Name: saccharomyces cerevisiae exponential growth kinetics in batch culture to analyze respiratory and fermentative metabolism
Uploaded: 2018-09-30T14:00:00
Description: Watch this Scientific Journal Video about Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism at JoVE.com

This project was supported by grants of the Consejo Nacional de Ciencia y Tecnolog&#237;a (grant number 293940) and Fundaci&#243;n TELMEX-TELCEL (grant number 162005585), both to IKOM.

1. Culture Media and Inoculum Preparation
<ol>
	<li>Prepare 100 mL of 2% yeast extract-peptone-dextrose (YPD) liquid medium (add 1 g of yeast extract, 2 g of casein peptone, and 2 g of glucose to 100 mL of distilled water). Dispense 3 mL of the media into 15 mL sterilizable conical tubes. Autoclave the media for 15 min at 121 &#176;C and 1.5 psi. 
	NOTE: The media can be stored for up to one month at 4&#8211;8 &#176;C.</li>
	<li>Inoculate a conical tube filled with 3 mL of cool sterile 2% YPD broth with 250 &#956;...

<ol>
	<li>Parrella, E., Longo, V. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+chronological+life+span+of+Saccharomyces+cerevisiae+to+study+mitochondrial+dysfunction+and+disease.">The chronological life span of Saccharomyces cerevisiae to study mitochondrial dysfunction and disease.</a> Methods. 46 (4), 256-262 (2008).</li><li>Rosas Lemus, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+glycolysis-derived+hexose+phosphates+in+the+induction+of+the+Crabtree+effect.">The role of glycolysis-derived hexose phosphates in the induction of the Crabtree effect.</a> Journal of Biological Chemistry. , (2018).</li><li>Xu, X. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Warburg+effect+or+reverse+Warburg+effect?+A+review+of+cancer+metabolism.">Warburg effect or reverse Warburg effect? A review of cancer metabolism.</a> Oncology Research and Treatment. 38 (3), 117-122 (2015).</li><li>De Deken, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Crabtree+effect:+a+regulatory+system+in+yeast.">The Crabtree effect: a regulatory system in yeast.</a> Journal of General Microbiology. 44 (2), 149-156 (1966).</li><li>Hagman, A., Sall, T., Piskur, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+the+yeast+short-term+Crabtree+effect+and+its+origin.">Analysis of the yeast short-term Crabtree effect and its origin.</a> The FEBS Journal. 281 (21), 4805-4814 (2014).</li><li>Hammad, N., Rosas-Lemus, M., Uribe-Carvajal, S., Rigoulet, M., Devin, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Crabtree+and+Warburg+effects:+Do+metabolite-induced+regulations+participate+in+their+induction?.">The Crabtree and Warburg effects: Do metabolite-induced regulations participate in their induction?.</a> Biochim Biophys Acta. 1857 (8), 1139-1146 (2016).</li><li>Keating, E., Martel, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antimetabolic+Effects+of+Polyphenols+in+Breast+Cancer+Cells:+Focus+on+Glucose+Uptake+and+Metabolism.">Antimetabolic Effects of Polyphenols in Breast Cancer Cells: Focus on Glucose Uptake and Metabolism.</a> Frontiers in Nutrition. 5, 25 (2018).</li><li>Pfeiffer, T., Morley, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+evolutionary+perspective+on+the+Crabtree+effect.">An evolutionary perspective on the Crabtree effect.</a> Frontiers in Molecular Biosciences. 1, 17 (2014).</li><li>Olivares-Marin, I. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interactions+between+carbon+and+nitrogen+sources+depend+on+RIM15+and+determine+fermentative+or+respiratory+growth+in+Saccharomyces+cerevisiae.">Interactions between carbon and nitrogen sources depend on RIM15 and determine fermentative or respiratory growth in Saccharomyces cerevisiae.</a> Applied Microbiology and Biotechnology. 102 (10), 4535-4548 (2018).</li><li>Monod, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+growth+of+bacterial+cultures.">The growth of bacterial cultures.</a> Annual Review of Microbiology. 3 (1), 371-394 (1949).</li><li>Cui, S., Xu, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+mathematical+models+for+the+growth+of+tumors+with+time+delays+in+cell+proliferation.">Analysis of mathematical models for the growth of tumors with time delays in cell proliferation.</a> Journal of Mathematical Analysis and Applications. 336 (1), 523-541 (2007).</li><li>Benzekry, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Classical+mathematical+models+for+description+and+prediction+of+experimental+tumor+growth.">Classical mathematical models for description and prediction of experimental tumor growth.</a> Public Library of Science Computational Biology. 10 (8), e1003800 (2014).</li><li>Ramos-Gomez, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resveratrol+induces+mitochondrial+dysfunction+and+decreases+chronological+life+span+of+Saccharomyces+cerevisiae+in+a+glucose-dependent+manner.">Resveratrol induces mitochondrial dysfunction and decreases chronological life span of Saccharomyces cerevisiae in a glucose-dependent manner.</a> Journal of Bioenergetics and Biomembranes. 49 (3), 241-251 (2017).</li><li>Madrigal-Perez, L. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Energy-dependent+effects+of+resveratrol+in+Saccharomyces+cerevisiae.">Energy-dependent effects of resveratrol in Saccharomyces cerevisiae.</a> Yeast. 33 (6), 227-234 (2016).</li><li>Peleg, M., Corradini, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microbial+growth+curves:+what+the+models+tell+us+and+what+they+cannot.">Microbial growth curves: what the models tell us and what they cannot.</a> Critical Reviews in Food Science and Nutrition. 51 (10), 917-945 (2011).</li></ol>

A long time has passed since J. Monod10 expressed that the study of the growth of bacterial cultures is the basic method of microbiology. The advent of the molecular tools delays the usage and study of the growth as a technique. Despite the complexity of growth which involves numerous interrelated processes, its underlying mechanisms can be described by using mathematical models11. This is a robust approach that can be used as a complementary tool to elucidate the most intr...

Saccharomyces cerevisiae growth has served as a valuable tool to identify dozens of physiological and molecular mechanisms. Growth is measured primarily by three methods: serial dilutions for spot testing, colony-forming unit counting, and growth curves. These techniques can be used alone or in combination with a variety of substrates, environmental conditions, mutants, and chemicals to investigate specific responses or phenotypes.
Mitochondrial respiration is a biological process in which growth kinetics has been successfully applied for discovering unknown mechanisms. In this case, the supplementation of growth media with non-fermentable carbon sources such as glycerol, lactate, or ethanol (which are exclusively metabolized by mitochondrial respiration), as the sole carbon and energy source allows for evaluating the respiratory growth, which is important to detect perturbations in oxidative phosphorylation activity1. On the other hand, it is complicated to use growth kinetic models as a method for deciphering the mechanisms behind fermentation.
The study of fermentation and mitochondrial respiration is essential to elucidate the molecular mechanisms behind certain phenotypes such as the Crabtree and Warburg effects2,3. The Crabtree effect is characterized by an increase of glycolytic flux, repression of mitochondrial respiration, and establishment of fermentation as the primary pathway to generate ATP in the presence of high concentrations of fermentable carbohydrates (&#62;0.8 mM)4,5. The Warburg effect is metabolically analog to the Crabtree effect, with the difference being that in mammalian cells, the main product of fermentation is lactate6. Indeed, the Warburg effect is exhibited by a variety of cancer cells, triggering glucose uptake and consumption even in the presence of oxygen7. Thereby, studying the molecular basis of the switch from respiration to fermentation in the Crabtree effect has both biotechnological repercussions (for ethanol production) and potential impacts in cancer research.
S. cerevisiae growth may be a suitable tool to study the Crabtree and Warburg effects. This idea is based on the fact that in the yeast exponential phase, the central pathways used to produce ATP are mitochondrial respiration and fermentation, which are essential to sustain growth. For instance, the growth of S. cerevisiae is intimately related to the function of ATP-generating pathways. In S. cerevisiae, the mitochondrial respiration produces approximately 18 ATP molecules per glucose molecule, whereas fermentation only generates 2 ATP molecules, hence it is expected that the growth rate has tight links with the metabolic pathways producing ATP8. In this regard, when fermentation is the principal route to generate ATP, the yeast compensates for the low ATP production by increasing the rate of glucose uptake. On the contrary, the glucose consumption by yeast cells that use mitochondrial respiration as the main ATP source is low. This indicates that it is important for the yeast to sense carbohydrate availability before determining how ATP will be generated. Therefore, glucose availability plays an important role in the switch between fermentation and mitochondrial respiration in S. cerevisiae. In the presence of high quantities of glucose, the yeast prefers fermentation as the central route to generate ATP. Interestingly, when the yeast is fermenting, the specific growth rate is maintained at its maximum. On the other hand, under low levels of glucose, S. cerevisiae produces ATP using mitochondrial respiration, maintaining lower growth rates. Thereby, variation in the concentration of glucose and the use of other carbon sources induce changes in the yeast&#39;s preference between fermentative and respiratory growth. By taking into account this fact with the exponential growth equation, one can obtain the biological meaning of kinetic parameters such as doubling time (Dt) and specific growth rate (&#181;). For example, lower &#181; values were found when the yeast uses mitochondrial respiration as the primary pathway. On the contrary, under conditions that favor fermentation, higher &#181; values were found. This methodology may be used to measure the probable mechanisms of any chemicals affecting fermentation and mitochondrial respiration in S. cerevisiae.
The objective of this paper is to propose a method based on growth kinetics for screening the effects of a given substance/compound on mitochondrial respiration or fermentation.

<table border="0" cellpadding="0" cellspacing="0" width="573">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Orbital Shaker</td>
			<td style="width:71px;">Thermo Scientific</td>
			<td align="right" style="width:119px;">4353</td>
			<td style="width:167px;">For inoculum incubation or conical fask cultures</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Bioscreen&#160;</td>
			<td style="width:71px;">Growth curves</td>
			<td style="width:119px;">C MBR</td>
			<td>For batch cultures in microplates</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Glucose</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">G7021</td>
			<td>For YPD broth preparation</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Peptone from casein, enzymatic digest</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td align="right" style="width:119px;">82303</td>
			<td>For YPD broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Yeast extract</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">09182-1KG-F</td>
			<td>For YPD broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Bacteriological Agar</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">A5306</td>
			<td>For YPD agar preparation</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;">NaH2PO4</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td>S8282</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">(NH4)2SO4</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td>A4418</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Yeast nitrogen base without amino acids and ammonium sulfate</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">Y1251</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Yeast synthetic drop-Out medium supplements</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">Y1501</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Ammonium sulfate granular</td>
			<td style="width:71px;">J.T. Baker</td>
			<td style="width:119px;">0792-R</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Resveratrol</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">R5010</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Galactose</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td>G8270</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Sucrose</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">S7903</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Absolut ethanol</td>
			<td style="width:71px;">Merck</td>
			<td align="right">107017</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Glycerol</td>
			<td style="width:71px;">J.T. Baker</td>
			<td>2136-01</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">GraphPad Prism</td>
			<td style="width:71px;">GraphPad Software</td>
			<td></td>
			<td>For data analysis</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Honeycomb microplates</td>
			<td style="width:71px;">Thermo Scientific</td>
			<td align="right">9502550</td>
			<td>For microplate cultures</td>
		</tr>
	</tbody>
</table>

saccharomyces cerevisiae exponential growth kinetics in batch culture to analyze respiratory and fermentative metabolism

Saccharomyces cerevisiae cells in the exponential phase sustain their growth by producing ATP through fermentation and/or mitochondrial respiration. The fermentable carbon concentration mainly governs how the yeast cells generate ATP; thus, the variation in fermentable carbohydrate levels drives the energetic metabolism of S. cerevisiae. This paper describes a high-throughput method based on exponential yeast growth to estimate the effects of concentration changes and nature of the carbon source on respiratory and fermentative metabolism. The growth of S. cerevisiae is measured in a microplate or shaken conical flask by determining the optical density (OD) at 600 nm. Then, a growth curve is built by plotting OD versus time, which allows identification and selection of the exponential phase, and is fitted with the exponential growth equation to obtain kinetic parameters. Low specific growth rates with higher doubling times generally represent a respiratory growth. Conversely, higher specific growth rates with lower doubling times indicate fermentative growth. Threshold values of doubling time and specific growth rate are estimated using well-known respiratory or fermentative conditions, such as non-fermentable carbon sources or higher concentrations of fermentable sugars. This is obtained for each specific strain. Finally, the calculated kinetic parameters are compared with the threshold values to establish whether the yeast shows fermentative and/or respiratory growth. The advantage of this method is its relative simplicity for understanding the effects of a substance/compound on fermentative or respiratory metabolism. It is important to highlight that growth is an intricate and complex biological process; therefore, preliminary data from this method must be corroborated by the quantification of oxygen consumption and accumulation of fermentation byproducts. Thereby, this technique can be used as a preliminary screening of compounds/substances that may disturb or enhance fermentative or respiratory metabolism.

Growth curves can be used to preliminarily discriminate between respiratory and fermentative phenotypes in the S. cerevisiae yeast. Therefore, we performed batch cultures of S. cerevisiae (BY4742) with different glucose concentrations that have been reported to induce fermentative growth: 1%, 2%, and 10% (w/v)9. Cultures showing a fermentative phenotype have a small lag phase and an exponential phase with a high growth rate (F...

Watch this Scientific Journal Video about Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism at JoVE.com

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Here we present a protocol to estimate the respiratory and fermentative metabolism by fitting the exponential growth of Saccharomyces cerevisiae to the exponential growth equation. Calculation of the kinetic parameters allows for the screening of influences of substances/compounds on fermentation or mitochondrial respiration.

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Saccharomyces cerevisiae cells in the exponential phase sustain their growth by producing ATP through fermentation and/or mitochondrial respiration. The ...

This method can help answer key questions in the biotechnological and biomedical fields such as what are the molecular basis behind the Warburg and the Crabtree effects. The main advantage of this technique is that it allows the high throughput study of the effects of certain substances in respiratory and fermentative metabolism. Begin by inoculating a 15-milliliter conical tube containing three milliliters of cool, sterile 2%yeast extract peptone dextrose, or YPD broth, with 250 microliters of S.cerevisiae yeast cells preserved in glycerol at negative 20 degrees Celsius.Incubate the yeast overnight in an orbital shaker at 30 degrees Celsius and 200 rpm. for streaking onto a 60-milliliter, 2%YPD agar-filled Petri dish the next morning. Culture the dish at 30 degrees Celsius until isolated colonies are observed.Then inoculate a single isolated colony in a new conical tube containing 10 milliliters of cool, sterile 2%YPD broth for overnight culture at 30 degrees Celsius with shaking. For microplate growth-curve setup, add 145 microliters of an appropriate experimental cultural medium to each well of a sterile 10-by-10 well microplate with a lid and inoculate each well with five microliters of the overnight culture. Then incubate the multi-well plate in a microplate reader at 30 degrees Celsius with constant agitation at 200 rpm for 48 hours, measuring the optical density at 600 nanometers every 30 or 60 minutes.For shaken conical flask growth-curve setup, inoculate 20 milliliter conical flasks containing 4.8 milliliters of an appropriate sterile culture media with 200 microliters of pre-inoculum culture at a 600 nanometer optical density of two for incubation at 30 degrees Celsius and 250 rpm. Agitation at 250 revolutions per minute is critical to achieve a suitable growth in low concentrations of carbon sources that exert respiratory growth as we have observed a reduced yeast growth in respiratory conditions at lower agitation speeds. To allow measurement of the optical density at 600 nanometer every two hours for 24 hours, dilute 100 microliters of the shaken conical flask culture in 900 microliters of distilled water in a one-milliliter spectrophotometer cuvette and gently mix by pipette.For data processing, in an appropriate statistical package software, create a new project file, open the new table and graph menu, and select XY.Under the sample data menu, select start with an empty data table and a points and connecting line graph. Leave the X section unselected in subcolumns for replicates or error values. In the Y section, select enter 10 replicate values in side-by-side subcolumns and plot mean and error SD.Then click create.Enter the time at which the OD measurements were obtained in the X column and the OD values obtained from the cultures in the Y column. To identify the exponential growth phase transforming the Y column data into logarithms, click analyze and select the transform analysis. Use Y equals log Y to select the Y values and open the gallery of results.Select the transform data table, click analyze, and select the linear regression analysis, excluding the optical density values that do not follow a linear trend by selecting the values in the table and depressing control and E.In the data-tables gallery, select the data one table and click analyze. Select the nonlinear regression curve fit analysis and the data sets to analyze, and click OK.Then apply least squares fit to the data, leaving the interpolate section unselected, and click OK.Next, open a new project file, and in the new table and graph menu, select the column choice, start with an empty data table, and the desired graph. Set the graph to plot the mean with the standard deviation, and click create.Copy the mean or delta time values from the nonlinear fit results table in the gallery of results and paste the data into a column. Finally, click analyze and select the analysis of interest in the column analyses menu to compare the kinetic parameters of the different nutrimental conditions. The growth kinetic threshold values vary between strengths and must be evaluated according to the conditions that we use in the analysis.Cultures demonstrating a fermentative phenotype have a small lag phase and an exponential phase with a high growth rate. Cultures that obtain energy mainly by oxidative phosphorylation exhibit a longer lag phase with a slow rate of growth during the exponential phase. Calculation of the specific growth rate and doubling time of the growth curves using the exponential growth equation allows for the setting of thresholds for the respiratory and fermentative growth values.For example, in these representative experiments, the effects of different resveratrol concentrations on S.cerevisiae BY4742 cells reveal the modification of the cell energetic status in response to varying glucose concentrations. Here, supplementation with 10%glucose demonstrates that lower concentrations of ammonium favor fermentative metabolism as evidenced by an extended exponential growth phase in these cultures, while a higher concentration induces a respiro-fermentative metabolism as evidenced by an extended lag phase and a slower growth rate during the exponential phase. Finally, robust differences in fermentative doubling-time values can be observed between these two different yeast strains grown under the same conditions, highlighting the necessity of validating the doubling-time threshold for each strain analyzed.While attempting this procedure, it's important to remember that this protocol is only used to screen out phenotype. The specific effects on respiration and fermentation must be confirmed by oxygen consumption assays or by the accumulation of fermentation byproducts respectively.

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Research

JoVE Journal

Biology

Dissection of Saccharomyces Cerevisiae Asci

Yeast is a highly tractable model system that is used to study many different cellular processes. The common laboratory strain Saccharomyces cerevisiae exists in either a haploid or diploid state. The ability to combine alleles from two haploids and the ability to introduce modifications to the genome requires the production and dissection of asci. Asci production from haploid cells begins with the mating of two yeast haploid strains with compatible mating types to produce a diploid strain. This can be accomplished in a number of ways either on solid medium or in liquid. It is advantageous to select for the diploids in medium that selectively promotes their growth compared to either of the haploid strains. The diploids are then allowed to sporulate on nutrient-poor medium to form asci, a bundle of four haploid daughter cells resulting from meiotic reproduction of the diploid. A mixture of vegetative cells and asci is then treated with the enzyme zymolyase to digest away the membrane sac surrounding the ascospores of the asci. Using micromanipulation with a microneedle under a dissection microscope one can pick up individual asci and separate and relocate the four ascopores. Dissected asci are grown for several days and tested for the markers or alleles of interest by replica plating onto appropriate selective media.

Dissection of Saccharomyces Cerevisiae Asci

Micromanipulation of yeast cells is needed for meiotic genetic analysis or to select diploid zygotes. These micromanipulations are carried out using the microneedle of a dissection microscope. The microneedle is used to relocate cells and is controlled by a micromanipulator which are available with various degrees of automation.

Yeast is a highly tractable model system that is used to study many different cellular processes. The common laboratory strain Saccharomyces cerevisiae ...

Quantitative Phosphoproteomics in Fatty Acid Stimulated Saccharomyces cerevisiae

This protocol describes the growth and stimulation, with the fatty acid oleate, of isotopically heavy and light S. cerevisiae cells. Cells are ground using a cryolysis procedure in a ball mill grinder and the resulting grindate brought into solution by urea solubilization. This procedure allows for the lysis of the cells in a metabolically inactive state, preserving phosphorylation and preventing reorientation of the phosphoproteome during cell lysis.  Following reduction, alkylation, trypsin digestion of the proteins, the samples are desalted on C18 columns and the sample complexity reduced by fractionation using hydrophilic interaction chromatography (HILIC). HILIC columns preferentially retain hydrophilic molecules which is well suited for phosphoproteomics.  Phosphorylated peptides tend to elute later in the chromatographic profile than the non phosphorylated counterparts. After fractionation, phosphopeptides are enriched using immobilized metal chromatography, which relies on charge-based affinities for phosphopeptide enrichment. At the end of this procedure the samples are ready to be quantitatively analyzed by mass spectrometry.

Quantitative Phosphoproteomics in Fatty Acid Stimulated Saccharomyces cerevisiae

Description of a quantitative phosphorylation procedure using cryolysis, urea solubilziation, HILIC fractionation and IMAC enrichment of phosphorylated peptides.

This protocol describes the growth and stimulation, with the fatty acid oleate, of isotopically heavy and light S. cerevisiae cells. Cells are ground ...

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent. In the experiment, yeast is grown for 48 hours in 1/2X YPD broth containing 3X glucose. The culture is split into a control and treated group. The experiment culture is treated with 0.5 mM H2O2 in Hanks Buffered Saline (HBSS) for 1 hour. The control culture is treated with HBSS only. Total RNA is extracted from both cultures and is converted to a biotin-labeled cRNA product through a multistep process. The final synthesis product is taken back to the UVM Microarray Core Facility and hybridized to the Affymetrix yeast GeneChips. The resulting gene expression data are uploaded into bioinformatics data analysis software.

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent.

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen ...

A Fluorescence Microscopy Assay for Monitoring Mitophagy in the Yeast Saccharomyces cerevisiae

Autophagy is important for turnover of cellular components under a range of different conditions. It serves an essential homeostatic function as well as a quality control mechanism that can target and selectively degrade cellular material including organelles1-4. For example, damaged or redundant mitochondria (Fig. 1), not disposed of by autophagy, can represent a threat to cellular homeostasis and cell survival. In the yeast, Saccharomyces cerevisiae, nutrient deprivation (e.g., nitrogen starvation) or damage can promote selective turnover of mitochondria by autophagy in a process termed mitophagy 5-9.
We describe a simple fluorescence microscopy approach to assess autophagy. For clarity we restrict our description here to show how the approach can be used to monitor mitophagy in yeast cells. The assay makes use of a fluorescent reporter, Rosella, which is a dual-emission biosensor comprising a relatively pH-stable red fluorescent protein linked to a pH-sensitive green fluorescent protein. The operation of this reporter relies on differences in pH between the vacuole (pH ~ 5.0-5.5) and mitochondria (pH ~ 8.2) in living cells. Under growing conditions, wild type cells exhibit both red and green fluorescence distributed in a manner characteristic of the mitochondria. Fluorescence emission is not associated with the vacuole. When subjected to nitrogen starvation, a condition which induces mitophagy, in addition to red and green fluorescence labeling the mitochondria, cells exhibit the accumulation of red, but not green fluorescence, in the acidic vacuolar lumen representing the delivery of mitochondria to the vacuole. Scoring cells with red, but not green fluorescent vacuoles can be used as a measure of mitophagic activity in cells5,10-12.

A Fluorescence Microscopy Assay for Monitoring Mitophagy in the Yeast Saccharomyces cerevisiae

A robust approach to monitor the delivery of organelles to the acidic lumen of the yeast vacuole for degradation and recycling is described. The method relies on the specific labeling of target organelles with a genetically encoded dual-emission fluorescence pH-biosensor, and visualization of individual cells using fluorescence microscopy.

Autophagy is important for turnover of cellular components under a range of different conditions. It serves an essential homeostatic function as well as a ...

Expression and Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein in Saccharomyces cerevisiae

The cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel, that when mutated, can give rise to cystic fibrosis in humans.There is therefore considerable interest in this protein, but efforts to study its structure and activity have been hampered by the difficulty of expressing and purifying sufficient amounts of the protein1-3. Like many 'difficult' eukaryotic membrane proteins, expression in a fast-growing organism is desirable, but challenging, and in the yeast S. cerevisiae, so far low amounts were obtained and rapid degradation of the recombinant protein was observed 4-9. Proteins involved in the processing of recombinant CFTR in yeast have been described6-9 .In this report we describe a methodology for expression of CFTR in yeast and its purification in significant amounts. The protocol describes how the earlier proteolysis problems can be overcome and how expression levels of CFTR can be greatly improved by modifying the cell growth conditions and by controlling the induction conditions, in particular the time period prior to cell harvesting. The reagants associated with this protocol (murine CFTR-expressing yeast cells or yeast plasmids) will be distributed via the US Cystic Fibrosis Foundation, which has sponsored the research. An article describing the design and synthesis of the CFTR construct employed in this report will be published separately (Urbatsch, I.; Thibodeau, P. et al., unpublished). In this article we will explain our method beginning with the transformation of the yeast cells with the CFTR construct - containing yeast plasmid (Fig. 1). The construct has a green fluorescent protein (GFP) sequence fused to CFTR at its C-terminus and follows the system developed by Drew et al. (2008)10. The GFP allows the expression and purification of CFTR to be followed relatively easily. The JoVE visualized protocol finishes after the preparation of microsomes from the yeast cells, although we include some suggestions for purification of the protein from the microsomes. Readers may wish to add their own modifications to the microsome purification procedure, dependent on the final experiments to be carried out with the protein and the local equipment available to them. The yeast-expressed CFTR protein can be partially purified using metal ion affinity chromatography, using an intrinsic polyhistidine purification tag. Subsequent size-exclusion chromatography yields a protein that appears to be &gt;90% pure, as judged by SDS-PAGE and Coomassie-staining of the gel.

Expression and Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein in Saccharomyces cerevisiae

Attempts to express the cystic fibrosis transmembrane conductance regulator (CFTR) in Saccharomyces cerevisiae have, until now, yielded relatively low amounts of protein. This protocol and the associated reagents distributed via the Cystic Fibrosis Foundation should allow the preparation of milligram amounts of this 'difficult' eukaryotic membrane protein.

The  cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride  channel, that when mutated, can give rise to cystic fibrosis in  ...

Visualization and Analysis of mRNA Molecules Using Fluorescence In Situ Hybridization in Saccharomyces cerevisiae

The Fluorescence in situ Hybridization (FISH) method allows one to detect nucleic acids in the native cellular environment. Here we provide a protocol for using FISH to quantify the number of mRNAs in single yeast cells. Cells can be grown in any condition of interest and then fixed and made permeable. Subsequently, multiple single-stranded deoxyoligonucleotides conjugated to fluorescent dyes are used to label and visualize mRNAs. Diffraction-limited fluorescence from single mRNA molecules is quantified using a spot-detection algorithm to identify and count the number of mRNAs per cell. While the more standard quantification methods of northern blots, RT-PCR and gene expression microarrays provide information on average mRNAs in the bulk population, FISH facilitates both the counting and localization of these mRNAs in single cells at single-molecule resolution.

Visualization and Analysis of mRNA Molecules Using Fluorescence In Situ Hybridization in Saccharomyces cerevisiae

This protocol describes an experimental procedure for performing Fluorescence in situ Hybridization (FISH) for counting mRNAs in single cells at single-molecule resolution.

The Fluorescence in situ Hybridization (FISH) method allows one to detect nucleic acids in the native cellular environment. Here we provide a protocol for ...

Coupled Assays for Monitoring Protein Refolding in Saccharomyces cerevisiae

Proteostasis, defined as the combined processes of protein folding/biogenesis, refolding/repair, and degradation, is a delicate cellular balance that must be maintained to avoid deleterious consequences 1. External or internal factors that disrupt this balance can lead to protein aggregation, toxicity and cell death. In humans this is a major contributing factor to the symptoms associated with neurodegenerative disorders such as Huntington's, Parkinson's, and Alzheimer's diseases 10. It is therefore essential that the proteins involved in maintenance of proteostasis be identified in order to develop treatments for these debilitating diseases. This article describes techniques for monitoring in vivo protein folding at near-real time resolution using the model protein firefly luciferase fused to green fluorescent protein (FFL-GFP). FFL-GFP is a unique model chimeric protein as the FFL moiety is extremely sensitive to stress-induced misfolding and aggregation, which inactivates the enzyme 12. Luciferase activity is monitored using an enzymatic assay, and the GFP moiety provides a method of visualizing soluble or aggregated FFL using automated microscopy. These coupled methods incorporate two parallel and technically independent approaches to analyze both refolding and functional reactivation of an enzyme after stress. Activity recovery can be directly correlated with kinetics of disaggregation and re-solubilization to better understand how protein quality control factors such as protein chaperones collaborate to perform these functions. In addition, gene deletions or mutations can be used to test contributions of specific proteins or protein subunits to this process. In this article we examine the contributions of the protein disaggregase Hsp104 13, known to partner with the Hsp40/70/nucleotide exchange factor (NEF) refolding system 5, to protein refolding to validate this approach.

Coupled Assays for Monitoring Protein Refolding in Saccharomyces cerevisiae

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.

Proteostasis, defined as the combined processes of protein folding/biogenesis, refolding/repair, and degradation, is a delicate cellular balance that must ...

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Mutation rates in young Saccharomyces cerevisiae cells measured through fluctuation tests are used to predict mutation frequencies for mother cells of different replicative ages. Magnetic sorting and flow cytometry are then used to measure actual mutation frequencies and age of mother cells to identify any deviations from predicted mutation frequencies.

Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this ...

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

Determining the mode of action of bioactive chemicals is of interest to a broad range of academic, pharmaceutical, and industrial scientists. Saccharomyces cerevisiae, or budding yeast, is a model eukaryote for which a complete collection of ~6,000 gene deletion mutants and hypomorphic essential gene mutants are commercially available. These collections of mutants can be used to systematically detect chemical-gene interactions, i.e. genes necessary to tolerate a chemical. This information, in turn, reports on the likely mode of action of the compound. Here we describe a protocol for the rapid identification of chemical-genetic interactions in budding yeast. We demonstrate the method using the chemotherapeutic agent 5-fluorouracil (5-FU), which has a well-defined mechanism of action. Our results show that the nuclear TRAMP RNA exosome and DNA repair enzymes are needed for proliferation in the presence of 5-FU, which is consistent with previous microarray based bar-coding chemical genetic approaches and the knowledge that 5-FU adversely affects both RNA and DNA metabolism. The required validation protocols of these high-throughput screens are also described.

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

Here we present a cost-effective method for defining chemical-genetic interactions in budding yeast. The approach is built on fundamental techniques in yeast molecular biology and is well suited for the mechanistic interrogation of small to medium collections of chemicals and other media environments.

Determining the mode of action of bioactive chemicals is of interest to a broad range of academic, pharmaceutical, and industrial scientists. ...

Growth-based Determination and Biochemical Confirmation of Genetic Requirements for Protein Degradation in Saccharomyces cerevisiae

Regulated protein degradation is crucial for virtually every cellular function. Much of what is known about the molecular mechanisms and genetic requirements for eukaryotic protein degradation was initially established in Saccharomyces cerevisiae. Classical analyses of protein degradation have relied on biochemical pulse-chase and cycloheximide-chase methodologies. While these techniques provide sensitive means for observing protein degradation, they are laborious, time-consuming, and low-throughput. These approaches are not amenable to rapid or large-scale screening for mutations that prevent protein degradation. Here, a yeast growth-based assay for the facile identification of genetic requirements for protein degradation is described. In this assay, a reporter enzyme required for growth under specific selective conditions is fused to an unstable protein. Cells lacking the endogenous reporter enzyme but expressing the fusion protein can grow under selective conditions only when the fusion protein is stabilized (i.e. when protein degradation is compromised). In the growth assay described here, serial dilutions of wild-type and mutant yeast cells harboring a plasmid encoding a fusion protein are spotted onto selective and non-selective medium. Growth under selective conditions is consistent with degradation impairment by a given mutation. Increased protein abundance should be biochemically confirmed. A method for the rapid extraction of yeast proteins in a form suitable for electrophoresis and western blotting is also demonstrated. A growth-based readout for protein stability, combined with a simple protocol for protein extraction for biochemical analysis, facilitates rapid identification of genetic requirements for protein degradation. These techniques can be adapted to monitor degradation of a variety of short-lived proteins. In the example presented, the His3 enzyme, which is required for histidine biosynthesis, was fused to Deg1-Sec62. Deg1-Sec62 is targeted for degradation after it aberrantly engages the endoplasmic reticulum translocon. Cells harboring Deg1-Sec62-His3 were able to grow under selective conditions when the protein was stabilized.

Growth-based Determination and Biochemical Confirmation of Genetic Requirements for Protein Degradation in Saccharomyces cerevisiae

This article describes a yeast growth-based assay for the determination of genetic requirements for protein degradation. It also demonstrates a method for rapid extraction of yeast proteins, suitable for western blotting to biochemically confirm degradation requirements. These techniques can be adapted to monitor degradation of a variety of proteins.