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Background  During  Drosophila  development, titers of the steroid ecdysone trigger and maintain temporal and tissue specific biological transitions. Decades of evidence reveal that the ecdysone response is both unique to specific tissues and distinct among developmental timepoints. To achieve this diversity in response, the several isoforms of the Ecdysone Receptor, which transduce the hormone signal to the genome level, are believed to interact with tissue specific cofactors. To date, little is known about the identity of these cofactor interactions; therefore, we conducted a bioinformatics informed, RNAi luciferase reporter screen against a subset of putative candidate cofactors identified through an  in silico  proteome screen. Candidates were chosen based on criteria obtained from bioinformatic consensus of known nuclear receptor cofactors and homologs, including amino acid sequence motif content and context.    Results  The bioinformatics pre-screen of the  Drosophila melanogaster  proteome was successful in identifying an enriched putative candidate gene cohort. Over 80% of the genes tested yielded a positive hit in our reporter screen. We have identified both cell type specific and common cofactors which appear to be necessary for proper ecdysone induced gene regulation. We have determined that certain cofactors act as co-repressors to reduce target gene expression, while others act as co-activators to increase target gene expression. Interestingly, we find that a few of the cofactors shared among cell types have a reversible roles to function as co-repressors in certain cell types while in other cell types they serve as co-activators. Lastly, these proteins are highly conserved, with higher order organism homologs also harboring the LXXLL steroid receptor interaction domains, suggesting a highly conserved mode of steroid cell target specificity.    Conclusions  In conclusion, we submit these cofactors as novel components of the ecdysone signaling pathway in order to further elucidate the dynamics of steroid specificity.

bmc developmental biology

Identification of common and cell type specific LXXLL motif EcR cofactors using a bioinformatics refined candidate RNAi screen in Drosophila melanogastercell lines