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Summary

This protocol outlines the steps for utilizing the automated platform Lustro to perform high-throughput characterization of optogenetic systems in yeast.

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.

Introduction

Optogenetics is a powerful technique that utilizes light-sensitive proteins to control the behavior of cells with high precision^1,2,3. However, prototyping optogenetic constructs and identifying optimal illumination conditions can be time-consuming, making it difficult to optimize optogenetic systems^4,5. High-throughput methods to rapidly screen and characterize the activity of optogenetic systems can accelerate the design-build-test cycle for prototyping constructs and exploring their function.

The Lustro platform was developed as a laboratory automation technique designed for high-throughput screening and characterization of optogenetic systems. It integrates a microplate reader, illumination device, and shaking device with an automation workstation⁶. Lustro combines automated culturing and light stimulation of cells in microwell plates (Figure 1 and Supplementary Figure 1), enabling the rapid screening and comparison of different optogenetic systems. The Lustro platform is highly adaptable and can be generalized to work with other laboratory automation robots, illumination devices, plate readers, cell types, and optogenetic systems, including those responsive to different wavelengths of light.

This protocol demonstrates the setup and use of Lustro for characterizing an optogenetic system. Optogenetic control of split transcription factors in yeast is used as an example system to illustrate the function and utility of the platform by probing the relationship between light inputs and the expression of a fluorescent reporter gene, mScarlet-I⁷. By following this protocol, researchers can streamline the optimization of optogenetic systems and accelerate the discovery of new strategies for the dynamic control of biological systems.

Protocol

The yeast strains utilized in this study are documented in the Table of Materials. These strains exhibit robust growth within the temperature range of 22 °C to 30 °C and can be cultivated in various standard yeast media.

1. Setting up the automation workstation

1. Equip the automated workstation with a Robotic Gripper Arm (RGA, see Table of Materials) capable of moving microwell plates (Figure 1).
2. Install a microplate heater shaker (see Table of Materials) into the automated workstation (Figure 1(1)) with an automatic plate locking mechanism that provides RGA access.
3. Position a microplate reader adjacent to the automated workstation (Figure 1(2)), ensuring RGA accessibility.
4. Incorporate a microplate illumination device (Figure 1(3)) that allows convenient RGA access. Examples include the optoPlate⁸ (as used in this study) or LITOS⁹ (see Table of Materials).

2. Preparation of the illumination device

1. Construct and calibrate the optoPlate (or alternative illumination device) following established methods^8,10,11.
2. Utilize an adaptor on the illumination device to enable RGA access.
3. Program the optoPlate using a spreadsheet input¹⁰ or a graphical interface¹². Follow step 3 to execute the light stimulation programs.

3. Designing a light stimulation program

1. Determine the desired light conditions for the experiment.
2. Enter the desired light conditions, including light intensity, light start time, pulse length, pulse number, and interpulse duration, into a spreadsheet.
   NOTE: Flash this information onto the optoPlate using the instructions provided in the GitHub repository: github.com/mccleanlab/Optoplate-96. Remember that the sample plate will not be illuminated while in the microplate reader or on the heater shaker. The duration and frequency of these events may require optimization based on specific experimental requirements.
3. Include dark conditions for each strain to enable proper background measurements.
4. For initial characterization experiments to assess transformant functionality, use a high light intensity.
   ​NOTE: The light intensity should be optimized for more sensitive experiments, as excessive light can be phototoxic to yeast¹³.

4. Preparation of the microplate reader

1. Configure the microplate reader to measure the desired quantity of interest before conducting experiments.
   NOTE: In this example, the microplate reader was configured to measure fluorescence from a reporter expressed by the strain of interest. Other outputs, such as luminescence or optical density, can be used depending on the experimental requirements.
2. Cultivate the strain of interest (along with a nonfluorescent control) in synthetic complete (SC) media¹⁴ (or another low fluorescence media) (see Table of Materials) to the highest cell density to be measured. Transfer the cultures into a glass-bottom black-walled microwell plate (see Table of Materials) and measure them to determine the optimal microplate reader settings.
   NOTE: Ensure accurate readings by correctly entering the plate dimensions and measuring the plate from below.
3. Refer to a fluorescent protein database (for example, fpbase.org) to obtain approximate absorption and emission spectra for the target fluorescent protein¹⁵.
4. Determine the z-value (distance between the plate and reader) by performing a z-scan on wells containing the fluorescent and nonfluorescent strains. Select the z-value that yields the highest signal-to-noise ratio.
5. Optimize the absorption and emission spectra by conducting absorption and emission scans on the fluorescent and nonfluorescent strains to determine the optimal signal-to-noise ratio.
6. Measure the fluorescent strain with the gain set to the optimal level, determining the highest optical gain that can be used without resulting in an overflow measurement error.
   ​NOTE: This optical gain should be manually set consistently across experiments involving the same strain to ensure consistency of the results.
7. Prepare a measurement script (refer to Figure 2) in the microplate reader software. This script configures the instrument to measure the optical density of the cultures and the fluorescence spectra of any fluorescent proteins to be measured.
   ​NOTE: Measure the optical density of strains at 600 nm unless they express red fluorescent proteins. For strains expressing red fluorescent proteins, measure the optical density at 700 nm to avoid bias¹⁶.
8. Set the measurement script to maintain an internal incubation temperature of 30 °C during measurements.
9. Configure the measurement script to export the data into a spreadsheet or ASCII files, according to preference.

5. Programming the robot

1. Configure the worktable definition in the automated workstation software based on the physical layout of carriers (e.g., heater shakers, nest platforms, illumination devices) and the labware (i.e., the 96-well plate) (see Table of Materials). Create a script in the automation workstation software to execute light induction and measurements (Figure 3), following the below steps.
2. Disable any internal illumination sources to prevent background activation of optogenetic systems.
3. Set the heater shaker to maintain a temperature of 30 °C. When the plate is not on the heater shaker, it will be at ambient temperature (22 °C).
4. Utilize loops, a timer, and a loop counting variable to repeat the steps of inducing and measuring the cells at regular intervals.
5. Before recording measurements, shake the sample plate to ensure proper suspension of all cells. A 60 s shake at 1,000 rpm with a 2 mm orbital is generally sufficient to resuspend S288C S. cerevisiae cells and avoid measurement bias.
6. Move the sample plate to the microplate reader using the robot arm and remove the lid (if applicable) to prevent bias in optical density measurement. The control software will automatically remove and replace the lid to the designated position if the microplate reader carrier definition is set to not allow lids.
7. Execute the microplate reader measurement script as described in step 4.
8. Replace the lid on the sample plate and move the plate to the illumination device using the robot arm.
9. Set the script to wait until the timer reaches the specified time interval (e.g., 30 min multiplied by the loop counting variable) and then repeat the entire loop for the desired number of iterations (e.g., 48 times for a 24 h experiment).
10. Troubleshoot potential errors and ensure the proper functioning of the carrier and labware definitions, as well as the RGA's ability to accurately pick up and place the plate by running an empty plate through the script loop multiple times.
11. Configure user alerts to notify the user of any instrument state changes or errors that may occur during the execution of the protocol.

6. Setting up the sample plate

1. Grow yeast strains on rich media plates, such as YPD agar¹⁷ (see Table of Materials). Include a nonfluorescent (negative) control.
2. Select colonies from the plates and inoculate them into 3 mL of SC media¹⁴ (or another low fluorescence media, such as LFM¹⁸) in glass culture tubes. Incubate the cultures overnight at 30 °C on a roller drum while keeping them in the dark or under non-responsive light conditions (e.g., red light for blue light-responsive systems).
3. Measure the optical density of the overnight cultures by diluting 200 µL of each culture into 1 mL of SC media and recording the optical density at 600 nm (OD600) using a spectrophotometer or microplate reader.
4. Dilute each overnight culture to an OD₆₀₀ of 0.1 in glass culture tubes. For higher throughput strain testing, perform automated dilutions in microwell plates.
5. Pipette the diluted cultures into the 96-well plate. Include triplicate wells for each condition (i.e., three identical wells with the same strain and light condition) to account for technical variation. Include wells with blank media and nonfluorescent cells as negative controls to measure background fluorescence and optical density.
6. Incubate the plate at 30 °C with shaking for 5 h before commencing the light induction experiment. Adjust the dilution amounts and incubation times as necessary to optimize for specific strains and experimental conditions.

7. Performing the experiment

1. Place the sample plate onto the heater shaker and initiate the automation script as outlined in step 5.
2. Commence the light stimulation program as described in step 3 once the initial measurement on the plate reader has been recorded.
3. If the automation workstation is not in a dark room, cover it with a blackout curtain to avoid background illumination.

8. Data analysis

1. Create a spreadsheet map for the experiment, reflecting the 8 x 12 layout of the 96-well plate. Ensure that the map includes the names of the strains being measured in one grid and descriptions of the light conditions used in another grid.
2. Utilize a Python script or another preferred programming language to analyze the exported data. Import the map spreadsheet into an array, associating the strain names and condition names with each well of the plate.
   NOTE: Sample code for analysis can be found at: https://github.com/mccleanlab/Lustro. Alternatively, one can employ an application to parse data from various plate readers¹⁹.
3. Read the data from the exported experiment spreadsheet into another array.
4. Generate plots of the optical density values and fluorescence values for each strain and condition over time, as illustrated in Figure 4.
5. Examine the optical density plots to determine the stages of exponential growth or saturation in the cultures. This information will aid in selecting appropriate timepoints for comparing fluorescence measurements between strains or conditions, as depicted in Figure 5.

Representative Results

Figure 4A shows the fluorescence values over time for an optogenetic strain expressing a fluorescent reporter controlled by a light-inducible split transcription factor. The different light conditions used in the experiment are reflected by variations in the duty cycle, which represents the percentage of time the light is on. The overall fluorescence level is observed to be proportional to the duty cycle of the light stimulation. Figure 4B displays the corresponding OD₇₀₀ values for the same experiment. The consistency of the optical density readings across different light conditions suggests that the experimental technique does not significantly affect the growth rate of the strains under varying light conditions.

By measuring fluorescence and optical density over time, a deeper understanding of how optogenetic systems respond to different light stimulation programs can be gained compared to techniques that only capture output at a single time point. This time-course data is valuable for selecting specific time points to compare different strains and conditions. Figure 5 illustrates a single time point (measured at 10 h into light induction) for two distinct optogenetic strains induced by different light stimulation programs. Both strains employ a light-inducible split transcription factor to drive the expression of a fluorescent reporter. Variations in light pulse intensity, period, and duty cycle elicit different responses in these strains.

Figure 1: Worktable layout and experimental workflow. Screenshot of a sample worktable layout, denoting the movement of the sample plate in Lustro. The plate is moved by the robotic arm from a heater shaker (1) to the microplate reader (2), and then to the illumination device (3). Photographs are provided in Supplementary Figure 1. Please click here to view a larger version of this figure.

Figure 2: Plate reader measurement script. Sample screenshot of a plate reader script setting the microplate reader to incubate at 30 °C and record fluorescence and optical density measurements. Please click here to view a larger version of this figure.

Figure 3: Automated workstation script. Sample screenshot of an automated workstation script for Lustro. The script starts a timer, ensures the interior light is turned off, sets a loop counting variable to an initial value of 0, and sets the heater shaker to incubate at 30 °C. Within each loop, the plate is locked, shaken for 1 min, moved to the plate reader, measured, then moved to the illumination device, and the robot is set to wait for the remainder of the 30 min loop interval. At the end of this time, the loop counter variable is increased by one, and the loop is repeated. Please click here to view a larger version of this figure.

Figure 4: Induction time course. Sample light induction time course data from a Gal4BD-eMagA/eMagB-Gal4AD split transcription factor strain with a pGAL1-mScarlet-I reporter (yMM1734⁶). Fluorescence of mScarlet-I⁷ is measured at 563 nm excitation and 606 nm emission with an optical gain of 130. Light intensity is 125 µW/cm² and error bars represent the standard error of triplicate samples. The vertical red dotted line shows when cultures reach saturation. (A) Fluorescence values from the strain over time. Light patterns (as indicated) were repeated for the full duration of the experiment shown. Inset shows that light pulse times are interspersed with dark interpulse times, repeated throughout the investigation. (B) Optical density (measured at 700 nm) values for the experiment shown in (A). Please click here to view a larger version of this figure.

Figure 5: Comparison of different optogenetic systems. Comparison of different light induction programs between CRY2(535)/CIB1 and eMagA/eMagBM split transcription factor strains with pGAL1-mScarlet-I reporters (yMM1763 and yMM1765⁶, respectively). Fluorescence of mScarlet-I⁷ is measured at 563 nm excitation and 606 nm emission with an optical gain of 130. The light intensity used is 125 µW/cm², except where otherwise noted. Error bars represent the standard error of triplicate samples (indicated as dots). Fluorescence values shown were recorded 10 h into induction. Please click here to view a larger version of this figure.

Supplementary Figure 1: Representative images of the devices used in Lustro. Picture of the Lustro setup and zoomed-in images of the devices used. The robotic arm moves the sample plate from the heater shaker to the plate reader and then to the illumination device in a cycle throughout the experiment. Components are numbered with a legend on the side. Please click here to download this File.

Discussion

The Lustro protocol presented here automates the culturing, illumination, and measurement processes, enabling high-throughput screening and characterization of optogenetic systems⁶. This is achieved by integrating an illumination device, microplate reader, and shaking device into an automation workstation. This protocol specifically demonstrates Lustro's utility for screening different optogenetic constructs integrated into the yeast S. cerevisiae and comparing light induction programs.

Several crucial steps emphasized in this protocol are essential for the effective utilization of Lustro. Careful design of customized light programs that align with the kinetics of the optogenetic construct under investigation is necessary. Additionally, precise calibration of the plate reader is crucial for obtaining reliable measurements. Thorough dry runs of the experiments on the robot, including necessary adjustments to ensure proper synchronization with the light programs, are critical to ensure the script runs smoothly.

The sample protocol provided here describes the comparison of a light-inducible split transcription factor driving the expression of a fluorescent reporter to a nonfluorescent control under various light stimulation conditions. Fluorescence measurements are taken from each well in the plate at 30 min intervals, preceded by 1 min of shaking on the heater shaker prior to measurement. As demonstrated in this protocol, Lustro is suitable for use with blue light-responsive optogenetic systems integrated into non-adherent cell types, including bacteria and other yeasts. However, with minor modifications, the protocol can be easily extended to different cell types, optogenetic systems, and experimental designs. Adjustments to the plate reader settings would allow measurement of outputs other than fluorescence, such as bioluminescence. For applications requiring finer temporal resolution, measurements can be taken more frequently. Incubation on the heater shaker can be repeated more often when critical for specific cell types requiring shaking and temperature control. Incorporation of gas and environmental control, such as through an incubated hotel, would enable the inclusion of mammalian cell lines. While the iteration of Lustro described here uses specific instrumentation, the Lustro platform can be readily adapted to work with other laboratory automation robots or microplate readers. Illumination devices, such as the LPA²⁰ or LITOS⁹, could substitute the optoPlate to stimulate different optogenetic systems. A future modification of the Lustro platform could involve incorporating liquid handling to facilitate automated dilutions for continuous culture applications. This would also enable Lustro to be adapted for cybergenetic feedback control, where real-time measurements inform changes in light or culture conditions to achieve or maintain a desired response^5,21,22.

High-throughput techniques are crucial for optimizing and harnessing the dynamic nature of optogenetic systems. Lustro overcomes many limitations of existing protocols. For instance, while bioreactor-based optogenetics techniques enable constant readout and culturing conditions, they suffer from low throughput^23,24,25,26. The optoPlateReader²⁷ device holds promise for real-time optogenetics experiments in microwell plates, but currently has low throughput due to the need for a high number of replicates to obtain reliable results and does not provide access to continuous culturing. Lustro, on the other hand, enables high-throughput screening of optogenetic systems to characterize their dynamic activity. Nonetheless, there are some limitations to the Lustro protocol. Intermittent shaking in Lustro causes a small growth lag for yeast cells⁶, but this could be addressed by adapting an illumination device to incorporate shaking. Another limitation of the Lustro system is that the sample plate is not incubated while on the illumination device and is maintained at ambient temperature (22 °C). Although the small volume of each sample allows for high-throughput screens, additional optimization of the illumination steps may be necessary when scaling to larger reaction volumes for bioproduction or other applications^28,29.

Overall, Lustro facilitates the rapid development and testing of optogenetic systems through high-throughput screening and precise light control. This automated approach enables efficient characterization and comparison of different optogenetic constructs under various induction conditions, leading to faster iteration and refinement of these systems. With its adaptability to different cell types, optogenetic tools, and automation setups, Lustro paves the way for advancements in the field of optogenetics, facilitating the exploration of dynamic gene expression control and expanding possibilities for studying biological networks and engineering cellular behavior.

Materials

96-well glass bottom plate with  #1.5 cover glass	Cellvis	P96-1.5H-N
BioShake 3000-T elm (heater shaker)	QINSTRUMENTS
Fluent Automation Workstation	Tecan
LITOS (alternative illumination device)	Hohener, et al. Scientific Reports. 2022
optoPlate-96 (illumination device)	Bugaj, et al. Nature Protocols. 2019
Robotic Gripper Arm	Tecan		Standard or long Z axes; regular gripper head or automatic Finger Exchange System gripper head, both with a choice of gripper fingers – eccentric, long eccentric, centric, tube; barcode reader option
Spark (plate reader)	Tecan
Synthetic Complete media	SigmaAldrich	Y1250
Tecan Connect (user alert app)	Tecan
yMM1734 (BY4741 Matα ura3Δ0::5' Ura3 homology, pRPL18B-Gal4DBD-eMagA-tENO1, pRPL18B-eMagB-Gal4AD-tENO1, pGAL1-mScarlet-I-tENO1, Ura3, Ura 3' homology  his3D1 leu2D0 lys2D0 gal80::KANMX gal4::spHIS5)	Harmer, et al. ACS Syn Bio. 2023
yMM1763 (BY4741 Matα ura3Δ0::5' Ura3 homology, pRPL18B-Gal4DBD-CRY2(535)-tENO1, pRPL18B-Gal4AD-CIB1-tENO1, pGAL1-mScarlet-I-tENO1, Ura3, Ura 3' homology  his3D1 leu2D0 lys2D0 gal80::KANMX gal4::spHIS5)	Harmer, et al. ACS Syn Bio. 2023
yMM1765 (BY4741 Matα ura3Δ0::5' Ura3 homology, pRPL18B-Gal4DBD-eMagA-tENO1, pRPL18B-eMagBM-Gal4AD-tENO1, pGAL1-mScarlet-I-tENO1, Ura3, Ura 3' homology  his3D1 leu2D0 lys2D0 gal80::KANMX gal4::spHIS5)	Harmer, et al. ACS Syn Bio. 2023
YPD Agar	SigmaAldrich	Y1500