CAMDEN — A pair of Rutgers–Camden researchers is taking an innovative approach to measuring how quickly cells react with chemicals. The new process could be a valuable resource in metabolic engineering and biochemical production.
The key lies within a cell’s genes.
“Genes produce the proteins that make chemical reactions happen. They tell you a lot about what’s going on in the cell,” says Desmond Lun, an associate professor and chair of the Department of Computer Science at Rutgers–Camden.
Determining a cell’s chemical reaction rates, or “fluxome,” is an expensive undertaking. Not all labs are equipped with the tools necessary for the research, Lun says. Therefore, he is using computer modeling to uncover how fast cells react with chemicals by looking at a cell’s RNA, or gene expression.
“If we are successful, instead of having to use the existing expensive ways of measuring the fluxome, a scientist can simply measure the transcriptome (gene expression) of a cell to determine the chemical reaction rate,” Lun says. “The applications for such a method are endless: biochemical production, biomedicine, bioremediation, and so on.”
“The applications for such a method are endless: biochemical production, biomedicine, bioremediation, and so on.”
The research is being funded by a grant from the Samsung Advanced Institute of Technology. Min Kyung Kim, a doctoral student in computational and integrative biology at Rutgers–Camden, is assisting Lun with the project.
“I was interested in doing computational research and I wanted to find a place where I could study different organisms using computational tools,” says Kim, who earned her bachelor’s degree from Korea University and her master’s degree from Seoul National University. “Rutgers–Camden has given me that opportunity through working with Dr. Lun. It’s been a very valuable experience.”
Kim says she is basing her research on E. coli and yeast cells. A cell takes chemical compounds in its environment, breaks them down into basic building blocks and energy compounds, and synthesizes them into the compounds required for cell maintenance and growth as well as by-products that can be used as drugs and fuels.
Using a metabolic network model of E. coli and yeast, Lun and Kim use gene expression information to predict metabolic behavior.
“Our method will help scientists determine what chemical flows are currently occurring in a cell,” Lun says. “A lot of people are interested in this because traditional chemistry has a hard time making complex products like drugs and fuels. Metabolic engineering can be used to produce many chemical compounds much cheaper than they are otherwise produced. Drugs and fuels are prime examples of chemical compounds that can be produced using living organisms.”
Lun, a Philadelphia resident, earned bachelor's degrees in mathematics and computer engineering from the University of Melbourne in Australia. He received his master’s in electrical engineering and doctorate in computer science from MIT.
His previous research has focused on how to alter the genetic makeup of E. coli to produce biodiesel fuel derived from fatty acids; using computer modeling to more accurately analyze DNA evidence; and developing of new methods to fight tuberculosis.