Animals

Mice were bred and maintained in accordance with approved Johns Hopkins University Institutional Animal Care and Use Committee protocols. Gde2 heterozygous (Gde2±) mice were bred, maintained, and genotyped as described previously [15]. SOD1G93A (Jackson Laboratory Strain #002,726), and SOD1WT (Jackson Laboratory Strain #002,297) animals were bred, maintained, and genotyped as described previously [17].

Human samples

Postmortem tissue: Frozen postmortem motor cortex samples and paraffin embedded sections of postmortem motor cortex were obtained from the Target ALS Multicenter Postmortem Tissue Core. Sections of postmortem motor cortex were also obtained from the Johns Hopkins Brain Resource Center. All procedures were performed with appropriate Health Insurance Portability and Accountability Act (HIPAA)-approved autopsy consents. The demographics of postmortem samples used in this study are provided in Additional File 1: Supplementary Table 1. CSF samples: CSF samples from 11 control individuals and 20 patients with ALS were obtained from the Northeast Amyotrophic Lateral Sclerosis (NEALS) consortium. Nine additional CSF samples from control individuals were provided by the Advancing Research and Treatment for Frontotemporal Lobar Degeneration Research Consortium (ARTFL) at the University of California San Francisco (UCSF). Study participants provided written informed consent, and all procedures were approved by the respective Institutional Review Boards (IRB). The demographics of CSF samples used in this study are provided in Additional File 2: Supplementary Table 2.

Immunohistochemistry

Paraffin sections (mouse)

Immunostaining was performed as previously described [17]. Briefly slides were deparaffinized in Xylenes, rehydrated, and washed with Phosphate Buffered Saline (PBS) containing 0.3% Triton-X-100 (PBST). Microwave antigen retrieval in 10 mM Sodium citrate followed by blocking in 5% Normal Goat Serum was performed.

Paraffin sections (human)

Human motor cortex sections were deparaffinized in Xylenes, then rehydrated in 100% ethanol, 95% ethanol, 70% ethanol, and rinsed with water [30]. Permeabilization was performed with 0.3% PBST followed by antigen retrieval in 10 mM Sodium Citrate with 0.5% Tween-20 (pH 6.0) in a 95 °C water bath. Sections were then washed in PBS followed by overnight blocking at 4 °C in 5% Bovine Serum Albumin (BSA). GDE2 primary antibody (cSS1[30], Covance,1:500) was diluted in 1% BSA and incubated overnight at 4 °C. After blocking endogenous peroxidases with 0.3% hydrogen peroxide and washing with PBS, tissue sections were incubated with horseradish peroxidase (HRP)-conjugated donkey anti-chicken secondary antibody (Jackson ImmunoResearch, 1:500) diluted in 1% BSA for 1 h at room temperature (RT). Sections were washed with PBS, and 3,3′-Diaminobenzidine solution (Sigma-Aldrich, D4168-50) was applied to sections for visualization. Sections were then washed and mounted with ProLong Antifade Gold with DAPI (ThermoFisher, P36931).

Primary antibodies

Rabbit Anti-Iba1 (Wako 019–19,741, 1:250), Mouse Anti GFAP (BD 556,328, 1:250), Mouse Anti-phospho-Neurofilament H (Calbiochem NE1022, 1:250), Rabbit Anti-Peripherin (Millipore Sigma AB1530, 1:250), and Chicken anti-human GDE2 (cSS1[30], Covance, 1:500).

Secondary antibodies

Jackson ImmunoResearch Goat Anti-Mouse Alexa 488 (115–545-166), Goat Anti Rabbit Alexa 594 (111–585-144), and Peroxidase-conjugated Donkey Anti-Chicken IgY (703–035-155). Brightfield and epifluorescence images were collected at 20 × using a Zeiss Axioskop 2 upright microscope or a Keyence BZ-X710 epifluorescence microscope. Confocal imaging was performed with an Olympus FV3000 Laser scanning confocal microscope. Images were analyzed using ImageJ (NIH) and Matlab Image Processing (Mathworks).

Image quantification

SOD Pathology (mouse)

The soma and vacuole sizes were calculated from brightfield H&E images. Custom Matlab imaging software was used to threshold and binarize the images to quantify the vacuolization and motor neuron number. A minimum of 12 ventral horns from lumbar spinal cord were analyzed per animal. Neuronal soma were distinguished from glia based on their location in the ventral grey matter and minimum size of 60 μm2. We analyzed a minimum of 900 neurons per genetic condition. To isolate large diameter vacuoles indicative of degeneration, vacuoles required a minimum size of 75 μm2 to be included in the dataset. Vacuole counts were binned in 3.75 μm2 intervals to create a frequency histogram. The number of vacuoles in each bin plus all smaller bins was calculated as a percentage of all detected vacuoles and graphed as a cumulative probability distribution. The distributions of neuronal sizes were compared with an independent samples Kruskal–Wallis Test, and vacuole size distributions were compared with the Kolmogorov–Smirnov test. Manual counts of the mean number of cytoskeletal inclusions were compared with a 2-tailed Student’s t test. Alpha level is 0.05. Error bars represent standard error of the mean unless otherwise indicated.

GDE2 distribution (human)

Cells with accumulations of GDE2 were manually quantified from paraffin sections of control (n = 7) and ALS patient (n = 10) motor cortices. All quantification of human samples was performed blinded. For each sample, 10–12 regions of interest (0.23 or 0.39 mm2) per section were chosen at random to be imaged and analyzed. Accumulations were scored as high intensity if they took up at least 25% of the cell body and were above a relative intensity threshold set to control using ImageJ (NIH). Manual counts of the mean number of high-intensity GDE2 accumulations per mm2 were analyzed using a 2-tailed Student’s t test. For this analysis, the alpha level is 0.05, and error bars represent standard error of the mean.

Western blot analysis

Lysate preparation

Human motor cortex samples were either sonicated in RIPA lysis buffer containing protease inhibitor cocktail (Sigma, P8340) or partitioned into detergent-poor and detergent-rich fractions with Triton-X-114 (Sigma, X114) as previously described [16]. Briefly, 2% Triton-X-114 was pre-conditioned in 100 mM Tris–HCl, pH 7.4, 150 mM NaCl buffer. The frozen tissues were sonicated in 1% Triton-X-114 containing protease inhibitor cocktail, followed by centrifugation (16,000 × g, 2 × 10 min, 4 °C). Detergent-rich and detergent-poor phases were separated by incubating the lysates at 30 °C for 10 min. After centrifugation (3000 × g, 3 min, RT), the detergent-rich pellet was collected for analysis of membrane-bound proteins. Batches of human samples were processed at the same time to minimize variability between samples, and protein amounts were standardized using a BCA Protein Assay kit (ThermoFisher, 23,225).

Immunoblotting

Samples were subject to reducing SDS-PAGE using 7.5 or 10% Criterion TGX Precast Gels (Bio-Rad Laboratories) in tris/glycine buffer, transferred onto polyvinylidene difluoride membranes at 100 V for 70 min, and blocked with 5% milk in tris-buffered saline containing 0.3% Tween-20 (TBST) for 2–3 h at RT. Membranes were then incubated with primary antibodies diluted in 5% milk in TBST overnight at 4 °C. HRP-conjugated secondary antibodies were diluted in 5% milk in TBST and incubated for 1 h at RT. Membranes were developed using the KwikQuant Imager (Kindle Biosciences) after incubation with enhanced chemiluminescence substrate (Kindle Biosciences, R1004). Imaged blots were analyzed using ImageJ software (NIH).

Primary antibodies

Chicken anti-human GDE2 (cSS1, [30] Covance, 1:1000), Rabbit anti-Na/K ATPase (Abcam, ab76020, 1:100,000), and Rabbit anti-GAPDH (Cell Signaling, 8884, 1:5000).

Secondary Antibodies: Peroxidase-conjugated Donkey Anti-Chicken IgY (Jackson ImmunoResearch, 703–035-155, 1:10,000) and Anti-Rabbit IgG-HRP (Kindle Biosciences, R1006, 1:10,000).

CSF sample preparation and trypsin digestion for MS experiments

Four experimental batches of 10 samples were examined, with each batch including a master pool (MP) sample containing an equal volume of all CSF samples for normalization between batches. The CSF samples were mixed with a urea buffer, composed of 10 M urea/20 mM tris (2-Carboxyethyl) phosphine hydrochloride (TCEP)/80 mM chloroacetamide (CAA) in 100 mM triethylammonium bicarbonate (TEAB), at a one-to-one ratio. Samples were incubated for 1 h at RT for reduction and alkylation. Protein digestion was carried out using LysC (lysyl endopeptidase mass spectrometry (MS) grade, Fujifilm Wako Pure Chemical Industries Co., Ltd., Osaka, Japan) at a one-to-fifty (w/w) ratio for 3 h at 37 °C and subsequently with trypsin digestion (sequencing grade modified trypsin, Promega, Fitchburg, WI, USA) at a one-to-fifty (w/w) ratio at 37 °C overnight after diluting the concentration of urea from 5 to 2 M by adding 50 mM TEAB. Peptides were desalted using C18 StageTips (3 M Empore™; 3 M, St. Paul, MN, USA) after acidifying with 1% trifluoroacetic acid (TFA) to the final concentration. The eluted solution containing peptides was dried with a Savant SPD121P SpeedVac concentrator (Thermo Fisher Scientific, San Jose CA) and then stored at ‒80 °C before use.

For tandem mass tag (TMT)-based quantitative MS, the digested peptides from CSF samples were labeled with 11-plex TMT reagents following the manufacturer’s instructions (Thermo Fisher Scientific). The MP sample was labeled with 131C, and CSFs from ALS and control individuals were labeled with the rest of the TMT tags. The labeling reaction was performed for 1 h at RT after mixing each peptide sample in 100 mM TEAB with TMT reagent in acetonitrile (ACN, HPLC grade), and then quenched by adding 1/10 volume of 1 M Tris–HCl (pH 8.0). The TMT labeled peptides were pooled, resuspended with 10 mM TEAB, and then subjected to basic pH reversed-phase liquid chromatography (bRPLC) fractionation to generate fractions on an Agilent 1260 offline HPLC system (Agilent Technologies, Santa Clara, CA, USA), which includes a binary pump, variable wavelength detector, an autosampler, and an automatic fraction collector. The pooled samples were reconstituted in solvent A (10 mM TEAB, pH 8.5) and loaded onto Agilent 300 Extend-C18 column (5 µm, 4.6 mm × 250 mm, Agilent Technologies). Peptides were resolved using a gradient of solvent B (10 mM TEAB in 90% ACN, pH 8.5) at a flow rate of 0.3 mL/min over 90 min, collecting 96 fractions. Subsequently, the fractions were concatenated into 24 fractions followed by vacuum drying using a SpeedVac (Thermo Fisher Scientific, San Jose, CA, USA). The dried peptides were suspended in 0.5% formic acid (FA), and 30% of each fraction was injected for MS analysis.

LC–MS/MS analysis

Peptide samples were analyzed on an Orbitrap Fusion Lumos Tribrid mass spectrometer interfaced with an Ultimate 3000 RSLCnano nanoflow liquid chromatography (LC) system (Thermo Fisher Scientific). The dried 24 fractionated peptides were reconstituted in 0.5% FA and then loaded onto a trap column (Acclaim™ PepMap™ 100 LC C18, 5 μm, 100 μm × 2 cm, Thermo Fisher Scientific) at a flow rate of 8 μl/min. Peptides were separated on an analytical column (Easy-Spray™ PepMap™ RSLC C18, 2 μm, 75 μm × 50 cm, Thermo Fisher Scientific) at a flow rate of 0.3 μl/min using a linear gradient with mobile phases consisted of 0.1% FA in water and in 95% ACN. The total run time was 120 min. The mass spectrometer was operated in a data-dependent acquisition mode. The MS1 (precursor mass) scan range for a full survey scan was acquired from 300 to 1,800 m/z (mass-to-charge ratio) in the “top speed” setting with a resolution of 120,000 at an m/z of 200. The AGC target for MS1 was set as 1 × 106 and the maximum injection time was 50 ms. The most intense ions with charge states of 2 to 5 were isolated in a 3-s cycle, fragmented using higher-energy collisional dissociation (HCD) fragmentation with 35% normalized collision energy, and detected at a mass resolution of 50,000 at an m/z of 200. The AGC target for MS/MS (MS2, fragment mass) was set as 5 × 104 and the ion filling time was 100 ms. The precursor isolation window was set to 1.6 m/z with a 0.4 m/z offset. The dynamic exclusion was set for 30 s, and singly charged ions were rejected. Internal calibration was carried out using the lock mass option (m/z 445.1200025) from ambient air.

Database searches for peptide and protein identification

The acquired tandem MS data were searched against the human UniProt database (released in May 2018, containing protein entries with common contaminants) using the SEQUEST search algorithm through the Thermo Proteome Discoverer platform (version 2.2.0.388, Thermo Fisher Scientific) for quantitation and identification. During MS/MS preprocessing, the top 10 peaks in each window of 100 m/z were selected for database searches. The search parameters included two maximum missed-cleavage sites by trypsin as a proteolytic enzyme. Carbamidomethyl (+ 57.02146 Da) at cysteine and TMT reagents (+ 229.162932 Da) modification at N-terminus of peptide and lysine residues were set as fixed modifications while oxidation (+ 15.99492 Da) of methionine was a variable modification. For MS data, MS1 error tolerance was set to 10 ppm and the MS/MS error tolerance to 0.02 Da. The minimum peptide length was set to 6 amino acids, and proteins identified by one peptide were filtered out. Both peptides and proteins were filtered at a 1% false discovery rate (FDR). The protein quantification was performed with the following parameters and methods. The most confident centroid option was used for the integration mode while the reporter ion tolerance was set to 20 ppm. MS order was set to MS2. The activation type was set to HCD. The quantification value correction was disabled. Both unique and razor peptides were used for peptide quantification. Protein groups were considered for peptide uniqueness. Missing intensity values were replaced with the minimum value. Reporter ion abundance was computed based on the signal-to-noise ratio. Quantification value corrections for isobaric tags were disabled. The co-isolation threshold was set to 50%. The average reporter signal-to-noise threshold was set to 50. Data normalization was disabled. Protein grouping was performed by applying strict parsimony principle as following; 1) all proteins that share the same set or subset of identified peptides were grouped, 2) protein groups that have no unique peptides among the considered peptides were filtered out, 3) Proteome Discoverer iterated through all spectra and selected which peptide-spectrum match (PSM) to use in ambiguous cases to make a protein group with the highest number of unambiguous and unique peptides, and 4) final protein groups were generated. The Proteome Discoverer summed all the reporter ion abundances of PSMs for the corresponding proteins in a TMT run.

Statistical analyses of the results from discovery proteomics

Statistical analysis was conducted with the Perseus software package (version 1.6.0.7). Protein abundance values across the samples were divided by those of MP included in each batch, followed by dividing values of each sample by their median value. After log2-transformation of all the values, values across proteins were z-score-transformed. The fold changes between the comparison groups were calculated by dividing the average abundance values across the samples of one group by the ones of another group. The P values between the comparison groups were calculated with the 2-tailed Student’s t test. The q-values for the volcano plots were calculated by significance analysis of microarrays (SAM) and a permutation-based FDR estimation [31].

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