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Endocrinology, doi:10.1210/en.2004-0691
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Endocrinology Vol. 145, No. 10 4513-4521
Copyright © 2004 by The Endocrine Society

Identification of Tissue-Restricted Transcripts in Human Islets

Antonella Maffei, Zhuoru Liu, Piotr Witkowski, Federica Moschella, Giovanna Del Pozzo, Eric Liu, Kevan Herold, Robert J. Winchester, Mark A. Hardy and Paul E. Harris

Institute of Genetics and Biophysics Adriano Buzzati-Traverso, National Research Center (A.M., G.D.P., P.E.H.), Naples 80125, Italy; Department of General Surgery, Medical University of Gdansk (P.W.), Gdansk 80-210, Poland; and Departments of Medicine (A.M., F.M., K.H., P.E.H.), Pediatrics (R.J.W.), and Surgery (Z.L., P.W., E.L., M.A.H.), Columbia University Medical School, New York, New York 10032

Address all correspondence and requests for reprints to: Dr. Paul E. Harris, Department of Medicine BB 20-06, Columbia University College of Physicians and Surgeons, 650 West 168th Street, New York, New York 10032. E-mail: peh1{at}columbia.edu.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results and Discussion
 References
 
The purpose of our study was to identify transcripts specific for tissue-restricted, membrane-associated proteins in human islets that, in turn, might serve as markers of healthy or diseased islet cell masses. Using oligonucleotide chips, we obtained gene expression profiles of human islets for comparison with the profiles of exocrine pancreas, liver, and kidney tissue. As periislet presence of type 1 interferon is associated with the development of type 1 diabetes, the expression profile of human islets treated ex vivo with interferon-{alpha}2ß (IFN{alpha}2ß) was also determined. A set of genes encoding transmembrane- or membrane-associated proteins with novel islet-restricted expression was resolved by determining the intersection of the islet set with the complement of datasets obtained from other tissues. Under the influence of IFN{alpha}2ß, the expression levels of transcripts for several of the identified gene products were up- or down-regulated. One of the islet-restricted gene products identified in this study, vesicular monoamine transporter type 2, was shown to bind [3H]dihydrotetrabenazine, a ligand with derivatives suitable for positron emission tomography imaging. We report here the first comparison of gene expression profiles of human islets with other tissues and the identification of a target molecule with possible use in determining islet cell masses.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results and Discussion
 References
 
WITHIN THE NORMAL adult human pancreas are 250,000–1,000,000 distinct microanatomical structures known as the islets of Langerhans. These cell masses, of which 50–80% are the insulin-secreting ß-cells, are also populated with other endocrine cells ({alpha}-, {delta}-, and {gamma}-cells); endothelial cells of a fenestrated capillary system; parasympathetic, sympathetic, and sensory nerves; and cells of hemopoietic origin (e.g. monocytes and dendritic cells). Type 1 diabetes (T1D) is a T cell-mediated autoimmune disease characterized by progressive destruction of islet ß-cells and loss of insulin production. Several studies have linked progression of T1D to viral infections (1, 2, 3), suggesting a role for type 1 interferons (IFNs) in disease progression. IFN{alpha} has been shown to regulate ß-cell permissiveness to viral infection (4), and its presence correlates with ß-cell injury in both animal models and recent-onset T1D (5, 6, 7).

In disease, the functional capacity of islet ß-cells can be estimated in vivo by measuring secreted insulin concentration in blood, but the ratio of secreted insulin to ß-cell mass, an index that would provide a measure of reserve capacity, is currently not ascertainable. Because there is no way at present to image pancreatic ß-cells, many questions remain unanswered regarding the pathogenesis and therapy of diabetes, particularly in the early phases of disease. A noninvasive means of imaging islets (e.g. radioimmunoscintigraphy) would allow longitudinal studies of islet mass during the clinical evolution of diabetes or after islet transplantation. Similarly, there is no direct way to gauge the intensity of autoimmune attack on ß-cells.

Both rodent and human islet tissue and/or derived cells have been analyzed by broad scale transcript profiling or proteomic methods (8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19). The purpose of this study, in contrast to those previously reported, was to identify transcripts specific for cell surface proteins and membrane-associated receptors in human islet tissue with the potential to serve as islet- or ß-cell-specific markers for use in imaging of islet cell masses, and to determine how the expression of these molecules might be regulated by IFN{alpha} to provide a measure of injury occurring in the islets. Toward this end, we have used gene expression profiling to identify a series of known and unknown (e.g. expressed sequence tags) transcripts corresponding to molecules with highly restricted distributions of tissue expression and known or inferred membrane associations with possible use in ß-cell mass determinations.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results and Discussion
 References
 
Chemicals
Tritiated and cold dihydrotetrabenazine (DTBZ) were purchased from American Radiolabeled Chemicals (St. Louis, MO). {alpha}-[2-3H]DTBZ was labeled to a specific activity of 10–20 Ci/mmol. All other chemicals, protease inhibitors, and biochemicals were purchased from Sigma-Aldrich Corp. (St. Louis, MO).

Tissue samples
Islet and exocrine pancreas tissue samples were obtained with institution review board approval from the New York Regional Islet Cell Resource Center at New York Presbyterian Hospital, Columbia Presbyterian Campus. Pancreata were removed from heart-beating donors within 48 h of brain death and stored in chilled University of Wisconsin solution after informed consent had been obtained from the donors’ relatives. Sample characteristics are given in Table 1Go. Normal kidney tissue was obtained with institution review board approval from patients with renal cell carcinoma. Total RNA from whole pancreas, liver, kidney, and other adult tissues were obtained commercially (Ambion, Inc., Austin, TX; BD Clontech, Palo Alto, CA).


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  		TABLE 1. Donor and sample characteristics

 
Islet and exocrine pancreas isolations
The islet and exocrine pancreas tissue used in these studies were prepared using minor modifications of the Edmonton purification protocol previously described by Shapiro et al. (20). Briefly, islets were isolated by perfusing the pancreatic duct with a cold enzyme mixture containing Liberase HI (Roche, Indianapolis, IN). Tissue was then transferred to a Ricordi chamber and separated by gentle mechanical agitation and enzymatic digestion at 37 C. Islets were purified with the use of discontinuous gradients of Ficoll-diatrizoic acid (21) in an aphaeresis system (model 2991, Cobe Laboratories, Lakewood, CO). The discontinuous Ficoll gradient used solutions densities of 1.108, 1.096, and 1.037 g/ml layered upon each other before the separation step. During centrifugation, islets migrate to the interface at 1.037 and 1.096 g/ml (22). The exocrine pancreas cells were obtained above the 1.108 g/ml Ficoll layer.

Determination of islet cell mass, viability, and purity
Aliquots were collected for determination of the yield and purity of the islets (as visualized by dithizone staining), expressed in terms of islet equivalents, the standard unit for reporting variations in the volume of islets, with the use of a standard islet diameter of 150 µm. Islet function was characterized by the extent of insulin secretion in vitro during a glucose challenge. The islet and exocrine cell viability was estimated by using trypan blue and propidium iodide (Molecular Probes, Eugene, OR). Purified islets after culture were insulin positive by immunohistochemistry (data not shown). To evaluate the composition of the islet tissue samples at the nucleic acid level, we compared the levels of expression of several islet-specific transcripts (Table 2Go) as well as determined the overall differences in gene expression patterns of the islet tissue and their relation to gene expression in the exocrine pancreas samples analyzed, For the latter analysis, we performed a hierarchical clustering on a subset of the expression data obtained using the U133-A and -B chipset (Affymetrix, Santa Clara, CA).


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  		TABLE 2. Transcript pool characteristics

 
Islet tissue culture and functional assays
Glucose-stimulated release of insulin by isolated islets was performed as previously described (23). In brief, the islets were incubated for 24 h at 37 C in CMRL 1066 medium with 2.5% (wt/vol) human serum albumin and 25 mmol HEPES buffer. Duplicate aliquots of equal numbers of similarly sized islets were incubated in a low concentration of glucose (30 mg/dl) and a high concentration of glucose (300 mg/dl) for 2 h, and the amount of insulin generated in response to the high glucose challenge was divided by the amount generated by the low glucose challenge to yield the mean insulin release index. The amount of insulin released into culture medium was measured using the ELISA kit from BioSource International (Camarillo, CA) following the manufacturer’s recommendations. The mean values for this assay performed on the islet samples analyzed are given in Table 1Go. As indicated in Table 1Go, in some experiments, islets were cultured for 36 h in complete CMRL with or without IFN{alpha}2ß (intron A; Schering Co., Kenilworth, NJ). Viability after culture was always greater than 90%.

RNA preparation
Kidney tissue samples were stored in RNAlater (Ambion, Inc.) at –20 C. Exocrine pancreas tissues were processed immediately after isolation. Islet tissue (~100,000 islets) was processed immediately after isolation or after a short period in tissue culture. Total RNA was prepared in two steps using the TRIzol reagent (Invitrogen Life Technologies, Carlsbad, CA), followed by RNeasy (Qiagen, Valencia, CA) purification. As preliminary estimate of the RNA integrity, electrophoresis of a 2-µg aliquot of the total RNA isolated from the samples was performed on a 1.6% agarose gel containing 1 µg/ml ethidium bromide.

cRNA probe preparation, oligonucleotide chip hybridization, and scanning
Total RNA extracted from islets and other tissues was converted into labeled cRNA and hybridized to the Human Genome U133 Set (Affymetrix), containing 44,928 probesets representing more than 39,000 transcripts. cRNA probes were synthesized from 5 µg total RNA in a single round amplification as recommended by Affymetrix and previously described (24). The generation, fragmentation, and hybridization of the biotinylated cRNA as well as the scanning of the chips were performed according to the Affymetrix protocol. After hydrolysis, the cRNA probe fragments ranged from 50–200 bp, as determined by agarose gel electrophoresis. The cRNA probes were first hybridized to the Affymetrix test chip. cRNA preparations of sufficient quality were then hybridized to the U133-A and -B chips. Fluorescence intensity at each probeset on the chip was measured at 570 nm in an Affymetrix GeneArray scanner. The detection call (present, absent, or marginal) and background-subtracted, noise-adjusted expression values (i.e. signal) for the probesets were determined with the statistical algorithms within the Affymetrix Microarray Suite software (version 5.0), using the following values; {alpha}1 = 0.05, {alpha}2 = 0.065, {tau} = 0.015, target signal value (TGT) = 250, and normalization factor (NF) = 1.000. Lastly, as a metric of cRNA probe quality, we examined the ratios of signal intensities of 3' and 5' probesets for specific housekeeping genes and the frequency of present, marginal, and absent calls generated by the Affymetrix data analysis software on data obtained from the U133-A and -B microarrays (Table 2Go).

Data analysis
In silico subtractive suppressive hybridization.
We devised the following approach to identify islet cell transcripts with restricted tissue distributions that could possibly encode useful markers for islet imaging (Fig. 1Go). Starting with the complete gene expression dataset (seven islet samples from four different donors, two kidney samples from pooled donors, and two liver samples from pooled donors queried by the ~45,000 probesets present on the U133-A and -B chipset), we removed all probesets that received an absent call across all islet samples analyzed (~15,000 probesets) and retained 29,000 probesets receiving present or marginal calls in one or more islet samples. We proceeded next to identify a set of transcripts expressed by human islets, but not by pooled liver and pooled kidney tissue (i.e. a set of transcripts receiving absent or marginal calls in both liver and kidney datasets, but present within the 29,000 probesets representing transcripts expressed in all human islet samples). This resulted in a group of about 8,000 probesets. We then examined the gene expression data from the exocrine tissue samples studied and identified the set of genes not detected in any of the exocrine tissue preparations studied and determined the overlap of this set (i.e. the complement of the set of genes detected in the exocrine tissue preparation) and the set of transcripts expressed by human islets, but not in kidney or liver. This subtraction produced a set of about 5,000 probesets, corresponding to transcripts expressed in human islet tissue but absent from the exocrine pancreas tissue preparations, kidney and liver. Approximately 500 of these probesets corresponded to genes of known or predicted transmembrane or membrane association, as determined by the current Affymetrix annotation files for the U133-A and -B chipset and Gene Ontology Consortium (Amigo) tools. In parallel, we identified the set of genes found to be up- or down-regulated in islet tissue after culture in IFN{alpha}2ß. The full gene expression dataset, comprising islets, exocrine, kidney, and liver samples, measured on the Affymetrix U133-A and -B chips will be made available at www.cbil.upenn.edu/RAD3/ php/query.php?.



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  		FIG. 1. Set annotation diagram of data filtering strategy. Using the Affymetrix call determinations (present, marginal, or absent) assigned for each probeset on the U133-A and -B chipset, data for each tissue sample analyzed were grouped into an absent (composed of absent and marginal calls) or present category. If a transcript received a present call in one tissue sample, it was considered present in all other samples of the same tissue and was included in subsequent analysis. Transcripts that were not detected (i.e. did not receive at least one present call) in any of the samples for a particular tissue formed the complement of present set (e.g. Is'). The islet tissue dataset was composed of all islet tissues analyzed (Table 1Go). Transcripts present in islet tissue, but not detected in any of the three other tissues (kidney, liver, and exocrine pancreas), formed the islet tissue-restricted set. A subset of transcripts present in islets, but regulated by IFN{alpha}, is designated Is ifn {alpha}.

 
Quantitative analysis of mRNA accumulation by real-time PCR.
Quantitative measurements of specific transcripts were acquired by real-time RT-PCR, using the Cepheid Smart Cycler System (Sunnyvale, CA). cDNA templates were obtained using the reverse transcription system from Promega Corp. (Madison, WI), from 1 µg total RNA. One one-hundredth of the cDNA obtained was used as template for each PCR. The QuantiTect SYBR Green PCR Kit (Invitrogen Life Technologies) was used to perform all the real-time PCRs in presence of 0.2 µM primers in a total volume of 25 µl. Reaction conditions were the same in all experiments, except for the annealing temperature, which differed depending on the primer. The following reaction conditions were used: one cycle at 95 C for 900 sec, followed by 45 cycles of amplification (94 C for 15 sec, 55–60 C for 20 sec and 72 C for 20 sec). All primers were designed to reside on two different exons separated by at least one intron. All oligonucleotides used as primers have been synthesized by Invitrogen Life Technologies or Ambion, Inc. The sequences of the oligonucleotides used as primers in the RT-PCR experiments were the following: 5'-TCATGAAGTGTGACGTTGACATCCGT-3' (ß-actin-5') and 5'-CCTAGAAGCATTTGCGGTGCACGATG-3' (ß-actin-3'); 5'-GGACAAAGCCAACCTGGAAA-3' [human leukocyte antigen (HLA)-DRA forward] and 5'-AGGACGTTGGGCTCTCTCAG-3' (HLA-DRA reverse); 5'-GCAAGGTGTACTGGGAGGTG-3' [IFN regulatory factor-7 (IRF7) forward] and 5'-CGAAGCCCAGGTAGATGGTA-3' (IRF7 reverse); 5'-ATTAACCAACAGAGTCCTTTCTGG-3' [potassium channel, subfamily J6 (KCNJ6) forward] and 5'-TAGGTCTCATGGAAGCTGTTGTAG-3' (KCNJ6 reverse); 5'-GCTGTACGCCTTCACCATCT-3' [neuronal pentraxin II (NPTX2) forward] and 5'-GTGTCGTCCAGGTGACACAG-3' (NPTX2 reverse); 5'-CCGAGCGTATCACCATCTTT-3' [neuroligin-2 (NLGN2) forward] and 5'-GCAGACACTCCACAGCTTCA-3' (NLGN2 reverse); 5'-ATCTCCGCTTCACCATCAAG-3' [ephrin-B3 (EFNB3) forward] and 5'-TCTCTTTCCATGGGCATTTC-3' (EFNB3 reverse); 5'-ATCTCATGCAGCAGGGAGTAAA-3' (KCNK17 forward) and 5'-AAGTAGAAGCCCTCTGTGTAGCTC-3' (KCNK17 reverse); and 5'-CTTTGGAGTTGGTTTTGC-3' [solute carrier family 18, member 2 (SLC18A2) forward] and 5'-GCAGTTGTGATCCATGAG-3' (SLC18A2 reverse) (25).

Human IL-1 ß primers were obtained from Ambion, Inc. (catalogue no. 5323). Each sample was run three times, and each PCR experiment included two nontemplate control wells. PCR products were confirmed as single bands of the expected molecular weight using agarose gel electrophoresis. The relative amount of mRNA was calculated by the comparative cycle threshold (CT) method described by Livak and Schmittgen (26) and were normalized by ß-actin expression. The cDNA from islet preparation Is9 was used as a reference for all genes tested to compare the relative amount of target in different samples and adjust for the variation in amplification efficiency. The N-fold differential expression of a specific gene in islet tissue compared with islets treated with IFN{alpha}2ß or with other tissues (e.g. exocrine pancreas, normal kidney, or normal liver tissue) was expressed as 2–{Delta}{Delta}CT. Where {Delta}{Delta}CT = (CT experimental sample – CT ß-actin experimental sample) – (CT reference sample – CT ß-actin reference sample). CT was defined as the fractional cycle number at which the amount of amplified target reached a fixed threshold. {Delta}CT was the difference in the CT values derived from the specific gene being assayed and the ß-actin CT value, whereas {Delta}{Delta}CT represented the difference between a specific tissue sample (e.g. islets, liver, and brain) and reference tissue (islet tissue sample Is9).

Islet and exocrine pancreas membranes.
Islets and exocrine pancreas tissue were purified as described above. Islet tissue (a total of 250,000 islet equivalents, pooled from five donors, pelleted, and snap-frozen) and exocrine pancreas tissue pellets were thawed directly in cold buffer [0.3 M sucrose, 25 mM HEPES (pH 7.5), and 5 mM MgCl2, containing a protease inhibitor mixture (100 µM phenylmethylsulfonylfluoride, 100 µM benzamidine, 20 µg/ml leupeptin, and 10 µg/ml soybean trypsin inhibitor; final concentrations)]. Tissues were homogenized at 4 C by 15 strokes with a loose pestle and 15 strokes with a tight pestle in a Dounce glass-glass tissue homogenizer (Kontes Co., Vineland, NJ). The homogenate was then centrifuged for 5 min at 735 x g at 4 C to pellet the nuclei. The supernatant was collected and then spun at 100,000 x g for 40 min at 4 C to prepare a total membrane fraction. This material was stored at –70 C. On the day of the assay, the membrane fraction was thawed and resuspended in assay buffer (0.3 M sucrose, 25 mM HEPES, 5 mM MgCl2, and 4 mM KCl with the protease inhibitor mixture, pH 7.5). The protein concentrations for the membrane preparations were assessed by the bicinchoninic acid method using Pierce protein assay reagents (Rockford, IL).

Binding of [3H]DTBZ.
Binding of [3H]DTBZ was performed as described by Scherman et al. (27) with minor modifications. Briefly, aliquots of islets (equivalent to about 2500 islets) or exocrine pancreas membrane preparations (containing equal amounts of protein as the islet samples) were added to assay buffer with protease inhibitors in the presence of increasing concentrations of [3H]DTBZ in a final assay volume of 1.5 ml for 30 min at 25 C in triplicate determinations. The reaction was terminated by the addition of 1 ml cold assay buffer, and the amount of membrane-bound radioactivity was determined by rapid filtration through Whatman GF/F filters (Clifton, NJ) on a vacuum manifold. Filters were washed three times with 2 ml ice-cold assay buffer. Radioactivity trapped in filters was counted using a liquid scintillation counter. Nonspecific binding was determined in binding assays of [3H]DTBZ containing a 1000-fold molar excess of cold DTBZ and membrane samples. Excel (Microsoft, Redmond, WA) was used to prepare the saturation isotherm, and Scatchard analysis was performed using the Equilibrate freeware tool (www.homestead.com/equilibrate).


   Results and Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results and Discussion
References
 
Hybridization signals for ß-, {alpha}-, {gamma}-, and {delta}-cell restricted transcripts for insulin, glucagon, somatostatin, pancreatic polypeptide, were detected in all islet samples analyzed (Table 2Go). To ascertain the purity and heterogeneity of the tissue preparations at the molecular level, we determined the relationships between the islet and exocrine tissues samples based on their patterns of gene expression using an unsupervised hierarchical clustering (data not shown). Clustering analysis revealed that all islet samples contained some exocrine tissue, as demonstrated by the presence of transcripts known to be exocrine pancreas specific (e.g. elastase IIB) but consistent with the purity reported by dithizone staining (Table 1Go). The finding of exocrine tissue transcripts in the islet samples was also consistent with the Edmonton purification protocol, in that the limited digestion time used to release islet cell masses from the pancreas often retains a mantle of exocrine cells. We next evaluated the level of islet depletion in the samples of exocrine pancreas (ExoA and ExoB). Depending on the specific gene product analyzed, we found that exocrine fractions showed 25- to more than 100-fold lower levels of islet-associated transcripts (e.g. glucagons and somatostatin) compared with the islet preparations. Compared with whole pancreas, the levels of islet-specific transcripts (e.g. pancreatic polypeptide) present in the exocrine fractions were approximately 50- to 100-fold lower, illustrating that exocrine tissue preparations were islet depleted, but not islet free.

Because the goal of this study was to identify tissue-specific transcripts, we devised a data analysis scheme analogous to suppressive subtractive hybridization (28) (Fig. 1Go). We first eliminated all probesets not expressed in any of the islet samples studied. We then identified a set of genes expressed by human islets, but not by pooled liver and pooled kidney tissue. The exclusion of genes expressed by the liver was necessary because we wanted to eliminate candidate markers that might be expressed around sites of islet transplantation. We then examined the gene expression data from the exocrine tissue samples and identified the set of transcripts present in human islet tissue but not detected in exocrine pancreas, kidney, and liver samples. Approximately 60% of this set corresponded to genes of unknown function and subcellular location. Using public database information, we selected the remaining gene products with known transmembrane or membrane associations.

From examination of the signal intensities of known ß-cell- and exocrine pancreas-specific transcripts, it was clear that the islet tissue preparations contained some acinar tissue and that the exocrine pancreas preparations were not completely ß-cell and islet depleted. As a consequence of the devised data analysis scheme, a number of possibly islet-restricted transcripts encoding transmembrane- or membrane-associated proteins were excluded from further analysis. However, fewer than less than 20 transmembrane or membrane-associated gene products showed average relative abundance in islet samples of four or more times than that measured in the exocrine tissue samples. Transcripts in this latter category included secretogranin II, neural cell adhesion molecule 1, and NPTX2.

We next ranked the dataset composed of known integral membrane or membrane-associated proteins expressed in islet samples, but not detected in liver, kidney, or exocrine pancreas samples, in the order of mean transcript abundance (i.e. average signal intensity) and performed a final filtering step on the probesets that lay above 50th percentile of signal intensity values. We turned to public sequence databases, both S.O.U.R.C.E and Cancer Genome Anatomy Project (SAGE anatomic viewer), and eliminated transcripts present in more than four other normal tissues but retained genes whose expression was shared by tissues of the central nervous system, peripheral nervous system, or other normal neuroendocrine cells. We retained genes whose expression was restricted to islets but was shared by tissues of neural crest derivation, because many of these cells express certain well characterized imageable receptors, and many of the shared gene products of islets and central nervous system are relevant to T1D pathogenesis (e.g. glutamic acid decarboxylase 67) (29). For example, dysfunction of the autonomic nerves is detectable in a subpopulation of T1D patients (30), and loss of sympathetic innervation has been reported to be an early event in the pathogenesis of type I diabetes in rodent models of T1D (29, 31). Thus, we speculated that within the set of molecules selected by this specific analysis scheme might be other shared targets of autoimmune attack beyond those currently recognized as being common to ß-cells and the peripheral nervous system [e.g. protein tyrosine phosphatase receptor type N (PTPRN)/islet cell antigen-512] (32).

The results of the selection are given in Table 3Go. Within this set, we found transcripts for synaptotagmin IV (33), ABCC8 (sulfonylurea receptor-1), PTPRN (IA-2; also called ICA 512), glutamate receptor, ionotropic (AMPA2) (34), somatostatin receptor-2, PTPRN2 (IA-2ß), activin receptor 1B (35), synaptophysin (36), SLC18A2 [also called vesicular monoamine transporter type 2 (VMAT2)] (31, 37) and neuroendocrine secretory protein 55 (NESP55) (38), all encoding known ß-cell transmembrane- or membrane-associated proteins, demonstrating the validity of the approach. The majority of these transcripts were specific for various inorganic and organic ion channels, including Na+, K+, and Ca+2 channels, which are known to exist on the surface of ß-cells (reviewed in Ref.39), but were defined by electrophysiological methods rather than the nucleic acid-based methods of this study. We also report in Table 3Go a series of genes whose expression had been previously unrecognized in islets. Neuroligins are postsynaptic transmembrane proteins whose extracellular domains associate with presynaptic proteins of the neurexin family (40). In islet tissue, we detected both neuroligin-2 and neurexin-1, probably representing sympathetic nerve terminals in islets. Similarly, contactin-1 and NPTX2, detected in the islet tissue studied here, have been reported to have a functional role in the synapse (41). Antisera recognizing the proteins with novel islet associations identified in this study were limited; however, we were able to confirm the expression of neuronal pentraxin 2 protein by Western blot (~65 kDa) in lysates from islet tissue. The 65-kDa signal was not present in lysates from an exocrine pancreas preparation (data not shown).


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  		TABLE 3. Islet tissue-restricted transmembrane- and membrane-associated molecules

 
Several other neurofunctional, tissue-restricted transcripts were found to be expressed in islets. Synaptogyrins are synaptic vesicle proteins involved in the Ca+2-dependant exocytosis (42). In islets, synatoptogyrin 4 may be involved in insulin release. Islet expression of EFNB3, a ligand for the Eph family of receptor tyrosine kinase, may represent an endothelial marker involved in islet structure (43) or endocrine cell neurotrophic factor (44). Calcyon is a dopamine receptor accessory protein facilitating Ca+2 ion signaling (45) and may also participate in insulin release. The cadherin family members characterized in the islets studied here (CDH10, CDH22, and PCDHA10) have been previously described as mediators of Sertoli and neuronal cell-cell interactions (46, 47). Islet expression of the ROBO2 gene may be involved in maintaining innervation or structure of the islet tissue (47). A previous proteomics-based study of rodent islets identified several proteins associated with neuronal guidance (18); however, none of the gene products identified here has been identified by proteomics, perhaps due to the difficulties of identifying transmembrane- and membrane-associated proteins by protein-based approaches (48).

The second aim of these studies was to identify possible gene products uniquely expressed by islets or ß-cells exposed to IFN{alpha} as a possible means to gauge active autoimmunity in islet tissue. Although no unique gene products were identified, we were able to identify a number of islet-restricted transcripts whose expression levels were modulated after treatment with IFN{alpha}. To determine the effect of IFN treatment on gene expression of cultured human islets, we first examined the signal intensities of a series of genes previously identified in other tissues to be regulated by IFN{alpha} (49). We observed that, similar to previous microarray studies of IFN{alpha}-treated human fibrosarcoma cells (50) or myeloid dendritic cells (24, 50), IFN{alpha}-treated islets (100 and/or 1000 U) accumulated more transcripts for products such as IL-1B and IRF7 relative to untreated cells. We performed independent quantitative real-time PCR-based experiments using total RNA isolated from IFN{alpha}2ß-cultured islets obtained from two additional donors. We found that IRF7 and IL-1B transcripts were increased in all islet tissue samples treated with IFN{alpha}2ß, confirming the microarray results and that the islet tissue had undergone interferon stimulation (Table 4Go).


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  		TABLE 4. Abundance and tissue distribution of selected islet transcripts by quantitative real-time PCR

 
We next identified a subset of islet tissue-restricted gene products whose specific RNA level changes upon IFN{alpha} stimulation. This subset included elements with increased accumulation of transcripts, such as NLGN2 and EFNB3. After treatment of the islets with IFNa2ß, other members of this group showed decreased amounts of transcripts relative to their controls. Genes in this category include KCNK17, ABCC8, and AMPA2 (data not shown). Quantitative real-time PCR measurements of the expression levels of EFNB3, NLGN2, KCNJ6, KCNK17, VMAT2, and NPTX2 confirmed not only the amount of transcript regulation by IFN{alpha} in islet tissue, but also their restricted tissue distributions (Table 4Go). Although none of the above-mentioned gene products has a clear association with inflammatory processes, it is not excluded that their expression levels measured in these experiments reflect the mild pancreatitis that has been observed in brain-dead organ donors (51).

Although not within the set of genes with islet-restricted expression, we also observed that transcripts for more than 10 major histocompatibility complex class II genes, including HLA-DRA, HLA-DQA1, HLA-DQB1, and HLA-DMA, showed an approximately 2- to 5-fold down-regulation after IFN{alpha}2ß treatment relative to their untreated donor-matched controls and other islet tissue studied. Using real-time RT-PCR, we confirmed these measurements for the HLA-DRA gene product (Table 4Go) in the original islet samples and in independent experiments using islet tissue from different donors (Is9 and Is10; Table 4Go). Coordinate down-regulation of gene products of the major histocompatibility complex class II locus by type 1 IFNs has been previously demonstrated in fibroblasts and antigen-presenting cells (52, 53, 54, 55), but represents a novel finding in human islet tissue and is of possible significance in the pathogensis of T1D (56, 57).

In this study we identified members of three receptor families that are potentially imageable by positron emission tomography (PET): glutamate receptors (58), serotonin receptors (59), and vesicular transporters (60). Recently, it has been demonstrated that the loss of expression of VMAT2, identified in our studies, is an early event in animal models of type 1 diabetes (31). Specific radioligands for this receptor are already in clinical use for imaging the brain by PET (60). We examined the binding of DTBZ, a VMAT2-specific ligand (61, 62), to preparations of islet and exocrine pancreas membranes. Both specific and nonspecific binding were observed (Fig. 2Go). DTBZ showed specific and saturable binding to islet membranes, but not to membranes prepared from exocrine tissue. In our assay conformation, specific [3H]DTBZ-binding sites were saturated by 10 µM DTBZ. When the specific binding, obtained with increasing [3H]DTBZ concentrations, was analyzed by the method of Scatchard, linear plots were obtained (Fig. 2Go), suggesting the presence of one class of binding sites. From two independent measurements, the experimentally determined Kd (0.8 nM; 0.6–1.4 nM at the 95% confidence interval) for DTBZ binding in islet tissue was similar to previous studies using tissue from the central nervous system (63, 64). PET measurements of uptake of [11C]DTBZ in the endocrine pancreas might provide a useful index of ß-cell mass.



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  		FIG. 2. Binding of [3H]DTBZ to purified islet and exocrine pancreas membranes. A, Saturation isotherm. Islet membranes were incubated with [3H]DTBZ (0.001–20 nM) in the absence ({triangleup}) or presence ({blacktriangleup}) of 10 µM DTBZ. Bound [3H]DTBZ was determined by filtration of membrane aliquots. Free [3H]DTBZ was estimated by counting a 100-µl aliquot of the assay mixture. Each point is the mean of triplicate determinations, and the experiment shown is representative of two separate experiments. Nonspecific binding to membranes prepared from exocrine pancreas tissue ({blacksquare}) was proportional to the free [3H]DTBZ concentration. The solid line is the theoretical curve for specific binding. Inset B, Scatchard plot of the specific binding. Data obtained by filtration were used; from these, a Kd of 0.8 nM was calculated.

 


   Acknowledgments
 
We acknowledge the help of Dr. Miljkovic of the Columbia University Microarray Project and Prof. Jesse Wolf of Cooper Union.


   Footnotes
 
This work was supported by grants from the United States Public Health Service, National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases [5-P30-DK-063608-02 and 1-U42-RR-016629-02 (to M.A.H.), and 5-RO1-DK-63567-01 (to P.E.H.)].

Abbreviations: AMPA2, Glutamate receptor, ionotropic; DTBZ, dihydrotetrabenazine; EFNB3, ephrin-B3; IFN{alpha}2ß, interferon-{alpha}2ß; IRF7, interferon regulatory factor-7; KCNJ, potassium channel, subfamily J; NLGN2, neuroligin-2; NPTX2, neuronal pentraxin II; PET, positron emission tomography; PTPRN, protein tyrosine phosphatase receptor type N; SLC18A2, soluble carrier family, member 2; T1D, type 1 diabetes; VMAT2, vesicular monoamine transporter type 2.

Received June 1, 2004.

Accepted for publication June 24, 2004.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results and Discussion
 References
 

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