Dataset Information

PGE2 signaling networks in T cells

ABSTRACT: We combined phosphoproteomics and phosphoflow cytometry with specific stimulation of the four PGE2 receptors to obtain a global overview of PGE2-regulated signaling pathways and networks in T cells. The study revealed phosphoproteomes regulated uniquely by each receptor and crosstalk between receptors. Previously unknown PGE2-regulated phosphosites were identified, including biologically significant sites.

INSTRUMENT(S): Orbitrap Fusion, LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Culture Condition:cd4+ Cell, T Cell, Blood, Culture Condition:cd8+ Cell, Regulatory T-lymphocyte

SUBMITTER: Piero Giansanti

LAB HEAD: Albert J. R. Heck

PROVIDER: PXD014503 | Pride | 2021-08-22

REPOSITORIES: Pride

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Publications

Systems approach reveals distinct and shared signaling networks of the four PGE2 receptors in T cells.

Lone Anna M AM Giansanti Piero P Jørgensen Marthe Jøntvedt MJ Gjerga Enio E Dugourd Aurelien A Scholten Arjen A Saez-Rodriguez Julio J Heck Albert J R AJR Taskén Kjetil K

Science signaling 20211005 703

Prostaglandin E2 (PGE2) promotes an immunosuppressive microenvironment in cancer, partly by signaling through four receptors (EP1, EP2, EP3, and EP4) on T cells. Here, we comprehensively characterized PGE2 signaling networks in helper, cytotoxic, and regulatory T cells using a phosphoproteomics and phosphoflow cytometry approach. We identified ~1500 PGE2-regulated phosphosites and several important EP1–4 ...[more]

PMID: 34609894

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Project description:Prostaglandin E2 (PGE2) is involved in several inflammatory conditions including periodontitis. The aim of this study was to investigate the global gene expression profile of tumor necrosis factor alpha (TNFalpha) stimulated human gingival fibroblasts, focusing on signal pathways related to PGE2 production and the new PGE2-synthesizing enzymes, prostaglandin E synthases (PGES). The expression of microsomal prostaglandin E synthase-1 (mPGES-1) as well as the upstream cyclooxygenase-2 (COX-2) was up-regulated by TNFalpha, accompanied by increased PGE2 production. In contrast, the expression of microsomal prostaglandin E synthase-2 (mPGES-2) and cytosolic prostaglandin E synthase (cPGES) was unaffected by TNFalpha. Using microarray analysis in a time-course factorial design including time points 1, 3 and 6 h, we identified differentially expressed genes in response to TNFalpha treatment. Enrichment analysis of microarray data identified two positively regulated signal transduction pathways: c-Jun N-terminal kinase (JNK) and Nuclear Factor-kappaB (NF-kappaB). We used specific inhibitors and phosphorylation analysis to confirm their role in PGE2 regulation. Both JNK and NF-kappaB inhibitors reduced the TNFalpha-stimulated up-regulation of mPGES-1 and COX-2 as well as subsequent PGE2 production. The novel finding that TNFalpha-stimulated mPGES-1 is regulated by JNK suggests this kinase as a potential future target for treatment strategies in inflammatory disorders, including periodontitis. Keywords: Time course, gene expression, factorial design. Three human gingival fibroblast cell lines were established from gingival biopsies obtained from 3 healthy patients, 3 to 12 years of age, with no clinical signs of periodontal disease. Cells were incubated with or without TNF-alpha (20 ng/ml) for 1, 3 or 6h. After incubation for 1, 3 or 6 h in the two conditions, the cells were immediately frozen in liquid nitrogen and then stored at -70°C for subsequent isolation of total RNA. The experimental design of the microarray study was set up as a time-course factorial design, to best observe the TNF-alpha induced gene expression changes over time. C++ program (G.F. Glonek, P.J. Solomon, Factorial and time course designs for cDNA microarray experiments, Biostatistics 5 (2004) 89-111) was used to determine the exact layout of the design in order to estimate the interaction effect between treatment and time, i.e. genes that are differentially expressed over time, with optimal statistical efficiency. Cyanine 5 and cyanine 3 were used for labeling. For each cell line 12 hybridizations were performed in a time-course factorial design. In total, 36 hybridizations were performed.

Project description:We combine high-resolution mass spectrometry with Ti4+-IMAC phosphopeptide enrichment and label-free quantification to monitor the phosphoproteome of Jurkat T-cells following stimulation by Prostaglandin E2. Jurkat T lymphoma cells were grown in RPMI 1640 medium supplemented with 10% fetal bovine serum and penicillin/streptomycin (Lonza). For PGE2 stimulation, cells were centrifuged for 1 min at 1500g. The growth medium was removed and the cells were resuspended at a final concentration of 1-2 × 106 cells/ml in RMPI and supplemented with 0 (control) or 10 uM PGE2 and incubated for 5, 10, 20, 30 or 60 min. After cell lysis, reduction and alkylation, proteins were digested with Lys-C and Trypsin. The digests were desalted using Sep-Pak C18 cartridges, dried in vacuo and stored at −80 °C for further use. Phosphopeptide enrichment was performed as described in Zhou H, Ye M, Dong J, Corradini E, Cristobal A, Heck AJ, Zou H, Mohammed S. Nat Protoc. 2013 Mar;8(3):461-80. The enriched phosphopeptides were subjected to a reversed phase nano-LC–MS/MS analysis consisting of a Proxeon EASY-nLC 1000, an analytical column heater (40°C) and an LTQ-Orbitrap Elite. After the survey scans, the 20 most intense precursors were selected for subsequent CID or ETD-IT fragmentation. A programmed data-dependent decision tree determined the choice of the most appropriate technique for a selected precursor. In essence, doubly charged peptides were subjected to CID fragmentation and more highly charged peptides were fragmented using ETD. Raw data were processed with MaxQuant version 1.3.0.523, and the peptides were identified from the MS and MS/MS spectra searched against a concatenated forward-decoy Swissprot Homo sapiens database version 2012_09 (40,992 sequences) using the Andromeda search engine. The database search was performed with the following parameters: an initial mass tolerance of ±20 ppm for precursor masses; final mass tolerance of ±6 ppm: ±0.6 Da for CID and ETD-ion trap fragment ions, allowing two missed cleavages. Cysteine carbamidomethylation was used as a fixed modification and methionine oxidation, protein N-terminal acetylation and serine, threonine and tyrosine phosphorylation as variable modifications. For the identification, the false discovery rate was set to 0.01 for peptides, proteins and sites and the minimum peptide length allowed was six amino acids and a minimum peptide score of 60. The match between run feature was set on. A site localization probability of at least 0.75 and a score difference of at least 5 were used as threshold for the phosphoresidue localization. Normalization was performed by subtracting the median of log transformed intensities for each LC-MS/MS run.

Project description:Background: Preclinical studies showed thatmesenchymal stem cells (MSCs) ameliorate tau phosphorylation, amyloid-betaaccumulation, and inflammation in Alzheimer’s disease (AD) mouse models viasecretion of neurotrophic factors and cytokines. We aimed to identify CSFbiomarkers that can be used to predict or monitor the response to MSCs inpatients with AD. Methods: AD patients were injected withhuman umbilical cord blood-MSCs (n=22) or placebo (n=12). The cerebrospinalfluid (CSF) samples were collected at baseline, one day after the firstinjection, and one day after the third injection. The patients injected withMSCs were classified into good responder (GR) or poor responder (PR) groupsbased on the rate of changes in the ratio of total-tau and phosphorylated-tauin the CSF. We selected three typical participants in each group, and their CSFprotein levels were analyzed using liquid chromatography-tandem massspectrometry (LC-MS/MS). Results: In the LC-MS/MS analysis 1,667proteins were identified. 11 proteins showed significant differences betweenthe typical GR and PR at baseline. Based on their significance level and knownfunctions two proteins, reticulocalbin-3 (RCN3) and follistatin-related protein3 (FSTL3), were selected as potential biomarkers to predict MSC response. 173proteins showed significant change one day after the third injection comparedto the baseline in typical GR. We excluded 45 proteins that showed significantchange after the third injection compared to the baseline in the typical PR.Based on their significance level and known function, four proteins,scrapie-responsive protein 1 (SCRG1), neural proliferation and differentiationcontrol protein (NPDC1), apolipoprotein E (ApoE), and cystatin C (CysC), wereselected as potential biomarker to monitor MSC response. Additionally,functional analysis revealed that the increased CSF proteins after the thirdinjection compared to the baseline in the typical GR were associated withsynaptogenesis. Conclusions: This study identified twoproteins (RCN3 and FSTL3) that may be potential biomarkers for predicting MSCresponse and four proteins (SCRG1, NPDC1, ApoE, CysC) that may be potentialbiomarkers for monitoring MSC response in patients with AD. Further studies areneeded to validate our results.

Dataset Information

PGE2 signaling networks in T cells

Publications

Systems approach reveals distinct and shared signaling networks of the four PGE<sub>2</sub> receptors in T cells.

Similar Datasets

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