Summary

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

Published: June 23, 2018
doi:

Summary

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

Abstract

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-β peptide variants with their respective intrinsic aggregation propensities.

Introduction

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's, Parkinson's, and Huntington'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-β peptide Aβ42 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.

Protocol

1. S. cerevisiae Cultures and Protein Expression Note: Aβ variants exhibit different relative aggregation propensities due to a mutation in a single residue at position 19 (Phe19) of the Aβ42 peptide (Figure 1A). These peptide variants are tagged with green fluorescent protein (GFP), which acts as an aggregation reporter (Figure 1)29. Transform plasmids encoding for 20 Aβ42-…

Representative Results

This protocol describes how to employ a collection of 20 variants of the Aβ42 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,…

Discussion

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 …

Acknowledgements

   

Materials

Yeast cells BY4741  ATCC 201388 Genotype: MATa his3Δ1 leu2Δ0 met15Δ0 ura3Δ0
pESC(-Ura) plasmid  Agilent Genomics 217454 Yeast expression plasmid with a Gal promotor. Selectable marker URA3
Yeast Synthetic Drop-out Medium Supplements Sigma Y1501 Powder
Yeast Nitrogen Base Without Amino Acids Sigma Y0626 Powder
Raffinose Sigma R7630 Powder
Glucose Sigma G7021 Powder
Galactose Sigma G0750 Powder
Phosphate Buffered Saline (PBS) Fisher Scientific BP3991  Solution 10X
CellROX Deep Red Reagent  Life Technologies C10422 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. 
Y-PER protein extraction reagent  Thermo Scientific 78990 Liquid cell lysis buffer
Acrylamide/Bis-acrylamide Sigma A6050 Solution
Bradford dye reagent Bio-Rad  5000205 Dye reagent for one-step determination of protein concentration
β-amyloid antibody 6E10  BioLegend 803001 Mouse IgG1. The epitope lies within amino acids 3-8 of beta amyloid (EFRHDS).
Goat anti-mouse IgG-HRP conjugate  Bio-Rad 1721011
Membrane Immobilon-P, PVDF Millipore IPVH00010
Luminata forte Merk WBLUF0100 Premixed, ready to use chemiluminescent HRP detection reagent
Phenylmethanesulfonyl fluoride solution (PMSF) Sigma 93482 Protease inhibitor. Dissolved at 0.1 M in ethanol
FACSCanto flow cytometer  BD Biosciences 657338 Equipped with a 488 nm blue laser for the detection of GFP, and 635 nm red laser / 530/30 nm BP filter and 660/20 BP filter
Mini Trans-Blot Electrophoresis Transfer cell Bio-Rad 1703930 Protein transference system
Mini-PROTEAN Tetra Handcast Systems Bio-Rad 1658000FC Electrophoresis system

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Carija, A., Ventura, S., Navarro, S. Evaluation of the Impact of Protein Aggregation on Cellular Oxidative Stress in Yeast. J. Vis. Exp. (136), e57470, doi:10.3791/57470 (2018).

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