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Display of wasp venom allergens on the cell surface of Saccharomyces cerevisiae

Background Yeast surface display is a technique, where the proteins of interest are expressed as fusions with yeast surface proteins and thus remain attached to the yeast cell wall after expression. Our purpose was to study whether allergens expressed on the cell surface of baker's yeast Saccharomyces cerevisiae preserve their native allergenic properties and whether the yeast native surface glycoproteins interfere with IgE binding. We chose to use the major allergens from the common wasp Vespula vulgaris venom: phospholipase A1, hyaluronidase and antigen 5 as the model. Results The proteins were expressed on the surface as fusions with a-agglutinin complex protein AGA2. The expression was confirmed by fluorescent cytometry (FACS) after staining the cells with antibody against a C-tag attached to the C-terminal end of the allergens. Phospholipase A1 and hyaluronidase retained their enzymatic activities. Phospholipase A1 severely inhibited the growth of the yeast cells. Antigen 5 - expressing yeast cells bound IgE antibodies from wasp venom allergic patient sera but not from control sera as demonstrated by FACS. Moreover, antigen 5 - expressing yeast cells were capable of mediating allergen-specific histamine release from human basophils. Conclusions All the three major wasp venom allergens were expressed on the yeast surface. A high-level expression, which was observed only for antigen 5, was needed for detection of IgE binding by FACS and for induction of histamine release. The non-modified S. cerevisiae cells did not cause any unspecific reaction in FACS or histamine release assay despite the expression of high-mannose oligosaccharides. In perspective the yeast surface display may be used for allergen discovery from cDNA libraries and possibly for sublingual immunotherapy as the cells can serve as good adjuvant and can be produced in large amounts at a low price.

Background
Identification and characterization of allergenic compounds is essential for development of advanced component-resolved allergy diagnostics and treatment [1,2]. Single allergens can be identified either by resolving an allergenic extract into single proteins or by recombinantly expressing a library of allergenic genes in a host organism. In the later approach phage display in E. coli is commonly used [3,4]. However, E. coli is known to fail to express a number of eukaryotic proteins due to the lack of foldases and chaperones, which are important for the correct folding of proteins. Most allergens have conformational IgE epitopes, which might disappear if the protein is folded incorrectly. This can represent a limitation of a phage display. Yeast offers an alternative approach for display and selection of antigens and antibodies. Firstly, it provides a wider repertoire of correctly folded and glycosylated proteins, secondly, it allows a more convenient and faster screening of positive clones by fluorescent-activated cell sorting. Bowley et al. [5] compared phage and yeast display for their ability to express HIV-1 immune scFv cDNA library. The obtained clones were screened with the same selecting antigen (HIV-1 gp120). Yeast library was far superior to the phage display library selecting all the scFv identified by phage display and twice as many novel antibodies. In another study Wadle et al. [6] identified 33 novel breast cancer-related antigens using yeast surface display library, of these only four were found previously when using bacterial-based libraries. In addition to being useful for novel antigens discovery, the yeast display can be used in various other applications such as protein engineering, immunoassays, affinity purification and as vaccines [7]. Baker's yeast Saccharomyces cerevisiae has GRAS (generally regarded as safe) status, which simplifies its use in pharmaceutical applications. To the best of our knowledge, there are no previous literature reports of yeast surface display technology applied to allergens. A major obstacle in the application of yeast surface display for expression of allergens could be interference from the high-mannose oligosaccharides, which may either bind IgE or hinder IgE binding to the peptide-determinant. IgE antibodies directed towards carbohydrate epitopes (cross-reactive carbohydrate determinants, CCDs) are common in sera of patients allergic to insect venoms and plant allergens [8]. For example, the anti-CCD IgE were found in 28% of honey-bee venom allergic patients [9], 33% of grassallergic patients [10], and 45-55% of carrot-celery allergic patients [11,12]. However, a number of studies have shown that the anti-CCD IgE are commonly directed towards core α1,3-fucose, which does not occur in yeast [8,13].
There are several systems that allow display on the yeast cells, based on a-agglutinin, α-agglutinin or flocculin proteins. A-and α-agglutinins mediate the cell-cell adhesion during the yeast cell mating and are located on the outmost surface of yeast cells. a-type mating cells express a-agglutinin, which consists of AGA1 subunit attached to the cell wall by glycosylphosphatidylinositol (GPI) anchor and of a small AGA2 subunit connected with AGA1 by disulfide bridges. The DNA sequence encoding protein of interest can be fused to the C-terminal of aga2 gene and transformed into an aga1-overexpressing S. cerevisiae strain, which will result in the protein being expressed as fusion with AGA2 on the outmost cell surface of the yeast cells ( Figure 1).
We have chosen common wasp Vespula vulgaris venom allergens as the model for testing allergen expression on the surface of S. cerevisiae. The diagnosis and treatment of stinging insect allergies as wasp and honey bee have been used as an allergy model for several decades [14]. After the substitution of whole body extract therapy by venom extracts in 1979, the efficacy of treatment reached 95% for wasp venom allergy and 80% for honey bee venom allergy [15]. The composition of the vespid venoms has been extensively studied and the major allergic components have been identified [16]. On average there is 1.7-17 μg of protein in a vespid venom sac with 3.3% being phospholipase A1, 1.5% hyaluronidase, and 8.1% antigen 5, which all can cause allergic response in humans [17,18]. Phospholipase A1 is a 35 kDa non-glycosylated enzyme; antigen 5 is a 23 kDa non-glycosylated protein with so far unidentified function [19]. Hyaluronidase is a 45 kDa glycoprotein, in which insect-type glycosylation with α1,3-fucoses is believed to be responsible for cross-reactivity with sera of honey-bee sensitized patients [8,20]. Three allergens from the common wasp venom have been expressed recombinantly in E. coli [21][22][23][24] and insect cells [25,26] and antigen 5 was additionally expressed in yeast Pichia pastoris [23].
Here we describe expression and characterization including the biological activity of three major wasp venom allergens phospholipase A1, hyaluronidase and antigen 5 on the surface of S. cerevisiae cells.

Cloning of allergen genes
The genes encoding major wasp allergens phospholipase A1 (Ves v 1.0101, further called Ves v 1), hyaluronidase (Ves v 2.0101, further called Ves v 2) and antigen 5 (Ves v 5.0101, further called Ves v 5) were amplified from the total RNA of common wasp V. vulgaris by RT-PCR. We also attempted amplifying the gene, encoding a hyaluronidase-like protein without enzymatic activity (Ves v 2.0201), which was found previously in V. vulgaris and V. germanica venoms [25], but only non-specific gene products of ves v 2.0201 were obtained. The genes were subsequently cloned into TOPO vector and sequenced.
There were a few differences from the gene sequences reported by King's group [21,27]. Phospholipase A1encoding gene had six variations, five of which were single point mutations and one was a change of all the three nucleotides in a triplet. For hyaluronidase 4 nucleotide discrepancies from the previously published sequence were observed, all were silent point mutations; hence, the amino acid sequence remained as reported before. Hyaluronidase is known to be more conserved than phospholipase A1. So common wasp hyaluronidase has 92% identity with amino acid sequence of a homolog from white faced hornet, while phospholipase A1 has only 67% identity [21]. The sequence of antigen 5-encoding gene had six single nucleotide variations from King's sequence, four of which have been reported elsewhere (GenBank accession nr. AJ238849). It is important to note that neither of the variations was positioned in the predicted active site (UniProt http:// www.uniprot.org) or affected cysteins, hence the disulfide bond formation should not be disturbed.
In general, the variations in the gene sequences can be explained firstly by different geographical locations as the wasps in King's work were from Vespa Labs (PA, USA), while our wasps were from Denmark in Europe. Secondly, it can come from polymorphism, which has been described even for genes within the same vespids' population. Thus Hoffman sequenced Ves m 1 protein from V. maculifrons and Dol m 1.02 from white faced hornet Dolichovespula maculate and found 3 amino acids variant positions in Ves m 1 and 2 variants positions in Dol m 1.02 [28]. Soldatova, Kochoumian and King [29] described 4 natural variants of dol m 1.01 mRNA sequence.

Expression of allergens on the surface of yeast
The genes were PCR-amplified with overhangs and directionally cloned into a-agglutinin expression vector to make an in-frame fusion with aga2 gene (Figure 1, 2). The plasmids were transformed into S. cerevisiae strain EBY100, which can overexpress another protein of the a-agglutinin system -AGA1. When the cells were grown on inducing medium, the AGA1 and AGA2-allergen fusion was expressed and exported on the cell surface as a complex held by disulfide bonds (Figure 1). A 51-amino acid long fragment of human CD20 protein was used as a non-allergen control. CD20 antigen is expressed on the surface of mature B-lymphocytes and to the best of our knowledge there are no reports on the presence of IgE antibodies to this autologous protein in human sera. The allergens also contained a 10 amino acid-long C-myc tag at the C-terminal. The expression of allergens was quantified by fluorescent cytometry after staining the expressing cells with anti-C-myc antibody conjugated with AlexaFluor488 ( Table 1). The expression of antigen 5 was almost just as high as of the reference protein CD20; however there was very weak expression of phospholipase A1 and hyaluronidase. We speculate that these allergens might be toxic to the yeast cells because of their enzymatic activity. The a-agglutinin vector is a replicating vector, which is retained in the cells due to tryptophan selection. As tryptophan is an amino acid needed in very small amounts, the selection is not very strong and the vector can be lost by the cells. To circumvent the problem we introduced zeocin resistance marker into the vector and performed cultivation in the presence of zeocin antibiotic so that constant selective pressure was applied ( Figure 3, Table 1). The expression level of CD20 and antigen 5 improved from when only tryptophan selection was used; now correspondingly 74.9 and 73.4% of the cells expressed the Figure 1 The principle of surface display using a-agglutinin system. The allergen of interest (here shown ves v 1) is cloned in-frame with aga2 gene and introduced into a yeast strain that can overexpress aga1 gene. The resulting proteins, Aga1 and Aga2-allergen fusion, get connected by disulfide bonds in the secretion process and are exported together on the surface of the cell where Aga1 remains attached to the cell wall by the glycosylphosphatidylinositol (GPI) anchor.
proteins against 43.7 and 32.8% before. Moreover increased mean ratio indicated higher amount of displayed protein per cell. The hyaluronidase and phospholipase A1 expressing cells had increased autofluorescence, which can be a sign of stress. About 5-4% of the cells expressed phospholipase A1 and hyaluronidase, though the amount of allergens per expressing cell was much lower than for antigen 5 or CD20, as can be judged from the low mean ratios (Table 1). Besides improving the allergen expression introduction of zeocin selection also had a positive effect on selecting correct yeast transformants as the false positives were fully eliminated.
In order to evaluate toxicity of the allergens to the expressing yeast cells we performed growth rate experiments, which showed that the phospholipase A1 expression decreased the maximal specific growth rate by 70% and 82% when cells were grown without or with zeocin selection correspondingly ( Figure 4). In contrast, addition of phospholipase A1 (Lecitase® Ultra) directly into The cells were stained with anti-C-myc antibody conjugated with AlexaFluor488 and analyzed by fluorescent flow cytometry. The intensity of the green fluorescent signal was measured. For calculation of percentage of expressing cells and geometrical mean ratio the labeled cells were compared with non-labeled cells. The labeling of CD-20-expressing cells was performed in triplicates and the average and standard deviation are shown.

Figure 2
Vector map of a surface display vector with zeocin resistance. The original vector pCTCON2 [36] was modified by addition of zeocin resistance cassette, containing yeast TEF1 promoter, prokaryotic EM7 promoter, zeocin resistance gene ble from Streptoalloteichus hindustanus and transcription terminator CYC1. The allergen genes were cloned flush downstream the flexible peptide linker (Gly 4 Ser) 3 , which was connected to aga2 gene under control of galactose-inducible promoter GAL1. The allergen genes were also cloned in-frame with C-terminal myc tag. The vector additionally contained ampicillin resistance marker Amp(R) for selection in E. coli, tryptophan selection marker TRP1 for selection in S. cerevisiae, pUC origin of replication for E. coli, and CEN6/ARSH4 origin for vector replication in S. cerevisiae.  the growth medium with CD20-expressing yeast in the amount of 3.3 u/ml (which is about an order of magnitude higher that the expressing cells can accumulate at the given conditions) did not have a reverse effect on the growth rate. Most likely the cells are protected from the extracellular phospholipase by their cell wall and therefore are not influenced by its presence in the medium, while the phospholipase which is produced inside the cells damages them during synthesis and secretion. The hyaluronidase expression caused a statistically significant decrease in the maximal specific growth rate (p < 0.05), though much less pronounced than the phospholipase A1: 8% and 11% for cells grown with tryptophan or with tryptophan-zeocin selection correspondingly. The external addition of Streptomyces hyalurolyticus hyaluronidase at the concentration of 17 u/ml did not affect the growth (the enzyme activity exceeds the recombinant hyaluronidase activity that the cells can accumulate by an order of magnitude). Expression of phospholipase A1 and hyaluronidase might also be limited by the capacity of yeast endoplasmic reticulum to fold these heterologous proteins, which would result in unfolded protein response, characterized by loss of protein expression and various stress reactions [30]. Lower cultivation temperatures have been shown to reduce the unfolded protein response and can be attempted in future studies to improve the cell surface expression of difficult proteins [31].

Enzymatic activity of the surface-bound allergens
We tested the enzymatic activity of the yeast cells expressing phospholipase A1 and hyaluronidase. The enzymatic activity of phospholipase A1 was measured to 0.08 and 2.6 units/10 9 cells when grown with only tryptophan or tryptophan/zeocin selection correspondingly. Hence the addition of zeocin selection improved the expression of phospholipase A1 by an order of magnitude. For the hyaluronidase an improvement was also found. Here the numbers were 31 and 90 units/10 9 cells, which is a 3-fold increase.

Binding IgE from patient serum by FACS
The ability of the surface-expressed allergens to bind human IgE antibodies was tested by incubating the yeast cells with serum, staining with anti-IgE biotinylated antibody and streptavidin-phycoerythrin and analyzing the cells by flow cytometry ( Figure 5). A serumpool from five wasp venom allergic patients was used as positive control and a serumpool from healthy individuals was used as negative control. Preceding FACS analysis the pool of wasp venom allergic sera was tested by western blot with venom extract to confirm that IgE against all the three allergens were present (data not shown).
The yeast cells without surface protein or expressing the reference CD20 protein did not bind IgE antibodies from either serumpool. Antigen 5-expressing cells bound IgE from the wasp venom allergic serumpool, but not from the control serumpool. Hyaluronidase-expressing cells bound very limited IgE but from both serumpools indicating an unspecific IgE effect. The binding of IgE to phospholipase A1 could not be detected presumably because of the low expression level. Double staining with anti-C-myc antibody and IgE confirmed that it is the cell population that binds anti-C-myc and hence has the allergen protein expressed that also gives a signal for IgE binding ( Figure 6).

Histamine release assay
The allergen-expressing cells were tested for their ability to mediate a histamine release from blood basophils sensitized with IgE from wasp venom allergics or healthy controls. Basophils were challenged with wasp venom to illustrate the wasp venom specific response and as seen in Figure 7, only the basophils sensitized with serum from wasp venom allergics released histamine.
Comparable to the IgE-binding analysis, the CD20expressing cells did not mediate a histamine release. Hyaluronidase did not mediate a histamine release supporting that the unspecific IgE binding seen with FACS is not biologically relevant. In 1 out of 4 experiments phospholipase A1 mediated an unspecific histamine release since both wasp venom sensitive and control basophils were activated (data not shown). Antigen 5 however did activate the wasp venom sensitive basophils and a dose response curve could be generated as seen in Figure 7A. The potency of 10 6 antigen 5 -expressing cells correspond to about 1 ng of wasp venom extract. Antigen 5 did not activate basophils sensitized with control serum.

Conclusions
The aim of the study was to test whether allergenic proteins retained their IgE-binding activity when expressed on the surface of yeast cells. Moreover, we aimed at studying whether allergen displaying yeast cells expressed allergenic activity in a biological model of the allergic reaction: the basophil histamine release test. We chose wasp venom allergens as the model allergens, which proved to be a difficult case due to the cellular toxicity of one allergen (phospholipase A1) and low expression of another allergen (hyaluronidase) for unknown reasons. However, some levels of expression of both allergens were obtained and corresponding enzymatic activities were detected, suggesting that the proteins obtained a certain degree of their native confirmation. There have been no reports so far on  The last allergen that we tested, antigen 5 was well expressed on the surface of yeast cells; it retained IgE binding and could induce allergen-specific histamine release. The non-modified yeast showed neither IgE binding in the FACS assay nor activity in the histamine release assay.
The procedure for allergen expression on the surface is fast and the cells can be tested directly for IgE binding by FACS and histamine release without the need for recombinant protein purification. As an eukaryotic host, yeast is more likely to fold eukaryotic proteins more efficiently and to form disulfide bonds correctly, which eliminates the need of refolding the proteins as after expression in E. coli [32,33]. The proteins made by yeast are also N-glycosylated [34], which is sometimes important for proper folding as in the case of hyaluronidase [35]. It should be mentioned that the glycosylation is of high-mannose type and its interaction with human immune system is largely unknown [8]. We, however, did not observe IgE binding to yeast cells that could be related to carbohydrate-determined IgE reactivity. The immunogenic reactivity of antigen 5 should not be related to CCD reactivity, because this protein is not Nglycosylated neither in its native form in the venom nor when expressed recombinantly in yeast P. pastoris [23].
The expression of allergens on the surface of yeast cells presents new opportunities as identification of novel allergens in yeast display cDNA libraries and immunotherapy with yeast cells.

Methods
Patients 5 patients were chosen based on their serum IgE reactivity with venom extract in ImmunoCap assay (Phadia), all CAP class 4 or above. The equal volumes of sera were pooled and used as the positive sera. The negative control sera pool consisted of 3 sera from non-allergic individuals as confirmed by negative histamine release assay with wasp venom. The usage of patients' sera in the current study was approved by the local ethical committee.

Chemicals
The chemicals were purchased from Sigma-Aldrich and BD Biosciences. Zeocin™ was purchased from Invitrogen. Anti-C-myc monoclonal mouse IgG antibody, conjugated to horse radish peroxidase, was purchased from Invitrogen. Mouse monoclonal anti-C-myc antibody (clone 9E10) conjugated with AlexaFluor® 488 was from AbD Serotec. Biotin-conjugated mouse anti-human IgE antibody (clone G7-26) and streptavidin-phycoerythrin (PE) conjugate (SAv-PE) were from BD Biosciences. Hyaluronic acid potassium salt from human umbilical cord and hyaluronidase from Streptomyces hyalurolyticus were from Sigma-Aldrich. The restriction enzymes and T4 DNA ligase were from New England Biolabs Inc. Vespula venom extract used in western blots was a kind gift of Jørgen Nedergaard Larsen (ALK Abelló, Hørsholm, Denmark). Vespula venom extract used in histamine release assay was from ALK Abelló and contained 136 μg/ml protein.

Strains and plasmids
The E. coli strains used for cloning were TOP10 and DH10B, both deficient in recombinase (recA) and endonuclease A (endA). The Saccharomyces cerevisiae strain was EBY100 (a GAL1-AGA1::URA3 ura3-52 trp1 leu2Δ1 his3Δ200 pep4::HIS2 prb1Δ1.6R can1GAL), Trp -Leu -, kindly provided by Dr. K. Dane Wittrup from MIT, USA. The plasmid pCTCON2 was also a gift from K. Dane Wittrup. Vector pPICZalphaA was purchased from Invitrogen. For longer storage the E. coli strains were stored in LB medium with 25% glycerol and yeast strains were stored in YPD with 15% glycerol at -80°C.

Insects
Common wasps (V. vulgaris) were caught at two nests in Denmark. The wasps were classified as V. vulgaris based on their morphology: 15 mm-long body with characteristic yellow and black colors, a black anchor on the head, and black rings on the abdomen.

RNA isolation
The venom sacs were removed with tweezers and immersed in RNAlater solution (Ambion, Inc.), stored overnight at 4°C and then transferred at -20°C for longer storage. For RNA isolation 10 venom sacs were removed from the RNAlater solution, grinded in liquid nitrogen, transferred to a FastPrep tube with 0.25-0.5 mm diameter acid-washed glass beads. 600 μl of RLT buffer was added and the samples were homogenized in a FastPrep FP120 machine (Qbiogene) at 2 cycles of 30 s with power set to 5.5. Further on the total RNA was extracted using RNeasy Mini kit (Qiagen) according to the manufacture's instructions. The final RNA concentration and purity was determined on spectrophotometer and on electrophoresis gel.

Cloning of allergen genes
The genes encoding phospholipase A1 (Ves v 1), hyaluronidase (Ves v 2.0101) and antigen 5 (Ves v 5) were amplified from the total RNA of V. vulgaris using RT-PCR (Superscript III One-Step RT-PCR System with Platinum Taq DNA Polymerase, Invitrogen). The gene encoding hyaluronidase variant (Ves v 2.0201) could not be amplified. As a positive control for RT-PCR reaction we amplified fragments of 18 S and 28 S RNA. The primers used for RT-PCR reactions are shown in Table 2. Two genes, ves v 1 and ves v 5, were amplified together with their signal sequences. For the hyaluronidase (ves v 2) the signal sequence was not known, hence only the part encoding mature protein was amplified. 2.5 μl of the RT-PCR reaction were further used as a template in a 100-μl PCR reaction with Expand High Fidelity polymerase (Roche Diagnostics) and with the same primers to generate sufficient amounts of the fragment for cloning. The PCR reaction product was separated on 1.1% agarose gel stained with SYBR-safe (Invitrogen). The fragments of the correct size were excised with a scalpel and purified from the gel using GFX PCR DNA and gel band purification kit (GE Healthcare). The fragments were cloned into pCR®2.1-TOPO® vector, using TOPO TA Cloning® kit (Invitrogen) and transformed into chemically competent E. coli TOP10 cells. The transformants were selected on SOB plates with 20 mM MgCl 2 , 50 μg/ml kanamycin and 50 μg/ml X-gal. White colonies were screened for the presence of the cloned fragment using colony PCR with the fragment-specific primers (the same as used for RT-PCR). 3-4 correct clones were grown overnight and the plasmid was extracted using GeneElute™ Plasmid Miniprep kit (Sigma-Aldrich). After confirmation of the correct construct by restriction, the plasmids were sequenced at Eurofins MWG Operon or StarSEQ.

Construction of surface display vectors
The genes ves v 1, ves v 2 and ves v 5 were amplified from the corresponding TOPO plasmids TOPO_vesv1, TOPO_vesv2 and TOPO_vesv5 with forward and reverse primers indicated in Table 2 (primers starting with "SD") using Expand High Fidelity polymerase (Roche Diagnostics). The PCR products were separated on 1.1% agarose gel, cut and purified from the gels using GFX kit (GE Healthcare). The purified PCR fragments were restricted with NheI and BamHI enzymes and cloned into pCTCON2 vector, which was digested with the same restriction enzymes and gel purified. The ligation of the vector and the insert was performed with T4 DNA ligase (New England Biolabs, UK) at room temperature for 30 min. The ligation mixture was transformed into chemically competent E. coli DH10B cells and the transformants were selected on Luria-Bertani (LB) agar plates with 100 μg/ml ampicillin. The transformants carrying inserts were identified by colony PCR with the same primers as above. The correct transformants were grown in LB broth with 100 μg/ml ampicillin overnight and the plasmids were isolated using GenElute Miniprep kit (Sigma-Aldrich). The resulting surface display vectors were named pSD_vesv1, pSD_vesv2 and pSD_vesv5. The sequence of the plasmids was confirmed by restriction digestion and by sequencing.

Construction of surface display vectors with zeocin resistance
The zeocin resistance cassette was PCR-amplified with zeo_fw and zeo_rv primers ( Table 2) using plasmid pPICZalphaA as the template. The resulting fragment was purified from the gel, digested with KpnI and cloned into surface display vectors pSD_vesv2 and pSD_vesv5 cut with the same enzyme. The transformants were selected on LB plates with 100 μg/ml ampicillin and 25 μg/ml zeocin, giving pSD_vesv2_zeo and pSD_vesv5_zeo. For the construction of pSD_vesv1_zeo vector a different strategy was applied because the vesv1 gene contained a KpnI restriction site. The PCR-amplified and KpnI-digested zeocin resistance cassette was ligated with pCTCON2 vector digested with KpnI and the ligation mixture was transformed into E. coli. After selection of the zeocin-resistant clones, the plasmid pCTCON2_zeo was isolated and the vesv1 gene was cloned into it in the same way as it was cloned into pCTCON2 vector above.

Yeast transformation
The surface display plasmids pCTCON2, pCTCON2_zeo, pSD_ves1, pSD_vesv2, pSD_vesv5, pSD_vesv1_zeo, pSD_vesv2_zeo, pSD_ves5_zeo were transformed into S. cerevisiae strain EBY100 as following. A single colony of S. cerevisiae was inoculated in 2 ml YPD medium overnight at 30°C with shaking. Next morning 50 ml YPD in a 500-ml shake flask was inoculated with the overnight culture to the start optical density (OD 600 ) of 0.2 and grown until OD 600 of 1.4-1.6. The cells were collected by centrifugation at 3,000 × g for 5 min, washed twice with 50 ml MilliQ water and once with 10 ml transformation buffer (20 mM HEPES in 1 M sorbitol). The cells were eventually resuspended in 100 μl transformation buffer. 40 μl of the cell suspension were mixed with 5 μl of plasmid preparation, electroporated on Gene Pulser (Bio-Rad Laboratories) at 1.5 kV. 1 ml transformation buffer was added to the cells immediately after electroporation and the cell suspension was transferred to a 15 ml tube. After incubation at 30°C for 1 hour the cells were centrifuged, resuspended in 100 μl buffer and volumes of 10 and 50 μl were plated on tryptophan-deficient SDCAA plates [36]. When transforming vectors with zeocin resistance cassettes the SDCAA was supplemented with 100 μg/ml zeocin. Colonies appeared after 2-3 days of incubation at 30°C. The presence of the vector was confirmed by colony-PCR using gene-specific primers.

Cultivation and induction of yeast cells
The cultivation medium was SDCAA and SGCAA as described in Chao et al. [36], except that the phosphate concentration was reduced to 50 mM in order to avoid zeocin inhibition by high salt concentration. The SDCAA medium contained 20 g/L dextrose as carbon source, while in SGCAA medium the dextrose was replaced by the same amount of galactose. A single colony was inoculated in 20 ml SDCAA medium in 500ml baffled flask and grown overnight at 30°C with shaking at 150 rpm to an OD 600 of about 1-2. The cells were harvested by centrifugation and resuspended in SGCAA medium to OD 600 of 1. The cultures were transferred into 500-ml baffled shake flasks and grown at room temperature (22-23°C) for 30 hours. The cultures were stored at +4°C until analysis, but never longer than one week.

Growth experiment
For the growth rate experiments the cells were grown in SDCAA as above and then resuspended to the OD 600 of 0.1 in SGCAA medium with or without 100 μg/ml zeocin. The cell suspensions were pipetted into a sterile 96well flat-bottom microtiter plate (100 μl suspension per well) (Nunc 96-microwell plate from Thermo Scientific).
Sterile SGCAA media was used as the background reference. All the samples were run in triplicates. The plates were covered by air-permeable transparent film and shaken during overnight incubation at room temperature. The OD 600 readings were performed automatically every half an hour with Multiscan Accent (Thermo Scientific). The data was exported into Excel (Microsoft) and used to calculate the maximum specific growth rates during the exponential growth phase.

SDS-Polyacrylamide Gel Electrophoresis
The gel was a pre-cast 10% NuPAGE® Novex® Bis-Tris electrophoresis gel from Invitrogen. The protein size marker was unstained or pre-stained PageRuler™ protein ladder from Fermentas (Germany). The samples were mixed with NuPAGE® LDS sample buffer (4×) and NuPAGE® reducing agent (10×) and heated at 70°C for 10 min before loading on the gel. The electrophoresis was performed at a constant voltage of 200 V for 35 min. The gel was used for western blot or stained with silver stain (Fermentas, Germany).

Western blot
For western blot the proteins were elecrophoretically transferred onto 0.2 μm PVDF membrane Amersham Hybond™-P (GE Healthcare) using Mini Trans-Blot® electrophoretic transfer cell (Bio-Rad Laboratories) at 100 V for 1 hour. The transfer was done in 25 mM Tris, 192 mM glycine, and 20% v/v ethanol buffer.

Detection of expression with anti-C-myc antibody
The cells grown in SGCAA were analyzed for expression of the allergen using Alexa488-conjugated anti-C-myc antibody. The analysis was possible because the allergens were cloned in-frame with c-myc epitope present in the pCTCON2 vector. The C-myc epitope was positioned at the C-terminal of the proteins. The cell volume containing about 10 6 yeast cells (OD 600 of 1 corresponds to about 10 7 cells/ml) was moved to an ependoff tube with 1 ml blocking buffer (5 g/L skim milk powder, 50 mM Tris, 150 mM sodium chloride, 0.1 g/L Tween 20, pH 7.5). The content was mixed by inversion and centrifuged at 4,000 × g for 2 min. The supernatant was removed with a pipette and the cells were resuspended in 45 μl blocking buffer and 5 μl anti-C-myc-Alexa488 and incubated in the dark at room temperature for 1 hour with occasional mixing. Non-labeled controls with omission of antibody were prepared as well. The cells were washed twice with cold TBST buffer (50 mM Tris, 150 mM sodium chloride, 0.1 g/L Tween 20, pH 7.5) and resuspended in 500 μl TBST. The cells were analyzed by flow cytometry on Cytomics FC 500 MPL flow cytometry system with MXP software (Beckman Coulter). The cell debris and other small particles were eliminated from analysis by setting the forward scatter threshold. Normally about 95-97% of the cells were gated.

Binding of IgE from patient serum
The induced cells were analyzed for binding IgE from patients' sera. The cell volume containing about 10 6 yeast cells was mixed with PBSF buffer (8 g/L NaCl, 0.2 g/L KCl, 1.44 g/L Na 2 HPO 4 , 0.24 g/L KH 2 PO 4 , 1 g/L bovine serum albumin, pH 7.4) to the total volume of 1 ml. The cells were centrifuged at 4,000 × g for 2 min and washed with 1 ml PBSF buffer. The cells were pelleted again and resuspended in 50 μl PBSF. 12.5 μl of cell suspension was mixed with 12.5 μl of positive or negative sera pool and incubated at room temperature for 1.5 hours with occasional mixing. The cells were washed with 1 ml ice-cold PBSF twice and mixed with biotinylated anti-IgE antibody diluted 1:200 in PBSF (total volume of 80 μl). For the double labeling the anti-C-myc antibody was added together with anti-IgE antibody at the dilution 1:10. The mix was incubated at 4°C for 1 hour. The cells were centrifuged and washed twice with ice-cold PBSF and mixed with streptavidin-phycoerythrin diluted 1:1000 in PBSF (total volume of 100 μl). The mix was incubated at 4°C for 30 min, the cells were washed twice with ice-cold PBSF, resuspended in 400 μl PBSF and analyzed by flow cytometry as above.

Histamine release assay
Peripheral blood mononuclear cells (PBMCs) from buffy coat blood (n = 3, non-allergic donor, anti-IgE responsive cells) were isolated by Lymphoprep gradient centrifugation. IgE was stripped off the basophils by a rebound in pH from 7.4 to 3.55 and back to 7.4. The PBMCs were then incubated 1 hour with wasp patient or control pool (non-allergic) serum to re-sensitize the basophils, which subsequently were mixed with erythrocytes and challenged in glass fiber coated microtiter plates with control yeast expressing CD20 or yeast expressing phospholipase A1 (Ves v 1), hyaluronidase (Ves v 2) or antigen 5 (Ves v 5). Released histamine bound to the glass fibers was coupled to o-phtahaldialdehyde, stabilized by HCLO 4 , and measured fluorometrically as described previously [37]. Results were expressed as percentage of total cellular histamine content and were considered positive when > 10%.

Enzymatic assays
The enzymatic activity of hyaluronidase was measured by turbidimetric method of Dorfman [38]. The volumes were reduced for microtiter plate format. After incubation with hyaluronic acid the mixture was centrifuged to remove the cells and only supernatant was added to the acid albumin solution. Hyaluronidase from S. hyalurolyticus was used as a standard. Phospholipase A1 enzymatic assay was performed using EnzChek® phospholipase A1 assay kit from Invitrogen according to the manufacturer's protocol. The controls without reagents addition were performed to ensure that the yeast cells did not fluoresce at the used wavelength. The Lecitase® Ultra (Invitrogen) was used as a standard.
The non-transformed yeast cells and the yeast cells expressing CD20 protein were used as the negative controls in both assays.


extfieldsofstudy: Biology Medicine

s2fieldsofstudy: Biology Medicine

text:
STAT1 Is a Master Regulator of Pancreatic β-Cell Apoptosis and Islet Inflammation*

Cytokines produced by islet-infiltrating immune cells induce β-cell apoptosis in type 1 diabetes. The IFN-γ-regulated transcription factors STAT1/IRF-1 have apparently divergent effects on β-cells. Thus, STAT1 promotes apoptosis and inflammation, whereas IRF-1 down-regulates inflammatory mediators. To understand the molecular basis for these differential outcomes within a single signal transduction pathway, we presently characterized the gene networks regulated by STAT1 and IRF-1 in β-cells. This was done by using siRNA approaches coupled to microarray analysis of insulin-producing cells exposed or not to IL-1β and IFN-γ. Relevant microarray findings were further studied in INS-1E cells and primary rat β-cells. STAT1, but not IRF-1, mediates the cytokine-induced loss of the differentiated β-cell phenotype, as indicated by decreased insulin, Pdx1, MafA, and Glut2. Furthermore, STAT1 regulates cytokine-induced apoptosis via up-regulation of the proapoptotic protein DP5. STAT1 and IRF-1 have opposite effects on cytokine-induced chemokine production, with IRF-1 exerting negative feedback inhibition on STAT1 and downstream chemokine expression. The present study elucidates the transcriptional networks through which the IFN-γ/STAT1/IRF-1 axis controls β-cell function/differentiation, demise, and islet inflammation.

Stressful signals are sensed by cells, which respond via the up-or down-regulation of relevant genes and proteins. This process can be divided in two broad steps; first, cells encode the stress signals internally by modulating the expression, activation, and localization of transcription factors, and second, these transcription factors trigger the expression of key downstream genes that mediate diverse cellular responses to the stress (1,2).
Signaling events occurring inside the pancreatic ␤-cells and triggered by diverse stressful mediators are decisive for the survival or death of these cells in type 1 diabetes (T1D) 4 (3). T1D is an inflammatory disorder characterized by infiltration of autoreactive immune cells in pancreatic islets (a process termed insulitis) and by selective destruction of insulin-producing ␤-cells (4). ␤-cell death in T1D occurs through apoptosis induced by a deadly "dialogue" between ␤-cells and infiltrating immune cells, where the proinflammatory cytokines IL-1␤, IFN-␥, and TNF-␣ produced by infiltrating macrophages and T cells play a key role (5)(6)(7)(8).
We have previously shown that pancreatic ␤-cells respond to the proinflammatory cytokines IL-1␤, TNF-␣, and IFN-␥ by modifying the expression of complex gene networks under the regulation of at least two master transcription factors, namely NF-B and STAT1 (3,5). Inhibition of NF-B expression in vitro or in vivo prevents cytokine-induced ␤-cell apoptosis (9,10), and array analysis of IL-1␤ and IFN-␥-treated ␤-cells in the context of NF-B blockade allowed us to identify several key mediators of ␤-cell dysfunction and death, including endoplasmic reticulum stress-related factors (11)(12)(13). Such information would be of particular interest for STAT1-regulated genes, because the IFN-␥-induced transcription factors STAT1 and downstream IRF-1 have been reported to exert opposite effects in ␤-cells. Thus, although STAT1 blockade prevents cytokine-induced ␤-cell death in vitro and diabetes induced by multiple low doses of streptozotocin (14,15), IRF-1 deficiency does not protect ␤-cells against cytokines in vitro. On the contrary, it actually exacerbates local production of chemokines, islet graft infiltration, and rejection in non-obese diabetic mice (16). These observations suggest that although STAT1 regulates genes triggering ␤-cell death and inflammation, IRF-1 may regulate putative anti-inflammatory genes. The nature of these genes, however, * This work was supported by grants from the Fonds National de la Recherche Scientifique (FNRS-FRSM) Belgium, the Communauté Française de Belgique (Actions de Recherche Concerté es), the European Union (NAIMIT, Health F22009-241447; in the Framework Programme 7 of the European Community) and the Belgium Program on Interuniversity Poles of Attraction initiated by the Belgian government (IUAP P6/40). □ S The on-line version of this article (available at http://www.jbc.org) contains supplemental Tables 1-5  remains to be clarified. IRF-1 is induced by IFN-␥ through binding of STAT1 to the IRF-1 promoter, but other transcription factors, such as NF-B, may also induce its expression (17,18). To characterize the broad network of genes regulated by STAT1 and IRF-1, we first validated siRNAs targeting each of these transcription factors and then coupled RNA interference to global evaluation of gene expression. This was done by the use of microarray analysis of insulin-producing INS-1E cells exposed or not to proinflammatory cytokines. These microarray findings were subsequently confirmed in INS-1E and primary rat ␤-cells, and the function of novel STAT1-and IRF-1-dependent genes characterized by RNA interference and additional functional studies. We observed that STAT1, but not IRF-1, up-regulates the proapoptotic protein DP5 (death protein 5/Hrk) and the synthesis of several proinflammatory chemokines, including the CXCR3 ligands CXCL9, -10, and -11, whereas down-regulating genes involved in ␤-cell differentiation and function. On the other hand, IRF-1 induces many genes independently of STAT1, including IL-6RA, PKI␣, or TAP binding protein. Interestingly, our data highlighted a novel role for IRF-1 in providing a negative feedback on STAT1-driven chemokine production through the induction of the regulatory protein SOCS-1. As a whole, these findings allow us to propose a unifying hypothesis explaining the effects of the transcription factors STAT1 and IRF-1 on ␤-cells.
Microarray Data Analysis-Total RNA was isolated from INS-1E using the RNeasy mini kit (Qiagen). Aminoallyl antisense-cRNA was obtained, coupled to either fluorophore indocarbocyanine (Cy3) or indodicarbocyanine (Cy5) (Amersham Biosciences) and prepared for hybridization (21). The gene expression profiling study was performed using the GeneChip Rat Genome 230 2.0 arrays (Affymetrix) containing Ͼ31,000 probe sets and covering Ͼ28,000 well defined rat genes. Gene expression values were calculated from the Affymetrix Cel files using the robust multichip average algorithm (22) implemented in the ArrayAssist Expression software (Stratagene). Only probe sets detected as "present" by the Affymetrix MAS5 normalization algorithm in at least two of eight conditions for at least one time point were considered as present and used for further analysis. The robust multichip average algorithm normalized intensities corresponding to the 21,569 filtered probe sets were then imported to the Bioconductor free software where a robust Welch's t test (based on robust estimators of central tendency and dispersion, namely the median and the interquartile range) was applied to compare each experimental condition at different time points (2, 12, or 24 h) to the corresponding control. Probe sets were considered as differentially expressed between two conditions if they had a mean fold change (up or down) Ͼ1.5 and a p value Ͻ0.02. Lists of cytokine-modified probe sets at each time point included those that were significantly modified when comparing both cytokine-treated to untreated untransfected INS-1E cells and cytokine-treated si-control-transfected to untreated siControl-transfected INS-1E cells. Cytokine-modified probe sets were considered as STAT1dependent when they were significantly modified when comparing cytokine-treated siSTAT1-transfected and cytokinetreated siControl-transfected samples. Cytokine-regulated and IRF1-dependent probe sets were defined in the same way, by comparing cytokine-treated siIRF1-transfected cells with cytokine-treated siControl-transfected INS1-E cells at each time point. The complete array data will be deposited after publication of this article in the EuroDia database.
Infection with Recombinant Adenoviruses-Cells were left uninfected or infected either with Ad-Luc (luciferase-expressing virus) or Ad-srIB (a virus expressing an NF-B super repressor protein) (23). Cells were infected for 2 h at 37°C with a multiplicity of infection of 10. The multiplicity of infection was selected based on lowest toxicity by viral infection combined with highest blockade of NF-B activation. After infection (24 h), cells were treated with cytokines. We have shown previously that infection of ␤-cells with Ad-srIB at the multiplicity of infection used in the present study does not change its function (23).
Assessment of Cell Viability-The percentage of viable, apoptotic, and necrotic cells was determined following a 15-min incubation with the DNA-binding dyes propidium iodide (5 g/ml, Sigma) and Hoechst 33342 (5 g/ml, Sigma) (50). A minimum of 500 cells was counted in each experimental condition. Viability was evaluated by two independent observers, one of them being unaware of sample identity. The agreement between findings obtained by the two observers was Ͼ90%. Results are expressed as percent apoptosis, calculated as (number of apoptotic cells/total number of cells) ϫ 100. Apoptosis was confirmed in some experiments by the Cell Death Detection ELISA PLUS kit (Roche Diagnostics), which detects cytoplasmic fragmented DNA.
Statistical Analysis-Data are presented as mean Ϯ S.E. Comparisons were performed by two-tailed paired Student's t test or by ANOVA followed by Student's t test with Bonfer-roni correction. A p value Ͻ0.05 was considered statistically significant.

Analysis of Gene Networks and Pathways Regulated by IRF-1 and STAT1 in INS-1E Cells-INS-1E
cells were left untransfected or transfected with si-control, siIRF-1, or si-

STAT1
, and subsequently treated with IL-1␤ and IFN-␥ for 2, 12, or 24 h ( Fig. 2A). In the microarray analysis, 21.569 probe sets corresponding to 10.874 annotated genes were detected as present. The complete list of probe sets present for each time point is provided as supplemental Tables 2, 3, and 4. Less than 0.5% of the genes were differentially regulated between the untransfected and si-control-transfected conditions, suggesting that the transfection per se had only minor influence on the cells (Fig. 2E). STAT1 silencing affected the expression of 2.6 -2.9% of the genes in untreated cells, suggesting a role for STAT1 in the control of basal ␤-cell function (supplemental Table 5). Cytokine treatment in untransfected and sicontrol-transfected conditions regulated 21-24% and 14 -18% of the genes at 12 and 24 h, respectively ( Fig. 2E and supplemental Tables 3 and 4), whereas only ϳ5% of the genes were regulated by cytokines at 2 h ( Fig. 2E and supplemental Table  2). At 12 h, ϳ50% of cytokine-regulated genes were at least partially modified by IRF-1 or STAT1 knockdown (Fig. 2C), whereas at 24 h, 42 and 58% of the cytokine-regulated genes were IRF-1-or STAT1-dependent, respectively (Fig. 2D). The effects of siSTAT1 and siIRF-1 on cytokine-induced genes showed only partial superposition, with 18 -33% of the genes regulated by only IRF-1 or STAT1 at 24 h (Fig. 2D). Analysis using Ingenuity Pathways Analysis software revealed that functions associated with cell cycle and development, inflammatory response, and endocrine system disorder were significantly affected by STAT1 silencing (supplemental Fig. 3A). Interestingly, cytokine-regulated functions such as cell death, antimicrobial response, inflammatory response, and antigen presentation were affected by IRF-1 deficiency, suggesting an inhibitory role of IRF-1 in these processes (supplemental Fig.  3A). Canonical pathways regulated by cytokines, including HMGB1, NF-B, and IL-17 signaling, death receptor, and apoptosis signaling were significantly altered by STAT1 knockdown (supplemental Fig. 3B). Supplemental Table 1 represents selected genes with a putative role in ␤-cell function/dysfunction and death using a method described previously (24). Based on both the "handmade" and unbiased analysis, we selected three pathways of high relevance in the context of T1D, namely ␤-cell function/differentiation, apoptosis, and inflammation for additional studies.

STAT1 Silencing Partially Prevents Cytokine-induced Down-regulation of Genes Involved in ␤-Cell Function and
Differentiation-Exposure of the ␤-cell to cytokines decreases the expression of genes involved in ␤-cell differentiation and function (24,25). The present microarray analysis confirmed these findings, since genes such as insulin, Glut2, glucokinase, Pdx1, MafA, and others were significantly down-regulated after 12 and 24 h of IL-1␤ and IFN-␥ exposure (Fig. 3, A-D). Importantly, STAT1 silencing partially prevented the downregulation of several of these genes, including insulin, Glut2, glucokinase, proconvertase 1 and 3 (Fig. 3, A and B), and all of the transcription factors involved in ␤-cell differentiation (Fig.  3, C and D). IRF-1 knockdown prevented the down-regulation of proconvertase 1, glucokinase, Pdx1, and Nkx2.2 at 12 h of cytokine (Fig. 3, A and C), but this protective effect was lost at 24 h (Fig. 3, B and D). These results were confirmed by realtime PCR for selected genes (insulin 1, Glut2, Pdx1, and MafA) in INS-1E cells (Fig. 3E) and primary ␤-cells (Fig. 3F). This suggests that STAT1 mediates at least in part the deleterious effects of cytokines on ␤-cell differentiation during inflammation.
Induction of the Proapoptotic Protein DP5 Is Partially Prevented after STAT1 Knockdown-DP5 (Hrk) is a proapoptotic BH3-only member of the Bcl2 family (26), which plays a central role in cytokine-induced ␤-cell apoptosis (27). The microarray data demonstrated that DP5 induction was hampered by IRF-1 and STAT1 knockdown at 12 h of cytokine treatment (supplemental Table 1). Real-time PCR analysis in INS-1E cells and primary ␤-cells confirmed that STAT1 silencing prevented DP5 induction at 12 and 24 h of cytokine treatment (Fig. 4, A and B), whereas siIRF-1 effect was only transient. Using a luciferase reporter containing the promoter sequence from the rat DP5 gene (28), we observed that STAT1 silencing completely abolished cytokine-induced DP5 promoter expression, whereas it was induced by 2-fold in untransfected, si-control-or siIRF-1-transfected cells (Fig. 4C). We then tested whether STAT1 overexpression affects cytokine-induced DP5 up-regulation. The transfection of a rat STAT1 expression vector in INS-1E cells resulted in increased STAT1 expression at both mRNA and protein levels (supplemental Fig. 4, A and B) and exacerbated DP5 induction after 16 -24 h of IL-1␤ and IFN-␥ treatment (supplemental Fig.  4C). These findings suggest that STAT1 participates in cytokinedependent DP5 up-regulation, a key mechanism of cytokineinduced ␤-cell apoptosis (27). Of note, parallel knockdown of STAT1 and DP5 by specific siRNAs induced a more marked inhibition of cytokine-induced apoptosis than DP5 or STAT1 silencing alone (supplemental Fig. 4, D and E). This suggests that STAT1 regulates other proapoptotic signals than DP5.

IRF-1 Provides a Negative Feedback on Cytokine-induced Chemokine Production-During islet inflammation, ␤-cells produce chemokines that further attract immune cells (7).
Our microarray data demonstrated that IL-1␤ and IFN-␥ exposure induced the early production of CXCL1, -2, -9, -10, -11, and CCL20 ( Fig. 5A; for statistical analysis, see supplemental Table 1). STAT1 silencing down-regulated the production of all chemokines at 12 and/or 24 h of cytokine treatment (Fig. 5A), whereas IRF-1 silencing exacerbated the production of CXCL9 and -11 after 12 h and of all chemokines after 24 h (Fig. 5A). This was confirmed by real-time PCR experiments in cytokine-treated INS-1E cells and primary ␤-cells for the chemokines CXCL1, -9, -10, and CCL20 (Fig. 5, B and C). Again, IRF-1 silencing exacerbated cytokineinduced CXCL1, -9, and -10. This indicates that IRF-1 may provide a negative feedback on STAT1-driven chemokine production. To further investigate this phenomenon, we evaluated the influence of IRF-1 knockdown on STAT1 activation. IRF-1 expression was induced by cytokines until 8 h, and it was silenced by the two IRF-1-targeting siRNAs (Fig. 6A). STAT1 phosphorylation was equally induced in all conditions at 2 and 4 h but remained up-regulated until 16 and 24 h of cytokine exposure in IRF-1-silenced cells (Fig. 6A and supplemental Fig. 5A). This effect was independent of the total STAT1 content and on the activity of the nuclear phosphatase PTPN2 previously reported by our group to regulate IFN-␥induced STAT1 activity in ␤-cells (Fig. 6A) (19). This prolonged STAT1 phosphorylation in IRF-1-silenced cells exacerbated STAT1 transcriptional activity because cytokines increased the activation of a STAT1 reporter in IRF-1-silenced cells as compared with controls (Fig. 6B), whereas an NF-B reporter (used as an external control) was equally induced in all tested conditions (supplemental Fig. 5B). We next evaluated the effect of IRF-1 silencing on the expression of SOCS-1, a negative regulator of STAT1 previously reported to be induced by IRF-1 in fibroblasts (29). The array data indicated that SOCS-1 expression was dependent on IRF-1 and STAT1 at 2 h and mostly STAT1-dependent at later time points (supplemental Tables 2, 3, and 4). Real-time PCR experiments showed that SOCS-1 induction reflected the cytokine-induced IRF-1 up-regulation in INS-1E cells, reaching a peak at 4 h and then slowly decreasing until 24 h (Fig. 6, C and  D). IRF-1 knockdown decreased cytokine-induced SOCS-1 expression at all time points, suggesting that IRF-1 contributes to SOCS-1 expression in ␤-cells (Fig. 6D). To confirm these findings, we transfected INS-1E cells with an expression vector for rat IRF-1, resulting in increased basal-and cytokine-induced IRF-1 expression in these cells (Fig. 6E and supplemental Fig. 5C). Overexpression of IRF-1 exacerbated cytokine-driven SOCS-1 induction (Fig. 6F) while significantly inhibiting the up-regulation of STAT1 and chemokines CXCL1 and -9 after IL-1␤ and IFN-␥ treatment (supplemental Fig. 5, D-F). To confirm the role of SOCS-1 for these inhibitory effects of IRF-1, we performed siRNA-mediated SOCS-1 silencing in INS-1E cells. As shown in Fig. 6G, the two SOCS-1-targeting siRNAs inhibited cytokine-induced SOCS-1 expression by 61-64% and, importantly, prolonged STAT1 phosphorylation as compared with si-control-transfected cells after 16 and 24 h of IL-1␤ and IFN-␥ treatment (supplemental Fig. 5G). Moreover, SOCS-1 silencing by both siRNAs significantly augmented cytokine-induced CXCL1, -9, and -10 mRNA synthesis after 24 h of exposure (Fig. 6, H-J). Collectively, these data suggest that IRF-1 inhibition exacerbates cytokine-induced chemokine production in ␤-cells

STAT1, Regulator of ␤-Cell Apoptosis and Inflammation
through a prolonged STAT1 activation resulting from a deficient SOCS-1 induction in IRF-1-silenced cells. These observations are summarized in Fig. 6K, which represents the proposed negative regulatory feedback loop by which IRF-1 modulates STAT1 activation.

DISCUSSION
Data-driven models based on array analysis identify large numbers of potential correlations, making it difficult to perturb each individual pathway experimentally. One alternative, followed in the present study, is to target key transcription factors regulating relevant gene networks. Cytokine-induced STAT1 activation in ␤-cells is associated with the induction of apoptosis and diabetes progression in murine models of T1D (14,15,30), whereas the STAT1 downstream transcription factor IRF-1 may decrease islet inflammation without directly regulating ␤-cell death (16,31). To explain these apparently divergent effects, we have presently combined siRNA-mediated STAT1-or IRF-1 silencing with global gene expression profiling. The siRNAs utilized (two independent ones for each target gene) were validated by showing their inhibitory effect on the target genes, by the protection they induced against cytokine-triggered ␤-cell death and by the good agreement between their effects and the observed effects in islets from STAT1 and IRF-1 KO mice (15,16). Importantly, the nonspecific siRNA used as control did not affect ␤-cell viability (present study and 19) or function (32) and had only minimal effect (Ͻ0.5%) on gene expression, as evaluated by array analysis (present study). Using this well controlled approach, we observed that cytokine-induced STAT1 and IRF-1 expression regulate gene networks associated with cell cycle, signal transduction, apoptosis, endoplasmic reticulum stress, and inflammation in ␤-cells. A list of some of the key regulated genes is shown in Fig. 7. IRF-1 silencing affected the expression of nearly 800 cytokine-induced genes independently of STAT1 expression (supplemental Table 3 and Fig. 7); this is somewhat surprising as IRF-1 is usually considered a downstream transcription factor of STAT1 (17). We presently show that early transcriptional control of IRF-1 expression in ␤-cells is also dependent on NF-B (that is rapidly activated by IL-1␤ or TNF-␣ in ␤-cells (10)), as NF-B blockade inhibits cytokine-induced IRF-1 up-regulation (supplemental Fig. 1 and Tables 2, 3, and 4). Moreover, IL-1␤ and IFN-␥-induced IRF-1 expression was not decreased by STAT1 silencing in primary rat ␤-cells (supplemental Fig. 1B), confirming that IRF-1 may act independently of STAT1.
Detailed examination of the array data, either manually or by unbiased analysis using the Ingenuity Pathways Analysis software, indicated three key pathways for ␤-cell survival and function, and local inflammation, potentially modulated by STAT1 and, for one of them, also by IRF-1. The first pathway is related to ␤-cell function and differentiation. Loss of a differentiated ␤-cell phenotype occurs during insulitis (5), and our group has reported recently that exposure of primary ␤-cells to IL-1␤ and IFN-␥ or TNF-␣ and IFN-␥ down-regulates several genes involved in ␤-cell-differentiated functions (e.g. insulin, glucokinase, Glut2, prohormone convertases, etc.) as well as many transcription factors involved in the differentiation and maintenance of ␤-cell phenotype (e.g. Pdx1, MafA, Nkx2.2, etc.) (24). Recent evidence points to the central role of IFN-␥ in vivo in this inhibitory effect of inflammation in BB rat ␤-cells (33). The present array confirmed these findings and indicated that STAT1 but not IRF-1 silencing par-  Fig. 1. A and B, DP5 mRNA expression was assayed by real-time RT-PCR and normalized for the housekeeping gene GAPDH. Results are mean Ϯ S.E. of four (A) or five (B) independent experiments. C, INS-1E cells were co-transfected with the DP5 promoter luciferase reporter and control pRL-CMV alone (NT) or in combination with si-control, siIRF-1, or siSTAT1. After 1 day of recovery, cells were left untreated or exposed to 10 units/ml IL-1␤ and 100 units/ml IFN-␥ for 24 h as indicated. Results are mean Ϯ S.E. of five independent experiments and represent fold variation as compared with untreated control condition. *, p Ͻ 0.05; **, p Ͻ 0.01; and ***, p Ͻ 0.001 versus untreated (i.e. not treated with cytokines) or untreated transfected with the same siRNA. §, p Ͻ 0.05; § §, p Ͻ 0.01; and § § § p Ͻ 0.001 versus NT & si-control treated with cytokines at the same time point, ANOVA followed by Student's t test with Bonferroni correction. tially protects ␤-cells against the "dedifferentiating" effects of proinflammatory cytokines. This is in line with observations in other tissues, suggesting that STAT1 inhibits the differentiation of osteoblasts, myoblasts, and human adipocytes (34 -36).

STAT1, Regulator of ␤-Cell Apoptosis and Inflammation
It has been reported that re-expressing a combination of three key developmental transcription factors (Ngn3, Pdx1, and mafA) in adult mouse pancreas reprograms pancreatic exocrine cells into cells that closely resemble ␤-cells (25). People expected to benefit most from reprogramming of pancreatic exocrine cells to ␤-cells are patients with T1D. Insulin epitopes are targets of the immune assault in T1D (37), and new insulin-producing cells will be recognized and attacked by the immune system (38). Our present and previous data (39) suggest that immune mediators of insulitis such as cytokines can "push back" newly developed ␤-cells into a dedifferentiated state. Unless novel strategies are found to prevent these cytokine effects, ␤-cell reprogramming will remain an interesting research finding with limited translational potential. The present data indicate that STAT1 is a promising target for this approach, and it will be of high interest to test whether combinations of key developmental regulators (25) with blockers of STAT1 (present study) or NF-B (3,9) restore and maintain ␤-cell mass in animal models of autoimmune diabetes.
The second pathway studied is related to ␤-cell apoptosis and focused on DP5. DP5 (Hrk) is a proapoptotic BH3-only member of the Bcl-2 family, playing a crucial role for apoptosis in neurons (40 -42). Recent work from our laboratory established that DP5 is central for cytokine-and endoplasmic reticulum-stress-induced ␤-cell death (27). The present data demonstrate that silencing of STAT1 but not IRF-1 prevents, to a large extent, cytokine-induced DP5 mRNA up-regulation in ␤-cells, whereas STAT1 overexpression results in exacerbated DP5 induction upon IL-1␤ and IFN-␥ exposure. This is probably a transcriptional effect, as siSTAT1 (but not IRF-1) also prevents cytokine-induced activation of a DP5 reporter promoter. However, we found no putative binding sites for STAT1 (GAS sequences) in the promoter region of the rat DP5 gene (data not shown), suggesting that STAT1 regulates DP5 expression in an indirect manner. Collectively, these observations are in line with the present and previous observations that inhibition of STAT1 activity but not of IRF-1 protects ␤-cells against cytokine-induced apoptosis ( Fig. 1) (15,16), suggesting that up-regulation of DP5 is an important mechanism by which STAT1 leads to ␤-cell apoptosis. Of K, schematic representation of the suggested regulatory loop controlled by IRF-1 in ␤-cells. IFN-␥ binding to its receptor induces Jak-mediated STAT1 phosphorylation and dimerization (1) and its subsequent migration to the nucleus (2), where it stimulates the transcription of many genes, including chemokines and IRF-1. Once synthesized in the cytoplasm (3), IRF-1 also migrates to the nucleus (4) to stimulate the transcription of several genes including SOCS-1 (5). SOCS-1 may then interfere with Jak-mediated STAT1 phosphorylation (6), hence hampering STAT1 activation over time. In the absence of IRF-1 signaling, the defective SOCS-1 induction allows prolonged Jak-mediated STAT1 phosphorylation (7) and sustained STAT1 activity (8). note, several other apoptosis-related genes such as Puma, CHOP (Ddit3), Bax, Bid, and caspase-4, -7, and -12 were also differentially regulated by cytokines following STAT1 knockdown (supplemental Table 1) and may contribute for cytokine-induced ␤-cell apoptosis. The third pathway identified as STAT1/IRF-1-modulated is related to islet inflammation. During insulitis, locally produced cytokines both contribute to ␤-cell apoptosis (5, 7) and stimulate the production of several chemokines by ␤-cells, further recruiting activated immune cells to the site of inflammation (7,43). This local production of chemokines may be crucial in early T1D, as transgenic expression of CCL2 in ␤-cells induces spontaneous diabetes (44), whereas KO of CXCR3 delays diabetes by preventing attraction of CXCR3expressing T cells (45). Furthermore, recent findings in new onset T1D patients show islet expression of CXCL10, whereas infiltrating lymphocytes expressed its receptor, CXCR3 (46). Our present findings indicate that STAT1 partially regulates cytokine-induced secretion of several chemokines by ␤-cells, including CXCL9, CXCL10, CXCL11, and CCL20. These results are in agreement with our previous observations that islets from STAT1 KO mice have decreased production of CXCL10 upon cytokine exposure in vitro and in vivo (15). In contrast to the inhibitory effect of STAT1 silencing, IRF-1 inhibition exacerbated cytokine-induced chemokine production in ␤-cells, especially at later time points (12 h and particularly 24 h), whereas IRF-1 overexpression hampered STAT1 induction and chemokine production after cytokine exposure (supplemental Fig. 5). These data provide a molecular explanation for our previous in vivo observations in mice, which showed increased primary non-function and rejection of grafted IRF-1 Ϫ/Ϫ islets, which was accompanied by augmented infiltration by macrophages and T cells (16). We thus suggest that IRF-1 provides a negative feedback on STAT1induced chemokine production, which is probably mediated via SOCS-1 up-regulation and STAT1 dephosphorylation. Indeed, SOCS-1 silencing also prolongs STAT1 phosphorylation and exacerbates CXCL1, -9, and -10 production in INS-1E cells (Fig. 6). Transgenic expression of SOCS-1 in ␤-cells reduces diabetes development in non-obese diabetic mice (47) and protects ␤-cells against the deleterious effects of infiltrating CD8 ϩ T cells in the same model (48), reinforcing the role of SOCS-1 downstream of IRF-1. Interestingly, a similar role has been described for STAT3 in myeloid cells, where IFN-␣-induced STAT3 expression represses STAT1driven CXCL9 and CXCL10 induction through heterodimerization and suppression of formation of STAT1 homodimers (49). This mechanism and the presently described IRF-1-mediated negative feedback on STAT1 are probably part of elaborate "defense" mechanisms utilized by long-lived cells, such as pancreatic ␤-cells, to down-regulate local inflammation and thus limit tissue damage (7). Analysis of the array data indicates that the negative feedback by IRF-1 on STAT1 activity is mostly restricted to up-regulation of chemokines; additional studies are required to clarify the mechanisms for this specificity.
In conclusion, we have presently combined RNA interference and array analysis to clarify the gene networks regulated by the IFN-␥-STAT1-IRF-1 pathway in ␤-cells. This enabled the identification of three key pathways that may play a role for loss of functional ␤-cell mass in T1D: 1) ␤-cell dedifferentiation, an effect mediated by STAT1; 2) ␤-cell apoptosis, an effect mediated by STAT1 via DP5 up-regulation; and 3) induction and modulation of chemokine production, an effect mediated by STAT1 but with IRF-1 providing a negative feedback through SOCS-1 induction. This and the discovery of a large number of additional STAT1-and IRF-1-regulated genes in ␤-cells, broadens our understanding of ␤-cell dysfunction and death and opens new possibilities for prevention of loss of functional ␤-cell mass in early T1D.