Dataset Information

Mass spectrometry analysis of estrogen receptor α -interacting proteins.

ABSTRACT: Quantitative mass spectrometry analysis using tandem mass tags (TMT) labelling of estrogen receptor α (ERα) pull downs. Co-immunoprecipitated proteins using a anti Erα antibody were compared quantitatively with material recovered in a mock to identify ERα-interacting proteins.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell, Epithelial Cell, Cell Culture

DISEASE(S): Breast Cancer

SUBMITTER: Juan Oses-Prieto

LAB HEAD: Davide Ruggero

PROVIDER: PXD025018 | Pride | 2022-10-14

REPOSITORIES: Pride

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Publications

ERα is an RNA-binding protein sustaining tumor cell survival and drug resistance.

Xu Yichen Y Huangyang Peiwei P Wang Ying Y Xue Lingru L Devericks Emily E Nguyen Hao G HG Yu Xiuyan X Oses-Prieto Juan A JA Burlingame Alma L AL Miglani Sohit S Goodarzi Hani H Ruggero Davide D

Cell 20210923 20

Estrogen receptor α (ERα) is a hormone receptor and key driver for over 70% of breast cancers that has been studied for decades as a transcription factor. Unexpectedly, we discover that ERα is a potent non-canonical RNA-binding protein. We show that ERα RNA binding function is uncoupled from its activity to bind DNA and critical for breast cancer progression. Employing genome-wide cross-linking immunoprecipitation (CLIP) sequencing and a functional CRISPRi screen, we find that ERα-associated mRN ...[more]

PMID: 34559986

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Project description:The closely related transcription factors (TFs), estrogen receptors ERα and ERβ, regulate divergent gene expression programs and proliferative outcomes in breast cancer. Utilizing MCF-7 breast cancer cells with ERα, ERβ, or both receptors as a model system to define the basis of differing response specification by related TFs, we show that these TFs and their key coregulators, SRC3 and RIP140, generate overlapping as well as unique chromatin-binding and transcription-regulating modules. Cistrome and transcriptome analyses and use of clustering algorithms delineated 11 clusters representing different chromatin-bound receptor and coregulator assemblies that could be functionally associated through enrichment analysis with distinct patterns of gene regulation and preferential coregulator usage, RIP140 with ERβ and SRC3 with ERα. The receptors modified each other’s transcriptional effect, and ERβ countered the proliferative drive of ERα through several novel mechanisms associated with specific binding site clusters. Our findings delineate distinct TF-coregulator assemblies that function as control nodes specifying precise patterns of gene regulation, proliferation, and metabolism, as exemplified by two of the most important nuclear hormone receptors in human breast cancer. MCF-7 cells expressing endogenous ERalpha were infected with adenovirus carrying either estrogen receptor beta (AdERb) or no insert (Ad) at multiplicity of infection (moi) of 50. ERβ only cells were generated from these cells by knockdown of ERα in parental cells using the following siERα sequences from Dharmacon: forward, 5’-UCAUCGCAUUCCUUGCAAAdTdT-3’, and reverse, 5’-UUUGCAAGGAAUGCGAUGAdTdT-3’. siRNA experiments were performed as previously described, and resulted in knocknown of ERα mRNA and protein by greater than 95% (GSE4006, PMID 16809442). Briefly, cells were transfected with 20 nM siCtrl [GSE4006] or siERα for 48 h after infection. Then cells were treated with 0.1% EtOH (Veh) or 10 nM E2 (Sigma-Aldrich) for 24h. All experiments were conducted with two replicates. key words; Adenovirus infection,siRNA knock-down, ligand treatment

Project description:Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during shifts in electron acceptor availability. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs), ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate > 80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Finally, based on the data we propose a feedforward with feedback trim regulatory scheme by showing extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r2 (p < 1e-6) correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. We also are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network. We integrated transcription factor binding regions and mRNA transcript abundance to elucidate the ArcA and Fnr regulons experimentally. To measure transcription factor binding at a genome scale, we employed a ChIP-chip method to derivative strains of E. coli K-12 MG1655 harboring ArcA-8myc or Fnr-8myc under various conditions. The E. coli strains harboring Fnr-8myc and ArcA-8myc were generated as described previously [PMID 16454042]. A 12 chip study with two different strains under two different culture conditions.

Dataset Information

Mass spectrometry analysis of estrogen receptor α -interacting proteins.

Publications

ERα is an RNA-binding protein sustaining tumor cell survival and drug resistance.

Similar Datasets

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