Literature DB >> 12808112

Comparative microarray analysis of gene expression during activation of human peripheral blood T cells and leukemic Jurkat T cells.

Zhaosheng Lin1, G Chris Fillmore, Tae-Hyun Um, Kojo S J Elenitoba-Johnson, Megan S Lim.   

Abstract

Activation of T cells involves a complex cascade of signal transduction pathways linking T-cell receptor engagement at the cell membrane to the transcription of multiple genes within the nucleus. The T-cell leukemia-derived cell line Jurkat has generally been used as a model system for the activation of T cells. However, genome-wide comprehensive studies investigating the activation status, and thus the appropriateness, of this cell line for this purpose have not been performed. We sought to compare the transcriptional profiles of phenotypically purified human CD2(+) T cells with those of Jurkat T cells during T-cell activation, using cDNA microarrays containing 6912 genes. About 300 genes were up-regulated by more than 2-fold during activation of both peripheral blood (PB) T cells and Jurkat T cells. The number of down-regulated genes was significantly lower than that of up-regulated genes. Only 79 genes in PB T cells and 37 genes in Jurkat T cells were down-regulated by more than 2-fold during activation. Comparison of gene expression during activation of Jurkat and PB T cells revealed a common set of genes that were up-regulated, such as Rho GTPase-activating protein 1, SKP2, CDC25A, T-cell specific transcription factor 7, cytoskeletal proteins, and signaling molecules. Genes that were commonly down-regulated in both PB T cells and Jurkat T cells included CDK inhibitors (p16, p19, p27), proapoptotic caspases, and the transcription factors c-fos and jun-B. After activation, 71 genes in PB T cells and only 3 genes in Jurkat T cells were up-regulated 4-fold or more. Of these up-regulated genes and expressed sequence tags, 44 were constitutively expressed at high levels in nonactivated Jurkat cells. Quantitative real-time RT-PCR analysis confirmed our microarray data. Our findings indicate that although there is significant overlap in the activation-associated transcriptional profiles in PB T cells compared with Jurkat T cells, there is a subset of genes showing differential expression patterns during the activation of the two cell types.

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Year:  2003        PMID: 12808112     DOI: 10.1097/01.lab.0000073130.58435.e5

Source DB:  PubMed          Journal:  Lab Invest        ISSN: 0023-6837            Impact factor:   5.662


  11 in total

1.  Alternative splicing networks regulated by signaling in human T cells.

Authors:  Nicole M Martinez; Qun Pan; Brian S Cole; Christopher A Yarosh; Grace A Babcock; Florian Heyd; William Zhu; Sandya Ajith; Benjamin J Blencowe; Kristen W Lynch
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Review 2.  T-helper cell intrinsic defects in lupus that break peripheral tolerance to nuclear autoantigens.

Authors:  Syamal K Datta; Li Zhang; Luting Xu
Journal:  J Mol Med (Berl)       Date:  2005-01-04       Impact factor: 4.599

3.  Tetraspanin CD81 provides a costimulatory signal resulting in increased human immunodeficiency virus type 1 gene expression in primary CD4+ T lymphocytes through NF-kappaB, NFAT, and AP-1 transduction pathways.

Authors:  Mélanie R Tardif; Michel J Tremblay
Journal:  J Virol       Date:  2005-04       Impact factor: 5.103

4.  Global analysis of alternative splicing during T-cell activation.

Authors:  Joanna Y Ip; Alan Tong; Qun Pan; Justin D Topp; Benjamin J Blencowe; Kristen W Lynch
Journal:  RNA       Date:  2007-02-16       Impact factor: 4.942

5.  Implementation of exon arrays: alternative splicing during T-cell proliferation as determined by whole genome analysis.

Authors:  Toni Whistler; Cheng-Feng Chiang; William Lonergan; Mark Hollier; Elizabeth R Unger
Journal:  BMC Genomics       Date:  2010-09-14       Impact factor: 3.969

6.  Ovalbumin Antigen-Specific Activation of Human T Cell Receptor Closely Resembles Soluble Antibody Stimulation as Revealed by BOOST Phosphotyrosine Proteomics.

Authors:  Xien Yu Chua; Arthur Salomon
Journal:  J Proteome Res       Date:  2021-05-21       Impact factor: 5.370

7.  Human promoter genomic composition demonstrates non-random groupings that reflect general cellular function.

Authors:  Markey C McNutt; Ron Tongbai; Wenwu Cui; Irene Collins; Wendy J Freebern; Idalia Montano; Cynthia M Haggerty; Gvr Chandramouli; Kevin Gardner
Journal:  BMC Bioinformatics       Date:  2005-10-18       Impact factor: 3.169

8.  T-cell activation and early gene response in dogs.

Authors:  Sally-Anne Mortlock; Jerry Wei; Peter Williamson
Journal:  PLoS One       Date:  2015-03-24       Impact factor: 3.240

9.  Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) Web-Server.

Authors:  Carla Proietti; Martha Zakrzewski; Thomas S Watkins; Bernard Berger; Shihab Hasan; Champa N Ratnatunga; Marie-Jo Brion; Peter D Crompton; John J Miles; Denise L Doolan; Lutz Krause
Journal:  Sci Rep       Date:  2016-12-06       Impact factor: 4.379

10.  Genome-wide analysis of immune activation in human T and B cells reveals distinct classes of alternatively spliced genes.

Authors:  Yevgeniy A Grigoryev; Sunil M Kurian; Aleksey A Nakorchevskiy; John P Burke; Daniel Campbell; Steve R Head; Jun Deng; Aaron B Kantor; John R Yates; Daniel R Salomon
Journal:  PLoS One       Date:  2009-11-19       Impact factor: 3.240

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