SGER: From Activity to ORF

点击翻译按钮获取中文摘要

The spectacular success of genome sequencing projects has led to associating many genes with the proteins they encode. However many genes remain that cannot be assigned a known protein and many known enzyme activities cannot be assigned to a gene. According to the literature, even with the use of innovative bioinformatics tools, 13 to 60% of the ORFs (open reading frames, those portions of genes that encode proteins) of most completely sequenced genomes are uncharacterized or miss annotated. To begin to "fill the holes" in metabolic maps, a strategy of beginning with the known activity of proteins whose ORF's have not been identified and proceeding to discover the associated gene has been developed. The activity of interest is dependent on simple, traditional biochemical purification techniques combined with innovative use of mass spectrometric technology. Using mass spectrometric techniques, the candidate genes are identified by correlating the increase in protein specific activity with the increase in the amount of protein in the partially purified fraction. Yeast strains have been made that over-express, one at a time, each of the 6,000 or so yeast genes. Using the strain corresponding to each candidate gene, the gene responsible for the activity of interest can be identified. In this way, the yeast gene for methylglyoxal reductase activity was identified with relatively little effort. However, the protein responsible for this activity is more abundant than are most other yeast proteins. Using state of the art mass spectrometry and sophisticated database mining tools, this project will determine the lower limit of abundance that will allow association of a protein with its gene. If successful, this methodology will provide information that is important for metabolic engineering, drug discovery and understanding metabolic networks. This project will incorporate undergraduate and high school students, including women and minorities into the project.