Cell-type and Donor-specific Transcriptional Responses to Interferon-α
2002; Elsevier BV; Volume: 277; Issue: 51 Linguagem: Inglês
10.1074/jbc.m205571200
ISSN1083-351X
AutoresJF Schlaak, Catharien M. U. Hilkens, Ana P. Costa‐Pereira, Birgit Strobl, Fritz Aberger, Anna‐Maria Frischauf, Ian M. Kerr,
Tópico(s)Immune Cell Function and Interaction
ResumoA sensitive, specific, reproducible, robust, and cost-effective customized cDNA array system based on established nylon membrane technology has been developed for convenient multisample expression profiling for several hundred genes of choice. The genes represented are easily adjusted (depending on the availability of corresponding cDNAs) and the method is accordingly readily applicable to a wide variety of systems. Here we have focused on the expression profiles for interferon-α2a, the most widely used interferon for the treatment of viral hepatitis and malignancies, in primary cells (peripheral blood mononuclear cells, T cells, and dendritic cells) and cell lines (Kit255, HT1080, HepG2, and HuH7). Of 150 genes studied, only six were consistently induced in all cell types and donors, whereas 74 genes were induced in at least one cell type. IRF-7 was identified as the only gene exclusively induced in the hematopoietic cells. No gene was exclusively induced in the nonhematopoietic cell lines. In T cells 12, and in dendritic cells, 25 genes were induced in all donors whereas 45 and 42 genes, respectively, were induced in at least one donor. The data suggest that signaling through IFN-α2 can be substantially modulated to yield significant cell-type and donor-specific qualitative and quantitative differences in gene expression in response to this cytokine under highly standardized conditions. A sensitive, specific, reproducible, robust, and cost-effective customized cDNA array system based on established nylon membrane technology has been developed for convenient multisample expression profiling for several hundred genes of choice. The genes represented are easily adjusted (depending on the availability of corresponding cDNAs) and the method is accordingly readily applicable to a wide variety of systems. Here we have focused on the expression profiles for interferon-α2a, the most widely used interferon for the treatment of viral hepatitis and malignancies, in primary cells (peripheral blood mononuclear cells, T cells, and dendritic cells) and cell lines (Kit255, HT1080, HepG2, and HuH7). Of 150 genes studied, only six were consistently induced in all cell types and donors, whereas 74 genes were induced in at least one cell type. IRF-7 was identified as the only gene exclusively induced in the hematopoietic cells. No gene was exclusively induced in the nonhematopoietic cell lines. In T cells 12, and in dendritic cells, 25 genes were induced in all donors whereas 45 and 42 genes, respectively, were induced in at least one donor. The data suggest that signaling through IFN-α2 can be substantially modulated to yield significant cell-type and donor-specific qualitative and quantitative differences in gene expression in response to this cytokine under highly standardized conditions. Type I (predominantly α and β) and type II (γ) IFNs 1The abbreviations used are: IFN, interferon; IRF, interferon regulatory factor; JAK, Janus kinase; STAT, signal transducer and activator of transcription; DC, dendritic cell; PBMC, peripheral blood mononuclear cells; TC, peripheral blood T cells; rIL, recombinant interleukin; LB, Luria-Bertani; RPA, RNase protection assay; SNP, single nucleotide polymorphism; ISGF, interferon-stimulated gene factorplay a central role in mediating antiviral, antiproliferative, and immunomodulatory responses. The pathways that are involved in IFN-induced gene expression include specific type I and II receptors, JAKs and STATs (1Stark G.R. Kerr I.M. Williams B.R. Silverman R.H. Schreiber R.D. Annu. Rev. Biochem. 1998; 67: 227-264Crossref PubMed Scopus (3388) Google Scholar). Upon ligand binding, STATs form homo- or heterodimers through phosphotyrosine-SH2 interactions following activation by JAKs. Whereas STAT dimers bind to γ-activated sequence elements, both STAT1–2 heterodimers and STAT1 homodimers bind to p48 (ISGF-3γ/IRF-9) resulting in a trimer that binds to interferon-stimulated regulatory elements in promoters of responsive genes (2Bluyssen A.R. Durbin J.E. Levy D.E. Cytokine Growth Factor Rev. 1996; 7: 11-17Crossref PubMed Scopus (118) Google Scholar). To date the gene expression profile induced by IFN-α2 has been studied predominantly in fibrosarcoma and melanoma cell lines (3Der S.D. Zhou A. Williams B.R. Silverman R.H. Proc. Natl. Acad. Sci. U. S. A. 1998; 95: 15623-15628Crossref PubMed Scopus (1543) Google Scholar, 4Certa U. Seiler M. Padovan E. Spagnoli G.C. Br. J. Cancer. 2001; 85: 107-114Crossref PubMed Scopus (47) Google Scholar). Little is known about the transcriptional profiles for other cell lines and nontransformed cells or of donor-specific differences. The definition of cell-type and donor-specific quantitative and qualitative differences is, however, central to a full understanding of the biology of the IFNs and their mechanisms of action. Approaches through expression profiling are also of potential clinical importance. IFN-α2 is widely used in the treatment of diseases including chronic viral hepatitis B and C and several malignancies (5McHutchison J.G. Gordon S.C. Schiff E.R. Shiffman M.L. Lee W.M. Rustgi Goodman Z.D. Ling M.H. Cort S. Albrecht J.K. N. Engl. J. Med. 1998; 339: 1485-1492Crossref PubMed Scopus (3366) Google Scholar,6Niederau C. Heintges T. Lange S. Goldmann G. Niederau C.M. Mohr L. Haeussinger D. N. Engl. J. Med. 1996; 334: 1422-1427Crossref PubMed Scopus (805) Google Scholar). Only a minority of patients, however, respond to this therapy (7Kjaergard L.L. Krogsgaard K. Gluud C. Br. Med. J. 2001; 323: 1151-1155Crossref PubMed Scopus (85) Google Scholar). The definition of gene expression profiles that correspond to "response" or "nonresponse" should ultimately result in further optimization of IFN treatment. Genes that are abnormally expressed in "nonresponders" to IFN-α2 may define novel pharmacological targets and provide further insight into the pathophysiology of the underlying disease. To address these questions it is critical to use read-out systems that cover expression from a large number of genes. Technological advances have made possible the simultaneous detection of thousands of gene transcripts using small tissue or cell samples. These technologies include DNA chips (high density oligoarrays (8Lockhart D.J. Dong H. Byrne M.C. Follettie M.T. Gallo M.V. Chee M.S. Mittmann M. Wang C. Kobayashi M. Horton H. Brown E.L. Nat. Biotechnol. 1996; 14: 1675-1680Crossref PubMed Scopus (2818) Google Scholar, 9Lipshutz R.J. Fodor S.P. Gingeras T.R. Lockhart D.J. Nat. Genet. 1999; 21: 20-24Crossref PubMed Scopus (1868) Google Scholar) or microarrays (10Schena M. Shalon D. Davis R.W. Brown P.O. Science. 1995; 270: 467-470Crossref PubMed Scopus (7667) Google Scholar)), differential display (11Liang P. Pardee A.B. Science. 1992; 257: 967-971Crossref PubMed Scopus (4707) Google Scholar), differential cDNA arrays (12Pietu G. Alibert O. Guichard V. Lamy B. Bois F. Leroy E. Mariage-Sampson R. Houlgatte R. Soularue P. Auffray C. Genome Res. 1996; 6: 492-503Crossref PubMed Scopus (160) Google Scholar, 13Rast J.P. Amore G. Calestani C. Livi C.B. Ransick A. Davidson E.H. Dev. Biol. 2000; 228: 270-286Crossref PubMed Scopus (82) Google Scholar, 14Zhang Q.H. Ye M. Wu X.Y. Ren S.X. Zhao M. Zhao C.J. Fu G. Shen Y. Fan H.Y. Lu G. Zhong M. Xu X.R. Han Z.G. Zhang J.W. Tao J. Huang Q.H. Zhou J. Hu G.X. Gu J. Chen S.J. Chen Z. Genome Res. 2000; 10: 1546-1560Crossref PubMed Scopus (161) Google Scholar), serial analysis of gene expression (15Velculescu V.E. Zhang L. Vogelstein B. Kinzler K.W. Science. 1995; 270: 484-487Crossref PubMed Scopus (3612) Google Scholar), and expressed sequence tag data base comparison (16Vasmatzis G. Essand M. Brinkmann U. Lee B. Pastan I. Proc. Natl. Acad. Sci. U. S. A. 1998; 95: 300-304Crossref PubMed Scopus (138) Google Scholar). These methods have been used to analyze gene expression in colon, breast, ovarian, and renal cell carcinomas, multiple sclerosis lesions, leukemic cells, and to monitor gene expression in resting, activated, and anergic lymphocytes (17Whitney L.W. Becker K.G. Tresser N.J. Caballero-Ramos C.I. Munson P.J. Prabhu V.V. Trent J.M. McFarland H.F. Biddison W.E. Ann. Neurol. 1999; 46: 425-428Crossref PubMed Scopus (223) Google Scholar, 18Alon U. Barkai N. Notterman D.A. Gish K. Ybarra S. Mack D. Levine A.J. Proc. Natl. Acad. Sci. U. S. A. 1999; 96: 6745-6750Crossref PubMed Scopus (3370) Google Scholar, 19Nacht M. Ferguson A.T. Zhang W. Petroziello J.M. Cook B.P. Gao Y.H. Maguire S. Riley D. Coppola G. Landes G.M. Madden S.L. Sukumar S. Cancer Res. 1999; 59: 5464-5470PubMed Google Scholar, 20Wang K. Gan L. Jeffery E. Gayle M. Gown A.M. Skelly M. Nelson P.S. Ng W.V. Schummer M. Hood L. Mulligan J. Gene (Amst.). 1999; 229: 101-108Crossref PubMed Scopus (286) Google Scholar, 21Moch H. Schraml P. Bubendorf L. Mirlacher M. Kononen J. Gasser T. Mihatsch M.J. Kallioniemi O.P. Sauter G. Am. J. Pathol. 1999; 154: 981-986Abstract Full Text Full Text PDF PubMed Scopus (372) Google Scholar, 22Golub T.R. Slonim D.K. Tamayo P. Huard C. Gaasenbeek M. Mesirov J.P. Coller H. Loh M.L. Downing J.R. Caligiuri M.A. Bloomfield C.D. Lander E.S. Science. 1999; 286: 531-537Crossref PubMed Scopus (9261) Google Scholar, 23Alizadeh A. Eisen M. Botstein D. Brown P.O. Staudt L.M. J. Clin. Immunol. 1998; 18: 373-379Crossref PubMed Scopus (97) Google Scholar, 24Marrack P. Mitchell T. Hildeman D. Kedl R. Teague T.K. Bender J. Rees W. Schaefer B.C. Kappler J. Curr. Opin. Immunol. 2000; 12: 206-209Crossref PubMed Scopus (47) Google Scholar, 25Glynne R. Akkaraju S. Healy J.I. Rayner J. Goodnow C.C. Mack D.H. Nature. 2000; 403: 672-676Crossref PubMed Scopus (148) Google Scholar). Although large scale array techniques are particularly useful to give a broad view of gene expression changes between samples and to discover "novel" genes that are induced by a particular cytokine or drug, they are, in general, costly, labor intensive, and unsuitable for the assay of multiple samples necessary for the detailed analysis of cytokine responses. Appropriate, customized, nylon membrane-based filter arrays, however, are attractive for precisely such analyses. Here, we describe a customized cDNA array system that is specific, sensitive, robust, reproducible, convenient to use, and cost-effective. Using this technology we have defined significant quantitative and qualitative differences in the response of cells of hematopoietic and nonhematopoietic origin to IFN-α2a under highly standardized conditions. Substantial quantitative and qualitative donor-specific differences for T cells and DC were observed in response to this cytokine. Human HT1080 (fibrosarcoma), HepG2 (hepatoma), HuH7 (hepatoma), and Kit255 (T cell lymphoma) were cultured in Dulbecco's modified Eagle's medium supplemented with 5% fetal calf serum, 2 mm l-glutamine, penicillin, and streptomycin at 37 °C in a humidified atmosphere containing 10% CO2. Recombinant human IFN-α2a was provided by Roche Molecular Biochemicals. The human IL-2-dependent T cell line Kit255 (26Hori T. Uchiyama T. Tsudo M. Umadome H. Ohno H. Fukuhara S. Kita K. Uchino H. Blood. 1987; 70: 1069-1072Crossref PubMed Google Scholar) was maintained in RPMI 1640 supplemented with 10% heat-inactivated fetal calf serum and 20 ng/ml rIL-2 (Proleukin, Chiron, Emeryville, CA). Prior to treatment of cells with IFN-α2, Kit255 cells were washed and then cultured for 48 h in the absence of rIL-2. PBMC were isolated from buffy coat by density centrifugation on Lymphoprep (Nycomed, Norway). To obtain TC, PBMC were activated with phytohemagglutinin (Murex, UK) and maintained in RPMI 1640 supplemented with 10% inactivated fetal calf serum and human rIL-2 (20 ng/ml) for 1 week. Prior to treatment of cells with IFN-α2, TC were washed and then cultured for 48 h in the absence of rIL-2. To generate DC, monocytes were isolated from PBMC by magnetic cell sorting using anti-CD14-conjugated magnetic microbeads (Miltenyi Biotec, Cologne, Germany) and cultured for 6 days in RPMI 1640 supplemented with 10% inactivated fetal calf serum, 50 ng/ml granulocyte-macrophage colony-stimulating factor, and 50 ng/ml IL-4 (both from R&D Systems). All experiments were performed under stringent endotoxin-free conditions. Total RNA was isolated from cells using Trizol (Invitrogen) according to the instructions of the manufacturer. RNA quantity and quality was analyzed by spectrophotometry and additional visualization by agarose gel electrophoresis. Genes of interest were selected from the UniGene data base (www.ncbi.nlm.nih.gov/UniGene/Hs.Home.html). 5′ IMAGE clones with 0.5–0.8 kb length were chosen and ordered from the Human Genome Mapping Project, Hinxton, UK (www.hgmp.mrc.ac.uk). Bacteria were streaked out onto 1.5% LB-agar plates containing 75 μg/ml ampicillin and cultured overnight at 37 °C. Single clones were picked, transferred to 96-well plates with 200 μl of LB medium containing 75 μg/ml ampicillin and 10% glycerol, and grown overnight at 37 °C in an incubator without shaking. A 1/10 dilution of individual clones was set up in 96-well plates by adding 10 μl of bacterial culture to 90 μl of sterile ddH2O. Throughout the duration of the experiments, the number of genes present on the filters was constantly extended from 150 to 231 genes (Fig. 1 A), reflecting the flexibility of the method. The data presented here are, however, restricted to the initial 150 genes (Table I).Table IComplete list of genes investigated in this studyGeneAccession No.GeneAccession No.GeneAccession No.2–5-A synthetaseX02875HouU32849NKC-4M598075′ NucleotidaseX55740HPAST proteinAF001434p48/ISGF-3γ/IRF-9M8750360 S Ribosomal protein L11U43522Hypoxia-induced factor-1U22431Phospholipid scramblase 1AF0986426–16U22970ICAM-1M24283PIAS x-βAF07795472-kDa type IV collagenaseJ03210ICSB 1M91196Pim-1M167509–27J04164IFI-16M63838PKRU50648α-1-AntiproteinaseK01396IFI-41L22342Placental calcium-binding proteinM80563Auto Ag SS-A/RoNM003141IFN-αR1J03171PLOD2U84573BST2D28137IFN-αR2L42243PML-1M79462BTG1X61123IFN-γM29383PPP3CAL14778CalcyclinJ02763IFN-γR1J03143PRAMEU65011CASP proteinAJ006470IFN-γR2U05875Prolyl-4-hydroxylase αM24486Caspase 8X98172IFP-35U72882Proton-ATPase-like proteinD89052Caspase-1M87507IFP-53X62570Putative serine/threonine kinaseG833810Catecholo-methyltransferaseM58525IL-1αM28983Pyridoxal kinaseU89606Cathepsin DM11233IL-10RαU00672RAP46/Bag-1Z35491CCR1L09230IL-10RβZ17227RbAp48X74262CCR5U54994IL-12Rβ2U64198ReticulocalbinD42073CIITAX74301IL-15U14407RHO GDP-diss. Inh. 2L20688c-junJ04111IL-15RαU31628RING12X62741c-mycL00058IL-18D49950RING4X57522Collagen α1 (I)Z74615IL-18-binding proteinAB019504Smad1U59423Collagen α2 (I)J03464IL-2RαK03122Smad2AF027964Collagen, type XVI, α1M92642IL-8M28130Smad4U44378Compl. compound C1rJ04080Ind.-2,3-dioxygenaseM34455Smad5U73825COX17L77701iNOS2AU20141Smad6U59914CTRL-1X71877Int-6U62962Smad7AF015261CXCR4AF005058Integrin β7M62880Smooth muscle α-actinJ00073DEAD box binding protein 1AF077951IL-6X04602SOCS1N91935DEAD-box protein p72U59321IP-10X02530SOCS2AF020590DestrinS65738IP-30J03909SOCS3AB004904DR-αJ00194IRF-1L05072SOCS4AB006968E2F-1U47677IRF-2X15949SPARCJ03040Elastase 2M34379IRF-7U73036StanninNM003498ERMX76184ISG-15M13755STAT1M97935F-actin capping proteinU56637ISG-56KM24594STAT2M97934Farnesyl pyrophosphateJ05262KIAA0129D50919STAT4L78440FAS/Apo-1M67454KIAA0336NM014635STAT5AL41142FK506-binding protein 6AF038847LIPAU04285STAT5BU47686Folate receptorX62753LMP-2X66401STAT6U16031Galectin-1J04456LMP-7Z14982Succinyl-CoA ligaseAF058953γ-ActinX04098L-selectinM25280TGF-βR1L11695γ-SynerginNM007247MEN1U93237TGF-βR2D50683GATA 3X58072MigX72755TGF-βR3L07594GBP-1M55542Mixed lineage kinase 2X90846TRAILU37518GBP-2M55543MMP-1M13509TransferrinM12530Granzyme BM17016MxAM33882TransthyretinD00096HCV-associated p44D28915MxBM30818TRIP14L40387HLA II Ag DP1M83664Neural cell adhesion moleculeM74387TTF2AF073771HLA-EX56841NF-IL-6X52560VEGF-CU43142Genes of interest were selected from the UniGene data base. These genes comprise known ISGs and genes of intrinsic interest that might or might not be induced by IFNs in different cell systems. They include genes involved in cell proliferation, immune responses, and the responses to a variety of cytokines. 5′ IMAGE clones with 0.5–0.8 kb length were chosen and obtained from the Human Genome Mapping Project. Open table in a new tab Genes of interest were selected from the UniGene data base. These genes comprise known ISGs and genes of intrinsic interest that might or might not be induced by IFNs in different cell systems. They include genes involved in cell proliferation, immune responses, and the responses to a variety of cytokines. 5′ IMAGE clones with 0.5–0.8 kb length were chosen and obtained from the Human Genome Mapping Project. 30-μl aliquots from the 10-fold diluted bacterial cultures were transferred into PCR strips on ice. The cDNA inserts were amplified in the presence of 50 mm KCl, 10 mm Tris, pH 9.0, 0.1% Triton X-100, 1.5 mm MgCl2, 0.2 mm of each of the deoxynucleotide triphosphates, and 50 units of Taqpolymerase using the following conditions: initial denaturation 94 °C, 3 min; denaturation 94 °C, 40 s; annealing 55 °C, 30 s; elongation 72 °C, 1 min for 30 cycles followed by a final elongation at 72 °C, 7 min using the M13 forward primer (5′-GTAAAACGACGGCCAGT-3′) and the M13 reverse primer (5′-CAGGAAACAGCTATGAC-3′). The PCR-amplified DNA was diluted 1/2 with Tris/EDTA, pH 8.0, in round-bottom 96-well plates, and stored at −20 °C. This DNA was used for spotting onto nylon membranes. To confirm the identity of the IMAGE clones, DNA was PCR amplified in 50-μl reactions, purified (QIAquick PCR purification kit, Qiagen, Crawley, UK), and sequenced (ABI Prism, Applied Biosystems, Foster City, CA). Membranes (Hybond N+,Amersham Biosciences) were cut (12.5 × 8 cm), placed on top of one 3MM sheet (12.5 × 8 cm) and assembled on an aluminum board using a registration device (V&P Scientific, San Diego, CA, catalog number VP382). 96-pin replicators (V&P Scientific, catalog number VP409) were treated with surfactant (V&P Scientific, catalog number VP110) prior to use according to the manufacturer's instructions. Library copiers (V&P Scientific, catalog number VP381) were used for exact positioning of the replicator on the 96-well plates containing the amplified IMAGE clones. DNA was then transferred from 96-well plates to the membranes using 96-pin replicators (1 stroke). Each clone was spotted in triplicate. Membranes were dried overnight at room temperature. Batches of four membranes were transferred to plastic boxes (20 × 20 × 5 cm) and the DNA was denatured in 1 liter of 0.66 m NaCl, 0.5 m NaOH for 10 min at room temperature. The membranes were washed in 1 liter of deionized water, neutralized (40 mmNa2HPO4/NaH2PO4, pH 7.2), and rewashed with deionized water all for 10 min at room temperature in an orbital shaker. Prior to use, the DNA on the membranes was UV cross-linked (120,000 μJ/cm2). Radiolabeled cDNA was generated from 5 to 40 μg of total RNA by reverse transcriptase at 42 °C for 2 h using 360 units of reverse transcriptase (Superscript II, Invitrogen), dATP, dTTP, dGTP (0.5 mm each, AmershamBiosciences), and dCTP (2 μm, Amersham Biosciences) in the presence of 30 μCi of [α-33P]dCTP (PerkinElmer Life Sciences, catalog number NEG613H), T23ACG anchored primers (1 μg), and RNase inhibitor (40 units Stratagene, Amsterdam, Netherlands, catalog number 300–151) in a total volume of 30 μl. After reverse transcription, residual RNA was hydrolyzed by alkaline treatment (15 μl of 0.1 m NaOH) at 70 °C for 20 min followed by neutralization with 15 μl of 0.1 mHCl. To remove unincorporated nucleotides the 33P-labeled cDNA was purified using Sephadex columns (ProbeQuant G-50, AmershamBiosciences, catalog number 27-5330-01). Before hybridization to the arrays, the labeled cDNA was mixed with 50 μg of COT1-DNA (Invitrogen, catalog number 15279-011) and 10 μg of poly(dA) DNA (Amersham Biosciences, catalog number 27-7836-02) in 4× SSC, 0.1% SDS, denatured at 95 °C for 5 min, and hybridized for 1 h to minimize nonspecific binding to repetitive sequences and the poly(A) tail. After denaturation, the cDNA was added directly to medium sized hybridization bottles (260 × 40 mm, Amersham Biosciences, catalog number RPN2516) containing the membrane arrays prehybridized in 20 ml of CHURCH buffer for 30 min in a rotary hybridization oven. Hybridization with the 33P-labeled cDNA was for 16 h at 65 °C. After hybridization the hybridization buffer was discarded and replaced by 150 ml of washing buffer: the membranes were washed once in 2× SSC, 0.1% SDS, twice in 0.2× SSC, 0.1% SDS, and once in 0.1× SSC, 0.1% SDS for 20 min each at 65 °C. The membranes were transferred to a sheet of 3MM paper, immediately wrapped in Saran wrap, exposed to intensifying screens for 48 h, and scanned with a PhosphorImager at 200-micron resolution (Storm 820, AmershamBiosciences). Images were subsequently analyzed with ImageQuant (Amersham Biosciences) and converted into a table of signal intensities. Further data analysis was performed using Excel (Microsoft). For normalization between samples data were corrected for glyceraldehyde-3-phosphate dehydrogenase present in 18 copies on each filter. A detailed laboratory protocol for the cDNA array method described here is available on request from the Schlaak ([email protected]) or Kerr ([email protected]) labs. RPAs were carried out as described previously (27Muller M. Laxton C. Briscoe J. Schindler C. Improta T. Darnell Jr., J.E. Stark G.R. Kerr I.M. EMBO J. 1993; 12: 4221-4228Crossref PubMed Scopus (373) Google Scholar). Briefly, probes were synthesized from SP6/T7 transcription vectors and labeled with [32P]UTP to a specific activity of 2–5 × 108 cpm/μg of input DNA. Aliquots equivalent to 1–3 × 105 cpm of each probe and 13 μg of total RNA were used per assay. The intensities of radioactive bands were quantified using a PhosphorImager (Storm,Amersham Biosciences). Bands of interest were quantitated and corrected for background. Data are expressed as -fold induction compared with unstimulated samples. Statistical analysis was performed using the two-sample Wilcoxon test. Here we have developed a customized cDNA array methodology for ISGs based on nylon filter technology. At present this system permits the analysis of between 288 (triplicate spot) and 864 genes (single spot) for up to 12 samples per day (Fig.1 A). Throughout the duration of the experiments it was constantly extended from 150 to 231 genes. The analysis presented here, however, is restricted to the initial 150 genes (Table I). A substantial spectrum of known ISGs can be assayed with this macroarray ("macro"array: spot size >300 μm; "micro"array: spot size <300 μm) and it allows the convenient investigation of complex experimental settings including, for example, extensive kinetic and dose-response curves. Moreover the processing, analysis, storage, and recovery of the data is significantly easier and quicker compared with that for microarrays, because only genes of interest are investigated. Accordingly, the analysis of the data for 12 arrays takes ∼60–90 min using standard Microsoft Excel software. Currently, each cDNA is spotted in triplicate (mean coefficient of variation for triplicates: 6–8%) to yield maximal reproducibility and sensitivity (Fig. 1 B). The high flexibility of the spotting procedure also permits the generation of filters with only one spot per gene that are particularly useful for scanning higher numbers of target genes with lower sensitivity. To enhance the performance of the system it is critical to block nonspecific hybridization through repetitive sequences or the poly(A) tail using COT1-DNA and poly(dA) (Fig.2). This is particularly useful for genes only marginally (1.5–2.5-fold) induced: differentials for highly induced genes are still detectable in the absence of prehybridization with COT1-DNA and poly(dA). The system offers a high degree of reproducibility as indicated by its low inter- and intra-assay variation (Fig. 3, A andB, Supplementary Materials for TableII, Table IV, experiment TC V/a-d). To achieve this it is essential to use strict endotoxin-free culture conditions because lipopolysaccharide can induce IFN-β and the expression of ISGs (28Navarro L. David M. J. Biol. Chem. 1999; 274: 35535-35538Abstract Full Text Full Text PDF PubMed Scopus (103) Google Scholar). 2J. F. Schlaak, unpublished data. For RNA extraction, to avoid artifacts induced by prolonged trypsinization and centrifugation, adherent cells were lysed directly on the tissue culture plates and suspension cells directly after spinning down without washing.Figure 3Assay variation. A, intra-assay variation. Two independent samples of total RNA were extracted from 10-cm dishes of unstimulated HT1080 cells, reverse transcribed into labeled cDNA, and hybridized to target cDNA spotted onto nylon membranes. In this scatter plot analysis data are shown as absolute intensity values for each gene. B, inter-assay variation. HT1080 cells were stimulated in two independent experiments with 1000 units/ml IFN-α2a for 8 h. Total RNA was extracted, reverse transcribed into labeled cDNA, and hybridized to target cDNA spotted onto nylon membranes. In this scatter plot analysis data are shown as -fold induction for each gene in the two experiments.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Table IICell type-specific responses to IFN-α2aView Large Image Figure ViewerDownload Hi-res image Download (PPT) Open table in a new tab Table IVDonor-specific IFN-α2a responses in T cellsView Large Image Figure ViewerDownload Hi-res image Download (PPT) Open table in a new tab All of the IMAGE clones used were sequence verified. Comparability of the macroarray data for known genes with data obtained by alternative accepted RNase protection methodology was established by data from experiments carried out as an integral part of our ongoing program. An example of the data from one such experiment (involving an analysis of the responses obtained through the endogenous type I and II IFN receptors and a receptor chimera 2fEgΔB (29Strobl B. Arulampalam V. Is'harc H. Newman S.J. Schlaak J.F. Watling D. Costa-Pereira A.P. Schaper F. Behrmann I. Sheehan K.C. Schreiber R.D. Horn F. Heinrich P.C. Kerr I.M. EMBO J. 2001; 20: 5431-5442Crossref PubMed Scopus (32) Google Scholar)), reveals, for the ISG-56k, IRF-1, and 9–27 ISGs, a good correlation (r = 0.89–0.99) between the data from the two approaches (Fig.4). Similarly good correlations have been obtained in a number of further experiments comparing the results by the two methods for the above and additional ISGs including IP-10, GBP-1, 6-16, MxA and 2–5OAS (for example, Fig. 7, TableV). 3C. M. U. Hilkens, J. F. Schlaak, and I. M. Kerr, manuscript in preparation.Figure 7Assessment of ISG induction in dendritic cells and T cells by RNase protection assay. Dendritic cells (lanes 1, 2,5, and 6) and T cells (lanes 3, 4,7, and8) were stimulated with 1000 units/ml IFN-α for 8 and 6 h, respectively. Aliquots of cytoplasmic RNA (13 μg) were analyzed by RNase protection assay using probes for IP-10 (lanes 1–4) or STAT1α, STAT1β, p48, ISG-56k, 2–5OAS, 6-16, 9-27, and GBP-1 (lanes 5–8). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (lanes 1–4) or γ-actin (lanes 5–8) were used as loading control.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Table VEvaluation of cell type-specific responses to IFN in dendritic cells and T cells using RNase protection assays and macroarraysView Large Image Figure ViewerDownload Hi-res image Download (PPT) Open table in a new tab The sensitivity of the method has also been assessed. As a rule of thumb, in most micro- and macroarray systems a 2-fold change in the expression level is regarded as being significant. Statistical analysis showed that the macroarrays are capable of detecting smaller differences, after stimulation with very low concentrations of IFN-α (e.g. 10 IU/ml, Fig. 5), changes in gene expression of 30% or less are detectable with a high degree of significance (p value < 0.05) by this method. This permits the analysis of dose-response curves for poorly induced (<2-fold, Fig. 6) genes considered marginally significant by other methods. Using more replicates of the spotted DNA this high sensitivity may be enhanced even further. The physiological relevance of these relatively small changes, however, still have to be determined for the individual genes. Accordingly, we have retained 2-fold as the threshold level for significant inducibility for comparative expression profiling (TablesTable II, Table III, Table IV), which is, in addition, associated with a very high degree of statistical significance (p = 0.001 and less, Fig.5).Figure 6Dose-response curves for "marginally induced" genes. HT1080 cells were stimulated with 10, 100
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