A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer's disease

BACKGROUND: Alzheimer's disease (AD) is characterized by the intra- and extracellular accumulation of amyloid-β (Aβ) peptides. How Aβ aggregates perturb the proteome in brains of patients and AD transgenic mouse models, remains largely unclear. State-of-the-art mass spectrometry (MS) methods can comprehensively detect proteomic alterations, providing relevant insights unobtainable with transcriptomics investigations. Analyses of the relationship between progressive Aβ aggregation and protein abundance changes in brains of 5xFAD transgenic mice have not been reported previously. METHODS: We quantified progressive Aβ aggregation in hippocampus and cortex of 5xFAD mice and controls with immunohistochemistry and membrane filter assays. Protein changes in different mouse tissues were analyzed by MS-based proteomics using label-free quantification; resulting MS data were processed using an established pipeline. Results were contrasted with existing proteomic data sets from postmortem AD patient brains. Finally, abundance changes in the candidate marker Arl8b were validated in cerebrospinal fluid (CSF) from AD patients and controls using ELISAs. RESULTS: Experiments revealed faster accumulation of Aβ42 peptides in hippocampus than in cortex of 5xFAD mice, with more protein abundance changes in hippocampus, indicating that Aβ42 aggregate deposition is associated with brain region-specific proteome perturbations. Generating time-resolved data sets, we defined Aβ aggregate-correlated and anticorrelated proteome changes, a fraction of which was conserved in postmortem AD patient brain tissue, suggesting that proteome changes in 5xFAD mice mimic disease-relevant changes in human AD. We detected a positive correlation between Aβ42 aggregate deposition in the hippocampus of 5xFAD mice and the abundance of the lysosome-associated small GTPase Arl8b, which accumulated together with axonal lysosomal membranes in close proximity of extracellular Aβ plaques in 5xFAD brains. Abnormal aggregation of Arl8b was observed in human AD brain tissue. Arl8b protein levels were significantly increased in CSF of AD patients. CONCLUSIONS: We report a comprehensive biochemical and proteomic investigation of hippocampal and cortical brain tissue derived from 5xFAD transgenic mice, providing a valuable resource to the neuroscientific community. We identified Arl8b, with significant abundance changes in 5xFAD and AD patient brains. Arl8b might enable the measurement of progressive lysosome accumulation in AD patients and have clinical utility as a candidate biomarker

Polyglutamine Expansion Accelerates the Dynamics of Ataxin-1 and Does Not Result in Aggregate Formation

Polyglutamine expansion disorders are caused by an expansion of the polyglutamine (polyQ) tract in the disease related protein, leading to severe neurodegeneration. All polyQ disorders are hallmarked by the presence of intracellular aggregates containing the expanded protein in affected neurons. The polyQ disorder SpinoCerebellar Ataxia 1 (SCA1) is caused by a polyQ-expansion in the ataxin-1 protein, which is thought to lead to nuclear aggregates.Using advanced live cell fluorescence microscopy and a filter retardation assay we show that nuclear accumulations formed by polyQ-expanded ataxin-1 do not resemble aggregates of other polyQ-expanded proteins. Instead of being static, insoluble aggregates, nuclear accumulations formed by the polyQ-expanded ataxin-1 showed enhanced intracellular kinetics as compared to wild-type ataxin-1. During mitosis, ataxin-1 accumulations redistributed equally among daughter cells, in contrast to polyQ aggregates. Interestingly, polyQ expansion did not affect the nuclear-cytoplasmic shuttling of ataxin-1 as proposed before.These results indicate that polyQ expansion does not necessarily lead to aggregate formation, and that the enhanced kinetics may affect the nuclear function of ataxin-1. The unexpected findings for a polyQ-expanded protein and their consequences for ongoing SCA1 research are discussed

The Anti-amyloid Compound DO1 Decreases Plaque Pathology and Neuroinflammation-Related Expression Changes in 5xFAD Transgenic Mice

Self-propagating amyloid-β (Aβ) aggregates or seeds possibly drive pathogenesis of Alzheimer's disease (AD). Small molecules targeting such structures might act therapeutically in vivo. Here, a fluorescence polarization assay was established that enables the detection of compound effects on both seeded and spontaneous Aβ42 aggregation. In a focused screen of anti-amyloid compounds, we identified Disperse Orange 1 (DO1) ([4-((4-nitrophenyl)diazenyl)-N-phenylaniline]), a small molecule that potently delays both seeded and non-seeded Aβ42 polymerization at substoichiometric concentrations. Mechanistic studies revealed that DO1 disrupts preformed fibrillar assemblies of synthetic Aβ42 peptides and decreases the seeding activity of Aβ aggregates from brain extracts of AD transgenic mice. DO1 also reduced the size and abundance of diffuse Aβ plaques and decreased neuroinflammation-related gene expression changes in brains of 5xFAD transgenic mice. Finally, improved nesting behavior was observed upon treatment with the compound. Together, our evidence supports targeting of self-propagating Aβ structures with small molecules as a valid therapeutic strategy

Additional file 1 of A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer’s disease

Additional file 1: Table S1. Commercial antibodies used in this study. Table S2. Characteristics of AD and HD patients and corresponding controls. Table S3. Spearman correlation analysis of Arl8b protein level measurements and AD biomarker levels

Additional file 2 of A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer’s disease

Additional file 2: Fig. S1. Aβ peptide levels and APP and PSEN1 expression in hippocampus and cortex of 5xFAD mice. Fig. S2. Analysis of Aβ aggregate formation using membrane filter assays and sucrose gradient centrifugations. Fig. S3. Analysis of wild-type expression profiles to assess whether the protein abundance changes detected in 5xFAD brains are more frequent among highly expressed mouse proteins. Fig. S4. Functional analysis of dysregulated proteins defined with a pairwise model in brains of 5xFAD mice. Fig. S5. Enrichment analysis of cell-type-specific marker proteins among dysregulated proteins in brains of 5xFAD mice. Fig. S6. IPA and gene ontology enrichment analysis of differentially expressed proteins defined with the full model in cortical and hippocampal tissues of 5xFAD mice. Fig. S7. Ingenuity pathway analysis of Aβ-correlated and anticorrelated DEPs defined by the pairwise model in brains of 5xFAD mice. Fig. S8. Numbers of pairwise common DEPs in the mouse datasets and datasets from human studies. Fig. S9. Strategy to define mouse protein signatures that are concordantly altered also in AD patient brains. Fig. S10. Investigation of the overlap of DEPs in brains of 5xFAD mice with DEPs in asymptomatic AD brains. Fig. S11. Analysis of the correlation in protein effect sizes between 5xFAD mouse and AD patient brains for proteins present in all studies. Fig. S12. Selection of the neuronal lysosome-associated protein Arl8b by step-by-step data filtering. Fig. S13. Immunofluorescence analysis of 5xFAD brain slices. Fig. S14. Analysis of Arl8b protein aggregates using human brain homogenates derived from AD patients and control individuals

Additional file 3 of A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer’s disease

Additional file 3: Supplementary Excel File 1a. DEPs from 5xFAD versus wild-type tissue comparisons in hippocampus and cortex; DEPs were defined using the “pairwise model”; Supplementary Excel File 1b. Summary of the statistical calculations from Supplementary Excel File 1a; Supplementary Excel File 1c. DEPs in both hippocampal and cortical tissues defined through the “full model”; Supplementary Excel File 2. DEPs that correlate or anticorrelate to Aβ aggregate load in both hippocampal and cortical tissues defined through the “pairwise model”; Supplementary Excel File 3. Identified genes differentially down- or upregulatedin cortex or hippocampus of 5xFAD mice; Supplementary Excel File 4. Results of the Ingenuity Pathway Analyses performed in Figures 3g and 4e; Supplementary Excel File 5a. Proteins with significant abundance changes from Johnson et al. 2020; Supplementary Excel File 5b. Proteins with significant abundance changes from Johnson et al. 2022; Supplementary Excel File 5c. Proteins with significant abundance changes from Johnson et al. 2022; Supplementary Excel File 5d. Proteins with significant abundance changes from Drummond et al. 2022; Supplementary Excel File 6. Numbers of common DEPs in mouse and human datasets; Supplementary Excel File 7. DEPs defined using a “pairwise model” and concomitantly altered both in mouse and human brain tissues from J20, J22 and D22. Supplementary Excel File 8a. The step-by-step selection process to identify the potential AD biomarker Arl8b. Supplementary Excel File 8b. The top 25 Aβ-correlated proteins in mouse hippocampal tissues

The DNAJB6 and DNAJB8 Protein Chaperones Prevent Intracellular Aggregation of Polyglutamine Peptides

Fragments of proteins containing an expanded polyglutamine (polyQ) tract are thought to initiate aggregation and toxicity in at least nine neurodegenerative diseases, including Huntington's disease. Because proteasomes appear unable to digest the polyQ tract, which can initiate intracellular protein aggregation, preventing polyQ peptide aggregation by chaperones should greatly improve polyQ clearance and prevent aggregate formation. Here we expressed polyQ peptides in cells and show that their intracellular aggregation is prevented by DNAJB6 and DNAJB8, members of the DNAJ (Hsp40) chaperone family. In contrast, HSPA/Hsp70 and DNAJB1, also members of the DNAJ chaperone family, did not prevent peptide-initiated aggregation. Intriguingly, DNAJB6 and DNAJB8 also affected the soluble levels of polyQ peptides, indicating that DNAJB6 and DNAJB8 inhibit polyQ peptide aggregation directly. Together with recent data showing that purified DNAJB6 can suppress fibrillation of polyQ peptides far more efficiently than polyQ expanded protein fragments in vitro, we conclude that the mechanism of DNAJB6 and DNAJB8 is suppression of polyQ protein aggregation by directly binding the polyQ tract

HDAC4 knock-down does not rescue global transcriptional dysregulation.

<p>(A) Affymetrix arrays were used to determine the effect of <i>Hdac4</i> knock-down on the cortical transcription profile of WT and R6/2 mice at 9 and 15 wk of age (<i>n</i>≥8 per genotype per time point). The number of genes that were significantly altered between genotypes with a fold-change of >30% for each pairwise comparison is noted. Statistical significance was determined after FDR-correction at a stringency of <i>p</i>≤0.05. (B) Taqman qPCR validation of the genes that were predicted to be differentially expressed between R6/2 and Dble::R6/2 cortex at 9 wk of age. See <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001717#pbio.1001717.s006" target="_blank">Table S3</a> for gene abbreviation definitions. (C) Cortical <i>Bdnf</i> mRNA levels for promoter transcripts 1, 2a, 4, and 5 as well as the coding exon (B) were assessed by Taqman qPCR at 15 wk of age. All Taqman qPCR values were normalized to the geometric mean of three housekeeping genes: <i>Atp5b</i>, <i>Canx</i>, and <i>Rpl13a</i>. Error bars are S.E.M (<i>n</i> = 8). *<i>p</i><0.05, **<i>p</i><0.01, ***<i>p</i><0.001; NS, not significant.</p

HDAC4 reduction improves the electrophysiological characteristics of MSNs and corticostriatal synaptic function.

<p>(A–H) Box and whisker plots of (A, E) input resistance (R_m), (B, F) RMP, (C, G) rheobase current, and (D, H) spike amplitude from corticostriatal slices at (A–D) 7–8 and (E–H) 12 wk of age. Box and whisker plots: +, mean; box, interquartile range; whisker, 10–90 percentile; outliers, closed circles. (I) Measurement of evoked EPSCs following cortical stimulation showed that the R6/2 mice show lower basal transmission compared to WT or <i>Hdac4</i>HET and that this is restored in the Dble::R6/2 mice at 7–12 wk of age. (J) R6/2 MSNs have a higher paired-pulse ratio than WT (interstimulus interval, 20 ms), indicating reduced glutamate release probability. This is fully restored in Dble::R6/2 mice at 12 wk of age. (K) Representative traces of miniature EPSCs (mEPSCs) at 8 wk. R6/2 mice show strongly depressed mEPSC frequency, which is significantly rescued in the Dble::R6/2 mice. (L, M) Average cumulative plot of mEPSC interevent interval (0.1 s bins) (L) or amplitude (1 pA bins) (M); <i>n</i> = 11–12 for all four genotypes. Statistical analysis was performed by (A–H and J) one-way ANOVA with Tukey's multiple comparison test, (I) two-way ANOVA with Bonferroni multiple comparison test, and (L, M) Kolmogorov–Smirnov (KS) test. *<i>p</i><0.05, **<i>p</i><0.01, ***<i>p</i><0.001.</p

HDAC4 knock-down delays aggregate formation in R6/2 and <i>Hdh</i>Q150 mouse models of HD.

<p>(A) Seprion ligand ELISA was used to quantify aggregate load in the cortex of R6/2 and Dble::R6/2 mice at 4, 9, and 15 wk of age. Values for the Dble::R6/2 mice were plotted as a percentage of R6/2 aggregate load (<i>n</i> = 6). (B) TR-FRET was used to determine the levels of soluble exon 1 HTT in the cortex of R6/2 and Dble::R6/2 mice at 4, 9, and 15 wk of age (<i>n</i> = 6). (C) Seprion ligand ELISA was used to quantify aggregate load in the striatum, cortex, and cerebellum of <i>Hdh</i>Q150 and Dble::<i>Hdh</i>Q150 mice at 6 and 10 mo of age. Values for the Dble::<i>Hdh</i>Q150 mice were plotted as a percentage of aggregate load of <i>Hdh</i>Q150 mice (<i>n</i>≥7). (D) Representative S830 immunoblot of cortical lysates showing the difference in soluble and aggregated exon 1 HTT between R6/2 and Dble::R6/2 (Dble) mice and how this change occurs with age. (E) Comparison of HDAC4 levels in the nuclear and cytoplasmic fractions of R6/2 and Dble::R6/2 (Dble) brains by western blot. The purity of the fractions is shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001717#pbio.1001717.s002" target="_blank">Figure S2D</a>. (F) Western blot of detergent-insoluble high molecular weight (HMW) aggregates isolated from the nuclear and cytoplasmic fractions of R6/2 and Dble::R6/2 (Dble) brains, resolved by agarose gel electrophoresis (AGERA), and immunodetected with the S830 antibody (representative of three experiments) (<i>n</i> = 8). The purity of the fractions is shown by western blotting with α-tubulin and histone H3. (G) Western blot of HDAC4 in the cytoplasmic fraction of R6/2 and Dble::R6/2 (Dble) brains at 9 wk of age. HDAC4 levels were measured by densitometry and calculated relative to α-tubulin. Error bars are SEM. <i>p</i> values were calculated using Student's <i>t</i> test.</p