Testimonios de Estudiantes referentes a la Fase II:

Cluster analysis is the most popular and commonly used method for gene expression analysis. One of the primary goals of clustering is to group together objects such as genes or transcriptomes with similar expression pattern. When genes with similar expression profiles are grouped together they are believed to be co-regulated and functionally related.

Tspleen vs Tblast TCNS vs Tblast Tblast vs Tresting Number of upregulated

( ≥ 2 fold) transcripts 587 514 919 Number of downregulated

( ≤ 0.5 fold) transcripts 1027 1149 1791

Total number of differentially

regulated transcripts 1614 1663 2710 Total number of transcripts 30200 30200 30200

Table 5. 1 A summary of differentially regulated transcripts from microarray dataset.

A summary of the number of differentially regulated transcripts is given in Table 5. 1. A cut off of ≥ 2 fold was chosen for upregulation and ≤ 0.5 fold for downregulation. A comparison between Tspleen and Tblast state resulted in 1614 differentially regulated

transcripts. The number of regulated transcripts in Tblast cells (i.e., after activation with

specific antigen) compared to Tresting cells was 2710 transcripts. This indicates that

Tblast cells upon migration to spleen experience a dramatic reorganization of their

Average linkage cluster analysis revealed surprisingly diverse gene expression patterns. Importantly, out of 30248 transcripts only a fraction (~6%) of them showed a differential regulation (Table 5. 1). Moreover, the regulation of genes in Tmigratory and

Teffector states is very similar, as can been seen from the heat map illustration of cluster

analysis (Figure 5. 3), implying a similar transcriptome between Tspleen and TCNS. In

vitro activated T cells undergo transcriptomic changes that imparts them migratory phenotype facilitating CNS infiltration. Two interesting clustering pattern could be observed from the analysis, namely (i) downregulated in Tactivated and upregulated in

Tmigratory and Teffector and (ii) upregualted in Tactivated and downregulated in Tmigratory and

Teffector. Several clustered genes are labelled and depicted in Figure 5. 4. One of the

prominent features evident from the cluster analysis is the reciprocal regulation of the same genes in Tactivated and Tmigratory. Genes that are upregulated in Tactivated state were

downregulated in Tmigratory state and vice versa (Figure 5. 2, Figure 5. 3 and

Figure 5. 4).

As expected, major differences between Tblast cells and Tresting cells included

genes responsible for strong immune activation and proliferation, i.e. genes encoding cytokines for e.g. interleukin 17f (IL17F), CC-ligand 2 (CCL2); cell cycle-associated genes, for e.g. cell division cycle 20 homolog (CDC20), cyclin E1 (CCNE1), cytoskeleton associated protein 5 (CKAP5); factors of the DNA replication machinery, for e.g. deoxyuridine triphosphatase (DUT), minichromosome maintenance complex component 7 (MCM7), replication factor C 3 (RFC3); DNA polymerases, for e.g. minichromosome maintenance complex component 4 (MCM4), minichromosome maintenance complex component (MCM6) and cell metabolism, for e.g. 3-hydroxy-3- methylglutaryl-Coenzyme A reductase (HMGCR), cytochrome P450, family 51 (CYP51), phosphomevalonate kinase (PMVK) (Appendix 1). In striking contrast Tmigratory state displayed a completely distinct genotype. The genes regulated in Tspleen

controlled functions such as cell communication for e.g. Rho GTPase activating protein 4 (ARHGAP4), dual specificity phosphatase 5 (DUSP5), dishevelled associated activator of morphogenesis 1 (DAAM1), plasminogen activator, urokinase receptor (PLAUR); cell adhesion for e.g. CD44 antigen (CD44), epithelial membrane protein 1 (EMP1), neuropilin (NRP1), selectin L (SELL); cell migration for e.g.

integrin β1 (ITGβ1), integrin β7 (ITGβ7), (CCR5), vinculin (VCL), and immune response for e.g. CXC-chemokine ligand 2 (CXCL2), GLI pathogenesis-related 1 (GLIPR1), immunoglobulin superfamily, member 6 (IGSF6) (Appendix 2). Overall cluster analysis revealed a strong association of cell cycle genes in a Tactivated state and

Figure 5. 1 Schematic illustration of green fluorescent TMBP-GFP cell sorting using

FACS from different milieus and subsequent microarray analysis.

TMBP-GFP were generated as described in detail previously (49). Activated T cells (Tblast) were

obtained 2 days post re-stimulation in vitro using thymocytes and MBP antigen, followed by FACS sorting. Resting T cells (Tresting) were obtained 7 days post antigen exposure followed

by FACS sorting. AT-EAE was induced as described before by injection of 5 million of in vitro activated TMBP-GFP (44). FACS sorting of TMBP-GFP cells from spleen (Tspleen) and TMBP-GFP

cells from CNS (TCNS) was performed, 3.5 days post AT-EAE induction. RNA was isolated

Figure 5. 2 Microarray dataset viewed as expression plot.

Annotated genes (17694 genes) from the microarray dataset were plotted with fold values on ordinate and TMBP-GFP cell states on abscissa. An imaginary line drawn in magenta indicates

zero fold value. The transcriptomes of three T cell states viz, Tactivated, Tmigratory and Teffector were

investigated. Tactivated transcriptome was represented as gene expression fold change values,

obtained by dividing gene expression values of Tblast by Tresting. Tmigratory transcriptome was

represented as gene expression fold change values, obtained by dividing gene expression values of Tspleen by Tblast whereas Teffector transcriptome was represented as gene expression fold

change values, obtained by dividing gene expression values of TCNS by Tblast. Genes that were

Figure 5. 3 Heat Map representation of cluster analysis of annotated genes.

Average linkage hierarchical clustering of annotated genes is depicted as a heat map with dendrogram. Three T cell states viz., Tactivated, Tmigratory and Teffector were investigated. Tactivated

transcriptome was represented as gene expression fold change values, obtained by dividing gene expression values of Tblast by Tresting. Tmigratory transcriptome was represented as gene

expression fold change values, obtained by dividing gene expression values of Tspleen by Tblast

whereas Teffector transcriptome was represented as gene expression fold change values,

obtained by dividing gene expression values of TCNS by Tblast. Scale for colour code is shown

on the top and values are log transformed to the base 2. Coloured bars labelled alphabetically indicate clustered genes.

Figure 5. 4 Depiction of clusters A-F.

Annotated genes were analysed via average linkage hierarchical cluster analysis and were grouped into 6 clusters, labelled here A to F. These are depicted as a heat map with a dendrogram separately.

Figure 5. 5 Pie chart analysis of clusters A to F.

Clusters A to F were individually analysed using Gene Ontology annotations. Gene expression changes (either upregulated or downregulated) in cluster A to F were plotted as pie charts.

Figure 5. 6 Cell cycle genes and chemokine receptors are clustered.

A part of cluster E depicts clustering of differentially regulated cell cycle genes in Tactivated,

Tmigratory and Teffector transcriptomes. A part of cluster D depicting clustering of differentially

regulated inflammatory chemokine receptors in Tactivated, Tmigratory and Teffector transcriptomes.

Figure 5. 7 Differential regulation of cell migration and cell cycle processes.

This graph depicts the percentage of annotated genes differentially regulated in four biological processes, viz. cell adhesion, cell migration, cell cycle and metabolism in the Tmigratory state