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Metabolic Pathway Engineering
The research group is interested in engineering efficient microbial cell factories to produce phytochemicals, natural products, polymers and oleochemiclas. Our approach provides promising solutions to build sustainable biorefinery platforms that upgrade chemical manufacturing with smaller environmental footprint and better economics.
Synthetic Biology
We build synthetic biology devices to better control and reprogram cell metabolism with increased genetic robustness and predictability. We are interested in developing platform techniques including efficient multi-gene assembly, combinatorial pathway engineering and sophisticated genome-editing tools.
Computational Modeling
Biophysical and biochemical models are important to understand genetic circuit dynamics, metabolic network constraints, cell-cell communications and microbial consortia interactions. Deterministic or stochastic models will be built to interrogate synthetic biological systems and understand the rules of life upon which we can engineer more efficient biological functions.
Intelligent Bio-manufacturing
Beyond process engineering strategies, we harness feedback genetic circuits and evolution to control cellular heterogeneity and address the scalability challenge for better economics. Quantitative perspectives and mathematical models are deployed to maximize the output of the engineered strain with reduced genetic instability and improved titer, yield and productivity.
Genetically Encoded Biosensors
We harness DNA, RNA and protein interactions to engineer portable, sensitive, specific and inexpensive biosensors with environmental applications and biomedical diagnostics. Upon responding to environmental signals, biosensors are also invaluable tools to engineer self-adapting biological function and improve metabolic pathway and genetic circuit performance.