Role of miR-146a on Jurkat T cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: jingyi li
PROVIDER: E-GEOD-21132 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Screening the differetial expressed genes with Jurkat-146a(miR-146a over expression),Jurkat-sponge(miR-146a knockdown),Jurkat-FF3(vector control)
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Project description:The aim of this study was to analyze expression differences between murine splenic miR-146a deficient and miR-146a sufficient T cells after allogeneic stimulation in vitro.
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Project description:This study was designed to explore the role of miRNA-146a (miR-146a) and its target genes in the endothelial cells. In this study we have demonstrated that lipopolysaccharide (LPS) induced upregulation of miR-146a in the human umbilical vein endothelial cells (HUVEC) and the induction was blocked by the silencing of the toll-like receptors (TLRs) adaptor molecules MyD88 and nonspecific NF-M-NM-:B inhibitor BAY 11-7082. In addition, knockdown of miR-146a by transfection of the locked nucleic acid (LNA)-antimiR-146a significantly decreased the increased cell migration and tube formation induced by LPS. A combined analysis of the bioinformatics miRanda algorithms and the whole genome expression microarray of the immunoprecipitated Ago2 ribonucleoprotein complex identified 14 transcripts as the potential target genes. Subsequent transfection with miR-146a precursor pre-miR-146a into the HUVEC validated that the CARD10 was the target gene of the miR-146a both in the transcript and protein level. immunoprecipitation of RNA-induced silencing complexes (RISC) with an Ago2-specific monoclonal antibody followed by RNA extraction and subsequent quantification of mRNAs on microarrays was utilized to identify mRNAs that are associated with the RNA-silencing machinery and are therefore targets of cellular miRNAs. In brief, 100 M-NM-<g of total protein was diluted with 200 M-NM-<L of PBS buffer (pH 7.4). For each sample, 25 M-NM-<L of Protein A/G plus agarose (Santa Cruz, Dallas, TX) was washed with PBS and incubated with 2 M-NM-<g of rabbit anti-Ago2 (Abcam, Cambridge, MA) or rabbit normal IgG (Santa Cruz) antibodies for 2 h at 4M-BM-0C. The beads containing the immobilized anti-Ago2 antibody were then added to 400 M-NM-<L of diluted serum and incubated for 4 h at 4M-BM-0C. The beads were washed 3 times with 1% NT-2 buffer (1% Nonidet P-40, 50 mM Tris-HCl, pH 7.4, 150 mM NaCl, and 2 mM EDTA) and the mixture was split in half. Each sample was eluted in 600 M-NM-<L of lysis/binding buffer for total RNA extraction and subsequent whole genome array experiment. Microarray analyses. Microarray experiments were performed on the total RNA samples from the Ago2 immunoprecipitate (pooling from n=4 in each group) from 1M-CM-^W106 HUVEC with or without 1 M-NM-<g/mL LPS treatment for 24 h in the presence or absence of miR-146a knockdown by LNA-antimiR-146a or LNA-control, respectively. The procedures were carried out following the manufacturerM-bM-^@M-^Ys protocols. Briefly, 0.5 M-NM-<g of total RNA was amplified by a Fluorescent Linear Amplification Kit (Agilent Technologies) and labeled with Cy3-CTP or Cy5-CTP (PerkinElmer, Waltham, MA) during the in vitro transcription process. RNA from the experimental groups and control group was labeled by Cy5 and Cy3, respectively. A total of 0.825 M-NM-<g of Cy-labled cRNA was fragmented to an average size of about 50-100 nucleotides by incubation with fragmentation buffer (Agilent Technologies) at 60oC for 30 minutes. Correspondingly fragmented labeled cRNA is then pooled and hybridized to Agilent Whole Human Genome 4x44k oligo microarray (Agilent Technologies) at 60M-BM-0C for 17 h. After washing and drying by nitrogen gun blowing, microarrays are scanned with an Agilent microarray scanner (Agilent Technologies) at 535 nm for Cy3 and 625 nm for Cy5. Scanned images are analyzed by Feature extraction software 9.5.3 (Agilent Technologies), an image analysis and normalization software is used to quantify signal and background intensity for each feature, substantially normalized the data by rank-consistency-filtering LOWESS method.
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