Amyloid Beta Ion Channel Hypothesis Statement

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Abstract

Alzheimer's disease (AD) is the threat of modern humankind that is provoked by increased human lifespan. Despite extensive studies on AD pathology for more than 100 years, there are no disease-preventing therapies. Growing evidence suggests the role of calcium (Ca2+) in the pathogenesis of AD. The main purpose of the article is to understand whether modern science is able to explain the synapse loss observed in early AD and discuss the role of Ca2+ hypothesis in it. Based on results obtained in our laboratory and others, we propose that familial AD-associated mutations in presenilins cause a Ca2+ overload of endoplasmic reticulum stores which leads to compensatory downregulation of the neuronal store-operated Ca2+ (nSOC) entry pathway. We propose that synaptic nSOC is necessary for the stability of mature synaptic spines and that dysfunction of this pathway may play an important role in synaptic and memory loss in AD.

© 2013 S. Karger AG, Basel


Alzheimer's disease (AD) is a well-known pathology destroying the human brain and the personality. The majority of known facts about AD pathogenesis come from discoveries in mouse models mimicking genetically caused cases of familial AD (FAD). Although FAD covers about 1-2% of all AD cases, the mouse models and clinical data agree that synapse loss is the major hallmark of AD that results in memory loss.

What is the physiological substrate of memory? Expression of long-term potentiation in response to brief high-frequency stimulation of synaptic ends in the hippocampus is strongly correlated with learning and memory [1,2]. Long-term potentiation takes place in small dendritic protrusions called dendritic spines. Based on their size and shape, spines are divided into three groups: stubby, thin and mushroom. It has been proposed that the mushroom spines are stable ‘memory spines', and therefore, they store memories, and that thin spines are ‘learning spines' that serve as physical substrates for the formation of new memories [3,4]. Since loss of memories is a hallmark of AD, we and others previously proposed that mushroom spines are more likely to be eliminated during AD progression [5,6,7].

What mechanism is responsible for mushroom spine elimination? The dominant amyloid-β (Aβ)-based hypothesis of AD states that soluble Aβ42 peptides possess synaptotoxic effects. Aβ could mediate the synapse loss through the potentiation of the N-methyl-D-aspartate receptor. Stimulation of the N-methyl-D-aspartate receptor triggers excessive calcium (Ca2+) influx that activates calcineurin, a Ca2+-activated phosphatase whose activation leads to synapse weakening and AD-associated spine loss [8]. However, many facts speak for early Ca2+ abnormalities that precede or even happen in the absence of Aβ pathology [9,10]. The Ca2+ hypothesis of brain aging and AD states for sustained changes in Ca2+ homeostasis could provide the common pathway for aging and the neuropathological changes associated with AD [11]. In particular, multiple evidence points to disregulated endoplasmic reticulum (ER) Ca2+ homeostasis in aging and AD neurons [9,10]. There are two channels in the ER that mediate Ca2+ release: ryanodine receptors (RyanR) and inositol triphosphate receptors (IP3R). Taking into account that IP3R predominantly resides in the soma, whereas RyanR-mediated signals are more distinct in dendritic spines and presynaptic terminals [12,13], the input of abnormal RyanR function on postsynaptic Ca2+ signaling could be stronger than IP3R-mediated signaling. Thus, blocking RyanR (for example with dantrolene) appears to be a potential way to stabilize Ca2+ signals in AD brains. However, inconsistent results were obtained when dantrolene was tested in AD mouse models [14,15,16,17].

In addition to RyanR and IP3R, our recent data show that presenilins (PS; mutations in PS are associated with FAD) could play the role of a low conductance ER Ca2+ leak channel, and many FAD mutations disrupt this function [18]. This idea remains controversial [19], but our hypothesis has found confirmation in a recent breakthrough study that demonstrates the crystal structure of a bacterial homologue of PS (PSH) [20]. In agreement with our mutagenesis data [21], the authors found that PSH has a water-filled hole that is large enough to allow the passage of small ions, suggesting that PSH may function as an ion channel. Our hypothesis was also supported by a recent unbiased screen for Ca2+ homeostasis modulators [22]. These authors demonstrated that knocking down PS2 dramatically reduced the ER Ca2+ leak rate in HEK293 cells, consistent with the ‘leak channel' hypothesis [22,23].

What is the connection between impaired ER Ca2+ leak function, ER Ca2+ overload and synaptic loss in AD? We previously proposed that abnormalities in ER Ca2+ handling may be linked to destabilization of mushroom postsynaptic spines [6,7]. Consistent with this idea, in recent experiments, we observed a significant downregulation of the synaptic neuronal store-operated Ca2+ (nSOC) entry pathway in PS mutant neurons [Sun and Bezprozvanny, unpubl. data]. In agreement with our findings, impaired SOC was reported by several groups for PS mutant cells [16,24,25,26,27,28]. Our results further indicate that reduced postsynaptic SOC leads to destabilization and elimination of mushroom spines - sites of memory storage [Sun and Bezprozvanny, unpubl. data].

Based on obtained results, we propose that synaptic ER Ca2+ overload and compensatory downregulation of the synaptic nSOC pathway play an important role in synaptic loss in AD and aging brains. Our results suggest that upregulation of the synaptic nSOC pathway may yield therapeutic benefits for the treatment of AD and age-related memory problems.

Acknowledgments

I.B. is a holder of the Carl J. and Hortense M. Thomsen Chair in Alzheimer's Disease Research. This work was supported by Welch Foundation I-1754 (I.B.), National Institutes of Health grant R01NS080152 (I.B.), by the contract with the Russian Ministry of Science 11.G34.31.0056 (I.B.), and by the Dynasty Foundation grant DP-B-11/13 (E.P.).


References

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Author Contacts

Ilya Bezprozvanny

Department of Physiology, ND12.200AA, UT Southwestern Medical Center at Dallas

5323 Harry Hines Blvd.

Dallas, TX 75390-9040 (USA)

E-Mail Ilya.Bezprozvanny@UTSouthwestern.edu


Article / Publication Details

Received: May 07, 2013
Accepted: August 01, 2013
Published online: September 24, 2013
Issue release date: January 2014

Number of Print Pages: 3
Number of Figures: 0
Number of Tables: 0

ISSN: 1660-2854 (Print)
eISSN: 1660-2862 (Online)

For additional information: https://www.karger.com/NDD

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Regulatory Compliance

All protocols were carried out in accordance with the Charles F. and Joanne Knight Alzheimer’s Disease Research Center and Washington University guidelines. This specific study was approved by the Knight Alzheimer’s Disease Research Center tissue committee. All donors or their surrogates gave informed consent for their brains to be used for research studies.


Human Tissue

Clinically and neuropathologically well-characterized human brain tissue samples were obtained from the Charles F. and Joanne Knight Alzheimer’s Disease Research Center (knight ADRC), Washington University School of Medicine, Saint Louis, Missouri. At the time of death, informed consent was obtained from the next of kin in accordance with the local Institutional Review Board. Cognitive status at expiration was determined using a validated retrospective post-mortem interview with an informant to establish the Clinical Dementia Rating (CDR)34. We used frozen tissue from the frontal lobe (Brodmann areas 8/9) of severely demented participants with Alzheimer’s disease dementia (CDR3, mean age at death = 84 ± 6.6 yrs; n = 6; mean post-mortem interval = 11.4 ± 4.8 hours (Table 1). In addition, parietal lobe was used for method development in addition to frontal lobe. Routinely, the right cerebral hemisphere was coronally sliced at 1 cm intervals and frozen by contact with pre-cooled Teflon®-coated aluminum plates and temperature equilibrated by immersion into liquid nitrogen vapor in a cryo-vessel. Following freezing, tissues were placed in Ziploc® storage bags and stored in freezer at −80 °C35.


Amyloid-beta (Aβ) Extraction and Separation of Soluble Aggregates from Insoluble Material

Complete methods are described in Esparza et al.20. Briefly, 1–2 g of frozen CDR3 (severe AD) frontal cortical samples, including both gray and white matter, were weighed, stripped of pia mater, leptomeningeal, and intraparenchymal vessels to the fullest extent possible. and dounce homogenized at a 10:1 buffer volume:tissue weight ratio using a constant 25–40 manual strokes. Homogenization buffer consisted of ice-cold 1X phosphate buffered saline (PBS) (137 mM sodium chloride, 7.76 mM sodium phosphate dibasic, 2.17 mM monopotassium phosphate, 2.7 mM potassium chloride) with 0.45% (w/v) (3-((3-cholamidopropyl) dimethylammonio)−1-propanesulfonate) (CHAPS) and 1X protease inhibitor (2 ug/mL aprotinin and 1 ug/mL leupeptin). The resulting homogenate was rotated for 15 min at 4 °C before centrifugation at 17,000 × g for 30 min in a Sorvall RC 5B centrifuge with a SS-34 rotor. The supernatant was centrifuged in Beckman Optima XPN-100 centrifuge with a Ti70.1 rotor for 60 min at 100,000 × g at 4 °C, and the pellet (insoluble material; see below) was resolubilized in 5 M guanidine hydrochloride. The supernatant of the 100,000 x g spin was centrifuged for 60 min at 475,000 × g at 4 °C with a 70% sucrose cushion. The bottom layers (~2 mL) atop of the sucrose cushion (see Fig. 1a) were used for analysis of soluble Aβ aggregates. These methods have been demonstrated to preserve the size distribution of soluble Aβ aggregates present in PBS lysates, and do not result in artefactual aggregation of monomeric Aβ20. All pipet tips and tubes were blocked with 2% bovine serum albumin to significantly reduce non-specific loss of Aβ.


Purification of Soluble Aβ Aggregates

The layers atop the 70% sucrose cushion of the 475,000 × g spin were immunoprecipitated with 100 uL/mL of a 50% slurry of beads conjugated to the monoclonal antibodies HJ3.4 and HJ5.1 overnight (22 hrs) at 4 °C. HJ3.4 binds the N-terminus of canonical Aβ, and HJ5.1 binds a mid-domain epitope. Beads were washed 15 times in (1 mL each) 1X PBS and eluted with formic acid at room temperature for 15 min. Total protein and Aβ concentrations were determined by NanoOrange (Molecular Probes, Eugene, OR) and ELISA, respectively. 5 ng of total Aβ from each participant sample was dried to completeness in vacuo. The 2D Clean-Up Kit (GE Healthcare, Piscataway, NJ) was used to desalt and delipidate the samples. Precipitated samples were subjected to C8 TopTips (Glygen, Columbia, MD) to separate full-length proteins from Aβ peptides (Supplementary Fig. 1, Supplementary Tables 1 and 2). C8 TopTips were conditioned in 60% ACN/ 0.05% TFA (w/v) and equilibrated in 0.05% TFA (aq., v/v) three times each for 1 min at 2,000 rotations-per-minute (rpm). Next, precipitated samples were resuspended in 80 uL of neat formic acid and applied to the C8 TopTips and spun for 1 min at 2,000 rpm. The flowthrough was collected and dried to completeness in vacuo and stored at −80 °C until analysis by nLC-MS/MS.


Purification of Insoluble Aβ Aggregates

The pellet of the 100,000 × g spin was resolubilized in 5 M guanidine hydrochloride (pH 8.0) overnight at 4 °C. The resulting guanidine solubilized 100 k pellet was centrifuged in a MicroCL 17 R centrifuge at 17,000 × g to remove any guanidine insoluble material. Next, the supernatant was diluted 1:10 (0.5 M guanidine, final concentration) in 1X PBS and immunoprecipitated with 100 uL/mL of a 50% slurry of immobilized monoclonal antibodies HJ3.4 and HJ5.1 overnight (22 hrs) at 4 °C. Beads were washed 15 times in 1X PBS (1 mL each) and eluted 3X with 100 uL formic acid at room temperature for 5 min each. Total protein and Aβ concentrations were determined by NanoOrange (Molecular Probes, Eugene, OR) and ELISA, respectively20. 5 ng of total Aβ from each patient sample was dried to completeness in vacuo. The 2D Clean-Up Kit (GE Healthcare, Piscataway, NJ) was used to desalt and delipidate the samples. Precipitated samples were subjected to C8 TopTips (Glygen, Columbia, MD) to separate full-length proteins from Aβ peptides (Supplementary Fig. 1, Supplementary Tables 1 and 2). C8 TopTips were condition in 60% ACN/0.05% TFA (v/v) and equilibrated in 0.05% TFA (aq., v/v) three times each for 1 min at 2,000 rpm. Next, precipitated samples were resuspended in 80 uL of neat formic acid and applied to the C8 TopTip and spun for 1 min at 2,000 rpm. The flowthrough was collected and dried to completeness in vacuo and stored at −80 °C until analysis by nLC-MS/MS.


Aβ ELISA

The Aβ1-x ELISA was performed as previously described20. Briefly, mouse monoclonal HJ5.1 (mid-domain) was used to coat 96-well Nunc MaxiSorp plates (464718, Nalge Nunc, Rochester, NY) at 20 μg/mL in a carbonate buffer (35 mM sodium bicarbonate, 16 mM sodium carbonate, 3 mM sodium azide, pH 9.6) using 100 μl/well overnight at 4 °C. After washing 5x and blocking in 2% bovine serum albumin (BSA, A7030, Sigma-Aldrich, St. Louis, MO) in 1X PBS for 30 min at room temperature, samples and standards (Aβ1–40 on a 8-point standard curve) were plated in dilution buffer20 and incubated overnight at 4 °C. Samples and standards were developed by incubating in sequence with biotinylated HJ3.4 (canonical N-terminus) at 100 ng/mL for 1 hour at room temperature, streptavidin HRP-20 (65R-S103PHRP, Fitzgerald, Acton, MA) for 30 min at room temperature, and finally 3, 3′, 5, 5′ – tetramethylbenzidine (TME) (T5569, Sigma-Aldrich, St. Louis, MO) for measurement on a BioTek Synergy 2 plate reader at 650 nm as previously described20.


Protease Inhibitor Control

While the truncation seen is not likely a post-mortem artifact, we used only two protease inhibitors in our homogenization buffer instead of a cocktail of inhibitors, which would protect against a broader spectrum of protease activities. To evaluate the possible impact of using only two protease inhibitors in the truncation profile of Aβ, we analyzed a representative sample (Pt1) using our standard inhibitors (aprotinin and leupeptin) or Halt Protease and Phosphatase Inhibitor Cocktail (78443, Thermo Fisher Scientific) at 1X (final concentration). Three grams of frontal tissue was diced (on ice) and split evenly for homogenization in either the standard buffer or the cocktail buffer and processed for insoluble and soluble fractions as described above (Supplementary Fig. 2). Mass spectrometry analysis we performed as described below. Spider search results with a score (−10logP) of 31.7 or higher (an estimated FDR value of 2.3% at the peptide level). Only truncated proteoforms were considered for further analysis.


nLC-MS/MS

Samples from each individual CDR3 participant (n = 6, biological replicates) across the HMW soluble and insoluble Aβ fractions were split into two technical replicates (of 5 ng total Aβ as measured by ELISA) with the exception of Participant 4 (Pt4), which did not have enough material for a second technical replicate. All samples were prepared (precipitation and C8 SPE) in two block-randomized sets (https://www.random.org)36 for each set of participant replicates across two days. Samples were resuspended in 1%/10%/5% FA/ACN/MeOH (v/v) and analyzed by non-stop nLC-MS/MS in a block-randomized fashion36 – to eliminate systemic bias due to run order – for a total of 22 Thermo.raw files on a LTQ-Orbitrap Fusion (Thermo Fisher Scientific). Throughout data acquisition, quality assurance/quality control (QA/QC) standard of 20 fmoles BSA (#P8108S, New England BioLabs, Ipswich, MA) was injected every 12–18 hrs to monitor instrument drift and variability over time. 29 BSA peptides from each interwoven QA/QC run were analyzed with AutoQC for instrument performance metrics37 (Supplementary Fig. 3).

Separations were performed using an online NanoAcquity UPLC (Waters). The chromatographic separation was performed on an ACQUITY UPLC HSS T3 (360 μm OD × 75 μm ID) column packed with 10 cm C18 (1.8 μm, 100 Å, Waters) at 300 nL/min and heated to 60 °C. Mobile phases were 0.1% FA in water (A) and 0.1% FA in ACN (B). Samples were eluted from the column with the gradient ramped to 35% B over 65 min and further increased to 95% B over 8 min and held for an additional 6 min. Total run time, including column equilibration, sample loading, and analysis was 89 min. The mass spectrometer was operated in data-dependent mode to automatically switch between MS and MS/MS acquisition. The survey scans at mass-charge ratio (m/z) 400–2000 (MS) were acquired in the Orbitrap at high resolution (60,000 at m/z 400) in profile mode, and the MS/MS spectra were acquired in the Orbitrap (15,000 at m/z 400) in centroid mode using XCalibur, version 3.0 (Thermo Fisher Scientific). Ion injection times for the MS and MS/MS scans were 500 ms each. The automatic gain control targets were set as 2 × 105 for MS and MS/MS in the Orbitrap. The most abundant precursor ions from each MS scan were sequentially isolated and fragmented in the Orbitrap using HCD (isolation width 2.0 Da, normalized collision energy 30%, activation Q 0.250, and activation time 10 ms) within a 3 sec duty cycle (TopSpeed method). Dynamic exclusion (±10 ppm relative to precursor ion m/z) was enabled with a repeat count of one, a maximal exclusion list size of 500, and an exclusion duration of 60 s. Monoisotopic precursor selection (MIPS) was enabled and unassigned ions were rejected.


Mass Spectrometry Data Processing

MS files (.raw) were imported into PEAKS (version 8, Bioinformatics Solutions Inc., Waterloo, ON) and searched against a UniprotKB/SwissProt Human database of reviewed, canonical sequences (October 2015; 20,204 entries) appended with the cRAP contaminant database (January 2015 version, The Global Proteome Machine, www.thegpm.org/cRAP/index.html). Precursor ion mass tolerance was set to 10 ppm, and fragment mass tolerance was 0.1 Da with no enzyme specificity. All modifications in the UniMod database (http://www.unimod.org) were considered in the PEAKS search. PEAKS automatically generates a decoy-fusion database, which appends a decoy sequence to each protein identification for the calculation of FDR38. The Spider search results with a score (−10logP) of 31.9 or higher (an estimated FDR value of 2.9% at the peptide level) for the CDR3 cohort data. Spider is an algorithm tool within PEAKS, which we utilized to search peptide spectrum matches not identified by the database search by altering the amino acids systematically at each residue until a new, better peptide sequence is constructed from the MS/MS data39. All non-Aβ peptides and those Aβ proteoforms containing formylation were removed. Immunoprecipitation elution was in neat formic acid (Sigma #94318); thus, formylation occurring endogenously or by the elution conditions is indistinguishable. Further, samples were resuspended in MS buffer containing 5% methanol (v/v) to maintain solubility of Aβ, which in combination with 1% FA could lead to artefactual methylation via Fischer esterification.

In the CDR3 cohort, 27 Aβ proteoforms were identified meeting the criteria described above. However, we sought reproducible identification of the 27 Aβ proteoforms on an independent platform. The filtered list of Aβ proteoforms were i) assigned identification numbers by a third party who had no part in the initial analysis and ii) transformed into chemical formulas. This chemical formula list was queried against each.raw file with National Resource for Top-Down Proteomics (NRTDP) pipeline version 1.3 at ± 10 ppm precursor ion mass tolerance and a 4 min retention time window alignment (Supplementary Fig. 4). If a given proteoform was not identified by both platforms (PEAKS and NRTDP), it was removed from analysis; 26 out of 27 were reproducibly identified on both platforms. MS intensity was calculated across all peaks within an isotopic cluster extracted with Skyline for each proteoform identified in Fig. 2 and exported as an Excel file.


Differential Mass Spectrometry (dMS)

In this method relative quantitation is performed from the full-scan MS. The high-resolution MS provides m/z, retention time, charge state, and relative abundance (intensity) of precursor ion across multiple samples for comparative analysis40,41,42,43. A table of proteoform intensities was imported into a custom SAS script for analysis. To detect differential (label-free) abundance from the intensities data40, the MS intensity measures (calculated as described above) for each proteoform were standardized to Z-scores across all measures of that proteoform. Different charge states were treated as independent measures of the same proteoform as reflected in the increased degrees of freedom for certain tests (Supplementary Table 3).

ANOVA based on a hierarchical linear model (HLM) with replicates nested within patients, and patients treated as random effects, was used to test the fixed effect difference between soluble aggregate Aβ and more insoluble Aβ fractions. All calculations were done using SAS PROC MIXED with restricted maximum likelihood estimations (SAS Institute, Cary, NC) and type 3 sums of squares (where appropriate). The HLM was used to test for differences in mean intensity between CDR3 soluble and insoluble Aβ fractions, while allowing each biological replicate to have its own overall mean. Each p-value of the resulting 26 F tests was corrected for multiple testing (q-value), and those with an FDR of ≤0.05 were considered significant44. Next, the same model was run on the log2-converted raw intensities. The difference in estimated mean between aggregate Aβ and more insoluble Aβ fractions in these tests was taken as an estimate of the overall fold change within the fractions. Thus two separate ANOVA analyses are run, the first to test the statistical significance of abundances of proteoforms between fractions, and the second to estimate effect size25, 45. The mass spectrometric data have been deposited in ProteomeXchange (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository46 with the data set identifier PXD005119.


Data Visualization

Analyses were performed and visualized with Excel 2013, PRISM (version 7) for correlation analysis of signal intensity and PMI and graphing volcano plots or SAS (version 9.4) for hierarchical linear modeling.

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