Characterization of Proteins Present in Isolated ... - ACS Publications

Jan 4, 2018 - College of Sciences, University of Texas at San Antonio, One UTSA Circle, San Antonio , Texas 78249 , United States. Stephan B. H. Bach...
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Characterization of Proteins Present in Isolated Senile Plaques from Alzheimer’s Diseased Brains by MALDI-TOF MS with MS/MS Andrea Renee Kelley, George Perry, and Stephan B. H. Bach ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.7b00445 • Publication Date (Web): 04 Jan 2018 Downloaded from http://pubs.acs.org on January 5, 2018

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Characterization of Proteins Present in Isolated Senile Plaques from Alzheimer’s Diseased Brains by MALDI-TOF MS with MS/MS Corresponding Author: Andrea R. Kelley: Department of Chemistry, University of Texas at San Antonio Address: One UTSA Circle, San Antonio, TX. 78249 Phone: 425-218-9206 Email: [email protected] Co-Authors: George Perry: College of Sciences, University of Texas at San Antonio Address: One UTSA Circle, San Antonio, TX. 78249 Phone: 210-458-4450 Email: [email protected] Stephan B.H. Bach: Department of Chemistry, University of Texas at San Antonio Address: One UTSA Circle, San Antonio, TX. 78249 Phone: 210-458-6896 Email: [email protected]

Abstract: The increase of insoluble senile plaques in the brain is a primary hallmark of Alzheimer’s disease. The usefulness of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with tandem MS for the characterization of senile plaques from AD brains and the relevance of the components identified to furthering AD research using MS is discussed. 33 components were reproducibly observed within tryptic aliquots of senile plaques from two different AD brains after sample preparation optimization. Additionally, this is one of the first accounts of LIFT being utilized for the direct sequencing of peptides from isolated senile plaques. While many of the species observed co-isolated within senile plaques have been linked to AD etiology, if only speculatively, this is the first instance that many of them have been demonstrated to be a part of the plaques themselves. This work is the first step in determining the potential roles that the species may have in the aggregation or proliferation of the plaques.

Keywords: MALDI, mass spectrometry, Alzheimer’s disease, senile plaque 1 ACS Paragon Plus Environment

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Alzheimer’s disease (AD) is a progressive neurodegenerative disease marked by irreversible neuronal death, resulting in impaired cognitive function.1 AD pathology is debated and there is still much to be discovered in order to determine the mechanisms of onset and progression. The AD brain is marked by lesions in the brain called senile plaques which are thought to primarily be made up of amyloid-beta peptides, which are derived from the amyloidbeta protein precursor (AβPP), and neurofibrillary tau tangles. 1-2 Senile plaques, extracellular aggregates and accumulations of various proteins and peptides, were first described and linked to dementia in the late 1800s,3 before the discovery of AD. Under cross-polarized light after staining with Congo red, amyloid-beta exhibits green birefringence. While this is helpful in confirming the presence of amyloid-beta in a plaque sample, it allows for little information to be gathered about the other components of the plaque. Fluorescent tags and antibodies can be unspecific and not particularly helpful when unknown components are to be identified. Therefore, while identifying amyloid-beta by microscopy is relatively simple, other, more complete analytical techniques are required to determine the full spectrum of proteins in a complex senile plaque. However, because amyloid-beta peptides are observed to be a part of senile plaques using Congo red, and senile plaques are shown to proliferate rapidly in AD brains, Aβ has been a primary target for AD drug discovery. In fact, in a 2006 study by Söderberg et al., intact plaque cores from human AD brain samples were analyzed by LC-MS/MS and Aβ was found to be the only protein present within the plaques. This indicated the possibility that no other proteins copolymerize with Aβ in plaque cores.4 It is argued that, even though Aβ-centric drugs have not been shown to reverse or stop disease progression in humans, the alteration of the disease state described in the transgenic mouse models is reason for continued focus.5 This reasoning is flawed. The need for transgenic mice for AD research, as opposed to unmodified animals, stems from the basis that mice do not exhibit senile-plaque-like buildups without intervention by gene mutation.5 As such, the drugs that are seemingly “working” are only removing something that was put in place by outside intervention and not by naturally-occurring biological processes. This further demonstrates that current mouse models, made to exhibit increased accumulation of Aβ in the brain, are lacking a fundamental means of comparison to their human counterparts. Hence, the precise analysis of human biological samples at a molecular level has gained critical importance. While human brain samples, particularly those tracking the progression of the disease in singular patients are nearly impossible to come by, the analysis of samples from deceased patients allows for the determination of new focal points for AD research. It is therefore of fundamental importance to establish a complete molecular profile of the plaques. This may eventually assist in determining new drug or therapeutic targets.2 Proteomic characterization of senile plaque composition, after isolation by laser-microdissection, has been accomplished, primarily utilizing 2D-gel electrophoresis and liquidchromatography with tandem MS (LC-MS).4, 6-7 The results of the studies have presented hundreds of potential co-localized proteins, including dynein and alpha 1 propeptides,6 which we have confirmed in the work presented herein. However, because of the need for an increased understanding of the potential roles these proteins play in the proliferation of plaques, we must continue to utilize novel techniques to further elucidate the composition of senile plaques. The information gained from the analysis of plaques on indium-tin-oxide (ITO)-coated glass slides with the addition of optimized washes, mimics the analysis parameters typical of a MALDI imaging experiment. Therefore, the ability to not only identify the components of a complex deposit, such as senile plaques has potential in the streamlining of MALDI imaging experiments where the species determined to be present by LIFT (the inherent MS/MS technology to the 2 ACS Paragon Plus Environment

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Bruker UltrafleXtreme mass spectrometer), can be directly localized on intact tissue sections and compared to normal brain proteome. The senile plaque extracts for LC-MS/MS analysis are typically isolated by laser capture microdissection.4, 6-7 This technique is useful in extracting the small 10-50 µm-diameter deposits. It is not uncommon for some surrounding material to be extracted, also. The senile plaques described herein, were isolated by a variation on the method developed by Selkoe et al. in 1989.8 The published method describes the isolation of purified amyloid cores of senile plaques. With the omission of fluorescence-activated cell-sorting (FAC) (meant to isolate the amyloid core), the cores, and surrounding plaque structure are left intact and the components, other than amyloid-beta, present within the plaque can be observed. The sucrose density gradient employed for separation yields interfaces primarily composed of relatively pure senile plaques. Other neocortical components, such as NFTs, may make their way through the gradient, lessening the purity of the plaque samples. However, by microscopic analysis (Figure S1), optimized sample preparation techniques and spot-to-spot averaging by MALDI analysis, the spectra collected can be said to be representative of senile plaques. Proteomic studies on isolated plaques from AD brains, meant to qualify, and relatively quantify, their components are few and far between. Even rarer, are mass spectrometric surveys of plaque samples. Our goal was to utilize MALDI-TOF MS and MS/MS to identify a list of molecular targets in isolated senile plaques from the brains of two AD brains. From this work, we were able to confirm the existence of 33 protein fragments after enzymatic digest, some of which have been identified within senile plaques before (confirming our methods), and some that have not. Due to some speculative relationships regarding AD etiology and pathogenesis, it is important to develop methods for isolated senile plaque analysis that will be useful in resolving the nature of the interconnections on a molecular level. The interdependency of the isolation procedure, sample preparation and mode of analysis are discussed herein. Results and Discussion: The present study examined tryptic aliquots of senile plaque samples from two AD brains by MALDI-TOF MS and MS/MS. All data collection was performed on tryptic digests of isolated plaques. The solvents employed in the isolation process and storage of the plaques make it difficult to produce meaningful spectra or MS/MS results due to ion suppression. To address the salts, a water wash is used to remove excess salts and hydrophilic species that may act as a means for ion suppression. A subsequent EtOH wash is used to remove excess water and insure that the plaque samples are predominantly pure before analysis. Senile plaques are hydrophobic and viscous on the glass slides used for MALDI-TOF analysis so no sample was lost during the wash steps. The removal of the salts or buffers either before or after digestion produced spectra with the same signals, proving that the salts and impurities did not affect the overall digestion of the proteins. The component identifications were pulled from two different sources. The most abundant species in the MALDI-TOF MS spectra were further examined by MS/MS (signal-tonoise greater than 4, resolution greater than 4000) for the same sample. Primary parent/daughter mass spectra were characterized using the MASCOT database (version listed in the methods section). Peptide sequences are produced for each species in this manner. The peptide sequence was then interpreted using the NCBI Blast search. This search produced all other identifications. Some of the most abundant proteins were shown to have been already linked to AD, if only speculatively, by other works.2, 9-18 3 ACS Paragon Plus Environment

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A primary consideration when utilizing MALDI-TOF MS as the analytical method for complex biological samples comes from the sample preparation methods. Our goal was to observe m/z signals representative of as many components as possible. The ability to develop representative spectra of components of senile plaques is imperative in determining the role of those components in the AD brain. The benefit of analysis by MALDI-TOF MS on a glass slide is that multiple aliquots of tryptic digests can be analyzed in succession and MS/MS experiments can be completed subsequently on the same sample. Because we were able to identify a greater number of proteins in positive ion mode, the negative ion mode results were omitted. Additionally, the matrix material used, HCCA, is more applicable to positive ion mode analysis due to the ionization processes of the matrix on the sample. The MS/MS results shown in Table 1 are the identifications representative of the most abundant peaks in the tryptic aliquots of the senile plaque samples. Peaks were observed at m/z values higher than 3500 and lower than 500. Identifications for those peaks with m/z values greater than 3500 were not resolved due to the energy of the LIFT fragmentation process. The energy required to isolate and fragment species with high molecular weights is too high to be accomplished using LIFT. Peaks with m/z less than 500 were also omitted due to the potential of matrix interference. Additionally, parent peaks at low sign-to-noise (below 4) and resolution (below 4000) were omitted from MS/MS experiments due to inability to isolate.

Table 1: Sequence identifications from tryptic aliquot of senile plaque sample from Case 1 by MS/MS. Identifications were reproduced for both cases described in Table 3. 4 ACS Paragon Plus Environment

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Parent Mass (M+H)+ (Da) 1267.7

HLSQPQLSSDR

1359.7

HIPGLIHNMTAR

1379.8

CASRFDSSSTEAFFGQG

1459.7

VKGILVDIGLDSCK

1546.8

LSMLSQEIQTLKR

1562.8

TEEEEEDLPSGPSSG

1584.7

QLPYFIRPAVPKR

1586.8 1720.8

KALLLMGSNEIEIR GPGPKGPVGTVSEAQLAR

1795.5

ASGYTFNDYCITWVR

1832.8 1848.8

NAVMGQPTEGALMALAMK LEEAVGATSTQIEMNKK

1961.8

GPQYCSGGSCYGGLDVWGR

1964.8

AALAPYNWPVWLGVHDR

1996.8 2105.8 2120.8 2208.8 2215.9 2383.9

ATNLQRVSYLVFDEADR ERDEGSYYCACDGVLGDTHWD AGLTVGWDLVLQTDFDFHS GAGDELHEPQACSLLIGRSQK MEPFIHVSPLISLRLKESNH ERDEGSYYCACDTLLGDTRNSWD

2458.1

LWEVPELACACDRLGARVLTDKL

2470.3

GDEELDSLIKATIAGGGVIPHIHK

2513.9

GLEWVAVIWYDGSIKNYADSVK

2546.5

SYYGSWYQQKPGQAPLLVIYGK

2674.7

AGLGRAAMPSDFISLLSADLDLESPK

2690.8

HSPQCCVEDGPESIDSIIDMDAVCK

2705.9 2728.0 2886.7 3119.1 3199.8

EELEGQEGSQSTRETPSEEEQAQK PGGNTLSLTCAVYGGSLSDSSWTWIR LDVLLEQTLLTAYWNVSRGLFEQHK GNPPDLSTEVTAAMTFPREFHLCVFPSR RKDVLVVPLGWLPLSGRAHSTSTSSMSSSGSRTPPLG

3215.9

ATLVCLATGFYPDHVELSWWVNGKEVHSG

3418.9

MGPKDHMVTSSFCCQSDGCNSAFLSACFLTCK

Peptide Sequence

Protein Hit hCG2039966, isoform CRA_a, partial Extracellular matrix protein 1 isoform 3 precursor T-cell receptor beta chain V13S2 activity-dependent neuroprotective homeobox protein 2 Fasciculation and elongation protein zeta-2 isoform 2 Chain A, Solution Structure Of The Rgs Domain Of Human Regulator Of G-Protein Signaling 10 Polymerase (RNA) III (DNA directed) polypeptide G (32kD) like, isoform CRA_b, partial Alpha 1 (I) chain propeptide, partial Predicted myoferlin isoform X1 Anti-tetanus toxoid immunoglobulin heavy chain variable region, partial KIAA0703 protein, partial Unnamed protein product Immunoglobulin heavy chain variable region, partial C-type lectin domain family 11 member A precursor ATP-dependent RNA helicase DDX42 T cell receptor delta chain Alternative protein SNAP29 hCG2017366, partial hCG2045763 T cell receptor delta chain V gamma 9JP/V delta 2DJ1 T cell receptor Cytotoxic clone SC9, rearranged junctional region Histone H2A.V isoform 5 Immunoglobulin heavy chain variable region, partial Immunoglobulin lambda variable region, partial Nuclear factor of activated T-cells 5 isoform c Predicted: pyroglutamyl-peptidase 1 isoform X3 Uncharacterized protein C15orf52 Immunoglobulin heavy chain, partial dynein heavy chain 6, axonemal hCG1644121, isoform CRA_b, partial ABO glycosyltransferase, partial T-cell receptor beta chain variable region, partial hCG39353

GenBank or NCBI Ref. EAX00293.1 NP_001189787.1 AAM12524.1 NP_055728.1 NP_001036013.1 PDB: 2DLR_A

EAW71413.1 AAA51995.1 XP_005269750.1 AEQ74054.1 BAA31678.2 CAA27380.1 AFN10783.1 NP_002966.1 NP_031398.2 AAC02455.1 CCQ43279.1 EAW74973.1 EAX05811.1 AAC02497.1 AAB26543.1 NP_958925.1 BAI52050.1 CAB56048.1 NP_006590.1 XP_006722846.1 NP_997263.2 CAB76519.1 NP_001361.1 EAW85822.1 AAF13183.1 ANO56040.1 EAW57204.1

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Figure 1: Representative reflectron positive MALDI-TOF mass spectra of a tryptic digested isolated SP sample. Figure 1 shows a full mass spectra of a senile sample from an AD brain after enzymatic digestion with trypsin. This spectrum was reproducible for two different AD brains. All of the peaks of a resolution greater than 4000 and signal-to-noise greater than 4 were fragmented and sequenced with tandem MS. Figure 2 represents just a few of the MS/MS spectra gathered. Although not depicted in Table 1, amyloid-beta and tau were also identified in both the undigested and digested senile plaque samples. Identification of amyloid-beta and tau in the digested samples was determined using previously observed fragments of digested synthetic amyloid-beta (1-42) and recombinant human tau (144) by laser-induced in-source decay (ISD).19

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Figure 2: Representative MS/MS spectra of top) m/z 1459; identified as activity-dependent neuroprotective homeobox Protein 2 and bottom) m/z 1586; identified as alpha 1 (I) chain propeptide, partial with major a, b, and/or y ion fragments utilized for identification. Unlabeled signals represent other laser-induced fragments present not used for sequence identification. Table 2 outlines the masses of the major a, b, and/or y fragments utilized by the MS/MS software and databases to provide an identification. MS/MS fragments with signal-to-noise below 3 were omitted from the search parameters. Additional fragment ions were used by the software as a means of identification. But, only fragments with certain sequences are listed in the table. The 6 peptides outlined in Table 1 that do not have identified ions in Table 2, were identified by overall amino acid sequence coverage by the MASCOT database search. MS/MS was still utilized for these identifications, however a, b, and y-ions are not listed.

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Table 2: Parent and MS/MS fragment ion masses identified from Case 1 trpytic aliquot described in Table 3. Results were reproduced with Case 2. Parent Mass (M+H)+ (Da) 1267.7 1359.7 1459.7 1546.8 1562.8 1584.7 1586.8 1720.8 1795.5 1832.8 1848.8 1961.8 1964.8 1996.8 2120.8 2208.8 2470.3 2513.9 2546.5 2674.7 2690.8 2705.9 2728.0 2886.7 3119.1 3215.9 3418.9

Fragment Masses Observed (Da) and Identified a,b,y Ion Fragments (where applicable) 1017.5 (y9), 1130.6 (y10) 175.1 (y1), 1109.6 (y10), 1222.7 (y11) 285.2 (b3), 398.3 (b4), 511.4 (b5), 610.4 (b6), 725.5 (b7), 1210.7 (b12) 173.1 (a2), 175.1 (y1), 303.2 (y2), 304.2 (a3) 1313.5 (b12), 1487.6 (b14) 175.1 (y1), 400.3 (y3), 1343.8 (y11), 1456.9 (y12) 172.1 (a2), 175.1 (y1), 285.2 (a3), 398.3 (a4), 417.2 (y3), 511.4 (a5), 1458.8 (y13) 155.1 (b2), 437.3 (b5), 494.3 (b6), 1475.8 (b16) 175.1 (y1), 1637.7 (y13) 533.3 (y5), 601.3 (b6), 698.3 (b7), 799.4 (b8), 905.5 (y9), 928.4 (b9), 985.4 (b10), 1056.5 (b11), 1169.6 (b12), 1718.9 (y17) 642.2 (a7), 931.5 (a10), 1059.5 (a11), 1172.6 (a12) 175.1 (y1), 1807.8 (y17), 1904.8 (y18) 1709.9 (y14), 1822.9 (y15) 175.1 (y1), 361.2 (y3), 490.2 (y4) 1622.7 (y13), 1992.9 (y17) 2081.0 (y19), 2152.1 (y20) 284.2 (y2), 397.3 (y3), 744.5 (y6), 1085.6 (y11), 2298.3 (y22) 796.4 (y7), 1037.6 (y9), 2343.2 (y20) 367.2 (y3), 902.6 (y8), 1255.7 (y12), 1511.9 (y14), 2459.3 (y21) 2433.2 (y23), 2546.3 (y24) 781.3 (y7), 2554.1 (y24) 2148.9 (y19), 2448.1 (y22), 2577.2 (y23) 1394.7 (y12), 2574.2 (y24) 783.5 (a7), 811.5 (b7), 1025.6 (b9), 1110.7 (a10) 58.0 (b1), 338.2 (a4), 481.2 (b5), 566.3 (a6), 681.3 (b7) 286.2 (b3), 3140.5 (b28) 611.3 (y5), 872.4 (y8), 3133.3 (y29)

The identifications presented require some discussion as they relate to AD pathogenesis. T-cell receptor chains have been linked to the inflammation response in AD brains.12, 14, 16 T-cells enter the brain through the blood-brain-barrier (BBB) to survey the brain’s metabolic and functional milieu.16 It is well documented that response to inflammation and damage to the BBB plays a large role in AD pathology.20 It is speculated that due to this change or damage, T-cells are able to enter the brains of those with AD much more rapidly and readily than in healthy brains. Although, contrary to our findings, T-cells are thought to be rare in senile plaques.12, 14, 16 Another identified species of particular interest is cytoplasmic dynein, which is the molecular motor of retrograde axonal transport.10-11, 21 Dynein is expressed in most tissues and there are several potential consequences of dynein dysfunction, particularly in the brain. Decreased retrograde transport means lowered organelle transport to cell bodies.10-11 More important to AD pathology, however, is the impact that dynein dysfunction would have on neuronal physiology. Much like with the correlation of T-cells to AD pathology, dynein has been primarily linked to axonal defects and inflammation.10-11, 20 Because of dynein’s role in cell survival, division, and differentiation, an impairment in dynein function would be a plausible cause of neuronal death associated with AD.10-11 The 2004 study by Liao et al. described 26 proteins that were enriched in SP samples including dynein.6 Apart from this work, however, 8 ACS Paragon Plus Environment

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most studies, to date, on the role of dynein in AD have shown indirect relationships between the two. There are a few other species identified that have been previously linked to AD. However, there has been little information published regarding their roles with or within senile plaques before this study. Myoferlin and dysferlin are transmembrane proteins that are expressed in muscle.22 While these proteins have been linked to muscular impairments, such as muscular dystrophy, dysferlin has also been found to be expressed in neuronal tissue and is said to accumulate in AD brains and senile plaques.22 It is reported that dysferlin neuritic pathology occurs in conjunction with tau pathology.22 Myoferlin is very similar to dysferlin in amino acid sequence but has not been linked to senile plaques in AD before now. It has been related to muscle regeneration and repair, however, indicating that the protein could be attempting to repair muscle degradation in AD brains.22 Therefore, the identification here, opens new avenues of possible AD pathogenesis research related to ferlins. Acitivty-dependent neuroprotective homeobox protein 2 (ADNP) has been linked to AD as a potential biomarker for the disease.13, 18 Previous studies have shown ADNP to be downregulated in AD serum samples.13, 18 NAP is a fragment of ADNP which has a neuroprotective effect and thus, it would be logical to assume that ADNP would be a lesser component of the AD body.18 Currently, ADNP is one of very few proteins that have been shown to be downregulated in blood from AD patients.13 A 2015 study linked a decrease in ADNP in blood serum to an increase in the number of senile plaques in the brain and hyperphosphorylation of tau.13, 18 To our knowledge however, until the present study, the identification of ADNP within senile plaques has not been reported. The identification of extracellular matrix (ECM) proteins co-localized with some of the other proteins in the senile plaques confirm previous reports regarding ECM proteins in senile plaques and AD.9, 15, 17, 23 ECM proteins are found in all multicellular organisms and are produced by a variety of cell types. They consist of collagens, noncollagenous proteins, proteoglycans and other glycoproteins.15, 17 ECM proteins act as molecular sieves, in a sense, and have important roles in developmental regulation, tissue homeostasis, cell differentiation, neuronal plasticity etc.9, 23 Because of the multiple binding sites associated with ECM proteins, their architectures may act in a variety of ways dependent on the types of binding.9, 23 It has been reported that the association of amyloid-beta with ECM proteins may be a cause for the progression of AD.9, 23 Additionally, pyroglutamly peptidase, lectin and alpha 1 chain propeptide (collagen)6, 24-25 have all been shown to play a potential role in the progression of AD and their identifications herein indicate their involvement in senile plaque structure. These identifications will allow for the continued work relating structural information to functional motifs at a molecular level. A majority of the proteins identified by MALDI-TOF MS with tandem MS and the sample preparations herein, while linked to AD, have not been identified within senile plaques in AD brains, previously. These identifications open new doors for research into the modes of aggregation of senile plaques and the components important to AD etiology. Conclusions: This research has enabled the identification of many previously unidentified proteins in isolated senile plaques, as well as confirmation of expression of some already identified. Many of the proteins identified had been previously linked to AD in one way or another, however, very few were demonstrated to be localized within senile plaques. This work is the first step in 9 ACS Paragon Plus Environment

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determining the potential roles that the proteins may have in the aggregation or proliferation of the plaques. In addition, this is one of the first studies to utilize MS/MS technology inherent to MALDI-TOF for the identification of proteins in AD plaques, without a focus on amyloid-beta. The sample preparation methods described herein and the use of MALDI-TOF MS with MS/MS have proven to be a viable means of senile plaque analysis. This research will allow for the newly directed molecular focus on the involvement of the proteins identified within the plaques in AD pathogenesis, as well as SP aggregation. This data will act as the basis of future studies for the localization of compounds presented in intact tissue sections via MALDI IMS and the relative abundance of each identification in relation to one another, within the plaque samples. Methods: Reagents: Ethanol (200 proof, CAS# 64-17-5), trifluoroacetic acid (0.1% in H2O, CAS# 76-05-1), trypsin protease (MS grade, CAS# 9068-82-0) and acetic acid (ACS grade, CAS# 6419-7) were purchased from Thermo Fisher Scientific, α-cyano-4-hydroxycinnamic acid (Ultrapure, MS grade, CAS# 28166-41-8) was purchased from Protea, acetonitrile (CAS# 75-058) and ammonium bicarbonate (CAS# 1066-33-7) was purchased from Sigma Aldrich. SDS, Tris buffer, NaCl and NaN3 were obtained from Case Western Reserve University. Senile plaque isolation: Senile plaques were isolated by a variation on the Selkoe method developed at Case Western Reserve University.8 Cortex rich in senile plaques (grey matter) of 2 AD brains (sample characteristics in Table 3) was separated from other brain matter which was subsequently minced and dissolved in 2% SDS and 50 mM Tris at pH 7.6. Samples were homogenized, heated to boiling (2 hours), sieved for particle size (110 µm nylon mesh) separation and centrifuged at 300g for 30 minutes. Resulting pellets were washed in 0.1% SDS, 150 mM NaCl, and 0.02% NaN3. Samples were once again spun at 300g for 10 minutes, homogenized and sieved (35 µm nylon mesh). Washed pellets were loaded onto a sucrose (1% SDS, 50 mM Tris buffer) gradient. Sucrose was prepared at concentrations of 1.2, 1.4, 1.6, and 1.8 M in 1% SDS and 50 mM Tris buffer. Gradients were spun at 72000g for 60 minutes. Interfaces were collected and diluted with 5 volumes of 0.1% SDS buffer before once again being spun down at 300g for 30 minutes.8 All layers of the gradient were kept. Samples were spotted onto glass slides and stained with Congo red to confirm plaque density (four representative images are displayed in Figure S1). Table 3: Sample characteristics. Case

Identifier

Sex

Age (years)

Braak score

1 2

A10-152 A08-171

M F

78 85

VI V/VI

Post-mortem interval (hours) 3 7

Sample preparation for MALDI and LIFT analysis: 10 µL of senile plaque were incubated with 10 µL of trypsin at 37 °C overnight. Trypsin was prepared by dissolving 20 µg of MS-grade trypsin solid in 20 µL of 50 mM acetic acid and 100 µL of 100 mM ammonium bicarbonate to a concentration of 0.01 mg/mL with a pH of 8.2 for optimal activity. The incubated sample was spotted onto an ITO-coated glass slide (Delta Technologies, Limited, Loveland, CO. Part# CB-50IN-5111) (2 spots, 5 µL each). The sample was dried under vacuum. 10 ACS Paragon Plus Environment

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The slide was washed in nanopure H2O and EtOH respectively for 2 minutes each in order to facilitate removal of salts from the sample. Petri dishes were filled with the solvents and the slides with the digested plaque aliquot spots were submerged at room temperature for the described amount of time. Each sample spot was topped with 5 µL of α-Cyano-4hydroxycinnamic acid (HCCA) (MALDI matrix) (10 mg/mL). The slide was dried under vacuum. There is a tendency for polar matrices to not co-crystallize as sufficiently with hydrophobic deposits, such as the senile plaques. This inhomogeneity present from hand-spotted samples can be compensated by increased laser power and spot averaging to make sure that the peaks have adequate signal-to-noise for observation and identification. Mass spectrometry: MALDI-TOF MS was performed using an UltrafleXtreme MALDITOF/TOF mass spectrometer (Bruker Daltonik; Bremen, Germany). The mass spectrometer was calibrated with a standard peptide mixture (Bruker Daltonik) using HCCA matrix before and after sample spectra were acquired. Spectra were collected over a m/z range of 900-5000 in reflectron positive mode. The laser rate was set to 1 kHz with 500 laser shots per spectra. The laser power was adjusted to just above the ionization threshold of the sample. MS/MS analysis was performed on each species resolved in the full reflectron TOF spectra. Peptides, and their corresponding protein identifications, listed in Table 5.2 were identified by fragment ions generated from MS/MS experiments. Multiple spots from each sample were spotted on the glass slides in order to make sure results were reproducible within the same sample. The most abundant species by MS were subsequently examined by MS/MS on the same sample. Data analysis/statistical analysis: A mass list of parent peaks was generated using FlexAnalysis from the reflectron TOF spectra of the senile plaque samples. Lower limit signalto-noise (5) and resolution (4000) were used for both full spectrum analysis and MS/MS fragment peak picking. Each of the sets of fragments from the selected parent ions were searched using MASCOT (10 CPU license for Mascot Server 2.4 on Linux) and NCBI Blast databases. Microscopy images were used for the calculation of the number of plaques in a 10 µL aliquot of sample (~600 plaques per 10 µL); our samples were therefore oversaturated with senile plaques. Experiments were completed with plaque samples from each of the two different AD brains. The peptides listed in Table 5.2 were observed in each sample aliquot. Database search peptide mass tolerance was set to +/- 150 ppm, fragment mass tolerance was set to +/- 2 Da, and up to 2 missed cleavages were allowed. These are typical settings for database searches using LIFT. Statistical analysis inherent to the MS/MS database software search ensured that only hits with significant likelihood of positive identification were reported. Supporting Information: Optical images of senile plaque samples stained with Congo red Author Information: Corresponding Author: (A.R.K.) E-mail: [email protected] Phone: (210)458-7055 Author Contributions: 11 ACS Paragon Plus Environment

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A.R.K. was responsible for carrying out all experiments (including plaque isolation), compiling data, and assembling the manuscript. G.P. was responsible for supervision and guidance regarding the direction of the project, information regarding AD and editing of/additions to the manuscript. S.B.H.B provided supervision and guidance as well as final editing and additions to the manuscript. Funding Sources: The authors gratefully acknowledge the National Institute on Minority Health and Health Disparities (G12MD007591) and the National Science Foundation under CHE-1126708. Work was also supported through the Semmes Foundation (Kelley and Perry). Conflict of Interest: The authors declare no competing financial interest. Acknowledgments: Senile plaque samples were isolated by Andrea R. Kelley at Case Western Reserve University in Dr. Xiongwei Zhu’s lab. References 1. Castellani, R. J., Lee, H. G., Zhu, X., Perry, G., Smith, M. A. (2008) Alzheimer disease pathology as a host response. J. Neuropathol. Exp. Neurol. 67, 523-531. 2. Gozel, Y. M., Peng, J., Lah, J. J., Levey, A. I. (2006) Proteomics of senile plaques in Alzheimer's disease. In Proteomics of Neurgodegenerative Disease, (Montine, T. J., Ed.), pp 6581, Trivandum: Kerala, India. 3. Beljahow, S. (1889) Pathological changed in the brain in dementia senilis. J. Mental Sci. 35, 261-262. 4. Söderberg, L., Bogdanovic, N., Axelsson, B., Winblad, B., Näslund, J., Tjernberg, L. O. (2006) Analysis of single Alzheimer solid plaque cores by laser capture microscopy and nanoelectrospray/tandem mass spectrometry. Biochem. 45, 9849-9856. 5. Hardy, J., Selkoe, D. J. (2002) The amyloid hypothesis of Alzheimer's disease progress and problems on the road to therapeutics. Science 297, 353-356. 6. Liao, L., Cheng, D., Wang, J., Duong, D. M., Losik, T. G., Gearing, M., Rees, H. D., Lah, J. J., Levey, A. I., Peng, J. (2004) Proteomic characterization of postmortem amyloid plaques isolated by laser capture microdissection. J. Biol. Chem. 279, 37061-37068. 7. Rüfenacht, P., Güntert, A., Bohrmann, B., Ducret, A., Döbeli, H. (2005) Quantification of the A beta peptide in Alzheimer's plaques by laser dissection microscopy combined with mass spectrometry. J. Mass Spectrom. 40, 193-201. 8. Selkoe, D. J., Abraham, C. R., Podlisny, M. B., Duffy, L. K. (1986) Isolation of Lowmolecular-weight proteins from Amyloid plaque fibers in Alzheimer's disease. J. Neurochem. 46, 1820-1834. 12 ACS Paragon Plus Environment

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9. Brandan, E., Inestrosa, N. C. (1993) Extracellular matrix components and amyloid in neuritic plaques of Alzheimer's disease. Gen. Pharmac. 24, 1063-1068. 10. Chen, X. J., Xu, H., Cooper, H. M., Liu, Y. (2014) Cytoplasmic dynein: a key player in neurodegenerative and neurodevelopmental diseases. Sci. China Life Sci. 57, 372-377. 11. Eschbach, J., Dupuis, L., Cytoplasmic dynein in neurodegeneration. Pharmacol. Ther. 130 (3), 348-363. 12. Fisher, Y., Nemirovsky, A., Baron, R., Monsonego, A. (2010) T cells specifically targeted to amyloid plaques enhance plaque clearance in a mouse model of Alzheimer's disease. PloS one 5, e10830. 13. Malishkevich, A., Amram, N., Hacohen-Kleiman, G., Magen, I., Giladi, E., Gozes, I. (2015) Activity-dependent neuroprotective protein (ADNP) exhibits striking sexual dichotomy impacting on autistic and Alzheimer's pathologies. Transl. Psychiatry 5, e501. 14. Monsonego, A., Zota, V., Karni, A., Krieger, J. I., Bar-Or, A., Bitan, G., Budson, A. E., Sperling, R., Selkoe, D. J., Weiner, H. L. (2003) Increased T cell reactivity to amyloid β protein in older humans and patients with Alzheimer disease. J. Clin. Investig. 112, 415-422. 15. Sethi, M. K., Zaia, J. (2017) Extracellular matrix proteomics in schizophrenia and Alzheimer's disease. Anal. Bioanal. Chem. 409, 379-394. 16. Town, T., Tan, J., Flavell, R. A., Mullan, M. (2005) T-cells in Alzheimer's disease. NeuroMol. Med. 7, 255-264. 17. Végh, M. J., Heldring, C. M., Kamphuis, W., Hijazi, S., Timmerman, A. J., Li, K. W., van Nierop, P., Mansvelder, H. D., Hol, E. M., Smit, A. B., van Kesteren, R. E. (2014) Reducing hippocampal extracellular matrix reverses early memory deficits in a mouse model of Alzheimer’s disease. Acta. Neuropathol. Commun. 2. 18. Yang, M. H., Yang, Y. H., Lu, C. Y., Jong, S. B., Chen, L. J., Lin, Y. F., Wu, S. J., Chu, P. Y., Chung, T. W., Tyan, Y. C. (2012) Activity-dependent neuroprotector homeobox protein: A candidate protein identified in serum as diagnostic biomarker for Alzheimer's disease. J. Proteomics 75, 3617-3629. 19. Kelley, A. R., Perry, G., Castellani, R. J., Bach, S. B. (2016) Laser-induced in-source decay applied to the determination of amyloid-beta in Alzheimer's brains. ACS Chem. Neurosci. 7, 261-268. 20. Finch, C. E., Inflammation and Oxidation in Aging and Chronic Diseases. (2007) In The Biology of Human Longevity, pp 1-112, Academic Press, New York. 21. Dupuis, L. (2014) Mitochondrial quality control in neurodegenerative diseases. Biochimie 100, 177-183. 22. Galvin, J. E., Palamand, D., Strider, J., Milone, M., Pestronk, A. (2006) The muscle protein dysferlin accumulates in the Alzheimer brain. Acta. Neuropathol. 112, 665-71. 23. Lepelletier, F. X., Mann, D. M., Robinson, A. C., Pinteaux, E., Boutin, H. (2017) Early changes in extracellular matrix in Alzheimer's disease. Neuropathol. Appl. Neurobiol. 43, 167182. 24. Forsell, C., Bjork, B. F., Lilius, L., Axelman, K., Fabre, S. F., Fratiglioni, L., Winblad, B., Graff, C. (2010) Genetic association to the amyloid plaque associated protein gene COL25A1 in Alzheimer's disease. Neurobiol. Aging 31, 409-415. 25. Kakuyama, H., Söderberg, L., Horigome, K., Winblad, B., Dahlqvist, C., Näslund, J., Tjernberg, L. O. (2005) CLAC binds to aggregated abeta and abeta fragments, and attenuates fibril elongation. J. Biochem. 44, 15602-15609.

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Graphical abstract 80x43mm (150 x 150 DPI)

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