Cis-Element Clustering Correlates with Dose-Dependent Pro- and Antisignaling Effects of IL18

FULL PAPER cis-Element clustering correlates with dose-dependent pro- and antisignaling effects of IL18

D Leyfer1, A Bond2, E Tworog2, D Perron2, S Maska2, A Brito2, J Kamens2, Z Weng1,3 and J Voss2 1Bioinformatics Program, Boston University, Boston, MA, USA; 2Abbott Bioresearch Center, Worcester, MA, USA; 3Biomedical Engineering Department, Boston, MA, USA

We examine the effects of IL18 on monocytes by performing microarray experiments using cell line KG1. Based on sensitivity to IL18, we identified three functionally distinct gene expression clusters (EC). We see little proinflammatory gene induction at low IL18 concentrations, but instead observe induction of diverse NFkB signaling inhibitors. Conversely, intermediate concentrations of IL18 induced proinflammatory genes including the activating subunits of NFkB. At the highest IL18 concentration, we observe a third gene cluster containing the proapoptotic Fas gene among others. Clustering of IL18- responsive genes based on cis-elements in their promoters agreed well with the ECs. We conclude that IL18 produces a dose- dependent transcriptional response that can in part be attributed to the composition of cis-elements in the promoters of IL18- responsive genes. These results also support a model for regulatory mechanisms that prevent spurious immune response due to weak cytokine fluctuations and a separate mechanism enabling induction of proinflammatory functions by higher levels of cytokine. Genes and Immunity (2004) 5, 354–362. doi:10.1038/sj.gene.6364099 Published online 10 June 2004

Introduction dose-dependent manner. Low concentrations of IL18 appear to provoke an anti-NFkB signaling response; IL18 is a proinflammatory cytokine structurally related higher concentrations result in expression of many to IL1. It is considered to play a critical role in the Th1 chemokines and other monocyte/macrophage activation polarization of T cells during an immune response.1,2 It is markers, whereas the highest concentration of IL18 also thought to activate NK cells3,4 and monocytes, results in activation of a third set of genes including including the myelomonocytic cell line KG-1.5–10 IL18 proapoptotic FAS, Fc receptor g and IL2 receptor. These signal transduction is mediated via a heterodimeric results suggest a model whereby a feedback mechanism receptor11 that engages IRAK via Myd8812–14 leading to limiting activation of NFkB-signaling at low or spurious activation of the NFkB pathway1,15 via NIK, as well as the cytokine concentration and a mechanism producing activation of AP1 via JNK.13 Whether IL18 receptor inflammatory responses at higher concentrations of IL18. engagement activates other pathways, is not known. We also performed computational analysis on the Thus far, most reports have studied the function of IL18 promoter regions of the IL18-responsive genes deter- in concert with other proinflammatory cytokines such as mined by microarray experiments. We discovered that a IL12, especially with respect to interferon gamma gene very high percentage of the genes responding to low and regulation.16–19 In fact, IL18 alone does not induce intermediate concentrations of IL18 contain putative interferon gamma expression in most experimental NFkB family binding sites. Using a computer program model systems. IL12 cooperation with IL18 has been CLOVER (Frith MC, Hansen U, Weng Z, manuscript in speculated to function via IL18 receptor upregulation preparation), we determined cis-elements in the prox- and STAT4 activation.17,20 Apart from interferon gamma imal promoters of all IL18-responsive genes. We then expression, little is known about other genes regulated clustered these genes based on their cis-element contents. by IL18 alone or in combination with other cytokines. Surprisingly, the resulting cis-element-based clusters In this study, we use oligonucleotide microarrays to agree well with gene clusters that are based on investigate the gene expression patterns induced by expression profile. We conclude that IL18 produces a physiologically relevant concentrations of IL18 in the dose-dependent transcriptional response that can be monocytic cell line KG1.21 Using various clustering and accounted for in part by the composition of cis-elements visualization techniques, we demonstrate that IL18 alone representing common signal transduction end points. is sufficient to induce expression of specific genes in a Results Correspondence: Dr J Voss, Abbott Bioresearch Center, Worcester, MA IL18 alone directly regulates gene expression in KG1 01605, USA. E-mail: [email protected] cells Received 12 January 2004; revised 22 March 2004; accepted 22 To determine the set of transcripts regulated directly by March 2004; published online 10 June 2004 IL18, we titrated recombinant IL18 into duplicate KG1 cis-Element clustering D Leyfer et al 355 cell cultures in the presence and absence of the protein (MIP1-a and -b, MIP2-a and -b and IL8) are all reported synthesis inhibitor cycloheximide. mRNA samples were to attract predominantly monocytes and neutrophils. We prepared and analyzed using Affymetrix HU6800 Gen- also detected upregulation of the cytokines IL1-b, TNF- echipss (see On-line Supplemental Information and 10 and the macrophage growth factor CSF-1. Among the Methods for MIAME data). Figure 1a is a heatmap surface molecules upregulated under these conditions representation of 60 genes whose expression levels were were ICAM-1, CD83 and CD36, which have established most significantly regulated by IL18. We did not consider roles in macrophage function. We also detected upregu- downregulated transcripts in this analysis due to the lation of at least 15 transcription factors including six well-documented effects of cycloheximide on mRNA members of the NFkB pathway (see below). The heatmap stability. Compared to vehicle treatment, these genes also indicates that some but not all transcripts had a increased expression under at least one IL18 concentra- dose-dependent response to IL18, which we examined tion (see Figure 1a). The genes comprised a variety of more closely. functional categories including transcription factors, kinases and surface molecules and secreted proteins of Bioinformatics analysis alone predicts IL18-induced which many have been previously identified as markers NFjB signaling of activated macrophages and monocytes. IL18 treatment Since some genes appeared to respond differently causes transcriptional activation of at least five chemo- depending on IL18 concentration, we attempted to kines and three cytokines. The upregulated chemokines determine computationally whether the genes in the

Figure 1 Genes induced by IL18 in KG1 cells. (a) Response of the 60 genes most significantly induced by IL18. KG1 cells were treated with the indicated amounts of IL18 in the presence or absence of cycloheximide. The heatmap was generated by selecting transcripts that were upregulated X2-fold with Po0.05 by t-test in IL18 and CHX þ IL18 samples, as compared to vehicle-treated samples, for at least one concentration of IL18, or were up X1.5-fold and had a Po0.01 by t-test in the IL18 and CHX þ IL18 samples, as compared to vehicle-treated samples, for at least one concentration of IL18. Each column represents the arithmetic average of biological duplicates. Indicated at the right by purple bars are the genes containing NFkB sites recognized by TRANSFAC.(b) NFkB binding site prediction using TRANSFAC. Each of the genes depicted herein was analyzed for NFkB regulation by literature searching using PubMed and by using the binding site identification tool TRANSFAC. In all, 25 of 27 literature-annotated genes were also identified by TRANSFAC as containing NFkB sites. TRANSFAC also predicted another 13 genes from the gene set in panel (a) to contain sites. These sites were not further validated. The high preponderance of NFkB site containing genes indicates a role for this factor in the IL18 pathway. (c) NFkB binding ELISA assay. Nuclear extracts were prepared from cells treated identically to those used for panel (a). These extracts were used in an ELISA-based assay using plate bound p50 and p65 binding sites as indicated. Soluble wild-type or mutant competitor oligonucleotides were included in parallel reactions as indicated. Reaction conditions and oligonucleotide sequences are described in Materials and Methods. Differences between 10 and 50 ng/ml IL18 for both p65 and p50 are significant to Po0.01 using Student’s t-test. (d) NFkB mobility shift. Nuclear extracts from cells were mixed with a 32P-labeled oligonucleotide probes encoding an NFkB binding site and electrophoresed through a polyacrylamide gel. -indicates the position of NFkB p65/p50 heterodimers and ) indicates the position of NFkB p50/50 homodimers. Lanes 1–7 contain nuclear extracts from KG1 cells treated with the indicated amounts of recombinant IL18. Lane 8 contains a 32P-labeled AP2 binding site and nuclear extract from KG1 cells incubated with 10 ng/ml IL18. Lanes 9 and 10 contain nuclear extracts from control and LPS-treated mouse peritoneal exudate cells. (e) NFkB antibody super shifts. Each panel contains EMSA analysis of KG1 nuclear extracts from control cells or cells incubated with 10 ng/ml IL18 as indicated incubated with a 32P-labeled oligonucleotide. -indicates the position of NFkB p65/p50 heterodimers and ) indicates the position of NFkB p50/50 homodimers. Indicated above each lane is the type of anti-NFkB monoclonal antibody or cold oligonucleotide competitor coincubated in each reaction.

Genes and Immunity cis-Element clustering D Leyfer et al 356 groups were related to each other in terms of transcrip- NFkB containing complexes dependent is perturbed by tion factor binding sites in their proximal promoters. an antibody specific for NFkB p50 (lane 6) whereas a p65- First, we used the MATCH program from the TRANSFAC specific antibody perturbs only the upper complex (lane database to scan the 50 upstream regions of these genes to 7). Both complexes fail to appear in the presence of a identify NFkB binding sites. The program identified 38 molar excess of an unlabeled oligonucleotide containing (out of 60) genes. We also performed literature searches an NFKB p50 binding site (lane 8). to determine which of the IL18-response genes had been previously annotated as NFkB regulated. The compar- Bioinformatics analysis reveals feedback mechanisms ison is summarized as a Venn diagram in Figure 1b. that limit inflammatory response to IL18 MATCH identified most of the genes annotated as NFkB- To examine the apparent IL18 dose-dependent response regulated (25 out of 27, or 97%). It also predicted 13 genes more carefully we created another heatmap based on not previously annotated. The rightmost column of more stringent filtering criteria. We selected transcripts Figure 1a denotes which genes contained predicted upregulated at least two-fold (Po0.05) at 50 ng/ml IL18 NFkB binding sites. Because these predicted sites are both in the absence and presence of cycloheximide. In biased toward the top of the heatmap we inferred a Figure 2a, these 34 transcripts are ordered by hierarchical potential transcriptional basis for the differential re- clustering using the Euclidean distance as a similarity sponse to IL18 meriting further biochemical and compu- measure. We observe a clear dose response since the tational analysis. number of transcripts upregulated Xtwo-fold increases across the 0.5–50 ng/ml IL18 concentration range (bot- IL18-induced NFjB binding tom of Figure 2a). Binning the transcripts induced at least To confirm the results of our preliminary bioinformatics two-fold by the incremental IL18 concentrations defines analysis, we set out to verify experimentally that NFkB three distinct ECs designated by white boxes in Figure 2a. activation occurred under our IL18 treatment conditions. Interestingly, the apparent IL18 dose-dependent in- The results of NFkB DNA-binding ELISA assays using creases in gene activation parallels the dose dependent two different NFkB-specific oligonucleotides are shown increases in NFkB binding. To confirm the presence of in Figure 1c. These experiments demonstrated induction the ECs, we used two other clustering methods: K-means of NFkB binding activity that was apparently bimodal. clustering and Principle Component Analysis (PCA). K- At the lowest IL18 concentration (0.5 ng/ml), we observe means clustering (Figure 2a, rightmost column) indicated a slight increase in NFkB binding activity above back- that the transcripts fell into three clusters similar to those ground level. The activity is further increased at 2 ng/ml, defined by hierarchical clustering. For PCA, the expres- but it remains unaltered when the concentration is sion values represented in Figure 2a were pivoted and increased to 10 ng/ml. A slight increase in the NFkB reduced to three principle components. In Figure 2b, binding activity is observed at 50 ng/ml. Based on the plotting principle component 3 against principle compo- high incidence of NFkB binding sites and concordance nent 1 for all genes clearly stratifies the genes according with binding data, these results validate the concept of to EC. Thus, all three clustering methods (hierarchical, K- computational identification of transcription factor bind- means and PCA) support the observation of three classes ing sites in conjunction with transcript profiling data. of IL18-responsive genes. Hence, we took a hypothesis-independent computational Gene ontology revealed functional trends within each approach to identify other cis-elements associated with EC (Table 1). EC1 contains genes that are upregulated by the dose-dependent IL18 response (see below). The the lowest dose of IL18. Only one chemokine gene, results of such an analysis would also be useful in CXCL2, is in this group. Instead, EC1 contains several determining whether other pathways, in addition to genes whose products attenuate activation of NFkB. NFkB activation, could be triggered by IL18 stimulation. These include IkB-a and -e, which both directly block IL18 treatment preferentially activates NFkBp65/p50 NFkB entry to the nucleus; TNFAIP3, BIRC3 and IER3, heterodimers over p50/p50 homodimers. We used which encode distinct proteins annotated as attenuating electrophoretic mobility shift assays (EMSA) to identify various steps in the TNF signaling pathway downstream the forms of NFkB activated by IL18 treatment. Hetero- of TRAF22–25. We confirmed IL18 induction of many dimers have been shown to be transcriptional activators transcript changes by quantitative PCR using KG1 RNA whereas p50 homodimers are believed to act most often samples and RNA samples prepared from whole human as transcriptional repressors. As shown in Figure 1d, blood treated with recombinant IL18 (Table 1). The nuclear extracts prepared from KG1 cells treated with results of the KG1 cell analysis suggest that the overall increasing amounts of IL18 were incubated with a 32P- response to weak IL18 stimulation is to activate expres- labeled oligonucleotide probe capable of binding both sion of genes whose function is to limit activation of p65/p50 heterodimers and p50 homodimers. Consistent NFkB. By contrast, the response to intermediate IL18 with the results shown in Figure 1c, we detected a dose- concentrations appears to be largely proinflammatory. dependent increase in a single band likely to correspond Nine proinflammatory molecules are induced including to the p65/p50 heterodimer. A very faint band corre- two Rel family members that are activating members of sponding to the p50 homodimer could also be detected NFkB signaling pathway (RELB and NFkB2). These upon longer exposure (Figure 1e). For comparison, results suggest a model whereby the difference in nuclear extracts from LPS-treated mouse peritoneal responses to low and intermediate IL18 concentrations exudate cells gave rise to two bands of similar intensity indicate a feedback mechanism that could establish an corresponding to homo and heterodimers. To confirm the IL18 signal threshold for activation of proinflammatory identity NFkB species induced by IL18, we used genes. Our results also suggest a third transcript group antibodies specific for p50 and p65 to interrogate the induced by higher concentrations of IL18 containing IL2 complexes. As shown in Figure 1e, formation of both receptor alpha, Rel and Fas among others (Table 1).

Genes and Immunity cis-Element clustering D Leyfer et al 357

Figure 2 IL18 regulates gene expression in cohorts. (a) Heatmap summary of transcripts induced directly by IL18 in KG1 cells. All transcripts regulated greater than or equal to two-fold7CHX with Po0.05. For each treatment, the two individual replicates and arithmetic average are represented, each row represents a different transcript. Bright red indicates four-fold upregulation, dark blue four-fold downregulation and white indicates no change. Indicated below the figure are the IL18 concentrations used and the fraction of all the indicated transcripts defined upregulated according to the fold change and P-value criteria above. White boxes demark Expression Clusters (EC) of transcripts whose expression appears to be increased as a cohort by the incremental IL18 concentrations. The rightmost column indicates the k-means cluster of each transcript. Using k-means cluster analysis only three of a possible of four centroids filled with transcript profiles. Black indicates transcripts falling into centroid one, yellow centroid two and gray centroid three. The gene ID of each row is as indicated by row in Table 1. (b) Principal Components Analysis of IL18 dose response. The data shown in panel (a) was pivoted such that each icon represents a single transcript colored by its expression cluster as designated in panel (a). Three principal components were determined, component 1 was plotted vs component 3 capturing 97.5% of the variability in the data set. The analysis validates the expression clusters visualized in panel (a) by resolving them using an independent method.

cis-Element clusters showed similarity to EC clusters ness correlated with similar promoter compositions We then investigated whether the similar IL18-response among IL18-responsive genes, and the second analysis behavior of genes in the ECs could result from similar to indicate specifically which cis-elements distinguished sets of cis-elements in their proximal promoters (defined the ECs. as 1000 bp upstream of the transcription start site). We Promoters were clustered based on log2 (raw CLOVER used an in-house program CLOVER, which can examine score) for each cis-element in TRANSFAC using Eucli- all cis-element matrices in TRANSFAC and determine if dean distance as the similarity measure. The results are any are over- or under-represented in a given sequence summarized as a dendrogram in Figure 3a. The genes in (or in a set of regulatory regions). We performed the Figure 2a were separated into distinct branches of the analysis in two ways: (1) unsupervised (regardless of our dendrogram. In order to facilitate comparison with the prior knowledge of expression cluster composition) ECs, we cut the dendrogram into three cis-element clustering of all the genes based on the CLOVER- clusters (CCs), with two neighboring branches lumped identified cis-elements in individual promoters: (2) into CC1 (Figure 3a). The number of genes shared by CCs detection of over-represented cis-elements in the promo- and ECs are listed in the figure, with 11 out of 12 EC1 ters of all genes in each EC. We expected the first analysis genes in CC1 and all CC2 genes in EC2. The rightmost to reveal whether the dose-dependent IL18 responsive- column on the heatmap in Figure 3b shows alignment of

Genes and Immunity cis-Element clustering D Leyfer et al 358 the CCs and ECs. The Exact Analysis of contingency tables with sparsely populated cells26 showed a statistically significant agreement between the ECs and CCs (P- value ¼ 0.004). cis-Elements that distinguish the ECs were identified by running CLOVER on the promoters of each EC, corresponding to genes in individual ECs. Genes in EC1 and EC2 (responding to low and intermediate concentrations of IL18) share a large number of cis-elements, including four NFkB-response elements. By contrast, NFkB elements are not apparent in the promoters of EC3 genes. Thus, we predict that the genes in EC3 respond to IL18 in an NFkB-independent manner, suggesting IL18 activation of another pathway. This is consistent with the only slight increase in NFkB detected in response to the highest concentration of IL18. Several cis-elements unique to EC3 were identified and could play a role in mediating an NFkB independent process. Unusual NFkB sites or those requiring cooperative binding interactions for functions would have escaped our detection. Several cis-elements distinguish EC1 from EC2, including E2F that may play a role in modifying the sensitivity of these genes to NFkB. Only ubiquitous TATA box and TANTI- GEN are common to all three ECs (Figure 3c).

Discussion Many reports have characterized the effects of IL18 and IL12 on IFNg production from NK, T and monocytic cells. Although there is agreement that IL18 and IL12 synergize in this effect, detailed characterization of the effects of IL18 alone on other genes is lacking. Here, we present a transcript profile analysis of the effects of IL18 on the myelomonocytic cell line KG1. Our results suggest that IL18 may regulate expression of functionally distinct cohorts of genes relevant to macrophage/monocyte function. Bioinformatics analysis of the upregulated genes indicated that many of these genes harbor NFkB binding sites. This result was in part anticipated based on previous experiments demonstrating IL18-dependent activation of the NFkB pathway.1,15 We further illustrated dose-dependent activation of NFkB binding using biochemical assays. Since we observed IL18-dependent activation in functional cohorts, rather than a single group, we classified all IL18-responsive genes according to the cis- element compositions of their promoters. The CCs we obtained agree well with clusters defined using transcript profiles at a statistically significant level. This analysis demonstrated a correlation between specific cis- elements and sensitivity to IL18 signaling. There are many difficulties in such analysis, namely, computationally identified cis-elements may not function in vivo; transcription regulation may require cis-elements outside Figure 3 Promoter similarity analysis. (a) Individual CLOVER the operationally defined 1000 bp proximal promoters; analysis separated promoters into three distinct groups designated incomplete lists of cis-elements in TRANSFAC; EC PC1, PC2 and PC3. PC1 resolves into two main groups. The number of genes in each Expression Cluster corresponding to each promoter definition may not be perfect (despite agreement cluster is indicated in the right half of the figure. (b) Expression between the three clustering techniques) as some cluster/promoter cluster alignment. Each transcript is aligned with transcripts may be on the borderline between ECs. its corresponding promoter class using the color code depicted in Nevertheless, our study has shown that bioinformatics panel (a). (c) Bulk CLOVER analysis identified cis-elements techniques can be powerful in guiding functional associated with each expression cluster. cis-Elements unique for genomics studies of novel cytokines, hormones and their the clusters are outlined using unique color code. receptors.

Genes and Immunity cis-Element clustering D Leyfer et al 359 Bioinformatic analysis suggested other insights into flammatory response; EC2, inflammation-committed; the regulation of these genes. The three proinflammatory EC3, containing proinflammatory genes, but also poten- factors (REL, RELB, NFkB2) share some cis-elements in tially restraining inflammatory response through a their promoter regions; however, the two IkB inhibitors proapoptotic mechanism. Our finding of similar trends do not have any cis-elements in common. This suggests among the promoters of the genes in each EC reinforces independent regulatory pathways for the two inhibitors, the integrity of the clusters. Other studies are necessary providing another mechanism of avoiding spurious to test this model and determine whether this is a general inflammatory reaction. Furthermore, there are some cis- feature of cytokine signaling or limited to IL18 and TNF elements that are over-represented in the activators and, family members. at the same time, under-represented in inhibitors. These cis-elements might be of particular importance for distinguishing between pro- and antisignaling factors. Methods Proinflammatory factors RELB and NFKB2 are both in Microarray experiments (MIAME check list) EC2 while REL is in EC3. However, REL and RELB share 12 cis-elements, but RELB and NFKB2 share only five. Experimental design This is intriguing because it suggests that only cis- Dose response to IL18 (see below for specifics). elements shared between RELB and NFKB2, but not with Each condition performed in duplicate. REL, may confer greater sensitivity to IL18. CLOVER Comparisons were made between conditions using analysis identified two such cis-elements, PAX5 and duplicate average values. CREB. PAX5 is the deciding factor in B-cell commit- Quality control: ment,27 while CREB together with REL are involved in T- RNA preparation: 28S/18SE2.0, 280/260E1.8. cell activation.28 Involvement of these factors in addition Microarrays: Present calls/chipX45%, Scaling factors to NFkB suggests a strengthened inflammatory response all within 2 Â , RawQo10. at intermediate concentrations of IL18. Bioinformatic analysis of transcript profiles suggested Samples, extract preparation and labeling. Approximately a hierarchical response to IL18 and a threshold model 3.0 Â 107 KG1 cells were used for each experimental that could prevent inappropriate activation by IL18. Low condition. Cells were treated with 0, 0.5, 2.0, 10 or 50 ng/ concentrations of IL18 induced little cytokine and ml recombinant IL18 with or without a 30 min. pre- chemokine expression yet induced expression of the incubation with 10 mg/ml cycloheximide. After 2 h, cells genes encoding IkB and other inhibitory molecules. One were harvested for RNA. Total RNA was prepared using interpretation of these results is that there is a mechan- TRIZOL Reagent (Life Technologies). An initial phase ism, by which low-level signals are dampened or edited, separation was performed according to the manufac- preventing inappropriate activation. Consistent with turer’s protocol and was followed by an additional this, at intermediate levels of IL18, we observed induc- extraction using a half volume of phenol : chloroform : i- tion of cytokine gene expression and induction of Rel soamyl alcohol (25 : 24 : 1, Life Technologies). RNA family members encoding activating subunits of NFkB. precipitation and wash were then performed according A model for dampening cytokine responses was recently to the TRIZOL protocol. Approximately 3 mg of RNA proposed by Hoffmann et al,29 who described distinct were electrophoresed on a 1.0% agarose/formaldehyde NFkB responses comparing transient and prolonged denaturing gel to assess quality. For experiments requir- stimuli. These authors observed that transient TNF ing TNF preincubation, KG-1 cells were incubated for stimulation resulted in degradation of IkB-a whereas 12 h with 2 ng/ml TNF prior to stimulation with 2, 10 or IkB-b and IkB-e were resistant. Degradation of the b and 40 ng/ml of IL18. e isoforms of IkB instead required prolonged TNF Preparation of probe and target hybridization—10 mg signaling. The authors also showed that duration of of total RNA and the SuperScript Choice System for signal could differentially regulate the NFkB target genes cDNA Synthesis (Gibco BRL) were used to synthesize IP10 and RANTES. Here, we test dose rather than double-stranded cDNA. The synthesis was carried out duration of exposure yet our results are consistent with according to Affymetrix protocol, which requires T7- those of Hoffmann et al in as much as a signal strength (dT)24 oligomer primers (GENSET) in place of the oligo threshold may also be part of a mechanism preventing (dT) or random primers provided with the kit and which inappropriate activation of inflammatory responses. calls for incubations at 421C during the temperature Failures in such a dampening system could have adjustment and first-strand synthesis steps. The resulting profound consequence in the development of autoim- cDNA was cleaned with Phase Lock Gel Light 2 ml tubes mune diseases. Our study suggests another safeguard for (Eppendorf), and the pellet was resuspended in 12 mlof regulating inflammatory response at the highest IL18 DEPC-H2O. A volume of 5 ml of the cDNA was used in concentration, namely that the Fas gene is upregulated. conjunction with the BioArray High Yield RNA Tran- This indicates the possibility of inhibiting excessive script Labeling Kit (Enzo) to produce biotin-labeled inflammatory activities via apoptosis. Indeed, Ohtsuki cRNA targets by in vitro transcription (IVT) from T7 et al30 reported IL18 upregulation of Fas ligand (FasL) RNA polymerase promoters. Free nucleotides were and induction of apoptosis in KG-1 cells. Two other removed from the IVT reaction with RNeasy Mini studies demonstrated that IL18 can induce apoptosis via Columns (Qiagen). the Fas–FasL pathway in a mouse NK cell line and in a canine cancer cell line, respectively.31,32 Hybridization. A measure of 15 mg of biotin-labeled Thus in our model for macrophage activation, IL18 cRNA was then fragmented according to Affymetrix activates three functionally distinct gene cohorts in a protocol. The entire fragmented sample was combined dose-dependent manner: EC1, inhibiting spurious in- with 5 ml control oligonucleotide B2 (Affymetrix), 15 ml

Genes and Immunity cis-Element clustering D Leyfer et al 360 Table 1 Genes contained within clusters 1–3

Gene name Unigene comment Taqman Affymetrix Blood Locus link

EC1 PTX3 Pentaxin-related gene, IL1 induced N.D. 14.0 5806 GRO2 MIP2a, cxc12 N.D. 10.5 2920 TNF AIP3 TNF alpha-induced protein 3 2.2 6.3 2.1 7128 NFKBIA Nuclear factor of kappa inhibitor, alpha 3.1 5.4 1.8 4792 TNF AIP2 TNF alpha-induced protein 2 N.D. 6.2 7127 IER3 Immediate-early response 3 2.2 7.6 2.3 8870 BIRC3 Baculoviral IAP repeat-containing 3 9.3 24.2 330 APBA2 Amyloid beta (A4) precursor N.D. 6.2 321 LTB Lymphotoxin beta 3.3 6.7 4050 NFKBIE Nuclear factor of kappa inhibitor, epsilon 1.7 7.1 4794 CD83 CD83 antigen 6.0 10.1 4.0 9308

EC2 SDC4 Syndecan N.D. 2.6 6385 SCYA4 Small inducible cytokine A4 N.D. 4.1 6.0 6351 ATF3 Activating transcription factorN.D. 3.0 2.2 467 NROB2 Nuclear receptor subfamily 0, group B, member2N.D. 4.6 8431 SCYA3 Small inducible cytokine A3 4.3 3.3 11.4 6348 IL8 Interleukin 8 4.8 3.9 3576 ICAM1 Intercellular adhesion molecule 1 (CD54) 7.7 2.3 1.3 3383 RELB v-rel homolog B 2.2 2.1 5971 NFKB2 Nuclear factor of kappa gene enhancer 2 2.8 2.8 4791 TRAF1 TNF receptor-associated factor 1 N.D 3.5 7185 GRO3 MP2b, cxc13 7.3 2.8 2921 CNTN2 Contactin 2 (axonal) N.D. 6.4 6900 IL8 Interleukin 8 N.D. 3.9 3576 RGS16 Regulator of G-protein signaling 16 N.D. 5.2 6004

EC3 CETP Cholesteryl ester transfer protein, plasmaN.D. 2.4 1071 L2RA Interleukin 2 receptor, alpha 3.3 3.0 3.8 3559 BPGM 2,3-bis-phosphoglycerate mutase N.D. 2.1 669 REL v-relavian reticuloendotheliosis viral oncogene 3.8 2.4 5966 TNFRSF6 Fas 2.0 2.2 2.0 355 ACADS Short-chain acyl-CoA dehydrogenase 3.6 35

Each table contains an annotated list of transcripts from the indicated Expression Cluster. Columns labeled Taqman indicate fold inductions measured using the Taqman method of quantitative PCR using KG1 mRNA samples. Affymetrix indicates the fold increases measured comparing the average difference values for IL18 treated and untreated KG1 RNA samples. Blood indicates the fold induction values for control and human whole blood treated with 50 ng/ml recombinant IL18 using Taqman. Transcripts colored red are literature annotated as proinflammatory whereas blue indicates antisignaling molecules. The proapoptotic gene Fas is indicated in green. N.D.: not done.

20 Â Eukaryotic Hybridization Control (Affymetrix), 3 ml MAS4 to Microsoft Excel then uploaded into Spotfire sonicated salmon sperm DNA (10 mg/ml, Stratagene), Decisionsite 7.0. MAS4 calculates average difference 3 ml acetylated BSA (50 mg/ml, Gibco BRL), 150 ml2Â values based on perfect match and mismatched probe MES hybridization buffer and water to a final volume of sets. Ratios between the average difference values for 300 ml. Following Affymetrix protocol, Genechip HuGen- treated and untreated samples were calculated. Compar- eFL Arrays (Affymetrix) were pre-wet with 1 Â MES. isons without a ratio of X2 for at least one condition The hybridization cocktails were then heated and were excluded from further consideration. Also excluded centrifuged, and 200 ml was loaded onto the chips. The from further consideration were probe sets assigned chips were spun in a 451C rotisserie oven for 16 h. ‘absent’ by MAS4 using the absolute call procedure. Washing, staining and scanning probe arrays—the Conclusions were based on the probe sets shown below. hybridization cocktail was removed from the chips and replaced with a nonstringent wash buffer. Chips were RT-qPCR reaction set-up. A measure of 250 ng of total washed and stained using the EukGE-WS2 protocol on RNA and the Taqman Gold RT-PCR Kit (Applied the GeneChip Fluidics Station 400 (Affymetrix), a Biosystems) were used to complete the RT-qPCR reac- protocol that stained the chips with both Streptavidin tions following the manufacturer’s instructions. Reac- Phycoerythrin (SAPE) stain solution and antibody solu- tions were carried out using an ABI 7900HT sequence tion. All necessary wash buffers and stains were detection system (Applied Biosystems). The reaction prepared according to Affymetrix protocols. parameters were optimized to include a RT step at 481C for 30 min, followed by an Amplitaq Gold activation step Measurement data. A GeneArray Scanner (Agilent) was at 951C for 10 min. After the enzyme activation, 50 PCR used to scan the stained arrays. Genechip Data Analy- cycles were run with a denaturing step at 951C for 15 s sis—Genechip data were transferred from Affymetrix and an annealing/extending step at 601C for 1 min.

Genes and Immunity cis-Element clustering D Leyfer et al 361 QPCR Data Analysis—qPCR measurements were ana- References lyzed using SDS 2.0 software (Applied Biosystems) for all dye layers and adjusting cycle thresholds to include 1 Robinson D, Shibuya K, Mul A et al. IGIF does not drive Th1 the logarithmic growth phase for all the genes run on development but synergizes with IL-12 for interferon-gamma each plate. The data were finally exported to Microsoft production and activates IRAK and NFkappaB. Immunity Excel for statistical analysis and graphing. qPCR probes 1997; 7: 571–581. were purchased from Applied Biosystems using the 2 Kohno K, Kataoka J, Ohtsuki T et al. IFN-gamma-inducing following catalog numbers: ATF3, Hs00231069_m1, factor (IGIF) is a costimulatory factor on the activation of Th1 BIRC3, Hs00154109_m1; GAPDH, 4333764F; GRO3, Hs00 but not Th2 cells and exerts its effect independently of IL-12. 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Supplementary Information accompanies the paper on Genes and Immunity’s website (http://www.nature.com/ gene).

Genes and Immunity