The Proteome Response to Amyloid Protein Expression
In Vivo
Ricardo A. Gomes1,2, Catarina Franco1, Gonçalo Da Costa2, Sébastien Planchon3, Jenny Renaut3,
Raquel M. Ribeiro2, Francisco Pinto2, Marta Sousa Silva2, Ana Varela Coelho1, Ana Ponces Freire2,
Carlos Cordeiro2*
1 Instituto de Tecnologia Quı́mica e Biológica, Universidade Nova de Lisboa, Oeiras, Portugal, 2 Centro de Quı́mica e Bioquı́mica, Faculdade de Ciências da Universidade
de Lisboa, Lisboa, Portugal, 3 Département of Environnent and Agrobiotechnologies, Centre de Recherche Public Gabriel Lippmann, Belvaux, Luxembourg
Abstract
Protein misfolding disorders such as Alzheimer, Parkinson and transthyretin amyloidosis are characterized by the formation
of protein amyloid deposits. Although the nature and location of the aggregated proteins varies between different diseases,
they all share similar molecular pathways of protein unfolding, aggregation and amyloid deposition. Most effects of these
proteins are likely to occur at the proteome level, a virtually unexplored reality. To investigate the effects of an amyloid
protein expression on the cellular proteome, we created a yeast expression system using human transthyretin (TTR) as a
model amyloidogenic protein. We used Saccharomyces cerevisiae, a living test tube, to express native TTR (nonamyloidogenic) and the amyloidogenic TTR variant L55P, the later forming aggregates when expressed in yeast. Differential
proteome changes were quantitatively analyzed by 2D-differential in gel electrophoresis (2D-DIGE). We show that the
expression of the amyloidogenic TTR-L55P causes a metabolic shift towards energy production, increased superoxide
dismutase expression as well as of several molecular chaperones involved in protein refolding. Among these chaperones,
members of the HSP70 family and the peptidyl-prolyl-cis-trans isomerase (PPIase) were identified. The latter is highly
relevant considering that it was previously found to be a TTR interacting partner in the plasma of ATTR patients but not in
healthy or asymptomatic subjects. The small ubiquitin-like modifier (SUMO) expression is also increased. Our findings
suggest that refolding and degradation pathways are activated, causing an increased demand of energetic resources, thus
the metabolic shift. Additionally, oxidative stress appears to be a consequence of the amyloidogenic process, posing an
enhanced threat to cell survival.
Citation: Gomes RA, Franco C, Da Costa G, Planchon S, Renaut J, et al. (2012) The Proteome Response to Amyloid Protein Expression In Vivo. PLoS ONE 7(11):
e50123. doi:10.1371/journal.pone.0050123
Editor: Mick F. Tuite, University of Kent, United Kingdom
Received February 8, 2012; Accepted October 17, 2012; Published November 21, 2012
Copyright: ß 2012 Gomes et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Work was supported by grants SFRH/BPD/41037/2007 (R.A.G.), PEst-OE/QUI/UI0612/2011, PTDC/QUI/70610/2006 and REDE/1501/REM/2005 from the
Fundação para a Ciência e a Tecnologia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail:
[email protected]
decreased cell capacity to clear misfolded proteins may be directly
involved in pathogenesis. In fact, one hypothesis to explain the late
onset of several conformational disorders considers the loss of
effectiveness of the protein quality control system with age, either
arising from environmental insults, mutations or unidentified
triggers [7]. Although the regulation of these pathways has been
considered a therapeutic strategy [8] our knowledge of these
processes is still very limited and therefore a deeper understanding
of the cellular response mechanisms, at the proteome level, to
misfolding and aggregation of amyloidogenic proteins is of great
interest. Importantly, even in familial neuropathies, where genetic
determinants play a key role, several observation points to the
involvement of non-genetic factors. In ATTR, where the amyloid
deposits are mainly composed of transthyretin (TTR), several
TTR amyloidogenic point mutations with different degrees of
amiloidogenicity (i.e., different tendency to misfold and aggregate)
are associated to disease onset and progression [9,10]. However, it
was observed that many mutation carriers are asymptomatic
throughout their lives and non-mutant TTR also forms amyloid,
causing senile systemic amyloidosis [11–13]. Additionally, patients
Introduction
Protein misfolding and aggregation are common features in
many neurodegenerative amyloid disorders, such as Alzheimer,
Parkinson and transthyretin amyloidosis (ATTR) [1,2]. In each
case, a specific amyloidogenic protein misfold and follows a toxic
aggregation pathway leading to a defined clinical outcome [1,2]. A
legion of factors that may trigger protein misfolding and
aggregation has been implied in the development of this kind of
pathologies, such as abnormal proteolysis, point mutations and
post-translational modifications, namely phosphorylation, oxidation and glycation [2,3]. Cell quality control mechanisms evolved
to cope with protein misfolding and aggregation, including
molecular chaperones and protein degradation pathways that
prevent protein aggregation by either protein refolding or
degradation [4–6]. However, in the disease process these
mechanisms are not sufficient to prevent the accumulation of
toxic protein aggregates and recent studies have implicated several
components of the protein quality control system in neurodegenerative disorders of amyloid type (reviewed in [5,6]). Thus, a
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Proteome Changes in Response to Protein Misfolding
is blocked previously to the filtration procedure, TTR-containing
insoluble protein aggregates are retained while soluble TTR do
not bind to the blocked membrane, in contrast to a regular dotblot assay using non-blocked nitrocellulose membrane (Figure 1C).
Thus this method is indeed a protein aggregation filter trap assay.
Using blocked nitrocellulose, a positive signal was only obtained in
the crude extract indicating the presence of TTR in the insoluble
fraction. As shown in Figure 1B, TTR aggregates insoluble in 2%
SDS were clearly observed in yeast cells expressing the amyloidogenic L55P variant (BTTR-L55P). SDS-insoluble aggregates were
not detected in BTTR-wt and, as expected, in the control
(Figure 1B). In addition, a substantially higher TTR amount was
found in the insoluble protein fraction of BTTR-L55P in
comparison to BTTR-wt (Figure 1B and C). Thus, even though
no cell toxicity and growth defects were observed (Figure 1D and
E), TTR-L55P variant, when expressed in yeast, forms highmolecular mass amyloid-like aggregates.
The 2D electrophoretic maps contained around 1800 spots
(Figure 2A). From these, a total of 78 protein spots were detected
with a statistically significant change in abundance (ANOVA
p,0.05) with an absolute variation $1.3-fold from at least one
experimental group. Examples of three spot patterns are shown in
Figure 2B. Spot 1461 increase its abundance only in BTTR-L55P
while spot 1643 decrease its abundance in both BTTR-wt and
BTTR-L55P. The spot 1698 is differentially expressed in both
experimental groups but shows a significantly higher abundance in
BTTR-L55P compared to BTTR-wt. A principal component
analysis (PCA) analysis shows that 2D gel images cluster into three
well separated groups (Figure 2C), indicating a clear differentiation
between the expression of the non-amyloidogenic TTR-wt and the
amyloidogenic TTR-L55P form with significant changes in
protein abundances. In fact, by directly comparing the 2D-DIGE
maps of BTTR-wt and BTTR-L55P with the control, a total of 24
and 75 spots, respectively, were differentially expressed, highlighting a much higher induced change upon expression of the
amyloidogenic TTR variant. Interestingly, of the 24 protein spots
with changes in abundance between BTTR-wt/control, 21 spots
were also differentially expressed in BTTR-L55P/control with a
similar fold variation. These changes are likely to be due to the
heterologous TTR expression and not because of TTR misfolding.
However, 54 protein spots exhibited significant changes in
abundance exclusively upon TTR-L55P expression, suggesting
that relevant proteins involved in the cell response to TTR
misfolding and aggregation are revealed with this approach.
carrying the same mutation show a wide range of age at onset
from 20 to 70 years [14]. We recently discovered that ATTR
patients show increased protein glycation that decreases the
chaperone activity of fibrinogen, a TTR protein binding partner,
hence promoting transthyretin unfolding and aggregation in
ATTR [15].
In this work we investigated the cellular responses to the
misfolding and aggregation of an amyloidogenic protein using a
high-throughput proteomics approach to screen differentially
expressed proteins. For that purpose, we used yeast Saccharomyces
cerevisiae as a host to express human TTR, used as a model
amyloidogenic protein. As the general protein quality control
systems are highly conserved, especially in eukaryotes, yeast is a
valuable model to evaluate fundamental aspects of protein
misfolding and the molecular mechanisms involved in the cellular
response. Additionally, Saccharomyces cerevisiae was the first eukaryote to have its genome sequenced and, recently, its entire
proteome has been mapped [16,17]. Yeast has been successfully
used to investigate fundamental aspects of protein misfolding
involved in syndromes like amyotrophic lateral sclerosis, Huntington’s disease and Parkinson’s disease [18–20]. TTR was investigated as an amyloidogenic protein for two main reasons: first, it is
one of the best structurally characterized amyloidogenic proteins
and second, several known point mutations are associated to
different degrees of amiloidogenicity and disease progression. This
allows the discrimination between the cell response to the
expression of a heterologous protein and the amyloidogenic
version of the same protein. Thus, wild-type TTR and the highly
amyloidogenic TTR variant L55P (leucine for proline at position
55) were selected for expression in yeast. Although these two
variants only differ in one amino acid, TTR-L55P has a higher
intrinsic propensity to misfold and aggregate and carriers of this
amyloidogenic mutation have a very early age at disease onset
[21].
Differential proteome changes between the control (cells
carrying the empty plasmid), cells expressing TTR-wt (BTTRwt) and cells expressing TTR-L55P (BTTR-L55P) were analyzed
by 2D-DIGE coupled to protein identification by tandem MS.
Expression of each TTR forms has no toxic effects on yeast and
does not impair cell division, population growth and metabolism,
despite the formation of TTR aggregates in yeast cells expressing
the L55P variant. About 20 proteins were found to be differentially
expressed in BTTR-wt while 70 were differentially expressed in
BTTR-L55P. Changes in proteins involved in folding and
degradation processes were detected, together with an increased
expression of translation pathways. Major changes at the
proteome level were associated with increased carbohydrate,
energy and amino acid metabolism.
Protein Identification and Gene Ontology Analysis
All spots highlighted in Figure 2A were picked and trypsin
digested using the Ettan Spot Handling Workstation and the
proteins were identified by MALDI-TOF-TOF MS. With this
approach, we were able to identify the corresponding proteins in
73 spots, resulting in the identification of 70 unique proteins
(Table 1). For the majority of the identified proteins, the molecular
mass and isoelectric points determined on the 2D gel are
consistent. In some cases, the same protein is identified in different
spots across the 2D gel with different molecular mass and
isoelectric point suggesting the presence of post-translational
modifications and/or protein isoforms. All spots representing the
same protein have a very similar regulation (see for example spot
991 and 994 both identified as alcohol dehydrogenase (ADH1)
where a similar trend and fold variation was observed). In seven
spots, more than one protein was identified (see Table 1). In some
cases, MSMS data allowed the identification of a particular
protein isoform (example, spot 613 identified as HSP75). In other
cases, this was not possible and thus both protein isoforms are
Results and Discussion
Protein Expression Analysis by 2D-DIGE
To quantitatively investigate proteome changes of yeast cells in
response to TTR expression we analysed and compared the
proteomes of yeast BY4741 cells carrying the plasmid without the
insert (control), TTR-wt (BTTR-wt) and TTR-L55P variant
(BTTR-L55P). TTR expression was confirmed by MS analysis
(data not shown) and western blot, where similar expression levels
of TTR-wt and TTR-L55P were detected (Figure 1A). To analyse
the presence of TTR aggregates, a protein aggregate filtration
assay was performed (Figure 1B). This microfiltration method is
based on the finding that high-molecular mass amyloid-like
aggregates are SDS-insoluble, being therefore retained in a
0.2 mm blocked membrane. In fact, if the nitrocellulose membrane
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Proteome Changes in Response to Protein Misfolding
Figure 1. Characterization of TTR expression in yeast. (A) Relative quantitation of TTR-wt and TTR-L55P expression by Western blot with antihuman TTR antibody. Since TTR-L55P aggregates, electrophoretic separation of proteins was performed in the presence of urea to compare the total
protein amount. TTR monomer is observed with molecular masses of approximately 14 kDa only in cells expressing TTR (BTTR-wt and BTTR-L55P).
Similar expression levels were observed for the two TTR variants. (B) Protein aggregate filtration assay of insoluble protein fraction. TTR aggregates
insoluble in 2% SDS were observed only in yeast cells expressing the amyloidogenic L55P variant (BTTR-L55P). This indicates that TTR-L55P when
expressed in yeast forms high molecular mass amyloid-like aggregates, in contrast to TTR-wt. A substantially higher TTR amount was also found in the
insoluble protein fraction of BTTR-L55P in comparison with BTTR-wt. (C) Control assay. The crude extract and the soluble protein fraction were
analysed through a nitrocellulose membrane (as a regular dot-blot assay) and a nitrocellulose membrane that was blocked prior to the filtration
procedure. Growth curves (D) and dilution spot assay (E) of yeast cells expressing the TTR variants and the control shows that, although the highly
amyloidogenic TTR variant L55P was expressed in yeast, no changes were detected in yeast cell growth and cell viability.
doi:10.1371/journal.pone.0050123.g001
19%). Several of these proteins have been described as stress
response ones, involved in the response to an increase protein
misfolding (as Hsp70 protein family). Proteins involved in
transport (2 proteins, 3%), cell redox-homeostasis (3 proteins,
4%) and proteins with unknown or poorly characterized function
(4 proteins, 6%) were also identified.
Concerning cellular location, a high number of identified
proteins were from mitochondria (27%), while 22% were from
cytoplasm, 12.5% from the plasma membrane and nucleus
(Figure 3B).
shown in table 1 (for example, spot 1542 identified as enolase 1
and/or enolase 2).
A significant change in protein abundance was clearly detected
for spot number 1492, absent from the control (Figure 2D). This
spot was unequivocally identified as human TTR. This is a
noteworthy observation for two main reasons: first, it shows that
our experimental system leads to a high TTR expression level;
second, the detection of this expected difference validates the
approach we chose to detect quantitative differences in protein
abundances.
The identified proteins were categorised into functional groups
and cellular location using Gene Ontology annotations. The 70
identified proteins fell into 10 functional categories (Figure 3A).
About 45% are proteins related to cell metabolism, including
carbohydrate (16 unique proteins, 23%), amino acid (6 proteins,
9%), energy (4 proteins, 6%), nucleotide (4 proteins, 6%) and lipid
metabolism (1 protein, 1%). A significant number of the identified
proteins (17 proteins; 24%) are involved in translation, including
ribosomal proteins and translational factors. Noteworthy, a high
number of the identified differentially expressed proteins are
related to protein folding and degradation pathways (13 proteins,
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Proteome Changes Induced by the Amyloidogenic TTR
Variant
As described above, a clear differentiation was evident between
the proteome of cells expressing the non-amyloidogenic TTR-wt
and the highly amyloidogenic TTR-L55P variant. In BTTR-wt,
22 proteins were differentially expressed (Figure 4A), with 15
proteins up-regulated and 7 down-regulated (Figure 5, grey). By
contrast, in cells expressing the amyloidogenic TTR-L55P,
significant proteome changes were induced with 67 unique
proteins differentially expressed, 49 being up-regulated and 18
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Proteome Changes in Response to Protein Misfolding
Figure 2. 2D-DIGE differential protein expression analysis. (A) Representative 2D-DIGE gel image showing the spot map corresponding to the
internal standard (Cy2 labeling), which is common to all gels analyzed. Sample preparation and labeling were performed as described in the material
and methods section. Indicated spots showed a statistically significant variation of spot volume with 95% confidence level (p,0.05) and a minimal
fold variation of 1.3. These spots were removed for subsequent protein identification by mass spectrometry (see Table 1 for code assignment). (B)
Example of one protein present in higher abundance only in BTTR-L55P (Ubiquitin-like protein SMT3, spot 1461), one protein with an increase
abundance in BTTR-wt and BTTR-L55P (FK506-binding protein, spot 1698) and one protein present in lower abundance both in BTTR-wt and BTTRL55P (60 S acidic ribosomal protein P0, spot 1643). The spots of interested are encircled and the graphs represent the normalized spot volume. The
spot volumes are an average of the 4 biological replicates used for each experimental group. (C) PCA of the 2D-DIGE results. Each data point in the
PCA plot represents the global expression values for all spots with a significant ANOVA value (p,0.05). The PCA clustered the 6 individual Cy3 and
Cy5-labeled 2D-gel images into three discreet groups differentiated by two principle components PC1 and PC2, explaining a cumulative 82% of all
the variation. A separation between the control (carrying the empty plasmid), cells expressing the non-amyloidogenic TTR-wt (BTTR-wt) and the
amyloidogenic variant TTR-L55P (BTTR-L55P) is clearly observed. Replicate samples were encircled manually for illustration. (D) 2D-DIGE image
analysis of the protein spot identified as human TTR. Figure shows the spot expression map and three-dimensional spot image for each experimental
group.
doi:10.1371/journal.pone.0050123.g002
The high number of the differentially expressed proteins
involved in metabolic processes hints that the cell response to
protein misfolding stress is accompanied by active metabolic
changes. The major metabolic pathways altered are illustrated in
Figure 6. Following TTR-L55P expression, we detected an upregulation of several glycolytic enzymes (Figures 5A and 6),
pointing to an increase in glucose catabolism. In addition, the two
enzymes that catalyse ethanol formation from pyruvate (PDC1,
pyruvate decarboxylase 1 and ADH1, alcohol dehydrogenase) are
down-regulated (Figures 5A and 6). This could reflect a shift in the
pyruvate fate, from alcoholic fermentation to the TCA cycle and
oxidative phosphorylation. Indeed, the TCA cycle enzymes citrate
synthase (CISY1) aconitate hydratase (ACON) and isocitrate
dehydrogenase (IDHP), which are responsible for the synthesis of
a-ketoglutarate from acetyl-CoA, are up-regulated in BTTR-L55P
in compassion to control cells. Consistently, an increased
down-regulated (Figure 4A, detailed in Figure 5, black). To further
explore the involvement of the uncovered pathways involved in
TTR misfolding, we performed a functional enrichment analysis
using DAVID (Database for Annotation, Visualization and
Integrated Discovery). This analysis revealed 8 functional clusters
with a significantly enrichment score (Table 2). Significant changes
in cell metabolism (namely glucose and amino acid metabolism)
and also in the regulation of translation and protein synthesis was
noticeable. Biological themes related to plasma membrane and
mitochondria proteins and a functional enrichment in the
molecular chaperones network and in protein refolding was
observed. In contrast, the DAVID analysis using the proteins
differentially expressed in BTTR-wt revealed three significant
clusters only: mitochondrial matrix (FDR of 6.10E-07), tricarboxylic acid cycle (FDR of 3.60E-06) and plasma membrane enriched
fraction (FDR of 5.40E-03).
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Table 1. Differentially expressed proteins identified by MALDI-TOF-TOF MSMS.
Gene
symbola)
Protein names
Control/BTTR-wt
Fold Var.
P value
Control/BTTR-L55P
Fold Var.
Functionb)
Acces. codec)
Spot
no.d)
P value
MS datae)
Prot. Score
Pep. score
#Matched
MSMS
peptides
ACON
Aconitatehydratase, mitochondrial
+1.7
6.39E-03
+1.4
5.64E-03
CM
P19414
424
321
249
4
ADH1
Alcohol dehydrogenase 1
21.6
7.84E-03
21.5
1.24E-02
CM
P00330
991
617
504
9
ADH1
Alcohol dehydrogenase 1
21.5
1.07E-03
21.4
1.19E-02
CM
P00330
994
704
563
9
ADH3
Alcohol dehydrogenase 3, mitochondrial
+1.4
1.23E-02
+1.5
2.75E-03
CM
P07246
950
977
774
10
ADK
Adenosine kinase
–
–
+1.4
3.62E-03
NM
P47143
1094
537
429
4
AIM29
Altered inheritance rate of mitochondria
protein 29
21.4
8.26E-03
21.4
1.29E-02
U
P36154
1453
121
76
2
ALF
Fructose-bisphosphatealdolase
–
–
+1.3
5.18E-03
CM
P14540
1035
221
130
3
ALF
Fructose-bisphosphatealdolase
–
–
+1.3
1.85E-02
CM
P14540
1131
277
168
3
ATP synthase subunit alpha, mitochondrial
21.4
1.29E-03
–
–
EM
P07251
780
647
484
6
ATP synthase subunit beta, mitochondrial
–
–
+1.5
3.19E-04
EM
P00830
971
639
519
8
BCA1
Branched-chain-amino-acid
aminotransferase, mithocondrial
–
–
+1.6
2.60E-04
AM
P38891
1565
130
110
2
BCA2
Branched-chain-amino-acid
aminotransferase, cytosolic
–
–
+1.6
2.60E-04
AM
P47176
1565
220
199
2
BMH2
Protein BMH2
–
–
21.4
8.98E-04
PFD
P34730
1127
505
395
6
5
ATPA
ATPB
CISY1
Citrate synthase, mitochondrial
21.4
1.11E-02
+1.5
2.31E-01
CM
P00890
881
167
118
2
COX14
Cytochrome c oxidase assembly protein
COX14
–
–
+1.5
1.62E-02
U
P39103
1532
104
77
1
Peptidyl-prolylcis-trans isomerase
–
–
+1.7
7.20E-03
PFD
P14832
1519
193
133
3
NADP-specific glutamate dehydrogenase 1
–
–
+1.6
3.17E-06
EM
P07262
837
977
771
9
DLD3
D-lactate dehydrogenase [cytochrome] 3
21.4
1.29E-03
–
–
CRH
P39976
780
1020
797
8
DTD
D-tyrosyl-tRNA(Tyr) deacylase
–
–
+1.4
2.59E-02
T
Q07648
1642
84
63
2
DUG1
Cys-Glymetallodipeptidase DUG1
–
–
+1.6
3.17E-06
PFD
P43616
837
343
303
4
EF1A
Elongation factor 1-alpha
–
–
+1.4
2.82E-03
T
P02994
891
802
692
8
EF1A
Elongation factor 1-alpha
+1.3
1.82E-02
+1.5
2.60E-03
T
P02994
895
129
88
2
EF1A
Elongation factor 1-alpha
+1.4
7.81E-03
+1.6
7.65E-04
T
P02994
1013
294
238
4
EF1A
Elongation factor 1-alpha
–
–
+1.4
4.58E-03
T
P02994
1029
846
714
8
EF1B
Elongation factor 1-beta
–
–
+1.5
7.07E-05
T
P32471
1429
236
222
3
EF2
Elongation factor 2
–
–
+1.3
1.27E-03
T
P32324
1621
86
78
2
EIF3G
Eukaryotic translation initiation factor 3
subunit G
–
–
21.3
1.85E-02
T
Q04067
1097
712
570
8
ENO1
Enolase 1
–
–
+1.5
3.07E-02
CM
P00924
1542
618
567
6
ENO2
Enolase 2
–
–
+1.5
3.07E-02
CM
P00925
1542
532
501
6
FHP
Flavohemoprotein
+1.6
1.75E-03
+1.8
7.61E-06
CRH
P39676
976
704
618
7
FKBP
FK506-binding protein 1
+1.4
1.91E-04
+2.2
4.90E-04
PFD
P20081
1698
163
110
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Proteome Changes in Response to Protein Misfolding
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CYPH
DHE4
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Table 1. Cont.
Gene
symbola)
Protein names
Control/BTTR-wt
Fold Var.
Control/BTTR-L55P
P value
Fold Var.
P value
Functionb)
Acces. codec)
Spot
no.d)
MS datae)
Prot. Score
Pep. score
#Matched
MSMS
peptides
6
G3P2
Glyceraldehyde-3-phosphate dehydrogenase –
2
–
+1.6
5.88E-03
CM
P00358
1609
226
211
3
G3P3
Glyceraldehyde-3-phosphate dehydrogenase –
3
–
+1.6
5.88E-03
CM
P00359
1609
226
211
3
GBLP
Guanine nucleotide-binding protein subunit –
beta-like protein
–
+1.5
7.49E-03
T
P38011
1541
315
223
3
GBLP
Guanine nucleotide-binding protein subunit –
beta-like protein
–
+1.4
8.16E-04
T
P38011
1556
108
92
1
GPP1
(DL)-glycerol-3-phosphatase 1
–
–
21.3
3.89E-03
LM
P41277
1152
479
343
6
HIS2
Histidine biosynthesis trifunctional protein
+1.4
4.50E-03
+1,5
3.63E-04
AM
P00815
1692
419
367
6
HSP10
10 kDa heat shock protein, mitochondrial
+1.7
9.55E-03
+1.8
1.15E-03
PFD
P38910
1522
465
347
4
HSP60
Heat shock protein 60, mitochondrial
+1.6
8.31E-03
+1.8
2.12E-03
PFD
P19882
687
383
204
4
HSP60
Heat shock protein 60, mitochondrial
–
–
+1.6
1.86E-02
PFD
P19882
1438
369
307
4
HSP71
Heat shock protein SSA1
–
–
+1.4
2.62E-03
PFD
P10591
960
161
51
2
HSP72
Heat shock protein SSA2
+1.3
1.40E-02
+1.5
2.88E-03
PFD
P10592
874
165
127
2
HSP72
Heat shock protein SSA2
+1.4
8.91E-03
+1.6
4.37E-04
PFD
P10592
967
272
135
3
HSP75
Heat shock protein SSB1
–
–
21.5
4.53E-03
PFD
P11484
613
177
138
4
Heat shock protein SSC1, mitochondrial
+1.6
1.23E-02
+1.4
1.28E-02
PFD
P12398
594
310
228
6
Heat shock protein SSC1, mitochondrial
+1.4
2.27E-02
–
–
PFD
P12398
596
329
196
6
IDHP
Isocitrate dehydrogenase [NADP],
mitochondria
+2.5
7.38E-03
+2.1
1.18E-02
CM
P21954
1703
139
92
2
3
IF4A
ATP-dependent RNA helicase eIF4A
22.2
2.09E-02
–
–
T
P10081
1396
170
111
IF4B
Eukaryotic translation initiation factor 4B
–
–
+1.5
9.26E-05
T
P34167
839
358
284
5
ILV5
Ketol-acid reductoisomerase, mitochondrial –
–
21.3
6.76E-03
AM
P06168
980
565
414
7
ILVB
Acetolactate synthase catalytic subunit,
mitochondrial
–
–
21.3
1.98E-02
AM
P07342
571
152
87
4
INO1
Inositol-3-phosphate synthase
–
–
+1.5
8.65E-04
CM
P11986
1168
282
255
3
KPYK1
Pyruvate kinase 1
–
–
+1.5
4.33E-03
CM
P00549
1140
345
197
4
MPCP
Mitochondrial phosphate carrier protein
+2.4
5.97E-03
+1.5
2.05E-02
TP
P23641
1716
335
286
4
NDK
Nucleoside diphosphate kinase
–
–
+1.3
3.39E-02
NM
P36010
1407
294
288
5
PDC1
Pyruvate decarboxylase isozyme 1
–
–
21.3
1.30E-01
CM
P06169
723
1390
1222
11
PDI
Protein disulfide-isomerase
–
–
+1.3
1.05E-02
PFD
P17967
1723
474
391
5
PGK
Phosphoglycerate kinase
–
–
+1.4
2.67E-02
CM
P00560
1220
457
348
5
PGK
Phosphoglycerate kinase
+1.5
1.75E-02
+1.6
1.62E-03
CM
P00560
1248
511
431
6
PUR92
Bifunctional purine biosynthesis protein
ADE17
–
–
+1.3
1.44E-02
NM
P38009
628
349
215
3
Proteome Changes in Response to Protein Misfolding
November 2012 | Volume 7 | Issue 11 | e50123
HSP77
HSP77
PLOS ONE | www.plosone.org
Table 1. Cont.
Gene
symbola)
Protein names
Control/BTTR-wt
Control/BTTR-L55P
Functionb)
Acces. codec)
Spot
no.d)
MS datae)
Fold Var.
P value
Fold Var.
P value
Prot. Score
Pep. score
#Matched
MSMS
peptides
PYRF
Orotidine 5’-phosphate decarboxylase
21.4
1.97E-02
21.5
5.28E-03
NM
P03962
1212
185
75
2
PYRF
Orotidine 5’-phosphate decarboxylase
–
–
+1.5
2.64E-03
NM
P03962
1385
86
63
2
RL11A
60S ribosomal protein L11-A
–
–
+1.5
7.07E-05
T
P0C0W9
1429
565
482
6
RL11B
60S ribosomal protein L11-B
–
–
+1.5
7.07E-05
T
Q3E757
1429
565
482
6
RL12
60S ribosomal protein L12
–
–
+1.3
5.32E-03
T
P17079
1410
125
112
2
RLA0
60S acidic ribosomal protein P0
–
–
21.5
2.02E-03
T
P05317
1643
443
358
6
RS12
40S ribosomal protein S12
–
–
21.4
3.05E-02
T
P48589
1497
307
271
4
RS3
40S ribosomal protein S3
+1.7
9.55E-03
+1.8
1.15E-03
T
P05750
1522
212
199
2
RS5
40S ribosomal protein S5
–
–
21.3
2.65E-05
T
P26783
1196
261
153
3
SAM2
S-adenosylmethionine synthase 2
–
–
+1.5
3.19E-04
AM
P19358
971
253
191
3
7
Ubiquitin-like protein SMT3
–
–
+1.5
5.90E-06
PFD
Q12306
1461
163
146
3
Superoxide dismutase [Cu-Zn]
–
–
+1.4
9.64E-03
CRH
P00445
1442
363
247
4
SYDC
Aspartyl-tRNAsynthetase, cytoplasmic
–
–
+1.3
1.44E-02
T
P04802
628
301
228
5
SYRC
Arginyl-tRNAsynthetase, cytoplasmic
–
–
21.3
5.76E-02
T
Q05506
620
245
164
3
SYRC
Arginyl-tRNAsynthetase, cytoplasmic
–
–
21.4
4.33E-02
T
Q05506
624
473
333
5
TKT1
Transketolase 1
–
–
21.3
1.73E-03
CM
P23254
550
322
296
5
TPIS
Triosephosphateisomerase
–
–
+1.4
1.61E-02
CM
P00942
1296
432
342
5
TPIS
Triosephosphate isomerase
–
–
+1.5
7.15E-03
CM
P00942
1669
906
750
7
TPIS
Triosephosphate isomerase
–
–
+1.4
6.10E-02
CM
P00942
1671
513
443
4
TTR
Human transthyretin
–
–
–
–
–
P02766
1492
592
534
6
UBX1
UBX domain-containing protein 1
–
–
21.4
1.65E-03
PFD
P34223
806
682
562
7
VDAC1
Mitochondrial outer membrane protein porin–
1
–
+1.4
2.67E-02
EM
P04840
1220
171
135
3
YBD6
UPF0001 protein YBL036C
–
–
21.5
4.47E-04
U
P38197
1206
156
109
3
YJV7
Uncharacterized protein YJL217W
–
–
+1.8
4.62E-03
U
P40893
1380
173
117
3
All the listed proteins showed a statistical difference of spot volume ratio between the control/BTTR-wt and control/BTTR-L55P with an ANOVA p,0.05.
a)
Gene code as in the yeast genome database (www.yeastgenome.org).
b)
CM – carbohydrate metabolism; AM – amino acid metabolism; NM – nucleotide metabolism; EM – energy metabolism; LM – lipid metabolism; U – unknown; CRH – cell redox homeostasis; T – translation; TP – transport; PFD –
protein folding and degradation.
c)
Accession code of the uniprot database (www.uniprot.org).
d)
Spot number on the master gel (see fig. 1A).
e)
Summary of the protein identification results. The protein and the peptide score as given by the GPS Explorer software (Applied Biosystems). The number of peptides with MSMS data is also given.
doi:10.1371/journal.pone.0050123.t001
Proteome Changes in Response to Protein Misfolding
November 2012 | Volume 7 | Issue 11 | e50123
SMT3
SODC
Proteome Changes in Response to Protein Misfolding
Figure 3. Gene ontology characterization of the identified differentially expressed proteins. (A) Biological function. (B) Cellular location.
doi:10.1371/journal.pone.0050123.g003
unfolding and aggregation [22]. An undesirable by-product of an
increased ATP formation via cell respiration is the formation of
reactive oxygen species such as superoxide anion which may
activate the oxidative stress response. This explains the upregulation found exclusively in BTTR-L55P of superoxide
dismutase [Cu-Zn] (SODC). These data may suggest a link
between protein misfolding and oxidative cellular stress derived
from a higher ATP demand. It has been show that oxidative
modifications may facilitate aggregation of amyloidogenic proteins
[23]. Upon aging, cellular defences towards oxidative stress are
compromised and oxidative protein modifications are also likely to
accumulate, which may be synergistically linked to the disease
onset [2].
abundance of ATP synthase (ATPB) and a down-regulation of the
pentose phosphate pathway enzyme transketolase (TKT1) and
(DL)-glycerol-3-phosphatase 1 (GPP1), an enzyme involved in
glycerol synthesis, was detected. Altogether, these results point to
the channelling of glucose catabolism through the TCA cycle,
leading to an increase ATP production via cell respiration
(Figure 6). Notably, this metabolic change is not apparent in
BTTR-wt (Figure 5A in grey). In these cells, D-glucose consumption and ethanol production are similar (Figure 4B).
The increased ATP demand is surely related with the higher
energy needed to actively refold or degrade misfolded proteins. In
fact, a similar metabolic change was apparent in the response to
heat shock that is also characterized by an increased protein
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Proteome Changes in Response to Protein Misfolding
Figure 4. Expression profile in BTTR-wt and BTTR-L55P versus the control. (A) Number of the identified proteins according to the biological
function, differentially expressed between the control and BTTR-wt (grey) and between the control and BTTR-L55P (black). Upon the expression of the
amyloidogenic TTR variant L55P, a substantial increase in the number of differentially expressed proteins namely in proteins involved in cell
metabolism, translation and protein folding and degradation is clearly detected. (B) D-Glucose consumption and ethanol production during cell
growth in the control (dotted line), BTTR-wt (grey) and BTTR-L55P (black). A representative analysis is shown.
doi:10.1371/journal.pone.0050123.g004
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Proteome Changes in Response to Protein Misfolding
Figure 5. Detailed expression profiles for all the identified differentially expressed proteins, according to its functional categories:
(A) cell metabolism; (B) unknown function; (C) Cell redox homeostasis; (D) protein folding and degradation; (E) translation. Grey
bars represent fold change in protein expression in BTTR-wt versus the control while black bars represent fold change in protein expression in BTTRL55P versus the control. The vertical axis indicates the identified protein while the horizontal axis represents the fold variation in protein expression.
Additional information for each protein, including full name, can be found in Table 1. For proteins identified in different spots (with slightly different
fold variations) the average is represented in the graph.
doi:10.1371/journal.pone.0050123.g005
the cell response to protein misfolding in a more complex way than
a simple activation or inhibition of protein synthesis. Although
further studies are needed to clarify this issue, our findings provide
a good starting point by revealing potential protein targets.
Several stress-response proteins involved in protein folding and/
or degradation were also identified, with 13 proteins differentially
expressed in BTTR-L55P (10 up-regulated and only 3 downregulated, Figure 5D). Some heat shock proteins were also found
up-regulated in BTTR-wt by a similar fold variation (HSP77,
HSP60, HSP72 and HSP10; Figure 5D, in grey). Interestingly,
HSP77, HSP60 and its co-chaperone HSP10 [29] are mitochondrial-resident chaperones, involved in folding of newly imported
proteins to the mitochondria. The other identified proteins
involved in protein folding and degradation changed their
Another major set of differentially expressed proteins are
involved in translation, with a complex pattern of expression (6
proteins down-regulated and 10 up-regulated in BTTR-L55P)
(Figure 5E). These changes may reflect an adaptive response to
cellular stress. It was reported that elongation factors are upregulated in response to stress conditions, such as oxidative stress
[24]. In addition to its canonical role in translation, unique cellular
activities, such as nuclear export, cytoskeleton organization and
apoptosis, have been attributed to elongation factor protein family
in eukaryotes [25]. Interestingly, a potential role in protein quality
control and co-translational degradation has been suggested for
these proteins [26–28]. Elongation factors interact with the 26S
proteasome and this association increases when translation is
inhibited [26]. Thus, the identified proteins may be important in
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Proteome Changes in Response to Protein Misfolding
context of conformational disorders and are good protein targets
for further studies.
DIGE Screen identified three additional molecular chaperones
exclusively in BTTR-L55P: an increased abundance of HSP71
(SSA1 gene) and HSP72 (SSA2 gene) and a reduction in HSP75
(SSB1 gene). Using an animal model of ATTR, it was recently
observed that TTR deposition leads to an increase in HSP70
expression [34], in agreement with our 2D-DIGE analysis.
However, contrary to our study, the interplay between the
different isoforms of the Hsp70 was not revealed, which is highly
relevant considering that a functional difference between members
of SSA and SSB is apparent [35,36]. Both classes of chaperones
affect de novo prion formation in yeast, although with opposite
effects [37]. After heat shock, a similar trend was observed with the
SSB isoform being down-regulated while the SSA isoforms is upregulated [35].
Besides HSP70, the endoplasmic reticulum lumen resident
protein disulfide isomerase (PDI) was up-regulated exclusively in
BTTR-L55P, which appears to be in concordance with an upregulation of the HSP70 resident endoplasmatic reticulum
chaperone BiP in tissues affected with TTR aggregation [38].
Thus, even though a simple model organism was used in this study
and TTR was used as a model amyloidogenic protein, it is likely
that relevant protein targets, even for familial amyloidosis, was
revealed by this screen.
The action of molecular chaperones is an essential first step to
avoid protein aggregation. At this point, misfolded proteins are
either refolded or degraded, avoiding their accumulation. It is now
recognized that some molecular chaperones are also involved,
either directly or indirectly, in protein disposal. HSP71, found upregulated exclusively in BTTR-L55P, and its co-chaperone
HSP40 specifically recognize misfolded protein domains and
escort them for proteasome degradation [39]. Yeast HSP71 is in
fact known to interact with proteasome regulatory subunits (like
the 26S RPN 2) [40]. Noteworthy, the ubiquitin-like protein
SMT3 was found up-regulated exclusively in BTTR-L55P
(Figure 5). This protein displays 50% sequence identity with
mammalian SUMO1 protein and is essential for yeast viability.
Protein sumoylation is known to be involved in neurodegenerative
disorders such as Alzheimer’s [41] and Huntington’s diseases [42]
although its exact role is presently controversial. For the
Huntington protein, sumoylation renders the protein more soluble
and apparently more toxic by inhibiting its aggregation into
inclusion bodies [42]. In Alzheimer’s disease, SUMO1 overexpression in tissue cultured cells co-transfected with the APP gene
suppresses Ab fragment accumulation [41]. Studies in human
samples of ATTR patients showed that TTR aggregates lead to a
significant increase in ubiquitin conjugates and an impairment of
the ubiquitin-proteasome system was observed [43].
Two proteins involved in protein folding and degradation were
down-regulated exclusively in BTTR-L55P: UBX domain-containing protein 1 (UBX1) and protein BMH2 (Brain Modulosignalin Homologue, member of the ubiquitous 14-3-3 gene
family) (Figure 5D, in black). UBX1 is known to interact with
proteasome regulatory subunits and with ubiquitylated proteins
in vivo, being required for the degradation of an ubiquitylated
model substrate [44]. Interestingly, UBX1 also interacts with
FKBP [45], with several isoforms of the HSP70 family (HSP71
[40] and HSP77 [46]) and also with PDI [47], proteins
differentially expressed in response to TTR-L55P expression.
Concerning BMH2, it is likely to be related to carbohydrate
metabolism and stress response [48,49]. It was observed that the
expression of BMH proteins is altered after exposure to several
stress conditions such as heat shock or dithiotreitol [50,51]. To our
Table 2. Functional annotation enrichment analysis of the
identified proteins using the Database for Annotation,
Visualization and Integrated Discovery (DAVID ) v6.7.
Annotation
Cluster
Annotation Terms
1
FDR
Glycolysis/Gluconeogenesis
2.70E-07
Pyruvate metabolic process
2.00E-09
Alcohol catabolic process
5.50E-09
2
Plasma membrane enriched fraction
1.40E-10
3
Regulation of translation
1.90E-06
4
Cytosolic ribosome
1.10E-03
Cellular amino acid biosynthetic process
4.10E-05
Cellular amino acid catabolic process
1.50E-04
Branched chain family amino acid metabolic process 1.80E-04
5
Pantothenate and CoA biosynthesis
3.00E-03
Glutamate biosynthetic process
5.10E-04
Molecular chaperone
2.60E-06
Protein refolding
1.20E-03
6
Mitochondrial matrix
6.80E-05
7
Metal-binding
1.80E-04
8
Nucleotide-binding
5.20E-03
Annotation terms are representative of a particular cluster. FDR – False
discovery rate.
doi:10.1371/journal.pone.0050123.t002
abundance only in BTTR-L55P. The potential role of these
proteins in TTR misfolding and aggregation is illustrated in
Figure 7.
Two interesting protein revealed by our study are the
cyclophilin FK506-binding protein 1 (FKBP) and cyclophilin A
(CYPH). These proteins, that have a peptidyl-prolyl-cis-trans
isomerase (PPIase) activity, were up-regulated in BTTR-L55P
(Figure 5D). FKBP changed its abundance also in BTTR-wt but it
increases significantly in BTTR-L55P (1.4 fold vs 2.2, Table 1).
The involvement of PPIases in the cell response to protein
misfolding and aggregation is still unclear. However, recent
experiments implied this protein family in conformational
neurodegenerative disorders. It was showed that FKBP52
overexpression reduced the Ab peptide toxicity and increases the
lifespan of flies expressing Ab peptide, whereas loss of function of
FKBP52 exacerbated these Ab phenotypes [30]. Our previous
results revealed that PPIase cyclophilin H is one of the major TTR
interactuant in human plasma of ATTR patients [15]. In yeast
cells, FKBP was shown to interact with the heat shock factor 1, a
major regulator of the cell response to stress conditions such as
heat shock and protein misfolding [31]. In addition to FKBP,
CYPH was up-regulated by 1.7 fold exclusively in BTTR-L55P.
The human homologue of yeast CYPH is a major Ab-peptide
interactuant found in the brain and elevated levels of this protein
were reported in human Alzheimers disease brains [32]. Moreover, it was showed that the Ab oligomeric form has a greater
affinity for CYPH, hinting for a relevant role of this protein in
protein aggregation [32]. Interestingly, yeast CYPH interacts with
several proteasome regulatory subunits and also with ubiquitin and
SMT3 (yeast homologue of mammalian SUMO1) [33] suggesting
a role in protein degradation associated processes. Altogether,
these observations suggest an important role of PPIases in disease
development and cellular responses to protein aggregation in the
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Proteome Changes in Response to Protein Misfolding
Figure 6. Major metabolic pathways altered in BTTR-L55P. Differentially expressed proteins are highlighted, those induced are framed in
purple and those repressed are framed in green. Protein full names can be identified in Table 1.
doi:10.1371/journal.pone.0050123.g006
knowledge, no association between 14-3-3 proteins and TTR
aggregation has been described until now.
Three proteins with unknown or poorly characterized functions
were also identified (Figure 5B). In addition to a down-regulation
of AIM29 (already detected in BTTR-wt), the UPF0001 protein
YBL036C was also down-regulated, while the uncharacterized
protein YJL217W and cytochrome c oxidase assembly protein
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COX14 increase its abundance. The biological function of these
proteins is not yet known. Some data seem to relate the YJL217W
protein in the regulation of enolase1 [52]. This could be related
with the detected increase in glucose catabolism and, considering
that yeast enolase1 also function as a heat shock protein [53], with
the misfolding of TTR-L55P. This is an interesting hypothesis that
requires further investigation, feasible in yeast considering that the
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Proteome Changes in Response to Protein Misfolding
Figure 7. TTR misfolding and protein quality control mechanisms. Differentially expressed proteins are highlighted, those induced framed in
purple and those repressed are framed in green. Protein full names are indicated in Table 1.
doi:10.1371/journal.pone.0050123.g007
individual protein spots were quantitatively analyzed. Our results
showed a clear cut differentiation between the expression of TTRwt and TTR-L55P, distinguishing the cell response to the
expression of a heterologous protein from the cell response to
protein misfolding and aggregation. The proteome changes
observed by the expression of TTR-wt and TTR-L55P share
about 20 proteins in common that may be attributed to the
expression of a heterologous protein in yeast. Expression of the
amyloidogenic TTR-L55P caused changes in about 50 exclusive
proteins that may be specifically associated to amyloidogenic
behavior and protein aggregation. Several heat shock protein (as
HSP70 and HSP60) and members of PPIase family (cyclophilin A
and FKBP) are up-regulated upon TTR-L55P expression. In
addition, several other processes were influenced by the misfolding
and aggregation of an amyloidogenic protein such as carbohydrate
and amino acid metabolism, energy production, translation and
oxidative stress response. The expression of the amyloidogenic
TTR variant causes a metabolic shift towards energy production
via mitochondrial cell respiration which is related to the high
energy demand of refolding and degradation pathways. This in
turn may promote oxidative stress. The up-regulation of
ENO1 yeast null mutant is viable. COX14 Is an integral
mitochondria membrane protein and a yeast null mutant for this
protein displays a respiratory growth deficiency [54]. Thus, the
increased expression of this protein may results in an improved
mitochondria function. No significant human homology was found
for this protein. Finally, UPF0001 protein YBL036C also
increased significantly its abundance in BTTR-L55P. A BLAST
homology search revealed that this yeast protein shares 43%
identity with proline synthase co-transcribed bacterial homolog
protein, whose function is nevertheless not yet known.
Concluding Remarks
The proteome response to protein misfolding and aggregation is
a key factor in understanding onset and evolution of conformational disorders. By uncovering specific proteins and pathways
effective therapeutic strategies may be devised. In this study, we
performed a high-throughput proteomics analysis using the 2DDIGE technology to screen changes in protein abundance upon
the expression of an amyloidogenic protein (TTR-L55P variant) in
comparison with the expression of the non-amyloidogenic version
of the same protein (TTR-wt). With this approach, around 1800
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Proteome Changes in Response to Protein Misfolding
D-Glucose and ethanol were enzymatically assayed during cell
growth using the D-Glucose assay kit and Ethanol assay kit
(NZYTech), following the manufacturer instructions.
mitochondrial chaperones (HSP60, HSP77, HSP10, protein
disulfide-isomerase) is also consisted with increased oxidative
stress and higher energy demands needed to face misfolding and
aggregation.
Although in transthyretin amyloidosis TTR accumulates as
amyloid deposits in the extracellular space, we believe that TTR is
a good amyloidogenic protein model to investigate the cellular
responses to the general misfolding and aggregation problem.
TTR has a high number of amyloidogenic point mutations and
thus the proteome response may be investigated with different
amyloidogenic potential against a defined genetic background. It
was recently discovered that intracellular signaling mechanisms
related to extracellular TTR aggregates in ATTR was elicited
[34,38,43]. Notably, similarly to our results, changes in the
chaperone network (such as HSP70 protein family and endoplasmatic resident chaperones) and degradation processes were
detected [38,43]. Moreover, a striking parallel was found on the
specific increased expression of PPIases in yeast expressing TTRL55P, found to be a specific TTR interacting partner only in
symptomatic ATTR subjects [15]. Yeast can thus be used as a
model to investigate TTR effects on living cells that is highly
relevant in the context of ATTR and other misfolding diseases.
Moreover, more than 100 TTR point mutants are known to be
associated to amyloid disease and the availability of a complete
gene set collection of yeast single gene deletion mutants shows its
potential for large scale screening.
Western Blotting and Protein Aggregate Filtration Assay
TTR expression levels were relatively quantified by western blot
using an anti-human TTR polyclonal antibody (SC 13098, Santa
Cruz Biotechnology). Protein extraction was performed by glass
bead lysis as previously described [56] and protein concentration
was determined using the Bio-Rad Bradford assay reagent.
Proteins (30 mg per lane) were separated using denaturant urea
gel electrophoresis in a Mini-protean 3 system (Bio-Rad). Proteins
were transferred to PVDF membranes (Immobilon-P PVDF,
Millipore), using the Mini Trans-Blot system (Bio-Rad) and the
membrane was blocked overnight at 4uC in TBS-T (50 mM Tris
and 150 mM NaCl, pH 7.5 with 0.1% (v/v) Tween 20) containing
5% (w/v) skimmed milk. TTR polyclonal antibody was used at a
dilution of 1:5000. Ponceau S staining was used to monitor protein
transfer and to confirm that equal amount of protein were loaded
in each lane. Washes, secondary antibody and detection procedures were performed using the BM Chemiluminescence Western
Blotting Kit (Roche), following the manufacturer’s instructions.
Protein aggregate filtration assay was performed essentially as
described [57,58], with slight modifications. Briefly, yeast cells
expressing TTR variants were suspended in modified lysis buffer
(50 mM Tris containing 5 mM MgCl2, 0.1 mM EDTA, 2 mM
PMSF and proteases cocktail inhibitor) and lysed with glass beads
as described [56]. Cell ghosts were removed by centrifugation at
2500 g for 5 min at 4uC. Supernatants were collected as the crude
protein extract and protein concentrations in all samples were
equalized. 150 ml Of the crude extract was centrifuged at 14000 g
for 30 min at 4uC to separate the soluble from aggregated
proteins. The pellet fractions, containing the insoluble aggregated
proteins, were suspended in 2% (w/v) SDS or in lysis buffer.
Samples were filtered on a dot-blot filtration unit (Bio-Rad)
through a nitrocellulose membrane (0.2 mm pore size) that was
previously blocked and pre-equilibrated with 2% (w/v) SDS.
Filters were washed twice with 0.1% (w/v) SDS (except the
samples suspended in lysis buffer, which were washed with the
same buffer). TTR aggregates were imunodetected using the antihuman TTR polyclonal antibody at a dilution of 1:5000. To assess
the assay specify toward TTR protein aggregates and not soluble
TTR, the crude extract and the soluble protein fraction were
analysed through a nitrocellulose membrane (as a regular dot-blot
assay) and a blocked nitrocellulose membrane.
Materials and Methods
Bacteria, Yeast Strains and Culture Conditions
Escherichia coli strain used (DH5a, F-; recA1; endA1; thi-1; gyrA96;
hsdR17; supE44; relA1;w89d; lacZ; DM15 l-) was cultured in LB
medium [1% (w/v) NaCl, 1% (w/v) tryptone, 0.5% (w/v) yeast
extract] at 37uC. Solid LB medium contained 2% (w/v) agar.
Transformed strains, carrying the plasmids, grew in LB medium
supplemented with 0.1 mg.ml21 ampicillin. Saccharomyces cerevisiae
strain used was the BY4741 (genotype BY4741 MATa; his3D1;
leu2D0; met15D0; ura3D0) from Euroscarf collection (Frankfurt,
Germany). Strains were kept in YPGlu agar slopes [0.5% (w/v)
yeast extract, 1% (w/v) peptone and 2% (w/v) D-glucose and 2%
(w/v) agar] at 4uC and cultured in liquid YPGlu medium at 30uC.
BY4741 strain carrying the TTR expression plasmids were
cultured in YNB minimal medium without uracil [0.67% (w/v)
yeast nitrogen base, 2% (w/v) D-glucose and 0.025% (w/v) Lmethionine, L-histidine, L-leucine].
Protein Sample Preparation and CyDye Protein Labeling
Plasmids and Yeast Transformation for TTR Expression
For 2D-DIGE analysis, cells were collected at mid-log phase of
growth, harvested by centrifugation and suspended in 2D-DIGE
labeling buffer [7 M urea, 2 M thiourea, 4% (w/v) CHAPS and
30 mM Tris] containing proteases inhibitors (PMSF and proteases
cocktail inhibitor, Sigma). Yeast cells were lysed using glass beads
as previously described [56]. All samples (four biological replicates)
were processed in parallel. Protein extracts were clarified by
centrifugation at 12000 g for 15 min at 4uC. The cell lysate pH
was then carefully adjusted to 8.5 with NaOH and afterwards
protein concentration was determined using the 2D Quant Kit
(GE Healthcare) with BSA as standard. Prior to electrophoresis,
protein extracts were labeled with CyDyesTM (GE Healthcare),
following the manufacturer instructions. Briefly, proteins were
labeled by mixing 240 pmol of fluorochromes (Cy3 or Cy5) with
30 mg of protein and incubated on ice for 30 min in the dark.
Lysine (1 ml, 10 mM) was then added to quench the reaction and
the samples were left on ice for 10 min in the dark. A pooled
Plasmids p426GPD carrying the different TTR genes (TTR-wt
and TTR-L55P) were a king gift of Dr. Tiago Outeiro (Cell and
Molecular Neuroscience Unit, IMM, Portugal). Plasmid DNA
extraction was performed using the Wizard Plus SV Minipreps
DNA Purification System (Promega), following the manufacturer’s
instructions. DNA concentration was evaluated spectrophotometrically at 260 nm and purity was assessed by standard procedures.
BY4741 yeast strain was transformed by the lithium acetate
method, and transformants were selected on minimal agar plates
deficient in uracil, following standard procedures [55]. Yeast cells
were also transformed with the p426GPD vector without the
inserted gene as control. Yeast growth curves were monitored at
640 nm and phenotypic growth assays were carried out by
spotting 3 ml of late-exponential-phase culture, sequentially diluted
(approx. 2000–20 cells), in selective medium. Growth was
recorded after 2 days at 30uC.
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Proteome Changes in Response to Protein Misfolding
internal standard was performed by mixing 15 mg of each sample
analyzed that was labeled with Cy2 dye and included in all gel
runs. A dye swap was used between Cy3 and Cy5 to avoid
problems associated with preferential labeling.
using the Ettan Digester robot from the same workstation.
Supernatants were collected, vacuum dried and peptides were
thoroughly dissolved in 3 ml of 50% (v/v) acetonitrile containing
0.1% (v/v) trifluroacetic acid. Peptides were spotted on MALDI
targets using a matrix consisting of 7 mg.ml21 of a-cyanohydroxycynamic in 50% (v/v) acetonitrile containing 0.1% (v/v)
trifluroacetic acid. Monoisotopic peptide mass determinations
were carried out using the MALDI-TOF/TOF 4800 Plus mass
spectrometer (Applied Biosystems). For spots with a low signal, the
peptide mixture was purified and concentrated using home-made
chromatographic microcolumns using GELoader tips packed with
POROS R2 as described [59]. MS experiments were performed in
positive reflectron mode for monoisotopic peptide mass determination. The mass spectrometer was externally calibrated using the
4700 Calibration Mix (Applied Biosystems). MS spectra were
collected in a result-independent acquisition mode, typically using
1000 laser shots per spectra and a fixed laser intensity of 3100 V.
For tandem experiments, fifteen of the strongest precursors were
selected for MS/MS, the weakest precursors being fragmented
first. MS/MS analyses were performed using CID (Collision
Induced Dissociation) with 1 kV collision energy at 1 6 106 torr
air pressure. Spectra were collected using a fixed laser intensity of
4200 V and 2000 laser shots. Raw data were generated by the
4000 Series Explorer Software v3.0 RC1 (Applied Biosystems) and
tryptic peptide contaminant m/z peaks resulting from trypsin autodigestion were excluded when generating the peptide mass list
used for comparison with the theoretical tryptic digest. Proteins
were identified by the GPS explorer (Applied Biosystem) using the
following search parameters: 1) carboxyiodomethylation of cysteine residues and methionine oxidation were taken as fixed and
variable modifications, respectively; 2) tolerance of one missed
cleavage; 3) maximum error tolerance of 50 ppm for MS data and
0.3 Da for the MS/MS data. Protein identifications were further
confirmed using the ProteinPilot software (Applied Biosystem).
Gene ontology and pathway analysis. The identified
proteins were categorized into functional groups using the gene
ontologies annotations available at the Universal Protein Resource
Protein Knowledge database (UniProtKB; http://www.uniprot.
org/), Kyoto Encyclopedia of Genes and Genomes (KEGG;
http://www.genome.jp/kegg/) and Saccharomyces Genome Database (www.yeastgenome.org/). BLAST searches were performed
using the UniProtKB tools. A functional annotation enrichment
analysis was performed using DAVID (Database for Annotation,
Visualization and Integrated Discovery) [60,61], available at
http://david.abcc.ncifcrf.gov/. In addition to gene ontology, the
PIR (Protein Information resource), COG (Clusters of Orthologous Groups), Uniprot, KEEG, Interpro and SMART (Single
Modular Architecture Research Tool) databases were used within
DAVID to generate biological theme by grouping like terms,
thereby creating functional annotation clusters. The results were
manually checked for significant enriched terms.
2D Gel Electrophoresis
For 2D gel electrophoresis, the two samples to be run on the
same gel plus the internal standard were mixed before adding 2x
lysis buffer [7 M urea, 2 M thiourea, 4% (w/v) CHAPS, 6 ml.ml21
DeStreak reagent (GE Healthcare)] and 2% (v/v) ampholytes
immobilized pH gradient buffer (pH 3–10 NL, GE Healthcare) to
a final volume of 125 ml. Isoelectric focusing was carried out on
pH 3–10 IPG-strips (24 cm, non-linear gradient; GE Healthcare)
using the IPGphor3 system from GE Healthcare. ImmobilineDryStrips were rehydrated overnight with 450 ml DeStreak Rehydration Solution (GE Healthcare), complemented with 1.5% ampholytes, before cup-loading of proteins and IEF on an EttanIPGphor
Manifold (GE Healthcare). The migration was performed at 20uC
(60 V for 2 h; gradient from 60 to 500 V for 5 h; hold 500 for 1 h,
gradient from 500 to 1000 for 3 h; hold 1000 V for 1 h; gradient
from 1000 V to 8000 V for 4 h, hold 8000 V until 64 000 Vh).
After the IEF, IPGstrips were equilibrated twice for 15 min in
equilibration buffer [50 mM Tris-HCl pH 8.8, 6 M urea, 30% (v/
v) glycerol, 2% (w/v) SDS and 0.002% (w/v) bromophenol blue]
supplemented with 1% (w/v) DTT and then with 2.5% (w/v)
iodoacetamide. Second-dimension SDS-PAGE was performed
using 1.0 mm large-format 12.5% polyacrilamide resolving gel
and run at 20uC overnight with 1.5W per gel, using the
EttanDALTtwelve system (GE Healthcare). Glass plates used for
picking gels were treated with Bind-Silane solution [80% (v/v)
ethanol, 2% (v/v) acetic acid and 0.1% (v/v) Bind-Silane (GE
Healthcare)] before casting. The gels ran simultaneously, with a
dye switching between repetitions, plus the internal standard. In
the end, ninety micrograms of proteins were loaded on each 2D
gel.
Scanning and Image Analysis
2D-DIGE gels were scanned at a pixel size of 100 mm using a
Typhoon Imager 9400 (GE Healthcare) at three different
wavelengths corresponding to the different CyDyes. Gel images
were exported into Progenesis SameSpot V3 image analysis system
(Nonlinear Dynamics), where quantitative analysis of protein spots
was performed. Following automatic and subsequent manual
editing, aligning and matching procedures as part of the
Progenesis SameSpot workflow, ANOVA p-values between the
samples were calculated within the Progenesis SameSpot software.
Variation of protein expression was considered statistically
significant if the absolute abundance variation was at least 1.3fold between spots of any experimental group with a p,0.05 by
ANOVA. Unsupervised PCA correlation analysis was performed
using the statistical tool within the gel analysis software. Clustering
of each sample was based on the expression pattern of each spot
with a significant ANOVA p-value. The spots of interest were
visually checked and selected for protein identification by mass
spectrometry.
Acknowledgments
The authors acknowledge Dr. Tiago Outeiro (Cell and Molecular
Neuroscience Unit, IMM, Portugal) for the gift of TTR-expressing
plasmids.
Spot Handling and Mass Spectrometry Analysis
Spots of interest were excised from gels using the EttanSpot
Picker from the Ettan Spot Handling Workstation (GE Healthcare). After washing and desalting in 50 mM ammonium
bicarbonate, 50% (v/v) methanol and 75% (v/v) acetonitrile,
spots were then digested with Trypsin Gold for 6 h at 37uC (MS
grade, Promega, 5 mg.mL–1 in 20 mM ammonium bicarbonate)
PLOS ONE | www.plosone.org
Author Contributions
Conceived and designed the experiments: RAG SP JR CC. Performed the
experiments: RAG CF GC SP MSS RMR. Analyzed the data: RAG SP JR
FP AVC APF CC. Wrote the paper: RAG GC FP MSS APF CC.
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Proteome Changes in Response to Protein Misfolding
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