New Technology Tracks Cells Containing Multiple Mutations Within a Cellular Population


Different techniques to generate large collections of cells intentionally mutated in a number of targeted genes are currently available, and specific mutants in those collections can be readily identified. However, to manipulate complex traits involving multiple genes, it is necessary to identify individual cells that contain several mutated genes. Tracking individual cells that harbor specific combinations of two or more mutations separated by long distances within their genome is a time-consuming and effort-intensive process. In a recent study, researchers at the University of Colorado in Boulder reported the development of a new method called “TRACE” that allows the identification of single bacterial or eukaryote cells with mutations in about six targeted genes. The technique uses mathematical modeling to design short DNA fragments (or primers) that specifically bind to the targeted mutation sites. These primers are synthesized in a way that allows amplification of the targeted regions and subsequent joining of the amplification products into a single DNA molecule. By performing the amplification and joining of the DNA products in an emulsion where each cell in the population is confined to a single droplet, the six targeted sites can be analyzed by high-throughput sequencing to identify which cells contain mutations in one or more of the sites. In proof-of-concept experiments, the team used TRACE to identify a combination of mutant genes that confer the bacterium Escherichia coli tolerance to the toxicity of cellulose hydrolysate and the biofuel isobutanol. Because of the much higher throughput of TRACE relative to other genotyping methods, this technology will substantially accelerate the engineering of microbes for the production of biofuels and other chemicals.


Zeitoun, R. I., A. D. Garst, G. D. Degen, G. Pines, T. J. Mansell, T. Y. Glebes, N. R. Boyle, and R. T. Gill. 2015. “Multiplexed Tracking of Combinatorial Genomic Mutations in Engineered Cell Populations,” Nature Biotechnology, DOI: 10.1038/nbt.3177.