Systems Analysis of Eukaryotic Proteomic Regulatory Mechanisms

Abstract

I studied three problems in my dissertation research. In the first study, I built a conceptual basis for understanding the cellular responses to multiple concurrent stimuli. A gene represents the inherent information of the cells while a stimulus represents the information outside their boundary. Since a gene and a stimulus are both packets of information, they can be considered analogues. This assumption allowed me to define the concepts of environmental interactions and environmental epistasis in terms of gene interactions and genetic epistasis. I used proteomic and transcriptomic changes in Saccharomyces cerevisiae to test the conceptual framework. In the second study, I designed and performed experiments to test the ribosome filter hypothesis. The ribosome filter hypothesis states that the amount of information flow from the transcriptome to the proteome is regulated by the composition of ribosomes. A difference in the protein composition of ribosomes from cells growing in two different conditions was evidence supporting the ribosome filter hypothesis. I used growth of S. cerevisiae with fermentable carbon source, glucose, and non-fermentable carbon source, glycerol, as the two conditions. I used iTRAQ labeling based quantitative proteomics and, in collaboration with the Joachim Frank lab, cryo-electron microscopy to measure the changes in the protein composition of ribosomes. It allowed identification of candidate ribosomal proteins that regulate the information flow from specific transcripts. I used yeast genetics and polysome profiling to measure the effect of loss of function of a candidate ribosomal protein paralog pair, Rpl8a or Rpl8b, on translation. In the third project, I studied the changes introduced in the skeletal muscle proteome of myotonic dystrophy patients, both DM1 and DM2, due to the disruption of information flow by microsatellite repeat expansions in the non-coding regions of mRNA transcripts. I used iTRAQ labeling based quantitative proteomics analysis to quantitate the changes in the skeletal muscle proteome of DM patients compared to healthy volunteers. I identified differentially present proteins and used pathway analysis to understand their role in the pathogenesis. In summary, I have studied three different ways the information content of cells and tissues are affected.