Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
Fritz, K.
Functional Proteomics and Metabolomics for the Study of Cancer Metabolism
PhD-Studium (Doctor of Philosophy); Humanmedizin; [ Dissertation ] Graz Medical University; 2016. pp.
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- Autor*innen der Med Uni Graz:
- Fritz Katarina
- Betreuer*innen:
- Birner-Grünberger Ruth
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- Abstract:
- Altered metabolism is one of the hallmarks of cancer. This is not limited to the well-known changes in glucose metabolism, but also includes changes in anabolism and catabolism of lipids in cancerous tissues and cells. The first chapter of this thesis investigates the impact of adipose triglyceride lipase (ATGL), the rate limiting enzyme in lipid degradation, on metabolism of cancer. As cancer model, B-cell tumors lacking ATGL (ATGL-KO), which have been shown to exhibit a growth advantage in mice, were used. The aim here was to depict metabolic mechanisms which might be responsible for this enhanced growth rate. However, no significant metabolic changes could be observed in ATGL-KO as compared to control cells by stable isotope resolved metabolomics, radioactive nutrient uptake and tracing and other biochemical tests in central carbon and fatty acid metabolism, which could explain the growth advantage. Interestingly, activity-based proteomics revealed an increased unknown serine hydrolase activity (of a putative phospholipase like protein named PLBD2) which might partly compensate for the loss of ATGL. However the native substrate of PLBD2 remains to be identified. Moreover, quantitative proteomics showed the downregulation of glycine dehydrogenase (GLDC), among other proteins, in ATGL-KO cells. This enzyme is involved in one-carbon metabolism. But a causal relationship remains to be established. The use of CRISPR-Cas9 to knock out ATGL in lung cancer cells (A549) led to a complete depletion of the enzyme and thus provided another cell model for the investigation of ATGL in cancer. However, in contrast to B-cells, the lack of ATGL rather decreased growth of the lung cancer cells. These contradictive results may hint toward a tissue-specific role of ATGL that can be very important in diagnosis and progression of cancer. In the second chapter this thesis shows the importance of including modified trypsin in proteomic database searches. Trypsin is the most common protease used in bottom-up proteomics workflows. In order to avoid the autolysis of trypsin, the enzyme is usually chemically modified. However, here it is shown that the modification is not complete and furthermore does not fully protect from autolysis. This results in the presence of modified peptides of trypsin in the sample. During downstream analysis, the modified peptides, if not included in the protein database, can lead to false positive identifications. Due to the high abundance of trypsin in digests modified peptides could be identified in large amounts. If modified trypsin was not included in the database these modified peptides were found to lead to misassignments in 18 % of analyzed publically available projects. Here a database search method is presented which includes modified trypsin. This easily implementable method avoids false positive assignments, while the increase in search space stays minimal and thus omits impaired result statistics.