Name: An Optimized LIVE/DEAD Assay Coupled with Flow Cytometry for Quantifying Post-Stress Survival in Yeast Cells (Video) | JoVE Journal
Uploaded: 2025-08-29T14:50:00.000+00:00
Duration: 9 min 58 s
Description: Learn a flow cytometry-based LIVE/DEAD assay to quantify post-stress survival in yeast cells using SYTO 9 and propidium iodide. This method provides quantitative assessment of live, dead, and damaged cell fractions.

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5 minutes

We would like to thank Dr. Michael Dailey and the Carver Center for Imaging for their training and support for the microscopy. We would like to thank past and current members of the Gene Regulatory Lab for invaluable feedback on the protocol. This work is supported by NIH R35GM137831 to BZH.

The details of the reagents and the equipment used in this study are listed in the Table of Materials.
1. Application of hydrogen peroxide stress
<ol>
	<li>At least a day before the experiment, innoculate&#160;an overnight culture of C. glabrata from a single colony on a freshly-streaked plate into 3 mL of Synthetic Complete (SC) media (1.7 g/L Yeast Nitrogen Base, complete amino acid mix, 2% w/v glucose, water), and culture it by placing the glass tube in a roller drum and grow at 30 &#176;C. Alternatively, an orbital shaker can be used by placing the glass tube at a slanted angle and shaking the culture at 200 rpm.
	<ol>
		<li>Measure the optical density (OD600) of the overnight culture next morning and dilute it with fresh SC media to OD600 ~0.2 in a total volume of 10 mL. Let it grow for two doublings, which takes about 4 h, to reach the mid-log (OD600 ~1) phase. 
		EXAMPLE: If an overnight culture has an OD600 = 10, add 200 &#181;L of this culture to 9.8 mL SC media.</li>
	</ol>
	</li>
	<li>Within 30 min before the stress treatment, prepare the hydrogen peroxide stress media. Serially dilute hydrogen peroxide from the 30% stock (9.798 M) into Synthetic Complete (SC) media to the desired concentration. Include a mock treatment (SC with no hydrogen peroxide added) and a lethal dose (1 M is suitable for C. glabrata). 
	EXAMPLE: To make a 100 mM hydrogen peroxide stress media, add 10.3 &#181;L of the 9.798 M hydrogen peroxide stock to 1 mL SC. Gently pipette to mix. To make a 10 mM hydrogen peroxide stress media, dilute 500 &#181;L of the 100 mM hydrogen peroxide stress media into 4.5 mL of SC.</li>
	<li>Measure the OD600 of the mid-log culture and standardize it to, e.g., OD600 = 1, by adding SC media. 
	&#8203;EXAMPLE: The mid-log culture is at OD600 = 1.2. Add 0.2 mL SC media per 1 mL of culture.</li>
	<li>Transfer 600 &#181;L mid-log culture per testing condition into a 96 deep-well plate. Pellet cells by centrifugation at 3,000 x g for 5 min at room temperature. Carefully remove the supernatant by aspiration without disturbing the cell pellet.</li>
	<li>Add 600 &#181;L of mock or hydrogen peroxide stress media prepared in step 1.2 to each well and gently pipette to resuspend the cells.</li>
	<li>Incubate the plate for 120 min at 30 &#176;C with shaking at 300 rpm. 
	NOTE: Incubation time depends on the biological question of interest.</li>
</ol>
2. Application of the SYTO 9/PI stain
<ol>
	<li>Prior to the experiment, prepare at least 10 mL sterile 0.85% saline buffer. 
	NOTE: We found 0.85% saline buffer to produce minimal staining artifacts, i.e., unstained and dead-like cells in mock-treated samples, compared with deionized water or growth media16.</li>
	<li>Prepare a working stock solution of PI at 0.2 mM using sterile, deionized water. 
	NOTE: This working stock of PI can be stored for up to 6 months at 4 &#176;C.</li>
	<li>Immediately before the experiment, prepare a working SYTO 9 stock solution at 33.4 &#181;M with sterile, deionized water. 
	NOTE: Prepare the SYTO 9 working stock fresh for each experiment. Do not store and reuse.</li>
	<li>Gently pipette to mix the cells in each well from the treatment plate. Measure OD600 of each treatment condition and calculate the amount of buffer needed to resuspend the cells to an OD600 of 1. 
	NOTE: Multi-channel pipettes can be used for efficient and uniform mixing. Avoid overmixing the samples.</li>
	<li>Collect yeast cells after the mock or stress treatment by centrifugation at 3,000 x g for 5 min. Remove supernatant carefully through aspiration. Resuspend cells in sterile 0.85% saline buffer to OD600 = 1 (calculated in step 2.4). 
	NOTE: Use a multi-channel pipette to resuspend the cells. Handle all post-treatment cultures with care and avoid overmixing.</li>
	<li>Reserve 50 &#181;L of each sample to serve as the unstained and single dye staining controls. 
	NOTE: Minimal autofluorescence was found for wild-type C. glabrata in both channels for SYTO 9 and PI. However, always check unstained samples for autofluorescence and perform proper background subtraction or use low autofluorescence growth media.</li>
	<li>Aliquot 16 &#181;L of post-treatment sample resuspended in 0.85% saline buffer to a 50 &#181;L PCR tube. Add 2 &#181;L of the 0.2 mM working stock of PI to the cell suspension. Then add 2 &#181;L of the 33.4 &#181;M working stock of SYTO 9 to the same tube to a final volume of 20 &#181;L.
	<ol>
		<li>Final concentrations of PI and SYTO 9 will be 20 &#181;M and 3.34 &#181;M, respectively. Gently pipette to mix and incubate for 30 min in the dark (a black box can be used) at room temperature.</li>
	</ol>
	</li>
</ol>
3. Setting up and calibrating the flow cytometer
NOTE: This should be done on each new instrument and also on new applications of the SYTO 9/PI staining, including for a different species/strain, new stressor, or growth protocol, etc. The settings below were developed on an Attune NxT flow cytometer. Refer to the user manual of the instrument in use for specific instructions.
<ol>
	<li>Choose proper&#160;fluorescence channels/filters for the flow cytometer: a 530 nm &#177; 30 nm bandpass filter (BL1) and a 600 nm long pass filter (&#62; 600 nm, BL3) were used to collect signals in the green (SYTO 9) and red (PI and SYTO 9) channels. Both were excited with a 488 nm blue laser.</li>
	<li>Set the flow rate to 200 &#181;L/min and stop when at least 30,000 events have been collected. 
	NOTE: The number of events per sample can be adjusted with the goal of achieving robust estimates of the percentages. Samples with too few events (cells) should be excluded. The next step is to adjust voltages on the FSC and SSC channels during the initial setup.</li>
	<li>Dilute 16 &#181;L mock-treated, unstained sample into 200 &#181;L sterile 0.85% saline buffer. Gently pipette to mix immediately before flow cytometry. Run this sample and adjust the voltages of the FSC and SSC channels so that the population is at the center of the FSC vs. SSC density plot. 
	NOTE: A voltage of 345 mV and 399 mV was used for the FSC and SSC, respectively. The next steps are to adjust voltages on the collection (BL1 and BL3) channels during the initial setup.</li>
	<li>Mix 24 &#181;L mock-treated sample with 24 &#181;L of 1000 mM hydrogen peroxide-treated or heat-killed sample.</li>
	<li>Divide the mixed live and dead cell sample into three tubes of 16 &#181;L each. Stain the three tubes with (1) 2 &#181;L SYTO 9 and 2 &#181;L water for 30 min; (2) 2 &#181;L PI and 2 &#181;L water for 30 min; (3) 2 &#181;L SYTO 9 and 2 &#181;L PI for 30 min. Follow the staining protocol from the previous section.
	<ol>
		<li>After the incubation, add 200 &#181;L of sterile 0.85% saline buffer to each tube. They are now ready for flow cytometry.</li>
	</ol>
	</li>
	<li>Run tube (1) to adjust the voltage of the green fluorescence (BL1) channel; then run tube (2) to adjust the voltage of the red fluorescence (BL3). The goal is to have the mode of each channel&#39;s intensity distribution be ~104-105 so as to utilize the full dynamic range of the instrument. 
	NOTE: Please follow the instructions of your specific flow cytometer when adjusting voltages. Some flow cytometers have fixed voltages, and this step is omitted.</li>
	<li>Run tube (3) to check if live and dead cell populations are well separated. Adjust BL1 or BL3 channel voltages if needed. 
	NOTE: A voltage of 200 mV was used for both the BL1 and BL3 channels on the Attune NxT.</li>
	<li>Run the mock-treated, unstained sample under the established voltage settings to ensure that the sample has minimal autofluorescence in the channels of interest (&#60;102).</li>
</ol>
4. Running samples on the flow cytometer
<ol>
	<li>Apply the flow cytometer settings established above and run the unstained sample first to ensure that autofluorescence signals are below 102 in both BL1 and BL3 channels.</li>
	<li>Add 200 &#181;L 0.85% saline buffer to each stained sample and run it on the flow cytometer. 
	NOTE: If multiple samples are assayed, stagger the staining step such that each sample is stained for 30 min before being run on the flow cytometer.</li>
	<li>Export flow cytometry output as .fcs files (FCS 3.0 or 3.1 standard).</li>
</ol>
5. Data analysis in R
NOTE: A sample analysis script is provided as Supplementary File 1. Example gating strategies are provided in the Representative Results section.
<ol>
	<li>Install and load the required packages: (1) flowCore (2) ggplot2 (3) ggcyto.</li>
	<li>Import .fcs files into the current R environment.</li>
	<li>Adjust file names and specify treatment conditions.</li>
	<li>Make a 2D density plot for all events on FSC.H against SSC.H. Use a polygon gate to exclude non-cell events. Name this gate &#34;cells&#34;. 
	NOTE: On certain flow cytometers, the Area parameter is recommended over Height. Check instrument-specific recommendations.</li>
	<li>For the &#34;cells&#34; gated population, make a 2D density plot on FSC.H against FSC.W. Typically, two clusters are visible with similar ranges of FSC.H but different FSC.W. The cluster with a lower mean FSC.W level contains the single cells (&#34;singlets&#34;). Draw a polygon gate to select them and name the gate &#34;singlets&#34;.</li>
	<li>For the &#34;singlets&#34; gated population, make a 2D density plot on BL1.H against BL3.H. Draw polygon gates for live, damaged, and dead populations based on live and dead cell controls. An example is provided in the Representative Results section.</li>
	<li>Determine survival using the percentages of each population and export the statistics.</li>
</ol>

<ol><li>Lourens-Hattingh, A., Viljoen, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Growth+and+survival+of+a+probiotic+yeast+in+dairy+products%5BTitle%5D)+AND+%22Food+Res+Int%22%5BJournal%5D)">Growth and survival of a probiotic yeast in dairy products.</a> Food Res Int. 34 (9), 791-796 (2001).</li>
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<li>Welsh, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Survival%2C+persistence%2C+and+isolation+of+the+emerging+multidrugresistant+pathogenic+yeast+Candida+auris+on+a+plastic+health+care+surface%5BTitle%5D)+AND+%22J+Clin+Microbiol%22%5BJournal%5D)">Survival, persistence, and isolation of the emerging multidrugresistant pathogenic yeast Candida auris on a plastic health care surface.</a> J Clin Microbiol. 55 (10), 2996-3005 (2017).</li>
<li>Millard, P. J., Roth, B. L., Thi, H. P., Yue, S. T., Haugland, R. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Development+of+the+FUN1+family+of+fluorescent+probes+for+vacuole+labeling+and+viability+testing+of+yeasts%5BTitle%5D)+AND+%22Appl+Environ+Microbiol%22%5BJournal%5D)">Development of the FUN1 family of fluorescent probes for vacuole labeling and viability testing of yeasts.</a> Appl Environ Microbiol. 63 (7), 2897-2905 (1997).</li>
<li>WlochSalamon, D. M., Bem, A. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Types+of+cell+death+and+methods+of+their+detection+in+yeast+Saccharomyces+cerevisiae%5BTitle%5D)+AND+%22J+Appl+Microbiol%22%5BJournal%5D)">Types of cell death and methods of their detection in yeast Saccharomyces cerevisiae.</a> J Appl Microbiol. 114 (2), 287-298 (2013).</li>
<li>Boulos, L., Prévost, M., Barbeau, B., Coallier, J., Desjardins, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((LIVE%2FDEAD+BacLight%3A+Application+of+a+new+rapid+staining+method+for+direct+enumeration+of+viable+and+total+bacteria+in+drinking+water%5BTitle%5D)+AND+%22J.+Microbiol.+Methods%22%5BJournal%5D)">LIVE/DEAD BacLight: Application of a new rapid staining method for direct enumeration of viable and total bacteria in drinking water.</a> J. Microbiol. Methods. 37 (1), 77-86 (1999).</li>
<li>Zhang, T., Fang, H. H. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quantification+of+Saccharomyces+cerevisiae+viability+using+BacLight%5BTitle%5D)+AND+%22Biotechnol+Lett%22%5BJournal%5D)">Quantification of Saccharomyces cerevisiae viability using BacLight.</a> Biotechnol Lett. 26 (12), 989-992 (2004).</li>
<li>Stocks, S. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Mechanism+and+use+of+the+commercially+available+viability+stain%2C+BacLight%5BTitle%5D)+AND+%22Cytometry+A%22%5BJournal%5D)">Mechanism and use of the commercially available viability stain, BacLight.</a> Cytometry A. 61A (2), 189-195 (2004).</li>
<li>Sun, S., Baryshnikova, A., Brandt, N., Gresham, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Genetic+interaction+profiles+of+regulatory+kinases+differ+between+environmental+conditions+and+cellular+states%5BTitle%5D)+AND+%22Mol+Syst+Biol%22%5BJournal%5D)">Genetic interaction profiles of regulatory kinases differ between environmental conditions and cellular states.</a> Mol Syst Biol. 16 (5), e9167(2020).</li>
<li>Li, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Allicin+shows+antifungal+efficacy+against+Cryptococcus+neoformans+by+blocking+the+fungal+cell+membrane%5BTitle%5D)+AND+%22Front+Microbiol%22%5BJournal%5D)">Allicin shows antifungal efficacy against Cryptococcus neoformans by blocking the fungal cell membrane.</a> Front Microbiol. 13, 1012516(2022).</li>
<li>Jin, Y., Zhang, T., Samaranayake, Y., Fang, H. H. P., Yip, H. K., Samaranayake, L. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+use+of+new+probes+and+stains+for+improved+assessment+of+cell+viability+and+extracellular+polymeric+substances+in+Candida+albicans+biofilms%5BTitle%5D)+AND+%22Mycopathologia%22%5BJournal%5D)">The use of new probes and stains for improved assessment of cell viability and extracellular polymeric substances in Candida albicans biofilms.</a> Mycopathologia. 159 (3), 353-360 (2005).</li>
<li>Bojsen, R., Regenberg, B., Folkesson, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Saccharomyces+cerevisiae+biofilm+tolerance+towards+systemic+antifungals+depends+on+growth+phase%5BTitle%5D)+AND+%22BMC+Microbiol%22%5BJournal%5D)">Saccharomyces cerevisiae biofilm tolerance towards systemic antifungals depends on growth phase.</a> BMC Microbiol. 14, 305(2014).</li>
<li>Ryan, L. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Activity+of+potent+and+selective+host+defense+peptide+mimetics+in+mouse+models+of+oral+candidiasis%5BTitle%5D)+AND+%22Antimicrob+Agents+Chemother%22%5BJournal%5D)">Activity of potent and selective host defense peptide mimetics in mouse models of oral candidiasis.</a> Antimicrob Agents Chemother. 58 (7), 3820-3827 (2014).</li>
<li>Chudzik, B., Koselski, M., Czuryło, A., Trębacz, K., Gagoś, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+new+look+at+the+antibiotic+amphotericin+B+effect+on+Candida+albicans+plasma+membrane+permeability+and+cell+viability+functions%5BTitle%5D)+AND+%22Eur.+Biophys.+J.+%28EBJ%29%22%5BJournal%5D)">A new look at the antibiotic amphotericin B effect on Candida albicans plasma membrane permeability and cell viability functions.</a> Eur. Biophys. J. (EBJ). 44 (1-2), 77-90 (2015).</li>
<li>Roscetto, E., Contursi, P., Vollaro, A., Fusco, S., Notomista, E., Catania, M. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Antifungal+and+antibiofilm+activity+of+the+first+cryptic+antimicrobial+peptide+from+an+archaeal+protein+against+Candida+spp.+clinical+isolates%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Antifungal and antibiofilm activity of the first cryptic antimicrobial peptide from an archaeal protein against Candida spp. clinical isolates.</a> Sci Rep. 8 (1), 17570(2018).</li>
<li>Tang, H., Liang, J., He, B. Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((An+optimized+LIVE%2FDEAD+assay+using+flow+cytometry+to+quantify+poststress+and+antifungaltreatment+survival+in+diverse+yeasts%5BTitle%5D)+AND+%22BioRiv%22%5BJournal%5D)">An optimized LIVE/DEAD assay using flow cytometry to quantify poststress and antifungaltreatment survival in diverse yeasts.</a> BioRiv. , (2025).</li>
<li>Stiefel, P., SchmidtEmrich, S., ManiuraWeber, K., Ren, Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Critical+aspects+of+using+bacterial+cell+viability+assays+with+the+fluorophores+SYTO9+and+propidium+iodide%5BTitle%5D)+AND+%22BMC+Microbiol%22%5BJournal%5D)">Critical aspects of using bacterial cell viability assays with the fluorophores SYTO9 and propidium iodide.</a> BMC Microbiol. 15 (1), 36(2015).</li>
<li>Rego, A., Ribeiro, A., CôrteReal, M., Chaves, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Monitoring+yeast+regulated+cell+death%3A+Trespassing+the+point+of+no+return+to+loss+of+plasma+membrane+integrity%5BTitle%5D)+AND+%22Apoptosis%22%5BJournal%5D)">Monitoring yeast regulated cell death: Trespassing the point of no return to loss of plasma membrane integrity.</a> Apoptosis. 27 (9), 778-786 (2022).</li>
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</ol>

The authors have no conflict of interest.

This protocol describes a LIVE/DEAD assay using two fluorescent dyes, SYTO 9 and PI, and using flow cytometry to quantify post-stress survival in yeast. While these two stains have been applied to assess survival in various yeast species in the literature and are available as a commercial kit, neither the manufacturer&#39;s manual nor the literature provides sufficient details on the staining protocol or flow cytometry settings7. Here, we present a standardized protocol resulting from systematic c...

The budding yeast subphylum contains many important biological and biotechnological models. A common and critical task in yeast research is quantifying the effect of genetic or environmental perturbations, the latter including stress or drug treatments. In industrial fermentation, for example, producers must monitor the viability of yeast cultures to ensure the efficiency and quality of the fermentation process1,2. When studying pathogenic yeast species, measuring their survival after stress or antifungal treatment is critical for understanding the genetic and mechanistic basis for infection-related traits such as antifungal resistance. Measuring survival on catheters and surfaces is also an important task in clinical settings3. These diverse scenarios all call for quantitative approaches that can rapidly and accurately measure the outcome of drug and stress treatments.
Existing methods for achieving the above goal fall into three main categories based on what they measure. The first category measures clonogenicity, or the ability of individual yeast cells to form a single colony following the stress. The representative method in this category is the Colony Forming Unit (CFU) assay. The second category measures vitality, which relies on detecting enzymatic activities in live cells. Examples include chemical probes such as the FUN-1 dye4. The third category of methods measure&#160;plasma membrane integrity - an irreversible loss of plasma membrane integrity is considered the &#34;point of no return&#34; for cell death5. Examples of this category include fluorescent dyes such as propidium iodide (PI).
This work presents an optimized LIVE/DEAD assay coupled with flow cytometry to achieve fast and scalable quantification of yeast survival after stress treatment. This membrane permeability-based assay is faster than CFU, taking 15-30 min of staining compared with 24-48 h of incubation for colonies to form. Also, samples stained with a LIVE/DEAD stain can be readily assayed using flow cytometry in addition to microscopy, which measures tens of thousands of cells in a few seconds and can easily process 96-well samples for high-throughput assays. As a result, this assay is rapid, quantitative, and scalable. In this protocol, a two-component LIVE/DEAD stain consisting of SYTO 9 and PI is used to achieve enhanced resolving power. SYTO 9 labels all cells, live or dead, while PI only enters cells with compromised plasma membranes6,7. Therefore, live cells only accumulate SYTO 9 while dead cells accumulate both SYTO 9 and PI. Because PI has a higher affinity than SYTO 9 for nucleic acid, it competitively excludes the latter in the cell8. Also, the two dyes form a F&#246;rster Resonance Energy Transfer (FRET) pair, where SYTO 9 emission is absorbed by PI as its excitation. As a result, dead cells exhibit muted green and strong red fluorescence. In contrast, live cells display bright green fluorescence8. This difference enables better differentiation between live and dead cells in the presence of variations in fluorescence intensity within each group.
Since an initial report of its application in yeast in 2004, the use of SYTO 9/PI in yeast studies has been spotty and largely limited to qualitative evaluations using microscopy7,9,10,11,12,13,14,15. A major limitation to its adoption as a quantitative assay for yeast survival is the lack of systematic characterization and comparison with widely used methods such as CFU. This protocol describes a standardized assay including the staining buffer, dye concentration, staining time, and flow cytometry settings, which were found to minimize artifacts and generate reproducible results when applied to C. glabrata and two other yeast species16. Because SYTO 9/PI staining reveals an intermediate &#34;damaged&#34; population of cells that differ from both the live and dead cells in their staining pattern, it can complement CFU by revealing more nuanced information on the effects of stress treatment on yeast cells, potentially enabling new applications.

<table><tbody><tr><td>96-Well Deep Well Plate</td><td>Thermo Fisher</td><td>278606</td><td>NUNC 96</td></tr><tr><td>Attune NxT flow cytometer with plate reader</td><td>Thermo Fisher A24858</td><td>A24858</td><td>Autosampler (A42901)</td></tr><tr><td>&lt;em&gt;Candida glabrata&lt;/em&gt;</td><td></td><td></td><td>CG99, lab strain derived from clinical isolate (Cormack &amp;amp; Falkow, 1999)</td></tr><tr><td>FungaLight Yeast LIVE/DEAD Kit</td><td>Thermo Fisher A24858</td><td>L34952</td><td>Contains SYTO 9 (3.34 mM) and Propidium Iodide (20 mM). These two components can also be purchased separately from various vendors.</td></tr><tr><td>Hydrogen Peroxide</td><td>Sigma Aldrich</td><td>H1009</td><td></td></tr><tr><td>Leica Confocal SP8 Microscope</td><td>Leica</td><td>TCS SP8 X</td><td></td></tr><tr><td>Sodium Chloride</td><td>Sigma Aldrich</td><td>S9888</td><td>Used to make sterilized 0.85% NaCl solution</td></tr><tr><td>Yeast Nitrogen Base without amino acids</td><td>Sigma Aldrich</td><td>Y0626</td><td>used to make the Synthetic Complete media with 2% glucose and amino acid mix</td></tr></tbody></table>

an optimized live/dead assay coupled with flow cytometry for quantifying post-stress survival in yeast cells

An Optimized LIVE/DEAD Assay Coupled with Flow Cytometry for Quantifying Post-Stress Survival in Yeast Cells

Quantifying survival is a common and critical task in yeast research. LIVE/DEAD stains based on plasma membrane integrity provide a rapid and high-throughput assay for yeast survival when coupled with flow cytometry. However, variations in staining buffer, dye concentration, incubation time, and flow cytometry settings can impact data quality and reproducibility. This protocol presents a standardized LIVE/DEAD assay for post-stress survival quantification in yeast using flow cytometry. After treating Candida glabrata, an opportunistic yeast pathogen, with different doses of hydrogen peroxide, the post-stress samples were stained with a two-component LIVE/DEAD stain consisting of SYTO 9 and propidium iodide (PI). Flow cytometry was used to distinguish live, damaged, and dead cell populations and quantify their percentages in each sample. Survival estimates based on the percent&#160;live statistic were compared to the Colony Forming Unit (CFU) result on the same sample. The two methods yielded consistent results for the mock- and lethal dose (1 M H2O2)-treated samples. At the sublethal dose of 100 mM H2O2, SYTO 9/PI estimated a higher survival rate than CFU, reflecting a key difference between the two, where the protocol presented here evaluates cell survival immediately after the stress, while CFU quantifies the percent of cells able to recover and reproduce. Hence, this protocol measures viability at an earlier stage of the cell-death process. In summary, the protocol described here provides a fast and scalable alternative to CFU for post-stress survival quantification in yeast. Its results provide complementary information to CFU by evaluating survival at an earlier stage and distinguishing between dead and damaged cells.

The SYTO 9/PI stain distinguishes live yeast cells from dead cells based on their fluorescence signals in the green (500 nm-560 nm) and red (&gt;600 nm) channels. Live cells, which only accumulate SYTO 9, fluoresce strongly in the green channel, with minimal red signals. Dead cells accumulate both SYTO 9 and PI and are expected to fluoresce strongly in the red channel, with lower green fluorescence signals compared to live cells due to competitive exclusion of SYTO 9 by PI and FRET.
<...

Here, we present a protocol to quantify post-stress survival in yeast samples. The assay employs two fluorescent dyes, SYTO 9 and propidium iodide (PI), to quantify plasma membrane integrity. It uses flow cytometry to provide quantitative and reproducible estimates of the live, dead, and damaged cell fractions for post-oxidative-stress samples.

Quantifying survival is a common and critical task in yeast research. LIVE/DEAD stains based on plasma membrane integrity provide a rapid and ...

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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.

Quantitative Live Cell Fluorescence-microscopy Analysis of Fission Yeast

Source: Chapman, I. J., et al., Molecular Probe Optimization to Determine Cell Mortality in a Photosynthetic Organism (Microcystis aeruginosa) Using Flow Cytometry. J. Vis. Exp. (2016)This video demonstrates the method for distinguishing live and dead Microcystis aeruginosa cells by combining fluorescent probe labeling with flow cytometric analysis of phycocyanin autofluorescence and probe signal.

Viability Analysis of Microcystis aeruginosa Using Flow Cytometry

This article describes the use of a firefly luciferase-GFP fusion protein to investigate in vivo protein folding in Saccharomyces cerevisiae.  Using this reagent, refolding of a model heat-denatured protein can be monitored simultaneously by fluorescence microscopy and an enzymatic assay to probe the roles of proteostasis network components in protein quality control.

Coupled Assays for Monitoring Protein Refolding in Saccharomyces cerevisiae

Two complementary methods based on flow cytometry and microscopy are presented which enable the quantification, at the single cell level, of the dynamics of gene expression induced by the activation of a MAPK pathway in yeast.

Temporal Quantification of MAPK Induced Expression in Single Yeast Cells

Microbial populations contain substantial cell heterogeneity, which can dictate overall behavior. Molecular probe analysis through flow cytometry can determine physiological states of cells, however its application varies between species. This study provides a protocol to accurately determine cell mortality within a cyanobacterium population, without underestimating or recording false positive results.

Molecular Probe Optimization to Determine Cell Mortality in a Photosynthetic Organism (Microcystis aeruginosa) Using Flow Cytometry

The study of metabolism is becoming increasingly relevant to immunological research. Here, we present an optimized method for measuring glycolysis and mitochondrial respiration in mouse splenocytes, and T and B lymphocytes.

An Optimized Protocol to Analyze Glycolysis and Mitochondrial Respiration in Lymphocytes

Protein aggregation elicits cellular oxidative stress. This protocol describes a method for monitoring the intracellular states of amyloidogenic proteins and the oxidative stress associated with them, using flow cytometry. The approach is used to study the behavior of soluble and aggregation-prone variants of the amyloid-β peptide.

Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast

This article describes a FRET-based flow cytometry protocol to quantify protein self-assembly in both S. cerevisiae and HEK293T cells.

Detecting and Characterizing Protein Self-Assembly In Vivo by Flow Cytometry

Yeast growth phenotypes are precisely measured through highly parallel time-lapse imaging of immobilized cells growing into microcolonies. Simultaneously, stress tolerance, protein expression, and protein localization can be monitored, generating integrated datasets to study how environmental and genetic differences, as well as gene-expression heterogeneity among isogenic cells, modulate growth.

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression

Here, we introduce a protocol for using yeast surface-displayed substrates for enzymatic modification assays. The platform was demonstrated using the analysis of the dephosphorylation activity of tyrosine phosphatase SHP-2 against one of its substrates as a representative enzymatic modification assay.

Enzymatic Modification and Flow Cytometry Assessment of Yeast Surface Displayed Proteins

Learn a flow cytometry-based LIVE/DEAD assay to quantify post-stress survival in yeast cells using SYTO 9 and propidium iodide. This method provides quantitative assessment of live, dead, and damaged cell fractions.

An Optimized LIVE/DEAD Assay Coupled with Flow Cytometry for Quantifying Post-Stress Survival in Yeast Cells

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