Published: Aug 23, 2013 8:00:00 AM
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Jin Wang, Buddy Redd associate professor in Auburn University’s Department of Chemical Engineering, has been awarded a $400,000 National Science Foundation grant to examine and model cellular changes in yeast. The project, “An Integrated Systems Engineering Approach to the Modeling of Cellular Dynamics and Bioreactors,” will focus on studying and then modeling cellular changes from aerobic growth to anaerobic fermentation, a method cells use to extract energy from carbohydrates when oxygen is unavailable.
Working with Thomas W. Jefferies, professor emeritus of bacteriology at the University of Wisconsin, and Peter He, associate professor of chemical engineering at Tuskegee University, Wang’s team hopes to answer a fundamental question behind the engineering and science of cell metabolism by examining the yeast strain Scheffersomyces stipitis and the commonly used industrial strain Saccharomyces cerevisiae. The researchers are working toward establishing a framework of processes that other researchers can apply to a variety of biological and industrial applications that require similar cellular changes, which could help biologists discover more efficient ways to generate ethanol on an industrial scale, as well as better detect and treat cancer.
“Understanding how a cell changes from aerobic growth to anaerobic fermentation provides valuable insight on why most yeast cells cannot grow anaerobically,” says Wang. “It’s an unsolved fundamental biological question. We will manipulate the cells, whether it is their environment or genetic materials, to find out more about the way they grow.”
Wang and her team will also use computer simulation to track cellular changes. Auburn is the first to study Scheffersomyces stipites’ cellular behavior this way. The team will collect time course data, which tracks a cell’s growth from one stage to the next. Jefferies, who is best known for his groundbreaking work sequencing the genome of Scheffersomyces stipitis, will help the team to record the first data set taken during cell transition from aerobic growth to anaerobic fermentation. Through Wang’s collaboration with He, a specialist in bioinformatics, data mining and algorithm development, the team will integrate computer simulations with their studies of the living yeast strain.
“We integrate wet lab experiments on the yeast strain with computational approaches to study the dynamics of cellular metabolism at the systems level,” says Wang. “Most research examines a steady state, but we’ll address it by studying a living organism as well as by using computer simulation.”