Objective
The objective of this proposal is to identify new low and medium abundance proteins involved in the pathophysiology of cystic fibrosis (CF), proteins that may constitute new diagnostic and prognostic biomarkers and be helpful in the development of new dr ugs for CF. To achieve this we will develop tools and standardize protocols for new approaches to study proteomics and facilitate generation of new knowledge in functional genomics. High performance techniques will be used and/or developed: Radio-isot ope and classical detection methods for differential display of proteins including their splicing variants and post-translational isoforms, i.e. the supersensitive analysis of 2D electrophoresis gels by a radio-isotopic technique (ProteoTope), Hig hly sensitive chromatographic methods for lipid analysis associated with different proteomic approaches for proteome-lipidome interactions, Surface plasmon resonance (Biacore®) for detection of interacting proteins, Protein sequence determination by mass spectrometric techniques (MS) using new, high sensitivity modalities including, Surface-Enhanced-Laser-Desorption-Laser/Ionization Time-of-Flight Mass Spectrometry (MS), FTICR-MS , multidimen- sional liquid chromatography -MS, Innovative bio-i nformatic tools. Our methodological goals are: To apply an integrated proteomic system for the detection of low and medium abundance proteins to different biological models of CF (serum, nasal ciliated cells, neutrophils, cell lines), To improve th e sensitivity of MS for the peptide sequences of differentially displayed proteins, To develop the MS methodology for analysis of protein without 2D gel protein separation To develop new tools for protein-, DNA-, and lipid- protein analysis. Our proje ct main goals are: To develop and apply highly sensitive methods for low abundance protein identification by MS which will be useful for the entire proteomic community,
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsproteomics
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencesbiological sciencesbiochemistrybiomoleculeslipids
- natural scienceschemical scienceselectrochemistryelectrophoresis
- natural scienceschemical sciencesanalytical chemistrymass spectrometry
Call for proposal
FP6-2003-LIFESCIHEALTH-I
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Funding Scheme
NoE - Network of ExcellenceCoordinator
PARIS
France