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DNA microarrays have become a standard technique to assess the mRNA levels for complete genomes. To identify significantly regulated genes from these large amounts of data a wealth of methods has been developed. Despite this, the functional interpretation (i.e. deducing biological hypothesis from the data) still remains a major bottleneck in microarray data analysis. Most available methods display the set of significant genes in long lists, from which common functional properties have to be extracted. This is not only a tedious and time-consuming task, which becomes less and less feasible with increasing numbers of experimental conditions, but is also prone to errors, since it is commonly done by eye. In the course of this work methods have been developed and tested, that allow for a computerbased analysis of functional properties being relevant in the given experimental setting. To this end the Gene Ontology was chosen as an appropriate source of annotation data, because it combines human-readability with computer-accessibility of the annotations term and thus allows for a statistical analysis of functional properties. Here the gene-annotations are integrated in a Correspondence Analysis which allows to visualize genes, hybridizations and functional categories in a single plot. Due to the increasing amounts of available annotations and the fact that in most settings only few functional processes are differentially regulated, several filter criteria have been developed to reduce the number of displayed annotations to a set being relevant in the given experimental setting. The applicability of the presented visualization and filtering have both been validated on datasets of varying complexity. Starting from the well studied glucose-pathway in S. cerevisiae up to the comparison of different tumor types in human. In both settings the method generated well interpretable plots, which allowed for an immediate identification of the major functional differences between the experimental conditions [90]. While the integration of annotation data like GO facilitates functional interpretation, it lacks the capability to identify key regulatory elements. To facilitate such an analysis, the occurrence of transcription factor binding sites in upstream regions of genes has been integrated to the analysis as well. Again this methodology was biologically validated on S. cerevisiae as well human cancer data sets. In both settings TFs known to exhibit central roles for the observed transcriptional changes were plotted in marked positions and thus could be immediately identified [206]. In essence, integration of supplementary information in Correspondence Analysis visualizes genes, hybridizations and annotation data in a single, well interpretable plot. This allows for an intuitive identification of relevant annotations even in complex experimental settings. The presented approach is not limited to the shown types of data, but is generalizable to account for the majority of the available annotation data.
In acute graft-versus-host disease (GVHD) alloreactive donor T cells selectively damage skin, liver, and the gastrointestinal tract while other organs are rarely affected. The mechanism of this selective target tissue infiltration is not well understood. We investigated the importance of alloantigen expression for the selective organ manifestation by examining spatiotemporal changes of cellular and molecular events after allogeneic hematopoietic cell transplantation (allo-HCT). To accomplish this we established a novel multicolor light sheet fluorescence microscopy (LSFM) approach for deciphering immune processes in large tissue specimens on a single-cell level in 3 dimensions. We combined and optimized protocols for antibody penetration, tissue clearing, and triple-color illumination to create a method for analyzing intact mouse and human tissues. This approach allowed us to successfully quantify changes in expression patterns of mucosal vascular addressin cell adhesion molecule–1 (MAdCAM-1) and T cell responses in Peyer’s patches following allo-HCT. In addition, we proofed that LSFM is suitable to map individual T cell subsets after HCT and detected rare cellular events. We employed this versatile technique to study the role of alloantigen expression for the selective organ manifestation after allo-HCT. Therefore, we used a T cell receptor (TCR) transgenic mouse model of GVHD that targets a single peptide antigen and thereby mimics a major histocompatibility complex (MHC)-matched single antigen mismatched (miHAg-mismatched) HCT. We transplanted TCR transgenic (OT-I) T cells into myeloablatively conditioned hosts that either express the peptide antigen ovalbumin ubiquitously (βa-Ova) or selectively in the pancreas (RIP-mOva), an organ that is normally not affected by acute GVHD. Of note, at day+6 after HCT we observed that OT-I T cell infiltration occurred in an alloantigen dependent manner. In βa-Ova recipients, where antigen was ubiquitously expressed, OT-I T cells infiltrated all organs and were not restricted to gastrointestinal tract, liver, and skin. In RIP-mOva recipients, where cognate antigen was only expressed in the pancreas, OT-I T cells selectively infiltrated this organ that is usually spared in acute GVHD. In conditioned RIP-mOva the transfer of 100 OT-I T cells sufficed to effectively infiltrate and destroy pancreatic islets resulting in 100% mortality. By employing intact tissue LSFM in RIP-mOva recipients, we identified very low numbers of initial islet infiltrating T cells on day+4 after HCT followed by a massive T cell migration to the pancreas within the following 24 hours. This suggested an effective mechanism of effector T cell recruitment to the tissue of alloantigen expression after initial antigen specific T cell encounter. In chimeras that either expressed the model antigen ovalbumin selectively in hematopoietic or in parenchymal cells only, transplanted OT-I T cells infiltrated target tissues irrespective of which compartment expressed the alloantigen. As IFN-γ could be detected in the serum of transplanted ovalbumin expressing recipients (βa-Ova, βa-Ova-chimeras and RIP-mOva) at day+6 after HCT, we hypothesized that this cytokine may be functionally involved in antigen specific OT-I T cell mediated pathology. In vitro activated OT-I T cells responded with the production of IFN-γ upon antigen re-encounter suggesting that IFN-γ might be relevant in the alloantigen dependent organ infiltration of antigen specific CD8+ T cell infiltration after HCT. Based on these data we propose that alloantigen expression plays an important role in organ specific T cell infiltration during acute GVHD and that initial alloreactive T cells recognizing the cognate antigen propagate a vicious cycle of enhanced T cell recruitment that subsequently culminates in the exacerbation of tissue restricted GVHD.
Background: The frequency of the most observed cancer, Non Hodgkin Lymphoma (NHL), is further rising. Diffuse large B-cell lymphoma (DLBCL) is the most common of the NHLs. There are two subgroups of DLBCL with different gene expression patterns: ABC (“Activated B-like DLBCL”) and GCB (“Germinal Center B-like DLBCL”). Without therapy the patients often die within a few months, the ABC type exhibits the more aggressive behaviour. A further B-cell lymphoma is the Mantle cell lymphoma (MCL). It is rare and shows very poor prognosis. There is no cure yet. Methods: In this project these B-cell lymphomas were examined with methods from bioinformatics, to find new characteristics or undiscovered events on the molecular level. This would improve understanding and therapy of lymphomas. For this purpose we used survival, gene expression and comparative genomic hybridization (CGH) data. In some clinical studies, you get large data sets, from which one can reveal yet unknown trends. Results (MCL): The published proliferation signature correlates directly with survival. Exploratory analyses of gene expression and CGH data of MCL samples (n=71) revealed a valid grouping according to the median of the proliferation signature values. The second axis of correspondence analysis distinguishes between good and bad prognosis. Statistical testing (moderate t-test, Wilcoxon rank-sum test) showed differences in the cell cycle and delivered a network of kinases, which are responsible for the difference between good and bad prognosis. A set of seven genes (CENPE, CDC20, HPRT1, CDC2, BIRC5, ASPM, IGF2BP3) predicted, similarly well, survival patterns as proliferation signature with 20 genes. Furthermore, some bands could be associated with prognosis in the explorative analysis (chromosome 9: 9p24, 9p23, 9p22, 9p21, 9q33 and 9q34). Results (DLBCL): New normalization of gene expression data of DLBCL patients revealed better separation of risk groups by the 2002 published signature based predictor. We could achieve, similarly well, a separation with six genes. Exploratory analysis of gene expression data could confirm the subgroups ABC and GCB. We recognized a clear difference in early and late cell cycle stages of cell cycle genes, which can separate ABC and GCB. Classical lymphoma and best separating genes form a network, which can classify and explain the ABC and GCB groups. Together with gene sets which identify ABC and GCB we get a network, which can classify and explain the ABC and GCB groups (ASB13, BCL2, BCL6, BCL7A, CCND2, COL3A1, CTGF, FN1, FOXP1, IGHM, IRF4, LMO2, LRMP, MAPK10, MME, MYBL1, NEIL1 and SH3BP5; Altogether these findings are useful for diagnosis, prognosis and therapy (cytostatic drugs).
The variant surface glycoprotein (VSG) of African trypanosomes plays an essential role in protecting the parasites from host immune factors. These trypanosomes undergo antigenic variation resulting in the expression of a single VSG isoform out of a repertoire of around 2000 genes. The molecular mechanism central to the expression and regulation of the VSG is however not fully understood.
Gene expression in trypanosomes is unusual due to the absence of typical RNA polymerase II promoters and the polycistronic transcription of genes. The regulation of gene expression is therefore mainly post-transcriptional. Regulatory sequences, mostly present in the 3´ UTRs, often serve as key elements in the modulation of the levels of individual mRNAs. In T. brucei VSG genes, a 100 % conserved 16mer motif within the 3´ UTR has been shown to modulate the stability of VSG transcripts and hence their expression. As a stability-associated sequence element, the absence of nucleotide substitutions in the motif is however unusual. It was therefore hypothesised that the motif is involved in other essential roles/processes besides stability of the VSG transcripts.
In this study, it was demonstrated that the 100 % conservation of the 16mer motif is not essential for cell viability or for the maintenance of functional VSG protein levels. It was further shown that the intact motif in the active VSG 3´ UTR is neither required to promote VSG silencing during switching nor is it needed during differentiation from bloodstream forms to procyclic forms. Crosstalk between the VSG and procyclin genes during differentiation to the insect vector stage is also unaffected in cells with a mutated 16mer motif. Ectopic overexpression of a second VSG however requires the intact motif to trigger silencing and exchange of the active VSG, suggesting a role for the motif in transcriptional VSG switching. The 16mer motif therefore plays a dual role in VSG in situ switching and stability of VSG transcripts. The additional role of the 16mer in the essential process of antigenic variation appears to be the driving force for the 100 % conservation of this RNA motif.
A screen aimed at identifying candidate RNA-binding proteins interacting with the 16mer motif, led to the identification of a DExD/H box protein, Hel66. Although the protein did not appear to have a direct link to the 16mer regulation of VSG expression, the DExD/H family of proteins are important players in the process of ribosome biogenesis. This process is relatively understudied in trypanosomes and so this candidate was singled out for detailed characterisation, given that the 16mer story had reached a natural end point. Ribosome biogenesis is a major cellular process in eukaryotes involving ribosomal RNA, ribosomal proteins and several non-ribosomal trans-acting protein factors. The DExD/H box proteins are the most important trans-acting protein factors involved in the biosynthesis of ribosomes. Several DExD/H box proteins have been directly implicated in this process in yeast. In trypanosomes, very few of this family of proteins have been characterised and therefore little is known about the specific roles they play in RNA metabolism. Here, it was shown that Hel66 is involved in rRNA processing during ribosome biogenesis. Hel66 localises to the nucleolus and depleting the protein led to a severe growth defect. Loss of the protein also resulted in a reduced rate of global translation and accumulation of rRNA processing intermediates of both the small and large ribosomal subunits. Hel66 is therefore an essential nucleolar DExD/H protein involved in rRNA processing during ribosome biogenesis. As very few protein factors involved in the processing of rRNAs have been described in trypanosomes, this finding represents an important platform for future investigation of this topic.