Name: Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism (Video) | JoVE Journal
Uploaded: 2018-09-30T14:00:00.000+00:00
Duration: 7 min 38 s
Description: Learn exponential growth kinetics in Saccharomyces cerevisiae to analyze respiratory and fermentative metabolism. This high-throughput method enables screening of compounds affecting yeast metabolic pathways.

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5 minutes

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;L of S. cerevisiae cells preserved in glycerol at -20 &#176;C. Incubate overnight in an orbital shaker at 30 &#176;C with agitation at 200 rpm.</li>
	<li>Streak a Petri dish (60 x 15 mm2) filled with sterile 2% YPD agar (add 10 g of yeast extract, 20 g of casein peptone, 20 g of glucose, and 20 g of bacteriological agar to 1,000 mL of distilled water) with the cells grown in the conical tube using a sterile loop. Incubate the Petri dish at 30 &#176;C until the isolated colonies show growth.</li>
	<li>Prepare the pre-inoculum by inoculating a single isolated colony into a conical tube filled with 10 mL of cool sterile 2% YPD broth and incubate it overnight at 30 &#176;C with continuous agitation at 200 rpm.</li>
</ol>
2. Culture Media and Growth Curves in Microplate
<ol>
	<li>Prepare 10 mL of 1% YPD broth (add 0.1 g of yeast extract, 0.2 g of peptone, and 0.1 g of glucose to 10 mL of distilled water), 10 mL of 2% YPD broth (add 0.1 g of yeast extract, 0.2 g of peptone, and 0.2 g of glucose to 10 mL of distilled water), and 10 mL of 10% YPD broth (add 0.1 g of yeast extract, 0.2 g of peptone, and 1 g of glucose to 10 mL of distilled water). Autoclave these growth mediums for 15 min at 121 &#176;C and 1.5 psi. 
	NOTE: The culture media serves as a control of fermentative growth.</li>
	<li>Prepare 10 mL of 2% yeast extract-peptone-ethanol (YPE) broth and 10 mL of 2% yeast extract-peptone-glycerol (YPG) broth. For 2% YPE: add 0.1 g of yeast extract, 0.2 g of peptone, and 0.2 mL of ethanol to 10 mL of distilled water. For 2% YPG: add 0.1 g of yeast extract, 0.2 g of peptone, and 0.2 mL of glycerol to 10 mL of distilled water. Autoclave these growth mediums for 15 min at 121 &#176;C and 1.5 psi. 
	NOTE: Glycerol and ethanol are non-fermentable carbon sources that are exclusively metabolized by mitochondrial respiration. For this reason, they are used as a respiratory growth controls. In this step, the type and concentration of carbon source in the culture media may be changed to test the effects on growth phenotype using yeast extract-peptone (YP) broth (10 g of yeast extract and 20 g of casein peptone in 1,000 mL of distilled water) as a base. To test the effects of other nutrients besides carbon, synthetic complete (SC) medium is supplemented according to the aim of the experiment. The base for SC medium is 1.8 g of yeast nitrogen base without amino acids, 5 g of ammonium sulfate [(NH4)2SO4], 1.4 g of monosodium phosphate (NaH2PO4), and 2 g of drop-out mix in 1,000 mL of distilled water. Supplement the media with a carbon source and additional nitrogen source in the needed concentrations.</li>
	<li>Add 145 &#956;L of suitable culture media for the experimental design to each well of a sterile microplate (10 x 10-well) with a lid and inoculate them with 5 &#956;L of the pre-inoculum. 
	NOTE: If the aim is to screen the influence of substances/compounds on the energetic metabolism of the yeast, that substance/compound should be added during this step. Also, any type of microplate with a lid should be useful.</li>
	<li>Incubate the multi-well plate in a microplate reader at 30 &#176;C with constant agitation at 200 rpm for 48 h. Measure the optical density (OD) at 600 nm every 30 or 60 min. 
	NOTE: If the microplate reader does not have the option to incubate the microplate, it may be incubated in an orbital shaker at the same conditions between every measurement of the OD.</li>
</ol>
3. Growth Curves in Shaken Conical Flasks
<ol>
	<li>Add 4.8 mL of the suitable culture media to 20 mL conical flasks and autoclave. Inoculate each flask with 200 &#956;L of the pre-inoculum culture at OD600nm ~2 in cool, sterile 2% YPD broth. Incubate them at 30 &#176;C with constant agitation at 250 rpm for 24 h. 
	NOTE: If the incubation period is higher than 24 h, add 12 mL of the suitable culture media to 50 mL conical flasks and autoclave. Inoculate them with 500 &#956;L of the pre-inoculum. It is also important to consider the fermentative growth controls (YP media with 1%, 2%, or 10% glucose) and respiratory growth controls (YP media with 2% glycerol or ethanol).</li>
	<li>Take 100 &#956;L of the shaken conical flask culture and dilute it in 900 &#956;L of distilled water in a 1 mL spectrophotometer cuvette, and gently mix by pipetting. Measure the OD at 600 nm using a spectrophotometer every 2 h. To obtain the real OD, multiply the result by ten.</li>
</ol>
4. Data Processing and Kinetic Parameters Calculation
<ol>
	<li>Create a new project file in the statistical package software. In the section of &#34;New table and graph&#34;, choose the &#34;XY&#34; option.
	<ol>
		<li>Select the option: &#34;Start with an empty data table&#34; in the &#34;Sample data&#34; section.</li>
		<li>Select the &#34;Points and connecting line&#34; graph type. Leave the &#34;X&#34; section unselected in the segment of &#34;Subcolumns for replicates or error values&#34;, and in the &#34;Y&#34; section choose the option: &#34;Enter (10) replicate values in side by side subcolumns and plot Mean and Error SD&#34;. Click the create button. 
		NOTE: The table format has one X column and several Y columns, each with the 10 subcolumns chosen previously.</li>
	</ol>
	</li>
	<li>Write the time at which OD measurements were taken in the X column (e.g., 0, 30, 60, 90 min or 0, 1, 1.5, 2 h). In the Y columns, write the OD values obtained from the cultures.</li>
	<li>Identify the exponential growth phase transforming the Y column data into logarithms. Click the &#34;Analyze&#34; button, choose the &#34;Transform&#34;&#160;analysis, select Y values using Y = Log(Y). Go to the &#34;Gallery of results&#34;, select &#34;Transform&#34;&#160;data table, click the &#34;Analyze&#34; button, and choose the &#34;Linear regression&#34;&#160;analysis. Exclude the OD values that do not follow a linear behavior. To exclude values, select them in the data table and type &#34;Ctrl + E&#34;. 
	NOTE: It is important to exclude values that not follow the exponential phase since the exponential growth equation fits well with the exponential phase.</li>
	<li>In the &#34;Data Tables gallery&#34;, select the data table &#34;Data 1&#34;. Click the &#34;Analyze&#34; button and choose the &#34;Nonlinear regression (curve fit)&#34;&#160;analysis among the &#34;XY analyses&#34;.</li>
	<li>Select the data sets to analyze and click the &#34;OK&#34; button. In the &#34;Fit&#34;&#160;tab choose the &#34;Exponential equation&#34; section and select the &#34;Exponential growth equation&#34;&#160;( , where X is cell concentration, X0 is cell concentration at zero time, &#956; is specific growth rate, and t is time). Use the &#34;Least squares fit&#34; as a fitting method and leave unselected the interpolate section. Click the &#34;OK&#34; button. 
	NOTE: The tab with the nonlinear fit results is in the &#34;Gallery of results&#34;. The software calculates doubling time (Dt) and specific growth rate (&#956;). The software shows &#956; as K in the results tab.</li>
	<li>Open a new project file, and in the &#34;New table and graph&#34;&#160;section, select the column choice. Choose the option &#34;Start with an empty data table&#34; and select the desired graph. Choose to plot the mean with the SD. Select the &#34;Create&#34; button.</li>
	<li>Copy the &#956; or Dt values from the nonlinear fit results tab that is in the &#34;Gallery of results&#34;&#160;and paste them in a column. Finally, select the &#34;Analyze&#34; button and choose the desired analysis in the&#160;&#34;Column analyses&#34;&#160;section to compare the kinetic parameters of the different nutrimental conditions. 
	NOTE: The kinetic parameters obtained from the fermentative growth controls (YP media with 1%, 2%, or 10% glucose) and respiratory growth controls (YP media with 2% glycerol or ethanol) helps establish the threshold of fermentative and mitochondrial respiration, respectively. Comparing the kinetic parameters from the nutritional condition and substance/compound assayed with the respiratory and fermentative growth help identify possible effect on respiratory or fermentative metabolism.</li>
</ol>

<ol><li>Parrella, E., Longo, V. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+chronological+life+span+of+Saccharomyces+cerevisiae+to+study+mitochondrial+dysfunction+and+disease%5BTitle%5D)+AND+%22Methods%22%5BJournal%5D)">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/pubmed?term=((The+role+of+glycolysis-derived+hexose+phosphates+in+the+induction+of+the+Crabtree+effect%5BTitle%5D)+AND+%22Journal+of+Biological+Chemistry%22%5BJournal%5D)">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/pubmed?term=((Warburg+effect+or+reverse+Warburg+effect%3F+A+review+of+cancer+metabolism%5BTitle%5D)+AND+%22Oncology+Research+and+Treatment%22%5BJournal%5D)">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/pubmed?term=((The+Crabtree+effect%3A+a+regulatory+system+in+yeast%5BTitle%5D)+AND+%22Journal+of+General+Microbiology%22%5BJournal%5D)">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/pubmed?term=((Analysis+of+the+yeast+short-term+Crabtree+effect+and+its+origin%5BTitle%5D)+AND+%22The+FEBS+Journal%22%5BJournal%5D)">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/pubmed?term=((The+Crabtree+and+Warburg+effects%3A+Do+metabolite-induced+regulations+participate+in+their+induction%3F%5BTitle%5D)+AND+%22Biochim+Biophys+Acta%22%5BJournal%5D)">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/pubmed?term=((Antimetabolic+Effects+of+Polyphenols+in+Breast+Cancer+Cells%3A+Focus+on+Glucose+Uptake+and+Metabolism%5BTitle%5D)+AND+%22Frontiers+in+Nutrition%22%5BJournal%5D)">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/pubmed?term=((An+evolutionary+perspective+on+the+Crabtree+effect%5BTitle%5D)+AND+%22Frontiers+in+Molecular+Biosciences%22%5BJournal%5D)">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/pubmed?term=((Interactions+between+carbon+and+nitrogen+sources+depend+on+RIM15+and+determine+fermentative+or+respiratory+growth+in+Saccharomyces+cerevisiae%5BTitle%5D)+AND+%22Applied+Microbiology+and+Biotechnology%22%5BJournal%5D)">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="https://www.annualreviews.org/doi/10.1146/annurev.mi.03.100149.002103">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="https://www.sciencedirect.com/science/article/pii/S0022247X07002260">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/pubmed?term=((Classical+mathematical+models+for+description+and+prediction+of+experimental+tumor+growth%5BTitle%5D)+AND+%22Public+Library+of+Science+Computational+Biology%22%5BJournal%5D)">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/pubmed?term=((Resveratrol+induces+mitochondrial+dysfunction+and+decreases+chronological+life+span+of+Saccharomyces+cerevisiae+in+a+glucose-dependent+manner%5BTitle%5D)+AND+%22Journal+of+Bioenergetics+and+Biomembranes%22%5BJournal%5D)">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/pubmed?term=((Energy-dependent+effects+of+resveratrol+in+Saccharomyces+cerevisiae%5BTitle%5D)+AND+%22Yeast%22%5BJournal%5D)">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/pubmed?term=((Microbial+growth+curves%3A+what+the+models+tell+us+and+what+they+cannot%5BTitle%5D)+AND+%22Critical+Reviews+in+Food+Science+and+Nutrition%22%5BJournal%5D)">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>

The authors have nothing to disclose.

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><tbody><tr><td>Orbital Shaker</td><td>Thermo Scientific</td><td>4353</td><td>For inoculum incubation or conical fask cultures</td></tr><tr><td>Bioscreen&amp;nbsp;</td><td>Growth curves</td><td>C MBR</td><td>For batch cultures in microplates</td></tr><tr><td>Glucose</td><td>Sigma&amp;nbsp;</td><td>G7021</td><td>For YPD broth preparation</td></tr><tr><td>Peptone from casein, enzymatic digest</td><td>Sigma&amp;nbsp;</td><td>82303</td><td>For YPD broth preparation</td></tr><tr><td>Yeast extract</td><td>Sigma&amp;nbsp;</td><td>09182-1KG-F</td><td>For YPD broth preparation</td></tr><tr><td>Bacteriological Agar</td><td>Sigma&amp;nbsp;</td><td>A5306</td><td>For YPD agar preparation</td></tr><tr><td>NaH&lt;sub&gt;2&lt;/sub&gt;PO&lt;sub&gt;4&lt;/sub&gt;</td><td>Sigma&amp;nbsp;</td><td>S8282</td><td>For SC broth preparation</td></tr><tr><td>(NH&lt;sub&gt;4&lt;/sub&gt;)&lt;sub&gt;2&lt;/sub&gt;SO&lt;sub&gt;4&lt;/sub&gt;</td><td>Sigma&amp;nbsp;</td><td>A4418</td><td>For SC broth preparation</td></tr><tr><td>Yeast nitrogen base without amino acids and ammonium sulfate</td><td>Sigma&amp;nbsp;</td><td>Y1251</td><td>For SC broth preparation</td></tr><tr><td>Yeast synthetic drop-Out medium supplements</td><td>Sigma&amp;nbsp;</td><td>Y1501</td><td>For SC broth preparation</td></tr><tr><td>Ammonium sulfate granular</td><td>J.T. Baker</td><td>0792-R</td><td>For medium supplementation example</td></tr><tr><td>Resveratrol</td><td>Sigma&amp;nbsp;</td><td>R5010</td><td>For medium supplementation example</td></tr><tr><td>Galactose</td><td>Sigma&amp;nbsp;</td><td>G8270</td><td>For medium supplementation example</td></tr><tr><td>Sucrose</td><td>Sigma&amp;nbsp;</td><td>S7903</td><td>For medium supplementation example</td></tr><tr><td>Absolut ethanol</td><td>Merck</td><td>107017</td><td>For medium supplementation example</td></tr><tr><td>Glycerol</td><td>J.T. Baker</td><td>2136-01</td><td>For medium supplementation example</td></tr><tr><td>GraphPad Prism</td><td>GraphPad Software</td><td></td><td>For data analysis</td></tr><tr><td>Honeycomb microplates</td><td>Thermo Scientific</td><td>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 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...

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

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Learn exponential growth kinetics in Saccharomyces cerevisiae to analyze respiratory and fermentative metabolism. This high-throughput method enables screening of compounds affecting yeast metabolic pathways.

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

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