A scoring system for the follow up study of nuclear receptor coactivator complexes

We have systematically isolated a variety of coactivator complexes from HeLa S3 cells using proteomic approaches. In the present report, we have evaluated twelve coactivator complexes involved in nuclear receptor-dependent gene transcription that have been purified by using an immunoprecipitation method. The twelve purified coactivator complexes are SRC-1, SRC-2, SRC-3, CBP, p300, CAPER, E6-AP, ASC-1, CoREST, CRSP3, CRSP2, and CDK7 containing complexes. We have identified 153 protein components associated with these coactivator complexes using mass spectrometry. In order to systematically characterize the functional roles for these components in nuclear receptor-dependent gene transcription and their investigative potential, we have developed a scoring system. This scoring system is comprised of biological and experimental parameters. The biological evaluation considers aspects such as intrinsic enzymatic activity of a protein component, cellular signaling processes in which protein components may be involved, associations with human disease, specific protein motifs, and the known biological roles of other interacting partners of the identified protein. In the experimental evaluation, we include parameters, such as the availability of research materials for the functional study of the identified protein component; such as full-length cDNA clones, antibodies, and commercially available knock-out embryonic stem (ES) cells. Each scoring parameter has been assigned an arbitrary number of points according to perceived relative importance. On the basis of this scoring system, we prioritized each of the protein components in terms of the likelihood of their importance for coactivator complex networking in nuclear receptor-dependent gene transcription

Nuclear Receptor Signaling Atlas (): hyperlinking the nuclear receptor signaling community

The nuclear receptor signaling (NRS) field has generated a substantial body of information on nuclear receptors, their ligands and coregulators, with the ultimate goal of constructing coherent models of the biological and clinical significance of these molecules. As a component of the Nuclear Receptor Signaling Atlas (NURSA)—the development of a functional atlas of nuclear receptor biology—the NURSA Bioinformatics Resource is developing a strategy to organize and integrate legacy and future information on these molecules in a single web-based resource (). This entails parallel efforts of (i) developing an appropriate software framework for handling datasets from NURSA laboratories and (ii) designing strategies for the curation and presentation of public data relevant to NRS. To illustrate our approach, we have described here in detail the development of a web-based interface for the NURSA quantitative PCR nuclear receptor expression dataset, incorporating bioinformatics analysis which provides novel perspectives on functional relationships between these molecules. We anticipate that the free and open access of the community to a platform for data mining and hypothesis generation strategies will be a significant contribution to the progress of research in this field

Feed-Forward Inhibition of Androgen Receptor Activity by Glucocorticoid Action in Human Adipocytes

SummaryWe compared transcriptomes of terminally differentiated mouse 3T3-L1 and human adipocytes to identify cell-specific differences. Gene expression and high content analysis (HCA) data identified the androgen receptor (AR) as both expressed and functional, exclusively during early human adipocyte differentiation. The AR agonist dihydrotestosterone (DHT) inhibited human adipocyte maturation by downregulation of adipocyte marker genes, but not in 3T3-L1. It is interesting that AR induction corresponded with dexamethasone activation of the glucocorticoid receptor (GR); however, when exposed to the differentiation cocktail required for adipocyte maturation, AR adopted an antagonist conformation and was transcriptionally repressed. To further explore effectors within the cocktail, we applied an image-based support vector machine (SVM) classification scheme to show that adipocyte differentiation components inhibit AR action. The results demonstrate human adipocyte differentiation, via GR activation, upregulates AR but also inhibits AR transcriptional activity

Recovering Protein-Protein and Domain-Domain Interactions from Aggregation of IP-MS Proteomics of Coregulator Complexes

Coregulator proteins (CoRegs) are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP) followed by mass spectrometry (MS) applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/

Distinct RNA motifs are important for coactivation of steroid hormone receptors by steroid receptor RNA activator (SRA)

Steroid receptor RNA activator (SRA) is an RNA transcript that functions as a eukaryotic transcriptional coactivator for steroid hormone receptors. We report here the isolation and functional characterization of distinct RNA substructures within the SRA molecule that constitute its coactivation function. We used comparative sequence analysis and free energy calculations to systematically study SRA RNA subdomains for identification of structured regions and base pairings, and we used site-directed mutagenesis to assess their functional consequences. Together with genetic deletion analysis, this approach identified six RNA motifs in SRA important for coactivation. Because all nucleotide changes in the mutants that disrupted SRA function were silent mutations presumed not to alter deduced encoded amino acid sequence, our analysis provides strong evidence that SRA-mediated coactivation is executed by distinct RNA motifs and not by an encoded protein

Steroid Receptor RNA Activator Stimulates Proliferation as Well as Apoptosis In Vivo

Steroid receptor RNA activator (SRA) is an RNA that coactivates steroid hormone receptor-mediated transcription in vitro. Its expression is strongly up-regulated in many human tumors of the breast, uterus, and ovary, suggesting a potential role in pathogenesis. To assess SRA function in vivo, a transgenic-mouse model was generated to enable robust human SRA expression by using the transcriptional activity of the mouse mammary tumor virus long terminal repeat. Transgenic SRA was expressed in the nuclei of luminal epithelial cells of the mammary gland and tissues of the male accessory sex glands. Distinctive evidence for SRA function in vivo was obtained from the elevated levels of estrogen-controlled expression of progesterone receptor in transgenic mammary glands. Although overexpression of SRA showed strong promoting activities on cellular proliferation and differentiation, no alterations progressed to malignancy. Epithelial hyperplasia was accompanied by increased apoptosis, and preneoplastic lesions were cleared by focal degenerative transformations. In bitransgenic mice, SRA also antagonized ras-induced tumor formation. This work indicates that although coactivation of steroid-dependent transcription by SRA is accompanied by a proliferative response, overexpression is not in itself sufficient to induce turmorigenesis. Our results underline an intricate relationship between the different physiological roles of steroid receptors in conjunction with the RNA activator in the regulation of development, tissue homeostasis, and reproduction

Maf1 and Repression of RNA Polymerase III-Mediated Transcription Drive Adipocyte Differentiation

Summary: RNA polymerase (pol) III transcribes a variety of small untranslated RNAs involved in transcription, RNA processing, and translation. RNA pol III and its components are altered in various human developmental disorders, yet their roles in cell fate determination and development are poorly understood. Here we demonstrate that Maf1, a transcriptional repressor, promotes induction of mouse embryonic stem cells (mESCs) into mesoderm. Reduced Maf1 expression in mESCs and preadipocytes impairs adipogenesis, while ectopic Maf1 expression in Maf1-deficient cells enhances differentiation. RNA pol III repression by chemical inhibition or knockdown of Brf1 promotes adipogenesis. Altered RNA pol III-dependent transcription produces select changes in mRNAs with a significant enrichment of adipogenic gene signatures. Furthermore, RNA pol III-mediated transcription positively regulates long non-coding RNA H19 and Wnt6 expression, established adipogenesis inhibitors. Together, these studies reveal an important and unexpected function for RNA pol III-mediated transcription and Maf1 in mesoderm induction and adipocyte differentiation. : Maf1 and RNA pol III transcription repression play a key role in cell fate determination by promoting mesoderm induction and adipocyte differentiation. Chen et al. show that alterations in RNA pol III transcription produce select changes in adipogenic genes, and inhibitory factors including Wnt6 and H19lnc RNA, to regulate adipogenesis. Keywords: RNA polymerase III, Maf1, transcription, adipogenesi