LIFEdb database for the integration and dissemination of functional data
Team: Heiko Rosenfelder, David Zhang, Stefan Wiemann
Former members: Alexander Mehrle, Detlev Bannasch
The sequences of several thousand novel full length cDNAs have been identified and collated by the German cDNA Consortium. Using bioinformatic analysis methods, functional predictions can only be made for about 50% of these novel cDNAs, rendering them primary candidates for functional classification.
In the recent years we have established a functional genomics pipeline which is comprised of a range of experiments, and which produces heterogenous data sets. Integration of data is prerequisite for an efficient analysis and mining of the information in order to draw significant and relevant conclusions. LIFEdb (Bannasch et al., 2004) has been designed to be able to take and present this data that is in part produced at remote locations by our collaborators and who need to have means for uploading e.g. of microscopic images, experimental data and conclusions. The functional data is generated through four parallel approaches.
- We analyze the relative expression levels of the endogenous mRNAs (corresponding to the cDNAs of interest) during growth factor modulated cell growth/arrest and apoptosis. This is a collaboration with the expression profiling group within the department.
- We tag the protein coding regions of novel full length cDNAs with the coding sequence of the green fluorescent protein, express the fusion proteins and analyze their subcellular localization.
- We up- or down-regulate the expression of the proteins and analyse the effects e.g. on cell growth/arrest or apoptosis in functional assays. This allows us to functionally test the relevance of the characterized expression profiles. Up-regulation is achieved by over-expression of the GFP-tagged proteins, down-regulation by treatment of target cells with mRNA-specific siRNAs and RNAi.
- We carry out proteomics projects that address analysis of the protein molecules directly, e.g. in protein activity assays, and in the analysis of protein-protein interactions.
LIFEdb allows us to collect, view and mine this data, to integrate data from external databases and to draw functional and disease relevant conclusions:
- Verify/improve the functional predictions made by sequence analyses and comparison with known genes (del Val et al., 2004).
- Infer a function to those novel cDNAs (50%) for which no functional predictions could be made by sequence analyses.
- Identify groups of cDNAs/proteins which have a similar localization/function or which play a role in cellular pathways involved in cell growth control or apoptosis.
- Identify and validate cDNAs/proteins as potential targets for pharmaceutical research applications, ultimately aiming at the development of anti-tumor drugs.
