Microarray analyses of hypoxia-regulated genes in an aryl hydrocarbon receptor nuclear translocator (Arnt)-dependent manner Su Mi Choi*, Hookeun Oh* and Hyunsung Park Department of Life Science, University of Seoul, South Korea Keywords Arnt; gene expression; HIF; hypoxia; microarray Correspondence H Park, Department of Life Science, University of Seoul, 90 Jeonnong-dong, Dongdaemun-gu, Seoul 130-743, South Korea Fax: +82 2210 2888 Tel: +82 2210 2622 E-mail: hspark@uos.ac.kr *These authors made equal contributions to this study (Received 17 July 2008, revised 12 September 2008, accepted 17 September 2008) doi:10.1111/j.1742-4658.2008.06686.x We investigated hypoxia-inducible factor (HIF)-dependent changes in the expression of 5592 genes in response to hypoxia (0.1% O2, 16 h) by performing cDNA microarray analyses of mouse hepa1c1c7 and BpRc1 cells BpRc1 cells are a hepa1c1c7 variant defective in HIF-b ⁄ aryl hydrocarbon receptor nuclear translocator (Arnt), and are therefore unable to induce HIF target genes in response to hypoxia By comparing hepa1c1c7 cells with BpRc1 cells, we were able to investigate hypoxia-regulated gene expression as well as the role played by HIF in regulating the hypoxicdependent response of gene expression This study identified 50 hypoxiainduced genes and 36 hypoxia-repressed genes Quantitative PCR analysis of nine genes confirmed our ability to accurately analyze changes in hypoxia-induced gene expression by microarray analysis By comparing quantitative PCR analyses of these nine genes in BpRc1 and hepa1c1c7 cells, we determined that eight of the nine hypoxia-induced genes are Arnt dependent Additional quantitative PCR analyses of eight hypoxiarepressed genes confirmed, with a 50% probability, that microarray analysis was able to predict hypoxia-repressed gene expression Only two of the four confirmed genes were found to be repressed in an Arnt-dependent manner Collectively, six of these 13 genes (46.2% probability) showed a pattern of expression consistent with the microarray analysis with regard to Arnt dependence Finally, we investigated the HIF-1a dependence of these 13 genes by quantitative PCR analysis in HIF-1a knockdown 3T3-L1 cells These analyses identified novel hypoxia-regulated genes and confirmed the role of Arnt and HIF-1a in regulating their expression These results identify additional HIF target genes and provide a more complete understanding of hypoxia signaling Abbreviations ABCC3, ATP-binding cassette, subfamily C (CFTR ⁄ MRP), member 3; Arnt, aryl hydrocarbon receptor (AhR) nuclear translocator; ATF-4, activating transcription factor-4; bHLH, basic helix–loop–helix; BNIP3, BCL-2 ⁄ adenovirus E1B 19 kDa-interacting protein 3; BSG, basigin; CCGN2, cyclin G2; DUSP12, dual specificity phosphatase 12; eIF1, eukaryotic translation initiation factor 1; ER, endoplasmic reticulum; FDR, false discovery rate; FKBP4, FK506 binding protein (59 kDa); GNA11, guanine nucleotide binding protein, a 11; HIF, hypoxia-inducible factor; HSP60, heat shock protein, 60 kDa; IER3, immediate early response 3; MAD2L1, MAD2 (mitotic arrest deficient, homolog)-like (yeast); MAPK, mitogen-activated protein kinase; MKP-1, mitogen-activated protein kinase phosphatase-1; MMP, matrix metalloproteinase; NDR1, N-myc downstream regulated 1; P4HA1, procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline 4-hydroxylase), a1 polypeptide; PAS, Per-Arnt-Sim; PERK, PKR-like ER kinase; PPAR, peroxisome proliferators-activated receptor; PSMA3, proteasome (prosome, macropain) subunit, a type 3; PTPN16, protein tyrosine phosphatase, non-receptor type 16; SFRS3, splicing factor, arginine ⁄ serine-rich (SRp20); shRNA, short hairpin RNA; SUI1-RS1, suppressor of initiator codon mutations, related sequence 1; VEGF, vascular endothelial growth factor 5618 FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS S M Choi et al Cellular oxygen is an important regulatory stimulus for many physiological and pathological processes Mammalian cells adapt to hypoxia by inducing the expression of genes involved in anaerobic metabolism, oxygen delivery and cell survival These diverse target genes are induced by a common heterodimeric transcription factor: hypoxia-inducible factor-a ⁄ b (HIF-a ⁄ b) [1–4] The HIF-a and HIF-b subunits belong to the basic helix–loop–helix (bHLH)-Per-Arnt-Sim (PAS) protein family HIF-a is rapidly degraded in normoxic cells, whereas HIF-b, also known as Arnt (aryl hydrocarbon receptor nuclear translocator), is constitutively expressed Under hypoxic conditions, HIF-a is stabilized and translocates into the nucleus, where it forms a heterodimer with the nuclear protein Arnt Structural analyses of bHLH-PAS proteins have determined that interaction between the HLH-PAS domains of each subunit mediates dimerization between HIF-a and HIF-b, and that individual basic regions from each protein interact with their corresponding DNA elements Therefore, dimerization of bHLH-PAS proteins is required for DNA binding [5] The stability and activity of the a subunit are inhibited by post-translational modification, specifically by hydroxylation HIF-a hydroxylation is catalyzed by HIF-a-specific proly-4-hydroxylase and HIF-a-specific asparaginyl-hydroxylase, which utilize molecular oxygen and a-ketoglutarate as cosubstrates The hydroxylated proline residues (human HIF-1a Pro402 and Pro564) are recognized by the E3 ubiquitin ligase, a von Hippel–Lindau protein which mediates HIF-1a polyubiquitination and degradation by the 26S proteasome [6,7] The hydroxylation of the human HIF-1a asparagine residue 803 prevents HIF-a from recruiting the CBP ⁄ p300 coactivator A lack of oxygen has been shown to reduce the activities of these two oxygendependent hydroxylases, resulting in the stabilization of the transactive form of HIF-1a [8,9] HIF-1a was the first HIF-a isoform identified by affinity purification, and HIF-2a (endothelial PAS domain-containing protein 1) was later identified through an homology search [10] Both HIF-1a and HIF-2a form functional heterodimers with Arnt Although knockout mice experiments have shown that HIF-1a and HIF-2a have unique functions and are nonredundant [11], no HIF-2a-specific target genes have been identified HIF-1a and HIF-2a share a number of target genes, but HIF-1a appears to be the predominant form responsible for the induction of target genes [12] Arnt was originally identified as a partner protein of aryl hydrocarbon receptor (AhR) Similar to Arnt, AhR also contains a bHLH-PAS domain at its N-terminal domain Dioxin, an environmental pollutant, is Arnt-dependent gene expression in hypoxia the most potent ligand for AhR Once bound to ligand, cytosolic AhR translocates into the nucleus and forms a heterodimer with Arnt Therefore, Arnt is a binding partner for both HIF-a and AhR [13,14] Previous studies by Miller and Whitlock [15] led to the isolation of variant mouse hepa1c1c7 cell lines that lose responsiveness to dioxin using benzo(a)pyrene selection and fluorescence-activated cell sorting One of the variant cell lines, BpRc1, has normal AhR, but is defective in the nuclear localization of AhR Arnt transfection can complement this defect in BpRc1 cells, indicating that these variant cells are defective in Arnt [16,17] As Arnt is also required for the hypoxic induction of HIF target genes, BpRc1 cells are also unresponsive to hypoxia, even in the presence of HIF-a Several studies have shown the role of Arnt in the basal expression of genes [18–20] Here, we emphasize the role of Arnt, especially in the hypoxic responses of gene expression By performing cDNA microarray analyses of hypoxic hepa1c1c7 cells and BpRc1 cells, we identified both hypoxia-regulated genes and their Arnt dependence In addition, using HIF-1a knockdown cells, we investigated whether HIF-1a is required for the hypoxic responses of the identified genes Results Microarray analyses of hypoxia-regulated gene expression We analyzed the changes in the expression of 5592 genes in response to hypoxic exposure (0.1% O2, 16 h) using Mouse 6K cDNA chips (TwinChipÔ Mouse-6K) from Digital Genomics Inc (Seoul, South Korea) Mouse hepa1c1c7 and BpRc1 cells were exposed to hypoxia or normoxia (20% O2) for 16 h prior to RNA isolation and subsequent cDNA microarray analysis Four replicates were performed for each cell type using twin chips that incorporated dye-reversed hybridization Comparison of hepa1c1c7 and BpRc1 cells enabled us to investigate hypoxia-regulated gene expression, as well as the role played by HIF in the regulation of the hypoxic response Based on our analyses of 5592 genes, we selected statistically relevant genes with q values less than 0.1 for further analysis; 420 and 565 genes were selected from the analyses of hepa1c1c7 and BpRc1 cells, respectively Of these genes, 259 demonstrated q values of less than 0.1 in both analyses From the 259 genes, we selected hypoxia-induced genes that demonstrated a greater than 1.5-fold induction; 50 and 40 genes were selected from the analyses of hepa1c1c7 and BpRc1 cells, respectively (Tables and S1) In addition, we selected FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS 5619 Arnt-dependent gene expression in hypoxia S M Choi et al Table Hypoxia-induced genes identified by microarray analyses GenBank accession number WT cells Gene symbol Folda Gene name Genes induced by hypoxia in both wild-type and BpRc1 cells AI956848 BNIP3c BCL2 ⁄ adenovirus E1B 19 kDa-interacting protein 3, NIP3 AI325917 PTPN16c Protein tyrosine phosphatase, non-receptor type 16 AI852322 MRPS22 Mitochondrial ribosomal protein S22 AI852317 NDR1c N-myc downstream regulated AI323719 SUI1-RS1c Suppressor of initiator codon mutations, related sequence (Saccharomyces cerevisiae) AI853078 H2AFY H2A histone family, member Y AI451894 CCNG2c Cyclin G2 AI450411 VEGFc Vascular endothelial growth factor AI415663 – RIKEN cDNA 2700038M07 gene AI415726 – DNA segment, Chr 7, ERATO Doi 458, expressed AI413228 – Mus musculus, clone MGC:18904 IMAGE:4240711, mRNA, complete cds AI839114 SQSTM1 Sequestosome AI853170 ANP32 Acidic nuclear phosphoprotein 32 AI504706 – ESTs, weakly similar to hair mouse hairless protein (M musculus) AI528680 TIEG TGFB inducible early growth response AI843944 IGH-4 Immunoglobulin heavy chain (serum IgG1) AI843941 – RIKEN cDNA 0610012D09 gene AI415729 – ESTs, moderately similar to sylm_human probable leucyl-tRNA synthetase, mitochondrial precursor (Homo sapiens) AW321053 AIRAP Arsenite inducible RNA-associated protein (Airap) AI326954 XTRP2 X transporter protein AW411617 – RIKEN cDNA 1810015C04 gene AI838844 LYNX1 Ly6 ⁄ neurotoxin AI839365 PLD3 Phospholipase D3 Genes induced by hypoxia in wild-type cells AI842086 BSGc Basigin AI323613 INPP5D Inositol polyphosphate-5-phosphatase, 145 kDa AI842506 P4HB Prolyl 4-hydroxylase, beta polypeptide AI448103 MDM2 Transformed mouse 3T3 cell double minute AI841020 PGK1 Phosphoglycerate kinase AI853802 PFKP Phosphofructokinase, platelet AI323680 IER3c Immediate early response AI323453 P4HA1c Procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline 4-hydroxylase), a1 polypeptide AI848411 BTG1 B-cell translocation gene 1, anti-proliferative AI451895 RPGRIP1 Retinitis pigmentosa GTPase regulator interacting protein AI452157 – ESTs, weakly similar to the KIAA0146 gene product is novel (H sapiens) AI448042 – Expressed sequence AI448042 AI835435 GPI1 Glucose phosphate isomerase complex AI842276 B3GALT2 UDP-Gal:betaGlcNAc beta 1,3-galactosyltransferase, polypeptide AI842546 NBR1 Next to the Brca1 AI528519 C3 Complement component AI428079 – DNA segment, Chr 1, ERATO Doi 101, expressed AI452183 – RIKEN cDNA 4930423K06 gene AI452214 – Expressed sequence AI452214 AI415675 – Expressed sequence AI415675 AI850555 JUNB Jun-B oncogene AI452202 – DNA segment, Chr 12, Wayne State University 95, expressed AI448149 PARVA Parvin a 5620 BpRc1 cells q valueb Folda q valueb 8.523 6.409 6.138 4.684 3.628 0.005 0.005 0.005 0.005 0.005 8.956 2.264 3.364 2.534 1.695 0.003 0.003 0.003 0.003 0.003 3.624 3.094 2.933 2.592 2.425 2.168 0.005 0.005 0.005 0.005 0.005 0.005 3.311 1.934 1.573 1.542 1.888 1.637 0.003 0.003 0.003 0.003 0.003 0.003 2.076 2.052 2.022 0.005 0.005 0.005 2.691 1.654 1.845 0.003 0.007 0.003 2.018 1.982 1.891 1.846 0.005 0.005 0.005 0.007 1.706 1.697 1.599 1.608 0.003 0.003 0.003 0.003 1.682 1.648 1.566 1.540 1.520 0.013 0.014 0.010 0.005 0.005 2.602 1.789 2.051 1.761 1.729 0.003 0.067 0.003 0.003 0.003 4.311 3.271 2.641 2.355 2.306 2.196 2.146 2.143 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 1.232 1.357 1.318 1.431 1.460 1.282 1.305 1.373 0.091 0.072 0.067 0.005 0.003 0.072 0.072 0.005 2.056 1.838 1.837 0.005 0.005 0.005 1.216 1.269 1.427 0.072 0.051 0.005 1.699 1.687 1.666 1.648 1.647 1.626 1.607 1.591 1.587 1.584 1.577 1.559 0.007 0.005 0.005 0.005 0.007 0.005 0.005 0.005 0.010 0.013 0.005 0.013 1.430 1.375 1.323 1.450 1.277 1.389 1.332 1.330 1.411 1.381 1.273 1.225 0.003 0.005 0.016 0.007 0.040 0.005 0.017 0.014 0.007 0.029 0.012 0.080 FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS S M Choi et al Arnt-dependent gene expression in hypoxia Table Continued WT cells GenBank accession number BpRc1 cells Gene symbol Folda q valueb Folda q valueb HK2 SNRPA AI642394 AI324697 Gene name Hexokinase Small nuclear ribonucleoprotein polypeptide A 1.523 1.519 0.005 0.025 1.333 1.449 0.014 0.005 a Fold: a ratio of expression in hypoxia ⁄ expression in normoxia b q value: significant difference, false discovery rate (FDR), selected q value < 0.1 c Bold characters indicate genes that were further investigated by Q-PCR as reported in Fig genes that were repressed in response to hypoxia and that demonstrated a less than 0.6-fold induction; 36 and 40 genes were selected from the analysis of hepa1c1c7 and BpRc1 cells, respectively (Tables S1 and 3) Compared with northern analyses or quantitative real-time reverse transcription-polymerase chain reaction (Q-PCR), we found that the cDNA microarray analyses underestimated the fold change of gene expression In order to take more genes into consideration, we arbitrarily chose the values of 1.5- and 0.6-fold induction Genes that are induced by hypoxia The 50 genes that demonstrated a greater than 1.5fold induction in hepa1c1c7 cells were considered to be induced by hypoxia (Table 1) Of these 50 genes, 26 demonstrated a less than 1.5-fold induction in BpRc1 cells, suggesting that these genes were induced by hypoxia in an Arnt-dependent manner The remaining 24 genes demonstrated a greater than 1.5fold induction in both cell lines, suggesting that their expression was regulated independent of Arnt To confirm these findings, nine of the 50 up-regulated genes were selected for Q-PCR analysis The fold induction of each gene in both hepa1c1c7 and BpRc1 cells was analyzed by one-way analysis of variance (ANOVA) (Table 2) Q-PCR analysis confirmed that each of the nine genes [suppressor of initiator codon mutations, related sequence (SUI1-RS1), protein tyrosine phosphatase, non-receptor type 16 (PTPN16), N-myc downstream regulated (NDR1), cyclin G2 (CCNG2), vascular endothelial growth factor (VEGF), BCL-2 ⁄ adenovirus E1B 19 kDa-interacting protein (BNIP3), basigin (BSG), immediate early response (IER3) and procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline 4-hydroxylase), a1 polypeptide (P4HA1)] was induced by hypoxia with the indicated fold and P value (P < 0.05) in hepa1c1c7 cells (Fig and Table 2) In contrast, Q-PCR analyses demonstrated that, in BpRc1 cells, the induction folds of eight genes (PTPN16, NDR1, CCNG2, VEGF, BNIP3, BSG, IER3 and P4HA1) were significantly lower, and their P values were greater than Table Hypoxia-induced gene expression analyzed by both microarray and Q-PCR up, hypoxia-induced expression pattern, fold ‡ 1.5; down, hypoxia-repressed expression pattern, fold < 0.6; nc, no change, 0.6 £ fold < 1.5; ns, not statistically significant, P value > 0.05; ), Arnt independent; +, Arnt dependent Microarray Q-PCR WT cells Gene symbol Fold SUI1-RS1 PTPN16 NDR1 CCNG2 VEGF BNIP3 BSG IER3 P4HA1 3.63 6.41 4.68 3.09 2.93 8.52 4.31 2.15 2.14 a a BpRc1 cells b q value up up up up up up up up up Fold 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 0.005 1.70 2.26 2.53 1.93 1.57 8.96 1.23 1.31 1.37 WT cells q value a Arnt dependence Fold 0.003 0.003 0.003 0.003 0.003 0.003 0.091 0.072 0.005 ) ) ) ) ) ) + + + 4.87 107.10 66.79 18.95 20.33 16.34 4.36 14.68 16.83 b up up up up up up nc nc nc Fold: a ratio of expression in hypoxia ⁄ expression in normoxia value < 0.1 b a BpRc1 cells P value up up up up up up up up up 0.00024 0.00023 0.00023 0.00023 0.00023 0.00023 0.00023 0.00023 0.00024 2.65 1.41 2.18 1.18 1.78 0.63 1.03 0.47 0.54 P value Folda up ns ns ns ns ns ns ns ns Arnt dependence 0.00038 0.91962 0.95664 0.97169 0.67472 0.99743 0.98929 0.80513 0.64244 ) + + + + + + + + q value: significant difference, false discovery rate (FDR), selected q FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS 5621 Arnt-dependent gene expression in hypoxia SUI1-RS1 mRNA Cell WT Relative mRNA level (IER3/18S) Relative mRNA level (BSG/18S) Cell – + WT – WT – + WT – + BpRc1 P4HA1 mRNA IER3 mRNA 25 Cell BpRc1 BNIP3 mRNA Cell 12 BpRc1 + Hypoxia 15 Hypoxia WT – 10 + – + 15 BpRc1 + – 20 + – Cell VEGF mRNA 18 Hypoxia WT Cell BSG mRNA 20 Hypoxia 10 Hypoxia 40 + – 15 + – 60 BpRc1 + 20 BpRc1 + – 25 Relative mRNA level (VEGF/18S) Relative mRNA level (CCNG2/18S) B Cell 10 Cell 20 Hypoxia CCNG2 mRNA – 40 + – 15 Hypoxia 60 BpRc1 + WT 20 80 Relative mRNA level (BNIP3/18S) – Relative mRNA level (NDR1/18S) NDR1 mRNA 80 100 Hypoxia PTPN16 mRNA 120 Relative mRNA level (PTPN16/18S) Relative mRNA level (SUI1-RS1/18S) Relative mRNA level (P4HA1/18S) A S M Choi et al – 15 10 + Hypoxia BpRc1 + WT 20 Cell – – + WT – + BpRc1 Fig mRNA levels of hypoxia-induced genes analyzed by Q-PCR (A, B) Wild-type (WT) hepa1c1c7 cells and BpRc1 cells were incubated in hypoxic conditions for 16 h Total RNA was isolated and quantified by Q-PCR 18S rRNA expression levels were used for normalization Values are presented as the average ± standard deviation of three independent experiments Statistical analysis of the Q-PCR data was evaluated using one-way ANOVA 0.05, suggesting that hypoxia induced these eight genes in an Arnt-dependent manner (Table 2) Furthermore, Q-PCR analysis confirmed that SUI1-RS1 expression was significantly induced in both hepa1c1c7 and BpRc1 cells, suggesting that expression of SUI1-RS1 was regulated in an Arnt-independent manner in response to hypoxia 5622 Based on these Q-PCR results, we were able to confirm the validity of our microarray analysis of hypoxia-induced gene expression Microarray analysis demonstrated that six genes (SUI1-RS1, PTPN16, NDR1, CCNG2, VEGF and BNIP3) were induced by hypoxia in both wild-type and Arnt-defective cells, and that an additional three genes (BSG, IER3 and FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS S M Choi et al Arnt-dependent gene expression in hypoxia P4HA1) were not induced in Arnt-deficient cells However, Q-PCR analysis indicated that, with the exception of SUI1-RS1, eight of the nine genes were found to be induced by hypoxia in an Arnt-dependent manner Therefore, only four of these genes (SUI1-RS1, BSG, IER3 and P4HA1) showed a consistent expression pattern in both Q-PCR and microarray analyses, indicating that our microarray analysis was able to predict Arnt-dependent expression of each gene in response to hypoxia with a 44.5% (4 ⁄ 9) probability Genes that are repressed by hypoxia The 36 genes that demonstrated a fold induction of less than 0.6 were considered to be repressed by hypoxia (Table 3) Of these, nine demonstrated a fold induction between 0.6 and 1.5 in BpRc1 cells, suggesting that they were repressed in an Arnt-dependent manner An additional 27 genes that demonstrated a fold induction of less than 0.6 in both cell lines were believed to be repressed in an Arnt-independent Table Hypoxia-repressed genes identified by microarray analyses GenBank accession number Genes repressed AI852475 AI324252 AI528620 AI837705 AI838039 AI843948 AI528616 AI326810 AI838959 Genes repressed AI504950 AW322036 AI325518 AI853888 AI482035 AI506703 AI850361 AI481173 AI481688 AI326238 AI850889 AI481596 AI837206 AI447856 AI447735 AI507479 AI853883 AI482173 AI504862 AI504558 AI505978 AI447741 AI449639 AI481136 AI448873 AI447724 WT cells Gene symbol Gene name by hypoxia in wild-type cells HNRPD Heterogeneous nuclear ribonucleoprotein D MAD2L1c MAD2 (mitotic arrest deficient, homolog)-like (yeast) GNA11c Guanine nucleotide binding protein, a 11 FKBP4c FK506 binding protein (59 kDa) HSP60c Heat shock protein, 60 kDa PSMA3c Proteasome (prosome, macropain) subunit, a type SFRS3c Splicing factor, arginine ⁄ serine-rich (SRp20) – Expressed sequence AI326810 ACTA2 Actin, a 2, smooth muscle, aorta by hypoxia in both wild-type and BpRc1 cells ABCC3c ATP-binding cassette, sub-family C (CFTR ⁄ MRP), member KPNA2 Karyopherin (importin) a GSR Glutathione reductase HIRIP5 Histone cell cycle regulation defective interacting protein – RIKEN cDNA 2310044F10 gene – DNA segment, Chr 3, ERATO Doi 176, expressed BRAL1 Brain link protein – RIKEN cDNA 2700033I16 gene – RIKEN cDNA 2310014B11 gene CRMP1 Collapsin response mediator protein CLDN11 Claudin 11 DUSP12c Dual specificity phosphatase 12 PTMA Prothymosin a – RIKEN cDNA 2610019N19 gene SH3YL1 Sh3 domain YSC-like – ESTs, moderately similar to Z277_human zinc finger protein 277 (Homo sapiens) SHD src homology domain-containing transforming protein D – RIKEN cDNA 1810013P09 gene – RIKEN cDNA 2610001M19 gene – Mus musculus, similar to hypothetical protein FLJ20174, clone IMAGE:3595651, mRNA, partial cds – RIKEN cDNA 1200014N16 gene – RIKEN cDNA 1300018J18 gene – RIKEN cDNA 1300017J02 gene – Expressed sequence AI482555 FLIZ1 Fetal liver zinc finger – Expressed sequence AI447724 BpRc1 cells Folda q valueb Folda q valueb 0.597 0.593 0.585 0.564 0.545 0.537 0.532 0.440 0.435 0.066 0.010 0.066 0.005 0.005 0.014 0.058 0.005 0.005 0.777 0.710 0.630 0.717 0.757 0.744 0.670 0.706 0.777 0.051 0.003 0.003 0.003 0.007 0.012 0.003 0.003 0.029 0.599 0.595 0.586 0.577 0.570 0.566 0.559 0.557 0.546 0.540 0.539 0.529 0.526 0.505 0.503 0.489 0.029 0.013 0.029 0.005 0.005 0.005 0.005 0.005 0.005 0.013 0.005 0.005 0.010 0.005 0.005 0.005 0.426 0.418 0.492 0.590 0.578 0.444 0.550 0.334 0.365 0.565 0.534 0.372 0.451 0.485 0.509 0.439 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.484 0.473 0.470 0.465 0.005 0.005 0.005 0.007 0.471 0.432 0.336 0.464 0.003 0.003 0.003 0.003 0.463 0.459 0.445 0.405 0.290 0.235 0.005 0.005 0.007 0.005 0.005 0.005 0.502 0.408 0.414 0.321 0.220 0.284 0.003 0.003 0.003 0.003 0.003 0.003 a Fold: a ratio of expression in hypoxia ⁄ expression in normoxia b q value: significant difference, false discovery rate (FDR), selected q value < 0.1 c Bold characters indicate genes that were further investigated by Q-PCR as reported in Fig FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS 5623 Arnt-dependent gene expression in hypoxia S M Choi et al sette, subfamily C (CFTR ⁄ MRP), member (ABCC3)] were selected for Q-PCR (Fig 2) Our analysis determined that four of the eight genes (MAD2L1, HSP60, FKBP4 and PSMA3) were significantly repressed in response to hypoxia as measured by Q-PCR analysis (P < 0.05) in hepa1c1c7 cells (Fig and Table 4) Based on these results, we were able to demonstrate that our microarray analysis was able to predict hypoxia-repressed gene expression with a 50% proba- manner in response to hypoxia To validate these results, eight of the 36 genes [MAD2 (mitotic arrest deficient, homolog)-like (yeast) (MAD2L1), heat shock protein, 60 kDa (HSP60), FK506 binding protein (59 kDa) (FKBP4), proteasome (prosome, macropain) subunit, a type (PSMA3), guanine nucleotide binding protein, a 11 (GNA11), splicing factor, arginine ⁄ serine-rich (SRp20) (SFRS3), dual specificity phosphatase 12 (DUSP12) and ATP-binding casA MAD2L1 mRNA HSP60 mRNA 1.5 1.0 0.5 – Cell 0.4 0.2 Hypoxia Cell 0.8 0.6 0.4 0.2 Cell WT Relative mRNA level (ABCC3/18S) Relative mRNA level (DUSP12/18S) 1.0 0.5 WT + WT – + BpRc1 SFRS3 mRNA 0.2 Cell – 2.0 1.5 1.0 0.5 WT + Hypoxia BpRc1 + Cell – – + WT – + BpRc1 ABCC3 mRNA + Hypoxia BpRc1 Cell – – 2.5 0.4 Hypoxia 1.5 + 0.2 Cell 0.6 DUSP12 mRNA Cell WT 0.8 2.0 – 0.4 Hypoxia 1.0 + – 0.6 + – 1.2 BpRc1 + 0.8 GNA11 mRNA 1.0 – 1.0 BpRc1 + 1.4 1.2 Hypoxia – PSMA3 mRNA Relative mRNA level (GNA11/18S) Relative mRNA level (PSMA3/18S) 0.6 + – 1.4 B 0.8 BpRc1 + WT 1.6 Hypoxia 1.0 Relative mRNA level (SFRS3/18S) Hypoxia Relative mRNA level (FKBP4/18S) Relative mRNA level (HSP60/18S) Relative mRNA level (MAD2L1/18S) 2.0 FKBP4 mRNA 1.2 1.2 2.5 – + WT – + BpRc1 Fig mRNA levels of hypoxia-repressed genes analyzed by Q-PCR (A,B) Wild-type (WT) hepa1c1c7 cells and BpRc1 cells were incubated in hypoxic conditions for 16 h The expression level of each gene was quantified by Q-PCR Values are presented as the average ± standard deviation of three independent experiments Statistical analysis of the Q-PCR data was evaluated using one-way ANOVA 5624 FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS S M Choi et al Arnt-dependent gene expression in hypoxia Table Hypoxia-repressed gene expression analyzed by both microarray and Q-PCR up, hypoxia-induced expression pattern, fold ‡ 1.5; down, hypoxia-repressed expression pattern, fold < 0.6; nc, no change, 0.6 £ fold < 1.5; ns, not statistically significant, P value > 0.05; ), Arnt independent; +, Arnt dependent Microarray Q-PCR WT cells Gene symbol Fold MAD2L1 HSP60 FKBP4 PSMA3 GNA11 SFRS3 DUSP12 ABCC3 0.59 0.55 0.56 0.54 0.59 0.53 0.53 0.60 a BpRc1 cells b q value down down down down down down down down Fold 0.010 0.005 0.005 0.014 0.070 0.060 0.005 0.029 0.71 0.76 0.72 0.74 0.63 0.67 0.37 0.43 WT cells q value a Arnt dependence fold 0.003 0.007 0.003 0.012 0.003 0.003 0.003 0.003 + + + + + + ) ) 0.52 0.16 0.06 0.46 0.64 1.86 1.68 1.02 b nc nc nc nc nc nc down down a BpRc1 cells P value down down down down ns up up ns 0.00039 0.00023 0.00023 0.00396 0.05276 0.02817 0.00044 0.99976 1.09 0.65 0.26 0.36 0.56 0.30 1.11 0.43 P value Folda ns nc down down down down ns down Arnt dependence 0.10562 0.00089 0.00041 0.00037 0.00717 0.00675 0.21254 0.00037 + + ) ) nac nac nac nac Fold: a ratio of expression in hypoxia ⁄ expression in normoxia b q value: significant difference, false discovery rate (FDR), selected q value < 0.1 c na, not applied; Arnt dependence was not applied when gene expression pattern of Q-PCR was different from microarray in hepa1c1c7 cells a bility (4 ⁄ 8) in hepa1c1c7 cells We next compared the fold induction of these eight genes in Arnt-defective BpRc1 cells Microarray analyses showed that two genes (DUSP12 and ABCC3) were repressed by hypoxia in both hepa1c1c7 and BpRc1 cells, whereas the remaining six genes (MAD2L1, HSP60, FKBP4, PSMA3, GNA11 and SFRS3) were only repressed in wild-type cells However, Q-PCR analyses indicated that only two (MAD2L1 and HSP60) of the four (MAD2L1, HSP60, FKBP4, and PSMA3) confirmed genes were believed to be repressed in an Arnt-dependent manner These results suggested that our microarray analysis was able to predict Arnt-dependent repression of each gene with a 50% probability Genes that are regulated by hypoxia in a HIF-1a ⁄ b-dependent manner Q-PCR analyses confirmed that nine genes were induced and four were repressed in response to hypoxia (Tables and 4), and that 10 of the 13 confirmed genes were regulated by hypoxia in an Arnt-dependent manner The remaining three genes (SUI1-RS1, FKBP4 and PSMA3) were found to be regulated in an Arnt-independent manner To substantiate the specific role of Arnt, we used BpRc1 cells infected with retrovirus expression full-length Arnt [17] BpRc1 cells reconstituted with full-length Arnt restored the hypoxia-induced (IER3, BSG, BNIP3, VEGF, CCNG2, NDR1, P4HA1, PTPN16) or hypoxiarepressed (HSP60, MAD2L1) gene expression (Table 5), confirming that these 10 genes are regulated by hypoxia in an Arnt-dependent manner The fold induction of the genes was often greater in BpRc1 cells reconstituted with Arnt, reflecting that overexpression of Arnt endowed the cells with increased responsibilities to hypoxia In addition, the Arnt-dependent induction of five genes (IER3, BSG, BNIP3, VEGF and NDR1) and Arnt-dependent repression of two genes (MAD2L1 and HSP60) were validated by northern blot analysis (Fig 3) Finally, we investigated the role of HIF-1a in regulating the expression of these genes in response to hypoxia by analyzing murine preadipoctyes 3T3-L1, in which HIF-1a was knocked down by infection of retrovirus encoding a short hairpin RNA (shRNA) against HIF-1a Western blot analyses confirmed a specific reduction of HIF-1a protein by the cognate shRNA in 3T3-L1 cells (Fig 4A) Q-PCR analysis determined that IER3, BSG, BNIP3, VEGF, CCNG2 and NDR1 were induced in response to hypoxia in both an Arnt- and HIF-1a-dependent manner, indicating that they are the target genes for HIF-1a ⁄ b (Table and Fig 4B,C) Interestingly, it was determined that hypoxia induced both P4HA1 and PTPN16 in an Arnt-dependent, but HIF-1a-independent manner shRNA knockdown of HIF-1a failed to completely abolish hypoxia-induced expression of both P4HA1 and PTPN16, but instead reduced the fold induction of these genes by approximately one-half, thereby suggesting that HIF-1a plays a role in regulating hypoxiamediated induction of these genes, at least in part (Table 5) As Arnt is a common binding partner for both HIF-1a and HIF-2a, HIF-2a may also play a partial role in regulating the hypoxia-dependent induction of these genes FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS 5625 5626 Fold a WT cells 0.00023 0.00023 0.00023 0.00023 0.00023 0.00023 0.00024 0.00023 0.00024 0.00396 0.00023 0.00039 0.00023 P value 0.47 1.03 0.63 1.78 1.18 2.18 0.54 1.41 2.65 0.36 0.65 1.09 0.26 Fold a ns ns ns ns ns ns ns ns up down nc ns down BpRc1 cells Fold b 0.00059 0.00088 0.00035 0.00001 0.00055 0.00037 0.00207 0.00003 0.01303 0.00254 0.00028 0.01628 0.00137 P value + + + + + + + + ) ) + + ) 31.83 10.97 57.94 5.42 6.95 13.59 10.50 3.59 1.51 0.53 0.10 0.53 0.33 WT Arnt dependence Folda up up up up up up up up up down down ns ns 0.00016 0.00016 0.00016 0.00016 0.00016 0.00016 0.00016 0.00644 0.00421 0.00017 0.00392 0.28610 0.53301 P value Q-PCR in 3T3-L1 cells 25.19 8.25 30.73 4.29 6.55 14.55 10.58 2.42 2.87 0.36 0.19 0.72 0.18 Fold a up up up up up up up up up down down ns down Control 0.00016 0.00016 0.00016 0.00022 0.00016 0.00453 0.00016 0.00016 0.00016 0.00016 0.00392 0.73432 0.00779 P value 3.88 1.26 8.57 1.12 2.06 6.16 5.59 1.94 1.64 0.58 0.99 0.94 0.72 Folda ns ns ns ns ns ns up up up down ns ns nc sh HIF-1a 0.66843 0.99925 0.55686 0.99131 0.66843 0.48301 0.00353 0.00096 0.00039 0.00016 0.99998 0.99868 0.00227 P value + + + + + + )⁄+ )⁄+ ) ) + nab nab [19] [20] [18,19] [18,26] [19,26] [18,19,26] [18,19,26] [18] – – – – – HIF-1a dependence Reference na, not applied; Arnt or HIF-1a dependence was not applied when gene expression pattern of Q-PCR was different from 0.80513 14.84 up 0.98929 5.06 up 0.99743 91.91 up 0.67472 21.29 up 0.97169 11.66 up 0.95664 544.44 up 0.94244 3.16 up 0.91962 20.72 up 0.00038 317.10 up 0.00037 0.46 down 0.00089 0.09 down 0.38923 0.56 down 0.00041 0.08 down P value a Arnt + BpRc1 cells Fold: a ratio of expression in hypoxia ⁄ expression in normoxia microarray in hepa1c1c7 cells a IER3 14.68 up BSG 4.36 up BNIP3 16.34 up VEGF 20.33 up CCNG2 18.95 up NDR1 66.79 up P4HA1 16.83 up PTPN16 107.10 up SUI1-RS1 4.87 up PSMA3 0.46 down HSP60 0.16 down MAD2L1 0.52 down FKBP4 0.06 down Gene symbol Q-PCR in hepa1c1c7 cells Table mRNA levels of hypoxia-regulated genes in both hepa1c1c7 cells and 3T3-L1 cells analyzed by Q-PCR up, hypoxia-induced expression pattern, fold ‡ 1.5; down: hypoxiarepressed expression pattern, fold < 0.6; nc, no change, 0.6 £ fold < 1.5; ns, not statistically significant, P value > 0.05; ), Arnt or HIF-1a independent; +, Arnt or HIF-1a dependent Arnt-dependent gene expression in hypoxia S M Choi et al FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS S M Choi et al Arnt-dependent gene expression in hypoxia A Arnt Hypoxia Arnt –/– WT – – – + – + + – + α-Arnt WB IER3 BSG BNIP3 NB VEGF NDR1 28S/18S B Arnt Hypoxia Arnt –/– WT – – – + – + + – + HSP60 NB MAD2L1 28S/18S Fig Northern analyses of hypoxia-regulated genes (A,B) Wildtype (WT) mouse hepa1c1c7 cells, the variant BpRc1 cells and BpRc1 cells reconstituted with Arnt were exposed to hypoxic conditions (0.1% O2) for h Western blot analysis was performed using 30 lg of the cell lysates and HIF-1b (ARNT) antibody (top panel: WB) For northern blot (NB) analysis, wild-type mouse hepa1c1c7 cells, the BpRc1 variant cell line and BpRc1 cells reconstituted with Arnt were exposed to hypoxic conditions for 16 h; 20 lg of total RNA from the treated cells was transferred onto a nitrocellulose membrane Each blot was hybridized with the indicated [a-32P]labeled probes Information on the probes is presented in Table S3 In contrast, our results demonstrated that SUI1-RS1 expression was induced in response to hypoxia, even in the absence of both Arnt and HIF-1a, suggesting that neither HIF-1a nor HIF-2a was required for hypoxiainduced expression of this gene Therefore, our results demonstrated that HIF was not required for the induction of SUI1-RS1 in response to hypoxia In addition, our results demonstrated that PSMA3 was repressed by hypoxia in the absence of both Arnt and HIF-1a, and that HSP60 was repressed by hypoxia in an Arntand HIF-1a-dependent manner Finally, we determined that MAD2L1 and FKBP4 were repressed in hepa1c1c7 cells, but not in 3T3-L1 cells, suggesting that these genes were repressed in response to hypoxia in a cell type-specific manner Discussion In this study, we identified 259 hypoxia-regulated genes by microarray analysis and confirmed the expression profiles of 17 of these genes by Q-PCR analysis Collectively, we determined that 13 of the 17 genes (76.5%) were regulated, as predicted, by microarray analysis By comparing the results of our microarray analysis between wild-type cells and BpRc1 cells, we predicted the Arnt dependence of the confirmed 13 genes (Tables and 4) Q-PCR analyses determined that only six of the 13 genes (46.2%) showed a consistent pattern of expression when compared with our microarray analysis for Arnt-dependent regulation in response to hypoxia BNIP3, VEGF, CCNG2 and NDR1 have been identified as HIF-1 target genes [21,22] However, the results of microarray analyses indicated that they were also induced in BpRc1 cells in response to hypoxia Compared with microarray analysis, it was determined that Q-PCR analysis of wild-type hepa1c1c7 cells resulted in a greater fold induction of these genes, suggesting that our microarray analysis quantitatively underestimated the changes in gene expression in wildtype cells In contrast, both microarray and Q-PCR analyses resulted in comparable levels of fold induction in BpRc1 cells (Table 2) [19] However, the P value of fold induction measured by Q-PCR was determined to be too large to accept the difference between the normoxic and hypoxic mRNA level of the gene in BpRc1 cells (P > 0.05) Therefore, Q-PCR analysis demonstrates that Arnt is important for the induction, but less necessary for the repression, of hypoxia-mediated gene expression when compared with predictions generated by microarray analysis We next investigated whether the expression of these 13 genes was also regulated by HIF-1a (Table 5) It was determined that seven of the 13 genes (IER3, BSG, BNIP3, VEGF, CCNG2, NDR1 and HSP60) were regulated by hypoxia in both an Arnt- and HIF-1a-dependent manner Two genes (P4HA1 and PTPN16) were found to be induced in response to hypoxia in an Arntdependent manner, but only partially regulated in a HIF-1a-dependent manner An additional two genes (SUI1-RS1 and PSMA3) were determined to be regulated under hypoxic conditions in both an Arnt- and HIF-1a-independent manner For the final two genes (MAD2L1 and FKBP4), it was determined that they were not repressed in 3T3-L1 cells, indicating that these genes are regulated in a cell type-specific manner In addition to identifying previously known HIF-1 target genes, including BNIP3, VEGF, CCNG2, NDR1 and P4HA1 [21,22], and other known hypoxia-inducible genes, including IER3, BSG and PTPN16 [21–23], this report is the first to identify a number of novel hypoxia-regulated genes, including SUI1-RS1, HSP60 and PSMA3 (Table 5) FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS 5627 Arnt-dependent gene expression in hypoxia A sh RNA Hypoxia 3T3-L1 Control – + – – + S M Choi et al HIF-1α α – + WB -HIF-1 -14-3-3 B 14 40 30 20 10 100 Relative mRNA level (BNIP3/18S) Relative mRNA level (BSG/18S) Relative mRNA level (IER3/18S) 50 12 10 0 Hypoxia – sh RNA + – – + Control – + Hypoxia HIF-1α α sh RNA + – sh RNA HIF-1α α sh RNA – + Control – Hypoxia HIF-1α α – + – – + Control Hypoxia α HIF-1α sh RNA – Control 3T3-L1 + – – 12 Hypoxia HIF-1α α sh RNA + – + HIF-1α α SUI1-RS1 mRNA 15 + – Control 2.5 + – 3T3-L1 Relative mRNA level (SUI1-RS1/18S) Relative mRNA level (PTPN16/18S) – PTPN16 mRNA + + – 18 – HIF-1α α 12 3T3-L1 10 + sh RNA 12 – Control NDR1 mRNA P4HA1 mRNA + + – 3T3-L1 + 14 – – 16 3T3-L1 Relative mRNA level (P4HA1/18S) Hypoxia 0 – 20 + – Relative mRNA level (NDR1/18S) Relative mRNA level (CCNG2/18S) Relative mRNA level (VEGF/18S) + 40 CCNG2 mRNA sh RNA + – 60 3T3-L1 Hypoxia – Control VEGF mRNA 80 – 3T3-L1 Hypoxia BNIP3 mRNA BSG mRNA IER3 mRNA 60 2.0 1.5 1.0 0.5 – + – – + Control 3T3-L1 – + Hypoxia HIF-1α α sh RNA – + – – + Control – + α HIF-1α 3T3-L1 Fig mRNA levels of hypoxia-regulated genes analyzed by Q-PCR HIF-1a knockdown 3T3-L1 cells and control 3T3-L1 cells were generated using the retroviral system as described in Experimental procedures (A) Level of HIF-1a protein by shRNA in 3T3-L1 cells The cells were incubated in 1% O2 for 16 h Western blot (WB) analysis was performed using HIF-1a antibody (Novus Biochemicals, Littleton, CO, USA), and anti-14-3-3c (Upstate Biotechnology, Lake Placid, NY, USA) was used as loading control (B, C) The cells were incubated under hypoxia for 16 h The mRNA levels of the indicated genes were analyzed by Q-PCR and normalized to the 18S rRNA levels Values are reported as the average ± standard deviation of three independent experiments Statistical analysis of the Q-PCR data was evaluated using one-way ANOVA 5628 FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS S M Choi et al Arnt-dependent gene expression in hypoxia C HSP60 mRNA PSMA3 mRNA Relative mRNA level (HSP60/18S) Relative mRNA level (PSMA3/18S) Hypoxia – sh RNA + – – + Control – + Hypoxia HIF-1α α sh RNA – + – 3T3-L1 MAD2L1 mRNA Relative mRNA level (FKBP4/18S) Relative mRNA level (MAD2L1/18S) – + α HIF-1α FKBP4 mRNA 1.5 1.0 0.5 sh RNA + 3T3-L1 2.0 Hypoxia – Control – + – – + Control – + Hypoxia HIF-1α α sh RNA 3T3-L1 – + – – + Control – + HIF-1α α 3T3-L1 Fig Continued Our results identified IER3 and BSG as HIF-1 target genes Both IER3 and BSG were induced by hypoxia in wild-type hepa1c1c7 cells and 3T3-L1 cells, but were not induced in either Arnt- or HIF-1a-defective cells In contrast with our findings, previous microarray analysis of hypoxic embryonic stem cells has demonstrated that IER3 is induced by hypoxia in both HIF-1a) ⁄ ) and HIF-2a) ⁄ ) embryonic stem cells [24] However, IER3, also known as the immediate early response gene X-1 (IEX-1), is a stress-inducible protein involved in the regulation of both cell proliferation and apoptosis in a cell type-dependent fashion Expression of IER3 ⁄ IEX-1 is tightly regulated by a number of transcription factors, including p53, Sp1, c-Myc, c ⁄ EBP, USF and NF-jB, and may therefore be regulated in response to a variety of signals [22,25] The second HIF-1 target gene identified, BSG (or CD147), was originally identified as a tumor surface receptor capable of inducing matrix metalloproteinase (MMP) expression in fibroblasts [26] Antibodies to BSG have been shown to decrease MMP expression, leading to an inhibition of tumor cell invasion [27] Cyclophilin A, a ligand of BSG, is also induced in response to hypoxia ⁄ reoxygenation and leads to the induction of a neuroprotective effect through BSG receptor signaling [23,28] Our observation that hypoxia induces BSG signaling through HIF-1 indicates that BSG signaling may play a role in HIF-mediated hypoxic preconditioning effects and tumor progression Q-PCR analysis demonstrated that hypoxic induction of P4HA1 and PTPN16 occurred in an Arntdependent manner However, HIF-1a knockdown partly attenuated the hypoxic induction of both genes (Table 5) Therefore, these results, in combination with previous findings demonstrating that HIF-1a and HIF2a share common target genes and that overexpression of both increases the expression of P4HA1 and PTPN16, confirmed that these genes were induced by hypoxia through both HIF-1a and HIF-2a [21,29] Furthermore, previous studies by Hofbauer et al [30] have demonstrated that hypoxia induces the expression FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS 5629 Arnt-dependent gene expression in hypoxia S M Choi et al of a number of collagen fiber-forming proteins, including proline 4-hydroxylase a1 (P4HA1), P4HA2 and procollagen lysyl hydroxylases, through both Arnt and HIF-1 signaling using Arnt-defective hepatoma cells and HIF-1a knockout embryonic fibroblast cells PTPN16, also known as mitogen-activated protein kinase phosphatase-1 (MKP-1) or DUSP1, is a phospho-threonine ⁄ phospho-tyrosine-specific phosphatase which inhibits mitogen-activated protein kinase (MAPK) activity by dephosphorylation Consistent with its role as a MAPK inhibitor, mice lacking PTPN16 ⁄ MKP-1 ⁄ DUSP1 demonstrate enhanced MAPK activity As MAPK has been shown to stimulate a number of cellular processes, PTPN16 as a MAPK antagonist can inhibit these processes Several studies have demonstrated that PTPN16 is involved in the innate immune response [31], diet-induced obesity [32] and human cancers [33] In addition to hypoxia, oxidative stress has been reported to increase PTPN16 protein levels in a p53-dependent manner, resulting in decreased MAPK activity and increased cellular susceptibility to oxidative damage Our results show that hypoxia was unable to induce either PTPN16 or P4HA1 genes in Arnt-defective cells, whereas hypoxia was able to partially induce the expression of these genes in HIF-1a knockdown cells (Table 5) The demonstration of the induction of SUI1-RS1 and the repression of PSMA3 in response to hypoxia in the absence of both Arnt and HIF-1a indicates that hypoxia regulates the expression of a number of genes in a HIF-independent manner Human SUI1 has been shown to be induced in response to DNA damage and endoplasmic reticulum (ER) stress [34] The amino acid sequence of the murine SUI1 protein demonstrates that it is identical to the eukaryotic translation initiation factor (eIF1) eIF1, in concert with eIF1a, binds to the small (40S) ribosomal subunit to form the initiation complex at the mRNA start codon Small ribosomes that lack eIF1 and eIF1a fail to reach the initiation site selection [35] Here, we demonstrate, for the first time, that the SUI1 ⁄ eIF1 gene is induced by hypoxia through a HIF-independent mechanism Severe hypoxia (less than 0.1% O2) or anoxia has also been reported to trigger ER stress, leading to the unfolded protein response and activation of the PKRlike ER kinase (PERK), suppression of translation and induction of several transcription factors and chaperone proteins, including activating transcription factor-4 (ATF-4) and its target gene, CHOP-10 ⁄ GADD153 Both ATF-4 and CHOP-10 ⁄ GADD153 have been shown to be induced by anoxia However, their induction is independent of HIF activity [36–38] Similarly to ATF-4 and CHOP-10, we report that SUI1 ⁄ eIF1 is 5630 induced by severe hypoxia (0.1% O2) in a HIF-independent manner However, the mechanisms by which hypoxia induces the expression of these genes, and how the induction of SUI1 ⁄ eIF1 affects translation efficiency in response to hypoxic stress, remain unclear PSMA3 ⁄ Lmpe8 is the a subunit of the 20S proteasome The 20S proteasome is composed of four rings, each of which contains seven subunits The outer rings comprise a subunits, and the inner rings are composed of b subunits [39] Oligonucleotide chip analysis has demonstrated that PSMA3 and its isoforms, PSMA2 and PSMA4, are down-regulated by antioxidants, including BO653 and probucol Previous studies have determined that two antioxidant responsive elements in the promoter region of PSMA3 are necessary for the down-regulation of PSMA3 [40] In the current study, we have demonstrated that PSMA3 is repressed by hypoxia in both an Arnt- and HIF-1a-independent manner In addition to PSMA3, we have determined that HSP60, a stress-responsive chaperone that exists in both the mitochondria and cytosol, is repressed by hypoxia in both an Arnt- and HIF-1a-dependent manner Using high-throughput proteomics screening, Ghosh et al [41] determined that HSP60 interacts with apoptosis inhibitors and contributes to a broad antiapoptotic program in tumors These data suggest that HSP60 inhibitors may function as a putative anticancer agent by differentially inducing apoptosis in tumor cells [41] However, it remains to be determined whether hypoxia decreases HSP60 protein levels in an Arnt- and HIF-1a-dependent manner [42] HIF is a transcriptional activator that is essential for the hypoxic repression of several genes, including E-cadherin, heme oxygenase 1, peroxisome proliferators-activated receptor c (PPARc) and MLH1 [43–45] HIF has been shown to repress genes by inducing specific transcriptional repressors, such as STRA13 ⁄ DEC1 ⁄ SHARP2, DEC2, SNAIL and Bach1 [44,46,47] In addition, HIF itself functions as a transcriptional repressor Several research groups have reported that HIF binding sites that are oriented on the antisense strand are important for the hypoxic repression mechanism Consistent with these findings, previous studies have determined that equilibrative nucleoside transporter 1, PPARa and Na-K-2Cl cotransporter all contain HIF binding sites oriented on the antisense strand of their respective promoters, and are repressed by hypoxia [48–50] This study further highlights the importance of HIFmediated regulation of cellular gene expression in both ischemic diseases and tumors by identifying additional, FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS S M Choi et al novel target genes and relating their functions to the hypoxic response Previous studies have demonstrated that HIF mediates hypoxic preconditioning effects by inducing VEGF and erythropoietin [51], whereas HIF accelerates tumor progression by regulating lysyl oxidase, E-cadherin and plasminogen activator inhibitor-1 [45] Therefore, our results from both microarray and Q-PCR analyses extend our understanding of the HIF target genes, and provide a better understanding of hypoxia-mediated signaling Experimental procedures Cell lines Mouse hepatoma hepa1c1c7 cells, the Arnt-defective BpRc1 variant and mouse preadipocyte 3T3-L1 cells were purchased from the American Type Culture Collection (ATCC) (Manassas, VA, USA) [15] Arnt-defective BpRc1 cells reconstituted with full-length Arnt were kindly provided by J P Whitlock, Jr [17] HIF-1a knockdown 3T3-L1 cells were generated using a retroviral vector system (BD Biosciences, Palo Alto, CA, USA) An shRNA oligonucleotide was generated against mouse HIF-1a and ligated with the pSIREN-RetroQ vector to generate pSIREN-RetroQ-shHIF-1a, according to the manufacturer’s instructions (BD Biosciences) The sequence for shRNA against mouse HIF-1a (GenBank accession number AF003695) was 5¢-GATCCGTGTGAGCTCACATCTTGATTTCAAGAG AATCAAGATGTGAGCTCACATTTTTTAGATCTG-3¢ The sequence for control shRNA was provided by BD Biosciences: 5¢-GATCCGTGCGTTGCAGTACCAACTTCAA GAGATTTTTTACGCGTG-3¢ 3T3-L1 cells were infected with the retrovirus encoding either shHIF-1a or the control shRNA, and selection with puromycin (2 lgỈmL)1) was performed to identify the infected cells Microarray analysis Wild-type mouse hepa1c1c7 and BpRc1 cells were grown to 80% confluence on a 100 mm tissue culture plate, and then exposed to hypoxic conditions (0.1% O2) by incubation in an anaerobic chamber (Model 1029, Forma Scientific, Inc., Marietta, OH, USA) in 5% CO2, 10% H2 and 85% N2 for 16 h at 37 °C [52] Total RNA was isolated using an RNeasy spin column, according to the manufacturer’s instructions (Qiagen Inc., Valencia, CA, USA) For microarray analysis, two sets of RNA samples were prepared for both normoxic and hypoxic hepa1c1c7 and BpRc1 cells The RNA quality of each sample was analyzed by electrophoresis on a denaturing agarose gel with northern blotting (data not shown) Mouse 6K cDNA twin chips (TwinChipÔ Mouse-6K, Digital Genomics Inc.), which contain two sets of 5592 independent mouse cDNA sequences, were Arnt-dependent gene expression in hypoxia used in this study Four replicate experiments were performed using two sets of RNA samples and two twin chips that incorporated dye-reversed hybridization, according to the instructions of the manufacturer (Digital Genomics Inc.) [53,54] Microarrays were processed as follows Briefly, cDNA probes were prepared by the reverse transcription of total RNA (50 lg) in the presence of aminoallyl-dUTP and lg of random primers (Invitrogen, San Diego, CA, USA) for h Contaminants were removed from the cDNA probes by a Microcon YM-30 column (Millipore, Bedford, MA, USA) Cleaned probes were then coupled to either Cy3 or Cy5 dye (Amersham Pharmacia Biotech, Uppsala, Sweden) The Cy3- or Cy5-labeled cDNA probes were purified with a QIAquick PCR Purification Kit (Qiagen) Dried Cy3- or Cy5-labeled cDNA probes were resuspended in hybridization buffer (30% formamide, 5· SSC, 0.1% SDS, 0.1 mgỈmL)1 salmon sperm DNA) The Cy3- or Cy5labeled cDNA probes were mixed, hybridized to a microarray slide and incubated overnight at 42 °C The slide was washed twice with wash solution (2· SSC and 0.1% SDS) for at 42 °C, once with wash solution (0.1· SSC and 0.1% SDS) for 10 at room temperature and, finally, four times with 0.1· SSC for at room temperature The slide was dried by centrifugation at 18 g for The hybridization image was analyzed by genepix 4100A and genepix pro 3.0 software (Axon Instrument, Union City, CA, USA) to obtain gene expression ratios (normoxic sample versus hypoxic sample) Data analysis Data were normalized in an intensity-dependent manner using a scatter plot smoother ‘lowess’ [55] The identification of genes with significant differences in expression levels was performed using the significance analysis of microarray software program (SAM, version 1.21) [56] SAM estimates the percentage of genes identified by chance, the false discovery rate (FDR) [54] We assessed the statistical significance of the differential expression of genes by computing a q value (minimum FDR) for each gene Genes were considered to be differentially expressed when the fold change between normoxia and hypoxia was determined to be greater than 1.5 or less than 0.6, or when the q value was less than 0.1 Q-PCR Total RNA was isolated using an RNeasy spin column (Qiagen Inc.) cDNA was reverse transcribed from total RNA (1 lg) using AMV reverse transcriptase with dNTPs and random primers (Promega, Madison, WI, USA) For Q-PCR, the iQÔ SYBR Green Supermix and MyiQ single color real-time PCR detection system (Bio-Rad, Hercules, CA, USA) was used The expression level of 18S rRNA FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS 5631 Arnt-dependent gene expression in hypoxia S M Choi et al (GenBank accession number X03205) was detected using the primers 5¢-ACCGCAGCTAGGAATAATGGAA TA-3¢ (forward) and 5¢-CTTTCGCTCTGGTCCGTCTT-3¢ (reverse), and then used for normalization Statistical analysis of the Q-PCR data was evaluated using one-way ANOVA Data were presented as the average ± standard deviation with values derived from at least three experiments A value of P < 0.05 was considered to be statistically significant For primer design, we carried out blast searches to determine the full-length cDNA sequences of the genes that were identified by microarray analyses The information for each primer used in the Q-PCR analysis of each gene is presented in Table S2 Acknowledgements We thank Professor James P Whitlock, Jr for providing BpRc1 cells reconstituted with full-length Arnt We thank Miss Hyun-Ju Cho and Miss Sujin Yim for technical assistance This work was supported by a grant (CBM-01-B-1-3) from the Center for Biological Modulators of the 21st Century Frontier R&D Program, the Ministry of Science and Technology and a grant (R200706192003) from the Basic Research Program of the Korean Science and Engineering Foundation, Korea to H Park S M Choi and H Oh are supported by a Brain Korea 21 Research Fellowship S M Choi is supported by a Seoul Science Fellowship References Hochachka PW (1986) Defense strategies against hypoxia and hypothermia Science 231, 234–241 Kim JW, Tchernyshyov I, Semenza GL & Dang CV (2006) HIF-1-mediated expression of pyruvate dehydrogenase 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microarray data: a robust composite method addressing single and multiple slide systematic variation Nucleic Acids Res 30, e15 Tusher VG, Tibshirani R & Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response Proc Natl Acad Sci USA 98, 5116–5121 Supporting information The following supplementary material is available: Table S1 Numbers of hypoxia-induced and hypoxiarepressed genes identified by microarray analyses Table S2 Sequences of the primers used for Q-PCR Table S3 Probes used in northern analyses This supplementary material can be found in the online version of this article Please note: Wiley-Blackwell is not responsible for the content or functionality of any supplementary material supplied by the authors Any queries (other than missing material) should be directed to the corresponding author for the article FEBS Journal 275 (2008) 5618–5634 ª 2008 The Authors Journal compilation ª 2008 FEBS ... than 1.5-fold induction in BpRc1 cells, suggesting that these genes were induced by hypoxia in an Arnt-dependent manner The remaining 24 genes demonstrated a greater than 1.5fold induction in. .. b-dependent manner Q-PCR analyses confirmed that nine genes were induced and four were repressed in response to hypoxia (Tables and 4), and that 10 of the 13 confirmed genes were regulated by hypoxia in an. .. activation of the PKRlike ER kinase (PERK), suppression of translation and induction of several transcription factors and chaperone proteins, including activating transcription factor-4 (ATF-4) and