Proteomics analysis reveals novel components in the detergent-insoluble subproteome in Alzheimer’s disease

Case Material

Post-mortem human brain tissues corresponding to diagnoses of AD, frontotemporal lobar degeneration with ubiquitinated inclusions (FTLD-U), and unaffected control were obtained from the Alzheimer’s Disease Research Center (ADRC) and Center for Neurodegenerative Disease (CND) Brain Bank at Emory University School of Medicine. Neuropathological assessment of AD was made according to the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) criteria³¹, as well as the National Institute on Aging (NIA)-Reagan³² criteria. The diagnosis of FTLD-U was based on consensus criteria^{33, 34}, with all cases exhibiting small, ubiquitin-positive, tau- and α-synuclein-negative neuronal cytoplasmic inclusions and immunoreactive dystrophic neurites in the hippocampal dentate gyrus or frontotemporal cortex. Additionally, TDP-43 immunoreactivity was histochemically confirmed in all FTLD-U cases. Finally, control cases had neither a clinical history nor a neuropathologic diagnosis of neurologic disease.

For proteomic analysis, small blocks of fresh frozen frontal cortex were obtained from 10 cases each of AD, FTLD-U, and control cases. Selected cases were matched according to sex, post-mortem interval (PMI), and age at death (see Tables 1 and S1 for detailed demographic information and Table 2 for detailed neuropathologic analysis of included AD cases). Immunohistochemical and biochemical validation of identified proteins was conducted on aldehyde-fixed and frozen brain tissues from additional cases. These included 9 AD, 2 FTLD-U, and 3 control cases for which neocortex and hippocampus was examined.

Antibodies

Primary antibodies used in these studies were Tau2 (1:5000, mouse monoclonal; Chemicon International, Temecula CA), ApoE (1:500, goat polyclonal; Calbiochem, Darmstadt, Germany), ankyrin B (1:200, mouse monoclonal; Santa Cruz Biotechnology, Santa Cruz CA), serine protease 15 (1:200, rabbit polyclonal; Atlas Antibodies, Stockholm, Sweden), YWHAH (0.5 μg/mL, rabbit polyclonal; Aviva Antibody Corporation; San Diego, CA), and ATP6V0D1 (1:200, mouse monoclonal; Novus Biologicals, Littleton CO). The antibody dilutions noted above reflect prior dilution of each antibody (1:1) with glycerol.

Sequential Biochemical Fractionation

Sequential extractions were performed as described³⁰ with slight modification (Figure 1). Briefly, post-mortem frontal cortex was extracted at 5mL/g (volume/weight) with ice-cold low salt (LS) buffer (10mM Tris, pH 7.5, 5mM EDTA, 1mM DTT, 10% sucrose, 10mM b-glycerophosphate, 10mM sodium orthovanadate, 10mM tetrasodium pyrophosphate, 50mM sodium fluoride, 1 × Roche complete protease inhibitor cocktail). Protein concentration of the resulting homogenate was determined by the bicinchoninic acid (BCA) method (Pierce, Rockford, IL) and used to equally pool ten cases each of AD, FTLD-U, and unaffected controls by diagnosis (3mg total protein per case). Notably, the FTLD-U pool and subsequent extraction was duplicated to discern experimental variance. The four pools were centrifuged at 25,000 × g for 30 minutes at 4°C and then washed with additional LS buffer. The resultant pellets were sequentially extracted with buffers of increasing stringency including Triton X-100 (TX) buffer (LS buffer + 1% Triton X-100, 0.5M NaCl), myelin floatation (MF) buffer (LS buffer with 30% sucrose + 1 % Triton X-100, 0.5M NaCl), and sarkosyl (SK) buffer (LS buffer + 1% N-Lauroyl-sarcosine, 0.5M NaCl). Specifically, each pooled sample was extracted with TX buffer and spun at 180,000 × g for 30 minutes at 4°C to generate a Triton-insoluble fraction. Following two washes with TX buffer, this fraction was incubated with MF buffer and centrifuged at 180,000 × g as noted above. Pellets were then sonicated briefly, incubated in SK buffer for 30 minutes at room temperature, and centrifuged at 180,000 × g for 30 minutes at 22°C. Two additional SK buffer washes were followed by extraction of the sarkosyl-insoluble fraction with urea buffer (30mM Tris, pH 8.5, 7M urea, 2M thiourea, 1% SDS), a brief sonication, and a final 30 minute centrifugation at 25,000 × g at 22°C. Since the BCA protein assay is incompatible with thiol reagents, final protein concentrations of urea-soluble fractions were obtained by estimating Coomassie Blue G-250 staining intensity of extracts (~2%) following electrophoresis in polyacrylamide gels using titrated BSA as a standard (10-fold range). The gel was run ~5mm in order to increase the accuracy of quantification by concentrating the proteins in a narrow region. Signal intensity of proteins in stained gel was quantified by densitometry with an Odyssey Infrared Imaging System (Li-Cor Biosciences, Lincoln, NE). Generally, the protein yield in urea samples during sequential extraction was approximately 2% of the starting material (see Table S2 for detailed sequential detergent extraction insoluble protein yields).

Proteomic Analysis

Comprehensive shotgun sequencing and label-free quantification of reduced, alkylated, and trypsin-digested proteins from urea fractions was performed. Urea fraction proteins (~50μg per sample) corresponding to pooled AD, control, or FTLD-U (replicates) were reduced with 10mM DTT and alkylated in the dark with 50mM iodoacetamide for 30 minutes. The samples were then separated on a 10% SDS gel (0.75 mm thickness) and stained with Coomassie Blue G-250 to both confirm equal sample loading and visualize proteins for subsequent processing. Each sample lane was then cut into five gel bands and subjected to in-gel digestion (12.5 μg/mL trypsin)³⁵. The resulting peptides from each gel piece were dissolved in buffer A (0.4% acetic acid, 0.005% heptafluorobutyric acid, 5% AcN), loaded onto a C₁₈ column (75 μm i.d., 10 cm long, ~300 nl/min flow rate) as described³⁶, and eluted over 2 hours during a 10–30% gradient of buffer B (0.4% acetic acid, 0.005% heptafluorobutyric acid, 95% AcN). The eluted peptides were detected by Orbitrap (350–1600 m/z, 1,000,000 AGC target, 1,000 ms maximum ion time, resolution 30,000 fwhm) followed by ten data-dependent MS/MS scans in LTQ (3 m/z isolation width, 35% collision energy, 5,000 AGC target, 200 ms maximum ion time) on a hybrid mass spectrometer (Thermo Finnigan, San Jose, CA). Peaklists were generated by Xcalibur 2.0 SR2 software (Thermo Finnigan, San Jose, CA).

The acquired MS/MS spectra were searched against the human reference database (29,575 proteins) of the National Center for Biotechnology Information (January 2007) using the SEQUEST-Sorcerer algorithm version 3.11 r11 (Sage-N-Research, San Jose CA)³⁷. Searching parameters included parent ion mass tolerance (50 ppm), partially tryptic restriction, and mass shifts for modification of carboxyamidomethylated Cys (+57.0215 Da), and for oxidized Met (+15.9949 Da). Only b and y series ions were considered. A target-decoy composite database was used to evaluate the level of false positive matches³⁸. The peptide matches were grouped by charge state (+1, +2, and +3) and trypticity (fully and partially tryptic), and then stringently filtered by (i) mass accuracy of 15 ppm, (ii) minimal peptide length of 7 amino acids, (iii) three maximal modification sites, (iv) two maximal miscleavages, and (v) matching scores (XCorr and ΔCn). In each group, the matching scores were dynamically increased until all decoy matches were discarded, suggesting that estimated false discovery rate was close to zero. To remove redundancy during the assignment of identified peptides to proteins, all accepted proteins sharing peptides were grouped together and represented by the protein with the highest spectral count. Generally, following manual validation of the spectra³⁸, we accepted proteins identified by at least one unique peptide.

Quantification of proteins was based on the comparison of paired peptides from the AD and control/FTLD-U samples. Ion current intensities for identified peptides were extracted in MS survey scans of high-resolution, and a ratio of the peak intensities for the peptide precursor ion was calculated^{39, 40}. For peptides identified in only one sample, corresponding non-sequenced ion peaks were identified for quantification in MS survey scans using the predicted m/z, and adjusted retention time. The resultant ratio is a measure of the relative abundance of the peptide in the two separate samples⁴¹. Statistical analysis to evaluate the significance of the protein changes and to correct for technical errors was performed as previously described with modifications^{42, 43}. Briefly, the peptide abundance ratios were logarithmically transformed (log₂). The mean and associated variance of the transformed ratios was calculated for peptides quantified multiple times. Abundance ratios for all peptides of a particular protein were then averaged to determine the protein abundance ratio. A histogram of all protein abundance ratios was fitted with a normal distribution on the basis of the central limit theorem (bins of 0.3 = log₂(ratio)). Because the majority of proteins likely display similar abundance in disease and control tissues, the abundance ratio for each protein was normalized by subtracting the fitted mean, as the mean should have been zero if sample preparation was ideal. Although most proteins in the data set correlate well with the fitted normal distribution, there are a few proteins demonstrating larger changes that distort the fit of the experimental distribution. These perturbations from the curve of the normal distribution represent proteins that are associated with disease, and presumably deviate from the normal population of unaltered proteins. To be considered significantly altered in AD, we established that a protein must have a consistently elevated log₂(ratio) ≥ ±1.0 (i.e. 2-fold change) in both AD/Control and AD/FTLD_avg distributions.

The quantified proteins were further manually examined to verify MS/MS assignment, ion peak matching, and ion intensity (signal-to-noise ratio ≥ 4). Proteins were scored in three categories, with 1 point awarded in each category: peptide quality, matching status, and extracted ion current. Proteins were scored for peptide quality if their quantitation was based only on fully tryptic peptides with no missed trypsin cleavage sites and no modifications. Only proteins whose quantitation was based on correctly matched peaks in each sample were scored for matching status. Finally, a score was awarded if the total extracted ion current for each peptide exceeded 4 times the moving average for noise level (signal to noise ratio ≥ 4).

Immunohistochemistry

50μm-thick brain sections were prepared with a freezing microtome (Microm, Heidelberg, Germany) with AD, FTLD-U, and control brain blocks from frontal cortex, cingulated cortex, and hippocampus. Sections were incubated in 3% hydrogen peroxide (H₂O₂) to quench endogenous peroxidase activity. Sections were subsequently incubated with normal serum followed by primary antibody overnight at 4°C. After extensive washes with TBS, sections were incubated with biotinylated secondary antibody for 1 hour at 4°C and an additional hour with avidin-biotin-peroxidase complex (Vector Elite ABC Kit, Vector Laboratories, Burlingame CA). Staining was visualized by light microscopy using 3,3′-diaminobenzidine (DAB) as a chromogen.

Western Blotting

Detergent-insoluble urea fractions from pooled homogenates or individual cases were separated by SDS-PAGE and transferred overnight to PVDF Immobilon-P membranes (Millipore, Billercia MA). To ensure both equal loading and complete transfer of proteins from the gel, membranes were reversibly stained with Ponceau S (Diasys Europe Ltd, Workingham, England). Blots were subsequently blocked for 1 hour at room temperature, probed with primary antibody overnight at 4°C, and incubated for 1 hour at room temperature with secondary antibodies (1:20,000) conjugated to fluorophores (Molecular Probes, Eugene OR; Rockland, Gilbertsville PA). Blots were dried, scanned, and quantified with an Odyssey Infrared Imaging System (Li-Cor Biosciences, Lincoln, NE). Statistical analysis was performed using Student’s t-test for independent samples.

Protein identification in urea samples by LC-MS/MS

The proteomic profiling of AD detergent-insoluble aggregated protein fractions was initialized with sample optimization and preparation as illustrated in Figure 2A. In our strategy, frontal cortical samples from postmortem AD, FTLD-U and control cases were individually homogenized and examined prior to pooling by SDS-PAGE followed by silver staining (data not shown). Although there were some differences in band intensities, there was little degradation of proteins such that the pattern of major bands was similar between cases. To minimize inter-case variation, homogenates from 10 cases of each diagnosis (supplemental Table S1) were then combined into a single pool with each case contributing 3 mg total protein. The FTLD-U pooled samples were divided into two identical samples that were processed in parallel as “technical replicates” to discern experimental variances and improve capacity to accurately identify disease-specific proteins^{44, 45}. AD, control, and both FTLD-U pools were serially extracted with triton X-100, sarkosyl, and urea buffers. Urea-soluble fractions were then separated by mass via SDS-PAGE (Figure 2B), excised in 5 bands from the gel, and trypsin-digested. To minimize variation associated with HPLC column performance and ionization efficiency, the tryptic peptide mixtures for each sample were analyzed sequentially under identical LC-MS/MS conditions on a high-resolution mass spectrometer. These spectra were searched against a human protein database, and further stringently filtered by mass accuracy and matching scores. A total of 1,045 proteins (3,216 peptides) were identified in all four samples in all gel bands and these were clustered into 512 protein groups based on shared peptides (Supplemental Table S3 and Table S4).

Relative quantification of proteins in urea samples by the label-free strategy

The comprehensive profiling of protein expression in AD detergent-insoluble preparation requires both the identification and the quantitation of proteins. To determine which of the identified proteins were preferentially enriched in AD, a quantitative protein comparison based on the extracted ion current (XIC) of identified peptides was performed. Abundance ratios corresponding to the relative protein abundance between AD and FTLD-U or control samples were calculated for all 512 proteins identified using peptide data from all gel bands. Abundance ratios for each possible comparison (e.g. AD/Control) were converted logarithmically and plotted as a histogram (Figure 3A). Theoretically, only the abundance of disease-related proteins should be altered in each comparison, and each Gaussian distribution fits the data very well (range of r² = 0.93 to 0.98), confirming the assumption that the majority of the proteins display similar abundance in disease and control urea extracts. Additionally, the fitted normal distribution was used to approximate the common variance of the whole data set, a feature that was used to establish significance thresholds for protein changes⁴². The means and standard deviations (SD) for all relevant case comparisons are shown in Figure 3C. As an initial filter for significantly changed proteins in AD, we required at least a 2-fold change in protein abundance for both AD/Control and AD/FTLD_avg comparisons. Although for a single comparison the probability associated with this 2-fold threshold is approximately 20% according to the average of the SD values (0.82, Figure 3C), when two comparisons were simultaneously considered, the probability of false positives falls to ~4% (20% × 20%). According to the null hypothesis, this probability is equivalent to 21 false positives in a list of 512 proteins. However, using the 2-fold cutoff in our data, 81 proteins were accepted in the filtering, suggesting ~60 (equivalent to 81-21) proteins could theoretically be altered specifically in the AD sample. To remove the false positives in the 81 remaining proteins, we manually examined these proteins and filtered according to additional criteria (Figure 3D, see Experimental Procedures), resulting in a final list of 11 AD-specific proteins (Table 3). Although this stringent manual processing increased our confidence in the quantitative measures, our criteria favor specificity over sensitivity in populating a list of less than the predicted 60 proteins.

The difference between the quantitative information obtained using the XIC method and the qualitative information obtained during peptide identification is further emphasized by the observation that, of the 11 AD-specific proteins in our final list, only the inflammatory complement C4 was identified in the AD sample alone. Since identification of a peptide relies on its fragmentation to produce a unique MS/MS spectrum, complex protein samples can easily saturate the sampling rates of the mass spectrometer⁴⁶. Therefore, due to inherent limitations in the duty cycle of the instrument, only a fraction of ionized peptides can be selected for sequencing. Hence, many nonsequenced ion peaks remain in the MS survey scans, an issue known as “undersampling” in shotgun LC-MS/MS analyses. Even a comparison of the technical replicates, FTLD₁ and FTLD₂, which are identical samples, reveals only a 66% overlap in identified proteins. Certainly, those remaining proteins not identified in both FTLD₁ and FTLD₂ do not represent true differences between these replicates, but instead reflect the capacity for the instrument to be overwhelmed by particularly complex samples. In contrast, quantification using the XIC method is derived from the MS survey scan and is, thus, not entirely dependent on the acquisition of MS/MS scans. Once a peptide has been detected in one of the samples, its corresponding non-sequenced ion peak in all of the other samples can be localized for quantitation using the predicted high resolution m/z value and adjusted retention time²¹. Using this strategy, we quantified peptides for all 35 proteins detected in the AD sample alone, and only complement C4 showed significant quantitative change.

Validation of selected AD-specific, detergent-insoluble proteins

To independently verify the accuracy of the LC-MS/MS generated data, we analyzed several of the proteins identified as altered in AD by immunoblotting and immunohistochemical methods. Among these, we selected several proteins that have been previously implicated in AD or have been associated with known pathogenic pathways. Notably, microtubule-associated protein tau and apolipoprotein E (ApoE) were among the most altered proteins, demonstrating enrichment in AD tissues of greater than 30-fold and 5-fold respectively by quantitative LC-MS/MS. Quantitative immunoblot analysis demonstrated significant enrichment of both tau and ApoE in urea fractions from pooled AD postmortem frontal cortex samples (Figure 4A & 4B). As insoluble proteins typically aggregate focally in disease pathology, immunohistochemistry provides a complementary method to visualize the distribution of altered proteins and their relationship to neurodegenerative changes. AD frontal cortex showed extensive neuropathology with striking enrichment of immunoreactivity for ApoE (Figure 5A & 5B) and tau (data not shown) as has been well-established previously^{8, 47, 48}. Although apolipoprotein E was primarily localized to amyloid plaques, there was also a striking association in multiple cases with neurofibrillary tangles in frontal cortex.

Having validated well-known AD-linked proteins by proteomics and immunological methods, we used similar methods to independently validate and characterize several novel proteins identified as increased in AD from our LC-MS/MS-based approach. Compared with control and FTLD-U cases, pooled urea samples from AD frontal cortex demonstrated up-regulation of ankyrin B, serine protease 15 (PRSS15), and 14-3-3η (Figure 4C–F) in Western blot analysis. Moreover, quantification of immunoblot band intensities in frontal cortex urea fractions from individual, non-pooled AD and control cases used in the proteomics analysis (n = 10 for both AD and control) showed a significant 2.1-fold enrichment (p = 0.008) of 14-3-3η in AD samples (Figure 4G–H). Immunohistochemical examination of both ankyrin B and 14-3-3η revealed thread-like structures with striking localization in plaque regions, confirming the enrichment suggested by the proteomic findings (Figure 5). In addition to being a plaque component, 14-3-3η also appeared to be significantly enriched in the surrounding neuropil in AD tissues. These broad changes in 14-3-3η expression may suggest a more general role in AD pathogenesis. Despite extensive overexpression in AD urea fractions, serine protease 15 (PRSS15) was not associated with classical AD pathology, and its localization remained unaltered in both hippocampus and frontal cortex (data not shown). Finally, although we attempted to validate changes in expression of dynamin 1 and aquaporin 1, the lack of specific immunoreactivity of the purchased commercially available reagents precluded confirmation of the proteomic results in these studies.