This work was supported by National Institutes of Health grant R35GM128873 and National Science Foundation grant 2045493 (awarded to M.N.M.). Megan Nicole McClean, Ph.D. holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund. Z.P.H. was supported by an NHGRI training grant to the Genomic Sciences Training Program 5T32HG002760. We acknowledge fruitful discussions with McClean lab members, and in particular, we are grateful to Kieran Sweeney for providing comments on the manuscript.

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 &#176;C to 30 &#176;C and can be cultivated in various standard yeast media.
1. Setting up the automation workstation
<ol>
	<li>Equip the automated workstation with a Robotic Gripper Arm (RGA, see Table of Materials) capable of moving microwell plates (Figure 1).</li>
	<li>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.</li>
	<li>Position a microplate reader adjacent to the automated workstation (Figure 1(2)), ensuring RGA accessibility.</li>
	<li>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).</li>
</ol>
2. Preparation of the illumination device
<ol>
	<li>Construct and calibrate the optoPlate (or alternative illumination device) following established methods8,10,11.</li>
	<li>Utilize an adaptor on the illumination device to enable RGA access.</li>
	<li>Program the optoPlate using a spreadsheet input10 or a graphical interface12. Follow step 3 to execute the light stimulation programs.</li>
</ol>
3. Designing a light stimulation program
<ol>
	<li>Determine the desired light conditions for the experiment.</li>
	<li>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.</li>
	<li>Include dark conditions for each strain to enable proper background measurements.</li>
	<li>For initial characterization experiments to assess transformant functionality, use a high light intensity. 
	&#8203;NOTE: The light intensity should be optimized for more sensitive experiments, as excessive light can be phototoxic to yeast13.</li>
</ol>
4. Preparation of the microplate reader
<ol>
	<li>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.</li>
	<li>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.</li>
	<li>Refer to a fluorescent protein database (for example, fpbase.org) to obtain approximate absorption and emission spectra for the target fluorescent protein15.</li>
	<li>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&#160;that yields the highest signal-to-noise ratio.</li>
	<li>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.</li>
	<li>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. 
	&#8203;NOTE: This optical gain should be manually set consistently across experiments involving the same strain to ensure consistency of the results.</li>
	<li>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. 
	&#8203;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.</li>
	<li>Set the measurement script to maintain an internal incubation temperature of 30 &#176;C during measurements.</li>
	<li>Configure the measurement script to export the data into a spreadsheet or ASCII files, according to preference.</li>
</ol>
5. Programming the robot
<ol>
	<li>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.</li>
	<li>Disable any internal illumination sources to prevent background activation of optogenetic systems.</li>
	<li>Set the heater shaker to maintain a temperature of 30 &#176;C. When the plate is not on the heater shaker, it will be at ambient temperature (22 &#176;C).</li>
	<li>Utilize loops, a timer, and a loop counting variable to repeat the steps of inducing and measuring the cells at regular intervals.</li>
	<li>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.</li>
	<li>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&#160;if the microplate reader carrier definition is set to not allow lids.</li>
	<li>Execute the microplate reader measurement script as described in step 4.</li>
	<li>Replace the lid on the sample plate and move the plate to the illumination device using the robot arm.</li>
	<li>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).</li>
	<li>Troubleshoot potential errors and ensure the proper functioning of the carrier and labware definitions, as well as the RGA&#39;s ability to accurately pick up and place the plate by running an empty plate through the script loop multiple times.</li>
	<li>Configure user alerts to notify the user of any instrument state changes or errors that may occur during the execution of the protocol.</li>
</ol>
6. Setting up the sample plate
<ol>
	<li>Grow yeast strains on rich media plates, such as YPD agar17 (see Table of Materials). Include a nonfluorescent (negative) control.</li>
	<li>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 &#176;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).</li>
	<li>Measure the optical density of the overnight cultures by diluting 200 &#181;L of each culture into 1 mL of SC media and recording the optical density at 600 nm (OD600) using a spectrophotometer or microplate reader.</li>
	<li>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.</li>
	<li>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.</li>
	<li>Incubate the plate at 30 &#176;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.</li>
</ol>
7. Performing the experiment
<ol>
	<li>Place the sample plate onto the heater shaker and initiate the automation script as outlined in step 5.</li>
	<li>Commence the light stimulation program as described in step 3 once the initial measurement on the plate reader has been recorded.</li>
	<li>If the automation workstation is not in a dark room, cover it with a blackout curtain to avoid background illumination.</li>
</ol>
8. Data analysis
<ol>
	<li>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.</li>
	<li>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.</li>
	<li>Read the data from the exported experiment spreadsheet into another array.</li>
	<li>Generate plots of the optical density values and fluorescence values for each strain and condition over time, as illustrated in Figure 4.</li>
	<li>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.</li>
</ol>

Yeast Optogenetic Response Analysis Using the Lustro Automation Technique

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The authors have nothing to disclose.

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&#39;s utility for screening different optogenetic constructs integrated into the yeast S. cerevisiae and comparing light induction program...

Optogenetics is a powerful technique that utilizes light-sensitive proteins to control the behavior of cells with high precision1,2,3. However, prototyping optogenetic constructs and identifying optimal illumination conditions can be time-consuming, making it difficult to optimize optogenetic systems4,5. 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.

<table><tbody><tr><td>96-well glass bottom plate with&amp;nbsp; #1.5 cover glass</td><td>Cellvis</td><td>P96-1.5H-N</td><td></td></tr><tr><td>BioShake 3000-T elm (heater shaker)</td><td>QINSTRUMENTS</td><td></td><td></td></tr><tr><td>Fluent Automation Workstation</td><td>Tecan</td><td></td><td></td></tr><tr><td>LITOS (alternative illumination device)</td><td>Hohener, et al. Scientific Reports. 2022</td><td></td><td></td></tr><tr><td>optoPlate-96 (illumination device)</td><td>Bugaj, et al. Nature Protocols. 2019</td><td></td><td></td></tr><tr><td>Robotic Gripper Arm</td><td>Tecan</td><td></td><td></td></tr><tr><td>Spark (plate reader)</td><td>Tecan</td><td></td><td></td></tr><tr><td>Synthetic Complete media</td><td>SigmaAldrich</td><td>Y1250</td><td></td></tr><tr><td>Tecan Connect (user alert app)</td><td>Tecan</td><td></td><td></td></tr><tr><td>yMM1734 (BY4741 Mat&amp;alpha; ura3&amp;Delta;0::5&#039; Ura3 homology, pRPL18B-Gal4DBD-eMagA-tENO1, pRPL18B-eMagB-Gal4AD-tENO1, pGAL1-mScarlet-I-tENO1, Ura3, Ura 3&#039; homology&amp;nbsp; his3D1 leu2D0 lys2D0 gal80::KANMX gal4::spHIS5)</td><td>Harmer, et al. ACS Syn Bio. 2023</td><td></td><td></td></tr><tr><td>yMM1763 (BY4741 Mat&amp;alpha; ura3&amp;Delta;0::5&#039; Ura3 homology, pRPL18B-Gal4DBD-CRY2(535)-tENO1, pRPL18B-Gal4AD-CIB1-tENO1, pGAL1-mScarlet-I-tENO1, Ura3, Ura 3&#039; homology&amp;nbsp; his3D1 leu2D0 lys2D0 gal80::KANMX gal4::spHIS5)</td><td>Harmer, et al. ACS Syn Bio. 2023</td><td></td><td></td></tr><tr><td>yMM1765 (BY4741 Mat&amp;alpha; ura3&amp;Delta;0::5&#039; Ura3 homology, pRPL18B-Gal4DBD-eMagA-tENO1, pRPL18B-eMagBM-Gal4AD-tENO1, pGAL1-mScarlet-I-tENO1, Ura3, Ura 3&#039; homology&amp;nbsp; his3D1 leu2D0 lys2D0 gal80::KANMX gal4::spHIS5)</td><td>Harmer, et al. ACS Syn Bio. 2023</td><td></td><td></td></tr><tr><td>YPD Agar</td><td>SigmaAldrich</td><td>Y1500</td><td></td></tr></tbody></table>

high-throughput optogenetics experiments in yeast using the automated platform lustro

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&#160;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&#39;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.

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 correspon...

Watch this Scientific Journal Video about Advancing Optogenetics Research Using Lustro at JoVE.com

Author Spotlight: Advancing Optogenetics Research Using Lustro 

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

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

Optogenetics offers precise control over cellular behavior by utilizing genetically encoded light-sensitive proteins. However, optimizing these systems to ...

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JoVE Journal

Bioengineering

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

Video: Author Spotlight: Advancing Optogenetics Research Using Lustro 

A Rapid Technique for the Visualization of Live Immobilized Yeast Cells

We present here a simple, rapid, and extremely flexible technique for the immobilization and visualization of growing yeast cells by epifluorescence microscopy. The technique is equally suited for visualization of static yeast populations, or time courses experiments up to ten hours in length. My microscopy investigates epigenetic inheritance at the silent mating loci in S. cerevisiae. There are two silent mating loci, HML and HMR, which are normally not expressed as they are packaged in heterochromatin. In the sir1 mutant background silencing is weakened such that each locus can either be in the expressed or silenced epigenetic state, so in the population as a whole there is a mix of cells of different epigenetic states for both HML and HMR. My microscopy demonstrated that there is no relationship between the epigenetic state of HML and HMR in an individual cell. sir1 cells stochastically switch epigenetic states, establishing silencing at a previously expressed locus or expressing a previously silenced locus. My time course microscopy tracked individual sir1 cells and their offspring to score the frequency of each of the four possible epigenetic switches, and thus the stability of each of the epigenetic states in sir1 cells. See also  Xu et al., Mol. Cell 2006.

A rapid technique for the visualization of growing immobilized yeast cells, here applied to fluorescent reporters at the silent mating loci HML and HMR

We present here a simple, rapid, and extremely flexible technique for the immobilization and visualization of growing yeast cells by epifluorescence ...

Biology

Mating-based Overexpression Library Screening in Yeast

Budding yeast has been widely used as a model in studying proteins associated with human diseases. Genome-wide genetic screening is a powerful tool commonly used in yeast studies. The expression of a number of neurodegenerative disease-associated proteins in yeast causes cytotoxicity and aggregate formation, recapitulating findings seen in patients with these disorders. Here, we describe a method for screening a yeast model of the Amyotrophic Lateral Sclerosis-associated protein FUS for modifiers of its toxicity. Instead of using transformation, this new screening platform relies on the mating of yeast to introduce an arrayed library of plasmids into the yeast model. The mating method has two clear advantages: first, it is highly efficient; second, the pre-transformed arrayed library of plasmids can be stored for long-term as a glycerol stock, and quickly applied to other screens without the labor-intensive step of transformation into the yeast model each time. We demonstrate how this method can successfully be used to screen for genes that modify the toxicity of FUS.

This article presents a mating-based method to facilitate overexpression screening in budding yeast using an arrayed plasmid library.

Budding yeast has been widely used as a model in studying proteins associated with human diseases. Genome-wide genetic screening is a powerful tool ...

Genetics

Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular processes. There is a need for culturing and measuring systems that incorporate programmed illumination and stimulation of optogenetic systems. We present a protocol for building and using a continuous culturing apparatus to illuminate microbial cells with programmed doses of light, and automatically acquire and analyze images of cells in the effluent. The operation of this apparatus as a chemostat allows the growth rate and the cellular environment to be tightly controlled. The effluent of the continuous cell culture is regularly sampled and the cells are imaged by multi-channel microscopy. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses in the fluorescence intensity and cellular morphology of cells sampled from the culture effluent are measured over multiple days without user input. We demonstrate the utility of this culturing apparatus by dynamically inducing protein production in a strain of Saccharomyces cerevisiae engineered with an optogenetic system that activates transcription.

We designed a continuous culturing apparatus for use with optogenetic systems to illuminate cultures of microbes and regularly image cells in the effluent with an inverted microscope. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses to illumination can be measured over several days.

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular ...

High-throughput Yeast Plasmid Overexpression Screen

The budding yeast, Saccharomyces cerevisiae, is a powerful model system for defining fundamental mechanisms of many important cellular processes, including those with direct relevance to human disease. Because of its short generation time and well-characterized genome, a major experimental advantage of the yeast model system is the ability to perform genetic screens to identify genes and pathways that are involved in a given process. Over the last thirty years such genetic screens have been used to elucidate the cell cycle, secretory pathway, and many more highly conserved aspects of eukaryotic cell biology 1-5. In the last few years, several genomewide libraries of yeast strains and plasmids have been generated 6-10. These collections now allow for the systematic interrogation of gene function using gain- and loss-of-function approaches 11-16. Here we provide a detailed protocol for the use of a high-throughput yeast transformation protocol with a liquid handling robot to perform a plasmid overexpression screen, using an arrayed library of 5,500 yeast plasmids. We have been using these screens to identify genetic modifiers of toxicity associated with the accumulation of aggregation-prone human neurodegenerative disease proteins. The methods presented here are readily adaptable to the study of other cellular phenotypes of interest.

Here we describe a plasmid overexpression screen in Saccharomyces cerevisiae, using an arrayed plasmid library and a high-throughput yeast transformation protocol with a liquid handling robot.

The budding yeast, Saccharomyces cerevisiae, is a powerful model system for defining fundamental mechanisms of many important cellular processes, ...

Quantitative Live Cell Fluorescence-microscopy Analysis of Fission Yeast

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using fluorochromes like Green Fluorescent Protein (GFP) directly attached to the protein of interest has become increasingly popular 1. Using GFP and similar fluorochromes the subcellular localisations and movements of proteins can be detected in a fluorescent microscope. Moreover, also the subnuclear localisation of a certain region of a chromosome can be studied using this technique. GFP is fused to the Lac Repressor protein (LacR) and ectopically expressed in the cell where tandem repeats of the lacO sequence has been inserted into the region of interest on the chromosome2. The LacR-GFP will bind to the lacO repeats and that area of the genome will be visible as a green dot in the fluorescence microscope. Yeast is especially suited for this type of manipulation since homologous recombination is very efficient and thereby enables targeted integration of the lacO repeats and engineered fusion proteins with GFP 3. Here we describe a quantitative method for live cell analysis of fission yeast. Additional protocols for live cell analysis of fission yeast can be found, for example on how to make a movie of the meiotic chromosomal behaviour 4. In this particular experiment we focus on subnuclear organisation and how it is affected during gene induction. We have labelled a gene cluster, named Chr1, by the introduction of lacO binding sites in the vicinity of the genes. The gene cluster is enriched for genes that are induced early during nitrogen starvation of fission yeast 5. In the strain the nuclear membrane (NM) is labelled by the attachment of mCherry to the NM protein Cut11 giving rise to a red fluorescent signal. The Spindle Pole body (SPB) compound Sid4 is fused to Red Fluorescent Protein (Sid4-mRFP) 6. In vegetatively growing yeast cells the centromeres are always attached to the SPB that is embedded in the NM 7. The SPB is identified as a large round structure in the NM. By imaging before and 20 minutes after depletion of the nitrogen source we can determine the distance between the gene cluster (GFP) and the NM/SPB. The mean or median distances before and after nitrogen depletion are compared and we can thus quantify whether or not there is a shift in subcellular localisation of the gene cluster after nitrogen depletion.

The fission yeast, Schizosaccharomyces pombe, is a good model system to study basic cellular processes. Here we describe a method to perform quantitative live cell analysis of fission yeast. In this particular experiment we focus on organisation of the genome within the cell nucleus, but the method can also be used to study cytosolic factors.

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using ...

High Throughput Yeast Strain Phenotyping with Droplet-Based RNA Sequencing

The powerful tools available to edit yeast genomes have made this microbe a valuable platform for engineering. While it is now possible to construct libraries of millions of genetically distinct strains, screening for a desired phenotype remains a significant obstacle. With existing screening techniques, there is a tradeoff between information output and throughput, with high-throughput screening typically being performed on one product of interest. Therefore, we present an approach to accelerate strain screening by adapting single cell RNA sequencing to isogenic picoliter colonies of genetically engineered yeast strains. To address the unique challenges of performing RNA sequencing on yeast cells, we culture isogenic yeast colonies within hydrogels and spheroplast prior to performing RNA sequencing. The RNA sequencing data can be used to infer yeast phenotypes and sort out engineered pathways. The scalability of our method addresses a critical obstruction in microbial engineering.

A bottleneck in the &#8216;design-build-test&#8217; cycle of microbial engineering is the speed at which we can perform functional screens of strains. We describe a high-throughput method for strain screening applied to hundreds to thousands of yeast cells per experiment that utilizes droplet-based RNA sequencing.

The powerful tools available to edit yeast genomes have made this microbe a valuable platform for engineering. While it is now possible to construct ...

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells

Reliable gene expression control in mammalian cells requires tools with high fold change, low noise, and determined input-to-output transfer functions, regardless of the method used. Toward this goal, optogenetic gene expression systems have gained much attention over the past decade for spatiotemporal control of protein levels in mammalian cells. However, most existing circuits controlling light-induced gene expression vary in architecture, are expressed from plasmids, and utilize variable optogenetic equipment, creating a need to explore characterization and standardization of optogenetic components in stable cell lines. Here, the study provides an experimental pipeline of reliable gene circuit construction, integration, and characterization for controlling light-inducible gene expression in mammalian cells, using a negative feedback optogenetic circuit as a case example. The protocols also illustrate how standardizing optogenetic equipment and light regimes can reliably reveal gene circuit features such as gene expression noise and protein expression magnitude. Lastly, this paper may be of use for laboratories unfamiliar with optogenetics who wish to adopt such technology. The pipeline described here should apply for other optogenetic circuits in mammalian cells, allowing for more reliable, detailed characterization and control of gene expression at the transcriptional, proteomic, and ultimately phenotypic level in mammalian cells.

Reliably controlling light-responsive mammalian cells requires the standardization of optogenetic methods. Toward this goal, this study outlines a pipeline of gene circuit construction, cell engineering, optogenetic equipment operation, and verification assays to standardize the study of light-induced gene expression using a negative-feedback optogenetic gene circuit as a case study.

Reliable gene expression control in mammalian cells requires tools with high fold change, low noise, and determined input-to-output transfer functions, ...

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Microbial cell factories offer a sustainable alternative for producing chemicals and recombinant proteins from renewable feedstocks. However, overburdening a microorganism with genetic modifications can reduce host fitness and productivity. This problem can be overcome by using dynamic control: inducible expression of enzymes and pathways, typically using chemical- or nutrient-based additives, to balance cellular growth and production. Optogenetics offers a non-invasive, highly tunable, and reversible method of dynamically regulating gene expression. Here, we describe how to set up light-controlled fermentations of engineered Escherichia coli and Saccharomyces cerevisiae for the production of chemicals or recombinant proteins. We discuss how to apply light at selected times and dosages to decouple microbial growth and production for improved fermentation control and productivity, as well as the key optimization considerations for best results. Additionally, we describe how to implement light controls for lab-scale bioreactor experiments. These protocols facilitate the adoption of optogenetic controls in engineered microorganisms for improved fermentation performance.

Optogenetic control of microbial metabolism offers flexible dynamic control over fermentation processes. The protocol here shows how to set up blue light-regulated fermentations for chemical and protein production at different volumetric scales.

Microbial cell factories offer a sustainable alternative for producing chemicals and recombinant proteins from renewable feedstocks. However, ...

Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS

Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies depicting the temporal dependence of gene expression provide insight into the dynamics of its regulation; however, there are many technical challenges to obtaining and analyzing fluorescence movies of single cells. We describe here a simple protocol using a commercially available microfluidic culture device to generate such data, and a MATLAB-based, graphical user interface (GUI) -based software package to quantify the fluorescence images. The software segments and tracks cells, enables the user to visually curate errors in the data, and automatically assigns lineage and division times. The GUI further analyzes the time series to produce whole cell traces as well as their first and second time derivatives. While the software was designed for S. cerevisiae, its modularity and versatility should allow it to serve as a platform for studying other cell types with few modifications.

We present a simple protocol to obtain fluorescence microscopy movies of growing yeast cells, and a GUI-based software package to extract single-cell time series data. The analysis includes automated lineage and division time assignment integrated with visual inspection and manual curation of tracked data.

Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies ...

Yeast Luminometric and Xenopus Oocyte Electrophysiological Examinations of the Molecular Mechanosensitivity of TRPV4

TRPV4 (Transient Receptor Potentials, vanilloid family, type 4) is widely expressed in vertebrate tissues and is activated by several stimuli, including by mechanical forces. Certain TRPV4 mutations cause complex hereditary bone or neuronal pathologies in human. Wild-type or mutant TRPV4 transgenes are commonly expressed in cultured mammalian cells and examined by Fura-2 fluorometry and by electrodes. In terms of the mechanism of mechanosensitivity and the molecular bases of the diseases, the current literature is confusing and controversial. To complement existing methods, we describe two additional methods to examine the molecular properties of TRPV4. (1) Rat TRPV4 and an aequorin transgene are transformed into budding yeast. A hypo-osmtic shock of the transformant population yields a luminometric signal due to the combination of aequorin with Ca2+, released through the TRPV4 channel. Here TRPV4 is isolated from its usual mammalian partner proteins and reveals its own mechanosensitivity. (2) cRNA of TRPV4 is injected into Xenopus oocytes. After a suitable period of incubation, the macroscopic TRPV4 current is examined with a two-electrode voltage clamp. The current rise upon removal of inert osmoticum from the oocyte bath is indicative of mechanosensitivity. The microAmpere (10-6 to 10-4 A) currents from oocytes are much larger than the subnano- to nanoAmpere (10-10 to 10-9 A) currents from cultured cells, yielding clearer quantifications and more confident assessments. Microscopic currents reflecting the activities of individual channel proteins can also be directly registered under a patch clamp, in on-cell or excised mode. The same oocyte provides multiple patch samples, allowing better data replication. Suctions applied to the patches can activate TRPV4 to directly assess mechanosensitivity. These methods should also be useful in the study of other types of TRP channels.

Yeast Luminometric and Xenopus Oocyte Electrophysiological Examinations of the Molecular Mechanosensitivity of TRPV4

To complement commonly used methods to study TRPV4&#8217;s, two methods are described: Its mechanosensitivity can be studied by Ca2+-aequorin luminometry in transgenic yeast upon hypo-osmotic challenge. It can also be examined in TRPV4-RNA injected Xenopus oocytes by whole-cell two-electrode voltage clamp or patch clamp in on-cell or excised mode.

TRPV4 (Transient Receptor Potentials, vanilloid family, type 4) is widely expressed in vertebrate tissues and is activated by several stimuli, including ...

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

Summary

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Chapters in this video

A Rapid Technique for the Visualization of Live Immobilized Yeast Cells

Mating-based Overexpression Library Screening in Yeast

Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications

High-throughput Yeast Plasmid Overexpression Screen

Quantitative Live Cell Fluorescence-microscopy Analysis of Fission Yeast

High Throughput Yeast Strain Phenotyping with Droplet-Based RNA Sequencing

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS

Yeast Luminometric and Xenopus Oocyte Electrophysiological Examinations of the Molecular Mechanosensitivity of TRPV4