Biotechnology can produce a vast number of valuable products from renewable sources. One barrier to making these products economically is our inability to easily redirect cellular metabolism to maximize production. New technologies to significantly improve our ability to control engineered microorganisms, using light and biological sensors, will be developed. This strategy will enable feed-back controls, in which light signals used to fine-tune enzyme concentrations are informed by fluorescence signals from biosensors in real time. The approach will allow the development of entirely new technologies to control, optimize, and operate fermentations, as well as improve our basic understanding of how enzyme concentrations affect product formation. The results of this project will be incorporated into several courses currently taught. Outreach activities to two organizations with which the PI has been involved previously (Hispanics Inspiring Student's Performance and Achievement, and Society for the Advancement of Chicano/Hispanics and Native Americans in Science) will promote STEM-related careers among under-represented groups and encourage their participation in related research.   The objective of this project is to develop a closed-loop control system for metabolic engineering using biosensors and optogenetics. Three components will be integrated in the same yeast strain: (i) a metabolic pathway to produce a chemical of interest; (ii) a biosensor to monitor the activity of said pathway; and (iii) optogenetic tools to control enzyme expression levels. This will allow fine-tuning of enzyme concentrations using light. These three components have been developed in separate yeast strains in the PI's lab. The first objective is to integrate all three components in a single yeast strain. Success will be demonstrated by the production of branched chain alcohols. The second objective is to adapt an existing optogenetic tool sensitive to red and infrared light to work orthogonally with the existing blue light system. This technology will open the door to new strategies to operate and optimize fermentations, such as by using periodic light pulses with feedback controls, providing unprecedented capabilities for operating, optimizing, and automating fermentations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2018-06-01
Budget End
2023-05-31
Support Year
Fiscal Year
2017
Total Cost
$524,786
Indirect Cost
Name
Princeton University
Department
Type
DUNS #
City
Princeton
State
NJ
Country
United States
Zip Code
08544