Curated Optogenetic Publication Database

Abstract: Optogenetics is a powerful tool that uses light to control cellular behavior. Here we enhance high-throughput characterization of optogenetic experiments through the integration of the LED Illumination Tool for Optogenetic Stimulation (LITOS) with the previously published automated platform Lustro. Lustro enables efficient high-throughput screening and characterization of optogenetic systems. The initial iteration of Lustro used the optoPlate illumination device for light induction, with the robot periodically moving the plate over to a shaking device to resuspend cell cultures. Here, we designed a 3D-printed adaptor, rendering LITOS compatible with the BioShake 3000-T ELM used in Lustro. This novel setup allows for concurrent light stimulation and culture agitation, streamlining experiments. Our study demonstrates comparable growth rates between constant and intermittent shaking of Saccharomyces cerevisiae liquid cultures. While the light intensity of the LITOS is not as bright as the optoPlate used in the previous iteration of Lustro, the constant shaking increased the maturation rate of the mScarlet-I fluorescent reporter used. Only a marginal increase in temperature was observed when using the modified LITOS equipped with the 3D-printed adaptor. Our findings show that the integration of LITOS onto a plate shaker allows for constant culture shaking and illumination compatible with laboratory automation platforms, such as Lustro.

Abstract: The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive spit transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

Abstract: Optogenetics offers precise control over cellular behavior by utilizing genetically encoded light-sensitive proteins. However, optimizing these systems to achieve the desired functionality often requires multiple design-build-test cycles, which can be time-consuming and labor-intensive. To address this challenge, we have developed Lustro, a platform that combines light stimulation with laboratory automation, enabling efficient high-throughput screening and characterization of optogenetic systems. Lustro utilizes an automation workstation equipped with an illumination device, a shaking device, and a plate reader. By employing a robotic arm, Lustro automates the movement of a microwell plate between these devices, allowing for the stimulation of optogenetic strains and the measurement of their response. This protocol provides a step-by-step guide on using Lustro to characterize optogenetic systems for gene expression control in the budding yeast Saccharomyces cerevisiae. The protocol covers the setup of Lustro's components, including the integration of the illumination device with the automation workstation. It also provides detailed instructions for programming the illumination device, plate reader, and robot, ensuring smooth operation and data acquisition throughout the experimental process.

Abstract: Optogenetic systems use genetically encoded light-sensitive proteins to control cellular processes. This provides the potential to orthogonally control cells with light; however, these systems require many design-build-test cycles to achieve a functional design and multiple illumination variables need to be laboriously tuned for optimal stimulation. We combine laboratory automation and a modular cloning scheme to enable high-throughput construction and characterization of optogenetic split transcription factors in Saccharomyces cerevisiae. We expand the yeast optogenetic toolkit to include variants of the cryptochromes and enhanced Magnets, incorporate these light-sensitive dimerizers into split transcription factors, and automate illumination and measurement of cultures in a 96-well microplate format for high-throughput characterization. We use this approach to rationally design and test an optimized enhanced Magnet transcription factor with improved light-sensitive gene expression. This approach is generalizable to the high-throughput characterization of optogenetic systems across a range of biological systems and applications.