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Transcriptional Regulation of Gene Networks TRANSCRIPTIONAL REGULATION OF GENE NETWORKS THOMAS R. BURKARD DOCTORAL THESIS Graz, University of Technology Institute for Genomics and Bioinformatics Petersgasse 14, 8010 Graz and Vienna, Research Institute of Molecular Pathology Eisenhaber Group Dr. Bohrgasse 7, 1030 Vienna Vienna, May 2007 Abstract Background: cDNA microarray studies result in a huge amount of expression data. The main focus lies often on revealing new components which end in long lists without understanding the global networks described by them. This doctoral thesis asks to which extent theoretical analyses can reveal gene networks, molecular mechanisms and new hypotheses in microarray expression data. For this purpose, gene expression profiles were generated using microarrays and a cell model for fat cell development. Results: A novel adipogenic atlas was constructed using microarray expression data of fat cell development. In total, 659 gene products were subjected to de novo annotation and extensive literature curation. The resulting gene networks delineate phenotypic observations, such as clonal expansion, up-rounding of the cells and fat accumulation. Based on this global analysis, seven targets were selected for experimental follow up studies. Further, 26 transcription factors are suggested by promoter analysis to regulate co-expressed genes. 27 of 36 investigated pathways are preferentially controlled at rate-limiting enzymes on the transcriptional level. Additionally, the first set of 391 universal proteins that are known to be rate-determining was selected. This dataset was hand-curated from >15,000 PubMed abstracts and contains 126 rate-limiting proteins from curated databases with increased reliability. Two thirds of the rate-determining enzymes are oxidoreductases or transferases. The rate-limiting enzymes are dispersed throughout the metabolic network with the exception of citrate cycle. The knockout of the rate-limiting adipose triglyceride lipase responds in transcriptional down-regulation of the whole oxidative phosphorylation and specific control of many rate-limiting enzymes in brown fat tissue. Finally, it was shown that selective transcriptional regulation of rate-limiting enzymes is a widely applied mechanism for the control of metabolic networks. Conclusion: This thesis demonstrates that large-scale transcription profiling in combination with sophisticated bioinformatics analyses can provide not only a list of novel players in a particular setting, but also a global view on biological processes and molecular networks. Page I Publications This thesis is based on the following publications as well as upon unpublished observations. Papers: Hackl* H, Burkard* TR, Sturn A, Rubio R, Schleiffer A, Tian S, Quackenbush J, Eisenhaber F and Trajanoski Z (*contributed equally): Molecular processes during fat cell development revealed by gene expression profiling and functional annotation. Genome Biol. 2005; 6(13):R108 Burkard T, Trajanoski Z, Novatchkova M, Hackl H, Eisenhaber F: Identification of New Targets Using Expression Profiles. In: Antiangiogenic Cancer Therapy, Editors: Abbruzzese JL, Davis DW, Herbst RS; CRC Press (in press) Hartler J, Thallinger GG, Stocker G, Sturn A, Burkard TR, Körner E, Scheucher A, Rader R, Schmidt A, Mechtler K, Trajanoski Z: MASPECTRAS: a platform for management and analysis of proteomic LC-MS/MS data. BMC Bioinformatics. (submitted) Conference proceedings and poster presentations: Hartler, J.; Thallinger, G.; Stocker, G.; Sturn, A.; Burkard, T.; Körner, E.; Mechtler, K.; Trajanoski, Z.: Management and Analysis of Proteomics LC-MS/MS Data. Fourth International Symposium of the Austrian Proteomics Platform. (2007), Seefeld in Tirol, Austria Hackl, H.; Burkard, T.; Sturn, A.; Rubio, R.; Schleiffer, A.; Tian, S.; Quackenbush, J.; Eisenhaber, F.; Trajanoski, Z.: Molecular processes during fat cell development revealed Page II by large scale expression analysis and functional annotation. 1st Symposium on Lipid and Membrane Biology. (2006), page. 12 – 12 Hartler, J.; Thallinger, G.; Stocker, G.; Sturn, A.; Burkard, T.; Körner, E.; Fuchs, T.; Mechtler, K.; Trajanoski, Z.: MASPECTRAS:Web-based System for Storage, Retrieval, Quantification and Analysis of Proteomic LC MS/MS Data. Third International Symposium of the Austrian Proteomics Platform. (2006), Seefeld in Tirol Hartler, J.; Thallinger, G.; Sturn, A.; Burkard, T.; Körner, E.; Fuchs, T.; Mechtler, K.; Trajanoski, Z.: MASPECTRAS: Web-basiertes Datenbanksystem zur Verwaltung von Proteomik-Daten. Österreichische Akademie der Wissenschaften (2005) Hackl, H.; Burkard, T.; Paar, C.; Fiedler, R.; Sturn, A.; Stocker, G.; Rubio, R.; Schleiffer, A.; Quackenbush, J.; Eisenhaber, F.; Trajanoski, Z.: Large Scale Expression Profiling and Functional Annotation of Adipocyte Differentiation. Keystone Symposia: Molecular Control of Adipogenesis and Obesity. (2004), S. 193 - 193 Hackl, H.; Burkard, T.; Paar, C.; Fiedler, R.; Sturn, A.; Stocker, G.; Rubio, R.; Quackenbush, J.; Schleiffer, A.; Eisenhaber, F.; Trajanoski, Z.: Large Scale Expression Profiling and Functional Annotation of Adipocyte Differentiation. -First Internatrional Symposium of the Austrian Proteomics Platform. (2004), Seefeld, Austra Hartler, J.; Thallinger, G.; Stocker, G.; Sturn, A.; Burkard, T.; Körner, E.; Fuchs, T.; Mechtler, K.; Trajanoski, Z.: MASPECTRAS:Web-based System for Storage, Retrieval, and Analysis of Proteomic LC MS/MS Data. HUPO 4th Annual World Congress. (2004) Munich Hackl, H.; Burkard, T.; Rubio, R.; Quackenbush, J.; Trajanoski, Z.: Gene expression analysis during adipocyte differentiation. High-Level Scientific Conferences: Molecular Mechanisms in Metabolic Diseases. (2003), S. 9 – 9 Page III Index of contents Abstract .....................................................................................................................................I Publications..............................................................................................................................II Index of contents....................................................................................................................IV 1. Introduction...................................................................................................................... 1 1.1. Fat cell differentiation............................................................................................. 1 3T3-L1 cell line – A model system to investigate adipogenesis...................................... 2 The complex process of adipogenesis is incompletely understood.............................. 2 Adipogenesis is primarily regulated at the transcriptional level .................................. 2 Expression profiling of 3T3-L1 differentiation to adipocytes...................................... 4 Identification of the molecular role of the gene products ................................................ 5 Gene networks are the basis for testing new hypothesis in fat cell development ............ 8 1.2. Transcriptional control of metabolic fluxes............................................................ 9 2. Results............................................................................................................................ 12 2.1. Fat cell development............................................................................................. 12 Annotation of expressed sequence tags is the basis for the comprehensive analysis of expression profiles ......................................................................................................... 13 The valid expression data is relevant for in vivo applications ....................................... 16 Biological functions can be assigned to dominant co-expression patterns .................... 18 A global molecular atlas describes complex changes during adipogenesis ................... 20 Clonal expansion is reflected in adipogenic gene networks....................................... 21 Target identification powered by the global adipogenic atlas........................................ 24 Enzymatic networks are regulated in an ordered manner .............................................. 28 2.2. Transcriptional regulation of rate-limiting steps .................................................. 29 Page IV An accurate set of 126 rate-determining enzymes from curated databases ................... 30 Comprehensive collection of known rate-limiting enzymes using PubMed.................. 31 Molecular functions associated with rate-limitation ...................................................... 31 Key loci are dispersed in the metabolic network ........................................................... 34 Disturbance of the enzymatic network by knocking out a single rate-limiting enzyme 35 Transcriptional regulation of rate-limiting enzymes during differentiation................... 37 3. Discussion ......................................................................................................................39 3.1. Fat cell development............................................................................................. 41 3.2. Rate-limitation ...................................................................................................... 43 4. Methods.......................................................................................................................... 48 4.1. Fat cell development............................................................................................. 48 EST mapping to genes and proteins..............................................................................
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