experimental and theoretical approaches to decipher the molecular
networks of nitrogen utilisation in yeast"
Funding: Communauté Française de
Project number: 04-09/307
The yeast Saccharomyces cerevisiae is the model living organism that
has been by far the most extensively used to develop the novel
experimental methods of genomics and proteomics. Multiple facets of the
metabolism of yeast cells have been explored using these approaches. In
this project, we plan for the first time to monitor at whole-genome
scale the response of yeast cells to supply conditions for a key
nutrient of all cellular systems: nitrogen. Yeast cells will be grown
under as wide a range of nitrogen supply conditions as possible (yeast
can use up to thirty different compounds as sole nitrogen source) and
the state of their transcriptome will be monitored using the DNA
microarray method. In parallel, the concentration of
nitrogen-containing metabolites in the cell will be measured. The
specific binding of key transcriptional regulators to their multiple
gene targets will also be monitored under various nitrogen supply
conditions. The numerical data thus generated will be interpreted by
combining statistical (clustering, supervised classification, time
series prediction), static (graph theory), and dynamic modelling
methods. Novel hypotheses resulting from these in numero analyses will
then be subjected to validation tests using classical methods of
molecular genetics. Thanks to this permanent cross-feeding between
experimental and theoretical analyses, the project aims to
progressively decipher the complete molecular network of nitrogen
metabolism in yeast, of its regulation, and of anticipated overlaps
between this network and other domains of cell activity. The suspected
dominant role played by membrane nutrient transport and sensing systems
in the orchestration of this network will also be investigated.
The project will be conducted by four research teams (as shown below),
including biologists with expertise in genomics applied to yeast (B.
André), computer scientists (G. Bontempi), bioinformaticians (J.
van Helden) and biomathematicians (M. Kaufman). Beyond its scientific
objectives, this project offers the exceptional opportunity to gather
around a specific biological question the different competences which
today appear absolutely essential to exploiting optimally the huge
flows of biological data issued from the growing number of
investigations based on genomics and proteomics.