Natural compounds have been largely excluded from characterization via high-throughput profiling strategies due to their limited abundance. Herein, I describe the modification of high-throughput yeast chemical genomic (CG) interaction profiling to permit identifying the modes of action of natural compounds. The previous assay proceeded by evaluating the genome-wide yeast deletion collection for drug-hypersensitivity in a volume of 0.7mL. Compound consumption was minimized with the adapted approach by reducing the assay volume 70% through simplifying the complexity of the yeast deletion pool screened. By recreating each yeast mutant in a drug-hypersensitive background, I created a novel resource that increases compound efficiency and further diminishes compound use. Evaluating a series of characterized compounds analyzed previously by the traditional CG approach validated the adaptations incorporated did not negatively affect the quality of data yielded. Ultimately, this modified strategy will be used to screen thousands of natural compounds contained within the RIKEN NPDepo library.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/32456 |
| Date | 19 July 2012 |
| Creators | Andrusiak, Kerry |
| Contributors | Boone, Charles |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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