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(Journal of Leukocyte Biology. 2001;69:912-920.)
© 2001 by Society for Leukocyte Biology

Functional classification of interferon-stimulated genes identified using microarrays

Michael J. de Veer*, Michelle Holko*, Mathias Frevel*, Eldon Walker{ddagger}, Sandy Der§, Jayashree M. Paranjape*, Robert H. Silverman* and Bryan R. G. Williams*


* Department of Cancer Biology, Lerner Research Institute, and
{ddagger} Computer Core, Cleveland Clinic Foundation, Ohio;
{dagger} Department of Genetics, Case Western Reserve University, Cleveland, Ohio; and
§ Department of Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada

Correspondence: Bryan R. G. Williams, Ph.D., Chairman, Department of Cancer Biology NB 40, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195. E-mail: williab{at}ccf.org


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 CONSTRUCTION OF THE ISG...
 FUNCTIONS OF ISGS
 REFERENCES
 
Interferons (IFNs) are a family of multifunctional cytokines that activate transcription of subsets of genes. The gene products induced by IFNs are responsible for IFN antiviral, antiproliferative, and immunomodulatory properties. To obtain a more comprehensive list and a better understanding of the genes regulated by IFNs, we compiled data from many experiments, using two different microarray formats. The combined data sets identified >300 IFN-stimulated genes (ISGs). To provide new insight into IFN-induced cellular phenotypes, we assigned these ISGs to functional categories. The data are accessible on the World Wide Web at http://www.lerner.ccf.org/labs/williams/, including functional categories and individual genes listed in a searchable database. The entries are linked to GenBank and Unigene sequence information and other resources. The goal is to eventually compile a comprehensive list of all ISGs. Recognition of the functions of the ISGs and their specific roles in the biological effects of IFNs is leading to a greater appreciation of the many facets of these intriguing and essential cytokines. This review focuses on the functions of the ISGs identified by analyzing the microarray data and focuses particularly on new insights into the protein kinase RNA-regulated (PRKR) protein, which have been made possible with the availability of PRKR-null mice.

Key Words: cytokine • Janus kinase • protein kinase RNA-regulated


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
CONSTRUCTION OF THE ISG...
 FUNCTIONS OF ISGS
 REFERENCES
 
The interferons (IFNs) are a diverse family of pleiotropic cytokines consisting in humans of the type I species with 12 IFN-{alpha} subtypes, IFN-{varpi} and IFN-ß, and the type II species IFN-{gamma}. IFNs play an essential role in innate immunity by inhibiting the replication and spread of viral, bacterial, and parasitic pathogens. They also modulate immune responses and exert antiproliferative effects in some cell types. As a result of these functions, IFNs are used in the clinic to treat certain viral infections, some cancer types, and multiple sclerosis [reviewed in ref. 1 ]. IFNs mediate their effects by binding to cell surface receptors activating members of the JAK kinase family of proteins. Activated JAK kinases phosphorylate the signal transducers and activators of transcription (STAT) family of transcription factors. The STAT proteins homo- or heterodimerize and form complexes with other transcription factors to activate transcription of IFN-stimulated genes (ISGs) [2 ]. The gene products regulated by IFNs are the primary effectors of the IFN response. Although the functions of most ISGs remain to be elucidated, some of the best studied ISGs play pivotal roles in host defense.

Experiments using mice indicate the IFNs are essential for innate immunity against viral infections. Mice with a targeted disruption of the type I or II IFN receptor genes are extremely susceptible to viral infections. These mice have multiple defects in host defense and show enhanced viral replication in many tissues [3 4 5 ]. IFNs induce the production of several known antiviral proteins including the double-stranded RNA-dependent kinase "protein kinase RNA-regulated" (PRKR), a family of 2',5'-oligoadenylate synthetases that lead to the activation of RNase L and the Mx proteins, all of which have been shown to restrict the growth of certain viruses [1 ]. However, the inhibition of viral replication induced by IFNs is only partially dependent on these particular ISGs, because mice triply deficient for PRKR, RNase L, and Mx1 genes retain partial responsiveness to the antiviral effects of IFNs [6 ]. These results imply that other as-yet-unidentified ISGs are also potent antiviral effectors.

To identify ISGs and perhaps elucidate new functions for IFN, we undertook extensive microarray analysis of RNA samples collected from experiments on human and murine cell lines treated with IFN-{alpha}, IFN-ß, or IFN-{gamma}. Previous work from our laboratory identified 122 ISGs, using HT1080 as the cell type and oligonucleotide microarrays [7 ]. Here we extend and confirm these results using other microarray-screening methods. By combining data from all sources listed in Table 1 , we have screened several thousand individual sequences and have extended the initial 122 ISGs to over 300. To uncover new IFN functions, each ISG was assigned to a series of defining functional categories. Furthermore, the categorized ISGs were assembled into a database that contains gene names, descriptions, accession numbers, and links to other databases containing nucleotide and protein sequence information. The genes were placed into progressively more specific functional categories that are fully searchable. Our laboratory is drawing from the microarray data to construct a cDNA microarray of human and murine ISGs.


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  		Table 1. Microarray Formats and Treatments Screened

 

   CONSTRUCTION OF THE ISG DATABASE
TOP
 ABSTRACT
 INTRODUCTION
 CONSTRUCTION OF THE ISG...
FUNCTIONS OF ISGS
 REFERENCES
 
To determine whether a gene is an ISG, a unique induction cutoff score for each array format was established. All mRNAs identified using Affymetrix (Santa Clara, CA) human 6800 and murine 6500 Genechips were analyzed and compiled with defined cutoff scores as described previously [7 ]. For an individual gene to be included in the database, it must have been induced by IFN-{alpha} at least twofold in two IFN-treated samples or threefold in a single treated sample. We found that this subset includes nearly all the known ISGs that were included on the Affymetrix arrays [7 ]. Only experiments that showed at least 1 in 3 genes to be present and a detection limit of between 1 and 5 pM, determined using spiked RNA controls, were included in the analysis. The INCYTE data sets were obtained using the UniGEM V microarrays (INCYTE, St Louis, MO). The sample RNA was harvested from cells treated as outlined in Table 1 , by Trizol extraction according to manufacturer instructions (Life Technologies, Gaithersburg, MD). The purified RNA was then shipped to INCYTE Corp. for hybridization and analysis. To be included in the database, genes must have increased in expression at least 2-fold in the IFN-{alpha}-treated sample or 1.5-fold by IFN-ß twice during treatment. In general, the INCYTE method underestimated the fold induction of ISGs compared with the Affymetrix method, even when identical RNA templates were analyzed (R. H. Silverman, unpublished results). The array format, cell type, and treatment applied are detailed in Table 1 .

The Affymetrix human 6800 chip set identified 122 ISGs [7 ] that were subsequently included in the functional groupings. This study showed that IFN positively influenced the expression of approximately 1 in every 55 human genes represented on the chip. By extrapolation, this suggests that there may be as many as 636–2,180 ISGs, assuming that the number of genes in the human genome is between 35,000 and 120,000. Because all the data sets are redundant and include both human and murine genes, no overall figure on the number of individual genes screened was determined. Combining the results from the three array experiments and applying the above cutoff criteria, 335 unique ISGs with high homology to known genes and 78 expressed sequence tag (EST) sequences were identified.

The genes were grouped into broad functional families and then further categorized into more specific groups. For example, an IFN-induced protease forming part of the proteosomal subunit was placed in the broad category "Host Defense" and then in the more specific group "Antigen Processing," then "Proteosome Subunit," and finally "Protease." Table 2 outlines the functional categories containing over 4 members, defined for the 335 unique ISGs identified by the microarrays. These groups were assigned by using resources from the following databases: GenBank (http://www.ncbi.nlm.nih.gov/Genbank/index.html), PubMed (http://www4.ncbi.nlm.nih.gov/entrez/query.fcgi), and Gene Cards (http://bioinfo.weizmann.ac.il/cards) [8 ].


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  		Table 2. ISG Categories Containing More Than Four Members

 
The genes have been assembled into a fully searchable database available at the following site: http://www.lerner.ccf.org/labs/williams/. The search options are keyword, accession number, human genome organization (HUGO) gene symbol, or category. A pull-down list of the categories is available for easy searching. Figure 1 outlines the search results obtained when the proteosome subunit category is selected. This search returned six entries and listed the GenBank accession number, Unigene number, a brief gene description, the HUGO gene symbol, and the chromosomal location of the gene if known. The accession number, if selected, will link to the sequence information contained in the GenBank database. The Unigene number links to the Unigene database, and the HUGO gene symbol links to the relevant gene card entry, where some basic functional data are available and alternative nomenclature is listed. The gene symbols and abbreviations used throughout this manuscript conform to HUGO gene symbols.



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  		Figure 1. ISG database search result from the proteosome subunit category. The accession numbers, Unigene number, and HUGO gene symbol all link to relevant databases. The database is accessible from http:www.lerner.ccf.org/labs/williams/.

 
The largest functional category of genes identified from the microarray analysis contained a total of 53 genes, all of which have roles in cellular-signaling pathways. Fifty-one genes have been implicated in contributing to host defense; 39 genes have roles in immune modulation; and 16 genes have roles in inflammatory responses. It is also interesting that 37 transcription factors were induced by IFN, 30 of which activate transcription, while 8 repress transcription and some are both activators and repressors. IFN has been implicated in the host apoptotic response to viral infection [9 10 11 ], which is supported by the identification of 19 ISGs with roles in apoptosis. IFN may also alter the translation or stability of proteins and not just the transcriptional profile of cells, because 11 genes with roles in translation, 7 proteases, and 5 genes in the ubiquitination pathway were identified. Thirteen genes coding for proteins involved in cellular adhesion events and 15 growth factors and 18 genes involved in development and 16 cytoskeletal proteins were identified. Table 2 lists the categories with over four members and the numbers of genes contained within each category. The following sections discuss the functions of the ISGs, with a focus on PRKR and new insights into IFN biology that have been elucidated using the microarrays.


   FUNCTIONS OF ISGS
TOP
 ABSTRACT
 INTRODUCTION
 CONSTRUCTION OF THE ISG...
 FUNCTIONS OF ISGS
REFERENCES
 
Host Defense
The PRKR gene is a previously identified ISG involved in host defense. This gene encodes a cellular double-stranded RNA (dsRNA)-activated kinase. dsRNA is a common intermediate in the replication of many viruses [10 , 12 ]. Many viruses have evolved strategies to inhibit the activation or function of the PRKR protein, implying that it plays an important part in the host response to viral infection [13 14 15 ]. On activation, PRKR phosphorylates the translational initiation factor eIF2{alpha} [10 , 16 ]. Phosphorylation of eIF2{alpha} halts cellular translation, thus inhibiting host and viral protein synthesis in infected cells [12 , 16 ]. We recently showed that PRKR also phosphorylates the B56{alpha} subunit of pyrophosphatase 2A (PP2A), which reduces translation of a luciferase reporter, presumably by inhibition of PP2A dephosphorylation of the eIF4E translation initiation factor [17 ]. Thus PRKR might inhibit translation and viral replication through multiple mechanisms.

Inhibition of translation by dsRNA was the assay used to clone PRKR [16 ]; however, the availability of mice with a targeted deletion in the PRKR gene [18 ] has allowed new roles for the PRKR protein to be elucidated. PRKR-null mice develop normally and have no overt defects [18 ]; however, murine embryonic fibroblasts (MEFs) derived from PRKR-null mice are less sensitive to some apoptotic stimuli than those obtained from isogenic normal mice [19 ]. Also, overexpression of PRKR in 3T3 cells induces apoptosis [20 , 21 ]. Recent evidence has indicated that PRKR is required for the activation of the nuclear factor-{kappa}B (NF-{kappa}B) transcription factor by some inducers [22 , 23 ]. NF-{kappa}B is a latent transcription factor that is sequestered in the cytoplasm by the I{kappa}B{alpha} subunit. The IKK{alpha} and IKKß kinases phosphorylate the I{kappa}B proteins, which targets them for degradation and releases the NF-{kappa}B transcription factor, which then translocates to the nucleus and activates gene expression [24 25 26 ].

The genes induced by NF-{kappa}B play an important role in apoptosis, immune modulation, and induction of inflammatory cytokines [27 ]. Others and we have shown that activation of NF-{kappa}B by dsRNA depends on PRKR activation of the IKKß kinase [22 ]. In PRKR-null cell lines, dsRNA failed to stimulate IKK activity compared with cells from an isogenic background that are wild type for PRKR. Coimmunoprecipitation assays showed that PRKR was physically associated with the IKK complex and transient expression of a dominant negative mutant of IKKß, or the NF-{kappa}B-inducing kinase inhibited dsRNA-induced gene expression from an NF-{kappa}B-dependent reporter construct [22 ]. Taken together, these results demonstrate that PRKR-dependent dsRNA induction of NF-{kappa}B is mediated by NF-{kappa}B-inducing kinase and IKK activation. Whether PRKR kinase activity is required for this function remains a subject of debate [28 , 29 ].

The PRKR protein is required for efficient activation of some stress-activated protein kinases (SAPKs). The cytokines tumor necrosis factor-{alpha} (TNF-{alpha}) and interleukin (IL)-1ß and pathogenic factors such as lipopolysaccharide (LPS) and dsRNA induced phosphorylation and activation of mitogen-activated protein (MAP) kinase kinase (MKK6), p38{alpha} MAPK and Jun N-terminal kinase SAPKs in normal MEFs but not in PRKR-null MEFs [30 ]. This did not reflect a global failure to activate the SAPKs in the PRKR-null background because other physiochemical stressors activated the SAPKs normally [30 ]. The failure to activate SAPKs also appeared to be important in vivo, because induction of two SAPK target genes, IL-6 and IL-12, by LPS was reduced in PRKR-null mice when compared with normal mice [30 ]. NF-{kappa}B and p38{alpha} can synergize to induce inflammatory cytokines, implying that PRKR may be an important mediator of the inflammatory response induced by foreign pathogens.

Recent work has identified that PRKR-null mice are highly sensitive to vesicular stomatitis virus (VSV) or influenza virus. It is interesting that the differences were apparent only when these viruses were administered intranasally and not when they were administered systemically [11 ]. The lungs from infected PRKR-null mice showed much higher titers of virus compared with wild-type mice. The reason PRKR-null mice are more sensitive is not entirely clear; it may be the failure of PRKR to halt protein synthesis in the lungs of PRKR-null mice, allowing increased viral replication, although other eIF2{alpha} kinases are known to exist. A lack of PRKR could result in a reduction of apoptosis, allowing the virus to replicate to higher levels in cells, or stimulation of the immune system may be defective in PRKR-null mice through reduced NF-{kappa}B or SAPK activity. Alternatively it has been demonstrated that MEFs derived from PRKR-null mice fail to produce nitric oxide (NO) in response to LPS, IFN{alpha} and dsRNA [31 ]. NO is an important inhibitor of VSV replication [32 ], and a defect in NO production in the lungs of PRKR-null mice may explain the sensitivity of the lungs to VSV. We are currently using various methods to determine the functions of PRKR which are important in host defense against viral and bacterial infection.

Another transcript encoding the antiviral OAS2 protein was induced by IFN in the array experiments. The OAS proteins are activated by dsRNA and produce 2'5'-oligoadenylates that bind and activate the latent ribonuclease RNase L. The RNase L protein cleaves viral and cellular mRNA and ribosomal RNA, halting cellular production of protein [1 ]. The OAS proteins form a gene family that resides on chromosome 12q24.1 and likely evolved from a single ancestral gene through gene duplication (32a). The p46 (OAS1) and p69 (OAS2) synthetase proteins have antiviral activity through the activation of RNase L after viral infection. However, the recently identified and largest member of this family, p100 (OAS100), does not activate RNase L but rather potentiates apoptosis in cells exposed to dsRNA. Overexpression of p100 but not other OAS family members sensitizes cells to apoptosis by dsRNA [32a ].

The array experiments showed induction of a family of large guanosine triphosphatases (GTPases) known in the mouse as Mx1 and Mx2 and in the human as MxA and MxB. The Mx genes are mutated in most inbred laboratory mouse strains that are highly sensitive to the influenza virus [33 ]. The Mx proteins belong to the dynamin family and inhibit the replication of some RNA viruses by binding to viral ribonucleoprotein structures and preventing transcription of viral RNA or movement of viral subparticles within the cell [34 , 35 ]. Another recently described IFN-induced guanylate-binding protein (GBP) 1 was identified using the arrays and has been shown to have innate antiviral activity [36 ]. Overexpression of GBP1 inhibited the replication of both VSV and encephalomyocarditis virus in 3T3 cells. Expression of antisense GBP1 also reduced the antiviral effect of IFN{gamma} but not IFN{alpha} [36 ]. The GBP1 gene was preferentially induced by IFN{gamma}.

The above ISGs are all previously characterized mediators of innate immunity; other ISGs must be involved in the inhibition of viral replication induced by IFNs because mice triply deficient for PRKR, RNase L, and Mx1 genes retain partial responsiveness to the antiviral effects of IFNs [6 ]. The GBP1 gene product also only partially protects cells from viral killing [36 ]. The complement of the intracellular innate immune response is the humoral immune response, which is mediated by immune effector cells that respond to and clear the infectious agent. The categorization of the ISGs showed a large subgroup of host defense gene-induced humoral immune responses. These immunomodulatory genes included the chemokines, which are small proteins that recruit lymphocytes to sites of inflammation or infection [37 38 39 ]. In all, genes for six chemokines—MIG, EBI1, SCYA2, SCYA5, SCYB10, and IL-8—were identified as ISGs. IFN also induced the expression of four genes—ICAM1, SELL, CD47 (see Fig. 2 ), and ALCAM—that promote lymphocyte adhesion to endothelial cells. Adhesion of lymphocytes to vessel walls is an important first step in the trafficking of lymphocytes to areas of infection. This is the first report we know of that details the induction of the CD47 protein by IFNs. The CD47 protein associates with integrins and plays roles in cell adhesion signaling [40 , 41 ], and CD47-null mice are extremely susceptible to bacterial infection primarily caused by a failure to recruit neutrophils [42 ]. Thus, IFN induces numerous genes that enhance recruitment of immune effector cells to the site of production.



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  		Figure 2. Confirmation of five previously unknown ISGs identified using the Affymetrix murine 6500 array by Northern blotting. Murine L929 cells were treated with the indicated reagents, and RNA was harvested and transferred to nylon membrane. The blots were hybridized with radiolabeled DNA corresponding to the coding region of each of the genes indicated. All probes were verified by DNA sequencing. The fold induction of each gene relative to the control untreated sample (lane 1) is indicated below each lane and was determined by standardizing to the GAPDH signal.

 
IFNs also facilitate the activation immune effector cells [1 , 43 ]. IFN induced the expression of eight genes involved in antigen processing and six genes involved in antigen presentation, and there was no redundancy between these two categories (see Table 2 ). The antigen-processing group contained the IFN-induced peptide transporter protein ABCB2 and also proteosome subunits involved in antigen peptide production such as PSMB8, PSMD8, PSMA2, PSME1, and PSMB10. These proteins form a chain that produces antigen peptides in the proteosome and then transports them to the major-histocompatibility-class (MHC) molecules for presentation on the cell surface [44 ]. IFN also induces both MHC class I (human leukocyte antigen subtyes) and MHC class II molecules, such as CD74 and the coactivator of the immune complex, ß-2-macroglobulin (ß2M). These proteins coordinate the activation of immune effector cells and are important in a robust, lasting immune response against the infectious agent [45 , 46 ]. Thus IFN induces the expression of proteins involved in recruitment of both immune effector cells such as chemokines and adhesion molecules, and IFN potentiates their activation by enhancing the presentation and repertoire of MHC-associated antigen [1 ].

Signaling
IFN induced 53 genes involved in modulating other signaling pathways, the largest single category of genes induced by IFN. The signaling category contained several genes involved in inflammatory cytokine signaling such as MYD88 [47 48 49 ], JUN, RELA, MAP2K1, MAP3K8, and TRADD. The MYD88 protein is an important link in toll-like receptor signaling pathways [49 , 50 ], as well as in the proinflammatory cytokine IL-1 signaling pathway. The TRADD protein is an adapter in the TNF-{alpha} and IL-1 signaling pathways [51 ]. Both the MYD88 and TRADD genes are important in activation of NF-{kappa}B by foreign pathogens and proinflammatory cytokines. Induction of these signaling proteins by IFN could potentially lead to an increased response to ligand binding, which may have implications for the clinical side effects of IFN, including high fever [52 ]. IFNs may alter the tissue specificity of some ligand responses through the induction of a crucial signaling protein in cell types where it is not normally expressed.

IFN also induced expression of an anti-inflammatory protein, LGALS3B [cyclophilin-c-associated protein (CYCAP) in the mouse; see Fig. 2 ]. Mice with a targeted deletion in the CyCAP gene are very susceptible to LPS killing [53 ] and express elevated levels of IFN-{gamma}, IL-12, and TNF-{alpha}. Thus CYCAP may function to curb the proinflammatory effects of IFN. The interplay between the various ISGs that mediate inflammation may be important in reducing the toxic side effects of high-dose IFN therapy, but this requires further study.

Another class of signaling proteins was the G proteins. These included RAN, RANBP, NET1A, and GEM. G proteins mediate many intracellular functions, including cytoskeletal remodeling, vesicle transport, and growth [these functions are reviewed in ref. 54 55 56 ]. Potential modifiers of the Ras G protein also were induced by IFN; RAN, ras homologue ARHC, ras-related rab-8 MEL, and ras GTPase-activating protein IQGAP1 were all identified as ISGs. The ras signaling pathway leads to activation of cell growth, and overstimulation of the ras pathway is a common defect in many cancers [57 , 58 ]. Activation of signaling pathways stimulated by mitogenic growth factors is also a common property of many cancers. IFN induced 15 genes that are involved with growth factors and growth factor signaling. These included VEGF, FGF, VRP, PDGFRL, ECGF1, EREG, and CTGF. Most of these growth factors are mitogenic and have been implicated in the control of angiogenesis and cancer [59 60 61 62 ], raising the interesting possibility that IFNs may influence angiogenesis. IFN is a potent antitumor agent in a limited number of cancer types [63 ]; however, if the induction of growth factors is confirmed in vivo, IFN treatment of cancers that rely on growth factors for survival might be detrimental.

The induction of signaling proteins by IFN was mirrored by the induction of a large number of transcription factors, 37 in total. Of the 37 transcription factors 30 activated transcription whereas only 8 were confirmed to repress transcription. Some of the genes categorized under transcription factors both activated and repressed transcription, and the direct role of others was unknown. The array experiments identified six members of the IFN response factor (IRF) family of proteins: IRF1, IRF2, IRF3, IRF4, IRF5, and IRF7. The IRF proteins are a family of secondary effectors that mediate immune modulation, IFN production after viral infection, and IFN signaling [64 65 66 67 ]. This family of proteins, which is crucial to the biological response to IFNs, was the most represented family of transcription factors identified by the array experiments.

Other interesting transcription factors induced by IFN were the hypoxia-inducible factor (HIF1A) gene (see Fig. 2 ) and the Myc promoter-binding protein (MPB1). The HIF1{alpha} protein stimulates transcription of genes that mediate the intracellular response to anoxia and induces angiogenesis [68 , 69 ]. This adds further support for a role of IFN in stimulating angiogenesis. HIF1{alpha} is overexpressed in some cancer types, where it is thought to be important for protecting the tumor cells from anoxia and stimulation of angiogenesis into the tumor [70 ]. The MPB1 protein binds the Myc promoter and represses transcription [71 ], which might be one of the mechanisms IFN uses to down-regulate myc expression and reduce proliferation in certain cell types [1 ]. This protein may play a role in the antitumor activities of the IFNs. Thus it appears that IFN induces proteins involved in both growth activation and attenuation. It will be interesting to see whether the induction of these genes is cell type specific and correlates with the effects of IFN on the cell type.

IFN also induced many proteins involved in the posttranscriptional regulation of gene expression. These include genes involved in translation, such as those encoding elongation and initiation factors: EIF2A, EIF2B, EIF2S2, EIF3S10, and EIF3S6 and the genes encoding the translational inhibitors IFN-inducible 56K (IFI56) [72 , 73 ] and PRKR [10 ]. It is unclear whether induction of the elongation and initiation factors increases translation of proteins, because IFN has never been shown to enhance translation. The role of induction of translation elongation and initiation factors in the IFN response remains to be studied. The dsRNA- and IFN-induced IFI56 protein appears to inhibit translation after IFN stimulation of cells, through sequestration of the translation initiation factor eIF-3 [73 ]. The PRKR protein kinase is activated by dsRNA and inhibits translation by phosphorylation of eIF2{alpha}.

IFN also regulated many genes involved in protein degradation with seven proteases and five ubiquitin related genes. Three of the proteases are catalytic components of the proteosomal subunits which, coupled with the ubiquitination pathway, are responsible for the targeted degradation of many proteins. As our understanding of the posttranslational modification of proteins expands, the roles it plays are becoming increasingly important [25 , 44 , 74 ]. IFN also regulated several RNA-interacting proteins, consisting of two helicases (DDX3 and DDX21) and four genes shown to play a role in RNA splicing (SFPQ, SFRF2, SF3A3, and SF3A1). Thus, IFN may modulate the production of functional proteins at several levels, transcriptional induction of mRNA, the splicing and processing of this RNA, translation, and finally degradation of the protein.

The apoptosis category contained 19 ISGs. Apoptosis is the result of a proteolytic cascade of cysteine proteases (caspases) which leads to cleavage of important substrates and subsequent cell death [75 ]. IFN induced mostly proapoptotic proteins including CASP4 (see Fig. 2 ), CASP8, trail (TNFSF10), BAK1, and Fas or CD95 (TNFRSF6). All these proteins are involved in the activation of apoptosis by numerous inducers [76 77 78 79 ]. CASP4 and CASP8 are caspases that actively cleave other caspases and transduce the proteolytic cascade. The TNFRSF6 protein is a death receptor protein involved in signaling T-cell killing [76 ], while the TNFSF10 protein is a soluble TNF-like molecule involved in the induction of apoptosis when it binds its receptor [78 ]. Also, the phospholipid scramblase (PLSCR1) protein, a new ISG, was induced by IFN and is implicated in moving phosphatidyl serine to the outside of the plasma membrane in apoptotic cells [79 ]. This is a critical step in facilitating the recognition and destruction of the apoptotic cell by immune effector cells and is also involved in blood clotting [79 ]. The IFNs have been reported to be proapoptotic cytokines; they induce apoptosis in cells infected with certain viruses [80 ] and can also cause apoptosis in some transformed cell lines [81 , 82 ].

To aid in analysis of the IFN-response, we are arraying as many ISGs as we can obtain onto a single ISG-chip. A prototype of this array has been screened using cDNA from a renal cancer cell line, RCC1, that was either treated with 100 IU of IFN{alpha}2b for 16 h or left untreated. Total RNA was isolated using the Trizol method (Life Technologies). A total of 1 µg of each RNA was amplified using two rounds of ds-cDNA synthesis followed by T7-driven in vitro transcription [83 ]. The untreated RNA was labeled with the Cy5 (red) fluorophore, and the RNA from IFN-treated cells was labeled with the Cy3 (green) fluorophore (Amersham Pharmacia Biotech, Little Chalfont, Buckinghamshire, England) [83 ]. The hybridized and scanned array and a selection of the results that were obtained are shown in Figure 3 . The genes induced by IFN show increased green fluorescence while those suppressed by IFN show increased red fluorescence. Those that remained unchanged during this experiment are yellow.



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  		Figure 3. In-laboratory ISG cDNA array. Shown is the result from hybridizing the ISG array created in our laboratory with cDNA from IFN-treated human RCC1 cells. cDNA prepared from RNA from control untreated RCC1 cells was labeled with the Cy5 dye (red), and cDNA from IFN-treated RCC1 cells was labeled with Cy4 (green). A sample portion of the array after hybridization is shown with known ISGs highlighted, and the relative intensities and fold induction values for known ISGs are indicated._art>

 
When the ISG array is completed, it will be used to confirm the induction patterns of the novel ISGs we identified using the different microarray formats (outlined in Table 1 ). The ISG chip will also allow rapid screening of a large number of ISGs to identify differences in the their induction pattern after many stimuli. We intend to monitor the expression of ISGs in cancer patients treated with IFN, which might identify ISGs that are important in the clinical responsiveness of cancers to IFN once the data are correlated with patient responses to IFN therapy.

Figure 4 summarizes the numbers and various functions of ISGs identified by microarray analysis. The analysis of microarray data has offered new insights into IFN biology through the identification of genes such as CyCAP, MYD88, and CD47 and the gene encoding phospholipid scramblase. These genes and others have opened up potential new areas of IFN biology and have provided insights into some of the proteins that are important in the IFN response. The further analysis of genes induced by IFN will lead to a greater understanding of the multitude of effects these cytokines exert on cells. It may aid in the identification of novel therapeutic uses for IFN and should identify new candidates that may prove useful to monitor clinical responsiveness to IFN therapy. It is important that the array experiments, although reliable, are still subject to error; some of the ISGs mentioned may not be confirmed in further studies or may be induced only by IFN in a small number of cell lines. The compilation of the ISGs we have presented in the ISG database provides a new resource that will facilitate further research on IFN-mediated cell responses. It is our aim to maintain and update the database and incorporate newly recognized ISGs as these become known. We will be pleased to add novel ISGs identified by other laboratories and invite investigators to contact us with new information and/or comments.



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  		Figure 4. Schematic diagram indicating the numbers and various functions of ISGs identified by the microarray analysis.

 


   ACKNOWLEDGEMENTS
 
This investigation was supported by U.S. Public Health Service grants from the Department of Health and Human Services, National Institute of Allergy and Infectious Diseases (AI34039 to B.R.G.W.) and National Cancer Institute (CA 44059 to R.H.S.) and by a grant from Ares-Serono (to R.H.S.).

We thank Mathias Frevel for constructive comments on the manuscript.

Received January 8, 2001; revised April 16, 2001; accepted April 19, 2001.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 CONSTRUCTION OF THE ISG...
 FUNCTIONS OF ISGS
 REFERENCES
 

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