TY - JOUR
AU - Petranovic, Dina
AB - Alzheimer's disease (AD) is the most common neurodegenerative disease, characterized by deposits of amyloid-β (Aβ) peptides. However, the underlying molecular mechanisms of neuron cell dysfunction and cell death in AD still remain poorly understood. Yeast Saccharomyces cerevisiae shares many conserved biological processes with all eukaryotic cells, including human neurons. Thanks to relatively simple and quick genetic and environmental manipulations, the large knowledge base and data collections, this organism has become a valuable tool to unravel fundamental intracellular mechanisms underlying neurodegeneration. In this study, we have used yeast as a model system to study the effects of intracellular Aβ peptides and we found that cells constitutively producing native Aβ directed to the secretory pathway exhibited a lower growth rate, lower biomass yield, lower respiratory rate, increased oxidative stress, hallmarks of mitochondrial dysfunction and ubiquitin–proteasome system dysfunction. These findings are relevant for better understanding the role of Aβ in cell stress and cell damage. Amyloid-β, Alzheimer's disease, yeast, mitochondria, oxidative stress, ubiquitin-proteasome system INTRODUCTION Alzheimer's disease (AD) is the most common progressive neurodegenerative disease and is responsible for 60–80% of dementia cases (Ferri et al.2005). It affects approximately 36 million people worldwide, and due to increasing longevity of the human population will become the world's leading cause of death by 2050 (Williams 2009). AD is pathologically characterized by the presence of extracellular plaques comprised of amyloid-β (Aβ) peptide (Hardy and Selkoe 2002). Aβ peptides (ranging in length from 38 to 43 amino acids) are proteolytic products of the amyloid precursor protein (APP) and are sequentially cleaved by β- and γ-secretases (Selkoe 2001). Mutations in the APP protein or the γ-secretases cause familial AD, and the mutations direct the APP cleavage towards the Aβ42 peptide production, that predominates in cerebral plaques. Aβ42 peptide is more hydrophobic and thus more prone to fibril formation (Selkoe and Wolfe 2007) and increasing evidence suggests that small oligomers of Aβ are the most toxic species (Hartley et al.1999; McLean et al.1999). In neurons, the cleavage of APP to generate the Aβ peptide occurs within the secretory and endosomal pathways (Thinakaran and Koo 2008). Although the extracellular amyloid plaques and oligomeric species of Aβ are considered important hallmarks of AD, emerging evidence from transgenic mice experiments and studies of patients in the clinic indicates that the Aβ can also accumulate within the cells, which may contribute to disease onset or progression (LaFerla, Green and Oddo 2007). It has been proposed that senile plaques originated from intraneuronal Aβ as a result of its release after neuronal death (Gouras et al.2000). Intracellular Aβ has been pointed out to be involved in early stages of the pathogenesis, directly causing neurotoxicity and initiating AD (Takahashi et al.2002; Knobloch et al.2007). There is growing evidence suggesting that alterations in energy metabolism are among the earliest events that occur in the AD-affected brain (Fukui and Moraes 2008). Mitochondria produce most of the ATP, and they are key regulators of cell survival and cell death, hence playing a central role in aging and AD onset and progression. Increasing evidence shows the occurrence of impaired mitochondrial functions in AD patients and in different models, such as impaired electron transfer, ATP synthesis, mitochondrial transcription, mitochondrial pre-protein maturation and protein synthesis, upregulation of voltage-dependent anion channel, decreased mitochondrial membrane potential, as well as increased production of reactive oxygen species (ROS) (Aleardi et al.2005; Matsumoto et al.2006; Crouch et al.2008; Yao et al.2009; Manczak et al.2010; Calkins et al.2011; Mossmann et al.2014). Nevertheless, the precise mechanism of mitochondrial dysfunction in AD pathogenesis still remains uncertain. Although different biological model systems have been used to study the role of Aβ, the complexity of AD has still prevented a comprehensive understanding of Aβ toxicity (Link 1995; Magrane et al.2004; Crowther et al.2005). Yeast Saccharomyces cerevisiae is a single cell eukarya organism that can be used as a model to study conserved biological processes, but it can also be used to study human proteins in so-called humanized yeast models which can be a valuable tool to study intracellular toxicity of Aβ. This model system has excellent genetic and molecular tools that can be used for molecular and cell biology, systems biology, single cell methods and also for screening chemical libraries that might modulate amyloid toxicity (Petranovic and Nielsen 2008; Khurana and Lindquist 2010; Munoz et al.2012; Mirisola, Braun and Petranovic 2014). During the last decade, S. cerevisiae has been exploited to study toxicity, aggregation and localization of Aβ or as screening tool for identification of compounds influencing Aβ oligomerization (Zhang et al.1997; Komano et al.1998; Caine et al.2007; Macreadie et al.2008; Winderickx et al.2008). However, in these previous studies, Aβ was expressed in the cytosol and recent studies in yeast showed that the secretory pathway is important for the generation of Aβ toxic species (Treusch et al.2011; D'Angelo et al.2013). The completely unbiased screen of compounds was performed for rescue of Aβ toxicity (Matlack et al.2014). Additionally, the previous models used either inducible expression systems (Treusch et al.2011) or non-native versions of Aβ peptide (D'Angelo et al.2013). Here we describe a yeast model of Aβ cellular toxicity that expresses native Aβ-peptides (Aβ40 and Aβ42), which are constitutively expressed, and possess the endoplasmic reticulum (ER) signal sequence for secretion. We demonstrate that this system produced Aβ40 and Aβ42 monomers and oligomers and induced cytotoxicity in yeast. Additionally, we found a decrease in the mitochondrial functions which was accompanied by an elevated production of ROS and reduced proteasomal activities. This model could also be developed as a discovery platform for screening of compounds that revert Aβ toxicity. MATERIALS AND METHODS Yeast strains, plasmids and standard growth conditions All yeast strains used in this work are derivatives of S. cerevisiae CEN.PK 113–11C (MATα his3Δ1 ura3–52 MAL2–8c SUC2). Plasmid constructions were performed following standard molecular biology techniques using Escherichia coli DH5α stain (fhuA2 Δ (argF-lacZ) U169 phoA glnV44 Φ80 Δ(lacZ)M15 gyrA96 recA1 relA1 endA1 thi-1 hsdR17). The different yeast shuttle plasmids were used for the expression of Aβ in yeast (listed in Table 1). The ER targeting signal sequence from Kar2 and Aβ42/ Aβ40 sequences were amplified by PCR from pDONR221-Aβ42 and pDONR221-Aβ40 plasmids (kindly provided by Prof. Susan Lindquist, Whitehead Institute for Biomedical Research at MIT). The yeast transformations were performed using a standard lithium acetate method and selected on synthetic dextrose plates SD-Ura−. For cultivation, all stains were grown at 30°C either in liquid SD-Ura− media (0.067% yeast nitrogen base, 2% glucose excluding uracil) or Delft medium (0.5% (NH4)2SO4, 0.3% of KH2PO4, 0.05% of MgSO4·7H2O, 0.1% vitamin solution and 0.1% trace metal solution, 2% ethanol, pH 6.5) as described previously (Chen et al.2013). Table 1. Plasmids and strains used in this study. Plasmid or strain  Relevant genotype  Reference  Plasmid      p416 ADH  CEN, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p416 TEF  CEN, TEF1 promoter, URA3 marker  Mumberg et al. (1995)  p416 GPD  CEN, GPD1 promoter, URA3 marker  Mumberg et al. (1995)  p426 ADH  2μ, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p426 TEF  2μ, TEF1 promoter, URA3 marker,  Mumberg et al. (1995)  p416 ADH-Kar2-Aβ42  p416 ADH with Kar2 and Aβ42 sequence  This study  p416 TEF-Kar2-Aβ42  p416 TEF with Kar2 and Aβ42 sequence  This study  p426 ADH-Kar2-Aβ42  p426 ADH with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ42  p416 GPD with Kar2 and Aβ42 sequence  This study  p426 TEF-Kar2-Aβ42  p426 TEF with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ40  p416 GPD with Kar2 and Aβ40 sequence  This study  Strain      CEN.PK 113–11C  MATα his3Δ1 ura3–52 MAL2–8c SUC2  This study  P416 EP  CEN.PK 113–11C/p416 GPD  This study  P426 EP  CEN.PK 113–11C/p426 ADH  This study  p416 ADH-Aβ42  CEN.PK 113–11C/p416 ADH-Kar2-Aβ42  This study  p416 TEF-Aβ42  CEN.PK 113–11C/p416 TEF-Kar2-Aβ42  This study  p426 ADH-Aβ42  CEN.PK 113–11C/p426 ADH-Kar2-Aβ42  This study  p416 GPD-Aβ42  CEN.PK 113–11C/p416 GPD-Kar2-Aβ42  This study  p426 TEF-Aβ42  CEN.PK 113–11C/p426 TEF-Kar2-Aβ42  This study  p416 GPD-Aβ40  CEN.PK 113–11C/p416 GPD-Kar2-Aβ40  This study  Plasmid or strain  Relevant genotype  Reference  Plasmid      p416 ADH  CEN, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p416 TEF  CEN, TEF1 promoter, URA3 marker  Mumberg et al. (1995)  p416 GPD  CEN, GPD1 promoter, URA3 marker  Mumberg et al. (1995)  p426 ADH  2μ, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p426 TEF  2μ, TEF1 promoter, URA3 marker,  Mumberg et al. (1995)  p416 ADH-Kar2-Aβ42  p416 ADH with Kar2 and Aβ42 sequence  This study  p416 TEF-Kar2-Aβ42  p416 TEF with Kar2 and Aβ42 sequence  This study  p426 ADH-Kar2-Aβ42  p426 ADH with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ42  p416 GPD with Kar2 and Aβ42 sequence  This study  p426 TEF-Kar2-Aβ42  p426 TEF with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ40  p416 GPD with Kar2 and Aβ40 sequence  This study  Strain      CEN.PK 113–11C  MATα his3Δ1 ura3–52 MAL2–8c SUC2  This study  P416 EP  CEN.PK 113–11C/p416 GPD  This study  P426 EP  CEN.PK 113–11C/p426 ADH  This study  p416 ADH-Aβ42  CEN.PK 113–11C/p416 ADH-Kar2-Aβ42  This study  p416 TEF-Aβ42  CEN.PK 113–11C/p416 TEF-Kar2-Aβ42  This study  p426 ADH-Aβ42  CEN.PK 113–11C/p426 ADH-Kar2-Aβ42  This study  p416 GPD-Aβ42  CEN.PK 113–11C/p416 GPD-Kar2-Aβ42  This study  p426 TEF-Aβ42  CEN.PK 113–11C/p426 TEF-Kar2-Aβ42  This study  p416 GPD-Aβ40  CEN.PK 113–11C/p416 GPD-Kar2-Aβ40  This study  View Large Table 1. Plasmids and strains used in this study. Plasmid or strain  Relevant genotype  Reference  Plasmid      p416 ADH  CEN, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p416 TEF  CEN, TEF1 promoter, URA3 marker  Mumberg et al. (1995)  p416 GPD  CEN, GPD1 promoter, URA3 marker  Mumberg et al. (1995)  p426 ADH  2μ, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p426 TEF  2μ, TEF1 promoter, URA3 marker,  Mumberg et al. (1995)  p416 ADH-Kar2-Aβ42  p416 ADH with Kar2 and Aβ42 sequence  This study  p416 TEF-Kar2-Aβ42  p416 TEF with Kar2 and Aβ42 sequence  This study  p426 ADH-Kar2-Aβ42  p426 ADH with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ42  p416 GPD with Kar2 and Aβ42 sequence  This study  p426 TEF-Kar2-Aβ42  p426 TEF with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ40  p416 GPD with Kar2 and Aβ40 sequence  This study  Strain      CEN.PK 113–11C  MATα his3Δ1 ura3–52 MAL2–8c SUC2  This study  P416 EP  CEN.PK 113–11C/p416 GPD  This study  P426 EP  CEN.PK 113–11C/p426 ADH  This study  p416 ADH-Aβ42  CEN.PK 113–11C/p416 ADH-Kar2-Aβ42  This study  p416 TEF-Aβ42  CEN.PK 113–11C/p416 TEF-Kar2-Aβ42  This study  p426 ADH-Aβ42  CEN.PK 113–11C/p426 ADH-Kar2-Aβ42  This study  p416 GPD-Aβ42  CEN.PK 113–11C/p416 GPD-Kar2-Aβ42  This study  p426 TEF-Aβ42  CEN.PK 113–11C/p426 TEF-Kar2-Aβ42  This study  p416 GPD-Aβ40  CEN.PK 113–11C/p416 GPD-Kar2-Aβ40  This study  Plasmid or strain  Relevant genotype  Reference  Plasmid      p416 ADH  CEN, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p416 TEF  CEN, TEF1 promoter, URA3 marker  Mumberg et al. (1995)  p416 GPD  CEN, GPD1 promoter, URA3 marker  Mumberg et al. (1995)  p426 ADH  2μ, ADH1 promoter, URA3 marker  Mumberg et al. (1995)  p426 TEF  2μ, TEF1 promoter, URA3 marker,  Mumberg et al. (1995)  p416 ADH-Kar2-Aβ42  p416 ADH with Kar2 and Aβ42 sequence  This study  p416 TEF-Kar2-Aβ42  p416 TEF with Kar2 and Aβ42 sequence  This study  p426 ADH-Kar2-Aβ42  p426 ADH with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ42  p416 GPD with Kar2 and Aβ42 sequence  This study  p426 TEF-Kar2-Aβ42  p426 TEF with Kar2 and Aβ42 sequence  This study  p416 GPD-Kar2-Aβ40  p416 GPD with Kar2 and Aβ40 sequence  This study  Strain      CEN.PK 113–11C  MATα his3Δ1 ura3–52 MAL2–8c SUC2  This study  P416 EP  CEN.PK 113–11C/p416 GPD  This study  P426 EP  CEN.PK 113–11C/p426 ADH  This study  p416 ADH-Aβ42  CEN.PK 113–11C/p416 ADH-Kar2-Aβ42  This study  p416 TEF-Aβ42  CEN.PK 113–11C/p416 TEF-Kar2-Aβ42  This study  p426 ADH-Aβ42  CEN.PK 113–11C/p426 ADH-Kar2-Aβ42  This study  p416 GPD-Aβ42  CEN.PK 113–11C/p416 GPD-Kar2-Aβ42  This study  p426 TEF-Aβ42  CEN.PK 113–11C/p426 TEF-Kar2-Aβ42  This study  p416 GPD-Aβ40  CEN.PK 113–11C/p416 GPD-Kar2-Aβ40  This study  View Large Batch fermentations Respiration assays were carried out in the DasGip 1.0-liter stirrer-pro bioreactors (DASGIP GmbH, Germany) with a 0.6-liter working volume under aerobic conditions. The temperature was controlled at 30°C with agitation at 600 rpm and aeration at 1 vvm. Dissolved oxygen was controlled above 30% throughout the experiment. The pH was maintained at 5.0 with 2 M KOH, in response to the pH sensor (Mettler Toledo, Switzerland). The emission of CO2 and residual O2 was monitored by DasGip fedbatch pro gas analysis systems. Strains were grown in Delft medium. All fermentations were performed in biological duplicates. The supernatants filtered through 0.45 μm membrane were loaded to an Aminex HPX-87H column (Bio Rad, Hercules, USA) on a Summit HPLC (Dionex, Sunnyvale, CA, USA) to measure the concentration of ethanol in the cultures. The samples were running with a flow rate of 0.5 ml min−1 at 65°C using 0.5 mM H2SO4 as the mobile phase. Spotting assay All spotting assays were performed under the same conditions. Tenfold serial dilution in sterile water starting with an equal number of cells (0.2 OD600) was used. Spotting assays were done in biological triplicates. Drops of 4.5 μl were plated onto the SD-Ura− plates. Plates were incubated at 30°C for 2–3 days. Chronological life span assay Chronological life span (CLS) was measured as previously described (Fabrizio and Longo 2003). Strains grown overnight at 30°C in SD-Ura− medium were diluted into 20 ml of medium to give an initial OD600 of 0.1. Cultures were grown with shaking (200 rpm) at 30°C to ensure proper aeration. After 24 h, these cultures had reached stationary phase, and this time point was designated day 1. Every 2 days, aliquots from the culture were serially diluted in YPD to achieve a cell density of ∼ 4 × 103 ml−1. One hundred microliters of the dilution was plated on to YPD plates, and incubated at 30°C for 2 days. The viability was estimated by colony forming units (CFUs). Viability at day 2 was considered to be the initial survival (100%). Averages and standard deviations for at least three biological replicates were calculated for each experiment. Propidium iodide staining Propidium iodide (PI) is a vital stain which stains cells with disintegrated plasma membranes, which are from a morphologically based state of view dead cells. For the PI staining of dead yeast cells, strains were pre-grown overnight and then diluted to 0.1 OD600 in 20 ml of SD-Ura− medium. A total of 0.5 OD600 unit of cells were taken at day 1, 3 and 9 of incubation. Cells were incubated with 0.5 μg ml−1 PI (Invitrogen) for 20 min, washed with PBS and then cells positive for red PI staining were observed under the fluorescence microscope and counted on a flow cytometer (Guava System). A total of 5000 cells for each sample were counted and the percentage of cells that stained positive for PI were recorded. The experiments were done in biological triplicates. As a positive control, we used cells that were incubated at 95°C for 20 min. Statistical significance was determined by using the two-tailed Student's t-test. Protein extraction and western blotting Strains were grown to post-diauxic phase in SD-Ura− medium at 30°C, and cells were spun down at 2000 g for 5 min. Cell pellets were resuspended in 200 μl of cold lysis buffer (50 mM HEPES pH7.5, 150 mM NaCI, 2.5 mM EDTA, 1% v/v Triton X-100) with freshly added Complete Mini Protease Inhibitors (Roche). Then the 200 μl of glass beads was added and the cells were shaken for 3 min on maximum speed. Following centrifugation at 13 000 g for 15 min, the supernatant was collected and protein concentrations were measured using Micro BCA protein assay kit (Thermo Scientific). A total of 50 μg protein of each sample was separated by a 4–12% Bis-Tris gel (invitrogen). Proteins were electrically transferred to 0.2 micron PVDF membrane (BioRad) using a Bio-Rad semi-dry transfer system. The membranes were probed with monoclonal mouse anti-Aβ antibody (6E10, 1:2000, Covance) or anti-GAPDH (1:2000, Santa Cruz) overnight at 4°C. Binding was detected with the ECL Prime reagent (GE Healthcare) and the ChemiDoc XRS image analyzer (Bio Rad). Immunostaining of intracellular Aβ Strains were cultured to post-diauxic phase in SD-Ura− medium. Cells were harvested and fixed in 5 ml of 50 mM KPO4 (pH6.5), 1 mM MgCI2 and 4% formaldehyde for 2 h. After fixation, the cells were washed three times in 5 ml of PM (0.1 M KPO4 pH 7.5, 1 mM MgCI2) and then resuspended in PMST (0.1 M KPO4 pH 7.5, 1 mM MgCI2, 1 M Sorbitol, 0.1% Triton X-100) to a final OD600 of 10. A total of 100 μl of cells were incubated with 0.6 μl of 2-mercaptoethanol and 1 mg ml−1 zymolyase (Zymo Research) for 20 min. Spheroplasted cells were washed three times in PMST and attached to a polylysine-coated coverslips. The adherent cells were blocked in 0.5% BSA/PMST for 30 min, and incubated overnight at 4°C with primary antibody (1:200 6E10 Aβ antibody) diluted in 0.5% BSA/PMST. Cells were washed in PMST, incubated with secondary antibody (1:300 anti-mouse Alexa 488) for 2 h at RT and incubated with 0.4 mg ml−1 DAPI (4’,6-diamidino-2-phenylindole) for 5 min. Cells were mounted in Vectashield (Vector Laboratories). The images were acquired using a Leica AF 6000 inverted microscope, and processed with the Leica Application Suite (LAS) software. Measurements of ROS The production of ROS was measured using dihydrorhodamine 123 (DHR, Sigma Aldrich). Strains were grown aerobically at 30°C in Delft medium. Samples of cells were grown to mid-exponential phase. A total of 0.5 OD600 of cells were harvested and incubated with 5 μM DHR for 20 min and used for analysis under the fluorescence microscope and for the flow cytometer analysis (Guava System). In each sample, 5000 cells were counted. The experiments were done in biological duplicates. Proteasome activity assay The 20S proteasomal activity was assessed using Proteasome-Glo cell-based assay (Promega GmbH, Germany) according to the manufacturer's instructions. Strains were grown aerobically at 30°C in Delft medium and harvested at OD600 of 1.0. Different numbers (20 000, 40 000 and 80 000) of cells were mixed with specific luminogenic proteasome substrates (Suc-LLVY-aminoluciferin for chymotrypsin-like activity, Z-LRR-aminoluciferin for trypsin-like activity and Z-nLPnLD-aminoluciferin for caspase-like activity), and substrate luminescence was measured by the FLUOstar Galaxy plate reader from BMG labtechnologies. All measurements were made in triplicate. In order to exclude that the detected signal resulted from non-proteasome cleavage of the aminoluciferin substrates by other proteases, some samples were incubated with the proteasome inhibitor epoxomicin for 1 h before measurement in a previous experiment. Since no significant luminescence was detected in the presence of epoxomicin, the signals detected in the samples without epoxomicin could be completely attributed to the activity of the 20S proteasome. RESULTS Effect of Aβ40 and Aβ42 on growth, CLS and cell death A series of vectors were used for constitutive Aβ42 expression at different levels. We chose three different promoters (ADH1: alcohol dehydrogenase 1; TEF1: translation elongation factor 1α and GPD1: glyceraldehyde-3-phosphate dehydrogenase) in two different plasmids (centromeric plasmid with a low copy number (CEN) and a high copy number plasmid (2μ)). Both plasmids are carrying the URA3 selective marker. The CEN derivatives were named p416 series, and the 2μ derivatives p426 (see Table 1 and Fig. 1A for plasmids and strains). The strength of transcription from different promoters is ADH1 < TEF1 < GPD1. The expression levels of these vectors were measured previously by cloning the lacZ gene downstream of the promoters and the β-galactosidase activity was determined: p416 ADH (3.0 units), p416 TEF (47.9 units), p426 ADH (90.8 units), p416 GPD (215 units) and p426 TEF (508 units) (Mumberg, Muller and Funk 1995). Figure 1. View largeDownload slide Construction of yeast strains expressing constitutively Aβ42 targeted for secretion. (A) Schematic map of the plasmids, different promoters (shaded boxes) and the Kar2-Aβ42 gene (striped box) used for the Aβ42 expression. Numbers below the boxes represent the regions of the promoters relative to the start codon. (B) Spot test (10-fold dilutions) to measure the relative viability of control and Aβ42 strains in exponential phase. Figure 1. View largeDownload slide Construction of yeast strains expressing constitutively Aβ42 targeted for secretion. (A) Schematic map of the plasmids, different promoters (shaded boxes) and the Kar2-Aβ42 gene (striped box) used for the Aβ42 expression. Numbers below the boxes represent the regions of the promoters relative to the start codon. (B) Spot test (10-fold dilutions) to measure the relative viability of control and Aβ42 strains in exponential phase. The constructed yeast strains with different Aβ42 expression levels were first tested for growth on plates (Fig. 1B) and in liquid SD-Ura− medium (Fig. 2A, Table 2). Compared to the controls (empty vector p416 EP), Aβ42 expressed in p416 ADH and p416 TEF plasmids did not affect growth (Table 2). Aβ42 expressed in p416 GPD plasmid caused an 11.3% decrease in growth (t-test, P < 0.05). Growth of p426 ADH-Aβ42 was reduced by 12.1% (t-test, P < 0.05), when compared to the control (high copy number empty vector p426 EP). The growth of cells expressing p416 GPD-Aβ42 and p426 ADH-Aβ42 was similar; however, the standard deviation of growth rate in high copy number plasmids was higher (0.013) than in low copy number plasmids (0.004). To get the stable expression of Aβ42, the p416 GPD plasmid was used for the experiments. This construct is a centromeric plasmid stably maintained at one or two copies per cell, and has the strong constitutive GPD promoter for heterologous gene expression. Aβ42 was also expressed in p426 TEF plasmid, but the strain did not grow. This hints to a strong cytotoxic effect of Aβ42 at high expression level, so this strain was not used for further studies. Figure 2. View largeDownload slide Aβ expression reduced growth and CLS. The p416 GPD plasmid was used to express the Aβ40 and Aβ42 proteins. The CEN.PK.113–11C cells were transformed with an empty vector (control), Aβ40 or Aβ42 plasmids. (A) Growth rate of control, Aβ40 and Aβ42 strains. (B) CLS assays of control, Aβ40 and Aβ42 strains. (C) Relative viability of control, Aβ40 and Aβ42 strains by plating serial 10-fold dilutions from CLS day 1 and day 9. (D) Flow cytometry analysis of PI staining following the CLS. The asterisk (*) indicates a value of P < 0.05. (E) Representative micrographs of PI staining of cells from CLS on day 3. All results are representative of at least three independent experiments and error bar indicates SD. The scale bars are 10 μm. Figure 2. View largeDownload slide Aβ expression reduced growth and CLS. The p416 GPD plasmid was used to express the Aβ40 and Aβ42 proteins. The CEN.PK.113–11C cells were transformed with an empty vector (control), Aβ40 or Aβ42 plasmids. (A) Growth rate of control, Aβ40 and Aβ42 strains. (B) CLS assays of control, Aβ40 and Aβ42 strains. (C) Relative viability of control, Aβ40 and Aβ42 strains by plating serial 10-fold dilutions from CLS day 1 and day 9. (D) Flow cytometry analysis of PI staining following the CLS. The asterisk (*) indicates a value of P < 0.05. (E) Representative micrographs of PI staining of cells from CLS on day 3. All results are representative of at least three independent experiments and error bar indicates SD. The scale bars are 10 μm. Table 2. Growth of CEN.PK.113–11C cells transformed with an empty vector (control) or Aβ42 in different vectors.   Generation time (min)  Growth rate (h−1)  p416 EP  108.83 ± 1.89  0.382 ± 0.0066  p416 ADH-Aβ42  99.86 ± 1.62  0.416 ± 0.011  p416 TEF-Aβ42  102.54 ± 2.29  0.406 ± 0.009  p416 GPD-Aβ42  122.69 ± 1.54  0.339 ± 0.004  p426 EP  117.69 ± 5.59  0.354 ± 0.017  p426 ADH-Aβ42  133.93 ± 5.74  0.311 ± 0.013    Generation time (min)  Growth rate (h−1)  p416 EP  108.83 ± 1.89  0.382 ± 0.0066  p416 ADH-Aβ42  99.86 ± 1.62  0.416 ± 0.011  p416 TEF-Aβ42  102.54 ± 2.29  0.406 ± 0.009  p416 GPD-Aβ42  122.69 ± 1.54  0.339 ± 0.004  p426 EP  117.69 ± 5.59  0.354 ± 0.017  p426 ADH-Aβ42  133.93 ± 5.74  0.311 ± 0.013  View Large Table 2. Growth of CEN.PK.113–11C cells transformed with an empty vector (control) or Aβ42 in different vectors.   Generation time (min)  Growth rate (h−1)  p416 EP  108.83 ± 1.89  0.382 ± 0.0066  p416 ADH-Aβ42  99.86 ± 1.62  0.416 ± 0.011  p416 TEF-Aβ42  102.54 ± 2.29  0.406 ± 0.009  p416 GPD-Aβ42  122.69 ± 1.54  0.339 ± 0.004  p426 EP  117.69 ± 5.59  0.354 ± 0.017  p426 ADH-Aβ42  133.93 ± 5.74  0.311 ± 0.013    Generation time (min)  Growth rate (h−1)  p416 EP  108.83 ± 1.89  0.382 ± 0.0066  p416 ADH-Aβ42  99.86 ± 1.62  0.416 ± 0.011  p416 TEF-Aβ42  102.54 ± 2.29  0.406 ± 0.009  p416 GPD-Aβ42  122.69 ± 1.54  0.339 ± 0.004  p426 EP  117.69 ± 5.59  0.354 ± 0.017  p426 ADH-Aβ42  133.93 ± 5.74  0.311 ± 0.013  View Large The expression of Aβ42 from p416 GPD plasmid caused a small but statistically significant reduction in growth (reduction of 11.3%, P < 0.05, Table 2). Expression of Aβ40 (also cloned in p416 GPD plasmid) was less toxic when compared to control (reduction of 2.3%) (Fig. 2A). Aβ40 is also an APP cleavage product but it was found to be less cytotoxic in various AD models (Luheshi et al.2007) presumably because of lesser tendency to aggregate when compared to Aβ42 peptides. To measure the long-term effect of Aβ42 and Aβ40 expression on the cells, we also examined the CLS. The number of viable cells in stationary phase of the control (empty vector p416 EP), the Aβ42 and the Aβ40 strains were determined over the course of several days using either CFUs or by spotting assay (Fig. 2B and C, respectively). Compared to control, Aβ42 strain displayed a drastically reduced ability to maintain viability in stationary phase and had therefore the CLS shortened from 13 days to 9 days. Though the expression of Aβ40 did not affect growth in exponential phase (Fig. 2A), it did reduce the CLS to 11 days. We also performed a PI staining to detect dead cells. PI is a vital stain that cannot permeate into living cells but which stains cells with damaged plasma membrane. We took samples at different days including during late stationary phase. This revealed that expression of Aβ42 increased cell death from day 1 (Fig. 2D and E). Expression and localization of Aβ40 and Aβ42 The expression of Aβ peptides was detected by western blot analysis using the Aβ-specific antibody, 6E10. The strains produced a peptide of the expected size (4 kDa). When lysates were loaded without denaturation by boiling in the denaturing loading buffer, we detected higher molecular weight species of Aβ, corresponding to different oligomers. In the Aβ42 strain, more oligomers were formed, and high molecular weight oligomers were detectable (Fig. 3A). Trimers and tetramers that are detectable in the Aβ42 strain (but not in the Aβ40 strain) are resolved when the sample is denatured by boiling in the SDS buffer, prior to SDS-PAGE. Thus, oligomeric Aβ forms seem to contribute to toxicity in yeast, as they probably do in neurons. Figure 3. View largeDownload slide Oligomerization of Aβ. The Aβ40 and Aβ42 peptides were expressed in p416 GPD plasmid. (A) Western blot analysis of Aβ40 and Aβ42 strains, using the Aβ-specific 6E10 antibody. GAPDH was used as a loading control. Samples were loaded onto a Bis-Tris gel with and without prior boiling in SDS sample buffer. (B) Immunostaining analysis of Aβ40 and Aβ42 localization using the 6E10 Aβ-specific antibody in vivo. Nuclei were visualized by DAPI staining. The scale bars are 5 μm. Figure 3. View largeDownload slide Oligomerization of Aβ. The Aβ40 and Aβ42 peptides were expressed in p416 GPD plasmid. (A) Western blot analysis of Aβ40 and Aβ42 strains, using the Aβ-specific 6E10 antibody. GAPDH was used as a loading control. Samples were loaded onto a Bis-Tris gel with and without prior boiling in SDS sample buffer. (B) Immunostaining analysis of Aβ40 and Aβ42 localization using the 6E10 Aβ-specific antibody in vivo. Nuclei were visualized by DAPI staining. The scale bars are 5 μm. In vivo cellular localization of Aβ peptides was confirmed by immunostaining. In the Aβ42 strain, Aβ was detected along the ER and was distributed in small foci throughout the cell. The ER was shown as a ring surrounding the nucleus which was stained with DAPI. By contrast, in the less toxic Aβ40 strain Aβ peptides seem to be more dispersed in the cell (Fig. 3B). Aβ42 affects mitochondrial respiratory capacity and induces production of ROS Mitochondrial dysfunction seems to play a key role in AD. We therefore tested whether the toxicity triggered by the expression of Aβ42 in yeast was associated with mitochondrial dysfunction in our model. We measured the carbon dioxide transfer rate (CTR), during respiration phase, as an indicator of respiratory rates. The cells were grown in the batch fermentation mode in the controlled bioreactor, in defined medium. In order to test the strains during the respiration, we used a non-fermentable carbon source, ethanol. Under these conditions, the CTR of the control, Aβ40 and Aβ42 strains was similar and unchanged during early exponential growth. By contrast, the respiratory rate in the Aβ42 strain was significantly decreased from mid-exponential phase (to 40% compared to control). The respiratory rate of Aβ40 strain decreased to a much lesser extent (Fig. 4B and C). The biomass yield was calculated based on the ratio of biomass produced, and ethanol consumed during the respiration. The biomass yield decreased in the Aβ42 strain after the mid-exponential phase (to 65% when compared to control) (Fig. 4D). This result correlates well with the slow growth phenotype of Aβ42 strain under respiratory conditions (Fig. 4A). Figure 4. View largeDownload slide The effect of Aβ expression on mitochondrial respiration and ROS production. The Aβ40 and Aβ42 peptides were expressed in p416 GPD plasmid. The strains were grown aerobically in batch fermentations in the Delft medium. (A) Growth of Aβ40 and Aβ42 strains during respiration. (B) Analysis of CTR during respiration. (C) The comparison of respiratory rates in mid-exponential phase. (D) The comparison of biomass yield in mid-exponential phase. (E) Flow cytometry analysis of ROS accumulation using DHR 123 staining in mid-exponential phase. Results are mean ± SD of at least two measurements performed on two independent cell cultures. The asterisk (*) indicates a value of P < 0.05 according to Student's t test. (F) Visualization of ROS producing cells in mid-exponential phase using DHR 123. The scale bars are 10 μm. Figure 4. View largeDownload slide The effect of Aβ expression on mitochondrial respiration and ROS production. The Aβ40 and Aβ42 peptides were expressed in p416 GPD plasmid. The strains were grown aerobically in batch fermentations in the Delft medium. (A) Growth of Aβ40 and Aβ42 strains during respiration. (B) Analysis of CTR during respiration. (C) The comparison of respiratory rates in mid-exponential phase. (D) The comparison of biomass yield in mid-exponential phase. (E) Flow cytometry analysis of ROS accumulation using DHR 123 staining in mid-exponential phase. Results are mean ± SD of at least two measurements performed on two independent cell cultures. The asterisk (*) indicates a value of P < 0.05 according to Student's t test. (F) Visualization of ROS producing cells in mid-exponential phase using DHR 123. The scale bars are 10 μm. Besides producing ATP, mitochondria are also involved in initiation of cell death and are also the main source of cellular ROS, which can damage cellular components and biomolecules and thus are involved in the pathogenesis of AD (Shahul and Ging-Yuek 2011). We measured intracellular ROS levels by flow cytometry using the non-fluorescent dihydrorhodamine 123 (DHR), to which yeast cells are permeable. DHR can be oxidized by the intracellular ROS into rhodamine 123, a fluorescent compound to which cells are impermeable, and which can be detected by flow cytometry. During respiration Aβ42 strain exhibited significantly higher levels of ROS, when compared to the control and the Aβ40 strain (Fig. 4E). We also qualitatively confirmed these results using fluorescence microscopy (Fig. 4F). Aβ42 affects the proteasomal activity The ubiquitin-proteasome system (UPS) is central for the degradation of abnormal proteins such as misfolded and oxidized proteins, and for the maintenance of cellular proteostasis. We therefore measured all three proteolytic activities of the 20S proteasome (the chymotrypsin-, caspase- and trypsin-like proteases) in exponentially growing cells. All three proteolytic activities were lower in Aβ42 strain compare to control and Aβ40 strains (Fig. 5). This suggests that an excess of misfolded proteins in Aβ42 strain inhibits the proteasome to degrade other substrates which possibly also contributes to the cytotoxic phenotype. Figure 5. View largeDownload slide The effect of Aβ expression on proteasomal activity. Proteasomal activity of the chymotrypsin-, caspase- and trypsin-like proteolytic activities of the 20S proteasome were measured as luminescence in control, Aβ40 and Aβ42 strains. The luminescent signal was proportional to the amount of proteasome activity in cells and recorded as relative luminescent units (RLU). Data are represented as mean ± SD from three independent experiments. Figure 5. View largeDownload slide The effect of Aβ expression on proteasomal activity. Proteasomal activity of the chymotrypsin-, caspase- and trypsin-like proteolytic activities of the 20S proteasome were measured as luminescence in control, Aβ40 and Aβ42 strains. The luminescent signal was proportional to the amount of proteasome activity in cells and recorded as relative luminescent units (RLU). Data are represented as mean ± SD from three independent experiments. DISCUSSION Yeast has been used as a model for several neurological disorders characterized by protein misfolding and aggregation (Winderickx et al.2008; Braun et al.2010; Khurana and Lindquist 2010). In order to study Aβ cytotoxicity, a few approaches have been used previously including chemically synthesized Aβ, intracellular fused Aβ and intracellular recombinant forms. Studies in Candida glabrata showed that the chemically synthesized Aβ induced oligomerization-dependent cytotoxicity (Bharadwaj et al.2008). The in vivo oligomerization of Aβ was studied using Aβ/Sup35p fusion expressed in yeast. The yeast translation termination factor Sup35p is essentially composed of three domains: the N-terminal domain (N), middle domain (M) and C-terminal release factor domain (RF). The Aβ peptide was fused to the MRF domain of Sup35p, thereby causing oligomerization of MRF and growth reduction (Bagriantsev and Liebman 2006). Similarly, when the Aβ peptide was fused to the green fluorescent protein (GFP) at the C- or N-terminus, it was shown that the heat shock response was induced and there was reduction of cell growth (Caine et al.2007). While Aβ fusions are helpful in many cases, it can be argued that fusions could alter the properties of Aβ, e.g. the intracellular Aβ could be stabilized and thus less toxic, so a system with native Aβ could be useful. Previous studies showed that there was no detectable native Aβ expression in yeast, despite the use of a copper-inducible expression system that has previously proved suitable for the production of toxic proteins such as HIV-1 Vpr (Macreadie et al.1995). In these previous studies, Aβ was expressed in the cytosol, whereas native Aβ derives from the APP, which generates Aβ peptide within the secretory and endosomal pathways. APP processing primarily occurs in the secretory network, with the release of Aβ into extracellular space, and subsequently internalized and recycled through endosomal vesicles and the trans-Golgi network via endocytosis (Thinakaran and Koo 2008). Recently, a new screen based on a secreted form of Aβ in yeast revealed the importance of the endocytic pathway in cellular toxicity (Treusch et al.2011). This finding was confirmed by other yeast Aβ expression models (D'Angelo et al.2013). The GFP-Aβ fusion targeted to the secretory pathway indicated decreased growth rates and markedly reduction of oxygen consumption on obligatory respiratory growth media. This yeast model of Aβ toxicity was used for a completely unbiased screen of compounds for rescue of Aβ toxicity. A small number of cytoprotective compounds including 8-hydroxyquinolines were identified (Matlack et al.2014). In this study, native Aβ was fused to an ER targeting signal sequence to direct correctly Aβ into the secretory compartments. Different plasmids and promoters were tested to generate different levels of Aβ42 peptides in yeast. We selected the strain exhibiting intermediate levels of toxicity that allowed for the analysis of Aβ42-induced cellular toxicity. The Aβ42 peptide expressed constitutively formed oligomers and aggregates throughout the cells, seemingly also along the secretory network. The Aβ42 strain showed a reduced growth rate, increased number of dead cells and significantly shorter chronological life span. Therefore, it is concluded that the expression of Aβ42 and the formation of oligomers impose a cytotoxic stress. The Aβ42 strain showed also impaired respiration capacity. Cells producing Aβ42 showed significant reduction of respiratory rate and biomass yield from mid-exponential stage, which was accompanied by an elevated production of ROS. Accumulating data suggest that mitochondrial dysfunction and oxidative stress occur in the neurons as well as in peripheral tissues of AD patients (Fukui and Moraes 2008). Studies have shown that Aβ is accumulating in mitochondria in post-mortem AD brain samples, in patients with cortical plaques and in TgAPP mice (Lustbader et al.2004; Caspersen et al.2005; Petersen et al.2008). In TgAPP mice, mitochondrial Aβ accumulation occurs prior to plaque formation, indicating that this is an early event in the development of pathogenesis. The mitochondria isolated from S. cerevisiae strains, mouse and human brain tissues shows signs of mitochondrial impairment upon prolonged exposure to cytosolic Aβ42, including inhibition of mitochondrial pre-protein maturation, increased ROS production, decreased mitochondrial membrane potential and reduced oxygen consumption (Mossmann et al.2014). It is interesting to consider how Aβ could reach the mitochondria. Intracellular Aβ42 has been shown to accumulate in intracellular multivesicular bodies (Gouras et al.2000) and it is possible that Aβ leaking from these vesicles could reach the mitochondria. Hansson et al. showed that Aβ ‘fed’ extracellularly is internalized by human neuroblastoma cells and later partly localized to mitochondria (Petersen et al.2008). These data suggest that secreted Aβ can be re-internalized into cells and reach mitochondria. We found previously that yeast can uptake considerable amounts of secreted protein (in the range of 1 g L−1 day−1). Characterizing the physiological state and combining metabolomics and transcriptomics, we have previously identified metabolic and regulatory markers that were consistent with uptake of whole proteins by endocytosis, followed by intracellular degradation and catabolism of substituent amino acids (Tyo et al.2014). Dysfunctions of the mitochondria and UPS have been strongly associated with the pathogenesis of many neurodegenerative disorders, including AD (Segref et al.2014). However, the order in which these events occur as well as the intracellular mechanisms remain unclear. Recent study shows that the accumulation of UBB+1, a frameshift variant of ubiquitin B, induces enhancement of the basic amino acids arginine, ornithine and lysine at mitochondria as a decisive toxic event (Braun et al.2015). In our model, the proteolytic activities were measured and showed decrease in Aβ42 strain compare to control and Aβ40 strains. A recent study has shown that the acute mitochondrial stress results in proteasomes dissociation, mitochondrial networks fragment and cellular ROS levels increase (Livnat-Levanon et al.2014). Conversely, the proteasome inhibition leads to mitochondrial oxidation followed by cytosolic oxidation, which can be prevented by a mitochondrial-targeted antioxidant (Maharjan et al.2014). In this study, we have created a yeast model for expression of native Aβ peptides that are constitutively expressed, form intracellular oligomers, are targeted to the secretory pathway and induce cytotoxic effects. We have also found that the toxicity is influencing the mitochondria, respiration and the proteasomal system. We thus believe that this model will be used in the future for discovery of mechanism of Aβ42 toxicity. We are grateful to Professor Susan Lindquist for giving us the inital Aβ plasmids and to Dr Yun Chen and Dr Mingtao Huang for their assistance with fermentations. FUNDING This work was supported by grants from the Novo Nordisk Foundation, Kristina Stenborgs Foundation and Sven & Lilly Lawski Foundation. Conflict of interest. None declared. REFERENCES Aleardi AM Benard G Augereau Oet al.   Gradual alteration of mitochondrial structure and function by beta-amyloids: importance of membrane viscosity changes, energy deprivation, reactive oxygen species production, and cytochrome c release J Bioenerg Biomembr  2005 37 207 25 Google Scholar CrossRef Search ADS PubMed  Bagriantsev S Liebman S Modulation of Abeta42 low-n oligomerization using a novel yeast reporter system BMC Biol  2006 4 32 Google Scholar CrossRef Search ADS PubMed  Bharadwaj P Waddington L Varghese Jet al.   A new method to measure cellular toxicity of non-fibrillar and fibrillar Alzheimer's A beta using yeast J Alzheimers Dis  2008 13 147 50 Google Scholar PubMed  Braun RJ Buttner S Ring Jet al.   Nervous yeast: modeling neurotoxic cell death Trends Biochem Sci  2010 35 135 44 Google Scholar CrossRef Search ADS PubMed  Braun RJ Sommer C Leibiger Cet al.   Accumulation of basic amino acids at mitochondria dictates the cytotoxicity of aberrant ubiquitin Cell Rep  2015 10 1557 71 Google Scholar CrossRef Search ADS   Caine J Sankovich S Antony Het al.   Alzheimer's A beta fused to green fluorescent protein induces growth stress and a heat shock response FEMS Yeast Res  2007 7 1230 6 Google Scholar CrossRef Search ADS PubMed  Calkins MJ Manczak M Mao PZet al.   Impaired mitochondrial biogenesis, defective axonal transport of mitochondria, abnormal mitochondrial dynamics and synaptic degeneration in a mouse model of Alzheimer's disease Hum Mol Genet  2011 20 4515 29 Google Scholar CrossRef Search ADS PubMed  Caspersen C Wang N Yao Jet al.   Mitochondrial A beta: a potential focal point for neuronal metabolic dysfunction in Alzheimer's disease FASEB J  2005 19 2040 1 Google Scholar PubMed  Chen Y Daviet L Schalk Met al.   Establishing a platform cell factory through engineering of yeast acetyl-CoA metabolism Metab Eng  2013 15 48 54 Google Scholar CrossRef Search ADS PubMed  Crouch PJ Harding S-ME White ARet al.   Mechanisms of Aβ mediated neurodegeneration in Alzheimer's disease Int J Biochem Cell B  2008 40 181 98 Google Scholar CrossRef Search ADS   Crowther DC Kinghorn KJ Miranda Eet al.   Intraneuronal Aβ, non-amyloid aggregates and neurodegeneration in a Drosophila model of Alzheimer's disease Neuroscience  2005 132 123 35 Google Scholar CrossRef Search ADS PubMed  D'Angelo F Vignaud H Di Martino Jet al.   A yeast model for amyloid-β aggregation exemplifies the role of membrane trafficking and PICALM in cytotoxicity Dis Model Mech  2013 6 206 16 Google Scholar CrossRef Search ADS PubMed  Fabrizio P Longo VD The chronological life span of Saccharomyces cerevisiae Aging Cell  2003 2 73 81 Google Scholar CrossRef Search ADS PubMed  Ferri CP Prince M Brayne Cet al.   Global prevalence of dementia: a Delphi consensus study Lancet  2005 366 2112 7 Google Scholar CrossRef Search ADS PubMed  Fukui H Moraes CT The mitochondrial impairment, oxidative stress and neurodegeneration connection: reality or just an attractive hypothesis? Trends Neurosci  2008 31 251 6 Google Scholar CrossRef Search ADS PubMed  Gouras GK Tsai J Naslund Jet al.   Intraneuronal Aβ42 accumulation in human brain Am J Pathol  2000 156 15 20 Google Scholar CrossRef Search ADS PubMed  Hardy J Selkoe DJ Medicine—the amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics Science  2002 297 353 6 Google Scholar CrossRef Search ADS PubMed  Hartley DM Walsh DM Ye CPPet al.   Protofibrillar intermediates of amyloid beta-protein induce acute electrophysiological changes and progressive neurotoxicity in cortical neurons J Neurosci  1999 19 8876 84 Google Scholar PubMed  Khurana V Lindquist S Modelling neurodegeneration in Saccharomyces cerevisiae: why cook with baker's yeast? Nat Rev Neurosci  2010 11 436 49 Google Scholar CrossRef Search ADS PubMed  Knobloch M Konietzko U Krebs DCet al.   Intracellular Aβ and cognitive deficits precede β-amyloid deposition in transgenic arcAβ mice Neurobiol Aging  2007 28 1297 306 Google Scholar CrossRef Search ADS PubMed  Komano H Seeger M Gandy Set al.   Involvement of cell surface glycosyl-phosphatidylinositol-linked aspartyl proteases in alpha-secretase-type cleavage and ectodomain solubilization of human Alzheimer beta-amyloid precursor protein in yeast J Biol Chem  1998 273 31648 51 Google Scholar CrossRef Search ADS PubMed  LaFerla FM Green KN Oddo S Intracellular amyloid-beta in Alzheimer's disease Nat Rev Neurosci  2007 8 499 509 Google Scholar CrossRef Search ADS PubMed  Link CD Expression of human beta-amyloid peptide in transgenic Caenorhabditis elegans P Natl Acad Sci USA  1995 92 9368 72 Google Scholar CrossRef Search ADS   Livnat-Levanon N Kevei E Kleifeld Oet al.   Reversible 26S proteasome disassembly upon mitochondrial stress Cell Rep  2014 7 1371 80 Google Scholar CrossRef Search ADS PubMed  Luheshi LM Tartaglia GG Brorsson ACet al.   Systematic in vivo analysis of the intrinsic determinants of amyloid beta pathogenicity PLoS Biol  2007 5 2493 500 Google Scholar CrossRef Search ADS   Lustbader JW Cirilli M Lin Cet al.   ABAD directly links A beta to mitochondrial toxicity in Alzheimer's disease Science  2004 304 448 52 Google Scholar CrossRef Search ADS PubMed  McLean CA Cherny RA Fraser FWet al.   Soluble pool of Aβ amyloid as a determinant of severity of neurodegeneration in Alzheimer's disease Ann Neurol  1999 46 860 6 Google Scholar CrossRef Search ADS PubMed  Macreadie I Lotfi-Miri M Mohotti Set al.   Validation of folate in a convenient yeast assay suited for identification of inhibitors of Alzheimer's amyloid-beta Aggregation J Alzheimers Dis  2008 15 391 6 Google Scholar PubMed  Macreadie IG Castelli LA Hewish DRet al.   A domain of human immunodeficiency virus type 1 Vpr containing repeated H(S/F)RIG amino acid motifs causes cell growth arrest and structural defects P Natl Acad Sci USA  1995 92 2770 4 Google Scholar CrossRef Search ADS   Magrane J Smith RC Walsh Ket al.   Heat shock protein 70 participates in the neuroprotective response to intracellularly expressed beta-amyloid in neurons J Neurosci  2004 24 1700 6 Google Scholar CrossRef Search ADS PubMed  Maharjan S Oku M Tsuda Met al.   Mitochondrial impairment triggers cytosolic oxidative stress and cell death following proteasome inhibition Sci Rep  2014 4 11 Google Scholar CrossRef Search ADS   Manczak M Mao P Calkins Met al.   Mitochondria-targeted antioxidants protect against Abeta toxicity in Alzheimer's disease neurons J Alzheimers Dis  2010 20 S609 S31 Google Scholar PubMed  Matlack KES Tardiff DF Narayan Pet al.   Clioquinol promotes the degradation of metal-dependent amyloid-β (Aβ) oligomers to restore endocytosis and ameliorate Aβ toxicity P Natl Acad Sci USA  2014 111 4013 8 Google Scholar CrossRef Search ADS   Matsumoto K Akao Y Yi Het al.   Overexpression of amyloid precursor protein induces susceptibility to oxidative stress in human neuroblastoma SH-SY5Y cells J Neural Transm  2006 113 125 35 Google Scholar CrossRef Search ADS PubMed  Mirisola MG Braun RJ Petranovic D Approaches to study yeast cell aging and death FEMS Yeast Res  2014 14 109 18 Google Scholar CrossRef Search ADS PubMed  Mossmann D Vögtle FN Taskin Asli Aet al.   Amyloid-β peptide induces mitochondrial dysfunction by inhibition of preprotein maturation Cell Metab  2014 20 662 9 Google Scholar CrossRef Search ADS PubMed  Mumberg D Muller R Funk M Yeast vectors for the controlled expression of heterologous proteins in different genetic backgrounds Gene  1995 156 119 22 Google Scholar CrossRef Search ADS PubMed  Munoz AJ Wanichthanarak K Meza Eet al.   Systems biology of yeast cell death FEMS Yeast Res  2012 12 249 65 Google Scholar CrossRef Search ADS PubMed  Petersen CAH Alikhani N Behbahani Het al.   The amyloid beta-peptide is imported into mitochondria via the TOM import machinery and localized to mitochondrial cristae P Natl Acad Sci USA  2008 105 13145 50 Google Scholar CrossRef Search ADS   Petranovic D Nielsen J Can yeast systems biology contribute to the understanding of human disease? Trends Biotechnol  2008 26 584 90 Google Scholar CrossRef Search ADS PubMed  Segref A Kevei E Pokrzywa Wet al.   Pathogenesis of human mitochondrial diseases is modulated by reduced activity of the ubiquitin/proteasome system Cell Metab  2014 19 642 52 Google Scholar CrossRef Search ADS PubMed  Selkoe DJ Alzheimer's disease: genes, proteins, and therapy Physiol Rev  2001 81 741 66 Google Scholar PubMed  Selkoe DJ Wolfe MS Presenilin: running with scissors in the membrane Cell  2007 131 215 21 Google Scholar CrossRef Search ADS PubMed  Shahul H Ging-Yuek RH The role of mitochondria in aging, neurodegenerative disease, and future therapeutic options B C Med J  2011 53 188 92 Takahashi RH Milner TA Li Fet al.   Intraneuronal Alzheimer Aβ42 Accumulates in multivesicular bodies and is associated with synaptic pathology Am J Pathol  2002 161 1869 79 Google Scholar CrossRef Search ADS PubMed  Thinakaran G Koo EH Amyloid precursor protein trafficking, processing, and function J Biol Chem  2008 283 29615 9 Google Scholar CrossRef Search ADS PubMed  Treusch S Hamamichi S Goodman JLet al.   Functional links between Aβ toxicity, endocytic trafficking and Alzheimer's disease risk factors in yeast Science  2011 334 1241 5 Google Scholar CrossRef Search ADS PubMed  Tyo KEJ Liu ZH Magnusson Yet al.   Impact of protein uptake and degradation on recombinant protein secretion in yeast Appl Microbiol Biot  2014 98 7149 59 Google Scholar CrossRef Search ADS   Williams M Progress in Alzheimer's disease drug discovery: an update Curr Opin Invest Dr  2009 10 23 34 Winderickx J Delay C DeVos Aet al.   Protein folding diseases and neurodegeneration: lessons learned from yeast BBA-Mol Cell Res  2008 1783 1381 95 Yao J Irwin RW Zhao LQet al.   Mitochondrial bioenergetic deficit precedes Alzheimer's pathology in female mouse model of Alzheimer's disease P Natl Acad Sci USA  2009 106 14670 5 Google Scholar CrossRef Search ADS   Zhang W Espinoza D Hines Vet al.   Characterization of beta-amyloid peptide precursor processing by the yeast Yap3 and Mkc7 proteases BBA-Mol Cell Res  1997 1359 110 22 © FEMS 2015. 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TI - Amyloid-β peptide-induced cytotoxicity and mitochondrial dysfunction in yeast
JO - FEMS Yeast Research
DO - 10.1093/femsyr/fov061
DA - 2015-09-01
UR - https://www.deepdyve.com/lp/oxford-university-press/amyloid-peptide-induced-cytotoxicity-and-mitochondrial-dysfunction-in-Lau1h0vRL1
SP - fov061
VL - 15
IS - 6
DP - DeepDyve
ER -