ENG Researchers Win $1.5M Department of Energy Grant
Collaboration could lead to better biofuel synthesis
By Liz Sheeley
Three ENG researchers, Assistant Professor Mary Dunlop (BME), Assistant Professor Wilson Wong (BME), and Professor Ji-Xin Cheng (ECE, BME, Chemistry, Physics), were awarded a three-year, $1.5M Department of Energy (DOE) grant to develop technology to better understand and measure the synthesis of biofuels in living cells.
“This project uses complementary skills from each of our labs and the intersection is a really exciting interdisciplinary approach to an important problem,” says Dunlop, the principal investigator on the project.
Biofuels, including biodiesel, are renewable sources of energy, but producing them economically has been one of the biggest hang-ups in widespread use. Scientists have managed to use synthetic biology and metabolic engineering to use living cells to produce the precursor to biofuels, fatty acids, but the production rate is relatively low and the process is not precise.
The current way to quantify fatty acid production is to use a method called gas chromatography—mass spectrometry (GC-MS). The alternative method Dunlop, Wong, and Cheng are proposing would allow researchers to test hundreds to thousands of cell types at once and greatly improve the current throughput of GC-MS.
The DOE-funded project uses an imaging method pioneered in the Cheng lab called stimulated Raman scattering (SRS) to image cells, which drives the potential to dramatically increase throughput while simultaneously providing a direct measurement of fatty acid biosynthesis.
“This new method would give us a lot more freedom to explore different types of cells, and change the DNA within them to increase or decrease cellular activities that we might think contribute to fatty acid production,” says Dunlop. “The ultimate promise of this type of approach is that it can be used on a wide variety of cell types.”
The project has three main objectives that blend into one ultimate goal: to design, screen, and categorize thousands of genetic variants to optimize fatty acid production. Along the way they will use SRS in combination with genome engineering and gene circuit design to reach their goal of building a library of genetically different cell types categorized by the quality and quantity of their fatty acid production.
The library would contain data specific to each cell type tested, including which fatty acid the cell makes, the quantity and quality of the product, and the byproducts made during synthesis. Down the line, a library like this could let engineers quickly pick the best genetic variant to produce high yields of their desired product, including biofuels.