«Gene Expression Profiling of Encephalitogenic CD4+ T cells: Identification of Genes Controlling Migration of Effector T cells into the CNS ...»
Max Planck Institut für Neurobiologie
Direktor: Prof. Dr. Hartmut Wekerle
Gene Expression Profiling of
Encephalitogenic CD4+ T cells:
Identification of Genes Controlling
Migration of Effector T cells into the CNS
Dissertation der Fakultät für Biologie
der Ludwig-Maximilian-Universität München
Vijay Kumar Ulaganathan
Hiermit erkläre ich ehrenwörtlich, dass ich die vorliegende Dissertation selbstständig und ohne unerlaubte Hilfe angefertigt habe. Die Arbeit wird hiermit erstmalig einer Prüfungskommission vorgelegt.
München, den Vijay Kumar Ulaganathan Eingereicht am: 12 April 2010
Mitglieder der Promotionskommission:
Erster Gutacher: Professor Dr. Tobias Bonhoeffer Zweiter Gutacher: Professor Dr. Elisabeth Weiss Sonderberichterstatter: Professor Dr. Alexander Flügel Tag des Promotionskolloquiums: 25 October 2010.
Table of contents Table of Contents Table of Contents
List of Tables
List of Figures
1.1 Multiple sclerosis
1.2 Clinical course
1.2.1 Relapsing-remitting MS
1.2.2 Secondary progressive MS
1.2.3 Primary progressive MS
1.2.4 Progressive relapsing MS
1.5 Experimental autoimmune encephalomyelitis
1.6 EAE in Lewis rats
1.6.1 Active EAE in Lewis rats
1.6.2 Adoptive transfer EAE in Lewis rats
1.7 T lymphocyte migration to the CNS in AT-EAE
1.8 Targeting T cell migration: Therapeutic strategies for multiple sclerosis.......... 10 2 Objectives
3.2 Cell lines
3.6 Buffers and Reagents
4.1 Generation of antigen specific T cells
4.2 Retroviral transduction of antigen specific T cells
4.3 Recombinant DNA cloning
4.4 Proliferation assay for T cells
4.5 Cytofluorometry FACS
4.6 Quantitative polymerase chain reaction
4.7 EAE induction
4.8 Memory animal generation
4.9 In vitro matrigel motility assay
4.10 Microarray data analysis
4.11 Dual luciferase assay
5.1 Microarray analysis of encephalitogenic T cells
5.2 Cluster analysis of the microarray expression data
iTable of contents
5.3 Gene Ontology based analysis of microarray expression data
5.4 Pathway based analysis of microarray data
5.5.1 PCR based validation
5.5.2 Antibody based validation
5.6 Bioinformatics prediction of KLF4 as a common transcriptional regulator for inflammatory chemokine receptors
5.7 Overexpression of KLF4 induces cell cycle arrest and upregulates CCR2 and CCR5
5.8 Transcriptional activity of KLF4 on CCR2 and CCR5 promoters
5.9 Identification of differentially regulated membrane molecules as potential candidate genes
5.10 EMP1 as a novel candidate gene
5.11 Bioinformatics based structural features of EMP1
5.12 Expression of EMP1 in T cells
5.13 Cloning of EMP1 full length cDNA from activated TMBP-GFP cells
5.14 Analysis of gene expression changes in EMP1 overexpressing T cells............. 76
5.15 EMP1 overexpressing T cells proliferate normally
5.16 Overexpression of EMP1 induces enhanced T cell motility in matrigel............ 79
5.17 EMP1 overexpressing encephalitogenic T cells induce accelerated onset of EAE
5.18 EMP1 overexpressing T cells infiltrate earlier into the CNS parenchyma......... 88
List of Tables Table 3. 1 List of mammalian cell lines used.
Table 3. 2 List of plasmids used.
Table 3. 3 List of primary antibodies used.
Table 3. 4 List of secondary antibodies used.
Table 4. 1 List of primers used for recombinant DNA cloning
Table 4. 2 List of Taqman primers and probes used for qPCR.
Table 5. 1 A summary of differentially regulated transcripts from microarray dataset.
Table 5. 2 GO: Molecular Class based annotations of differentially regulated transcripts in Tactivated transcriptome
Table 5. 3 GO: Molecular Class based annotations of differentially regulated transcripts in Tmigratory transcriptome
Table 5. 4 GO: Biological Process based annotation of differentially regulated transcripts in Tactivated transcriptome
Table 5. 5 GO: Biological Process based annotation of differentially regulated transcripts in Tmigratory transcriptome
Table 5. 6 qPCR and microarray data indicating up regulation of quiescence factors.
Table 5. 7 List of genes selected for microarray data validation by quantitative PCR.
Table 5. 8 Inflammatory chemokine receptors’ transcripts are upregulated in Tmigratory transcriptome.
Table 5. 9 KLF4 binding motifs are present in inflammatory chemokine receptors.
. 61 Table 5. 10 Overexpression of KLF4 upregulates CCR2 and CCR5 in ovalbuminspecific T cells.
Table 5. 11 List of cell membrane receptors which are established drug targets for multiple sclerosis
Table 5. 12 List of cell membrane molecules differentially regulated in Tspleen cells compared to Tblast cells as indicated by microarray data.
Table 5. 13 Prediction for transmembrane helix regions in EMP1 amino acid sequence.
Table 5. 14 Encephalitogenic T cells migration to different organs post intra peritoneal transfer
iii iv List of Figures List of Figures Figure 1. 1 Schematic representation of different clinical forms of MS.
Figure 1. 2 Clinical course of AT-EAE in Lewis rats.
Figure 1. 3 Illustration depicting the mode of action of natalizumab.
Figure 4. 1 Diagrammatic representation of time lapse video microscopy setup for matrigel motility assay.
Figure 5. 1 Schematic illustration of green fluorescent TMBP-GFP cell sorting using FACS from different milieus and subsequent microarray analysis.
........ 35 Figure 5. 2 Microarray dataset viewed as expression plot.
Figure 5. 3 Heat Map representation of cluster analysis of annotated genes.
............ 37 Figure 5. 4 Depiction of cluster A-F.
Figure 5. 5 Pie chart analysis of clusters A to F.
Figure 5. 6 Cell cycle genes and chemokine receptors are clustered.
Figure 5. 7 Differential regulation of cell migration and cell cycle processes.
......... 41 Figure 5. 8 Cholesterol biosynthetic pathway is upregulated in Tactivated transcriptome.
Figure 5. 9 Cholesterol biosynthetic pathway is downregulated in Tmigratory transcriptome.
Figure 5. 10 Cell cycle pathway is upregulated in Tactivated transcriptome.
................. 49 Figure 5. 11 Cell cycle pathway is downregulated in Tmigratory transcriptome............. 50 Figure 5. 12 Cell migration pathway is upregulated in Tmigratory transcriptome.......... 53 Figure 5. 13 Intracellular propidium iodide staining of DNA for cell cycle analysis by flow cytometry.
Figure 5. 14 Validation of microarray data by qPCR.
Figure 5. 15 Differential regulation of KLF4 in vivo.
Figure 5. 16 Inflammatory chemokine receptors are upregulated in Tspleen.
............... 60 Figure 5. 17 Inflammatory chemokine receptors are clustered in the genome............ 60 Figure 5. 18 Standardization of KLF4 qPCR primers.
Figure 5. 19 Overexpression of KLF4 inhibits cell cycle progression in MBP-specific T cells.
Figure 5. 20 Overexpression of KLF4 upregulates CCR2, CCR5 but not CXCR3 in MBP specific T cells.
Figure 5. 21 Overexpression of KLF4 upregulates CCR2 and CCR5 in RBL1 cell lines.
Figure 5. 22 Dual luciferase assay for CCR2, CCR5 and CXCR3 promoter activity.
65 Figure 5. 23 ClustalW multiple sequence alignment of mammalian EMP1 protein sequences.
Figure 5. 24 Phylogram tree for mammalian EMP1 are related.
Figure 5. 25 ClustalW multiple sequence alignment of rat EMP1 family amino acid sequences.
Figure 5. 26 Computer based prediction of EMP1 topology.
Figure 5. 27 Standardization of EMP1, EMP2 and EMP3 qPCR primers.
................. 73 Figure 5. 28 Differential regulation of EMP1 family genes in T cells.
Figure 5. 29 EMP1 protein detection in activated T lymphocytes.
Figure 5. 30 Cloning of rat EMP1 from activated T cells.
vList of Figures
Figure 5. 31 Gene overexpression of EMP1 in activated T cells.
Figure 5. 32 Gene expression of cytokines.
Figure 5. 33 Gene expression of transcription factors.
Figure 5. 34 Proliferation assay of in vitro cultured T cells.
Figure 5. 35 Matrigel T lymphocyte motility assay in vitro.
Figure 5. 36 Adoptive transfer EAE induced by intraperitoneal injection and migratory pattern of encephalitogenic T cells in vivo 5 days post intra peritoneal injection.
Figure 5. 37 Adoptive transfer EAE induced by sub cutaneous injection and migratory pattern of encephalitogenic T cells in vivo 5 days post sub cutaneous injection.
Figure 5. 38 Adoptive transfer EAE induced by intra venous injection and migratory pattern of encephalitogenic T cells 4 days in vivo post intra-venous injection.
Figure 5. 39 Migration of EMP1 overexpressing T cells to the draining lymph nodes.
Figure 5. 40 Active EAE induced in memory animals by MBP/CFA immunization.
84 Figure 5. 41 Encephalitogenic T cell infiltration to CNS post AT-EAE induction..... 87 Figure 5. 42 Encephalitogenic T cell migration coincides with expression of T cell specific genes in CNS post AT-EAE.
Figure 6. 1 Model illustrating the molecular changes taking place in encephalitogenic T cells from the time of injection until they reach their target organ.
..... 93 vi Summary Summary T cells directed against brain antigens are generally held to play a crucial role in the initiation of multiple sclerosis (MS). This was deduced from experimental autoimmune encephalomyelitis (EAE). In this model for MS, T cells reactive for myelin antigens induced a severe paralytic disease upon transfer to healthy syngeneic recipients.
Intriguingly, the disease does not start immediately upon transfer of the pathogenic effector T cells. Instead, as earlier studies have shown, the effector T cells attack their target organ only after having migrated in the periphery through secondary lymphoid organs. The aim of the project was to characterize the functional properties of these migrating encephalitogenic T cells during the course of EAE and to identify biological pathways which determine their migratory behaviour and pathogenic potential. To this end, average linkage hierarchical clustering, pathway and gene ontology (GO) analyses of transcriptomes from cultured and ex vivo-isolated myelin basic protein-reactive T cells (TMBP cells) were performed.
At the time of transfer, encephalitogenic T cells in vitro are maximally activated, i.e. they exhibit a prominent upregulation of cell cycle genes such as cyclin A2 (CCNA2) and cyclin B2 (CCNB2) among others. In contrast, T cells isolated from spleen 3 days post transfer, downregulated activation markers such as interleukin 2 receptor (IL2R) and interferon γ (IFNγ), and at the same time upregulated migration specific genes such as CC-chemokine receptor 1 (CCR1), CC-chemokine receptor 2 (CCR2) and CC-chemokine receptor 5 (CCR5). Hierarchical cluster analysis revealed that several transcription regulators known for inhibiting cell cycle progression such as krüppel-like factor 4 (KLF4), B-cell translocation gene 2 (BTG2) and transducer of ERBB2, 1 (TOB1) were clustered together with cell cycle and migration genes. Overexpression of KLF4 in T cells not only inhibited G1/S phase progression of the cell cycle but additionally induced upregulation of CCR2 and CCR5. A novel tetraspan membrane protein called epithelial membrane protein (EMP1), was found to be up regulated in ex vivo-isolated effector T cells. Overexpression of EMP1 in encephalitogenic T cells influenced the migratory behaviour of effector T cells both in vitro and in vivo. EMP1 enhanced T cell motility
within the extracellular matrix milieu in vitro and promoted T cell migration from the connective tissue to lymph nodes in vivo resulting in an accelerated onset of EAE.
In conclusion, gene expression profiling of encephalitogenic T cells revealed interesting genome wide transcriptomic changes and established a correlation between cell cycle progression and cell migration. As a result, in silico analysis put forth several interesting candidate genes that hold promise as potential targets for therapeutic intervention.