Evan OlsonView all speakers
Evan Olson is an Applied Physics PhD student in Jeff Tabor’s Bioengineering Lab at Rice University. Evan graduated from Central College in Iowa where he studied Physics, Mathematics, and Computer Science. In the Tabor lab, he has extensively characterized two bacterial light-sensing systems using the Light Tube Array (LTA), a custom apparatus which he designed and built. The LTA can generate up to 64 independently programmed light environments for cultures grown in a standard culture tube format.
This hardware solution enabled Evan to develop a standardized experimental workflow and to collect a large quantity of dynamical gene expression data. Using this data, he constructed quantitatively-predictive light-input/gene-expression-output models of both light-sensing systems. These models have enabled pre-computation of light programs which result in precise control of expression dynamics. Evan is now working to develop an optically-controllable continuous culture apparatus with fluorescence readouts which will enable long-timescale online control of light-sensing systems.
We have utilized both the red/green-sensing CcaS/CcaR and red/dark-sensing Cph8/OmpR two component systems (TCSs) to achieve precise, quantitative control of gene expression dynamics in E. coli. First, we have constructed a programmable array of light emitting diodes (LEDs) that allows calibrated dosing of different colors of light in any desired temporal pattern in up to 64 standard tubes of growing cells. We demonstrate for each TCS that the application of different activating to inactivating light ratios allows us to set a desired analog gene expression level. By shining light ratios in a time-varying sequence, we can then drive cells to move between desired analog expression levels without adjusting the growth media. Gene expression is reported by fluorescent proteins and single-cell data is acquired from each culture via flow cytometry. Our observations of cells grown in a variety of time-varying light sequences are well described by a phenomenological model whose kinetics and steady-state levels are determined by the illumination intensities. After calibrating the parameters of the model for each system with a dataset of gene expression time-courses under a variety of illumination patterns, the model has successfully predicted light control sequences that drive each TCS to generate arbitrary gene expression time-courses including linear ramps, accelerated steady-state switching, and sine waves of varying amplitude and period. Furthermore, we have under development a dual-input system which allows for the simultaneous control of both TCSs. This level of quantitative, temporal control of gene expression would be extremely difficult to achieve with traditional modes of gene regulation. Utilizing optogenetic devices, researchers can more readily adapt well-developed approaches for system identification, characterization, and control to biological systems, helping to make biology more engineerable. Thus, as it has in neurobiology, the precise perturbative nature of optogenetic tools therefore stands to contribute significantly to systems and synthetic biology.