Simultaneous Detection of Changes in Protein Expression and

ARTICLE pubs.acs.org/jpr

Simultaneous Detection of Changes in Protein Expression and Oxidative Modification as a Function of Age and APOE Genotype Robert M. DeKroon,†,‡ Cristina Osorio,†,§ Jennifer B. Robinette,†,§ Mihaela Mocanu,†,§ Witold M. Winnik,|| and Oscar Alzate*,†,‡,§ UNC Systems-Proteomics Center, §Program of Molecular Biology and Biotechnology and ‡Department of Cell and Developmental Biology, School of Medicine, University of North Carolina, Chapel Hill, North Carolina 27599, United States NHEERL Proteomics Research Core, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States

)

†

bS Supporting Information ABSTRACT: To better elucidate temporal changes in protein oxidation resulting from aging and the Alzheimer’s diseaseassociated Apolipoprotein E (ApoE), we developed a 2DDIGE-based method for simultaneously detecting differential expression and carbonyl oxidation of proteins. Specifically, we examined changes in the levels of oxidation and total protein expression in hippocampi from young-adult (25-30 weeks) and old (76-97 weeks) mice transgenic for the human Apolipoprotein E gene (APOE, APOE3, APOE4) isoforms, APOE3 or APOE4. Protein samples were labeled with either a fluorescent aminooxyacetamide (Alexa Fluor 488) to detect carbonyl modifications or with NHS-Cy3 to detect total protein expression. A protein sample used as an internal control was labeled with NHS-Cy5 and run on each gel. DIGE analysis revealed 38 differentially oxidized and 100 differentially expressed protein spots with significantly different levels (P < 0.05). For oxidized proteins, principal component analysis revealed two distinct clusters: one in which oxidation increased with age independent of APOE genotype, and the second in which oxidation was dependent on APOE genotype. For total protein expression, principal component analysis revealed a large overlap between changes with overall aging and between APOE genotypes. The use of a fluorescent tag to label oxidized proteins, in combination with a NHS-Cy3 to label total protein, makes it possible to determine changes in both protein oxidation and protein expression levels in a single experiment. These studies reveal that the expression levels of peroxiredoxin protein family members Prdx2, 3, and 6 are modified by age, APOE genotype, or both. KEYWORDS: APOE genotype, Alzheimer’s disease, carbonylation, oxidation, aldehyde labeling, proteomics, Peroxiredoxin-2, -3, -6

’ INTRODUCTION Protein oxidation is a widely accepted model of aging and has been implicated in a number of age-associated diseases, such as Parkinson’s,1 diabetes,2 cardiovascular,3 and Alzheimer’s disease (AD).4-7 An individual’s susceptibility to AD and cardiovascular diseases is also influenced by their APOE genotype.8-10 The APOE gene has three common alleles, APOE ε2, ε3, and ε4. In comparison with APOE3, which is considered the “normal” genotype, the APOE4 allele increases susceptibility to late onset AD, while both the APOE4 and APOE2 alleles increase the risk of cardiovascular disease.11 Among the most stable and irreversible markers of protein oxidation are reactive carbonyl groups (aldehyde formation).12-15 Carbonyl groups are produced by the direct oxidation of lysine, arginine, histidine, threonine, and proline amino acid residues;14 they may also be produced by secondary reactions of cysteine, histidine and lysine with lipid peroxidation products containing carbonyl groups or advanced glycation end products.14 Currently, r 2011 American Chemical Society

detection of aldehyde-modified proteins by 2D-PAGE typically involves transferring DNPH (2,4-dinitrophenyl hydrazine)-labeled samples to a membrane followed by Western blotting.12 A duplicate gel is then required for spot picking and subsequent identification by mass spectrometry (MS). In this study, we used a fluorescent hydroxylamine dye to directly detect carbonyl modifications on proteins. This dye has several strongly hydrophilic zwitterionic functional groups and a polar linker between the fluorescent ring and the chemically reactive hydroxylamine group. The polar groups enhance the solubility of the labeled proteins. The flexible linker minimizes the steric hindrance caused by the bulky portion of the dye and allows easier penetration of the reactive hydroxylamine end of the molecule into an unfolding protein so that it can react with the aldehyde group. By including a Cy3-labeled aliquot of the Received: September 24, 2010 Published: January 07, 2011 1632

dx.doi.org/10.1021/pr1009788 | J. Proteome Res. 2011, 10, 1632–1644

Journal of Proteome Research

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Figure 1. Experimental design. Protein lysates from hApoE3/3-TR and hApoE4/4-TR young-adult and old mice hippocampi were labeled with NHSCy3 to determine total differential protein expression and with AF-488 to determine differential protein oxidation. An aliquot from each sample was prepared and all the aliquots were pooled to produce an internal control that was labeled with NHS-Cy5. Labeled proteins were pooled and then fractionated using 2D-DIGE electrophoresis, and the proteins of interest were analyzed by tandem mass spectrometry. Matching and statistical comparisons were possible by using the same internal control in all the gels (indicated with the block arrows).

same sample and a Cy5-labeled internal control (IC), it is possible to determine both differential protein oxidation and differential protein expression levels in a single experiment. This methodology allows for use of smaller sample size and is effective in determining changes in the level of protein oxidation in hippocampi from young-adult and old mice transgenic for human APOE3 or APOE4 (hApoE). Differential in-gel electrophoresis (DIGE) analysis revealed oxidized and total protein spots with significantly different (P < 0.05) expression levels. Oxidized proteins did separate into two distinct clusters: one in which oxidation increased with age independent of APOE genotype, and the second in which oxidation was dependent on APOE genotype. In contrast, for total protein expression the effects of aging and APOE genotype largely overlapped.

’ MATERIALS AND METHODS Sample Preparation

All the tissues for these experiments were donated by Dr. Patrick Sullivan (Duke University, School of Medicine) from animals maintained under protocols approved by Duke University’s Institutional Animal Care and Use Committee. Hippocampi from young-adult (25-30 weeks) mice transgenic for hApoE3

(n = 3) or hApoE4 (n = 3) and old (76-97 weeks) hApoE3 (n = 3) or hApoE4 (n = 3) were homogenized in lysis buffer (8 M urea, 4% CHAPS, 30 mM Tris, pH 8.5) supplemented with a protease inhibitor cocktail (Roche) and NaVO4, as described elsewhere.16 Homogenates were then sonicated on ice and centrifuged at 14 000 rpm for 20 min. The resulting supernatants were cleaned using the 2D Clean-Up kit (GE Healthcare, Piscataway, NJ), according to the manufacturer’s instructions. The final pellet was resuspended in lysis buffer and the protein concentration was determined using a 2D Quant kit (GE Healthcare). Sample Labeling

To detect aldehyde-modified proteins, lysates were labeled with Alexa Fluor 488 C5-aminooxyacetamide (AF-488, Sigma, St. Louis, MO). An aliquot of each lysate was also labeled with NHS-Cy3 (GE-Healthcare) to determine total protein expression levels. An internal control (IC) was prepared as described below, and then labeled with NHS-Cy5 (GE-Healthcare). A 1 mM stock of fluorophore was prepared by dissolving 1 mg of AF-488 in 1.117 mL Milli-Q water. Aliquots of 7.5 μL (7.5 nmol) were dried down in a speed-vac, protected from light, and stored at -80 °C until use. To label the samples, a volume of lysate equivalent to 60 μg of protein was added to the lyophilized 1633

dx.doi.org/10.1021/pr1009788 |J. Proteome Res. 2011, 10, 1632–1644


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Table 1. Identities of Differentially Oxidized and Expressed Proteins (t test) Oxidized t test

average ratio

master no.

E4O vs E4Y E3O vs E3Y Y vs O E3Y vs E4Y E3O vs E4O E4 vs E3 no. peptides

names

oxidized

total

accessions

-1.75

-1.16

P63017

440

0.33

1

0.43

0.2

0.11

0.031

13

Heat shock cognate 71 kDa protein

445

0.1

0.9

0.2

0.45

0.067

0.05

11


447

0.44

0.62

0.77

0.043

0.22

0.0088

5

Stress-70 protein, mitochondrial

-3.39

565

0.35

0.95

0.47

0.38

0.12

0.05

8 7

Tubulin alpha-1A chain Tubulin alpha-4A chain

-1.70

þ 1.24

P68369 PS8368

779

0.16

0.26

0.043

0.79

0.68

0.68

2

Gamma-enolase

78S

0.24

0.99

0.52

0.28

0.18

0.05

8

Gamma-enolase

-2.23

þ1.40

P17183

790

0.11

0.29

0.05

0.095

0.51

0.22

10

811

0.6

0.84

0.87

0.05

0.24

0.042

5

P63017 P38647

P17183

Gamma-enolase

P17183 -1.93

Alpha-enolase

P17182

910

0.083

0.49

0.18

0.018

0.043

0.0096

6

Actin, cytoplasmic 2

-1.73

P63260

917

0.6

0.89

0.79

0.11

0.25

0.034

3


-1.72

P63260

1990

0.37

0.093

0.039

0.83

0.33

0.86

16

Alpha-internexin

P46660

Total t test master

E4O vs

E3O vs

E3Y vs

E3O vs

E4 vs

no.

no.

E4Y

E3Y

Y vs O

E4Y

E4O

E3

peptides

268 333 336

0.59 0.11 0.89

0.54 0.13 0.037

0.78 0.24 0.26

0.078 0.03 0.39

0.51 0.06 0.34

0.036 0.0084 0.96

5 18 11

339 385 401 409 442

0.55 0.024 0.38 0.21 0.024

0.89 0.6 0.88 0.51 0.31

0.76 0.41 0.92 0.1 0.016

0.055 0.71 0.0081 0.063 0.097

0.095 0.41 0.11 0.48 0.5

0.0039 0.41 0.0005 0.049 0.33

3 5 4 4 5 9

452

0.0089

0.14

0.017

0.045

0.72

0.22

453

0.0066

0.066

0.05

0.02

0.012

0.038

544 572 592 613

0.85 0.8 0.53 0.079

0.022 0.29 0.49 0.15

0.41 0.34 0.41 0.022

0.8 0.9 0.33 0.31

0.086 0.54 0.036 0.3

619 S21 626 627 631 639

0.91 0.0094 0.67 0.037 0.13 0.16

0.93 0.97 0.43 0.34 0.15 0.13

0.81 0.18 0.97 0.062 0.031 0.66

0.04 0.0011 0.85 0.017 0.13 0.025

0.049 0.18 0.05 0.12 0.43 0.81

66S 914

0.65 0.031

0.51 0.49

0.85 0.022

0.14 0.25

918

0.0041

0.67

0.31

0.2

954

0.3

0.69

0.75

978

0.45

0.0041

993

0.089

996

0.9

names

accessions

Ubiquilin-2 Heat shock cognate 71 kDa protein V-type proton ATPase catalytic subunit A

Q9QZM0 P63O17 P50516

Stress-70 protein, mitrochondrial Dihydropyrimidinase-related protein 2 Dihydropyrimidinase-related protein 2 Heterogeneous nuclear ribonucleoprotein K Heterogeneous nuclear ribonucleoprotein K Tubulin alpha-1A chain

P38647 O08553 O08553 P61979 P61979 P68369

8 11

Tubulin alpha-4A chain Tubulin alpha -1A chain

P68368 P68369

0.36 0.67 0.036 0.21

7 8 6 5 13 13 19

Tubulin alpha-4A chain Tubulin alpha-1 A chain Tubulin alpha-4A chain Pyruvate dehydrogenase protein X component, mitochondrial ATP synthase subunit beta, mitochondrial Dynactin subunit 2 Gamma-enolase

P68368 P68369 P68368 Q8BKZ9 P56480 Q99KJ8 P17183

0.0008 0.0025 0.22 0.007 0.1 0.14

2 10 14 16 16 6

Gamma-enolase Gamma -enolase Gamma -enolase Gamma -enolase Glial fibrillarv acidic protein Alpha-enolase

P17183 P17183 P17183 P17183 P03995 P17182

0.012 0.82

8 5

Protein phosphatase 1 regulatorv subunit 7 Guanine nucleotide-binding protein G(I)/G(S)/G(T)

Q3UM45 P62874

0.021

0.01

6

subunit beta-1 Phosphoglycolate phosphatase

Q8CHP8

0.22

0.0022

0.033

5

EF-hand domain-containing protein D2

Q9D8Y0

0.05

0.04

0.22

0.048

6

Glvoxalase domam-containins protein 4

Q9CPV4

0.31

0.17

0.034

0.22

0.026

13

Prohibitin

PS7778

0.25

0.37

0.53

0.018

0.04

5

Tropomyosin alpha-1 chain

P58771

2


P21107

0.08 44

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Table 1. Continued Total t test master

E4O vs

E3O vs

no.

E4Y

E3Y

Y vs O

E3Y vs

E3O vs

E4 vs

no.

E4Y

E4O

E3

peptides

names

accessions

1021

0.58

0.61

0.67

0.26

0.012

0.017

4

14-3-3 protein zeta/delta

P63101

1022

0.81

0.28

0.46

0.44

0.0011

0.11

5

Calretinin

QO8331

1023

0.53

0.43

0.43

0.34

0.0015

0.11

10

Calretinin

QO8331

0.026

0.39

0.031

0.15

5

0.14 0.6

0.039 0.39

0.7 0.043

0.73 0.013

10 5

1028 1071 1096

0.12 0.17

0.091 0.14

Rho GDP-dissociation inhibitor 1

Q99PT1

Peroxiredoxin-6 Thioredoxin-dependent peroxide reductase. mitochondrial

008709 P20108 Q9R257

1106

0.8

0.023

0.12

0.53

0.034

0.045

2

Heme-binding protein 1

1114

0.0046

0.47

0.098

0.051

0.022

0.017

2

Peroxiredoxin-2

Q61171

1115

0.61

0.006

0.043

0.83

0.19

0.77

4

UMP-CMP kinase

Q9DBP5

1123

0.021

0.43

0.16

0.014

0.089

0.0055

5

Phosphatidylethanolamine-binding protein 1

P70296

1129

0.22

0.75

0.83

0.13

0.0047

0.001

9

Peroxiredoxin-2

Q61171

1172

0.45

0.9

0.43

0.25

0.019

0.034

5

Alpha-synuclein

O55042

fluorophore, and Milli-Q water was added to a final volume of 7.5 μL. The reaction mixture was incubated at RT for 2 h followed by overnight incubation at 4 °C. The Internal Control (IC), to be loaded in all gels, was prepared by pooling equal amounts of protein (30 μg) from all 12 samples, and then labeled with 400 pmol of NHS-Cy5 for every 30 μg of protein (Figure 1). A 30 μg aliquot of total protein from each individual sample was labeled with 400 pmol of NHS-Cy3. The labeling reaction was carried out on ice for 30 min, protected from light. To quench the reaction, 1 μL of 10 mM lysine was added, and the reaction was then incubated for an additional 10 min on ice in the dark. After labeling, corresponding samples were combined. An equal volume of 2 sample buffer (8 M urea, 4% CHAPS, 20 mg/mL DTT, 2% (v/v) IPG buffer 4-7 (GE Healthcare)) was added and the mixture was placed on ice for 15 min. Rehydration buffer (8 M urea, 4% CHAPS, 2 mg/mL DTT, 1% (v/v) IPG buffer 4-7) was then added to a final volume of 250 μL. 2D Gel Electrophoresis and Imaging

The labeled samples (250 μL) were applied to immobilized pH gradient (IPG) strips (24 cm, pI range 4-7, GE Healthcare) which had been hydrated in 200 μL of rehydration buffer for 2 h at RT. Samples were actively rehydrated at 30 V up to 450 Vhr, followed by isoelectric focusing using an Ettan IPGphor II (GE Healthcare) for a total of 68 kVhr (step to 500 V for 1 h, step to 1000 V for 1 h, step to 8000 V to a total of 68 kVhr). After isoelectric focusing, the samples were reduced and alkylated by placing the strips in 20 mL equilibration buffer (6 M urea, 50 mM Tris, pH 8.8, 30% glycerol, 2% SDS) containing 5 mg/mL DTT for 10 min, after which the strips were incubated for 10 min in fresh equilibration buffer containing 45 mg/mL iodoacetamide. Each IPG strip was placed on a 12% homogeneous polyacrylamide gel (Sigma), and run at 9 mA for 16 h in an Ettan-Dalt Six (GE Healthcare). Individual images of the AF-488-, Cy3-, and Cy5-labeled proteins in each gel were obtained using a GE Healthcare Typhoon TRIOþ imager, using excitation/emission wavelengths of 480/530 nm for AF-488, 520/590 nm for Cy3, and 620/680 nm for Cy5.

Data Analysis

Gels were analyzed using DeCyder 2D v 7.0 software (GE Healthcare). A “spot number” of 4500 was used to generate spot maps using the differential in-gel analysis (DIA) component. Spot maps were filtered with the built-in algorithm using a “max slope” of 1.0, and manually edited to remove signals from dust particles. Normalization and standardization of the spot maps for each sample were performed using the biological variation analysis (BVA) component of the software. Spot maps for each gel image (individual samples and IC) were matched and a statistical comparison (t test, 2-way ANOVA) performed between young and old, as well as hApoE3 and hApoE4 data for each spot. The extended data analysis (EDA) component of DeCyder was used for principal component analysis (PCA) and partition cluster analysis; in addition DeCyder’s EDA module was used to interrogate Gene Ontology (http://www.geneontology.org/) and KEGG (http://www.geneome.jp/kegg/) protein databases for protein function and pathway analysis. Protein Digestion, Extraction, and Preparation for Mass Spectrometry

Spots showing differential expression, using the criteria described above, were excised from the pick gel using Ettan spot picker (GE Healthcare), digested with trypsin, and the peptides were extracted. A modified digestion procedure was used.17 Briefly, gel plugs were destained twice using (1) 100 μL of 200 mM ammonium bicarbonate (AMBIC) and 40% (v/v) acetonitrile (ACN), and (2) 25 mM AMBIC in 50% (v/v) ACN. The gel plugs were first dehydrated using 50 μL ACN, which was then removed using a vacuum evaporator (Centrivap, Labconco). The gel plugs were then rehydrated using 10 μL of Proteomics grade trypsin (Sigma, Cat # T 6567, 20 μg/mL) dissolved in trypsin reaction buffer (40 mM AMBIC, 2% (v/v) ACN). After 2 h at RT, a 20 μL aliquot of the trypsin reaction buffer was added, and the digestion solutions were incubated overnight in an Eppendorf thermomixer at 37 °C, 300 rpm. Finally, 5 μL of 3% trifluoroacetic acid (TFA) aqueous solution was added to recover the resulting peptides. The peptide mixture was desalted using C18 Ziptips (Millipore, Billerica, MA). The samples were eluted in 0.7-1.0 μL of R-cyano-4-hydroxycinnamic acid MALDI 1635



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Figure 2. 2D-DIGE of oxidized and total protein expression. (A) Overlaid images of AF-488-labeled oxidized proteins (blue) and NHS-Cy3-labeled total protein (green) from the same sample demonstrating a shift in pI. Separated images from the gel in (A) are also shown in (B) AF-488, (C) Cy3, and (D) Cy5-labeled internal control. These images demonstrate ‘matching’ between total protein and the internal control, while AF-488 produces a shift in pI (indicated by the spots in oval, and the arrows in panel A).

matrix dissolved in 0.1% TFA in a 4:1 ACN/water mixture, which is sufficient to create three MALDI spots per sample. The first two spots were used directly for MALDI-MS and data-dependent MS/MS analysis, and the remaining spot was used for massselected MALDI-MS/MS. Protein Identification by Mass Spectrometry

Proteins were identified using a 4800 MALDI TOF/TOF (Applied Biosystems (AB), Foster City, CA) mass spectrometer at the US EPA NHEERL Proteomics Research Core Facility. The online proteomics software “Aldente” (http://expasy.org/tools/ aldente) was used to identify proteins from background-subtracted MALDI-MS data. This step was followed by MALDIMS/MS sequencing, and the final protein identification was done using Protein Pilot 3.0 software (AB), searching against the mouse (Mus musculus) subdatabase of the SwissProt protein database (http://expasy.org/sprot/). Mass-selected MALDIMS/MS spectra acquisition was performed to increase protein sequence coverage. The MS peaks proposed by Aldente are used to acquire more MS/MS data from the remaining MALDI spots, indicating the scores for protein identification probability, which corresponds to a product of the individual probabilities assigned to the peptide MS/MS spectra. The reported proteins were identified based on at least two high-quality (99 or better)

peptide sequence identifications made from the MS/MS data by the Protein Pilot Software (Table 1 and Supplement 2, Supporting Information—“Protein Table”).

’ RESULTS Changes in the levels of total protein expression and protein oxidation in the hippocampi of young-adult (25-30 weeks) and old (76-97 weeks) mice transgenic for the APOE gene isoforms, APOE3 and APOE4, were examined according to the experimental design shown in Figure 1 (Supplement 1, Supporting Information—“Differential Protein Expression”). Each gel contained aliquots labeled for oxidized and total protein from a single sample, and a pooled IC. Oxidized proteins were detected by labeling with AF-488, total protein from the same sample with NHS-Cy3, and a pooled IC labeled with NHS-Cy5 (Figure 1). However, there was a pI shift induced by the AF-488 label relative to the same sample labeled for total protein with NHS-Cy3 (Figure 2A, arrows; and oval in Figure 2B-D). To save confusion the resulting images for oxidized and total protein differential expression were analyzed separately, using the same IC, as the oxidized and total protein spot numbers would not correlate to the same protein. Furthermore, even with the separated data, the DIA component of DeCyder 2D 7.0 creates a merged image 1636



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Figure 3. Spot maps of significant differential expression of (A) oxidized and (B) total protein. The oxidized and total protein spots with significantly different (t test or 2-way ANOVA) expression levels are shown. The master spot numbers for each analysis are indicated. Differentially oxidized and differentially expressed proteins were selected based on the data included in Supplement 1, Supporting Information.

Figure 4. Differential expression analysis of 2-way ANOVA data. Differential expression analysis of oxidized and total protein followed the same trends. Of the proteins whose oxidation and expression levels were significantly different between the two APOE genotypes, the majority increased in the APOE3 genotype (approximately 60%). For proteins whose oxidation levels changed with age, 90% increased in older mice (middle, top panel). In comparison, only 75% of proteins significantly different with age where higher in older mice. 1637



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Figure 5. Differential expression analysis. Differential expression analysis of (A) oxidized and (B) total protein followed the same trends. Of the proteins whose oxidation and expression levels were significantly different between the two APOE genotypes, the majority increased in the APOE3 genotype. For proteins whose expression levels changed with age, the majority increased in older mice. These same trends were also observed when comparing APOE genotypes within age groups and also when comparing age groups within each APOE genotype.

(spot map) from both images in a gel ensuring that all spots are represented in both images. Therefore, although the protein spot distribution from oxidized and IC samples do not correspond, the overall spot map can be used to match and normalize the oxidized protein samples. Even when spots are absent in an oxidation-labeled image or internal control-labeled image (due to a shift in pI) a value is still assigned, and a valid normalization and relative abundance can be calculated. This would be similar to spiking a gel with a mixture of proteins with known quantities, as suggested by Berth et al, 2007.18

Using 2-way ANOVA analysis, we found 35 differentially oxidized protein spots (P < 0.05) and 69 differentially expressed protein spots (Figure 3 and Supplement 1, Supporting Information). Of the 35 differentially oxidized proteins, 21 (60%) were significantly different between APOE genotype, while only 11 (31%) differed with age (Figure 4A). A significant interaction (P < 0.05) was seen in only 8 oxidized proteins. Similarly, of the 69 differentially expressed proteins 46 (67%) were significantly different between APOE genotype, while only 27 (39%) differed with age (Figure 4B). 1638



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Figure 6. Principal component analysis of oxidized proteins. In all plots APOE genotype effects are distributed along the x-axis and age effects along the y-axis. (A) Age and APOE genotype effects using 2-way ANOVA, and (B) age and APOE genotype effects using t test data. The overall effects of age and APOE genotype show two distinct clusters with t test data being more apparent (B). One is associated with increased age independent of APOE genotype, and the other is dependent upon APOE genotype. (C) With regard to within-genotype, the effects appear equivalent between APOE3 and APOE4 mice. (D) With regard to within-age, there is also a clear distribution between APOE genotype, with the majority of increased protein oxidation occurring in APOE3 mice.

Significant interactions (P < 0.05) were seen in only 13 proteins. Differential expression analysis of the 2-way ANOVA data revealed that, among the oxidized proteins that differed between APOE genotypes, 60% were higher in APOE3, while 90% of those that changed with age were higher in old mice (Figure 4A). In the total protein expression analysis, 67% of proteins differentially expressed between APOE genotypes were higher in the APOE3 mice (Figure 4B), and 74% of those that changed with age were higher in old mice. Similarly, when comparing the individual groups using Student’s t test19 we found, overall, 38 oxidized and 100 total protein spots with significantly different (P < 0.05) expression levels in the hippocampi from young and old, APOE3 and APOE4 transgenic mice (Figure 3, and Supplement 1, Supporting Information—“Differential Protein Expression”). Of the 38 differentially oxidized proteins, almost half (44.7%) were significantly different between the two APOE genotypes (Figure 5A, upper left panel), while only 15% differed between old and young-adult mice (Figure 5A, upper right panel). Similarly, of the 100 differentially expressed proteins, 48% were significantly different between the two APOE genotypes (Figure 5B, upper left panel), while only 14% differed between young and old mice, irrespective of genotype (Figure 5B, upper right panel). Differential expression analysis revealed that, among the oxidized proteins that differed between APOE genotypes, 86% were higher in APOE3, while 83% of those that changed with age

were higher in old mice (Figure 5A). This same trend was also observed when comparing APOE3-old and APOE4-old mice, and APOE3-young and APOE4-young samples. Similarly, in the total protein expression analysis, 80% of those proteins that showed significant differences between the two APOE genotypes were higher in the APOE3 mice (Figure 5B) or with increasing age. For oxidized proteins, PCA of the t test data revealed two distinct clusters: one in which oxidation increased with age, independent of APOE genotype, and a second in which oxidation was a function of APOE genotype (Figure 6B). This separation of age and APOE genotype effects is also apparent using the 2-way ANOVA data, although not as distinct (Figure 6A). For differential protein expression, PCA revealed a large overlap between proteins whose expression changed with age, irrespective of APOE genotype, and proteins whose expression changed as a function of APOE genotype (Figure 7). In addition, all proteins within the APOE4 genotype whose expression changed as a function of age, largely overlapped with proteins whose expression changed as a function of age, irrespective of genotype. In contrast, proteins whose expression changed as a function of age within the APOE3 genotype, only partially overlapped with proteins whose expression changed as a function of age within the APOE4 genotype. To identify differentially oxidized or expressed proteins, 25 μg of each AF-488-labeled sample (equivalent to 300 μg) and 20 μg Cy3-labeled IC were pooled and run on a “pick” gel which was 1639



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Figure 7. Principal component analysis of differential protein expression. Neither (A) 2-way ANOVA data, nor (B) t test data, showed significant clustering of age and APOE genotype effects. A similar overlap was found for proteins that changed between genotypes but within an age group (D). In contrast, (C) proteins whose expression changed as a function of age within the APOE3 genotype, only partially overlapped with proteins whose expression changed as a function of age within the APOE4 genotype.

then stained with Coomassie G250 (BioRad, Hercules, CA). Protein identification was performed using a combination of MALDI-MS and MS/MS, as described above. Of the spots displaying significant statistical parameters (2-way ANOVA or t test) on the analytical gels, 78 were positively matched in the pick gels, and were picked and submitted for identification by mass spectrometry. Fifty-six proteins (of the 78 picked spots) were identified with more than 99.99% confidence based on the amino acid sequences deduced from the MS and MS/MS peaks for a minimum of two peptides (Table 1 and 2, Supplement 2, Supporting Information—“Protein Table”). Notably, some of the differentially oxidized proteins identified (e.g., R-tubulin, heat shock cognate 71 kDa protein (Hsc71), and γ- and Renolase) were also differentially expressed. Proteins identified as being differentially oxidized, but not differentially expressed, were R-internexin, mitochondrial stress-70 protein (mt-Hsp70; mortalin), and actin. The identities of the differentially oxidized and differentially expressed proteins were entered into the Extended Data Analysis (EDA) component of GE Healthcare’s DeCyder 7.0 for Gene Ontology and UniProt Knowledgebase pathway analysis. This functional analysis revealed that the differentially oxidized proteins are involved in the biological processes shown in Figure 8 (Supplement 3, Supporting Information—“GO and UniProt Database Analysis”). Of these differentially oxidized proteins, Hsc71 and mt-Hsp70 are involved in cellular stress responses; γ- and R-enolase are involved in glycolysis; while R-tubulin, actin, R-internexin, and R- and γ-enolase are all involved in cytoskeletal organization. Interestingly, in addition to these same proteins and functions, the differentially expressed proteins also

included peroxiredoxin-2 (Prdx-2) and mitochondrial thioredoxin-dependent peroxide reductase (peroxiredoxin-3 (Prdx-3)), both of which are involved in the regulation of oxidative processes. Moreover, Prdx-2 expression was higher in APOE3-mice, while Prdx-3 expression was higher in APOE4-mice (Figure 9). Additionally, peroxiredoxin-6 was also differentially expressed with age but independently of APOE genotype, although with a lower significance (P < 0.039 t test, P < 0.07 2-way ANOVA).

’ DISCUSSION Our data demonstrate the effectiveness with which differences in oxidized and total protein expression can be determined simultaneously using specific fluorescent labels. Even though the use of an Alexa Fluor-aminooxyacetamide label for carbonylated (oxidized) proteins resulted in a pI shift compared to NHS-Cy dye labeling, accurate differences were determined by the use of a common internal control. Of the differentially carbonylated proteins that were identified, many are associated with AD and aging, including Hsc71,20,21 mortalin,16 γ-enolase,22 R-enolase,22 tubulin,23 and actin.24 Protein carbonylation is generally believed to inhibit protein function;25 therefore, the increase in expression levels also found with some of these proteins may be a compensatory response to this decrease in function. In addition, it has been suggested that protein carbonylation leads to protein unfolding, degradation, or aggregation, which is associated with cellular inclusions found in many forms of age-induced neurodegeneration (reviewed in ref 26). These processes can be regulated by molecular chaperones such as heat shock proteins.26,27 In this study, we found that 1640



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Table 2. Identities of Differentially Oxidized and Expressed Proteins (2-Way ANOVA) 2-way ANOVA master no.

APOE-GENOTYPE

AGE

interaction

names

accessions

oxidized 440

0.08

0.24

0.24


445

0.031

0.095

0.081

Heat .shock cognate 71 kDa protein

P63017

Stress-70 protein, mitochondrial

P38647

447 565

0.1 -

0.22 -

0.25 -

P63017

Tubulin alpha-1 A chain

P68369

Tubulin alpha-4A chain

P68368

Gamma-enolase

P17183

788

0.077

0.48

0.5

Gamma-enolase

P17183

790 811

0.18 0.066

0.064 0.85

0.9 0.61

Gamma-enolase Alpha-enolase

P17183 P17182

910

0.0038

0.046

0.16


P63260

917

0.051

0.57

0.69


P63260

1990

0.84

0.061

0.55

Alpha-internexin

P46660

268

0.075

0.96

0.43

Ubiquilin-2

Q9QZM0


P63017

0.19

V-type proton ATPase catalytic Subunit A Stress-70 protein, mitochondrial

P5051S P38647

779

total 333

-

034

-

336

0.77

339

0.0086

0.66

0.56

Dihydropyriminidinase-related protein 2

O08553

385

0.41

0.41

0.9

Dihydropyriminidinase-related protein 2

O08553

401

0.0043

0.81

0.59

Heterogeneous nuclear ribonucleoprotein K

P61979

409

0.09

0.073

0.33

Heterogeneous nuclear ribonucleoprotein K

P61979

442

0.38

0.066

0.17


P68369


P68368

452

0.041

0.0058

0.068

Tubulin alpha-1A chain Tubulin alpha-4A chain

P68369 P68368

453

0.0017

0.0018

0.13


P68369

Tubulin alpha-4 A chain

P68368

544

0.48

0.39

0.24

Pyruvate dehydrogenase protein X component, mitochondrial

Q8BKZ9

572

0.79

0.39

0.63

ATP synthase subunit beta, mitochoridrial

P56480

592

0.05

0.34

0.77

Dynactin subunit 2

Q99KJS

613

0.13

0.023

0.93

Gamma-enolase

P17183

619 621

0.0034 0.0014

0.97 0.071

0.87 0.065

Gamma -enolase Gamma-enolase

P17183 P17183

626

0.26

0.97

0.43

Gamma-enolase

P17183

627

0.0029

0.017

0.16

Gamma-enolase

P17183

631

0.09

0.028

0.51

Glial fibrillary acidic protein

P03995

639

0.41

0.6

0.039

Alpha-enolase

P17182

668

0.021

0.41

0.8

Protein phosphatase 1 regulatory subunit 7

Q3UM45

914

0.67

0.03

0.17

Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-1

P62874

918 954

0.012 0.061

0.18 0.95

0.59 0.47

Phosphoglycolate phosphatase EF-hand domain-containing” protein D2

Q8CHP8 Q9D8Y0

978

0.034

0.043

0.57

Glyoxalase domain-containing protein 4

Q9CPV4

993

0.04

0.16

0.98

Prohibitin

P67778

996

0.038

0.27

0.23


P58771

1021 1022

0.027 0.14

0.42 0.65

0.84 0.87

1023 1028

0.14

0.42

0.64 -

1071

0.76

0.07

0.34


P21107

14-3-3 protein zeta/delta Calretinin

P63101 Q08331

Calretinin Rho GDP-dissociation inhibitor 1

Q08331 Q99PT1

Peroxiredoxin-6

008709

1641



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Table 2. Continued 2-way ANOVA master no.

APOE-GENOTYPE

AGE

interaction

1096 1106

0.0089 0.02

0.21 0.091

0.12 0.078

Thioredoxin-dependent peroxide reductase. mitochondrial Heme-binding protein 1

1114

0.0079

0.028

0.32

Peroxiredoxin-2

061171

1115

0.9

0.051

0.59

UMP-CMP kinase

Q9DBP5

1123

0.0037

0.033

0.3

Phosphatidylethanolamine-binding piotein 1

P7029S

1129

0.014

0.86

0.76

Peroxiredoxin-2

Q61171

1172

0.05

0.53

0.48

Alpha-synuclein

055042

names

Figure 8. Functional classification of (A) differentially oxidized and (B) differentially expressed proteins. Each classification is expressed as a percentage of the total number of differentially oxidized or differentially expressed proteins. The chart was created with Decyder’s EDA module using Supplement 3, Supporting Information—“GO and UniProt database analysis”.

accessions P20108 Q9R257

mortalin and Hsc71 are differentially carbonylated and differentially expressed between APOE3 and APOE4 mice. Previously, we demonstrated that mortalin isoforms are differentially expressed in the hippocampi of AD patients, as well as in the hApoE-targeted-replacement mice used in this study.16 In agreement with previous reports,21,27 our results suggest that increasing mortalin and Hsc71 dysfunction contributes to the progression of aging-related differences associated with the APOE4 genotype. Overall, differentially carbonylated proteins separated into two distinct groups (Figure 6): those in which carbonylation increased with age independent of APOE genotype, and those in which carbonylation was a function of APOE genotype. This suggests that age and APOE genotype influence protein carbonylation in distinct ways, with little interaction (8 proteins with 2-way ANOVA of P < 0.05). In addition, genotype-dependent carbonylation was generally higher in the APOE3 mice (60%) as were the levels of differential protein expression (67%), suggesting that in general the increased carbonylation with the APOE3 genotype may be attributed to a corresponding increase in expression level. This may signify little relative change in protein carbonylation between the APOE3 and APOE4 genotypes. Previous studies demonstrated that antioxidant capacity associated with APOE genotype is in the order of E2 > E3 > E4;28-30 however, APOE genotype effects on protein carbonylation have rarely been measured. In fact, there are only two previous publications with which to compare our results. One in which basal total-protein carbonylation levels were not significantly different between the APOE3 and APOE4 genotypes,31 and a second in which protein carbonylation was decreased in the cerebral spinal fluid of APOE4 carriers,32 both in agreement with the interpretation of our results. Furthermore, given the increased risk of AD associated with the APOE4 genotype and its reduced antioxidant capacity, one may expect higher carbonylation in this group. However, neither the APOE4 nor APOE3 mice used in our study develop AD, making it impossible to test this hypothesis, which assumes that the increased risk of AD associated with the APOE4 genotype is mediated by global protein carbonylation or a lack of response to protein carbonylation. In fact, the definitive association of global protein carbonylation to the onset of AD has not been established. The onset of disease may still be associated with one or more of the proteins with increased carbonylation associated with the APOE4 genotype (40%), or with those that showed changes in protein expression and not oxidation. Intriguingly, the difference in carbonylation between aging and APOE genotype in our study correlates with the differential expression of peroxiredoxin family members. Prdx-2 expression 1642



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In conclusion, we demonstrated that by using a fluorescent label against carbonylated proteins in conjunction with an NHSfluorescent label for total protein, it is possible to determine differences in protein carbonylation and total protein expression levels simultaneously. This methodology eliminates the need for gel-to-gel comparisons. Using this method, we studied the effects of APOE genotype and aging on protein carbonylation and total protein expression in the hippocampi of mice. Our results suggest that age and APOE genotype independently influence protein carbonylation. Furthermore, our data indicate that this effect may be mediated by the differential expression of peroxiredoxins, as indicated by the age- and APOE genotype-related differential expression of various peroxiredoxin proteins.

’ ASSOCIATED CONTENT

bS

Supporting Information Supplement 1, differential protein expression. Supplement 2, protein table. Supplement 3, GO and UniProt database analysis. This material is available free of charge via the Internet at http://pubs.acs.org.

’ AUTHOR INFORMATION Corresponding Author

*Oscar Alzate, Ph.D., 438A Taylor Hall, CB #7090, 104 Mason Farm Road, Chapel Hill, NC 27599. Telephone: þ1 (919) 962-3698. E-mail: [email protected].

Figure 9. Differential expression analysis of 2-way ANOVA data for Prdx-2 and Prdx-3. Two protein spots were identified for Prdx-2 (top), 1114 and 1129. Both were significantly higher in hippocampi of APOE3 genotype mice. Only 1114 was significantly higher in older mice, while 1129 showed no change. In contrast, Prdx-3 expression (Bottom) was higher in APOE4 genotype mice, and did not change significantly with age.

increased in APOE3 mice, Prdx-3 expression increased in APOE4 mice, and Prdx-6 expression increased with age, independent of APOE genotype. Prdx-2 is found in the cytosol of neurons and has been demonstrated to be up-regulated in AD patient brains where it is has been proposed to have a protective effect against oxidation and β-amyloid toxicity.33 However, APOE genotypes were not established in this study, and as stated previously neither the APOE4 nor APOE3 mice used in our study develop AD, making a comparison difficult. In addition, Prdx-2 knockout mice have shown an increase in mitochondrial ROS generation, a decline in long-term potentiation, reduced activation of synaptic plasticity-related signaling pathways, and a failure to maintain mitochondrial functional integrity,34 all of which are conditions that simulate those associated with AD. Therefore, the lower expression of Prdx-2 with the APOE4 genotype suggests an increase in these conditions, and may in fact contribute to an increased susceptibility to AD. Additionally, Prdx-6 is found primarily in the cytosol of glial cells, and is known to be carbonylated in AD and mild cognitive impairment.35 Prdx-3, in contrast, is restricted to mitochondria, and in the brain is found primarily in neurons.36-38 Prdx-3 is unique in that it scavenges both H2O2 and peroxynitrite. Overall, these differences in peroxiredoxin isoform expression as a function of age, genotype, and subcellular localization may result in the ageand APOE genotype-related differential carbonylation we observed.

’ ACKNOWLEDGMENT This work was supported by start-up funds from the Program in Molecular Biology and Biotechnology of UNC (O. A.). We thank Dr. Patrick Sullivan and Mr. Brian Mace (Duke University Medical Center) for donating APOE-TR mouse brain tissues. The research described in this article was reviewed by the National Health and Environmental Effects Research Laboratory, United States Environmental Protection Agency, and approved for publication. Approval does not signify that the contents necessarily reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. ’ REFERENCES (1) Danielson, S. R.; Andersen, J. K. Oxidative and nitrative protein modifications in Parkinson’s disease. Free Radic. Biol. Med. 2008, 44 (10), 1787–94. (2) Telci, A.; Cakatay, U.; Salman, S.; Satman, I.; Sivas, A. Oxidative protein damage in early stage Type 1 diabetic patients. Diabetes Res. Clin. Pract. 2000, 50 (3), 213–23. (3) Brennan, M. L.; Hazen, S. L. Amino acid and protein oxidation in cardiovascular disease. Amino Acids 2003, 25 (3-4), 365–74. (4) Butterfield, D. A.; Drake, J.; Pocernich, C.; Castegna, A. Evidence of oxidative damage in Alzheimer’s disease brain: central role for amyloid beta-peptide. Trends Mol. Med. 2001, 7 (12), 548–54. (5) Markesbery, W. R. Oxidative stress hypothesis in Alzheimer’s disease. Free Radic. Biol. Med. 1997, 23 (1), 134–47. (6) Sultana, R.; Perluigi, M.; Butterfield, D. A. Protein oxidation and lipid peroxidation in brain of subjects with Alzheimer’s disease: insights into mechanism of neurodegeneration from redox proteomics. Antioxid. Redox Signal. 2006, 8 (11-12), 2021–37. (7) Sultana, R.; Perluigi, M.; Butterfield, D. A. Oxidatively modified proteins in Alzheimer’s disease (AD), mild cognitive impairment and 1643


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Simultaneous Detection of Changes in Protein Expression and

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