Quantification of the Brain Proteome in Alzheimer's Disease Using

Article pubs.acs.org/jpr

Quantification of the Brain Proteome in Alzheimer’s Disease Using Multiplexed Mass Spectrometry Sravani Musunuri,† Magnus Wetterhall,† Martin Ingelsson,‡ Lars Lannfelt,‡ Konstantin Artemenko,† Jonas Bergquist,† Kim Kultima,§ and Ganna Shevchenko*,† †

Analytical Chemistry, Department of Chemistry-BMC and ‡Department Public Health/Geriatrics, Uppsala University, Uppsala, Sweden § Department of Medical Sciences, Cancer Pharmacology and Computational Medicine, Uppsala University Academic Hospital, Uppsala, Sweden S Supporting Information *

ABSTRACT: We have compared the brain proteome in the temporal neocortex between Alzheimer’s disease (AD) patients and non-AD individuals by using shotgun mass spectrometry based on a stable isotope dimethyl labeling. A total of 827 unique proteins were identified and quantitated. Of these, 227 proteins were found in at least 9 out of 10 AD/ control pairs and were further subjected to statistical analysis. A total of 69 proteins showed different levels (p-value < 0.05) in AD versus control brain samples. Of these proteins, 37 were increased and 32 were decreased as compared to the non-AD subjects. Twenty-three proteins comprise novel proteins that have not previously been reported as related to AD, e.g., neuronal-specific septin-3, septin-2, septin-5, dihydropteridine reductase, and clathrin heavy chain 1. The proteins with altered levels in the AD brain represent a wide variety of pathways suggested to be involved in the disease pathogenesis, including energy metabolism, glycolysis, oxidative stress, apoptosis, signal transduction, and synaptic functioning. Apart from leading to new insights into the molecular mechanisms in AD, the findings provide us with possible novel candidates for future diagnostic and prognostic disease markers. KEYWORDS: Alzheimer’s disease (AD), dimethyl labeling (DML), quantitative proteomics, mass spectrometry (MS), brain tissue

1. INTRODUCTION Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the most common form of dementia.1 It is characterized by massive cell death throughout the cortex leading to gradually impaired memory and various degrees of dyspraxia and speech difficulties. This devastating disease causes great suffering for patients as well as relatives and places an immense economic burden to the health care system. AD can be confirmed post mortem by the presence of extracellular plaques of the amyloid-β (Aβ) peptide and neurofibrillary tangles of the microtubule-associated protein tau in the cortex.2 Several neuropathological processes have been proposed to associate with the onset and progression of AD. Primarily, the “amyloid cascade hypothesis” posits that accumulation of Aβ, cleaved from the amyloid precursor protein (APP) by β-secretase and γ-secretase, is a central pathological event that can induce the formation of plaques and cell death.3 Additionally, impaired mitochondrial functions, oxidative stress, and inflammatory processes have also been suggested to play a role in AD pathogenesis.4,5 The protein brain abnormalities can be mirrored in cerebrospinal fluid (CSF).6−8 Increased levels of total tau and phosphorylated tau (phospho-tau) together with decreased © 2014 American Chemical Society

levels of the 42 amino acid long form of amyloid-β (Aβ42) have in numerous studies been found to discriminate AD from nondemented aged individuals.6,7 Proteomic approaches have also been applied to study AD-related changes in protein levels of plasma and blood samples9,10 as well as post mortem brain tissues.11 Studies using two-dimensional gel electrophoresis (2DE), comparing blood/plasma samples from AD patients and healthy subjects, distinguished quantitative changes in the pattern of the most abundant proteins present in lymphocytes, red blood cells, and platelets.9 In another study, reduced levels of cytoskeletal and actin proteins were found in platelets and lymphocytes of the AD patient samples compared to controls.12 The 2-DE studies9,13 revealed altered levels of immunoglobulin isoforms, albumin, ceruloplasmin precursor, complement factor H precursor, α-2-macroglobulin, and Apo A-1 in AD as compared to control plasma samples. However, the domination of high abundant proteins in blood and plasma samples usually prevents the successful identification of low abundant biomarker candidates.9 Received: December 6, 2013 Published: March 10, 2014 2056

dx.doi.org/10.1021/pr401202d | J. Proteome Res. 2014, 13, 2056−2068

Journal of Proteome Research

Article

Figure 1. Schematic overview of the experimental setup. Sections of brain tissue were homogenized, and the brain proteins were extracted using a solubilizing solution containing the nonionic detergent n-octyl-β-D-glucopyranoside. Extracted proteins were delipidated and tryptically digested on 3 kDa spin filters. Dimethyl isotope labels were used to globally label the tryptic peptides for relative quantification. Individually labeled peptides from samples and controls were combined and analyzed by LC−MS/MS using a 7 T hybrid LTQ FT mass spectrometer. The proteins were quantified using the MSQuant software.

Juhazs et al.14 summarized a list of 36 “overlapping” brain proteome changes in AD human brain samples and in animal models of AD based on the protein lists of 2-DE proteomics studies of Sowell et al.15 and Korolainen et al.16 However, despite the good resolution, dynamic range, and high throughput protein separation, 2-D gels do not reflect a true representation of very basic, very acidic, very large, and very small proteins.17,18 In fact, many CNS proteins are hydrophobic low abundant membrane proteins, which occupy a unique niche in the brain proteome research due to their important physiological roles.19 Over the past years, alternative mass spectrometry based proteomic approaches have been widely used for identification and quantification of proteins that fall outside the range of 2DE.20 These provide new opportunities to elucidate diseaseassociated changes and to identify new diagnostic markers and therapeutic targets. MS-based proteomics in combination with multiplexed quantitation facilitates accurate identification and relative quantification of complex protein samples. Dimethyl labeling (DML),21 isobaric tags for relative and absolute quantitation (iTRAQ),22 and stable isotope labeling of amino acids in cell culture (SILAC)23 are examples of stable isotope tagging to generate the mass signatures that assist in

distinguishing sample origin and accurate quantification. Recent studies in our group show the robustness and reliability of the DML method to identify changes in protein levels.24,25 This method involves the introduction of cost-effective isotopic dimethyl labels21 into proteome digests followed by nanoLC− MS/MS analysis and can be easily used for large-scale proteomic experiments. The purpose of this study was to quantitatively compare the levels of different proteins in post mortem brain tissue from AD patients and control subjects in order to gain an improved understanding of the changes in the proteomes in the AD brain. We performed a quantitative neuroproteomic analysis of temporal neocortex samples of AD and non-neurological control brains using a stable isotope DML MS approach.

2. EXPERIMENTAL SECTION The workflow for sample processing and analyses is depicted in Figure 1. Temporal neocortex samples from 10 patients with AD and five non-AD controls were homogenized and the brain proteins were extracted using solubilizing solution containing the nonionic detergent n-octyl-β-D-glucopyranoside (β-OG). A stable isotope dimethyl labeling and a shotgun nanoLC−MS/ 2057



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2.3. Protein Extraction

MS approach was used for the detection and quantification of the proteins.

The temporal neocortex samples were homogenized in liquid nitrogen, and the brain powder was stored at −80 °C prior to analyses. Aliquots of 30 mg of brain powder were homogenized for 60 s in a blender (POLYTRON PT 1200, Kinematica) with 1 mL of lysis buffer (10 mM Tris-HCl pH 7.4, 0.15 M NaCl, 1 mM EDTA, and PBS containing 1% β-octyl glucopyranoside). Protease inhibitor cocktail (10 μL) was added during the sample preparation to prevent protein degradation. After homogenization, the samples were incubated for 90 min at 4 °C during mild agitation. The tissue lysates were clarified by centrifugation for 30 min (10000 × g at 4 °C) using a Sigma 2K15 ultracentrifuge (Sigma Laborzentrifugen GmbH, Osterode, Germany). The supernatant containing extracted proteins was collected and further processed.

2.1. Brain Specimens

Frozen human brain tissues from the temporal neocortex were collected post mortem from 10 AD patients and 5 control subjects that had not been diagnosed with any neurodegenerative disorder. The AD cases were neuropathologically diagnosed as CERAD C, Braak stages IV−VI.26 All brain samples were obtained from the Uppsala Berzelii Technology Centre for Neurodiagnostics biobank at the Uppsala University hospital. On average, the samples were collected 27 h (minimum 5 h/maximum 60 h) post mortem. The samples were put in prefrozen and prelabeled 1.5 mL Eppendorf tubes and stored in −80 °C pending analyses. The collection of brain tissues and the conducted research had been approved by the Regional Ethical Review Board in Uppsala, Sweden. A summary of the main clinical and neuropathological aspects is shown in Table 1.

2.4. Delipidation and Protein Precipitation

An adapted delipidation protocol according to Mastro et al. was used.27,28 Aliquots (200 μL) of the protein extracts were mixed with 1.4 mL of ice-cold trin-butylphosphate/acetone/methanol mixture (1:12:1) and incubated at 4 °C for 90 min. The precipitate was pelleted by centrifugation for 15 min (2800 × g at 4 °C), washed sequentially with 1 mL of acetone and 1 mL of methanol, and finally air-dried.

Table 1. Patient and Control Clinical and Neuropathological Data patient

case

gender

age, years

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

AD AD AD AD AD AD AD AD AD AD control control control control control

female female female male female female female male female male male female male male male

61 84 92 64 85 76 77 90 63 71 88 88 63 90 91

duration of disease (years)

age of onset (years)

postmortem interval (h)

3 3 12

58 81 80

2

83

6 6 10 8

71 84 53 63

48 20 5 12 21 30 7 11 48 60 39 22 30 30 27

2.5. Protein Quantification

The total protein content of delipidated proteins was determined using the DC Protein Assay Kit (BioRad Laboratories, Hercules, CA, USA), which is based on the modified Lowry method with bovine serum albumin as standard.29 The protein pellets were redissolved in 200 μL of 6% SDS. The DC assay was carried out according to the manufacturer’s instructions using 96-well microtiter plate reader model 680 (BioRad Laboratories). 2.6. On-Filter Tryptic Digestion of Proteins

Portions (200 μL) of the extracts (220−300 μg of proteins) were delipidated as described in Section 2.4. Delipidated protein pellets were redissolved in 200 μL of digestion buffer (8 M urea, β-octyl glucopyranoside in 50% ACN). A volume of 35 μL protein solution was used for digestion. An on-filter digestion protocol was used for tryptic digestion of the samples using 3 kDa filters (Pall Life Sciences, Ann Arbor, MI, USA). Centrifugation was carried out at a centrifugal force of 14,000 × g throughout the protocol. A volume of 10 μL of 45 mM aqueous DTT was added to all samples, and the mixtures were incubated at 50 °C for 15 min to reduce the disulfide bridges. The samples were cooled to room temperature, and 10 μL of 100 mM aqueous IAA was added before the mixtures were incubated for an additional 15 min at room temperature in darkness to carabamidomethylate the cysteines. The samples were transferred to spin filters that had been prewashed with 250 μL of 50% ACN for 15 min and then 500 μL of water for 20 min. Next, the samples were centrifuged for 10 min to remove the added salts, detergents, and other interfering substances. An additional volume of 100 μL of 50 mM NH4HCO3 in 2% ACN was added, and the filters were spun for 10 min followed by 100 μL of 50 mM NH4HCO3 in 50% ACN and 150 μL of 50 mM NH4HCO3 and centrifugation for another 10 min. Finally, a volume of 100 μL of 50 mM NH4HCO3 (pH 7.8) and 16 μL of trypsin (0.1 μg/μL) were added to the samples. The tryptic digestion was performed at 37 °C overnight in darkness. The digests were spun through the filter for 20 min to collect the tryptic peptides. An

2.2. Chemicals and Reagents

Acetonitrile (ACN), methanol (MeOH), acetic acid (HAc), formic acid (FA), sodium chloride (NaCl), and ammonium bicarbonate (NH4HCO3) were obtained from Merck (Darmstadt, Germany). Acetone, ethylenediaminetetraacetic acid tetrasodium salt dihydrate (EDTA), protease inhibitor cocktail, phosphate buffered saline (PBS), trifluoroacetic acid (TFA), noctyl-β-D-glucopyranoside, triethyl ammonium bicarbonate (TEAB), and formaldehyde CH 2O (37% (v/v)) were purchased from Sigma Aldrich (St. Louis, MO, USA). For tryptic digestion, iodoacetamide (IAA), urea, and dithiothreitol (DTT) obtained from Sigma Aldrich and trypsin (sequencing grade from bovine pancreas 1418475; Roche Diagnostic, Basel, Switzerland) were used. Deuterated formaldehyde CD2O (20% (v/v)) was purchased from ISOTEC (Miamisburg, Ohio, USA). Sodium cyanoborohydride (NaBH3CN) was obtained from Fluka (Buchs, Switzerland). Sucrose was purchased from Fisher Scientific Company (Göteborg, Sweden). Ultrapure water was prepared by Milli-Q water purification system (Millipore, Bedford, MA, USA). 2058



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additional volume of 100 μL of 50% ACN, 1% HAc was added, and the filters were spun for 10 min and pooled with the first tryptic peptide filtrate. The collected filtrates were vacuum centrifuged to dryness using a Speedvac system ISS110 (Thermo Scientific, Waltham, MA, USA).

2.9. Data Analysis

Acquired data (.RAW-files) were converted to the .mgf format using an in-house written program (C++) and subjected to protein identification using MASCOT search engine (version 2.2.2, Matrix Science, U.K.) against the SwissProt database version 51.6 519348 sequences, 183273162 residues). The search parameters were set to Taxonomy: Homo sapiens (20287 sequences), Enzyme: Trypsin. Fixed modification was Carbamidomethyl (C), and variable modifications were Oxidation (M); Deamidated (NQ); Dimethyl (K); Dimethyl (N-term); Dimethyl:2H(4) (K) and Dimethyl:2H(4) (Nterm), Peptide tolerance: 10 ppm, MS/MS tolerance: 0.7 Da and maximum 2 missed cleavage sites. Only proteins identified with at least one peptide passing the require bold red criteria with a Mascot score of ≥30 (p-value < 0.05) selected and quantified. For all runs these requirements resulted in a false discovery rate (FDR) less than 5% for peptide identification. Quantification was done using the open source sofware MSQuant (version 2.05b5) (http://msquant. sourceforge.net). The MSQuant was customized for duplex DML. Peptide ratios were obtained by calculating the extracted ion chromatograms of the light and medium forms of the peptide using the monoisotopic peaks only, and protein ratios were calculated from the average of all quantified peptides. The protein was selected with peptide MSQuant ≥30. After saving the MASCOT search results as MSQuant-compatible html format, the search results and corresponding raw data were associated in MSQuant. The final quantification result was exported as an Excel file and subjected to further calculation. All of the quantified ratios obtained from MSQuant were normalized by dividing the ratios with the median of the ratios. Since each labeled mixture was injected twice, the normalized ratios for technical replicates were used to calculate the average ratio for the same protein found in the replicate runs. If a protein was found in only one replicate, then the single normalized ratio was sustained. A list of average protein ratios from each pair AD/control was shortened by excluding all proteins whose ratios were reported in less than 9 out of 10 AD/control pairs. Afterward, the normalized average ratios from independent runs were transformed to the log scale. In this experimental setup, we cannot assume all log2 ratios to be independently sampled, and the underlying distribution of resulting ratios is unknown. As such, we performed a permutation test where the exact p-values were calculated by randomly permuting class labels within each pair, enumerating all possible permutations. The p-values were calculated as pe = b/n, where b is the number of tpermuted greater or equal to tobserved and n is the number of distinct values of the test statistic. As test statistics we calculated, t-values testing the null hypothesis H0: μ=0 with the alternative of H1: μ≠0. A pe of < 0.05 was considered statistically significant. The differentially expressed proteins were annotated using terms from UniProt knowledge base and Gene Ontology (GO) database.

2.7. Stable-Isotope Dimethyl Labeling

Dimethyl labeling was performed according to Boersema et al.21 Briefly, the tryptic peptide mixtures were reconstituted in 100 μL of 100 mM TEAB. According to Supplementary Table 1, 50 μL of each sample containing (∼10 μg) proteins from control and AD samples were mixed with 4 μL of regular formaldehyde CH2O (4%, v/v) and deuterated formaldehyde CD2O (4%, v/v), marked as light and medium, respectively. After a brief vortexing, 4 μL of freshly prepared 0.6 M NaBH3CN solution was added to each light and medium labeled sample. The vials were incubated for 60 min at room temperature while mixing. The reaction was terminated by adding 16 μL of ammonia (1%, v/v), after which 8 μL of formic acid (5%, v/v) was added to consume the excess labeling reagents. Finally, the samples labeled with light and medium isotopes were mixed together. In total, 10 samples were constructed, each containing one AD and one control sample. Since only five controls were available, each control was used twice for two different AD samples. The mixed samples were desalted on Isolute C18 solid phase extraction (SPE) columns (1 mL, 50 mg capacity, Biotage, Uppsala, Sweden) using the following schedule: The column was first wetted in 500 μL of 100% ACN and equilibrated with 5 × 500 μL 1% HAc. The tryptic peptides were adsorbed to the media using five repeated cycles of loading. The column was washed using 5 × 1 mL of 1% HAc, and finally the peptides were eluted in 250 μL of 50% ACN, 1% HAc. After desalting, the eluate was vacuum centrifuged to dryness and redissolved in 0.1% trifluoroacetic acid to a concentration of 0.4 μg/μL (assuming full recovery from SPE column) prior to nano-LC−MS/MS. 2.8. NanoLC−MS/MS for Protein Identification

The nanoLC−MS/MS experiments were performed using a 7 T hybrid LTQ FT mass spectrometer (ThermoFisher Scientific, Bremen, Germany) fitted with a nanoelectrospray ionization (ESI) ion source. Online nanoLC separations were performed using an Agilent 1100 nanoflow system (Agilent Technologies, Waldbronn, Germany). Each sample was analyzed by RP-nanoLC−MS/MS in duplicates (technical replicates). The peptide separations were performed on inhouse packed 15-cm fused silica emitters (75 μm i.d., 375 μm o.d.). The emitters were packed with a methanol slurry of reversed-phase, fully end-capped Reprosil-Pur C18-AQ 3 μm resin (Dr. Maisch GmbH, Ammerbuch-Entringen, Germany) using a PC77 pressure injection cell (Next Advance, Averill Park, NY, USA). The injection volumes were 5 μL and corresponded to 2 μg of tryptic peptides. The separations were performed at a flow of 200 nL/min with mobile phases A (water with 0.5% acetic acid) and B (89.5% acetonitrile, 10% water, and 0.5% acetic acid). A 100-min gradient from 2% B to 50% B followed by a washing step with 98% B for 5 min was used. Mass spectrometric analyses were performed using unattended data-dependent acquisition mode, in which the mass spectrometer automatically switches between acquiring a high resolution survey mass spectrum in the FTMS (resolving power 50000 fwhm) and consecutive low-resolution, collisioninduced dissociation fragmentation of up to five of the most abundant ions in the ion trap.

3. RESULTS AND DISCUSSION 3.1. Quantitative Analysis of AD Brain Protein Profile Using DML Method

In order to quantitatively compare the brain proteome in AD and nondiseased post mortem brains, we applied a shotgun based MS proteomic strategy using stable isotope dimethyl labeling quantification. Samples from temporal neocortex were 2059



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Figure 2. Volcano plot displaying the difference in the protein levels between AD and control brains. Log2 protein ratios are plotted against negative log10 p-values. Increased protein levels are represented on the positive x-axis, and decreased levels are represented on the negative x-axis.

pathology and, thus, represents a novel finding. ENOA, FRIL, and GFAP are involved in energy metabolism, oxidative stress, and inflammation, respectively.15,32,35 Among all 69 identified significantly regulated proteins (pvalue < 0.05), nine (13%) were identified by only one peptide, while 60 proteins (87%) were identified by two or more peptides. From the 60 proteins identified by more than one peptide, 15 proteins (25%) were identified by two peptides, while 23 (38%) were identified by three or four peptides. Yet another 22 (37%) proteins were identified by five or more peptides.

chosen for analysis, since this region is early and robustly affected in AD.30 Each labeled mixture was injected twice, and an average ratio for each protein was calculated based on the MSQuant analysis. If the protein was found only in one of the replicates, the same ratio was used for further statistical evaluation. Proteins displaying altered levels were then further classified according to their functional roles. Despite a similar total protein concentration between the AD and healthy control, we found a considerable difference in the protein levels between the AD and control groups (Figure 2). A total number of 827 unique proteins were identified (Supplementary Table 2). Among these, 227 proteins found in at least 9 out of 10 patient pairs were further subjected to statistical analysis (Supplementary Table 3). Of these, 69 proteins were found to be significantly (p < 0.05) increased (n = 37) or decreased (n = 32) in the AD brains. The list of significantly differentially regulated proteins together with their log2 changes, corresponding p-values, and the number of peptides used for quantitation is found in Table 2. A literature survey revealed that out of the 69 proteins, 46 of them had previously been reported in proteomic and immunohistochemical studies, either in AD patient samples or in transgenic animal models of Aβ pathology. The rest of the significantly regulated proteins (23) have not previously been identified as connected with AD. Of all the identified proteins, the levels of glial fibrillary acidic protein (GFAP), α-enolase (ENOA), ferritin light chain (FRIL) with p-value < 0.01 and neuronalspecific septin-3 (SEPT3) showed a 2-fold increase. In addition, there was a 2-fold decrease of tubulin β-3 chain (TBB3) (p < 0.01), which is involved in axon guidance and maintenance.31 The possible role of GFAP, ENOA, and TBB3 proteins in AD pathogenesis has been described earlier,32−34 whereas SEPT3 (p-value = 0.02) has not previously been associated with AD

3.2. Protein Changes Related to AD Pathology

The significantly increased and decreased protein levels were grouped according to their known functional relationships in connection with reported biological processes, e.g., energy and cholesterol metabolism, glycolysis, apoptosis, oxidative stress, stress response, inflammatory response, altered synaptic function, etc. The significantly regulated proteins were classified according to their known or predicted biological function as given by Uniprot and are shown in Figure 3. There are notable differences of predicted biological functions of the altered proteins. In general, the groups of proteins that are increased in AD compared to control brains contain a proportionally large number of proteins involved in metabolic processes (40%) in comparison to proteins that are decreased (10%). Some features are unique to the increased protein level in the AD (Figure 3A), including a high proportion of antioxidant proteins (14%) and inflammatory response proteins (6%). Among the biological functions of the proteins that were found to be decreased in AD (Figure 3B), the majority relate to either signal transduction (16%) or altered synaptic function (16%). 2060



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Table 2. List of Significantly Regulated Proteins in AD versus Control Brain Samples Found Using Stable Isotope DML MS Approach no.

protein name

entrya

no. of peptides

log2 of av ratio

p-value

Sdc

localization

Altered Energy Metabolism PRRT2_HUMAN 2 ↓−0.43 ODO2_HUMAN 1 ↓−0.35 QCR1_HUMAN 4 ↓−0.32

0.025 0.029 0.035

0.47 0.41 0.36

membrane mitochondrion membrane

synapse enzyme activity transport enzyme activity, metabolic process metabolic process metabolic process metabolic process, enzyme activity metabolic process

biological process

4

Proline-rich transmembrane protein 2b α-Ketoglutarate dehydrogenase complex Cytochrome b-c1 complex subunit 1, mitochondrial Malate dehydrogenase, cytoplasmic

MDHC_HUMAN

8

↑0.34

0.008

0.35

cytoplasm

5 6 7

Serum albumin Aspartate aminotransferase, cytoplasmic Aldehyde dehydrogenase, mitochondrial

ALBU_HUMAN AATC_HUMAN ALDH2_HUMAN

16 8 4

↑0.81 ↑0.53 ↑0.45

0.008 0.016 0.023

0.65 0.70 0.48

extracellular cytoplasm mitochondrion

8

6PGD_HUMAN

3

↑0.64

0.004

0.44

cytoplasm

9 10

6-Phosphogluconate dehydrogenase, decarboxylating Transketolase Glutathione S-transferase P

TKT_HUMAN GSTP1_HUMAN

4 4

↑0.71 ↑0.87

0.006 0.004

0.63 0.58

enzyme activity enzyme activity

11

Carbonic anhydrase 2

0.006

0.57

12

Acetyl-CoA acetyltransferase, mitochondrial

4 ↑0.68 Cholesterol Metabolism THIL_HUMAN 2 ↑0.15

cytosol, nucleus cytoplasm, mitochondrial cytoplasm

0.043

0.20

mitochondrion

enzyme activity

13 14

↑1.18 ↑0.66

0.002 0.008

1.28 0.48

PGK1_HUMAN KPYM_HUMAN

↑0.26 ↑0.39

0.016 0.006

0.22 0.28

glycolysis glycolysis, structural

17 18

Fructose-bisphosphate aldolase C L-Lactate dehydrogenase B chain

ALDOC_HUMAN LDHB_HUMAN

0.006 0.002

0.13 0.30

19 20

B-cell receptor-associated protein 31b Cytochrome c

BAP31_HUMAN CYC_HUMAN

13 ↑0.16 10 ↑0.49 Apoptosis 2 ↓−0.75 2 ↓−0.49

membrane cytoplasm, cytoskeleton cytoplasm cytoplasm, nucleus cytosol cytoplasm

oxidized protein apoptosis, glycolysis

15 16

α-Enolase Glyceraldehyde-3-phosphate dehydrogenase Phosphoglycerate kinase 1 Pyruvate kinase isozymes M1/M2

0.008 0.012

0.69 0.47

cytoplasm mitochondrion

apoptosis apoptosis, energy metabolism

21 22 23 24 25

Peroxiredoxin-6 Peroxiredoxin-1 Peroxiredoxin-2 Ferritin heavy chain Ferritin light chain

PRDX6_HUMAN PRDX1_HUMAN PRDX2_HUMAN FRIH_HUMAN FRIL_HUMAN

0.004 0.018 0.045 0.006 0.004

0.62 0.49 0.31 0.56 0.82

cytoplasm cytoplasm cytoplasm cytosol cytosol

antioxidant antioxidant antioxidant ion transport ion transport

26 27

Heat shock protein HSP 90-α Stress-70 protein, mitochondrialb

HS90A_HUMAN GRP75_HUMAN

0.035 0.029

0.93 0.65

stress response structural

28

Heat shock 70 kDa protein 1A/1B

0.016

0.38

29 30

Glial fibrillary acidic protein Apolipoprotein D

0.008 0.008

0.95 0.61

cytoplasm cytosol

structural transport, aging

31 32 33

Syntaxin-1A Synaptogyrin-1 Synaptic vesicle glycoprotein 2Ab

HSP71_HUMAN 5 ↑0.38 Inflammatory Response GFAP_HUMAN 25 ↑1.60 APOD_HUMAN 2 ↑0.69 Altered Synaptic Function STX1A_HUMAN 3 ↓−0.48 SNG1_HUMAN 1 ↓−0.51 SV2A_HUMAN 2 ↓−0.71

cytosol mitochondrion, nucleus cytoplasm

0.010 0.004 0.018

0.51 0.40 0.71

transport synaptosomal protein transport

34 35

Syndapin 1 Profilin-2

PACN1_HUMAN PROF2_HUMAN

4 1

↓−0.67 ↓−0.76

0.010 0.012

0.90 0.84

membrane membrane membrane (trans) membrane cytoplasm, cytoskeleton

36

Septin-5b

SEPT5_HUMAN

2

↓−0.51

0.023

0.58

37 38

Synaptic cell adhesion molecule 2b Synapsin-1

0.012 0.031

39 40

14-3-3 Protein β/α 14-3-3 Protein ζ/δ

3 ↓−0.33 9 ↓−0.58 Signal Transduction 1433B_HUMAN 3 ↓−0.77 1433Z_HUMAN 11 ↓−0.36

0.010 0.012

1 2 3

CAH2_HUMAN

ENOA_HUMAN G3P_HUMAN

Glycolysis 13 14 10 19

Oxidative Stress 4 ↑0.88 5 ↑0.43 4 ↑0.23 3 ↑0.71 2 ↑1.02 Stress Response 8 ↓−0.69 3 ↓−0.51

CADM2_HUMAN SYN1_HUMAN

2061

transport

structural, glycolysis oxidized protein

stress response

0.42 0.93

synaptic vesicle, cytoplasm membrane Golgi apparatus

endocytosis synaptic vesicle exocytosis, lipid transport cell cycle, synaptic vesicle targeting cell adhesion synaptic transmission

0.68 0.37

cytoplasm cytoplasm

signal transduction signal transduction



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Table 2. continued no.

entrya

Signal Transduction GDIR1_HUMAN 2 ↓−0.54 GBB2_HUMAN 2 ↓−0.58

0.031 0.027

0.51 0.67

cytoplasm cytoplasm

signal transduction synaptic transmission

↓−0.58

0.012

0.84

membrane

↑0.52

0.018

0.60

cytoplasm

signaling pathway, endocytosis signal transduction

↓−0.77 ↓−0.28

0.033 0.031

0.99 0.34

membrane membrane

44

Annexin A5

ANXA5_HUMAN

45 46

Clathrin heavy chain 1b Clathrin assembly protein AP-2 α-A large chain Plasma membrane calcium-transporting ATPase 1b Plasma membrane calcium-transporting ATPase 3b Annexin A6 Rab GDP dissociation inhibitor β Plasmolipinb Dihydropyrimidinase-related protein 2

CLH1_HUMAN AP2A1_HUMAN

48 49 50 51 52

log2 of av ratio

Sdc

43

47

no. of peptides

p-value

Rho GDP-dissociation inhibitor 1b Guanine nucleotide-binding protein G(I)/ G(S)/G(T) subunit β-2b Endophilin A1b

41 42

SH3G2_HUMAN

4 5 Others 14 4

localization

biological process

AT2B1_HUMAN

3

↓−0.75

0.006

0.80

membrane

membrane trafficking membrane trafficking, transport ion transport

AT2B3_HUMAN

2

↓−0.72

0.008

0.54

membrane

transport

ANXA6_HUMAN GDIB_HUMAN PLLP_HUMAN DPYL2_HUMAN

9 2 1 23

↑0.16 ↑0.58 ↑0.64 ↑0.36

0.008 0.002 0.035 0.006

0.15 0.43 0.84 0.36

cytoplasm Golgi apparatus membrane cytoplasm

COF1_HUMAN TBB3_HUMAN TPPP_HUMAN

3 2 3

↓−0.24 ↓−1.51 ↓−0.78

0.039 0.004 0.004

0.33 0.71 0.66

membrane cytoplasm cytoplasm

BASP1_HUMAN ACTN1_HUMAN HEM2_HUMAN NEUM_HUMAN CEND_HUMAN

8 3 1 2 1

↓−0.67 ↓−0.41 ↑0.58 ↓−0.75 ↓−0.32

0.008 0.018 0.004 0.012 0.043

0.67 0.39 0.31 0.84 0.39

membrane membrane cytosol membrane membrane

structural structural structural cell growth others

61 62 63 64

Cofilin-1 Tubulin β-3 chain Tubulin polymerization-promoting proteinb Brain acid soluble protein 1 α-Actinin-1 δ-Aminolevulinic acid dehydrataseb Neuromodulin Cell cycle exit and neuronal differentiation protein 1b Cathepsin D Neural cell adhesion molecule 2 Septin-2b Neuronal-specific septin-3b

ion transport transport transport regulation of neuron differentiation structural structural structural

CATD_HUMAN NCAM2_HUMAN SEPT2_HUMAN SEPT3_HUMAN

3 2 3 2

↑0.52 ↑0.21 ↑0.65 ↑1.65

0.033 0.037 0.002 0.020

0.64 0.27 0.69 1.60

enzyme activity cell adhesion cell cycle cell cycle

65

NAD-dependent deacetylase sirtuin-2b

SIRT2_HUMAN

4

↑0.83

0.012

0.80

66 67 68

Rab GDP dissociation inhibitor αb Dihydropteridine reductaseb Opioid-binding protein/cell adhesion moleculeb Neurotriminb

GDIA_HUMAN DHPR_HUMAN OPCM_HUMAN

12 6 2

↑0.27 ↑0.75 ↓−0.53

0.010 0.029 0.016

0.25 0.86 0.54

extracellular membrane membrane cytoplasm, cytoskeleton cytoplasm, cytoskeleton cytoplasm mitochondrion membrane

NTRI_HUMAN

1

↓−0.25

0.039

0.31

membrane

cell adhesion

53 54 55 56 57 58 59 60

69 a

protein name

cell cycle enzyme activity enzyme activity cell adhesion

Uniprot knowledge entry. bProteins which have been not reported in previous studies as related to AD pathology. cSd = standard deviation.

3.3. Proteomic Changes in AD Pathology Reveal Disruptions in Different Biological Functions

Proteins related to mitochondrial apoptosis and synaptic dysfunction were all found to be decreased in the AD brain. The individual changes of significantly altered protein levels on log2 scale (AD/control) are plotted in a heat map in Figure 3C. The proteins are sorted on decreasing average value within each predicted biological function category. In general, there is a concordance in resulting expression values between the examined samples. However, AD6/C1 is deviating some to all other samples. Since C1 has also been compared to AD1 we can conclude that the deviation is probably due to AD6 deviating to other AD samples. This may be due to unknown sources of variation during sample preparation or the biological sample being different from other AD samples. There is no deviating post mortem sample time for this sample, but the onset and duration of the disease are unknown. This may be one reason for the deviating result for this particular sample. However, since this is a human sample we can anticipate heterogeneity within sample groups and therefore only speculate in the source of variation.

To date, about 90 proteins have been proposed to be associated to AD pathogenesis.16,36 In the current study, we were able to identify and quantify 69 significantly differentially regulated proteins among which 46 have been previously implicated in AD pathogenesis. The remaining 23 proteins comprise novel proteins that have not previously been reported to be related to AD. Among the 69 significantly regulated proteins, 28 proteins showed a significance of p < 0.01 (Figure 2). Altered Energy Metabolism. Brain cells are highly energy dependent on maintaining ion homeostasis during metabolic activity of which glucose is the primary source of energy for the brain.37 Disease induced alterations can lead to the disruption of important energy-producing processes and result in the death of nerve cells. Metabolic failure has been described in several neurodegenerative diseases and was suggested as an early event in these pathologies.38 This hypothesis is supported 2062



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Figure 3. Pie charts representing the predicted biological processes of increased (A) and decreased (B) proteins levels in AD compared to control brains (p-value < 0.05). (C) Heat map displaying individual regulations for proteins and samples in combination with the predicted biological functions of significantly increased and decreased protein levels. The protein fold changes are displayed in log2 scale.

findings are in accordance with studies on mouse models for Aβ pathology, which have shown that aspartate aminotransferase and glutathione S-transferase P levels were increased in the hippocampus and cerebral cortex of 3xTgAD and Tg2576 transgenic mice.40 Increased levels of transketolase is in agreement with studies involving a APPE693Δ model.41 Sultana et al.32 have shown that the levels of carbonic anhydrase 2 also are increased in the AD brain. α-Enolase, which is involved in ATP production, was also found to be

by previous studies indicating metabolic failure in the AD brain.39 In this study, we found alterations in the levels of proteins involved in different metabolic functions in the mitochondria. Proteins with higher levels in AD brains include energy metabolic enzymes such as aspartate aminotransferase, aldehyde dehydrogenase, 6-phosphogluconate dehydrogenase, transketolase, glutathione S-transferase P, carbonic anhydrase 2, α-enolase, malate dehydrogenase, and serum albumin. These 2063



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increased in the AD brain.33 An increase in malate dehydrogenase level was also observed in AD brains.42,43 In addition, malate dehydrogenase also plays a key role in the tricarboxylic acid cycle (TCA).42 Decrease in the mitochondrial respiratory enzymes might cause generation of reactive oxygen species and apoptosis in connection to AD.44 To our knowledge, prolinerich transmembrane protein 2 has not previously been connected to AD pathology. Our results show higher levels of albumin in AD brains, which is in accordance with a previous study.33 Albumin is usually not found in adult brain tissue. However, increased level of albumin in AD brain might be due to a damage to the blood−brain barrier, a feature also demonstrated on APP transgenic mice.45 Glycolysis. In the AD brains, we found an increase in the levels of proteins involved in the regulation of glucose metabolism, including α-enolase, glyceraldehyde-3-phosphate dehydrogenase, and L-lactate dehydrogenase B chain. These findings are consistent with previous studies showing elevated levels of the glycolytic proteins in AD brains.46,47 The reduced levels of glucose metabolism during AD might lead to accumulation of glycolytic enzymes in the brain.48 Increased levels of pyruvate kinase isozyme might also suggest increased metabolic activity of activated glial cells.49 Apoptosis. Neuronal cell loss and synaptic loss due to apoptosis is a common feature in many neurodegenerative disorders.50,51 In this study, we found decreased levels in the AD brain of two proteins involved in the regulation of mitochondrial apoptosis: cytochrome c and B-cell receptorassociated protein 31 (BAP31). Cytochrome c is one of the key proteins in mitochondrial electron transport and decreased cytochrome c activity has been reported in several neurological diseases.52 In a recent study, we have also found a significant reduction of cytochrome c levels in brain tissue of the Tg2576 mouse model.53 These findings are in agreement with studies involving a triple transgenic mouse model of AD54 and brains from patients with AD and Down’s syndrome.44 B-cell receptor-associated protein 31 is an integral membrane protein of the endoplasmic reticulum (ER), which is a key regulator of protein trafficking and ER stress apoptosis.55 To our knowledge, BAP31 has never been found to be related to AD pathology. Oxidative Stress. Increased oxidative stress induced by free radical damage and hydrogen peroxide is a prominent features of AD pathology and other neurodegenerative diseases.56 We found increased levels of the antioxidant proteins (peroxiredoxin I and VI, heavy and light ferritin chain) in the AD brain, which is in agreement with the hypothesis of elevated oxidative stress in AD. It has been proposed that peroxiredoxin I and VI levels and ferritin heavy chain are elevated in AD brain as a defensive mechanism against oxidative stress to protect the neurons from the damage caused by hydrogen peroxide and reactive free radical species.33,47,57 Higher levels of peroxiredoxin VI as a protective mechanism during membrane damage due to phospholipid peroxidation was revealed in the studies conducted on cells.58 Peroxiredoxin VI inactivation showed oxidative stress in mice, establishing its role in oxidative defense.59 Stress Response. Molecular chaperone proteins such as heat shock proteins (HSPs) are associated with conformational changes, such as protein folding.36 In our study HSPs showed altered levels in the AD brain. A decreased level of HSP90A and increased level of HSP71 were observed, which is consistent

with previous studies.60 The alterations in the level of HSPs might be due to the different response to stress conditions.36 Decreased level of HSPs can be associated with their protective role in neuronal death associated with AD, whereas increased level of HSPs might be a response to the aggregation and selfassembly of proteins into amyloid fibrils.57,61 Inflammatory Response. We found that the glial fibrillary acidic protein level is more than 2-fold increased in the AD brain. This protein is an astrocyte-specific intermediate filament thought to provide structural support to normal astrocytes and is also a biomarker of astrocyte differentiation.62 Increased levels of glial fibrillary acidic protein in response to inflammation has been observed in AD brains32 and APP transgenic mouse models with amyloid plaque deposition.49 AD brains with inflammation is characterized by activated microglial cells, plaques with reactive astrocytes, and inflammatory mediator’s expression.63 Moreover, we found a clear increase in apolipoprotein D (ApoD) levels in AD brain. ApoD is a member of the lipocalins that plays a pivotal role in the transport of small hydrophobic ligands such as cholesterol, progesterone, and arachidonic acid.64 However, the exact function of ApoD is not yet known.65 It has been found to be associated with many neurodegenerative and neuropsychiatric disorders including schizophrenia, bipolar disorder, Niemann−Pick disease, cerebrovascular disease, motoneuron diseases, and meningoencephalitis.66 Increase in ApoD levels were shown to be associated with reactive astrocytes in relation to aging and glial funtion.67 Studies of ApoD in the CSF66 and in the hippocampus68 of AD patients have also showed a significant increase in protein levels. Recent studies have shown that ApoD acts by different molecular mechanism compared to other apolipoproteins and the elevated levels of ApoD might be related to the cognitive and behavioral decline observed in AD patients.69 Altered Synaptic Function. We found reduced levels of eight synaptic proteins (syntaxin-1A, synaptogyrin-1, synaptic vesicle glycoprotein 2A, syndapin 1, profilin-2, septin-5, synaptic cell adhesion molecule 2, and synapsin-1) in the AD brain. A loss of synaptic contacts in both the neocortex and hippocampus represents one of the major neuropathological hallmarks associated with AD. The decreased level of syntaxin1A, which is involved in the regulation of vesicular trafficking for exocytosis and for insertion of proteins into the plasma membrane,70 may reflect changes in synaptic properties. Our recent study has also shown a significant reduction of syntaxin1 levels in the brain of the Tg2576 amyloid mouse model.53 Synaptogyrin-1 is believed to perform a redundant function in synaptic plasticity.71 Previous studies have shown that synaptogyrin-1 and synapsin-1 levels are reduced in the hippocampus during AD progression.72 Moreover, recent studies on rat brain by Suzuki et al. suggested that syndapin 1 is linked to phosphorylation of tau.73 The decrease of profilin2 levels was also showed in the studies by Schonberger et al.33 The role of synaptic vesicle glycoprotein, septin-5, and synaptic cell adhesion molecule 2 have not previously been suggested to be involved in AD pathology. Signal Transduction Proteins. The levels of signal transduction proteins, such as 14-3-3 β/α, 14-3-3 γ, ρ GDPdissociation inhibitor 1, guanine nucleotide-binding protein subunit β-2, and endophilin A1 were found to be decreased, whereas annexin A5 were found to be increased, in the AD brain. 14-3-3 proteins play a major role in many cellular processes including signal transduction, neuronal development, 2064



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distribution of tubulin polymerization-promoting protein and δ-aminolevulinic acid dehydratase found in our study has not been published elsewhere. Levels of neuromodulin (GAP-43) associated with neuronal growth and neurite formation was found to be decreased in the AD brains, which is in agreement with a previous study.85 Elevated levels of aspartic protease cathepsin D were observed in the AD brains. Cathepsin D is localized in the neuritic plaques and might to be involved in AD pathology through the proteolysis of apolipoprotein E.86 Neural cell adhesion molecule 2 (NCAM) is one of the glycoproteins that play a key role in normal brain development.87 We identified an increase in the levels of NCAM in AD brain, which is in agreement with elevated NCAM levels in human AD serum samples88 and increased levels of NCAM1 in Tg2576 mouse models.53 Furthermore, we observed increased levels of septin-2, neuronal-specific septin-3, NAD-dependent deacetylase sirtuin-2, rab GDP dissociation inhibitor α, and dihydropteridine reductase proteins and decreased levels of opioid-binding that were not previously reported in connection to AD pathology. Accumulation of Iron in AD. One of the hypothesis as to why neuronal death occurs in AD is that an excess of iron can mediate oxidative stress.35 An increase in iron concentration, relative to the amount of ferritin, in the AD brain has been shown before.89 Ferritin is composed of heavy and light chains, involved mainly in the storage and transportation of iron to the cells. We found an increase in both ferritin heavy and light chain (FRIH and FRIL) in the AD brains. FRIL showed a 2fold change increase (p-value = 0.004). FRIL has been shown to interact with presenilin enhancer 2 (PEN-2), one of the components of the γ-secretase.90 Iron accumulation leads to the elevated levels of FRIL, which in turn promotes γ-secretase activity leading to enhanced Aβ production. Thus the dysregulation of iron may contribute to AD by promoting APP expression and Aβ deposition.

ion channel regulation, neurite growth, regulation of synaptic transmission, and plasticity.74 14-3-3 proteins are highly expressed in brain and make up as much as 1% of the soluble proteins in the brain.74 Immunohistochemical studies on post mortem AD brains have demonstrated the role of 14-3-3 in the AD pathology based on their colocalization with neurofibrillary tangles.75 An increase in levels of annexin A5 was found in the brains of Tg2576 mouse model.76 We observed a decrease in the rho GDP-dissociation inhibitor 1, guanine nucleotidebinding protein subunit β-2, and endophilin A1 levels in AD brains, which have not previously been reported in relation to AD. Other Proteins. Other proteins found to be differentially regulated are related to various biological processes, such as membrane trafficking, transport, cell adhesion, cell cycle, neuronal development, and diverse enzymatic activities. For example, the level of clathrin heavy chain 1 was found to be reduced in the AD brain. The clathrin family was observed as major proteins that constitute coated vesicles and with a major role in receptor mediated endocytosis, membrane trafficking, secretory function of neurons, and maintenance of synaptic functions.77 Irregularities in axonal transport leads to damage in clathrin associated membrane trafficking that might cause neuronal dysfunction.78 Abnormal distribution of clathrin light chain was shown in AD brains using immunohistochemical studies,78 but no previous studies have indicated a connection between clathrin heavy chain and AD pathogenesis. Transport defects have been suggested to play a role in the AD pathology cascade, including oxidative stress and plaque formation. Plasma membrane calcium-transporting ATPases (PMCAs) 1 and 3 were found to be decreased in levels in this study. Among different proteins involved in Ca2+ regulation, PMCAs act as active transporters that pump Ca2+ ions out of the cells. Disturbed neuronal Ca2+ homeostasis has been reported for AD and other neurodegenerative disorders,79 and a recent study showed that Ca2+ dysregulation can be influenced by Aβ.80 However, PMCAs 1 and 3 have not previously been discussed in connection with AD pathology. Moreover, the level of transport proteins annexin A6 (AnxA6) and rab GDP dissociation inhibitor β (GDIB) were found to be increased in our study. It has been demonstrated that AnxA6 is implicated in vesicular transport, membrane aggregation, and membrane fusion.81 In addition, a recent study of human AD hippocampal tissue showed increased levels of AnxA6 and GDIB,82 but plasmolipin has not been previously identified in connection to AD pathogenesis. Increased levels of dihydropyrimidinase-related protein 2 (DRP-2) were also observed in the AD brains. DRP-2 is a neuronal protein known to be hyperphosphorylated in neurofibrillary tangles, which is a characteristic feature observed in AD pathology.83 The increase in DRP-2 might be due to neuritic reorganization and the development of dystrophic neurites around amyloid plaques.49 Increased levels of DRP-2 in our study is consistent with the studies on APP Tg mouse models.49 Neuronal cytoskeleton derangement is a feature of the neurodegerative brain.34 Accordingly, the levels of cytoskeleton proteins including tubulin β-3 chain, tubulin polymerizationpromoting protein, and brain acid soluble protein 1 were reduced in the AD brains. The decreased level of tubulin β-3 chain is in agreement with other studies of human AD brain.34 A decrease in the brain acid soluble protein was mentioned in proteomic studies on transgenic mice.84 The abnormal

4. CONCLUSIONS In summary, we have used differential dimethyl labeling in combination with a shotgun based MS approach and found a significant difference in the brain proteome profile between AD and nondiseased control cases. In total, 69 proteins were found to be either increased or decreased in AD. Mainly, these proteins play key roles in energy metabolism, cholesterol metabolism, glycolysis, inflammatory response, oxidative stress, synaptic functions, stress response, signal transduction, membrane trafficking, and cellular transport mechanisms. In addition, our study revealed changes in the levels of 23 proteins that had not previously been implied in AD pathogenesis. Thus, our findings provide us with new information on the proteome changes that occur in AD brain and the identified proteins may be explored in plasma and/or CSF as potential novel potential biomarker candidates for AD diagnosis and progression.

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ASSOCIATED CONTENT

S Supporting Information *

Supplementary Table 1: Sample labeling setup. Supplementary Table 2: List of all proteins identified AD versus control brain samples found using stable isotope DML MS approach. Supplementary Table 3: List of all proteins with the relative quantifications found in at least 9 out of 10 AD/control pairs 2065



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using stable isotope DML MS approach. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Tel: +46 18 471 3688. Fax: +46 18 471 3692. E-mail: ganna. [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was supported by Uppsala Berzelii Technology Centre for Neurodiagnostics, with financing from the Swedish Governmental Agency for Innovation Systems. We acknowledge Dr. Andreas Dahlin for help with preparing Figure 1 and Dr. Rolf Danielsson for technical assistance with data analysis.

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