Summary. Proteomics is the global analysis of proteins that covers a broad range
of ... In this thesis, I have developed and applied robust and sensitive subpro-.
Proteomics in biomarker research Insights into the effects of aging and environment on biological systems
“Unless you expect the unexpected you will never find it, as it is hard to discover and hard to attain.” Heraclitus
To my parents.
Summary
Proteomics is the global analysis of proteins that covers a broad range of technologies aimed at determining the identity and quantity of proteins expressed in the cell, their three-dimensional structure and interaction partners. In contrast to genome, proteome reflects more accurately on the dynamic state of the cell, tissue, or an organism. Therefore much is expected from proteomics to yield better disease markers for early diagnosis and therapy monitoring, as well as biomarkers that would indicate environmental exposure or provide prediction of biological age. In this thesis, I have developed and applied robust and sensitive subproteomic approaches to study the effect of aging as well as and environmental pollution using different animal models. In the first part, a high-throughput proteomic method based on liquid chromatography coupled to 2-dimensional gel electrophoresis (LC/2-DE) was developed. The usefulness of this method has been demonstrated by applying it to the assessment of marine pollution in a field experiment. Next, I have utilized this subproteomic approach to study the effect of aging in mouse kidney of both genders. As a result, a protein expression signature (PES) of aging kidney was obtained, revealing gender-dependent alterations in proteome profiles of aging mouse kidney. In order to further reduce the dynamic range of protein expression and increase the sensitivity of proteomic analysis, I have applied a shotgun mass spectrometry-based proteomic approach using isobaric tags for relative and absolute quantification (iTRAQ) coupled to liquid chromatography and tandem mass spectrometry (LC-MS/MS) to study age-related differences in peroxisome-enriched fractions from mouse liver. Only eight proteins showed statistically significant difference in expression (p
