Dataset Information

Identification of Merlin binding proteins

ABSTRACT: To identify proteins interacting with Merlin in response to calcium signaling, Flag-tagged Merlin was stably transduced into LN229 cells. These cells and empty vector-transduced LN229 cells were treated with DMSO or thapsigargin for 15 minutes and subjected to immunoprecipitation followed by Mass Spectrometry.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

TISSUE(S): Cell Culture

SUBMITTER: Wei Li

LAB HEAD: Wei Li

PROVIDER: PXD021058 | Pride | 2020-12-07

REPOSITORIES: Pride

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Publications

NEDD4L-mediated Merlin ubiquitination facilitates Hippo pathway activation.

Wei Yiju Y Yee Patricia P PP Liu Zhijun Z Zhang Lei L Guo Hui H Zheng Haiyan H Anderson Benjamin B Gulley Melissa M Li Wei W

EMBO reports 20201014 12

The tumor suppressor Merlin/NF2, a key activator of the Hippo pathway in growth control, is regulated by phosphorylation. However, it is uncertain whether additional post-translational modifications regulate Merlin. Here, we show that ubiquitination is required to activate Merlin in the Hippo pathway. Ubiquitinated Merlin is mostly conjugated by one or two ubiquitin molecules. Such modification is promoted by serine 518 dephosphorylation in response to Ca<sup>2+</sup> signaling or cell detachmen ...[more]

PMID: 33058421

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Project description:Dendritic cells (DCs) are a special class of leukocytes able to activate both innate and adaptive immune responses. They interact with microbes through germline-encoded pattern-recognition receptors (PRRs), which recognize molecular patterns expressed by various microorganisms. Upon antigen binding, PRRs instruct DCs for the appropriate priming of natural killer cells, followed by specific T-cell responses. Once completed the effector phase, DCs reach the terminal differentiation stage and eventually die by apoptosis. We have observed that following lipopolysaccharide (LPS)-stimulation the initiation of the apoptotic pathway in DCs is due the activation of NFAT proteins. Indeed, LPS induces Src-family kinase and phospholipase C (PLC)Î³2 activation, influx of extracellular Ca2+ and calcineurin-dependent nuclear NFAT translocation. The initiation of this pathway is independent of TLR4 engagement, and dependent exclusively on CD14. According with this observation CD14-deficient DCs do not die following LPS stimulation. Nevertheless, CD14-deficient DC death following LPS activation can be restored by co-stimulating DCs with LPS and thapsigargin. Thapsigargin empties the intracellular calcium stores by blocking calcium pumping into the sarcoplasmic and endoplasmic reticulum and thereby activates plasma membrane calcium channels. This, in turn, allows an influx of calcium into the cytosol and NFAT activation. To identify the NFAT controlled apoptosis genes in LPS activated DCs we have performed a kinetic microarray analysis (0, 48 and 60 h) in conditions allowing or inhibiting NFAT activation. Four genes have been selected: Nur77, Gadd45g, Ddit3/Gadd153/Chop-10 and Tia1. To identify apoptosis genes selectively modulated by NFAT, a comparative kinetic (time points 0, 48 and 60 h) microarray analysis was performed in the following conditions: 1) wild type bone marrow derived DCs (wtBMDCs) stimulated with LPS; 2) CD14-deficient BMDCs stimulated with LPS; 3) wtBMDCs stimulated with LPS in presence of thapsigargin; 4) CD14-deficient BMDCs stimulated with LPS in presence of thapsigargin.

Project description:Purpose: microRNA profiles were generated from NIH-3T3 cells control and thapsigargin treated, in duplicate. The goal of this study was to compare microRNA profiles of untreated and thapsigargin treated NIH-3T3 fibroblast cells. Methods: NIH-3T3 cells were grown to confluency and either untreated or treated with 500 nM thapsigargin in media for 24 hours. Cells were harvested with TriZol and RNA isolated according to manufacturers protocol Analysis Outline: Short reads in fastq format were assembled using BclToFastq.pl script from Illumina CASAVA 1.8.1 software pipeline.Read quality was examined using FastQC program (http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc). Adapters were trimmed at the 3'end using Btrim prgram (PMID:21651976), only sequences equal to and longer than 18nt were retained, leading N base was trimmed at the 5' end. Unique reads were collapsed using Raw_data_parse program from miRExpress suite (PMID:19821977) (the result of this process is a file that contains unique sequences in one column and number of times this sequence was found in the library in another). They can be found in *.merge files in trimmed_reads directory. Collapsed reads were reformatted and uploaded into miRanalyzer web-based pipeline (http://bioinfo2.ugr.es/miRanalyzer/miRanalyzer.php; PMID:21515631) and matched to known mature miRNA (miRBase vesion 16), RFAM database (version 15) of known non-coding RNAs and known gene transcripts. The purpose of miRAnalyzer analysis was to only detect known miRNAs, prediction of novel miRNAs was not performed; search parameters were kept at default. MiRanalyzer output is saved in miRanalyzer folder with detailed information about mapping to known miRNA. Known miRNAs were divided into mature, maturestar (star sequences), maturestarunobs (star sequences not in miRBase) and hairpin. For each of the libraries there are files with unique and ambiguous mappings. Differentional expression analysis was based on unique alignments to known miRNAs (mature_unique.txt file in miRanalyzer folder). Mature_unique.txt has following columns: name: mature miRNA ID from miRBase; #unique reads: number of unique reads mapped; readCount: number of reads mapped; norm_expressed_all: normalized to all reads; norm_expressed_mapped: normalized to mapped reads. miRNA expression profiling was performed using edgeR bioconductor package (PMID:20478825). For differential expression analysis, used TMM normalization and analysis using common disperion (using tagwise dispersion yielded the same results). FDR was calculated according to Hochberg-Benjamini procedure (PMID:2218183). Results of differential expression analysis were saved in diff_exp folder as diff_exp.txt. diff_exp.txt contains miRNA concentrations in log scale, log2 ratio of WT to KO; p-values and FDR corrected p-values. miRNAs were sorted by p-value. NIH-3T3 cells grown to confluency and treated with 500 nM thapsigargin in media for 24 hours

Dataset Information

Identification of Merlin binding proteins

Publications

NEDD4L-mediated Merlin ubiquitination facilitates Hippo pathway activation.

Similar Datasets

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