SAMITProject reference: 204575
Funded under :
"Systems Analysis of Plant Metabolism through the Integration of Heterogeneous Data from Genetics, Informatics and Metabolomics"
Total cost:EUR 1 009 000
EU contribution:EUR 1 009 000
Call for proposal:ERC-2007-StGSee other projects for this call
Funding scheme:ERC-SG - ERC Starting Grant
"The term METABOLISM describes all the chemical reactions and interactions that take place in a biological system. The regulation of metabolic pathways is constantly tuned in order to suit the needs of development and fitness. The main goal of the proposed research is to unravel networks of genes and proteins which coordinate the activity of metabolic pathways during plant development and stress response. In Phase I of the project, an infrastructure will be set-up that includes metabolite analyses technologies, a large tomato mutant population and a collection of tomato transcription factor genes. In Phase II, the population will be screened for novel mutants and genes associated with the research interests of the lab. The screens will include: a) visual screening, b) HTP, non laborious assays, c) non-targeted metabolite analysis for the detection of differential metabolites using LC-MS, and d) screening by a reverse genetic approach (from sequence to mutant) through transposon display. The collection of transcription factors will be used for rapid gene function analysis by means of Virus Induced Gene silencing (VIGS), and for the generation of a tomato transcription factors ""Interactome"" map. In Phase III, selected genes and mutants will be subjected to a detailed characterization including: a) the regulatory networks controlling fruit development, b) the regulation of metabolic pathways associated with plant surface metabolism and c) the regulation of the Isoprenoid pathway (including the glycoalkaloids and carotenoids). Data gathered from diverse platforms and screens will be integrated using computational tools to provide new knowledge on the genetic control of metabolic pathways that is currently very limited. This research addresses a major challenge, namely, the extensive acquisition of an heterogeneous set of data (genetic, gene expression, protein interaction and metabolic) and their integration to identify regulatory networks controlling plant metabolism."