1. S. cerevisiae Cultures and Protein Expression
Note: A&#946; variants exhibit different relative aggregation propensities due to a mutation in a single residue at position 19 (Phe19) of the A&#946;42 peptide (Figure 1A). These peptide variants are tagged with green fluorescent protein (GFP), which acts as an aggregation reporter (Figure 1)29.
<ol>
	<li>Transform plasmids encoding for 20 A&#946;42-...

<ol>
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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=Alpha-synuclein+blocks+ER-Golgi+traffic+and+Rab1+rescues+neuron+loss+in+Parkinson's+models.">Alpha-synuclein blocks ER-Golgi traffic and Rab1 rescues neuron loss in Parkinson's models.</a> Science. 313, 324-328 (2006).</li><li>Johnson, B. S., McCaffery, J. M., Lindquist, S., Gitler, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+yeast+TDP-43+proteinopathy+model:+exploring+the+molecular+determinants+of+TDP-43+aggregation+and+cellular+toxicity.">A yeast TDP-43 proteinopathy model: exploring the molecular determinants of TDP-43 aggregation and cellular toxicity.</a> Proceedings of the National Academy of Sciences of the United States of America. 105, 6439-6444 (2008).</li><li>Bharathi, V., 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=Use+of+ade1+and+ade2+mutations+for+development+of+a+versatile+red/white+color+assay+of+amyloid-induced+oxidative+stress+in+saccharomyces+cerevisiae.">Use of ade1 and ade2 mutations for development of a versatile red/white color assay of amyloid-induced oxidative stress in saccharomyces cerevisiae.</a> Yeast. 33, 607-620 (2016).</li><li>Pallar&#232;s, I., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+the+prediction+of+protein+aggregation+propensity.">Advances in the prediction of protein aggregation propensity.</a> Current Medicinal Chemistry. , (2017).</li><li>Villar-Piqu&#233;, A., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+aggregation+propensity+is+a+crucial+determinant+of+intracellular+inclusion+formation+and+quality+control+degradation.">Protein aggregation propensity is a crucial determinant of intracellular inclusion formation and quality control degradation.</a> Biochimica et Biophysica Acta. 1833, 2714-2724 (2013).</li><li>Navarro, S., Villar-Piqu&#233;, A., Ventura, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Selection+against+toxic+aggregation-prone+protein+sequences+in+bacteria.">Selection against toxic aggregation-prone protein sequences in bacteria.</a> Biochimica et Biophysica Acta. 1843, 866-874 (2014).</li><li>Morell, M., de Groot, N. 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A wide range of diseases is linked to the accumulation of misfolded proteins into cellular deposits6,7,8,33. Many efforts have been made to unravel the molecular mechanisms that trigger the onset of these diseases using computational approaches, which do not take into account protein concentrations, or in vitro approaches, in which the protein concentration remains constant during the ...

Proteostasis is a fundamental determinant of cell fitness and aging processes. In cells, protein homeostasis is maintained by sophisticated protein quality control networks aimed to ensure the correct refolding of misfolded protein conformers by chaperones and/or their targeted proteolysis with several well-conserved mechanisms1,2,3,4,5. A large number of studies provide support to the link between the onset and progression of a broad range of human diseases and the failure of proteostasis, leading to protein misfolding and aggregation. For instance, the presence of protein deposits is considered a pathological hallmark of many neurodegenerative disorders, such as Alzheimer&#39;s, Parkinson&#39;s, and Huntington&#39;s diseases6,7,8, prionogenic diseases, and non-degenerative amyloidoses9. It has been suggested that early oligomeric and protofibrillar assemblies in the aggregation reaction are the main elicitors of cytotoxicity, establishing aberrant interactions with other proteins in the crowded cellular milieu10. In addition, protein inclusions (PI) can be transmitted between cells, propagating their toxic effect11,12. Therefore, it could be that the formation of PI might indeed constitute a detoxifying mechanism that restricts the presence of dangerous aggregated species to specific locations in the cell, where they can be processed or accumulated without major side effects13,14.
Standard in vitro biochemical approaches have provided important insights into the different species that populate aggregation reactions and their properties15,16. However, the conditions used in these assays are clearly different from those occurring within the cell and, therefore, question their physiological relevance. Because of the notable conservation of cellular pathways such as protein quality control, autophagy, or the regulation of the cellular redox state17,18 among eukaryotes19,20,21,22,23, the budding yeast Saccharomyces cerevisiae (S. cerevisiae) has emerged as a privileged simple cellular model to study the molecular determinants of protein aggregation and its associated cytotoxic impact in biologically relevant environments24,25,26.
Protein aggregation propensity is a feature inherently encoded in the primary sequence. Thus, the formation of amyloid-like structures can be predicted based on the identification and evaluation of the potency of aggregation-promoting regions in polypeptides27. However, despite the success of bioinformatic algorithms to predict the in vitro aggregation properties of protein sequences, they are still far from forecasting how these propensities translate into in vivo cytotoxic impact. Studies that address the link between the aggregated state of a given protein and its associated cellular damage in a systematic manner may help to circumvent this computational limitation. This connection is addressed in the present study, taking advantage of a large set of variants of the amyloid-&#946; peptide A&#946;42 differing only in a single residue, but displaying a continuous range of aggregation propensities in vivo28. In particular, an FC-based approach to identify the conformational species accounting for the oxidative damage elicited by aggregation-prone proteins in yeast cells is described. The methodology provides many advantages such as simplicity, high-throughput capability, and accurate quantitative measurement. This approach made it possible to confirm that PI play a protective role against oxidative stress.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Yeast cells BY4741&#160;</td>
			<td>ATCC</td>
			<td>201388</td>
			<td>Genotype: MATa his3&#916;1 leu2&#916;0 met15&#916;0 ura3&#916;0</td>
		</tr>
		<tr>
			<td>pESC(-Ura) plasmid&#160;</td>
			<td>Agilent Genomics</td>
			<td>217454</td>
			<td>Yeast expression plasmid with a Gal promotor. Selectable marker URA3</td>
		</tr>
		<tr>
			<td>Yeast Synthetic Drop-out Medium Supplements</td>
			<td>Sigma</td>
			<td>Y1501</td>
			<td>Powder</td>
		</tr>
		<tr>
			<td>Yeast Nitrogen Base Without Amino Acids</td>
			<td>Sigma</td>
			<td>Y0626</td>
			<td>Powder</td>
		</tr>
		<tr>
			<td>Raffinose</td>
			<td>Sigma</td>
			<td>R7630</td>
			<td>Powder</td>
		</tr>
		<tr>
			<td>Glucose</td>
			<td>Sigma</td>
			<td>G7021</td>
			<td>Powder</td>
		</tr>
		<tr>
			<td>Galactose</td>
			<td>Sigma</td>
			<td>G0750</td>
			<td>Powder</td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline (PBS)</td>
			<td>Fisher Scientific</td>
			<td>BP3991&#160;</td>
			<td>Solution 10X</td>
		</tr>
		<tr>
			<td>CellROX Deep Red Reagent&#160;</td>
			<td>Life Technologies</td>
			<td>C10422</td>
			<td>Free radical cell-permeant fluorescent sensor, non-fluorescent while in a reduced state, and exhibits bright fluorescence upon oxidation by reactive oxygen species (ROS), with absorption/emission maxima at 644/665 nm.&#160;</td>
		</tr>
		<tr>
			<td>Y-PER protein extraction reagent&#160;</td>
			<td>Thermo Scientific</td>
			<td>78990</td>
			<td>Liquid cell lysis buffer</td>
		</tr>
		<tr>
			<td>Acrylamide/Bis-acrylamide</td>
			<td>Sigma</td>
			<td>A6050</td>
			<td>Solution</td>
		</tr>
		<tr>
			<td>Bradford dye reagent</td>
			<td>Bio-Rad&#160;</td>
			<td>5000205</td>
			<td>Dye reagent for one-step determination of protein concentration</td>
		</tr>
		<tr>
			<td>&#946;-amyloid antibody 6E10&#160;</td>
			<td>BioLegend</td>
			<td>803001</td>
			<td>Mouse IgG1. The epitope lies within amino acids 3-8 of beta amyloid (EFRHDS).</td>
		</tr>
		<tr>
			<td>Goat anti-mouse IgG-HRP conjugate&#160;</td>
			<td>Bio-Rad</td>
			<td>1721011</td>
			<td></td>
		</tr>
		<tr>
			<td>Membrane Immobilon-P, PVDF</td>
			<td>Millipore</td>
			<td>IPVH00010</td>
			<td></td>
		</tr>
		<tr>
			<td>Luminata forte</td>
			<td>Merk</td>
			<td>WBLUF0100</td>
			<td>Premixed, ready to use chemiluminescent HRP detection reagent</td>
		</tr>
		<tr>
			<td>Phenylmethanesulfonyl fluoride solution (PMSF)</td>
			<td>Sigma</td>
			<td>93482</td>
			<td>Protease inhibitor. Dissolved at 0.1 M in ethanol</td>
		</tr>
		<tr>
			<td>FACSCanto flow cytometer&#160;</td>
			<td>BD Biosciences</td>
			<td>657338</td>
			<td>Equipped with a 488&#160;nm blue laser for the detection of GFP, and 635&#160;nm red laser / 530/30 nm BP filter and 660/20 BP filter</td>
		</tr>
		<tr>
			<td>Mini Trans-Blot Electrophoresis Transfer cell</td>
			<td>Bio-Rad</td>
			<td>1703930</td>
			<td>Protein transference system</td>
		</tr>
		<tr>
			<td>Mini-PROTEAN Tetra Handcast Systems</td>
			<td>Bio-Rad</td>
			<td>1658000FC</td>
			<td>Electrophoresis system</td>
		</tr>
	</tbody>
</table>

evaluation of the impact of protein aggregation on cellular oxidative stress in yeast

Protein misfolding and aggregation into amyloid conformations have been related to the onset and progression of several neurodegenerative diseases. However, there is still little information about how insoluble protein aggregates exert their toxic effects in vivo. Simple prokaryotic and eukaryotic model organisms, such as bacteria and yeast, have contributed significantly to our present understanding of the mechanisms behind the intracellular amyloid formation, aggregates propagation, and toxicity. In this protocol, the use of yeast is described as a model to dissect the relationship between the formation of protein aggregates and their impact on cellular oxidative stress. The method combines the detection of the intracellular soluble/aggregated state of an amyloidogenic protein with the quantification of the cellular oxidative damage resulting from its expression using flow cytometry (FC). This approach is simple, fast, and quantitative. The study illustrates the technique by correlating the cellular oxidative stress caused by a large set of amyloid-&#946; peptide variants with their respective intrinsic aggregation propensities.

This protocol describes how to employ a collection of 20 variants of the A&#946;42 peptide where Phe19 has been mutated to all natural proteinogenic amino acids28. The theoretical aggregation propensities of these proteins can be analyzed using two different bioinformatic algorithms (AGGRESCAN and TANGO31,32). In both cases, this analysis renders a progressive gradation of aggregation tendencies, ascribing,...

Watch this Scientific Journal Video about Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast at JoVE.com

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

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-&#946; peptide.

Protein misfolding and aggregation into amyloid conformations have been related to the onset and progression of several neurodegenerative diseases. ...

The overall goal of this procedure is to determine the relationship between the formation of intracellular protein aggregates and their impact on cellular oxidative stress using the baker's yeast Saccharomyces cerevisiae. This method can help answer key questions in the field of protein misfolding and aggregation diseases, such as neurodegenerative disorders and non-neuropathic amyloidoses. The main advantage of this technique is that it's simple, fast, and allows quantification of the cellular oxidative stress damage in a large yeast population.With this method, we can provide insight into the correlation between intracellular soluble or aggregated state of an amyloidogenic protein with oxidative stress levels in yeast. In addition, it can also be applied to other model organisms expressing recombinant proteins. Demonstrating the flow cytometry analysis will be Manuela Costa, a technician from the Flow Cytometry Facility at the UAB.In this study, the intracellular aggregation state of different A-beta-42 peptide variants is tracked using S.cerevisiae transformed with a plasmid encoding for A-beta-42 fused to GFP under the control of a galactose-inducible promoter. Pick one colony of the transformed yeast cells, and inoculate into 20 milliliters of SC minus Ura medium containing 2%glucose. Grow the culture at 30 degrees Celsius under agitation overnight.On the following day, inoculate 100 microliters of the overnight culture into five milliliters of fresh SC minus Ura medium, and grow the cells at 30 degrees Celsius for two to three hours. When the culture is at an optical density at 590 nanometers or OD 590 of 0.5, centrifuge the culture at 3, 000 times g for four minutes, discard the supernatant, and resuspend the cells in five milliliters of fresh SC minus Ura medium containing 2%raffinose. Incubate the cells at 30 degrees Celsius under agitation for 30 minutes.After 30 minutes, centrifuge the cells at 3, 000 times g for four minutes, discard the supernatant, and resuspend the cells in fresh SC minus Ura medium containing 2%galactose to induce recombinant protein expression. Return the cells to the incubator for 16 hours. After 16 hours, harvest the cells by transferring one-milliliter aliquots of the culture to sterile microcentrifuge tubes and centrifuging at 3, 000 times g for four minutes.Begin this procedure by determining the OD 590 of the 16-hour-induced yeast cells. Then dilute the cells in sterile PBS to an OD 590 of 0.1. Transfer the expressing cell suspensions to appropriately labeled round-bottom polystyrene tubes, and protect them from light.Prepare non-induced cells as a negative control for the flow cytometry analysis. Add the oxidative stress probe to each sample at a final concentration of five micromolar. Cover the samples with aluminum foil, and incubate at 30 degrees Celsius for 30 minutes.When the incubation is done, spin down the cells, remove the supernatant, and resuspend the cell pellets in PBS. Wash the cells three times in this manner with PBS. After the third wash, resuspend the cells in the same volume of PBS.Make sure non-stained cells are included in the flow cytometry analysis. Using the appropriate lasers and filters, perform the flow cytometry analysis to detect GFP and the fluorescent signal of the oxidative stress probe. Start by clicking on the Open New Worksheet panel, and give the experiment a name.From the toolbar, select the Scatter Plot Tool, and create a plot with the variables Side Scatter Area on the y-axis versus Forward Scatter Area in a linear scale on the x-axis. Click the Scatter Plot Tool, and create a plot with the variables FITC Area on the x-axis versus APC Area in a logarithmic scale on the y-axis. Click the Instrument Setting icon, and set all compensation levels to zero in the Compensation tab.Then click on the Acquisition tab, and select a total number of 20, 000 events to be recorded with a low flow rate. Because the fluorescent emission signal of one fluorochrome can be detected by another detector, it is important to perform a compensation process to equalize the min signal of each fluorochrome in all detectors by a single-color control. Rename tube 001 as negative control, and click the Acquire tab to start running the non-induced, unstained cells.Adjust the voltage in the Instrument Settings of the forward and side scatter until the population is distributed in the middle left quadrant. Click on the Polygon icon to set a region R1 around the cell population excluding cell debris, and use this gated population P1 equals R1 for all fluorescent dot plots and histogram representations. To adjust the PMT voltage of the fluorescence signal, run the unstained cells in the FL1 to FL3 dot plot, tuning the gain in the Instrument Setting tab, until the cells are distributed in the lower left quadrant.Using the Scatter Plot Tool, create a dot plot with the variables FITC-A in the x-axis versus FSC-A and a second dot plot with the variables APC-A in the x-axis versus FSC-A. Next, change the sample to the induced cells to measure GFP fluorescence. In the Instrument Setting tab, set the gain in the FSC-A versus FITC when the population is distributed in the low right quadrant.Define the GFP-positive cell population with a gate. Change the sample to the non-induced stained cells. Display oxidative stress by the fluorescence on an FSC-A versus APC-A dot plot.Tune the gain until the cell population is distributed in the left upper quadrant. Gate the positive cell population in P3.With the Histogram icon, make two histogram plots to represent the cell fluorescence, one for FITC and another for APC fluorescence. Create a table displaying the mean fluorescent intensity and median fluorescence with its corresponding standard error and/or the coefficient of variance for GFP fluorescence and oxidative stress levels.Click the Compensation tab, and set all compensation levels to zero. Click on the Acquisition tab, and select a total number of 20, 000 events to be recorded. Prepare three new tubes of samples, and name them non-induced, induced soluble, and induced aggregated.Acquire data from the samples with the preset settings. Analyze the data by opening a new sheet and creating a dot plot for the variables FITC-A and APC-A, gating the positive cells for CellROX staining. For each sample, create a statistics table with the mean fluorescence and the standard error for the FITC and APC channels.It is also possible to sort cells with a FACS sorter following the aggregated protein counting. Yeast cells expressing A-beta-42 variants after an induction period of 16 hours are visualized under a fluorescence microscope to determine the recombinant protein distribution inside the cells. These images are representative of selected A-beta-42 GFP variants.The formation of protein inclusions, or PI, was confirmed in 10 out of the 20 variants from the analyzed collection. This bar graph indicates the percentage of cells containing different numbers of PI calculated from a total of 500 fluorescent cells for each variant into biological replicates. An excellent agreement between predicted and in vivo aggregation properties was observed.The protein expression levels in cellular extracts were quantified using an A-beta-specific antibody. As a general trend, PI-forming A-beta-42 variants, colored in green, are present at lower levels than those diffusely distributed in the cytosol, colored in red. Important differences among A-beta-42 variants were observed when their oxidative stress probe fluorescence, protein levels, and GFP fluorescence properties were represented relative to their ability to form PI and their intrinsic aggregation propensities predicted by either the AGGRESCAN or TANGO bioinformatics algorithm.The PI-forming variants are in green, and the non-PI-forming variants are in red. Following this procedure, other methods such as propidium iodide or annexin V staining can be also performed to answer additional questions like determining the impact of an intracellular expressed protein variant on cell apoptosis or cytotoxicity.

evaluation-impact-protein-aggregation-on-cellular-oxidative-stress

Research

JoVE Journal

Biochemistry

7.2K Views.  Universitat Autònoma de Barcelona. The overall goal of this procedure is to determine the relationship between the formation of intracellular protein aggregates and their impact on cellular oxidative stress using the baker's yeast Saccharomyces cerevisiae. This method can help answer key questions in the field of protein misfolding and aggregation diseases, such as neurodegenerative disorders and non-neuropathic amyloidoses. The main advantage of this technique is that it's simple, fast, and allows quantification of the cellul...