Computer Control of Cell Populations

The limited toolset for light control in bacteria motivated us to develop a light-inducible transcription system that is independent from cellular regulation through the use of an orthogonal RNA polymerase. We engineered blue light-responsive T7 RNA polymerases (Opto-T7RNAPs) that show properties such as low leakiness of gene expression in the dark state, high expression strength when induced with blue light with an inducible range of more than 300-fold, while returning to inactive state within mintues in the dark. Our approach expands the applicability of using light as an inducer for gene expression independent from cellular regulation and allows for a more reliable dynamic control of synthetic and natural gene networks.

To meet the speed and reversibility requirements of control applications, we employed a photosensitive transcription factor consisting of a nuclear localization signal, the VP16 transactivation domain, and the bacterially derived LOV-domain protein EL222 to build a blue light transcriptional activation system. Light timulation induces structural changes in EL222 in seconds, leading to transcriptional activation, while deactivating within 1 min in the dark. This system is at the heart of multiple optogenetic applications in yeast, in our lab and other labs.

Dynamic control of gene expression can have far-reaching implications for biotechnological applications and biological discovery. Thanks to the advantages of light, optogenetics has emerged as an ideal technology for this task. We deveoped a novel fully automatic experimental platform for the robust and precise long-term optogenetic regulation of protein production in liquid Escherichia coli cultures. Using a computer-controlled light-responsive system we accurately tracked prescribed dynamic green fluorescent protein expression profiles through the application of feedback control, and showed that the system adapts to global perturbations such as nutrient and temperature changes. We demonstrated the efficacy and potential utility of our approach by placing a key metabolic enzyme under optogenetic control, thus enabling dynamic regulation of the culture growth rate with potential applications in bacterial physiology studies and biotechnology.

Working with collaborators from the Lygeros and El-Samad groups, we showed that difficulties in regulating cellular behavior with synthetic biological circuits may be circumvented using in silico feedback control. By tracking a circuit's output in Saccharomyces cerevisiae in real time, we precisely controled its behavior using an in silico feedback algorithm to compute regulatory inputs implemented through a genetically encoded light-responsive module. This was the first time a computer was interfaced with living cells to control gene expression.  

We have designed and built new bioreactors outfitted with optogenetic actuators and various sensors. With this platform, we are applying cybergenetic population control for enhacing product yield in yeast and E. coli at larger scales.