Semiquantitative proteomic analysis of human hippocampal tissues from Alzheimer’s disease and age-matched control brains
- Ilijana Begcevic†1, 2,
- Hari Kosanam†1, 2,
- Eduardo Martínez-Morillo1, 2,
- Apostolos Dimitromanolakis2,
- Phedias Diamandis1,
- Uros Kuzmanov1, 2,
- Lili-Naz Hazrati1, 3 and
- Eleftherios P Diamandis1, 2, 4, 5Email author
© Begcevic et al.; licensee BioMed Central Ltd. 2013
Received: 15 March 2013
Accepted: 5 April 2013
Published: 1 May 2013
Alzheimer’s disease (AD) is the most common type of dementia affecting people over 65 years of age. The hallmarks of AD are the extracellular deposits known as amyloid β plaques and the intracellular neurofibrillary tangles, both of which are the principal players involved in synaptic loss and neuronal cell death. Tau protein and Aβ fragment 1–42 have been investigated so far in cerebrospinal fluid as a potential AD biomarkers. However, an urgent need to identify novel biomarkers which will capture disease in the early stages and with better specificity remains. High-throughput proteomic and pathway analysis of hippocampal tissue provides a valuable source of disease-related proteins and biomarker candidates, since it represents one of the earliest affected brain regions in AD.
In this study 2954 proteins were identified (with at least 2 peptides for 1203 proteins) from both control and AD brain tissues. Overall, 204 proteins were exclusively detected in AD and 600 proteins in control samples. Comparing AD and control exclusive proteins with cerebrospinal fluid (CSF) literature-based proteome, 40 out of 204 AD related proteins and 106 out of 600 control related proteins were also present in CSF. As most of these proteins were extracellular/secretory origin, we consider them as a potential source of candidate biomarkers that need to be further studied and verified in CSF samples.
Our semiquantitative proteomic analysis provides one of the largest human hippocampal proteome databases. The lists of AD and control related proteins represent a panel of proteins potentially involved in AD pathogenesis and could also serve as prospective AD diagnostic biomarkers.
KeywordsAlzheimer’s disease Cerebrospinal fluid Hippocampus Human brain Mass spectrometry
Alzheimer’s disease (AD) is a progressive neurodegenerative disease mainly affecting people over the age 65. The hallmarks of AD are the extracellular deposits known as amyloid β (Aβ) plaques and the intracellular neurofibrillary tangles (NFT), the principal players thought to be involved in synaptic loss and neuronal cell death [1, 2]. Currently, diagnosis of AD is based on clinical criteria that are relied on neuropsychological examination, mental status testing and insight into the medical history of the patients. However, still, the gold standard for AD diagnosis remains histological examination of post mortem brain regions. Furthermore, there are no accurate methods to track the efficacy of new therapies. Hence, there is a desperate need for specific biomarkers that proactively identify evolving cases of AD and may lend way to more favorable medical outcomes . Cerebrospinal fluid (CSF) has been so far the most promising source of potential protein biomarkers. CSF amyloid β 1–42 fragment (Aβ 1–42) has shown about 50% decrease in AD patients in comparison to cognitively normal individuals [4, 5], however it is not consistent in distinguishing AD from other forms of dementia . Other prospective candidates, total tau (T-tau) and phosphorylated tau (P-tau) levels have been found increased in CSF AD cases compared to controls . Although T-tau levels have a trend to be elevated in other neurodegenerative diseases as well , indicating the lack of specificity, P-tau levels may discriminate AD from other types of dementias [9, 10]. The combination of these three biomarkers represents markers for Aβ depositions as well as neuronal injury and have confirmed good diagnostic accuracy in early AD by multicenter studies in CSF . In addition, measurement of Aβ 1–42, T-tau and P-tau levels in CSF are included in the diagnostic criteria for diagnosis of mild cognitive impairment due to AD . Human brain tissue proteomics have been studied gradually in the last decade [12–14]. A recent proteomic study with mass spectrometry analysis has demonstrated a total of 197 proteins differentially abundant in AD versus controls, after examining the temporal lobe region , whereas in another study 18 proteins were identified in hippocampus region with altered protein level that are involved in different cellular functions in AD pathology . Together with temporal lobe, hippocampus is one of the earliest affected regions in AD pathology, when memory and cognitive functions are already impaired [17, 18]. Therefore, proteomic analysis of AD hippocampus, combined with pathway analysis, could help in defining the etiology of the disease as well as identify potential biomarkers and therapeutic targets. We present here one of the first comprehensive proteomic analyses of the hippocampal region of three brains affected by AD and three age-matched controls.
Results and discussion
It should be noted that when the same amount of total protein was processed for proteomic analysis; more proteins were identified in controls, compared to AD tissues. Lower number of protein identifications in AD tissues may be attributed to inherent insolubility of protein aggregates which renders them inaccessible to trypsin proteolytic activity. To the best of our knowledge, the current report presents the largest hippocampal proteome dataset published to date. Moesin (MSN), heat shock protein beta-1 (HSPB1), S100B protein (S100B), and chloride intracellular channel protein 1 (CLIC1) were the top four over-expressed proteins (≥ 4.5-fold measured in terms of spectral counts) in AD tissues. Elongation factor 1-alpha 2 (EEF1A2), 2-oxoglutarate dehydrogenase (OGDH), isoform 1 of immunoglobulin superfamily member 8 (IGSF8) and actin-related protein 2 (ACTR2) are highly down-regulated proteins (≥ 4.5-fold) in AD tissues. Top 150 highly over-expressed and under-expressed protein fold changes are presented as additional information.
The underlying objective of the current study was to segregate promising candidate biomarkers from the list of 2954 proteins for future verification studies. To this end, we considered the 204 and 600 proteins that were identified exclusive to AD tissues and control tissues, respectively. The failure to detect these proteins does not endorse their absence; however, it does imply that these proteins are differentially expressed. Mere differential expression of a protein in AD tissues does not qualify the protein to be a biomarker, unless its disease-specific higher expression in tissues is reflected in easily accessible bio-fluids such as CSF or serum. In this light, we compared the current hippocampal proteome with literature-based CSF proteome ; 25% of 2954 tissue proteins were present in CSF (see Additional file 1). A considerable finding is that 40 of the 204 AD-exclusive proteins and 106 of 600 control-exclusive proteins were also detected in CSF (Figure 1B). Secretory origin is one of the most important qualifications of biomarker candidate . It is well-established that majority of CSF and serum proteins are of extracellular and secretory origin. Therefore, we assume that extracellular and secreted proteins, identified in CSF and up/down-regulated in AD tissues are favourable candidates for biomarker verification. As most of the 40 and 106 proteins that are present in CSF proteome were either extracellular/secretory or membranous origin, therefore, it is worthwhile to include these proteins as a potential source of candidate biomarkers that need to be further studied and verified in CSF samples (please see Additional files 3 and 4). Please see Additional files 5 and 6 for differentially-expressed proteins in AD and Control tissue pools.
Hippocampus is one of the primary regions of the brain affected by Alzheimer’s disease. This structure is known to host tangles and plaques in the earliest phases of the disease cascade, even before the appearance of clinical symptoms. The proteome of such a pivotal region represent a promising source of diagnostic markers and molecular targets for therapeutic intervention. Herein, we performed proteomic analysis of freshly-frozen post-mortem hippocampal tissue sections from Alzheimer’s patients (n = 3) and age-matched controls (n = 3). Our detailed proteomic analysis utilizing offline multidimensional chromatography coupled with the LTQ-Orbitrap XL mass spectrometer and semiquantitative spectral counting methods identified 2954 proteins, one of the largest human hippocampal proteome database published to date. We applied a hypothesis-driven set of filtering criteria, based on protein’s cellular origin and identification in the cerebrospinal fluid proteome to find proteins that can be used as potential biomarkers in cerebrospinal fluid.
Post-mortem frozen brain hippocampal tissues were obtained with Research Ethics Board approval from the University Health Network, Toronto, Canada. Three pathologically confirmed AD tissues (all three had Braak stage 6/6) were obtained from three female patients (aged 69, 75 and 98 years) with PMI of 13, 4 and 19.5 hours, respectively, while three control tissues were obtained from one female (aged 77 years) and two male patients (aged 78 and 80 years) with PMI of 12, 12 and 4 hours, respectively. Control patients were diagnosed with non-metastatic colon cancer, cardiovascular disease and heart failure, respectively. Prior to digestion, frozen tissue sections from both AD and controls were cut and weighted (~150 mg wet weight). Proteins from these six brain tissues were extracted and solubilized using 0.2% RapiGest (Waters Corporation, Milford, USA) in 50 mM ammonium bicarbonate. Briefly, tissue samples were homogenized (Polytron PT3100, Capitol Scientific, Austin, USA) at 15,000 rpm, for 15 s and sonicated on ice three times for 15 s with MISONIX immersion tip sonicator (Q SONICA LLC, CT, USA). The samples were centrifuged at 15,000 g at 4°C for 20 min; the supernatants were collected and measured for total protein content. Three AD tissues and three control tissues were pooled separately and an equal amount (3 mg) of protein from each pool was processed. Proteins were reduced and alkylated with 5 mM dithiothreitol and 15 mM iodoacetamide. To digest the proteins, sequencing grade trypsin (Promega, WI, USA) was added, at an enzyme to substrate ratio of 1:50 and the digestion was carried out at 37°C for 18 hours. Fractionation of acidified tryptic-peptides was performed on a PolySULFOETHYL aspartamide strong cation exchange (SCX) column (2.1 mmID × 200 mm; 5 μ; 200 °A; The Nest Group, Inc., MA, USA) connected to an Agilent 1100 HPLC system. SCX fractionation was performed in triplicate for AD and control pools, and 20 fractions were collected per chromatographic run. This amounted to a total of 120 SCX fractions, which were then subjected to LC-MS/MS analysis after a brief desalting procedure. A 60 min linear gradient method was operated with buffer A → B (Buffer A: 0.26 M formic acid (FA) in 5% acetonitrile, B: 0.26 M FA in 5% acetonitrile and 1 M ammonium formate) at a flow rate of 250 μL/min. SCX fractionation was performed in triplicate for AD and control pools. The peptides from SCX fractions were desalted and injected onto a nano-LC system (Proxeon Biosystems, Odense, Denmark) connected online to LTQ-Orbitrap XL mass spectrometer (Thermo Fisher Scientific, San Jose, CA, USA). A 90 min linear gradient reverse-phase chromatography (Buffer A: 0.1% FA in water and B: 0.1% FA in acetonitrile) at a flow rate of 400 nL/min was performed to resolve peptides on a C18 column (75 μM × 5 cm). The mass spectra were acquired in data-dependent mode. The MS spectra were searched against the non-redundant IPI human database (version 3.71 containing both forward and reverse protein sequences) using two search engines, separately: Mascot, version 2.1.03 (Matrix Science) and the Global Proteome Machine manager, version 2006.06.01. The following parameters were used: (I) enzyme: trypsin; (II) one missed cleavage allowed; (III) fixed modification: carbamidomethylation of cysteines; (IV) variable modifications: oxidation of methionines; (V) MS1 tolerance, 7 ppm; and (VI) MS2 tolerance, 0.4 Da. The resulting Mascot DAT and X! Tandem XML files were merged using Scaffold® (version 2.06, Proteome Software Inc., Portland, Oregon) with ‘MudPIT’ (multidimensional protein identification technology) option checked. Scaffold data was filtered using the X! Tandem Log E (min 3.0) and Mascot ion-score filters [ion score 15, 30 (+2) and 40 (+3)] in order to obtain a protein false-positive rate (FPR) of ≤ 1%. FPR = 2 × (number of proteins identified by searching the reverse sequences)/(the total number of identified proteins). Scaffold® protXML reports were exported and uploaded into Protein Center (Proxeon Biosystems, Odense, Denmark) to create Venn diagrams.
The proteomic data associated with this manuscript may be downloaded from ProteomeCommons.org Tranche using the following hash Khn5Yg/CHsUFAZFaObXXCrT75bIRXHdWuJLgEDPWwgT + A5+/62Ijmc4Y/jhNS1GTXxORV7gfkaIbskPpU6RCbwIDDF4AAAAAAAADIg==Encrypt passcode: ecPC48nIVr0iD6OzSDSa
The data can be viewed with Scaffold (ver. 2.6) viewer, a freeware available on http://www.proteomesoftware.com/Scaffold/Scaffold_viewer.htm
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