Mardi 23 mars 2004

Laurence Lejay UMR B&PMP (Equipe Intégration)
A systems based approach to C: N signaling in plants

Studies have shown that multiple input signals can affect expression of amino acid biosynthesis genes in plants. We were specifically interested in determining how multiple input signals such as light, carbon and nitrogen intersect to regulate genes involved in the primary assimilation of nitrogen into amino acids using Arabidopsis as a model.To address this issue in a systematic and thorough way, we employed a math tool initially developed for software testing called Combinatorial Design (CD) to model this experimental exploration space. Initially, we considered six input signals; light, carbon, inorganic N, glutamine, glutamate and starvation. If the value of each input is binary (+/-), examining all possible combinations of the six inputs (26) would result in 64 treatments. This experimental space would grow exponentially if every input were represented by three different concentrations e.g. 36 or 729 treatments. We used Combinatorial Design to reduce the number of the experimental treatments to a small number that would systematically sample and effectively cover the same experimental space. In the case of the 64 combinations, CD reduced the experiments to a mere 6 treatments, while it reduces the 729 treatment space to a mere 14 experiments. We validated this CD approach by comparing a small set of CD experiments (6) to a complete dataset of 64 treatments. We performed Boolean analysis of the CD and compared it to the entire dataset in order to model circuits for the multiple input signal regulation of this pathway. We are also performing gene chip experiments on CD samples to monitor the regulation of all amino acid biosynthesis genes in the genomes by these multiple input signals. For this analysis, we developed a bioinformatic tool, called « PathExplore » that can be used to query microarray expression datasets to determine how all the genes in pathways are regulated. The « PathExplore » database includes genes for biosynthetic pathways of N-assimilation, all amino acid biosynthesis pathways and related co-factors, as well as C-metabolism pathways, and signaling pathways. To then generate a comprehensive model of the metabolic network of Arabidopsis in order to visualize gene expression we recently developped a computational modeling using a programm called Cytoscape. Combinatorial Design plus gene chip analysis with « PathExplore » and Cytoscape should enable us to model genome wide regulatory circuits, a first step to the construction of a virtual plant.