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Aug 25, 2014 - Label-Free Quantitative Proteomic Profiling Identifies Disruption of Ubiquitin Homeostasis As a Key Driver of Schwann Cell Defects in S...
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Label-Free Quantitative Proteomic Profiling Identifies Disruption of Ubiquitin Homeostasis As a Key Driver of Schwann Cell Defects in Spinal Muscular Atrophy Arwin Aghamaleky Sarvestany,†,‡ Gillian Hunter,†,‡ Amy Tavendale,§ Douglas J. Lamont,§ Maica Llavero Hurtado,∥ Laura C. Graham,∥ Thomas M. Wishart,†,∥,⊥ and Thomas H. Gillingwater*,†,‡,⊥ †

Euan MacDonald Centre for Motor Neurone Disease Research, University of Edinburgh, Edinburgh EH8 9XD, United Kingdom Centre for Integrative Physiology, University of Edinburgh, Edinburgh EH8 9XD, United Kingdom § Fingerprints Proteomics Facility, Dundee University, Dundee DD1 4HN, United Kingdom ∥ Neurobiology Division, Roslin Institute, University of Edinburgh, Edinburgh EH8 9XD, United Kingdom ‡

S Supporting Information *

ABSTRACT: Low levels of survival of motor neuron (SMN) protein cause the neuromuscular disease spinal muscular atrophy (SMA), characterized by degeneration of lower motor neurons and atrophy of skeletal muscle. Recent work demonstrated that low levels of SMN also trigger pathological changes in Schwann cells, leading to abnormal axon myelination and disrupted deposition of extracellular matrix proteins in peripheral nerve. However, the molecular pathways linking SMN depletion to intrinsic defects in Schwann cells remained unclear. Label-free proteomics analysis of Schwann cells isolated from SMA mouse peripheral nerve revealed widespread changes to the Schwann cell proteome, including disruption to growth/proliferation, cell death/survival, and molecular transport pathways. Functional clustering analyses revealed significant disruption to a number of proteins contributing to ubiquitination pathways, including reduced levels of ubiquitin-like modifier activating enzyme 1 (Uba1). Pharmacological suppression of Uba1 in Schwann cells was sufficient to reproduce the defective myelination phenotype seen in SMA. These findings demonstrate an important role for SMN protein and ubiquitin-dependent pathways in maintaining Schwann cell homeostasis and provide significant additional experimental evidence supporting a key role for ubiquitin pathways and, Uba1 in particular, in driving SMA pathogenesis across a broad range of cells and tissues. KEYWORDS: spinal muscular atrophy, SMA, label-free proteomics, Schwann cell, mouse, ubiquitin, uba1



INTRODUCTION Proximal spinal muscular atrophy (SMA) is an autosomal recessive disease that is a leading genetic cause of infant mortality in humans.1 In the most severe form of SMA (type I), disease onset occurs in the perinatal period, with a maximum life expectancy of two years. Clinically, SMA is characterized as a neuromuscular condition, with a loss of lower alpha motor neurons from the ventral horn of spinal cord and skeletal muscular atrophy the major pathological features.1 SMA is primarily caused by defects in the survival of motor neuron 1 (SMN1) gene, whose full-length protein product, SMN, is ubiquitously expressed.2,3 Humans also have an SMN2 gene as part of a 500 kb inverted duplication on chromosome 5q13, but this copy of the gene has undergone a C−T substitution at base pair 840 resulting in the exclusion of exon 7 from the majority of its transcripts.4 This results in the production of a truncated protein that cannot fully compensate for the loss of full-length SMN protein when the SMN1 gene is lost.3,4 Although low levels of full-length SMN protein are known to cause pathological changes in lower motor neurons and skeletal © XXXX American Chemical Society

muscle, a growing body of evidence suggests that pathological changes also occur across multiple other cell-types and tissues in SMA, albeit to varying degrees.5 For example, recent studies have demonstrated intrinsic defects in Schwann cells (the main glial cell present in peripheral nerve) in SMA, leading to defective myelination and deposition of extracellular matrix proteins in peripheral nerve.6 In vitro coculture experiments of healthy neurons with SMA-derived Schwann cells demonstrated that loss of SMN protein in the latter impacted on the stability of neighboring neuronal processes, suggesting that Schwann cells may also contribute to neuronal pathology in SMA.6 Despite our increased awareness of the contribution of Schwann cells to peripheral nerve pathology in SMA, it remains unclear how low levels of SMN protein lead to intrinsic defects Special Issue: Proteomics of Human Diseases: Pathogenesis, Diagnosis, Prognosis, and Treatment Received: May 20, 2014

A

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in this specific cell population. Although SMN is known to play important roles in RNA processing pathways,7,8 whether defects in these pathways directly contribute to disease pathogenesis remains unclear.9,10 Several studies have identified other noncanonical roles for SMN that can contribute to disease pathogenesis, including functions in translational regulation,11 axonogenesis,12 and modulation of ubiquitin homeostasis.13 To determine the molecular consequences of SMN depletion in Schwann cells in an unbiased manner, in order to identify key cellular mechanisms driving pathology in this specific cell type, we used label-free proteomics analysis to quantify and compare the proteome of Schwann cells isolated from SMA mice and control littermates. We report on widespread changes in the Schwann cell proteome when levels of SMN were reduced, including significant disruption to a range of functional pathways and canonical protein clusters, including perturbations in ubiquitination focused around reduced levels of ubiquitin-like modifier activating enzyme 1 (Uba1).



Figure 1. Schematic diagram illustrating experimental design for labelfree proteomics comparison of the proteome of SMA and control Schwann cells.

MATERIALS AND METHODS

Generation of In Vitro Schwann Cell Preparations

concentration was then determined using BCA assay. Aliquots (100 μg) of each Schwann cell preparation were processed through FASP (filter-aided sample preparation) involving buffer exchange to 8 M urea and alkylation with 50 mM iodoacetamide prior to a double digestion with trypsin (Roche, sequencing grade), initially for 4 h, then overnight at 30 °C. Trypsin-digested peptides were separated using an Ultimate 3000 RSLC (Thermo Scientific) nanoflow LC system. Using an ESI Easy Spray source at 50 °C, technical replicates (3 × ∼2.5 μg) of each sample were loaded with a constant flow of 5 μL/ min onto an Acclaim PepMap100 nanoViper C18 trap column (100 μm inner diameter, 2 cm length; Thermo Scientific). After trap enrichment, peptides were eluted onto an Acclaim PepMap RSLC nanoViper, C18 column (75 μm, 50 cm; Thermo Scientific) with a linear gradient of 2−40% solvent B (80% acetonitrile with 0.08% formic acid) over 124 min with a constant flow of 300 nL/min. The HPLC system was coupled to a linear ion trap Orbitrap hybrid mass spectrometer (LTQOrbitrap Velos Pro, Thermo Scientific) via a nanoelectrospray ion source (Thermo Scientific). The spray voltage was set to 1.6 kV, and the temperature of the heated capillary was set to 250 °C. Full-scan MS survey spectra (m/z 335−1800) in profile mode were acquired in the Orbitrap with a resolution of 60 000 after accumulation of 1 000 000 ions. Lock mass was set at 445.120 024. The 15 most intense peptide ions from the preview scan in the Orbitrap were fragmented by collisioninduced dissociation (normalized collision energy, 35%; activation Q, 0.250; and activation time, 10 ms) in the LTQ after the accumulation of 10 000 ions. Dynamic exclusion parameters were set as follows: repeat count, 1; repeat duration, 30 s; exclusion list size, 500; exclusion duration, 45 s; exclusion mass width, plus/minus 10 ppm (relative to reference mass). Maximal filling times were 1,000 ms for the full scans and 150 ms for the MS/MS scans. Precursor ion charge state screening was enabled, and all unassigned charge states as well as singly charged species were rejected. The lock mass option was enabled for survey scans to improve mass accuracy. Data were acquired using the Xcalibur software. Raw data was imported into Progenesis LCMS for label-free differential analysis and subsequent identification and quantification of relative ion abundance ratios. Following alignment of

“Taiwanese” SMA mice on a congenic FVB background (Smn−/−;SMN2tg/0 mice carrying two SMN2 copies on one allele on a null murine Smn background)14 were obtained from breeding pairs originally purchased from Jackson Laboratories and were maintained following the breeding strategy devised by Riessland et al.15 Littermate mice (Smn±) were used as controls. Litters were retrospectively genotyped using standard PCR protocols, as previously described.6 All mice were maintained within animal care facilities at the University of Edinburgh under standard SPF conditions. All animal procedures and breeding were performed in accordance with Home Office and institutional guidelines. Schwann cells were isolated from midsymptomatic SMA mice at postnatal day 8 (P8) as previously described.6 Briefly, brachial plexii and sciatic nerves were rapidly dissected following sacrifice, treated with 0.125% trypsin and 0.05% collagenase A, and then resuspended in basic growth medium containing 10−6 M insulin before plating out on 60 mm dishes coated with neat poly-L-lysine (PLL) and laminin. Schwann cells were purified using complement-mediated cytolysis to remove contaminating fibroblasts before being expanded in Schwann cell growth medium containing 10−6 M insulin to reach 80% confluency. Differentiation to a myelinating phenotype was induced by the addition of NRG-1 and dbcAMP6 and cells were taken 72 or 120 h later for analysis. For experiments where pharmacological inhibition of Uba1 was required, UBEI-41 (Biogenova), a cell-permeable Uba1 inhibitor with an IC50 ∼ 5 μM, was added to the culture medium (10 μM) for 24 h, as previously described.13 Label-Free Proteomics

The experimental design for label-free proteomics experiments was based on previous similar analyses of SMA skeletal muscle16 and is shown in Figure 1. Protein isolated from preparations of SMA-derived Schwann cells (Smn−/ −;SMN2tg/0 mice) and control Schwann cells (littermate control mice) 72 h postdifferentation was extracted in SDT lysis buffer containing 100 mM Tris-HCl (pH 7.6), 4% (W/V) Sodium dodecyl sulfate (VWR) and 0.1 M D/L-dithiothreitol (Sigma). For efficient protein extraction, lysates were freeze− thawed and homogenized in SDT buffer several times. Protein B

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MS data, principal component analysis and preliminary filtering (power < 0.8, fold-change > 2, P > 0.05 (peptide filtering)), data sets were exported from Progenesis in mgf files for subsequent identification of individual peptide sequences using IPI-mouse (Date: 20130120, 59 534 entries) database via Mascot Search Engine (V2.3.2). Enzyme specificity was set to that of trypsin, allowing for cleavage N-terminal to proline residues and between aspartic acid and proline residues. Other parameters used were as follows. (i) Variable modifications: methionine oxidation, methionine dioxidation, protein Nacetylation, gln → pyro-glu. (ii) Fixed modifications: cysteine carbamidomethylation. (iii) MS/MS tolerance: FTMS- 10 ppm, ITMS- 0.6 Da. (iv) Minimum peptide length: 6. (v) Maximum missed cleavages: 2. (vi) False discovery rate: 1%. A cutoff score of >34 was used based on Mascot probability threshold of 0.05 that the observed hit is a random event. As an indication of identification certainty, the false discovery rate for peptide matches above identity threshold was set at 1%. Statistical P values were automatically generated using Progenesis software through a 1 way Anova on the ArcSinh transform of the normalized data. Mascot-generated data were then reimported into Progenesis for subsequent conflict resolution and protein expression comparison. A stringent selection criteria was used before a protein was included in our analyses; quantitation was calculated using only unique peptides; identification of at least two peptides was needed and a P value of 20% compared to wild-type controls (Figure 2). Outputs from the Progenesis software can be found in Supporting Information Tables 1 and 2. Bioinformatics analyses were performed using Ingenuity Pathway Analysis (IPA) software, as previously described.13,17

Figure 2. Filtering of label-free proteomics data. Scatter plot showing the process of filtering undertaken on raw proteomics data (see Materials and Methods) in order to generate a final list of 195 proteins considered to be modified in SMA Schwann cells compared to control Schwann cells. The left column shows all proteins identified by the Progenesis label-free proteomics software (n = 663 proteins in total) in both control and Schwann cells, with the relative expression levels between samples represented as a ratio (SMA/Control). The solid grey bars indicate the 20% cut off threshold for being up-regulated or down-regulated in SMA cells compared to controls. The right column shows the proteins remaining in the data set following filtering (e.g., that were either up- or down-regulated by >20% and were identified by at least 2 peptides (n = 195 proteins in total)).

Immunocytochemical Analysis of Primary Schwann Cell Cultures

Cells were fixed with 4% PFA for 10 min (min) and permeabilized in ice-cold methanol for 15 min before being blocked in a solution of 1% BSA/PBS for 1 h before a 1 h incubation in primary antibodies against β-catenin (mouse, 1:50; BD transduction), Uba1 (mouse, 1:50; abcam), or MPZ (mouse, 1:1000; gift). After washing with 1% BSA in PBS, cells were incubated for 1 h in a solution of donkey antimouse secondary antibody conjugated to Cy3 (1:250; Jackson Research Laboratories). Following several final washes in PBS, cells were incubated for 10 min with TOPRO-3 (1:500; Life Technology) to label cell nuclei, before being coverslipped using Mowiol (Calbiochem). Fluorescent images of immunocytochemically labeled Schwann cells were captured using a Zeiss 710 laser-scanning confocal microscope (40× objective; 1.4NA). Protein labeling intensities were quantified using an established protocol.6 Briefly, protein levels were quantified in individual cells by generating confocal micrographs using identical microscope settings, ensuring that signal from the brightest cells was not saturated. Quantitative measurements of signal intensity were then obtained using the point analysis tool in ImageJ software. All data were collected into Microsoft Excel and analyzed using GraphPad Prism software (specific statistical tests used for each comparison are detailed in the text). For all statistical analyses, P < 0.05 was considered to be significant.



RESULTS

Label-Free Proteomics Analysis of the Schwann Cell Proteome Reveals Widespread Disruption When SMN Levels Are Reduced

We previously demonstrated that isolated Schwann cells derived from SMA mice had lowered levels of SMN protein and failed to respond normally to differentiation cues in vitro, contributing to perturbations in myelination and extracellular matrix composition in peripheral nerve in vivo.6 In particular, we identified 72 h postdifferentiation in vitro as a time point at which the molecular responses required for myelination had been instigated in control Schwann cells (but, importantly, significant synthesis of major myelin proteins had yet to occur) and were perturbed in SMA Schwann cells.6 In order to identify proteins and pathways underlying the deficient differentiation response in SMA Schwann cells in an unbiased manner, we used label-free proteomics screens to quantify and compare the proteome of SMA versus control Schwann cells (Figure 1). C

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Table 1. Proteins with Increased Expressiona in SMA Schwann Cells Compared to Control Schwann Cells gene name Rab11b Ptrf Me1 Hist1h2bj; Hist1h2bn; Hist1h2bf; Hist1h2bl Nap1l1 Surf4 Crlf1 Cald1 Uchl1 Prdx1 Hyou1 S100a10 Cct2 Kpnb1 Hspa9 Inf 2 Sod1 Sorbs2 Dbn1 S100a4 Hadha Gpi1 Dnaja2 Psmc1 Rtn4 Mtap Aldh1a1 Anxa1 Spna2 Col1a2 Gnb2 Alb Capg Fmr1 Lasp1 Txnrd1 Hk1 Serpinb6a Cf l1 Ctnna1 Plod2 Hspd1 Lamc1 Dnaja1 Spnb2 Actr3 Atp5a1 Aldoa Txnl1 Rpn2 Clic1 Asah1 Hist1h4 LOC100047183 Col1a1

protein name

accession number

peptides (unique)

fold change

Anova (p value)

protein coverage

Ras-related protein Rab-11B Polymerase I and transcript release factor NADP-dependent malic enzyme Histone H2B type 1-F/J/L

IPI00135869 IPI00117689 IPI00128857 IPI00114642

2 2 3 3

41.92 28.47 25.09 20.20

2.25 1.29 9.71 1.10

× × × ×

10−06 10−05 10−07 10−07

15.2 6.8 6.5 11.8

Nucleosome assembly protein 1-like 1 Surfeit locus protein 4 Cytokine receptor-like factor 1 caldesmon 1 Ubiquitin carboxyl-terminal hydrolase isozyme L1 Peroxiredoxin-1 Hypoxia up-regulated protein 1 Protein S100-A10 T-complex protein 1 subunit beta Importin subunit beta-1 Stress-70 protein, mitochondrial Isoform 1 of Inverted formin-2 Superoxide dismutase [Cu−Zn] Uncharacterized protein Isoform A of Drebrin Protein S100-A4 Trifunctional enzyme subunit alpha, mitochondrial Glucose-6-phosphate isomerase DnaJ homologue subfamily A member 2 26S protease regulatory subunit 4 Isoform 1 of Reticulon-4 S-methyl-5′-thioadenosine phosphorylase Retinal dehydrogenase 1 Annexin A1 Isoform 2 of Spectrin alpha chain, brain Collagen alpha-2(I) chain Guanine nucleotide-binding protein G(I)/G(S)/G (T) subunit beta-2 Serum albumin Macrophage-capping protein Isoform ISO3 of Fragile X mental retardation protein 1 homologue LIM and SH3 domain protein 1 Isoform 2 of Thioredoxin reductase 1, cytoplasmic Isoform HK1-SA of Hexokinase-1 Serpin B6 Putative uncharacterized protein Catenin alpha-1 Procollagen-lysine,2-oxoglutarate 5-dioxygenase 2 isoform 1 Isoform 1 of 60 kDa heat shock protein, mitochondrial laminin subunit gamma-1 precursor DnaJ homologue subfamily A member 1 Isoform 1 of Spectrin beta chain, brain 1 Actin-related protein 3 ATP synthase subunit alpha, mitochondrial fructose-bisphosphate aldolase A isoform 1 Thioredoxin-like protein 1 Dolichyl-diphosphooligosaccharide–protein glycosyltransferase subunit 2 Chloride intracellular channel protein 1 Acid ceramidase Histone H4 Protein AHNAK2-like Isoform 1 of Collagen alpha-1(I) chain

IPI00123199 IPI00133249 IPI00408751 IPI00122450 IPI00313962 IPI00121788 IPI00123342 IPI00222555 IPI00320217 IPI00323881 IPI00133903 IPI00678133 IPI00130589 IPI00177047 IPI00135475 IPI00124096 IPI00223092 IPI00228633 IPI00136251 IPI00133428 IPI00469392 IPI00132096 IPI00626662 IPI00230395 IPI00753793 IPI00222188 IPI00162780

4 2 2 6 3 7 2 2 3 2 4 3 2 2 4 2 3 2 3 3 6 2 6 5 15 2 2

12.40 10.17 8.26 8.14 6.68 6.67 5.97 5.84 5.03 4.44 3.66 3.62 3.53 3.42 3.39 3.34 3.20 3.18 3.16 3.14 3.09 3.07 3.06 3.03 2.90 2.77 2.67

3.38 7.08 6.22 2.29 2.89 4.52 3.11 1.20 4.44 3.72 1.29 6.14 7.83 1.86 1.23 4.26 3.97 1.25 1.83 9.42 1.51 2.87 4.87 7.18 6.87 1.92 5.53

× × × × × × × × × × × × × × × × × × × × × × × × × × ×

10−05 10−05 10−06 10−05 10−06 10−06 10−04 10−04 10−05 10−05 10−04 10−04 10−06 10−04 10−03 10−04 10−05 10−04 10−03 10−05 10−04 10−04 10−05 10−05 10−05 10−04 10−05

23.2 11.1 8.8 19.1 23.2 29.5 3.8 26.3 9.3 2.7 11.6 5.1 17.8 3.0 9.0 22.1 5.7 4.9 10.9 11.6 13.0 12.2 14.0 18.3 11.5 6.1 9.5

IPI00131695 IPI00136906 IPI00227005

3 4 2

2.65 2.61 2.60

4.69 × 10−05 1.23 × 10−05 2.18 × 10−03

6.1 11.7 3.8

IPI00125091 IPI00469251 IPI00283611 IPI00121471 IPI00407543 IPI00112963 IPI00123758

2 2 2 4 2 2 2

2.52 2.51 2.51 2.48 2.47 2.37 2.35

1.84 2.00 1.19 8.35 5.88 6.64 1.05

10−04 10−02 10−04 10−07 10−04 10−04 10−04

8.0 8.4 2.6 13.6 12.2 3.5 3.1

IPI00308885

4

2.15

9.32 × 10−04

11.9

IPI01027808 IPI00132208 IPI00319830 IPI00115627 IPI00130280 IPI00856379 IPI00266281 IPI00475154

2 2 18 4 4 6 2 3

2.15 2.14 2.03 2.01 1.94 1.89 1.81 1.75

1.44 1.99 7.28 5.79 4.07 2.87 8.53 2.37

× × × × × × × ×

10−04 10−04 10−05 10−05 10−05 10−05 10−04 10−04

2.5 11.3 11.0 11.5 12.7 22.7 13.5 8.6

IPI00130344 IPI00125266 IPI00407339 IPI00988375 IPI00329872

2 3 4 5 10

1.75 1.74 1.71 1.68 1.64

3.42 1.75 2.18 2.01 4.97

× × × × ×

10−03 10−03 10−04 10−03 10−05

18.1 7.3 21.3 8.9 14.0

D

× × × × × × ×

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Table 1. continued gene name Gstp1 Cdc42 Dhx9 Anxa2 Hnrnpm Anxa6 Eif4a1 Cct8 Anxa5 Pfn1 Gsn Atp5b Ywhag Plec Pgd Rpsa; LOC100505031 Nedd4 Calm2; Calm1; Calm3 Akap12 Hnrnpk Lmna Canx Tcp1 Rab1 Flna Serpinh1 Hspa5 a

protein name

peptides (unique)

fold change

Anova (p value)

protein coverage

IPI00555023 IPI00113849

2 2

1.62 1.61

7.70 × 10−04 2.05 × 10−03

14.8 13.8

IPI00339468 IPI00468203 IPI00918137 IPI00554894 IPI00118676 IPI00469268 IPI00317309 IPI00224740 IPI00117167 IPI00468481 IPI00230707 IPI00229509 IPI00466919

2 10 3 11 4 2 6 4 6 7 2 27 4

1.59 1.58 1.55 1.54 1.51 1.51 1.50 1.47 1.46 1.45 1.42 1.41 1.40

8.87 1.08 5.98 8.75 1.97 4.75 2.17 2.68 5.64 2.56 2.09 8.83 2.04

10−03 10−04 10−04 10−04 10−04 10−03 10−02 10−04 10−04 10−04 10−03 10−04 10−03

2.2 35.6 7.1 26.0 9.0 9.7 33.8 38.6 14.9 23.3 15.1 8.9 14.7

accession number

Glutathione S-transferase P 1 Isoform 2 of Cell division control protein 42 homologue Uncharacterized protein Annexin A2 Uncharacterized protein Annexin A6 Eukaryotic initiation factor 4A-I T-complex protein 1 subunit theta Annexin A5 Profilin-1 Isoform 1 of Gelsolin ATP synthase subunit beta, mitochondrial 14-3-3 protein gamma Plectin isoform 1b2alpha 6-phosphogluconate dehydrogenase, decarboxylating 40S ribosomal protein SA E3 ubiquitin-protein ligase NEDD4 Uncharacterized protein Isoform 1 of A-kinase anchor protein 12 36 kDa protein Isoform 2 of Heterogeneous nuclear ribonucleoprotein K Isoform A of Prelamin-A/C Calnexin Isoform 1 of T-complex protein 1 subunit alpha Ras-related protein Rab-1A Isoform 1 of Filamin-A Serpin H1 Isoform 1 of General vesicular transport factor p115

× × × × × × × × × × × × ×

IPI00123604 IPI00462445; IPI00403303 IPI00467841 IPI00123709 IPI00988228 IPI00224575

2 4

1.38 1.37

8.22 × 10−04 4.04 × 10−03

3 11 3 2

1.35 1.34 1.33 1.32

3.84 2.12 2.50 8.86

× × × ×

10−04 10−03 10−03 10−04

28 15.6 13.7 6.6

IPI00620256 IPI00119618 IPI00459493 IPI00114560 IPI00131138 IPI00114733 IPI00319992

8 2 5 1 11 7 8

1.32 1.31 1.28 1.25 1.24 1.23 1.21

1.97 6.77 1.38 4.76 1.85 1.21 1.99

× × × × × × ×

10−03 10−04 10−02 10−03 10−02 10−03 10−02

15.2 4.7 11.7 15.9 9.1 20.1 16.4

11 6.1:2.1

Expression > 20%.

Robust Schwann cell isolation and purification techniques were used to establish in vitro preparations of cells from the pooled brachial plexii and sciatic nerves SMA and control littermate mice with >97% purity.6 Schwann cell cultures were obtained 72 h after triggering differentiation through the addition of dbCAMP and NRG1 to the culture media (N = 3 cultures per genotype, n = 5 SMA mice or 5 littermate control mice pooled per culture). For each genotype three replicate runs were performed. Raw mass spectrometry data was uploaded to Progenesis software for analysis. Based on its minimum distortion pattern, sample three from the SMA Schwann cell cultures was automatically assigned by the Progenesis software as the reference data set for further comparative analyses. All other MS/MS spectra were then automatically aligned to the reference run, with minimal manual alignment correction where required. Alignment scores of the runs were 96.2% for SMA sample 1, 87.2% for SMA sample 2, 80.7% for Control 1, 80.1% for Control 2, and 67.4% for Control 3. All ions with retention time of less than 19.589 and more than 138.961 min were excluded due to lack of separation. After filtering by retention time and charge 53 589 of the original 67 883 features were excluded. A further filter using a “rank” value of a maximum of 3 was applied to further reduce the number of MS/MS assigned to each feature. MS/MS data for candidate peptides (21 505 peptides) were exported to the Mascot database for comparison to known peptides and identification of corresponding proteins. 14 294

peptides were assign to proteins. Through this process, 663 proteins were identified and were reimported into Progenesis software for further filtering: 195 proteins were identified by two or more unique peptides and demonstrated a greater than 20% difference in expression between SMA and control Schwann cell samples (Figure 2). Statistical analysis applied to the data was carried out by the integrated statistical module of Progenesis software, as previously described.16 This process therefore led to the identification of 83 proteins that were considered to have increased levels in SMA Schwann cells and 112 proteins with decreased expression (Tables 1 and 2). Bioinformatic Analysis of Label-Free Proteomics Data Reveals Signficant Disruption of a Number of Core Functional Pathways in SMA Schwann Cells

In an initial attempt to establish any functional clustering of differentially expressed proteins in Schwann cells from SMA mice, a systems level analysis of label-free proteomics data was performed using Ingenuity Pathway Analysis (IPA) software. IPA software is populated and annotated with data from the published scientific literature to allow analysis of candidate molecules with respect to their known functions in biological systems. A total of 183 out of 195 proteins identified were present within the IPA databases for analyses of functional clustering. Interestingly, 64 of the proteins identified as having modified expression levels in SMA Schwann cells had previously been E

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Table 2. Proteins with Decreased Expressiona in SMA Schwann Cells Compared to Control Schwann Cells gene name Krt78 Wdr1 Adh5 Gorasp2 Dsg1b Rps8 Jup Rnh1 Pgam1 Dsp Psap Rpl10 Fhl2 Eef1g Rpl12 Pls3 Prmt1 Sqstm1 Glud1 Uggt1 Gnb2l1 Hsph1 Gf pt1 Vdac2 Vwa5a Add1 Rps4x Sugt1 Mtap1b Coro1c Fn1 Dnm2 Stat3 Copg Nars Aldh7a1 Sacm1l Lta4h Slc25a12 Eif 2s3x Rpl10a Hnrnpu Ddah2 Pcbp1 Cttn Ap2a2 Mdh1 Npc2 Adam10 Capzb Sncg Sec23a Fkbp10 Lepre1 Ctsb Ass1 Sucla2

protein name Keratin Kb40 WD repeat-containing protein 1 Alcohol dehydrogenase class-3 Isoform 1 of Golgi reassembly stacking protein 2 Desmoglein-1-beta 40S ribosomal protein S8 Junction plakoglobin Ribonuclease inhibitor Phosphoglycerate mutase 1 Desmoplakin Sulfated glycoprotein 1 60S ribosomal protein L10 Four and a half LIM domains protein 2 Elongation factor 1-gamma 60S ribosomal protein L12 Plastin-3 Isoform 1 of Protein arginine N-methyltransferase 1 Isoform 1 of Sequestosome-1 Glutamate dehydrogenase 1, mitochondrial UDP-glucose:glycoprotein glucosyltransferase 1 Guanine nucleotide-binding protein subunit beta-2-like 1 Isoform HSP105-alpha of Heat shock protein 105 kDa Isoform 1 of Glucosamine–fructose-6-phosphate aminotransferase [isomerizing] 1 Voltage-dependent anion-selective channel protein 2 Von Willebrand factor A domain-containing protein 5A Isoform 1 of Alpha-adducin 40S ribosomal protein S4, X isoform Suppressor of G2 allele of SKP1 homologue Microtubule-associated protein 1B Coronin-1C Fibronectin Isoform 1 of Dynamin-2 Isoform Stat3B of Signal transducer and activator of transcription 3 Coatomer subunit gamma Asparaginyl-tRNA synthetase, cytoplasmic Isoform 1 of Alpha-aminoadipic semialdehyde dehydrogenase Phosphatidylinositide phosphatase SAC1 Leukotriene A-4 hydrolase Calcium-binding mitochondrial carrier protein Aralar1 Eukaryotic translation initiation factor 2 subunit 3, X-linked 60S ribosomal protein L10a Heterogeneous nuclear ribonucleoprotein U N(G),N(G)-dimethylarginine dimethylaminohydrolase 2 Poly(rC)-binding protein 1 Src substrate cortactin AP-2 complex subunit alpha-2 Malate dehydrogenase, cytoplasmic Epididymal secretory protein E1 Disintegrin and metalloproteinase domain-containing protein 10 Isoform 2 of F-actin-capping protein subunit beta Gamma-synuclein Protein transport protein Sec23A Peptidyl-prolyl cis−trans isomerase FKBP10 Isoform 1 of Prolyl 3-hydroxylase 1 Cathepsin B Argininosuccinate synthase Succinyl-CoA ligase [ADP-forming] subunit beta, mitochondrial

peptides (unique)

fold change

2 3 2 2 3 2 7 3 4 10 4 3 3 3 5 2 2 2 3 2 3 4 2

−8.58 −8.56 −7.34 −6.14 −5.70 −5.62 −5.45 −5.09 −4.83 −4.72 −4.69 −4.63 −4.59 −4.57 −4.49 −4.06 −4.00 −3.94 −3.88 −3.80 −3.76 −3.75 −3.58

1.79 6.40 6.56 9.25 5.19 3.66 2.30 1.92 7.21 2.39 3.80 8.18 2.40 6.51 3.39 2.40 8.71 1.04 6.57 2.01 1.24 1.10 7.21

× × × × × × × × × × × × × × × × × × × × × × ×

10−08 10−05 10−06 10−05 10−05 10−04 10−07 10−06 10−07 10−06 10−06 10−05 10−04 10−07 10−06 10−04 10−05 10−03 10−06 10−04 10−04 10−04 10−03

1.4 9.8 14.2 7.7 1.5 12.1 11.2 8.5 25.1 3.2 8.9 21.5 12.6 7.2 49.6 6.8 7.2 11.3 9.5 2.0 15.2 7.7 4.2

IPI00122547 IPI00221817;IPI00460122 IPI00136000 IPI00331092 IPI00408957 IPI00130920 IPI00124820 IPI00113539 IPI00131445 IPI00227814

2 4 3 2 2 3 2 2 3 2

−3.57 −3.56 −3.48 −3.38 −3.35 −3.28 −3.25 −3.24 −3.06 −3.05

2.92 1.17 2.58 2.25 6.99 3.63 2.36 4.60 1.85 1.31

× × × × × × × × × ×

10−04 10−04 10−05 10−04 10−04 10−04 10−04 10−04 10−04 10−04

10.5 6.0:1.0 10.3 10.0 7.7 2.7 5.1 1.4 5.0 3.5

IPI00223437 IPI00223415 IPI00230084 IPI00109221 IPI00229527 IPI00308162; IPI00135651 IPI00230415; IPI00230416 IPI00849927 IPI00458583 IPI00336881 IPI00128904 IPI00118143 IPI00310131 IPI00336324 IPI00129186 IPI00131881

2 5 2 2 2 2 2 2 2 2 2 2 2 3 2 2

−3.03 −3.03 −3.00 −2.99 −2.98 −2.96 −2.95 −2.93 −2.87 −2.87 −2.85 −2.84 −2.81 −2.79 −2.78 −2.75

3.68 1.38 5.72 5.11 5.46 1.28 1.90 1.82 3.16 5.08 2.86 4.32 4.94 7.42 6.63 8.39

× × × × × × × × × × × × × × × ×

10−04 10−05 10−05 10−03 10−03 10−04 10−05 10−07 10−06 10−05 10−06 10−05 10−04 10−05 10−06 10−05

5.7 10 5.9 4.6 4.3 4.0; 1.9 6.8; 6.4 12.8 3.7 14.3 7.8 7.3 2.3 12.3 18.4 3.7

IPI00269481 IPI00271440 IPI00123349 IPI00122493 IPI00109205 IPI00113517 IPI00134746 IPI00261627

3 3 4 2 2 3 6 2

−2.74 −2.71 −2.71 −2.70 −2.70 −2.68 −2.65 −2.62

1.11 1.58 7.27 1.36 7.44 4.55 1.17 7.02

× × × × × × × ×

10−05 10−06 10−05 10−04 10−05 10−05 10−06 10−06

11.7 31.8 7.2 4.4 3.3 17.9 15.7 4.8

accession number IPI00348328 IPI00314748 IPI00555004 IPI00165716 IPI00380460 IPI00466820 IPI00229475 IPI00313296 IPI00457898 IPI00553419 IPI00321190 IPI00474637 IPI00118205 IPI00318841 IPI00849793 IPI00115528 IPI00120495 IPI00133374 IPI00114209 IPI00762897 IPI00317740 IPI00123802 IPI00406371

F

Anova (p value)

protein coverage

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Table 2. continued gene name Psma4 P4ha2 Itgb1 Copa Eif 3c Eif 2s2 Tpp2 Erp44 Rpl4 Myl6 Epb4.1l2 Sec31a Igf 2r Pdcd6ip Ap2a1 Gapdh Golgb1 Rplp2 Anxa7 Nucks1 Rps3 Rplp0 Tuf m Prx Uso1 P4ha1 Hnrnpa3 Uba1 Gnb1 Rps17 Nomo1 Prdx2 Rab6 Vcp Txndc5 Eef1b2 Mvp Copb1 Sept2 Tkt Psmd1 Pdia4 Gdi2 Ywhaz Hsp90b1 Hspa4 Rcn2 Pgk1 Eef 2 Myo1c Krt79 Col3a1 Vdac1 Pcyox1 a

peptides (unique)

fold change

IPI00277001 IPI00120100 IPI00132474 IPI00229834 IPI00321647 IPI00116302 IPI00227843 IPI00134058 IPI00111412 IPI00354819 IPI00309481 IPI00853859 IPI00308971 IPI00323483 IPI00108780 IPI00273646 IPI00929857 IPI00139795 IPI00114017 IPI00341869

2 5 2 3 3 3 2 2 3 3 3 2 2 2 2 5 2 2 2 2

−2.62 −2.56 −2.55 −2.55 −2.50 −2.46 −2.46 −2.44 −2.44 −2.40 −2.39 −2.38 −2.35 −2.35 −2.33 −2.30 −2.29 −2.28 −2.26 −2.24

4.78 2.28 7.82 3.55 3.90 1.71 2.86 4.68 3.05 2.18 2.85 9.61 4.46 6.97 1.26 2.01 1.02 6.98 6.06 1.04

× × × × × × × × × × × × × × × × × × × ×

10−06 10−05 10−05 10−03 10−04 10−04 10−03 10−04 10−04 10−06 10−04 10−06 10−03 10−06 10−03 10−05 10−03 10−05 10−05 10−04

9.6 11.5 3.6 3.7 3.2 15.2 3.9 5.6 8.6 24.4 5.7 2.6 0.9 3.6 2.2 23.8 0.8 31.2 6.6 17.6

IPI00134599 IPI00314950 IPI00274407 IPI00469952 IPI00128071 IPI00399959 IPI00269661 IPI00123313 IPI00120716

2 4 2 2 4 6 2 4 3

−2.24 −2.23 −2.20 −2.18 −2.16 −2.15 −2.06 −1.99 −1.87

2.18 2.44 2.90 2.78 6.99 1.07 1.60 4.40 9.59

× × × × × × × × ×

10−03 10−05 10−03 10−04 10−04 10−03 10−03 10−05 10−04

10.7 24.3 7.1 2.2 5.6 13.5 7.7 5.9 8.9

IPI00465880 IPI00222429 IPI00117910 IPI00116697 IPI00622235 IPI00163011 IPI00320208 IPI00111258 IPI00120503 IPI00114945 IPI00137409 IPI00267295 IPI00271951 IPI00122565 IPI00116498 IPI00129526 IPI00331556 IPI00474959 IPI00555069 IPI00466069 IPI00467172 IPI00124499 IPI00129571 IPI00122549

3 2 2 2 7 4 3 2 3 4 3 3 4 3 5 4 4 2 6 10 2 1 9 2

−1.83 −1.71 −1.70 −1.65 −1.64 −1.61 −1.59 −1.59 −1.56 −1.55 −1.55 −1.54 −1.52 −1.51 −1.49 −1.48 −1.46 −1.43 −1.41 −1.37 −1.35 −1.35 −1.33 −1.31

9.14 3.78 1.28 4.74 4.81 2.28 1.63 5.09 1.87 1.64 1.32 1.01 2.50 2.12 5.36 2.53 9.24 1.91 2.62 2.09 3.62 3.52 7.54 5.55

× × × × × × × × × × × × × × × × × × × × × × × ×

10−04 10−04 10−03 10−03 10−05 10−03 10−03 10−03 10−04 10−05 10−05 10−04 10−05 10−03 10−04 10−03 10−04 10−02 10−04 10−04 10−03 10−03 10−04 10−03

24.7 2.0 16.5 12.1 14.3 12.6 23.9 2.8 4.4 16.1 9.3 6.4 10.7 8.2 22.5 9.5 5.9 9.4 31.3 18.2 2.2 8.2 11.0 16.9

IPI00460063

2

−1.21

1.03 × 10−02

7.2

protein name Proteasome subunit alpha type-4 Isoform IIb of Prolyl 4-hydroxylase subunit alpha-2 Integrin beta-1 Coatomer subunit alpha Eukaryotic translation initiation factor 3 subunit C Eukaryotic translation initiation factor 2 subunit 2 Isoform Short of Tripeptidyl-peptidase 2 Endoplasmic reticulum resident protein 44 60S ribosomal protein L4 Isoform Smooth muscle of Myosin light polypeptide 6 Band 4.1-like protein 2 Isoform 2 of Protein transport protein Sec31A Cation-independent mannose-6-phosphate receptor Isoform 3 of Programmed cell death 6-interacting protein Isoform A of AP-2 complex subunit alpha-1 Glyceraldehyde-3-phosphate dehydrogenase Golgi autoantigen, golgin subfamily b, macrogolgin 1 60S acidic ribosomal protein P2 Annexin A7 Nuclear ubiquitous casein and cyclin-dependent kinases substrate 40S ribosomal protein S3 60S acidic ribosomal protein P0 Isoform 1 of Elongation factor Tu, mitochondrial Isoform 1 of Periaxin Isoform 1 of General vesicular transport factor p115 Isoform 2 of Prolyl 4-hydroxylase subunit alpha-1 Isoform 1 of Heterogeneous nuclear ribonucleoprotein A3 Ubiquitin-like modifier-activating enzyme 1 Guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-1 40S ribosomal protein S17 Nodal modulator 1 Peroxiredoxin-2 Isoform 1 of Ras-related protein Rab-6A Transitional endoplasmic reticulum ATPase Thioredoxin domain-containing protein 5 Elongation factor 1-beta Major vault protein Coatomer subunit beta Septin-2 Transketolase 26S proteasome non-ATPase regulatory subunit 1 Protein disulfide-isomerase A4 Isoform 1 of Rab GDP dissociation inhibitor beta 14-3-3 protein zeta/delta Endoplasmin Heat shock 70 kDa protein 4 Putative uncharacterized protein Phosphoglycerate kinase 1 Elongation factor 2 Isoform 2 of Myosin-Ic Keratin, type II cytoskeletal 79 Collagen alpha-1(III) chain Isoform Pl-VDAC1 of Voltage-dependent anion-selective channel protein 1 Prenylcysteine oxidase

accession number

Anova (p value)

protein coverage

Expression > 20%.

implicated in a range of neurological disorders including skeletal and muscular disorders. This suggests that the protein

modifications occurring in SMA Schwann cells were likely to be similar to molecular alterations occurring in a range of other G

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Table 3. IPA-Generated Identification of Canonical Molecular Pathways Significantly Modified in SMA Schwann Cells Compared to Control Schwann Cells name

p value

ratio

genes

Gluconeogenesis I Protein Ubiquitination Pathway

1.75 × 10−07 8.03 × 10−07

6/48(0.125) 14/270 (0.052)

Caveolar-mediated Endocytosis Signaling Huntington’s Disease Signaling EIF2 Signaling

1.38 × 10−06

8/85 (0.094)

ALDOA, GP1, MDH1, ME1, PGAM1, PGK1 DNAJA1, HSP90B1, HSPA4, HSPA5, HSPA9, HSPD1, HSPH1, PSMA4, PSMC1, PSMD1, SUGT1, UBA1, UCHLl.USOl ALB, COPA, COPB1, COPG1, DNM2, FLNA, ITGB1, PTRF

3.39 × 10−05 3.42 × 10−05

11/252(0.044) 10/201 (0.05)

AP2A2, ATP5B, CTSD, DNM2, GNB1, GNB2, GNB2L1, HSPA4, HSPA5, HSPA9, NSF EIF2S2, EIF3C/EIF3CL, EIF4A1, RPL4, RPL12, RPL10A, RPLP0, RPLP2, RPS3, EPS4X

Figure 3. IPA-generated network of ubiquitin/proteasome-related proteins modified in SMA Schwann cells. Ingenuity Pathway Analysis (IPA) network of ubiquitin/proteasome-related proteins incorporating 21 proteins found to have modified expression in SMA Schwann cells. Proteins within this network identified as being modified in SMA Schwann cells are indicated using colored shapes (red = increased levels in SMA Schwann cells; green = decreased levels in SMA Schwann cells). Solid connecting lines indicate the presence of a direct interaction and dashed connecting lines indicate the presence of an indirect interaction based on published evidence incorporated into IPA software. Note the presence of the 26S proteasome as a “hub” in the middle of the network (highlighted in blue, with immediate interactions indicated by blue connecting lines), alongside the presence of the 20S proteasome and key ubiquitination proteins Uba1 and Uchl1.

This clustering of a large proportion of the identified protein alterations into a few distinct functional pathways suggested that low levels of SMN led to specific, targeted downstream effects on a relatively restricted number of key cellular functions.

affected cell types in similar diseases. From the molecular and cellular perspective, IPA analysis highlighted significant disruption across a range of functional pathways in SMA Schwann cells. These included more than 90 proteins involved in cellular growth and proliferation pathways, as well as more than 90 proteins involved in cell death and survival pathways. H

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Figure 4. Validation of reduced levels of Uba1 in Schwann cells isolated from SMA mice. (a) Representative confocal micrographs of differentiated Schwann cells from control mice (top panels) and SMA mice (lower panels) immunolabeled with antibodies against Uba1 (red) with cell nuclei counterstained with TOPRO3 (blue). Uba1 levels were noticeably lower in SMA-derived Schwann cells. (b) Bar graph showing significant reduction of Uba1 levels in SMA-derived Schwann cells (*** P < 0.001; two-tailed, unpaired t test; N = 4 cultures per genotype, 2 fields of view imaged per culture, >25 cells quantified per field of view).

Figure 5. No change in β-catenin levels in Schwann cells isolated from SMA mice. (a) Representative confocal micrographs of differentiated Schwann cells from control mice (top panels) and SMA mice (lower panels) immunolabeled with antibodies against β-catenin (red) with cell nuclei counterstained with TOPRO3 (blue). β-catenin levels and distribution appeared identical between SMA-derived and control Schwann cells. (b) Bar graph showing no significant difference in β-catenin levels between SMA-derived and control Schwann cells (ns P > 0.05; two-tailed, unpaired t test; N = 4 cultures per genotype, 2 fields of view imaged per culture, >25 cells quantified per field of view).

Supporting Information Figure 1). Similar changes in levels of these two proteins have previously been reported in spinal cord and skeletal muscle from SMA mice13 and fibroblasts from SMA patients,20 with Uchl1 upregulation recently found to be a major compensatory response to Uba1 depletion.21 More importantly, however, mutations in the UBA1 gene are sufficient to cause a rare form of SMA in human patients.22 Thus, when taken together with the published literature, bioinformatics analysis of the label-free proteomic data pointed toward perturbations in ubiquitination pathways as a major potential contributor to Schwann cell dysfunction in SMA.

To further explore the molecular pathways disrupted in SMA Schwann cells leading to perturbations in key functional pathways, we performed a canonical molecular pathways analysis of the proteomic data using IPA. This analysis revealed significant modifications to several canonical molecular pathways in SMA Schwann cells (Table 3). Of these identified pathways, the one with the largest number of contributing proteins (14) was ubiquitination (Table 3). This finding was of particular interest because several recent studies have demonstrated that ubiquitination pathways play a major role in regulating SMN protein stability and turnover,18,19 as well as being a major driver of motor neuron and skeletal muscle pathology in SMA.13 An IPA-generated functional network of interacting proteins implicated in ubiquitination pathways confirmed modifications in expression levels for a range of core ubiquitination proteins (Figure 3). Of particular note were increased levels of ubiquitin carboxyl-terminal hydrolase L1 (Uchl1) in SMA Schwann cells and decreased levels of ubiquitin activator-like modifier E1 (Uba1) (Figure 3,

Loss of Uba1 in SMA Schwann Cells Contributes to Myelination Defects via a β-Catenin-Independent Pathway

Given the potential importance of Uba1 to SMA pathogenesis,13,22 we next wanted to validate and extend our proteomic data by measuring Uba1 protein levels in freshly prepared SMA and control Schwann cells using immunocytochemical techniques at 72 h postdifferentiation.6 These I

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Figure 6. Pharmacological inhibition of Uba1 is sufficient to disrupt myelin protein expression in Schwann cells (a) Representative confocal micrographs of differentiated Schwann cells from control mice (upper panels), control mice treated with the Uba1 inhibitor UBEI-41 (middle panels), and from SMA mice (lower panels) immunolabeled with antibodies against myelin protein MPZ (red) with cell nuclei counterstained with TOPRO3 (blue) 120 h postdifferentiation. MPZ levels were noticeably lower in both UBEI-41 treated and SMA-derived Schwann cells. (b) Bar graph showing significant reduction of MPZ levels in both UBEI-41 treated and SMA-derived Schwann cells compared to control Schwann cells (*** P < 0.001; “ns” P > 0.05; ANOVA with Tukey’s posthoc test; N = 4 cultures per genotype, 2 fields of view imaged per culture, >25 cells quantified per field of view).

experiments confirmed a ∼50% loss in levels of Uba1 in SMA Schwann cells (Figure 4), closely mirroring changes in Uba1 levels observed elsewhere in the neuromuscular system in SMA mice.13 Low levels of Uba1 have been shown to cause modified ubiquitination and subsequent accumulation of β-catenin in both spinal cord and skeletal muscle in SMA mice, but not in other cells, tissues, and organs.13 Thus, Uba1 appears to influence both β-catenin-dependent and β-catenin-independent downstream pathways. β-Catenin was putitavely present in our label-free proteomic data set but did not pass the strict filtering criteria to be included for further analysis, as it was only identified by one peptide. Therefore, to establish whether βcatenin was being modified as a consequence of Uba1 disruption in Schwann cells we repeated our immunocytochemical labeling experiments in SMA and littermate control Schwann cells, but using antibodies against β-catenin. This analysis showed that β-catenin levels remained unchanged in SMA Schwann cells (Figure 5). Finally, we wanted to establish whether suppression of Uba1 was sufficient to replicate the defective differentiation and myelination phenotype observed in SMA Schwann cells at 120 h postdifferentiation in vitro. Therefore, we examined the consequences of pharmacological inhibition of Uba1 on the ability of control, wild-type Schwann cells to respond to myelination cues by generating myelin proteins. Control Schwann cells were exposed to UBEI-41, a cell-permeable Uba1 inhibitor (10 μM), for 24 at 96 h postdifferentiation and myelin protein zero (MPZ) levels were measured as a readout of myelination. MPZ levels were robustly increased in healthy control Schwann cells 120 h postdifferentiation (Figure 6). In

stark contrast, MPZ levels were significantly less elevated in UBEI-41 treated Schwann cells, with MPZ levels similar to those observed in untreated SMA Schwann cells (Figure 6). Thus, pharmacological suppression of Uba1 phenocopied the differentiation/myelination defects observed in SMA Schwann cells due to low SMN levels.



DISCUSSION In this study, we used label-free proteomics approaches to reveal robust modifications to the proteome of Schwann cells isolated from SMA mice. These findings, therefore, significantly extend previous morphological data6 by demonstrating SMNdependent disruption of Schwann cell function in SMA at the molecular level, through targeted disruption of several core cellular pathways, including ubiquitination. The defects in ubiquitin-dependent pathways we identified in SMA Schwann cells closely mirrored those previously shown to contribute to motor neuron and skeletal muscle pathology in SMA.13 This provides further experimental evidence in support of a major role for ubiquitin-like modifier activating enzyme 1 (Uba1) in SMA pathogenesis. Taken together, these findings demonstrate an important role for SMN protein and ubiquitin-dependent pathways in maintaining Schwann cell homeostasis and provide significant additional experimental evidence supporting a key role for ubiquitin pathways, and Uba1 in particular, in driving SMA pathogenesis across a broad range of cells and tissues. Our demonstration of robust molecular defects in Schwann cells during the pathogenesis of SMA adds further weight to the idea that glial cells play a crucial role in the development, functionality and survival of the peripheral nervous system, including a critical role in regulating neurodegeneration.23,24 J

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Notes

Given the important role that myelinating Schwann cells play in regulating the form and function of lower motor neurons in peripheral nerves,6,25 these data suggest that further studies into the contribution of Schwann cells to motor neuron diseases such as SMA are warranted, from both scientific and therapeutic perspectives. The finding that disruption to ubiquitin pathways, and Uba1 in particular, was a major feature of SMA Schwann cells provides additional experimental evidence in support of a key role for this protein in SMA pathogenesis. Previous work had demonstrated disruption of Uba1 levels in the spinal cord and skeletal muscle of SMA mice.13 Interestingly, however, we found that the downstream mediator of SMN/Uba1-dependent pathology in spinal cord and muscle, β-catenin, was not responsible for mediating defects in SMA Schwann cells. This is consistent with the proposal that fundamentally different molecular pathways drive neuromuscular and non-neuromuscular pathology in SMA,13 placing Schwann cells in the non-β-catenin-dependent category. An additional interesting observation we made when analyzing the proteomics data was the number of proteins identified as being modified in SMA Schwann cells that have previously been implicated in the pathogenesis of neuromuscular diseases. For example, mutations in Uba1 cause a rare form of non-SMN based SMA, X-linked infantile spinal muscular atrophy.21 Similarly, mutations in ASAH1 cause spinal muscular atrophy associated with progressive myoclonic epilepsy.26 The finding that the protein products of these two genes were altered in Schwann cells deficient in SMN protein suggests potential shared molecular mechanisms linking SMNdependent and SMN-independent forms of SMA. In addition, levels of plastin 3, a protective modifier of SMA,27 were found to be reduced 4-fold in SMA Schwann cells. Alongside modifications in levels of proteins linked to SMN-dependent and SMN-independent SMA, we also noted a 3.5-fold increase in levels of SOD1 in our SMA Schwann cells. SOD1 mutations are a well-established familial cause of adult-onset motor neuron disease (amyotrophic lateral sclerosis [ALS]28), with recent studies suggesting shared possible convergent mechanistic links between SMA and SOD1-dependent ALS.29 Thus, isolated Schwann cells from SMA mice may represent an attractive, homogeneous cell preparation in which to study divergent and convergent aspects of molecular pathways contributing to neuromuscular pathology, relevant to a wide range of human neurodegenerative conditions.



The authors declare no competing financial interest. ⊥ Joint senior authors.



ACKNOWLEDGMENTS The authors would like to thank Peter Rutherford and Derek Thomson for assistance with animal husbandry and Professor Archelos-Garcia for the gift of MPZ antibody. This work was supported by grants from the Muscular Dystrophy Campaign, the SMA Trust, and the Euan MacDonald Centre for Motor Neurone Disease Research to T.H.G. T.M.W. is currently a career-track fellow at the Roslin Institute supported by BBSRC ISPG funding. M.L.H. is supported by a Darwin trust Ph.D. scholarship, and L.G. is is supported by a BBSRC EastBio DTP scholarship.



(1) Lunn, M. R.; Wang, C. H. Spinal muscular atrophy. Lancet 2008, 371, 2120−2133. (2) Lefebvre, S.; Burglen, L.; Reboullet, S.; Clermont, O.; Burlet, P.; Viollet, L.; Benichou, B.; Cruaud, C.; Millasseau, P.; Zeviani, M.; Le Paslier, D.; Frézal, J.; Cohen, D.; Weissenbach, J.; Munnich, A.; Melki, J. Identification and characterization of a spinal muscular atrophydetermining gene. Cell 1995, 80, 155−165. (3) Burghes, A. H.; Beattie, C. E. Spinal muscular atrophy: why do low levels of survival motor neuron protein make motor neurons sick? Nat. Rev. Neurosci. 2009, 10, 597−609. (4) Lorson, C. L.; Hahnen, E.; Androphy, E. J.; Wirth, B. A single nucleotide in the SMN gene regulates splicing and is responsible for spinal muscular atrophy. Proc. Natl. Acad. Sci. U. S. A. 1999, 96, 6307− 6311. (5) Hamilton, G.; Gillingwater, T. H. Spinal muscular atrophy: going beyond the motor neuron. Trends Mol. Med. 2013, 19, 40−50. (6) Hunter, G.; Aghamaleky Sarvestany, A.; Roche, S. L.; Symes, R. C.; Gillingwater, T. H. SMN-dependent intrinsic defects in Schwann cells in mouse models of spinal muscular atrophy. Hum. Mol. Genet. 2014, 23, 2235−2250. (7) Zhang, Z.; Lotti, F.; Dittmar, K.; Younis, I.; Wan, L.; Kasim, M.; Dreyfuss, G. SMN deficiency causes tissue-specific perturbations in the repertoire of snRNAs and widespread defects in splicing. Cell 2008, 133, 585−600. (8) Lotti, F.; Imlach, W. L.; Saieva, L.; Beck, E. S.; Hao le, T.; Li, D. K.; Jiao, W.; Mentis, G. Z.; Beattie, C. E.; McCabe, B. D.; Pellizzoni, L. An SMN-dependent U12 splicing event essential for motor circuit function. Cell 2012, 151, 440−454. (9) Bäumer, D.; Lee, S.; Nicholson, G.; Davies, J. L.; Parkinson, N. J.; Murray, L. M.; Gillingwater, T. H.; Ansorge, O.; Davies, K. E.; Talbot, K. Alternative splicing events are a late feature of pathology in a mouse model of spinal muscular atrophy. PLoS Genet. 2009, 5, e1000773. (10) Praveen, K.; Wen, Y.; Matera, A. G. A Drosophila model of spinal muscular atrophy uncouples snRNP biogenesis functions of survival motor neuron from locomotion and viability defects. Cell Rep. 2012, 1, 624−631. (11) Sanchez, G.; Dury, A. Y.; Murray, L. M.; Biondi, O.; Tadesse, H.; El Fatimy, R.; Kothary, R.; Charbonnier, F.; Khandjian, E. W.; Côté, J. A novel function for the survival motoneuron protein as a translational regulator. Hum. Mol. Genet. 2013, 22, 668−684. (12) Fallini, C.; Bassell, G. J.; Rossoll, W. Spinal muscular atrophy: the role of SMN in axonal mRNA regulation. Brain Res. 2012, 1462, 81−92. (13) Wishart, T. M.; Mutsaers, C. A.; Riessland, M.; Reimer, M. M.; Hunter, G.; Hannam, M. L.; Eaton, S. L.; Fuller, H. R.; Roche, S. L.; Somers, E.; Morse, R.; Young, P. J.; Lamont, D. J.; Hammerschmidt, M.; Joshi, A.; Hohenstein, P.; Morris, G. E.; Parson, S. H.; Skehel, P. A.; Becker, T.; Robinson, I. M.; Becker, C. G.; Wirth, B.; Gillingwater, T. H. Dysregulation of ubiquitin homeostasis and β -catenin signaling

ASSOCIATED CONTENT

S Supporting Information *

Two supplementary tables containing Progenesis outputs for abundance of proteins and peptides within each sample, and one supplementary figure validating the increase in Uchl1 protein in SMA Schwann cells using Western blot. This material is available free of charge via the Internet at http:// pubs.acs.org.



REFERENCES

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel.: +44 (0) 131 650 3724. Fax: +44 (0) 131 650 4193. Address: College of Medicine and Veterinary Medicine, University of Edinburgh, Old Medical School, Teviot Place, Edinburgh, EH8 9XD, United Kingdom. K

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