Sandia National Laboratories, New Mexico
P.O. Box 5800
Albuquerque, NM 87185-9292
Di Liu’s major research interests involve engineering microorganisms for the production of renewable chemicals. The biological world provides us with many possibilities to produce valuable chemicals through the assembly of metabolic pathways. Further, some microorganisms possess desirable properties for the production of certain compounds. She is interested in harnessing the potential of those organisms and building novel metabolic pathways to improve the titer, productivity, and yield of various chemicals.
Bachelor’s Degree: Materials Chemistry, University of Science and Technology of China (2007-2011)
Doctoral Degree: Energy, Environmental, and Chemical Engineering, Washington University, St. Louis (2011-2017)
Postdoctoral Fellowships: Sandia National Laboratories (2017-Present)
Liu’s educational background spans across materials chemistry, chemical engineering, and biological engineering. On the materials science side, she has participated in research projects on the synthesis of nano-materials for environmental applications. Then moving forward into the field of synthetic biology, she led a few projects on the development of genetically-encoded biosensors and exploring their applications in metabolic engineering.
To direct metabolic flux towards the product, it is essential to understand the metabolism of the host organism. Multi-omics analysis will be used to provide a systematic understanding of the host metabolism and the regulatory landscapes. Genetic engineering strategies will then be designed to alter the carbon flow towards our target molecules.
Engineering microorganisms require efficient genetic engineering tools. Unlike commonly used model organisms, engineering tools are still lacking for Liu’s host organism. Thus, another effort will be focused on developing tools including promoters, genome editing methods, and genetic transformation methods.
- Liu, D., Zhang, F. (2018) Metabolic feedback circuits provide rapid control of metabolic dynamics. ACS Synthetic Biology. 7.2
- Mannan, A. A.*, Liu, D.*, Zhang, F., Oyarzún, D. A. (2017) Fundamental design principles for transcription-factor-based metabolite biosensors. ACS Synthetic Biology 6.10: 1851-1859.
- Liu, D., Xiao, Y., Evans, B. S., and Zhang, F. Z. (2015) Negative Feedback Regulation of Fatty Acid Production Based on a Malonyl-CoA Sensor-Actuator, ACS Synthetic Biology 4, 132-140.
- Liu, D., Evans, T., and Zhang, F. (2015) Applications and advances of metabolite biosensors for metabolic engineering, Metabolic Engineering 31, 35-43.
- Xiao, Y., Bowen C. H., Liu, D., Zhang, F. (2016) Exploiting nongenetic cell-to-cell variation for enhanced biosynthesis. Nature Chemical Biology 12, 339-344.
Selected Book Chapter
- Liu, D., Bentley, G., Chu, K., Zhang, F. (2016) Book Chapter: Design of Dynamic Pathways, Biotechnology for Biofuel Production and Optimization, Elsevier, 2016