Sauer Lab, Metabolomics, Functional genomics
Proteome-scale enzyme discovery in yeast using nontargeted metabolomics.
Background
Metabolic enzymes catalyze biochemical reactions among small molecules, thereby driving cellular proliferation, signal processing and interactions. Despite these key functions, many enzymes remain undiscovered, constraining our understanding of metabolism and our ability to perform rational manipulations in the contexts of biotechnology and health. Many missing enzymes are expected to be encoded by functionally uncharacterized genes that make up 30-50% of the genome in all sequenced organisms including model species such as E. coli or yeast. Additionally, known enzymes may catalyze additional reactions to those that have been reported, a concept known as enzyme promiscuity. Finally, even known non-catalytic proteins such as transcriptional regulators or structural proteins may have yet undiscovered enzymatic activities, a concept referred to as moonlighting. However, how many enzymes are still missing and, in most cases, which reactions they would catalyze, remains unknown.
Your project
In your project, you will purify proteins of the yeast Saccharomyces cerevisiae using 96-well format expression and purification systems. The purified proteins will then be tested for enzymatic activity using an automated nontargeted mass spectrometry method developed in our lab. We have already applied this method to screen E. coli protein libraries and discovered numerous novel enzymes. Thus, we are confident that you will successfully discover novel enzymes in yeast. This will enable you to investigate to what extent enzyme promiscuity and moonlighting occur in the yeast proteome and how this affects metabolism at a systems level. During your stay, you will learn the basics of high-throughput biochemistry, cutting-edge mass spectrometry, analysis of large datasets and genome-scale metabolic modeling using Matlab.
Requirements
Basic skills in the lab (cultivating cells, preparing buffers and media) are expected. No previous experience with Matlab is required. The project is conceived as a Master thesis (6 months).
Contact: Daniel Sévin