large-scale sequencing, gene expression profiling combined with classic linkage analysis and congenic and physical ..... V. K., and Wilder, R. L. 1999. Mapping ...
Neurochemical Research, Vol. 27, No. 10, October 2002 (© 2002), pp. 1157–1163
Gene-Expression Profiling of Experimental Autoimmune Encephalomyelitis Eilhard Mix,1 Jens Pahnke,1 and Saleh M. Ibrahim2,3 (Accepted July 31, 2002)
Experimental autoimmune encephalomyelitis (EAE) is a mouse model that serves as an experimental tool for studying the etiology, pathogenesis, as well as new therapeutic approaches of multiple sclerosis (MS). EAE is a polygenic chronic inflammatory demyelinating disease of the nervous system that involves the interaction between genetic and environmental factors. Previous studies have identified multiple quantitative trait loci (QTL) controlling different aspects of disease pathogenesis. However, progress in identifying new susceptibility genes outside the MHC locus has been slow. With the advent of new global methods for genetic analysis such as large-scale sequencing, gene expression profiling combined with classic linkage analysis and congenic and physical mapping progress is considerably accelerating. Here we review our preliminary work on the use of gene expression mapping to identify new putative genetic pathways contributing to the pathogenesis of EAE.
KEY WORDS: EAE; multiple sclerosis; oligonucleotide-microarrays; QTL.
INTRODUCTION
different myelin antigens, e.g., myelin basic protein (MBP), proteolipid protein (PLP) or with spinal cord homogenate. Myelin oligodendrocyte glycoprotein (MOG) is another highly immunogenic myelin protein, which can elicit humoral and cellular immune responses leading to chronic EAE in susceptible animals (5). MOG-induced EAE is thought to be more MS-like than other rodent EAE models (1,6,7). Furthermore, MOG represents also a potent candidate autoantigen in MS (8,9), since it possesses several properties typical for autoantigens like (a) molecular mimicry, i.e. sharing of epitopes with common infectious agents (10), (b) determinant spreading (11) and (c) complement binding (12). For these reasons MOG-induced EAE is an excellent model for investigating pathogenetic processes and therapeutic approaches applicable to
EAE is a chronic inflammatory disease of the nervous system that serves as model to understand the pathogenesis of MS (1–3). The disease is characterized by the generation of activated antigen-specific T and B cells, their migration to the nervous system, local reactivation by resident antigen-presenting cells, activation of local glial and microglial cells, secretion of chemokines, cytokines, and other inflammatory mediators, e.g., complement, and NO and eventually demyelination of neuronal axons (4). EAE can be induced in susceptible mouse strains carrying the H2r, s, or b genes by immunization with one of a number of 1
Department of Neurology, University of Rostock, Rostock, Germany, Schillingallee 70, 18055 Rostock, Germany. 2 Department of Immunology, University of Rostock, Rostock, Germany, Schillingallee 70, 18055 Rostock, Germany. 3 Address reprint request to: Department of Immunology, University of Rostock, Schillingallee 70, 18055 Rostock, Germany. Tel: ⫹49381-494-5872; Fax: ⫹49-381-494-5882; E-mail: saleh.ibrahim@ med.uni-rostock.de
Abbreviations: EAE, experimental autoimmune encephalomyelitis, MS, multiple sclerosis, MHC, major histocompatibility complex, QTL, quantitative trait loci, PCR, polymerase chain reaction, MOG, myelin oligodendrocyte glycoprotein, IFN, interferon, TNF, tumor necrosis factor.
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MS and it has, therefore, be chosen for our first study of gene expression profiling in EAE. The genetic dissection of the EAE susceptibility trait performed in a variety of mouse strains has led to the identification of several EAE-linked QTLs (13). As in MS susceptibility to disease has been linked to the MHC locus (H2) (14). However, expression of the linked MHC haplotype is not necessarily sufficient to determine EAE susceptibility indicating important non MHC-genetic contributions. Despite considerable efforts identifying putative susceptibility genes in these QTL has so far not been feasible. With the advent of gene expression profiling using cDNA and /or oligonucleotide-microarrays an additional powerful tool is now available that could speed this process (15). Our strategy, and that of others, has been to combine gene expression profiling, gene mapping and linkage analysis to narrow down the number of candidate genes for further analysis, a process we call differential gene expression mapping (Fig. 1). A strategy that we think will facilitate the search for new genetic pathways of EAE as well as other autoimmune diseases (16,17) as compared to the conventional congenic and physical mapping experiments (18,19). It may also enable us to create new hypothesis concerning pathogenetic pathways and candidate genes for autoimmune diseases (20–22). Here we present first results of the gene expression mapping approach in MOG-induced EAE as an example of the potential of this new molecular methodology. EXPERIMENTAL PROCEDURE Animals, Antigen, and Induction of Disease. C57B1/6 mice were obtained from Harlan-Winkelmann (Borchen, Germany) and kept under standard conditions at the animal facility of Rostock university. Seven-week-old mice were immunized subcutaneously with 150 g of rat MOG peptide 35–55 in complete Freund’s adjuvant (CFA). Mice received an intraperitoneal injections of 500 ng pertussis toxin on day 1 postimmunization (p.i.). Mice were killed at the first signs of disease (onset, day 16 p.i.) or after consistently exhibiting severe paraparesis for more than 2 days (peak, day 22 p.i.). Control mice were immunized with CFA only. All experiments were approved by the competent authorities of the state of MecklenburgVorpommern, Germany. Sample Preparation and Microarray Hybridization. Spinal cords from three mice/group were dissected and immediately transferred into Fast prep RNA tubes (Bio101, CA) with 500 L of lysis buffer (Qiagen, Germany) for RNA preparation or snap frozen in liquid nitrogen for immunohistochemical analysis. Total RNA was extracted from homogenized spinal cords using RNA extraction kit following the manufacturer’s instructions (Qiagen). RNA probes were labelled according to the supplier’s instructions (Affymetrix, Santa Clara, CA). Analysis of gene expression was carried out with the Mu11K array (Affymetrix). Hybridization and washing of gene chips was done as described (16,23). Microarrays were analysed by laser scanning (Hewlett-Packard Gene ScannerTM) and the expres-
Fig. 1. Schematic representation of main experimental steps for identification of disease susceptibility genes by conventional and gene expression mapping strategies. sion levels were calculated with a commercially available software provided by Affymetrix. Data are given as fold change of gene expression in the inflamed spinal cords (onset and peak) compared with the expression in the normal spinal cords. Only genes with more than 4-fold change were considered significant. Differential expression analysis was confirmed by quantitative reverse transcription– polymerase chain reaction (RT-PCR) using the LightCycler (Roche, Mannheim, Germany) (24). Histological Analysis and Imunocytochemistry. Then 10-m cryosections were mounted on poly- L -lysine–coated slides and processed as described (25). Cellular infiltrates were characterized in serial sections of spinal cord by incubation with the monoclonal rat antibody RM 4-5 (dilution 1:1,000; PharMingen, San Diego, CA) staining mouse CD4 T-cells, the monoclonal rat antibody 53-6.7 (dilution 1:1,000; PharMingen) labeling mouse CD8 T-cells, and F4/80 (dilution 1:300; Serotec, Oxford, UK) for detection of mouse macrophages. Cells were then visualized using a biotinylated rabbit anti-rat IgG (H ⫹ L) (dilution 1:100; Vector Laboratories, Burlingame, CA) and the ABC-detection system (Dako, Hamburg, Germany) with 3,3⬘-diaminobenzidine as peroxidase substrate. Finally, sections were counterstained with hematoxylin, dehydrated, and mounted in Eukitt (Kindler, Freiburg, Germany).
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Isolation of Mononuclear Cells (MNCs) from Lymph Nodes and Cell Culture. Popliteal, preperitoneal, inguinal, mesenterial, axilary, and cervical lymph nodes were removed under aseptic conditions. Single cell suspensions of MNC of pooled lymph nodes form individual mice were prepared. The cells were washed three times in culture medium before being suspended to 2 ⫻ 106 MNC/mL in round-bottomed 96-well polystyrene microtiter plates (Nunc, Copenhagen, Denmark) in a total volume of 200 L. The culture medium consisted of RPMI 1640 with Glutamax-II (Gibco BRL, Life Technologies, Karlsruhe, Germany) supplemented with 50 IU/mL penicillin, 60 /mL streptomycin (Gibco) and 5% inactivated fetal bovine serum (Gibco) without mercaptoethanol. For lymphocyte stimulation, 10-mL aliquots of MOG 35–55 peptide were added to cultures at a final concentration of 10 to 50 g/mL or 10 mL of concanavalin A (ConA) (Difco, Detroit, MI) at a final concentration of 4 g/mL. These concentrations had optimal stimulator effects as assessed in preliminary experiments. Cells were incubated at 37°C in humidified air with 5% CO2 for 72 hours. For proliferation assay, cultures were done in triplicate, and for ELISA measurements of interferon-␥ (IFN-␥) in duplicates. Proliferation Assay. After 60 hours of incubation, cells were pulsed with 10 L 3H-methyl-thymidine (1 Ci/well; Amersham Pharmacia Biotech, Freiburg, Germany) and cultured for an additional 12 hours. Cells were harvested onto glass-fiber filters (Titertek, Skatron, Lierbyen, Norway). 3H-Methyl-thymidine incorporation was measured in a liquid scintillation counter. The results were expressed as counts per minute (cpm). ELISA Measurement of IFN-g. After 72 hours of incubation supernatants were collected from the lymph node cell cultures and frozen in two aliquots at ⫺80°C. Concentrations of IFN-␥ in the supernatants were determined with the Cytoscreen Immunoassay Kit (BioSource, Camarillo, CA) according to the instructions by the manufacturer.
RESULTS AND DISCUSSION Profile of gene expression in inflamed spinal cords of EAE mice reflects the immune-mediated nature of disease. Gene expression profiles of the inflamed spinal cords of normal and EAE mice at onset and peak or disease, days 16 and 22 p.i., respectively, were determined using Affymetrix 11K oligonucleotidemicroarrays (covering ⬃6,000 full-length genes and ⬃5,000 ESTs). Onset and peak of disease were determined from clinical evaluation of disease. Immunohistochemistry of spinal cord lesions and T cell response to MOG in lymph nodes confirmed the T cell– dominated infiltration and the T cell–mediated immune reaction to the antigen used for induction of the disease (Fig. 2). The microarray analysis revealed that 213 genes showed more than 4-fold differential expression in EAE when compared to noninflamed tissue. One hundred of them were consistently observed at onset and peak of disease, whereas 45 were only seen at onset and 68 at peak of disease (16). More genes were up-regulated, 166, than were down-regulated,
Fig. 2. Immunohistochemical characterization of spinal cords and assessment of immune response in EAE mice. Immunohistochemical staining of cellular infiltrates in frozen sections of spinal cords at onset (A, C, E) or peak of disease (B, D, F) for CD4 T-cells, A, B, CD8 T-cells, C, D, and macrophages, E, F. Bar in A represents 25 M for all photos. 3H-Thymidine incorporation, G, and concentrations of IFN-␥ in the supernatants, H, of lymphocyte cultures in response to different concentrations of MOG peptide.
47, at either onset or peak of disease. An independent validation of the oligonucleotide microarray data was carried out by using a quantitative RT-PCR method for analysis of a subset of six genes that were either down- or up-regulated (16). Genes encoding immune-related molecules, e.g., complement components, cytokines, and chemokines, constituted the largest group (n ⫽ 72) supporting the current disease models. In addition, there was an increased gene expression of extracellular matrix and cell adhesion molecules and of molecules involved in cell division and death and transcription, and a differential regulation of molecules involved in signal transduction, protein synthesis, and cell metabolism. Interestingly, almost all nervous system-related genes (13 of 14) were down-regulated (16), suggesting a
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Fig. 2. Continued.
lack of regenerative processes in this phase of the disease. Differentially Expressed Genes Mapping to EAE QTLs We furthermore analysed differentially expressed genes in relation to known EAE susceptibility loci other than the MHC locus (Table I). Of the 91 nonMHC genes with known chromosomal positions, we found that 40 (44.0%) map to these loci assuming that linkage is observed within a 10 cM distance from the marker with highest LOD score as suggested by Todd et al. (26) or as defined in the original publications. By applying this criterion EAE linked loci would cover approximately 200 cM, i.e., 13.3% of the mouse genome estimated to be 1503 cM (27). An observed gene distribution that is significantly higher than random distribution (p ⬍ 0.001) (16), suggesting that putative susceptibility genes are among genes differentially expressed in our data set. Expected putative susceptibility genes included 13 genes mapping to the MHC locus EAE1 (data not shown), C3, IgK, and TCR genes. This is not surprising, since those molecules play a central role in disease susceptibility and their role in disease susceptibility has been extensively studied (28–31). Only one
Mix, Pahnke, and Ibrahim cytokine (IFN-), two chemokines (Scya5, Scya9) and one cytokine receptor, TNFR2, map to known EAE QTLs. Other cytokines were not observed in our data set despite their well-documented role in disease pathogenesis (32). TNFR2 been suggested to be a susceptibility gene of MS patients (33). Other up-regulated genes mapping to EAE QTLs include those coding for molecules with down-regulatory (CD52, Fc-R1, or up-regulatory (YM-1, IFR1) function of immune response. IFR1 is a transcription factor involved in IFN regulation and monocyte/ macrophage differentiation. Its promotion of autoimmunity has been suggested through experiments using mutant mice lacking this molecule, which were resistant to antigen-induced autoimmune disease (34). Other genes of interest mapping to EAE QTLs, but having no known role in EAE pathogenesis are acrogranin, a growth factor involved in germ cell differentiation, adipose differentiation related protein (ADFP), Hox2.2 (Hoxb6), UCP2, Lissencephaly-1, and beta ig-h3, a TGF-beta inducible gene. Our data establish for the first time a geneexpression profile for early stages of EAE and demonstrate that gene-expression mapping could be a powerful tool in identifying new putative susceptibility genes in predefined QTLs of polygenic autoimmune diseases. Preliminary analysis of some candidate genes is currently under way both to identify sequence polymorphism in coding regions and regulatory sequences in common susceptible and resistant strains, e.g., B6, SJL and B10.s, and to confirm their role in the pathogenesis of disease. This powerful new technology will help to (a) identify new disease-promoting factors as recently found for osteopontin (35) and 5-lipoxygenase (36), (b) revise outdated simplifying views of signal pathways and therapeutic mechanisms in MS (37), (c) identify new surrogate markers for prediction of the disease course and monitoring of therapeutic efficacy (21), and (d) discover new targets of therapeutic intervention avoiding adverse effects in clinical trials (38,39).
ACKNOWLEDGMENTS The work was supported by grants from the German Federal Ministry of Education and Research (BMBF) program NBL3, 01 ZZ0108, to S.M.I. The authors would like to thank colleagues who contributed to the original published experiments namely Tobias Boettcher, Ralf Gold, Dirk Koczan, Arndt Rolfs, and Hans-Juergen Thiesen. We would also like to thank I. Klamfuß for excellent technical assistance and A. Mueller for help with the manuscript.
M94584 Z16078 M31314 M37761 Z29396 X87096 U09399 M55561 V00755 X66295 M93275 X16874 M91458 X00619 V00802 M59377 L39879 U69135 L34676 D85561 L33768 X69063 U92565 U23184 U59807 U96726 U02298 M86736 M21065 M19681 M92649 U19482 X56461 U95116
Secretory protein (YM-1) CD53 Fc-gamma R1 Calcyclin Annexin V Brevican Glycine receptor beta-subunit
Phosphatidylinositol-linked antigen (pB7 ⫽ CD52) Interferon beta (type 1) C1q C-chain Adipose differentiation related protein (ADFP) C1q B-chain Sterol-carrier protein X
T-cell receptor beta-chain
Kappa-immunoglobulin (constant region) Tumor necrosis factor 2 receptor
Ferritin L-subunit UCP2 X11 protein (beta-amyloid precursor binding Protein A2)
MECL1 Protein tyrosine kinase (JAK3) Erythroid ankyrin Fractalcine Carboxypeptidase E
Cystatin B Phosphatidylinositol transfer protein alpha (Pitpn) Rantes (Scya-5) Acrogranin Interferon regulatory factor 1 PDGF-inducible protein (SCYA-2) Nitric oxide synthase C10-like chemokine (SCYA-9) Hox2.2 (Hoxb6) Lissencephaly-1 protein
12.3 19.6 13.1 10.2 5.9 4.7 4.5 4.5 ⫺6.6 ⫺7.6
10.7 A ⫺5.2 A ⫺1.5
5.0 4.8 ⫺4.9
2.6 4.8
7.0
19.6 16.9 6.3 5.9 4.9 ⫺1.3
16.2 8.4 4.3 4.2 1.0 ⫺7.3 A
Fold change/ onset (day 16)
10.2 16.3 11.5 14.6 4.2 3.7 A 9.9 ⫺3.9 ⫺10.6
15.3 6.8 ⫺3.4 ⫺5.5 ⫺4.1
4.0 6.7 A
11.8 6.5
6.1
16.3 13.6 7.6 5.9 4.4 ⫺4.3
5.3 5.1 4.3 4.2 5.2 A ⫺7.3
Fold change/ peak (day 22)
10 11 11 11 11 11 11 11 11 11
8 8 8 8 8
7 7 7
6 6
6
4 4 4 4 4 4
3 3 3 3 3 3 3
Chromosome
42.0 44.11–13 47.4 60 29 46.5 45.6 47.4 56 44
51 33 9.5 46 32.6
24.5 50 25.5
30 60.5
20.5
73.5 42.6 66.1 38.9 66.1 52
50.5 50.5 45.2 43.6 19.2 48 36
CM
(64) (36.6–71.8) (60–70) (36.6–71.8) (60–70) (36.6–71.8)
(45–53) (45–53) (45–53) (35) EAE 3 (29.3) (45–53) (30– 41) EAE 3
36 11 11 11 11 11 11 11 11 11
8 8 8 8 8
EAE17 (44– 52) EAE 7 (44–52) EAE 7 (44.5–62) EAE 7 (28) (44–52) EAE 7 (44–52) EAE 7 (44–52) EAE 7 (44.5–62) EAE 7 (44–52) EAE 7
(47.3) (25) (18.3) (47.3) (25)
7 (24–53) 7 (24–53) 7 (25–51) EAE 4
6 (30) 6 (46–63)
6 (20–60)
4 4 4 4 4 4
3 3 3 3 3 3 3
EAE linked locus chromosomes (cM)
47 48 48 40 46 48 48 48 40 48
42 33 42 42 33
46 46 40
28–30, 43– 44 45 46
33 42 33 42 33 42
40 40 40 41 42 40 40
Ref.
Gene expression profiling was carried out using the Mu11K oligonucleotide microarrays (Affymetrix). Only genes of 4-fold change of levels of expression using normal spinal cords as a baseline were included. The chromosomal positions were obtained from the Jackson Laboratory (http://www.informatics.jax.org). EAE QTL were defined as intervals of ⫾10 cM of the genetic marker showing highest lod score or as the interval described in references.
Accession No.
Gene
Table I. Differentially Expressed Genes Mapping to Non-MHC EAE Susceptibility Loci
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