure by a great diversity of micro- and macroorganisms (biofouling). The development of biofilms constitutes a key stage in this process. In such biological structures, communication systems are mainly controlled by chemical signals. In this work, chemical profiles of natural biofilms collected along a pollution gradient (Bay of Toulon) and on several types of antifouling coatings were studied. Marked chemical variations were observed and compared with microbial community structure. The specific study of cultures of four bacterial strains isolated from natural biofilms allowed, after optimization of the analytical protocols, their discrimination according to their metabolic profiles. Discriminant biomarkers were then identified and, among them, ornithine lipids were found to be particularly over-expressed in Pseudoalteromonas lipolytica TC8. The biological responses of this strain depending on its phenotype and face to copper stress were studied by a combined metabolomics and proteomics analysis. It showed significant changes of some biosynthetic pathways.
Keywords:
Marine bacteria; Biofilms; Metabolomics; LC-MS; Proteomics; Molecular networking; Amino lipids; Statistical analyses
