The discovery in yeast cells of a genetic network that guards against lethal DNA damage is a first step in the creation of a database of disease-causing combinations of mutated human genes, according to researchers at The Johns Hopkins University School of Medicine led by Jef. D. Boeke, Ph.D. In a report in the March 10 issue of Cell, the Hopkins team described a genetic network that is necessary for ensuring genomic stability in yeast. This study also identified previously unrecognized genes critical for maintaining DNA integrity and novel functions for well-known genes.
"A lot of human diseases are caused by multiple gene mutations that are difficult to identify," said Boeke, who is a professor of molecular biology and genetics and director of the High Throughput Biology Center at the Hopkins School of Medicine.
The yeast cell is an excellent model for this kind of study because 25 percent of human disease genes are also found in yeast, according to Boeke. Therefore, the discovery of this network of genes could help to identify mutations whose combined deleterious effects cause human diseases, including cancer and neurodegeneration, as well as aging.
"The interactions we discovered in yeast could also help researchers select the human versions of these genes suitable as targets for the development of new, more targeted and less toxic cancer therapies," Boeke said.
The goal of the Hopkins study was to identify pairs of genes that, while different, play redundant roles in governing genomic integrity in yeast cells, filling in for each other when one of the genes is mutated or deleted. Such redundancies ensure that each task in the network of biochemical reactions governing DNA stability is accomplished, Boeke noted.
Based on the data from this study, the investigators were able to separate the genes governing the stability of yeast DNA into 16 modules, or mini-pathways of genes, based on these genetic interactions, which are called synthetic fitness or lethality interactions. Synthetic lethality is a phenomenon in which two mutations that are not individually lethal cause cell death when combined. Specifically, the Hopkins team identified 4,956 interactions among 875 genes involved in DNA repair, DNA replication, the halting of replication and cell cycle progression by "checkpoints" so that damaged DNA can undergo repair, and responses to oxidative stress necessary for reducing the intracellular levels of highly reactive molecules that bind to and damage DNA.
The yeast has about 6,000 genes, of which about 1,000 are essential to survival and 5,000 are not, Boeke said. Specifically, 1,000 of the 5,000 non-essential genes are important enough so that the yeast grows slowly if any one of them is absent. And any of the 4,000 other genes can be deleted from the cell without interfering with the cell's growth.
A major goal of the Hopkins team is to determine which of the non-essential genes interact with each other, said Boeke. All such pair-wise combinations of the 5,000 non-essential genes in the yeast genome would require about 25 million tests, he added. In the current study, 74 genes were tested in pair-wise combination with the 5,000 non-essential genes, a feat approximately equivalent to 370,000 gene-pair tests.
The Hopkins team used a technology known as dSLAM (heterozygote diploid-based synthetic lethality analyzed by microarray) to look at the effects of 5,000 different double mutations on cell fitness in a single experiment. With this technology, only 5,000 tests would be required to map the 25 million pair-wise combinations, greatly speeding the work.
The dSLAM strategy is somewhat like pulling out parts of a radio at random to see what happens, Boeke said.
"With yeast, as with a radio, you might rip out part A or part B and find that the radio still works; but if you pull out both parts and the radio dies you would learn that A and B can compensate for each other's absence. The parts we're pulling out of yeast are genes, and we look to see what happens when both of the genes are pulled out."
The dSLAM technology takes advantage of DNA barcode that identifies which genes a yeast cell is missing. This is much like using a commercial barcode in a store to quickly identify items at the checkout counter. The scanner in this case is a microarray: a grid of thousands of spots on a piece of glass that holds a unique "sensor" strand of DNA that matches one of the barcodes. Machines then read the microarray to identify which of the sensors found matching barcodes that identified specific yeast cells with specific mutations. If two genes that compensated for each other are knocked out, the yeast cell dies and the microarray doesn't record that cell, Boeke noted. That means the two genes interact with each other, he said.
"This strategy for finding interacting genes will open the door to an extraordinarily rich source of new data on DNA damage, repair, and human diseases," Boeke added.
This work was supported by the National Human Genome Research Institute, a National Institutes of Health Roadmap grant, and the Whitaker Foundation.
Other contributors to this paper from Johns Hopkins include Joel S. Bader, Ph.D., an assistant professor; Xuewen Pan, Ph.D., the first author of the paper and a postdoctoral fellow; Ping Ye, Ph.D., a postdoctoral fellow, and Daniel S. Yuan, M.D., a research associate. All authors work in the new, interdisciplinary High Throughput Biology Center at Johns Hopkins.
Materials provided by Johns Hopkins Medical Institutions. Note: Content may be edited for style and length.
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