High-Throughput Optogenetics Experiments in Yeast Using the Automated Platform Lustro

Harmer, Zachary P; McClean, Megan N.

doi:10.3791/65686

Cited by 3 publications

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“…Automated optogenetic experiments were conducted as previously described , using a Tecan Fluent Automation Workstation equipped with a Robotic Gripper Arm (RGA) and integrated with an optoPlate, a BioShake 3000-T elm heater shaker designed for well plates, and a Tecan Spark plate reader. The optoPlate was assembled and calibrated in accordance with previously established procedures.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, we present a strategy for taking advantage of the native differences in response kinetics between protein photoswitches by using a previously described automated high-throughput optogenetic platform, Lustro, , to identify light induction programs that allow for dynamic multiplexed control over optogenetic systems in Saccharomyces cerevisiae . We use the high-throughput measurement capabilities of Lustro to characterize a set of 13 blue light-responsive optogenetic split transcription factors (TFs).…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

Harmer,

Thompson,

Cole

et al. 2024

ACS Synth. Biol.

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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 highthroughput 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 split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the highthroughput 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.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

Harmer,

Thompson,

Cole

et al. 2024

ACS Synth. Biol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Automated optogenetic experiments were conducted as previously described 7,19 using a Tecan Fluent Automation Workstation equipped with a Robotic Gripper Arm (RGA) and integrated with an optoPlate 45 , a BioShake 3000-T elm heater shaker designed for well plates, and a Tecan Spark plate reader. The optoPlate was assembled and calibrated in accordance with previously established procedures.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, we present a strategy for taking advantage of the native differences in response kinetics between protein photoswitches by using a previously described automated high-throughput optogenetic platform, Lustro 7,19 , to identify light induction programs that allow for dynamic multiplexed control over optogenetic systems. We use the high-throughput measurement capabilities of Lustro to characterize a set of 13 blue light-responsive optogenetic split transcription factors (TFs).…”

Section: Graphical Abstractmentioning

confidence: 99%

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

Harmer,

Thompson,

Cole

et al. 2023

Preprint

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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.Graphical abstract

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The Yeast Optogenetic Toolkit (yOTK) for Spatiotemporal Control of Gene Expression in Budding Yeast

Harmer,

McClean

2024

Methods in Molecular Biology

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High-Throughput Optogenetics Experiments in Yeast Using the Automated Platform Lustro

Cited by 3 publications

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Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The Yeast Optogenetic Toolkit (yOTK) for Spatiotemporal Control of Gene Expression in Budding Yeast

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