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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.
Im Genom von Listeria monocytogenes konnten zwei Gene identifiziert werden, die mutmaßlich für niedermolekulare Protein-Tyrosin Phosphatasen (LMW-PTPs) kodieren, Lmo0938/Ptp-1 und Lmo2540/Ptp-2, beide ähneln LMW-PTPs von B. subtilis. Einzel- und Doppeldeletionen der ptp-Gene beeinflussten die Transkription zahlreicher Gene, wie anhand von Gesamtgenom-DNA-Microarray-Analysen und quantitativer RT-PCR gezeigt werden konnten. Insbesondere waren die Gene für i) die Internaline A und B, ii) den Osmoprotektanten-Transporter OpuC, iii) MCP, notwendig zur Flagellen-Bewegung und iv) eine Anzahl von den Proteinen, die in die Nährstoffaufnahme sowie den intrazellulären Metabolismus involviert sind, in vitro herunterreguliert. Die PrfA-regulierten Virulenzgene wurden in den Mutanten verstärkt exprimiert. Im Wesentlichen konnte das gleiche Transkriptionsmuster in infizierten Caco-2-Enterocyten beobachtet werden. Die verringerte Invasivität (abhängig von InlA) und die Unbeweglichkeit der Mutanten passt zu den Transkriptionsergebnissen. Jedoch wurden weder die intrazelluläre Replikation innerhalb eukaryontischer Wirtszellen noch die Resistenz gegen Stressbedingungen durch die Deletion beeinträchtigt. Die Proteome des Wildtyps und der ptp-Mutanten wurden durch 2-dimensionale Gelelektrophorese verglichen und es zeigte sich, dass die Transkriptionsergebnisse nicht vollständig im Proteom reflektiert wurden. Die Ergebnisse zeigen, dass die Ptps in die Regulationsnetzwerke des alternativen Stress-Sigmafaktor SigB und von PrfA eingreifen. Der ähnliche Effekt beider Ptps auf die Transkription oder auf den Proteinlevel deutet eine Interaktion oder Kooperation der beiden Enzyme an.