Early immune response and regulation of IL-2 receptor subunits
University of California, Berkeley, Berkeley, California, United States Cellular Signalling
(Impact Factor: 4.32).
09/2005; 17(9):1111-24. DOI: 10.1016/j.cellsig.2004.12.016
Affymetrix oligonucleotide arrays were used to monitor expression of 8796 genes and probe sets in activated T-cells; analysis revealed that 217 genes were significantly upregulated within 4 h. Induced genes included transcription factors, cytokines and their receptor genes. Analysis by semi-quantitative RT-PCR confirmed the significant induction of IL-2, IL-2R(gamma) and IL-2R(alpha). Forty-eight of the 217 induced genes are known to or predicted to be regulated by a CRE promoter/enhancer. We found that T-cell activation caused a significant increase in CREB phosphorylation furthermore, inhibition of the PKC pathway by GF109203 reduced CREB activation by 50% and inhibition of the PKA pathway caused a total block of CREB phosphorylation and significantly reduced IFN(gamma), IL-2 and IL-2R(alpha) gene expression by approximately 40% (p<0.001). PKC(theta) plays a major role in T-cell activation: inhibition of PKC significantly reduced the expression of IFN(gamma), IL-2 and IL-2R(alpha). Since PKC blocked activation of CREB, we studied potential cross-talk between the PKC and the PKA/MAPK pathways, PMA-stimulated Jurkat cells were studied with specific signal pathway inhibitors. Extracellular signal-regulated kinase-2 (ERK2) pathway was found to be significantly activated greater than seven-fold within 30 min; however, there was little activation of ERK-1 and no activation of JNK or p38 MAPK. Inhibition of the PKA pathway, but not the PKC pathway, resulted in inhibition of ERK1/2 activation at all time points, inhibition of MEK1 and 2 significantly blocked expression of IL-2 and IL-2R(alpha). Gene expression of IL-2R(alpha) and IFN(gamma) was dependent on PKA in S49 wt cells but not in kin- mutants. Using gel shift analysis, we found that forskolin activation of T-cells resulted in activation of AP1 sites; this increase in nuclear extract AP1 was significantly blocked by MEK1 inhibitor U0126. Taken together, these results suggest that the PKA in addition to PKC and MAPK pathways plays a role in early T-cell activation and induction of IL-2, IL-2R(alpha) and IFN(gamma) gene expression.
Available from: Masachika Senba
- "Reverse transcription–polymerase chain reaction (RT-PCR) was carried out as described previously . The sequences of the primers for IκB-ζ, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) , interleukin-2 receptor α chain (IL-2Rα) , Bcl3 , GBP-1 , signal transducer and activator of transcription 1 (STAT1) , SLAM family member 7 (SLAMF7) , Tax in HTLV-I–infected T cell lines and ATL cells , and Tax in JPX-9 cells  are summarized in Table 1. PCR was halted during the exponential phase of DNA amplification, and the reaction products were fractionated on agarose gels and visualized by ethidium bromide staining. "
[Show abstract] [Hide abstract]
ABSTRACT: Human T cell leukemia virus type I (HTLV-I) is the etiologic agent of adult T cell leukemia (ATL) and various inflammatory disorders including HTLV-I-associated myelopathy/tropical spastic paraparesis. HTLV-I oncoprotein Tax is known to cause permanent activation of many cellular transcription factors including nuclear factor-κB (NF-κB), cyclic adenosine 3',5'-monophosphate response element-binding protein, and activator protein 1 (AP-1). Here, we show that NF-κB-binding cofactor inhibitor of NF-κB-ζ (IκB-ζ) is constitutively expressed in HTLV-I-infected T cell lines and ATL cells, and Tax transactivates the IκB-ζ gene, mainly through NF-κB. Microarray analysis of IκB-ζ-expressing uninfected T cells demonstrated that IκB-ζ induced the expression of NF-κB. and interferon-regulatory genes such as B cell CLL/lymphoma 3 (Bcl3), guanylate-binding protein 1, and signal transducer and activator of transcription 1. The transcriptional activation domain, nuclear localization signal, and NF-κB-binding domain of IκB-ζ were required for Bcl3 induction, and IκB-ζ synergistically enhanced Tax-induced Bcl3 transactivation in an NF-κB-dependent manner. Interestingly, IκB-ζ inhibited Tax-induced NF-κB, AP-1 activation, and HTLV-I transcription. Furthermore, IκB-ζ interacted with Tax in vitro and this interaction was also observed in an HTLV-I-transformed T cell line. These results suggest that IκB-ζ modulates Tax-dependent and Tax-independent gene transcription in T cells. The function of IκB-ζ may be of significance in ATL genesis and pathogenesis of HTLV-I-associated diseases.
Available from: Paolo Degan
- "The senescence-like phenotype  in which cells thrive in a state of apparent idleness  observed in cells exposed to modeled and real microgravity, is however hiding important changes in the expression of multiple genes. Microgravity has selective effects on cell viability and proliferation , on gene transcription, in the stability of the transcripts  and in the modulation of the immune response [5,6]. Several studies employed microarray technologies to characterize the gene expression of lymphocytes exposed to modeled and real microgravity [7,8]. "
[Show abstract] [Hide abstract]
ABSTRACT: Whether microgravity might influence tumour growth and carcinogenesis is still an open issue. It is not clear also if and how normal and transformed cells are differently solicited by microgravity. The present study was designed to verify this issue.
Two normal, LB and HSC93, and two transformed, Jurkat and 1310, lymphoblast cell lines were used as representative for the two conditions. Two lymphoblast lines from Fanconi's anemia patients group A and C (FA-A and FA-C, respectively), along with their isogenic corrected counterparts (FA-A-cor and FA-C-cor) were also used. Cell lines were evaluated for their proliferative ability, vitality and apoptotic susceptibility upon microgravity exposure in comparison with unexposed cells. Different parameters correlated to energy metabolism, glucose consumption, mitochondrial membrane potential (MMP), intracellular ATP content, red-ox balance and ability of the cells to repair the DNA damage product 8-OHdG induced by the treatment of the cells with 20 mM KBrO3 were also evaluated.
Transformed Jurkat and 1310 cells appear resistant to the microgravitational challenge. On the contrary normal LB and HSC93 cells display increased apoptotic susceptibility, shortage of energy storages and reduced ability to cope with oxidative stress. FA-A and FA-C cells appear resistant to microgravity exposure, analogously to transformed cells. FA corrected cells did shown intermediate sensitivity to microgravity exposure suggesting that genetic correction does not completely reverts cellular phenotype.
In the light of the reported results microgravity should be regarded as an harmful condition either when considering normal as well as transformed cells. Modeled microgravity and space-based technology are interesting tools in the biomedicine laboratory and offer an original, useful and unique approach in the study of cellular biochemistry and in the regulation of metabolic pathways.
Available from: PubMed Central
- "Gene expression analysis of T-cell activation at a single timepoint has been reported [8,9], and using a single donor sample, the gene expression patterns of T-cell activation with or without co-stimulation by anti-CD28 antibody were compared [10,11]. However, to the best of our knowledge, the genome-scale donor-independent temporal gene expression analysis of primary, human T-cell activation has not been reported, and this is the goal of this study. "
[Show abstract] [Hide abstract]
ABSTRACT: T-cell activation is an essential step of the immune response and relies on the tightly controlled orchestration of hundreds of genes/proteins, yet the cellular and molecular events underlying this complex process are not fully understood, especially at the genome-scale. Significantly, a comparative genome-scale transcriptional analysis of two T-cell subsets (CD4+ and CD8+) against each other and against the naturally mixed population (CD3+ cells) remains unexplored.
Comparison of the microarray-based gene expression patterns between CD3+ T cells, and the CD4+ and CD8+ subsets revealed largely conserved, but not identical, transcriptional patterns. We employed a Gene-Ontology-driven transcriptional analysis coupled with protein abundance assays in order to identify novel T-cell activation genes and cell-type-specific genes associated with the immune response. We identified potential genes involved in the communication between the two subsets (including IL23A, NR4A2, CD83, PSMB2, -8, MIF, IFI16, TNFAIP1, POU2AF1, and OTUB1) and would-be effector-function-specific genes (XCL2, SLAMF7, TNFSF4, -5, -9, CSF3, CD48 and CD244). Chemokines induced during T-cell activation, but not previously identified in T cells, include CCL20, CXCL9, -10, -11 (in all three populations), and XCL2 (preferentially in CD8+ T cells). Increased expression of other unexpected cytokines (GPI, OSM and MIF) suggests their involvement in T-cell activation with their functions yet to be examined. Differential expression of many receptors, not previously reported in the context of T-cell activation, including CCR5, CCR7, IL1R2, IL1RAP, IL6R, TNFRSF25 and TNFRSF1A, suggests their role in this immune process. Several receptors involved in TCR activation (CD3D, CD3G, TRAT1, ITGAL, ITGB1, ITGB2, CD8A and B (CD8+ T-cell specific) along with LCK, ZAP70 and TYROBP were synchronously downregulated. Members of cell-surface receptors (HLA-Ds and KLRs), none previously identified in the context of T-cell activation, were also downregulated.
This comparative genome-scale, transcriptional analysis of T-cell activation in the CD4+ and CD8+ subsets and the mixed CD3+ populations made possible the identification of many immune-response genes not previously identified in the context of T-cell activation. Significantly, it made possible to identify the temporal patterns of many previously known T-cell activation genes, and also identify genes implicated in effector functions of and communication between CD4+ and CD8+ T cells.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.