Quantitative Proteome Profiling of CNS-Infiltrating Autoreactive CD4+

Article pubs.acs.org/jpr

Quantitative Proteome Profiling of CNS-Infiltrating Autoreactive CD4+ Cells Reveals Selective Changes during Experimental Autoimmune Encephalomyelitis Michelle E. Turvey,† Tomas Koudelka,#,‡ Iain Comerford,† Judith M. Greer,§ William Carroll,∥ Claude C. A. Bernard,⊥ Peter Hoffmann,*,‡ and Shaun R. McColl*,† †

Chemokine Biology Laboratory, School of Molecular and Biomedical Science, University of Adelaide and Centre for Molecular Pathology, South Australia 5005, Australia ‡ Adelaide Proteomics Centre, University of Adelaide, South Australia 5005, Australia § University of Queensland Centre for Clinical Research, Royal Brisbane & Women’s Hospital, Herston, Queensland 4029, Australia ∥ Department of Neurology, Sir Charles Gairdner Hospital, Nedlands, Western Australia 6009, Australia ⊥ Monash Immunology and Stem Laboratories, Monash University, Clayton, Victoria 3800, Australia S Supporting Information *

ABSTRACT: Experimental autoimmune encephalomyelitis (EAE) is a murine model of multiple sclerosis, a chronic neurodegenerative and inflammatory autoimmune condition of the central nervous system (CNS). Pathology is driven by the infiltration of autoreactive CD4+ lymphocytes into the CNS, where they attack neuronal sheaths causing ascending paralysis. We used an isotope-coded protein labeling approach to investigate the proteome of CD4+ cells isolated from the spinal cord and brain of mice at various stages of EAE progression in two EAE disease models: PLP139−151-induced relapsing-remitting EAE and MOG35−55induced chronic EAE, which emulate the two forms of human multiple sclerosis. A total of 1120 proteins were quantified across disease onset, peak-disease, and remission phases of disease, and of these 13 up-regulated proteins of interest were identified with functions relating to the regulation of inflammation, leukocyte adhesion and migration, tissue repair, and the regulation of transcription/translation. Proteins implicated in processes such as inflammation (S100A4 and S100A9) and tissue repair (annexin A1), which represent key events during EAE progression, were validated by quantitative PCR. This is the first targeted analysis of autoreactive cells purified from the CNS during EAE, highlighting fundamental CD4+ cell-driven processes that occur during the initiation of relapse and remission stages of disease. KEYWORDS: autoimmunity, experimental autoimmune encephalomyelitis (EAE), CD4+ T lymphocyte, isotope-coded protein labeling (ICPL), MALDI-TOF/TOF least in part, an autoimmune pathology.1−3 Further evidence of the possible autoimmune nature of multiple sclerosis derives from the pathological and immunological similarities with an extensively studied animal model of the disease termed experimental autoimmune encephalomyelitis (EAE).4,5 There are two commonly used mouse models of EAE: PLP139−151-induced EAE that models the relapsing-remitting form of multiple sclerosis and MOG35−55-induced EAE, which models the chronic/progressive form of the disease. Active disease is induced in SJL/J or C57BL/6 mice by the subcutaneous administration of the abundant CNS peptide antigens proteolipid protein (PLP) or myelin oligodendrocyte glycoprotein (MOG), respectively. These peptide antigens are

1. INTRODUCTION Multiple sclerosis is a chronic inflammatory demyelinating disease of the central nervous system (CNS). It affects the areas of the brain and spinal cord known as the white matter, which carry signals between gray matter areas where messages are processed and subsequently relayed to the rest of the body. Specifically, the condition is typified by the destruction of oligodendrocytes. These are the cells responsible for creating and maintaining a fatty layer, known as the myelin sheath that acts as an insulating layer for the electrical signals transmitted by neurons. Genetic linkage with genes involved in the activation of the immune system, the presence of inflammatory cells of the immune system within CNS lesions, and extensive evidence of immune reactivity of CD4+ lymphocytes from multiple sclerosis patients against a number of CNS antigens has led to the widely accepted view that the condition has, at © 2014 American Chemical Society

Received: March 2, 2014 Published: June 16, 2014 3655

dx.doi.org/10.1021/pr500158r | J. Proteome Res. 2014, 13, 3655−3670

Journal of Proteome Research

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2.2. Active Induction of PLP139−151-EAE

sampled in the periphery and trafficked to lymphoid organs, where PLP- or MOG-specific autoreactive CD4+ lymphocytes are activated and driven to infiltrate the CNS, where the antigens are re-encountered. Here CD4+ lymphocytes are reactivated and instigate an extensive inflammatory response, leading to the demyelination of axons and inappropriate neural transmission, culminating in the onset of ascending paralysis. While both models of EAE closely mimic the complex priming events and generation of autoreactive CD4+ lymphocytes that instigate the immunopathology and demyelination within the CNS, only PLP139−151-induced EAE emulates the resolution of inflammation and tissue repair that occurs during disease remission.5,6 It is known that different subpopulations of CD4+ T lymphocytes, which have distinct and contrasting physiological roles in either the propagation or the resolution of inflammation, exist within and traffic through the inflamed CNS at different stages of EAE progression.7 Thus, these distinct CD4+ populations are crucial to both the acute disease and remission phases of relapsing-remitting EAE. However, the precise counter-regulatory mechanisms and interactions that exist within the CNS stroma and infiltrating lymphocytes that facilitate the switch from neuro-injury to an immunosuppressive profile conducive to repair and recovery of hind limb mobility are still poorly defined. Therefore, because EAE and multiple sclerosis disease feature cell trafficking and immune and inflammatory processes, CD4+ cell-derived proteins involved in these actions were of particular interest. To date, only whole CNS tissue proteomic analyses have been performed for EAE or multiple sclerosis studies. These global approaches are not capable of distinguishing between the effects of CNS stromal or resident cells and infiltrating immune cells.8−11 Therefore, we isolated CNS-infiltrating CD4+ cells from the spinal cord and brain at three PLP139−151-EAE disease stages [disease onset (preparalysis stage), peak-disease (full hind limb paralysis), and remission (recovery of limb and tail mobility)] for ICPL proteomic analysis and compared these with unactivated CD4+ cell control samples isolated from the spleens of naive mice. As a secondary model, the proteome of CNS-infiltrating CD4+ cells isolated during MOG35−55-induced chronic EAE disease (disease onset and peak-disease timepoints only) was also assessed. By examining two independent disease models and analyzing disease progression at multiple stages of disease, we have identified candidate proteins that are relevant in the actions and effects of CNS-infiltrating CD4+ lymphocytes during EAE disease both in the induction and resolution of inflammation and repair.

Female 8−10 week old SJL/J mice were immunized for PLP139−151-EAE by subcutaneous injection of 50 μg myelin proteolipid protein PLP139−151 peptide (HSLGKWLGHPDKF) (Biomedical Research Centre, University of British Columbia, Vancouver BC, Canada) emulsified 1:1 in Complete Freunds Adjuvant (CFA) to each hind flank (50 μL each), in addition to intravenous Pertussis toxin injection (300 ng in endotoxin-free PBS) (List Biological Laboratories, Campbell, CA) administered in two doses, 2 h prior and 48 h post subcutaneous injection, as previously described.12 CFA stocks (for PLP immunization) were prepared by mixing 15% mannide manooleate (Sigma-Aldrich, St. Louis, MO), 85% mineral oil (Sigma-Aldrich), 8.33 mg/mL M. tuberculosis, and 0.5 mg/mL M. Butyricum (Difco Laboratories, Becton Dickinson, Franklin Lakes, NJ) and grinding extensively using a mortar and pestle. EAE disease progression was monitored daily from day 7 postinduction according to clinical disease symptoms (see Supplementary Table 1 in the Supporting Information: Clinical Disease Scoring for Murine Experimental Autoimmune Encephalomyelitis), adapted from Comerford et al.13 Disease states for analyses are defined as follows: disease onset: disease score 0.5 (preparalysis onset but reaching for hind paws); peakdisease: disease score of at least 2.5 (fully flaccid tail and hind limb paralysis); and remission: recovered disease score of 0.5/1 (recovery of at least two disease scores, full hind limb function, and at least partial tail mobility). Mice were scored daily and euthanized at defined disease scores by CO2 asphyxiation, perfused with PBS to remove circulating leukocytes, and the spinal cord and brain (CNS) harvested for processing. Healthy control mice for naive splenocyte CD4+ samples were age- and sex-matched. 2.3. Active Induction of MOG35−55-EAE

Female 8−10 week old C57BL/6 mice were immunized for MOG35−55-EAE by subcutaneous injection of 25 μg myelin oligodendrocyte glycoprotein MOG35−55 peptide (MEVGWYRSPFSRVVHLYRNGK)(GL Biochem, China) emulsified 1:1 in CFA to each hind flank (50 μL each) and the scruff of the neck (20 μL) in addition to intravenous Pertussis toxin injection (300 ng in endotoxin-free PBS) administered in two doses: 2 h prior and 48 h post subcutaneous injection. CFA stocks (for MOG immunization) were prepared by mixing 15% mannide manooleate (Sigma-Aldrich), 85% mineral oil (SigmaAldrich), and 8.33 mg/mL M. tuberculosis (Difco Laboratories, Becton Dickinson) and grinding extensively using a mortar and pestle. EAE disease score was monitored daily from day 7 postinduction, as previously described. 2.4. Sample Preparation

Harvested CNS samples were cut into small pieces and subjected to enzymatic dissociation in 2 mg/mL Collagenase D (Roche Diagnostics, Australia) and 10U DNase I (SigmaAldrich) for 1 h at room temperature, then homogenized through a 25 μM cell strainer into PBS. Pelleted CNS was then applied to a 70%/40% Percoll (Sigma-Aldrich) gradient in HBSS (Gibco, Invitrogen, Carlsbad, CA) to isolate mononuclear cells. Single-cell suspensions were subjected to red cell lysis for 5 min at 37 °C before resuspension in 0.1% BSA/PBS for Invitrogen DynaBead positive isolation for CD4+ cells, according to kit instructions (Invitrogen). Isolated CD4+ cells were released from the beads using Invitrogen Detach-a-Bead for mouse CD4, according to kit instructions (Invitrogen), and finally washed three times in ice-cold PBS. Unactivated CD4+

2. EXPERIMENTAL PROCEDURES 2.1. Animals

SJL/J mice were purchased from the Animal Resources Centre Breeding Facility, Western Australia; C57BL/6 mice were purchased from The University of Adelaide Waite Campus breeding facility, South Australia. All animals were housed at The University of Adelaide Laboratory Animal Services facility for the duration of experimental protocols. All experimental protocols used in this study were approved by the University of Adelaide Animal Ethics Committee. At all times, the principals of reduce, refine, and replace were adhered to and animal suffering was kept to a minimum. 3656



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version 1.5 (Roche Applied Science) and graphed using GraphPad Prism software version 5.0 (GraphPad Software).

cell control samples were isolated from the spleen of naive animals. Spleens were homogenized through a 25 μM cell strainer, washed once in PBS, and subjected to red cell lysis for 10 min at 37 °C. Control samples were resuspended in 0.1% BSA/PBS for CD4+ cell isolation and processed simultaneously with CNS samples.

2.8. Protein Classification with Gene Ontology and Network Analysis

Total identified proteins from relapsing-remitting and chronic EAE disease progression data sets were analyzed using DAVID Bioinformatics Resources version 6.7 (http://david.abcc.ncifcrf. gov/) and were allocated to functional gene ontology annotation groups according to GOTERM_BP_1. Of this list, proteins found to have increased expression (>2-fold upregulation) compared with the naive control group were further subjected to the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) version 9.0 (http://string-db.org/) to generate functional protein association network maps. Protein interaction maps were created by allowing for experimental evidence (where different connecting line colors represent the types of evidence for the association) as well as for the predicted functional links: co-occurrence, coexpression, databases, and text-mining. The minimum required confidence was set to “high confidence” (0.700). Proteins with no associations were excluded from the output.

2.5. Flow Cytometric Analysis

Flow cytometry was used to confirm the purity of isolated CD4+ cells using the DynaBead method (see previously described sample preparation) from complex cell mixtures of the CNS and spleen. Total tissue recovered cells post-red cell lysis were separated into two, half kept on ice as preisolation samples and the other half processed for CD4+ cell isolation as previously described. Pre- and post-isolation samples were resuspended to 4 × 106 cells/mL in PBS/1% BSA/0.04% azide, then Fc receptors were blocked with murine gamma globulin (50 μg/million cells) for 30 min on ice. Cells (1 × 105 cells/ well) were incubated with either PE-conjugated rat antimouse CD4 (BD Biosciences, San Jose, CA ) or a PE-conjugated rat IgG2A isotype control (BD Biosciences) at 5 μg/mL for 1 h on ice. Stained cells were then washed three times in PBS/1% BSA/0.04% azide and resuspended in PBS for acquisition. Data were acquired on a FACSCanto II flow cytometer (BD Biosciences) and analyzed using FlowJo version 7.6.5 (Tree Star, Ashland, OR).

2.9. Isotope-Coded Protein Labeling and LDS-PAGE

15 μg protein from each control or disease stage (naive control, disease onset, peak-disease ± remission) was reduced, alkylated, and then labeled with ICPL 0, ICPL 6, and ICPL 10 for MOG35−55-EAE samples or with ICPL 0, ICPL 4, ICPL 6, and ICPL 10 for PLP139−151-EAE samples, respectively, according to protocols provided with the SERVA ICPL Quadruplex PLUS Kit instructions (SERVA, Heidelberg, Germany).14 Following labeling, samples were combined (triplex for MOG35−55-EAE; 45 μg total protein or quadruplex for PLP139−151-EAE; 60 μg total protein). Protein was then precipitated using acetone precipitation as described in the provided protocols, followed by solubilization in 20 μL of 1× LDS loading buffer with 20 mM DTT using sonication. Samples were heated to 95 °C for 10 min, allowed to cool, and separated by LDS-PAGE on a 1 mm 4−12% NuPAGE Bis-Tris gel (Invitrogen) using MOPS running buffer at 200 V for 50 min.15

2.6. Cell Lysis for Proteomic Analysis

Isolated CD4+ cells were lysed in an NP-40 lysis buffer (50 mM Tris-HCl pH 7.5, 200 mM NaCl2, 1 mM EDTA, 1% NP-40) at 100 μL per 105 cells and incubated on ice for 30 min. Lysates were centrifuged at 20 000g for 10 min to remove insoluble particulates and cleared lysates were stored at −80 °C for the remainder of the sample collection period. All CD4+ cell lysates for each disease or control group were pooled, total protein was precipitated using acetone precipitation (5 volumes −20 °C HPLC grade acetone), and samples were resuspended in ICPL lysis buffer according to protocols provided with the ICPL labeling kit (SERVA, Heidelberg, Germany). 14 Protein concentration was determined using the EZYQ protein quantitation kit (Invitrogen, Life Technologies), and 15 μg of each sample was separated for ICPL labeling.

2.10. Excision of Gel Bands for In-Gel Tryptic Digestion

Following separation, gel bands were visualized using colloidal coomassie blue staining (Amersham Biosciences, USA) prior to manual excision and in-gel reduction (DTT), alkylation (iodoacetamide), and tryptic digestion (100 ng modified porcine trypsin, Promega, Madison, WI). Peptides were extracted from the gel plugs using sonication in 50% ACN with 0.1% TFA, followed by 100% ACN. Combined peptide eluates for each gel band were dried down in a vacuum centrifuge, and each was reconstituted using 2% ACN with 0.1% TFA.

2.7. RNA Isolation and cDNA Synthesis for Quantitative PCR

RNA was isolated from purified CD4+ cells using an RNeasy Micro kit according to manufacturer’s instructions (Qiagen Sciences, Germantown, MD). cDNA synthesis was performed according to the Roche cDNA synthesis kit (Roche Diagnostics, Australia). Relative transcript expression of the following targets, annexin A1 (F: GCAACCATCATTGACATTCTTACC; R: TGTAAGTACGCGGCCTTGATC), annexin A2 (F: AAGGACATCATCTCTGACACATCTG; R: GCTCGTCTGCCCTTTGCA), S100A4 (F: TTGAGGGCTGCCCAGATAAG; R: GCAAACTACACCCCAACACTTCA), and S100A9 (F: GAAGCCCTCATAAATGACATCATG; R: CATCAGCATCATACACTCCTCAAAG), were assessed in comparison with the reference gene RPLP0 (F: TGCAGATCGGGTACCCAACT; R: ACGCGCTTGTACCCATTGA). Quantitative PCR reactions were prepared using LightCycler 480 SYBR Green I Master Mix (Roche Applied Science, Mannheim, Germany) according to kit instructions and run on a LightCycler 480 Real-Time PCR System (Roche Applied Science). Data were analyzed using LightCycler 480 Software

2.11. HPLC, Fraction Collection, and Mass Spectrometry #1 (ICPL Triplex)

An Agilent 1100 system was operated using binary gradients of mobile phase A (0.1% TFA in 95% H2O, 5% ACN) and B (0.1% TFA in 95% ACN, 5% H2O). The Agilent 1100 was controlled using the Hystar software platform (V3.2-SR2, Bruker Daltonics, Bremen, Germany). Peptide samples were eluted and separated directly over an Acclaim PepMap100 C18 analytical column (180 μm i.d. × 15 cm, 5 μm particle size, 100 Å, Dionex) at a flow rate of 1 μL/min. The peptides were eluted with an ACN gradient of 0% B for 10 min, 0 to 48% 3657



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Matrix consisted of 748 μL of 95% ACN in 0.1% TFA, 36 μL of saturated CHCA in 90% ACN and 0.1% TFA, 8 μL of 10% TFA, and 8 μL of 100 mM ammonium phosphate. 1 μL of Peptide Calibration Standard II (Bruker, Daltonics) dissolved in 125 μL of 0.1% TFA was mixed with 99 μL of 30% ACN in 0.1% TFA and 150 μL of matrix. 600 nL of this mixture was deposited onto calibration spots. MS and MS/MS analyses were performed using an UltrafleXtreme MALDI-TOF/TOF system (Bruker Daltonics, Bremen, Germany) in reflectron positive-ion mode using WARP-LC (V1.2 Bruker Daltonics) interfaced with flexControl. Laser power was operator determined to provide optimal MS intensity and resolution. 3000 laser shots were collected for both sample and calibration spots. Acquisition settings: m/z range of 700−4000, 5.0× reflector gain, and 2.00 GS/s acquisition rate. MS spectra were smoothed (Gaussian, 1 cycle, width - m/z 0.02) and baseline-subtracted (TopHat). Peak masses and intensities were detected in flexAnalysis using the SNAP algorithm. WARP-LC was used to calculate a compound list for automated MS/MS based on a preset LC-MALDI method. MS/MS instrument settings were defined by the LIFT method. Following automated MS/MS acquisition, MS/MS spectra were imported into Proteinscape version 3.0.0346 (Bruker Daltonics) and submitted to Mascot (V2.3.02) for identification using the following search parameters: taxonomy, Mus musculus; database, Swiss-Prot release 2013_04; maximum missed cleavages, 1; MS tolerance, 50 ppm; MS/MS tolerance, 0.8 Da; enzyme, Arg-C; fixed modifications, carbamidomethyl (C); variable modifications, oxidation (M), ICPL_0 (lysine), ICPL_0 (protein N-terminal), ICPL_4 (lysine), ICPL_4 (protein N-terminal), ICPL_6 (lysine), ICPL_6 (protein Nterminal), and ICPL_10 (lysine), ICPL_10 (protein Nterminal). To prepare a list of candidate peptides for quantitation, all protein identifications with at least one identification with an ion score greater than the identity threshold were accepted.

solvent B in 54 min, 48 to 60% solvent B in 5 min, 60 to 80% solvent B in 0.5 min, followed by 80% B for 5 min. Fractions (15 s) were collected onto a MTP 384 MALDI 800 μm AnchorChip target (Bruker Daltonics, Bremen, Germany) using a Proteineer Fraction Collector (Bruker Daltonics). A supporting liquid (50% ACN in 0.1% TFA) was added discontinuously over the last 2 s during deposition onto the MALDI target via sheath flow to reduce peak tailing. After the spots air-dried, 1 μL of α-cyano-4-hydroxycinnamic acid (CHCA) matrix solution was added manually to each fraction according to Zhang et al.16,17 and left to dry. For calibration spots 1 μL of Bruker Daltonics Peptide Calibration Standard II (dissolved in 125 μL of 0.1% TFA) was mixed with 99 μL of 30% ACN in 0.1% TFA and 600 nL deposited onto the target. After drying, 0.8 μL of matrix solution was subsequently added and left to dry. MS analysis was performed on an Ultraflex III MALDI-TOF/ TOF system (Bruker Daltonics) in reflectron positive ion mode, using WARP-LC (V1.2 Bruker Daltonics) interfaced with flexControl. Laser power and detector gain were operatordetermined to provide optimal MS intensity and resolution. 500 and 400 laser shots were collected for both sample and calibration spots, respectively, using an acquisition m/z range of 700−4500. Following MS collection, MS spectra were smoothed (Gaussian, 1 cycles, width: m/z 0.05), and baseline-subtracted (TopHat). Peak masses and intensities were detected with flexAnalysis using the SNAP algorithm. WARP-LC was used to calculate a compound list for automated MS/MS based on a preset LC−MALDI method. MS/MS instrument settings were defined by the LIFT method. Following automated MS/MS acquisition, MS/MS spectra were imported into Proteinscape version 3.0.0346 (Bruker Daltonics) and submitted to Mascot (V2.3.02) for identification using the following search parameters: Taxonomy, Mus musculus; Database, Swiss-Prot release 2013_04; maximum missed cleavages, 1; MS tolerance, 50 ppm; MS/MS tolerance, 0.8 Da; enzyme, Arg C; variable modifications, oxidation (M), ICPL_0 (Lysine), ICPL_0 (Protein N-terminal), ICPL_6 (Lysine), ICPL_6 (Protein N-terminal), ICPL_10 (Lysine), ICPL_10 (Protein N-terminal); fixed modifications; carbamidomethyl (cysteine).

2.13. Determination of Peptide and Protein Ratios

Peptide identifications were exported from Proteinscape to tab delimited text, and LC-MALDI data were converted to the open mzMXL format using CompassXport (version 1.3 Bruker Daltonics). For each ICPL-labeled peptide, the expected monoisotopic m/z of the corresponding ICPL-0-, ICPL-4-, ICPL-6-, and ICPL-10-labeled peptides were calculated, and their intensities extracted from the data as follows: the spectra from the LC-MALDI fraction from which the identification was made and both the preceding and following two fractions (a 75 s window) were loaded into R using the mzR package,19 and m/z peaks were detected using the MALDIquant package;20 the intensity of peaks with 0.1 Da of each calculated ICPL m/z were then extracted from each spectrum and summed to give an intensity for each ICPL labeled species (where peak detection failed, the maximum signal within 0.05 Da of the expected m/z was taken). For peptides with a single ICPL label, the intensity of ICPL 6 monoisotopic peak was corrected by subtracting the predicted intensity of the overlapping third isotope of the ICPL-4-labeled species. The correction factor was determined empirically from the data set by examining the relative heights of the isotopes of all peptides identified as being modified with two or more ICPL 4 labels. The ICPL 4, ICPL 6, and ICPL 10 intensities were each divided by the ICPL 0 signal to give ratios for each peptide. log 2 ratios were then

2.12. HPLC, Fraction Collection, and Mass Spectrometry #2 (ICPL Quadruplex)

An UltiMate 3000 RS Nano/Cap System (Dionex, Sunnyvale, CA) was operated using binary gradients of mobile phases A (0.05% TFA in 98% H2O, 2% ACN) and B (0.04% TFA in 80% ACN, 20% H2O) and controlled using Hystar (V3.2-SR2, Bruker Daltonics). A micro-WPS-3000 autosampler (Dionex) injected 5 μL samples onto an Acclaim Pepmap 100 trap column (75 μm × 2 cm, 3 μm, 100 Å). Sample loading was performed at 3 μL/min at 0% B for 10 min. For analytical separation, the trap was switched inline to an Acclaim Pepmap100 C-18 analytical column (75 μm × 15 cm, 3 μm, Dionex) running at 300 nL/min. Peptides were eluted with 4− 8% B in 1 min, 8−42% B in 44 min, 42−90% B in 5 min, followed by 90% B for 10 min. Fractions (15 s) were collected onto a MTP 384 MALDI 800 μm AnchorChip target (Bruker Daltonics) using a Proteineer Fraction Collector (Bruker Daltonics), as previously described.18 In brief, eluate was mixed with CHCA matrix, supplied by a syringe pump (Cole-Parmer, Vernon Hills, IL), in a MicroTee junction (PEEK, 1/32 in, Upchurch Scientific). 3658



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Table 1. Proteins Up-Regulated by CNS-Infiltrating CD4+ Cells during Both Relapsing-Remitting and Chronic EAE Progressione

a Accession designations are derived from the UniProt database. bProtein names are derived from the UniProt database. cMultiplets before/after manual accuracy review of individual spectra (Supporting Information 1−4). dFold changes were calculated relative to ICPL peptide intensities of naive CD4+ cell control samples eProteins enriched in ICPL analysis of both EAE disease models. Intensity of green shading depicts degree of upregulation (between 2- and 5-fold = light green; >5-fold = dark green). Protein candidates for validation are highlighted in blue.

Table 2. Proteins Down-Regulated by CNS-Infiltrating CD4+ Cells during Both Relapsing-Remitting and Chronic EAE Progressione

a Accession designations are derived from the UniProt database. bProtein names are derived from the UniProt database. cMultiplets before/after manual accuracy review of individual spectra (Supporting Information 1−4). dFold changes were calculated relative to ICPL peptide intensities of naive CD4+ cell control samples eProteins enriched in ICPL analysis of both EAE disease models. Intensity of red shading depicts degree of downregulation (between 2 and 5-fold = light red; >5-fold = dark red).

Table 3. Established Cellular Functions of Identified Regulated Proteins

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Figure 1. Sample collection and proteomic workflow. CD4+ cells were isolated from the spleen of naive healthy controls; or the diseased CNS of mice immunized for PLP139−151-induced EAE (in SJL/J mice) or MOG35−55-induced EAE (in C57BL/6 mice) at disease onset, peak-disease and remission (SJL/J), or disease onset and peak-disease (C57BL/6), respectively. Protein samples were labeled by ICPL quadruplex or triplex methods and separated by LDS-PAGE for tryptic digest. Differentially regulated peptides were identified by LC−MS/MS analysis and subjected to pathway/ network analyses using Database for Annotation, Visualization and Integrated Discovery (DAVID), and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) evaluation tools. The mRNA transcript expression of selected protein candidates by CNS-infiltrating CD4+ cells isolated during EAE disease progression was then assessed by quantitative PCR analysis for individual biological replicates.

workflow (LDS-PAGE, tryptic digest of excised bands and LC− MALDI-TOF MS analysis). From four prominent protein bands, the experimental deviation from 1:1 was determined. The mean and standard deviations relative to ICPL_0 were d et e r m in ed [ I C PL _0 / I C P L_ 4 / I C PL _6 / I CP L _ 1 0 ] [1:0.85:0.95:0.90]. The standard deviation for the ratios was relatively low: 0.2011 for ICPL _4, 0.1332 for ICPL_6, and 0.1442 for ICPL_10. The mean of the standard deviation was 0.1595, and to be conservative we defined the regulation window, which is considered to be above the technical variation by being two times the mean standard deviation below the lowest and above the highest value (0.531 to 1.269). Considering these values, protein regulation was considered to be significant if there was at least a two-fold change in regulation.

normalized by subtracting the mean log 2 ratios for ICPL 4/ ICPL 0, ICPL 6/ICPL 0, and ICPL 10/ICPL 0 for the data set. Finally, protein regulations were expressed as the mean of the log 2 of their peptide ratios. The spectra for the 23 proteins presented as regulated (Tables 1−3) were manually inspected and reviewed for accuracy. The annotated spectra and extracted ion chromatograms are provided as Supporting Information (Supporting Information 1−4). Differential regulation of protein expression was defined as at least two-fold change in peptide intensity of a disease stage sample (ICPL_4, ICPL_6, ICPL_10; either increase >2.0 or decrease 2.5), and remission (clinical disease score 0.5/1, recovery >2 scores) (n = 14). Right panel, chronic model of EAE: disease onset (clinical disease score 0.5) and peak-disease (clinical disease score >2.5) (n = 14). (B) Representative flow cytometric analyses of CD4+ cell purity from a naive splenocyte suspension pre- and post-CD4+ cell isolation. Cells were labeled with a PE-conjugated isotype control (gray shaded histogram) or PE-conjugated anti-CD4 monoclonal antibody (black histogram). Live lymphocytes were pregated (left panel) and subsequent CD4+ gates display the percentage of gated cells that are positive for CD4 expression (center and right panels). (C) Number of CD4+ cells recovered from pooled CNS samples during each isolation procedure was counted immediately following CD4+ cell isolation. Each data point represents the average number of cells isolated per mouse from each isolation sample. PLP139−151-induced EAE in SJL/J mice: disease onset n = 53 (11 isolations), peak-disease n = 17 (7 isolations), remission n = 20 (6 isolations); MOG35−55-induced EAE in C57BL/6 mice: disease onset n = 51 (8 isolations), peak-disease n = 22 (6 isolations). 3661



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Figure 3. Examining two EAE disease models: ICPL analysis of CD4+ cells isolated from the CNS during relapsing-remitting and chronic EAE disease progression. (A) Individual cell lysates were assigned to disease groups and pooled, and 15 μg from each group was labeled with ICPL isotope labels. Total labeled protein was apportioned into annotated gel bands (dotted excision marks) for analysis. (B) Summary tables display a comparison between PLP139−151-induced relapsing-remitting EAE analysis (top panel) and MOG35−55-induced chronic EAE analysis (bottom panel). (C) Venn diagram. Fold-regulation of peptide intensity was calculated relative to naive CD4+ control samples for quadruplex and triplex labeling, where significance is considered to be >2-fold up- or down-regulation.

3. RESULTS

proteolipid protein, PLP139−151, or myelin oligodendrocyte glycoprotein, MOG35−55, respectively, to induce disease. Disease progression for both models was found to be as previously reported,13,21,22 and the time points chosen for analyses are annotated (Figure 2 A; Supplementary Table 1 in the Supporting Information). Designated time-points were selected because they represent disease onset, peak-disease, and remission and would allow the examination of the changes in the CD4+ cell proteome in the CNS during the transition from an autoreactive inflammatory phenotype through to an immunosuppressive environment conducive to remyelination and repair. Spinal cord and brain tissues were harvested from diseased mice, and CD4+ cells were isolated by positive selection using beads coated with antibodies specific for CD4. Unactivated control samples were derived from resting CD4+ cells isolated from the spleens of age- and sex-matched naive mice. The purity of isolated CD4+ cells was confirmed by flow cytometric analysis of samples before and after positive purification, and it was shown that CD4+ cells could be isolated to a purity of >95% from a complex splenocyte mixture composed of T- and B-lymphocytes, dendritic cells, macrophages, and natural killer cells (Figure 2B).

3.1. Proteomic Workflow Used in this Study

The aim of this study was to investigate the proteome of CD4+ T lymphocytes present in the CNS at different disease stages in two independent models of EAE. Therefore, a proteomic workflow was developed to achieve this (Figure 1). In brief, PLP139−151-EAE and MOG35−55-EAE disease were actively induced in SJL/J or C57BL/6 mice, respectively, and disease progression was monitored daily according to clinical disease scoring. (See Supplementary Table 1 in the Supporting Information.) CNS-infiltrating CD4+ cells were isolated from the spinal cord and brain of mice at defined disease stages: disease onset, peak-disease ± remission, in addition to naive CD4+ cells purified from the spleen of healthy controls, which were used as an unactivated proteome comparison. ICPL analysis was used to identify differentially regulated protein candidates common to both independent disease models, and the transcript expression of selected candidates was validated by quantitative PCR. 3.2. CD4+ Cell Isolation during Disease

SJL/J mice (relapsing-remitting EAE) or C57BL/6 mice (chronic EAE) were immunized with the peptides myelin 3662



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induced EAE samples similarly present during PLP139−151induced EAE. Of these, the expression of 13 common proteins was found to be up-regulated, and 10 were down-regulated by at least two-fold during disease progression relative to that of naive controls (Figure 3C, Tables 1−3). The ICPL data sets for PLP139−151-induced relapsing remitting EAE and MOG35−55-induced chronic EAE were further compared using DAVID Functional Annotation Bioinformatics. Among the proteins quantified, a major percentage could be annotated to the functional GO terms: cellular and metabolic processes (PLP: 77.8%, MOG: 83.7% and PLP: 61.7%, MOG: 64.6%, respectively) in addition to immune system processes (PLP: 6.9%) (Supplementary Table 2 in the Supporting Information) and establishment of localization and cell migration (PLP: 16.0%) (Figure 4A). As previously mentioned, proteins comprising these latter two functional groups were of particular interest as they potentially reflect CD4+ cell-driven mechanisms responsible for inflammation within the CNS. Furthermore, of the proteins determined to be up-regulated during disease progression in each model, a proportion of these were found to cluster as a functional group when analyzed using the protein association network tool, STRING, which is based on experimental evidence (Figure 4B). This grouping could be attributed to associations based on a role in immune function during inflammation and disease. Among the clustered proteins were proinflammatory factors (Lcn2; S100A4; S100A9; S100A10), anti-inflammatory factors (Anxa1), adhesion molecules involved in trans-endothelial migration (Lgals3), mediators of signal transduction (AnxA2; Calm1; Nfkb1), and regulators of cytoskeletal rearrangement, lymphocyte adhesion, and transmigration (Lcp1; Vim). Other major clusters were attributed to the up-regulation of protein translation (Rpl and Rps ribosomal subunits) and glycolysis (Pgk1; Tpi1), which was expected for activated cells. By collating all quantified data sets from each of the disease stages across both PLP139−151-induced relapsing-remitting and MOG35−55-induced chronic EAE analyses, the expression of 13 proteins was determined to be up-regulated, while the expression of 10 proteins was determined to be down-regulated by CNS-infiltrating CD4+ cells by at least two-fold during disease relative to their expression by naive control cells (Figure 3C). Tables 1 and 2 summarize the degree of regulation of these proteins across the two analyses, where the intensity of shading is related to the fold-increase/fold-decrease in peptide intensities (Tables 1 and 2; refer to Supporting Information 1− 4: Annotated Spectra and Extracted Ion Chromatograms). From these initial lists, four up-regulated candidate proteins were selected for validation based on their previously known functions in either inflammation (S100A4, S100A9), tissue repair (AnxA1), or membrane cytoskeletal rearrangements and heterotetrameric complex formation with S100A10 (AnxA2) (highlighted in Table 3), as these potentially represent novel CD4+ cell-driven mechanisms of EAE disease regulation.

While immune cells have been shown to infiltrate the CNS as early as day 6 post-EAE induction,23,24 it was found that on average 2 × 104 CD4+ cells could be isolated from the CNS of mice at disease onset and ∼1 × 105 CD4+ cells could be isolated from the CNS of mice at peak-disease or remission (Figure 2C). Since relatively few target cells were present in the CNS, particularly at disease onset, the number of individual mice required to be immunized for EAE in each model was adjusted to recover sufficient cells for a comprehensive proteomic analysis (data not shown). 3.3. ICPL Analysis of CNS-Isolated CD4+ Cells

The analytical reliability of the ICPL quadruplex labeling was assessed using a single sample portioned into four identical replicates labeled with each of the quadruplex isotope labels (light 1H412C6; light-med 2H412C6; med-heavy 1H413C6; heavy 2 H413C6) for analysis. Considering the technical error as determined in Section 2.13, statistically significant differential regulation was defined as a minimum of two-fold change in peptide intensity compared with control samples. This was selected as a conservative value far exceeding the technical error. Lysates were prepared from CNS-infiltrating CD4+ cells isolated during EAE disease progression as described. Grouped lysates were prepared for ICPL labeling with one of three (triplex) or four (quadruplex) isotope labels according to established protocols (light 1H412C6; light-med 2H412C6; medheavy 1H413C6; heavy 2H413C6).25 Labeled samples were pooled, separated by LDS-PAGE, and excised into 34 distinct gel bands for tryptic digest and LC−MS/MS analysis (Figure 3A). A total of 1622 unique proteins were identified across both analyses: 1059 unique to quadruplex, 107 unique to triplex, and 456 common to both approaches. The discrepancy between the number of proteins identified in the two analyses is due to the more sensitive technical platform used for the acquisition of ICPL quadruplex data. The next-generation UltrafleXtreme instrument has superior resolving power and higher sensitivity than the UltraFlexIII system and became available to us after the acquisition of the triplex data set. Analysis of the PLP139−151-induced relapsing-remitting model of EAE in SJL/J mice resulted in the identification of 1515 proteins (1112 proteins identified by more than 2 peptides) of which 1073 proteins were successfully quantified across the four disease stages (disease onset, peak-disease, and remission relative to naive control samples). In comparison, analysis of the MOG35−55-induced chronic model of EAE in C57BL/6 mice resulted in the identification of 565 proteins (372 proteins identified by more than 2 peptides), of which 336 proteins were quantified across three disease stages (disease onset and peakdisease relative to naive control samples). Of the total quantified proteins, 30.8% were found to be differentially regulated by at least two-fold during disease progression compared with naive controls (Figure 3B). While the main goal of this study was to identify proteins that are coregulated in both EAE disease models, differentially regulated proteins for each individual analysis are presented in Supplementary Tables 3−6 in the Supporting Information and include a number of immune-related proteins of potential interest. A total of 289 quantified proteins were detected in both analyses, which represents common expression of these proteins by CNS-infiltrating CD4+ cells during disease in both chronic and relapsing-remitting models of EAE. This translated to 86% of proteins quantified from MOG35−55-

3.4. Candidate Validation by Quantitative PCR

The expression of selected candidate proteins was then assessed and validated at the transcriptional level by quantitative PCR analysis of CD4+ cells isolated from the CNS of individual SJL/ J mice during PLP139−151-induced EAE at corresponding disease stages to the previous analysis (naive control, n = 6; EAE peakdisease, n = 6; EAE remission, n = 10)(Figure 5A). In line with quantitative proteomic data, the mRNA expression of three of 3663



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the four candidate genes (S100A4, S100A9, and AnxA1) was found to be significantly up-regulated relative to the reference gene RPLP0 during disease compared with naive control cells (Figure 5B−D). Interestingly, unlike the expression of inflammatory proteins S100A4 and S100A9, which stabilized or decreased as disease progressed toward the remission phase, an increasing trend in the expression of AnxA1 was observed during remission (Figure 5D). Contrary to protein expression levels of AnxA2, transcriptional analyses show no significant difference in mRNA levels relative to naive control cells (Figure 5E), suggesting a degree of translational regulation.

4. DISCUSSION The present study aimed to investigate cell-specific proteome changes in CNS-infiltrating CD4+ cells that contribute to important processes of disease development and resolution in EAE, a murine model of the neurodegenerative disease multiple sclerosis. ICPL analysis was used to quantitatively assess changes in these cells at various stages of disease progression compared to resting naive CD4+ cells in two models of EAE, PLP139−151-induced relapsing-remitting, and MOG35−55-induced chronic EAE. An ICPL approach was utilized because labeling is performed at the protein level, and all subsequent processing steps following the labeling of individual samples, such as downstream separation processes, are conducted with combined labeled samples, thereby decreasing technical variance. In addition, quantitation was performed at the MS level, and area under the curve of peptide m/z peaks was taken as the value for quantitation of peptides and proteins. Quantitation at the MS level is, in our opinion, superior to quantitation of reporter ions at the MS/MS level used by other labeling approaches. The novel aspect and experimental strength of this study was the cell-specific nature of the sample, as CD4+ cells were isolated directly from the spinal cord and brain of diseased mice rather than whole CNS tissue, and additionally the comparison between two independent EAE models that progress to either a chronic disease coupled to prolonged pathogenesis and paralysis or regress into a remission phase where mobility is restored. This approach ensured a high degree of confidence that the identified protein candidates found to be differentially regulated during disease would be biologically relevant to disease progression. 4.1. CD4+ Cell-Isolation Workflow

EAE is characterized by the infiltration of primed autoreactive CD4+ T lymphocytes into immune-privileged areas of the CNS and the release of pro-inflammatory mediators, leading to the subsequent influx of immune cells that together contribute to tissue damage and the onset of paralysis. Disease-instigating CD4+ cells were specifically targeted for this analysis and were successfully isolated to a purity of >95% CD4+ cells, as confirmed by flow cytometric analysis. However, in addition to T-helper lymphocytes, there are a small number of leukocyte subsets that express CD4 under a variety of conditions. These include monocytes/macrophages and to a lesser extent natural killer cells and some populations of granulocytes.26−30 However, because these cells express much lower levels of CD4 or they represent a minor proportion of the isolated population, it is unlikely that they would contribute to proteins identified in subsequent analyses. Consequently, because the major population of CD4+ cells present in the CNS during EAE disease has been previously shown to be T-helper lymphocytes,7 we were confident that the CD4+ cell isolation workflow

Figure 4. Analyses of CNS-infiltrating CD4+ cells isolated during relapsing-remitting and chronic EAE disease progression identified a broad coverage of regulated proteins. (A) DAVID functional gene ontology annotation (GOTERM_BP_1) output of proteins quantified for PLP139−151-induced relapsing-remitting and MOG35−55-induced chronic EAE analyses. (B) Protein association network maps of proteins up-regulated during PLP139−151-induced relapsing-remitting and MOG35−55-induced chronic EAE disease progression. Total association clusters were built using Search Tool for Retrieval of Interacting Genes/Proteins (STRING 9.05) allowing for experimentally verified and predicted protein−protein interactions at high confidence level (0.700). Highlighted is a subnetwork of proteins with known functions in immune function during inflammation and disease. 3664



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Figure 5. Candidate validation by quantitative PCR of mRNA transcript levels. (A) PLP139−151-induced relapsing-remitting EAE disease progression. Arrows represent disease stages in which CD4+ cells were isolated from the CNS of diseased mice for analysis relative to naive CD4+ splenocytes. (B−E) Quantitative real-time PCR analyses of S100A4 (B), S100A9 (C), Annexin A1 (D), and Annexin A2 (E) expression (normalized to reference gene RPLP0) by CNS-isolated CD4+ cells from PLP139−151-induced EAE diseased mice during peak-disease (n = 6) and remission (n = 10) relative to naive control CD4+ cells (n = 6). Asterisks denote statistical significance (t test, 95% confidence) (expression elevated relative to naive controls; *p < 0.05; **p < 0.01; ***p < 0.001).

based on displayed symptoms, and samples were collected at defined disease scores rather than a particular time-point postimmunization. This strategy was employed to attain consistent samples with respect to the desired disease stage, thus reducing unavoidable variability in the response to immunization because in our experience individual mice may begin to show symptoms between days 7 and 10 post-immunization in each of the two models investigated. To conduct a comprehensive proteomic analysis on this cell population, we required CNS samples from individual diseased mice to be pooled due to the small number of CD4+ cells present in and isolated from the tissue, particularly during early stages of disease. After the initial infiltration of lymphocytes into the CNS and subsequent breakdown of the blood−brain barrier, there is a secondary influx of leukocytes recruited by inflammatory mediators released by autoreactive cells.7,22,31 At peak-disease, in excess of 1 × 105 CD4+, cells could be isolated from the CNS of diseased mice, which was sustained through to remission in the case of the PLP139−151-induced EAE model. However, it is unlikely that the CD4+ cells identified at peak stages persist in the CNS throughout the course of disease, as it has been previously shown that CD4+ cells in the CNS undergo a burst of proliferation and then enter apoptosis soon after an acute inflammatory episode.32 This suggests that a degree of dynamic regulation of CD4+ cell populations through the CNS exists, which contribute to and influence disease severity. The Thelper lymphocyte subsets known to be involved at various stages of EAE are Th1, Th17, and Treg cells, where it has been reported that pro-inflammatory Th1 and Th17 cells are initially recruited to the CNS and immunosuppressive T regulatory

was sufficient to recover the desired autoreactive lymphocyte population for analysis. Indeed, successful identification of T lymphocyte-specific markers such as surface antigen Thy1 and T-cell receptor (TCR) complex coreceptor CD4 and CD3 subunits was consistent with the aforementioned population. In addition, several activation markers such as tumor necrosis factor receptors (TNR18_MOUSE), nuclear factor of activated Tcells (NFAC2_MOUSE), pro-interleukin-16 (IL16_MOUSE), and integrins (ITAL_MOUSE, ITB2_MOUSE) were identified as well as a number of proteins related to cell migration (ACTBN_MOUSE, CALM1_MOUSE, CRLF3_MOUSE, DOCK2_MOUSE, ELMO1_MOUSE, EZRI_MOUSE, FLNA_MOUSE). We therefore conclude that the method for CD4+ cell isolation and sample preparation was suitable for the detailed analysis of CNS-infiltrating CD4+ lymphocytes. Recovery of CD4+ cells from the CNS at various stages of EAE disease permitted the examination of regulated protein expression as disease progressed from the initial proinflammatory phase, through peak inflammation to the resolution of inflammation and a potentially immunosuppressive profile. Infiltration of CD4+ T-helper lymphocytes (predominantly Th1 and Th17 subsets) into the CNS has been reported to occur as early as day 6 post-immunization in the MOG35−55-induced model of chronic EAE in C57BL/6 mice24(unpublished observations), which marginally precedes the onset of disease symptoms. This is consistent with our findings that ∼2 × 104 CD4+ cells could be isolated from the CNS harvested from mice at a defined disease score of 0.5, which was designated disease onset. Individual mice were monitored and scored daily 3665



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infiltrating CD4+ cells at peak-disease and remission phases of EAE progression relative to naive CD4+ cells from healthy counterparts. The S100 family of EF-hand Ca2+-binding proteins represent a group of over 20 functionally diverse regulatory proteins that primarily exist as homo- and heterodimers or multimeric complexes. In the presence of intracellular calcium, S100 complexes adopt an “open” conformation, allowing them to bind and regulate the activity of their specific protein targets. We have identified S100A4 and S100A9 as being highly upregulated by CNS-infiltrating CD4+ cells during EAE disease progression. These proteins have previously been identified as being highly proinflammatory and have been implicated in the pathogenesis of several inflammatory disorders such as experimental arthritis, transplant rejection, and sarcoidosis.58−61 In addition, S100A4 is best characterized as a tumor metastasis-promoting factor, and its expression has been strongly correlated with many metastatic cancers in humans.62,63 Several studies have also implicated S100A4 and S100A9 in antigen-induced rheumatoid arthritis (RA), where proliferating synovial fibroblasts from RA patients were found to have increased mRNA expression and elevated plasma levels of S100A4 and S100A9 in RA synovial fluid compared with healthy controls, which coincided with exacerbated joint swelling and cartilage destruction.58,64 While S100 proteins have a broad tissue distribution and have been shown to be expressed by a number of immune cells such as activated neutrophils and macrophages, dendritic cells, and some resting T lymphocytes;58,65−67 this is the first description of S100A4 and S100A9 expression by activated CD4+ T lymphocytes during disease. The production of these proinflammatory mediators by CD4+ cells within the CNS is particularly biologically relevant because they were isolated from the peripheral site of autopathogenic damage in two disease models of EAE and therefore likely represent a key factor in the inflammatory milieu contributing to disease through the further recruitment of inflammatory cells. Annexin A1 (AnxA1), also called lipocortin, is a 37 kDa member of the annexin superfamily of calcium- and phospholipid-binding proteins and acts as an inhibitor of phospholipase A2 activity. Although highest mRNA expression has been reported in cells of the innate immune system, AnxA1 has been shown to be critical during the resolution of inflammation and tissue repair in disease models characterized by the activation of the adaptive immune system.68,69 This primarily occurs by restricting lymphocyte transmigration and recruitment through targeting of adhesion events at the microvasculature.70,71 Importantly, this is one of the major sites of anti-inflammatory action of glucocorticoids.72 T lymphocytes have been shown to constitutively express low levels of both intracellular and soluble AnxA1, which is upregulated following TCR activation.73,74 In addition, exogenous AnxA1 provided to activated T cells in vitro was shown to promote generation of anti-inflammatory T regulatory or mature “suppressor” cells that have been previously associated with tissue repair during the remission phase of EAE.75 In contrast with the actions of AnxA1 on activated T cells, exposure of naive cells to exogenous AnxA1 during T cell priming and differentiation has been shown to promote the skewing of the T helper response toward inflammatory Th1 and Th17 phenotypes.74,76 AnxA1 null T lymphocytes (AnxA1−/−) have impaired activation following TCR stimulation and reduced proliferative capacity. Furthermore,

cells appear later during remission and repair phases of disease.7,33 However, as previously acknowledged, it is still largely unclear whether these are distinct cell populations that enter and exit the CNS or whether there is a degree of plasticity between subsets determined by the nature of the surrounding milieu, as has been shown for other disease models.34−36 4.2. Correlation with Previous Whole Tissue Proteomic Analysis of EAE and Multiple Sclerosis

While the present study is the first targeted proteomic analysis of the specific cell type responsible for pathology within the CNS, there have been a number of whole diseased tissue studies investigating global proteome changes in EAE and multiple sclerosis samples.37 These have included spinal cord, 8,11,38 brain stem, 9,39 cerebrospinal fluid, 10,40−45 serum,46,47 multiple sclerosis autopsy lesions,48 and microvasculature.49 Although these broad tissue analyses offer a global perspective on expression changes during disease, they are often dominated by highly abundant serum proteins associated with the breakdown of the blood−brain barrier, potentially masking key regulatory events involving lower abundant cell-specific proteins. Analysis of localized lesions from post-mortem multiple sclerosis patient samples offers a more defined evaluation of acute, chronic active, and chronic plaques; however, this is often limited to a representation of established chronic disease rather than early inflammatory events occurring in developing lesions.48 Of proteins identified to be differentially regulated in both relapsing-remitting and chronic EAE disease models in the present study, a number have been previously associated with either EAE studies in rodents, multiple sclerosis tissue proteome studies, or in global transcriptome analyses of diseased tissues. These included three down-regulated proteins (aconitate hydratase and isocitrate dehydrogenase at the protein level; heterogeneous nuclear ribonucleoprotein subunits at both transcript and protein levels) and six up-regulated proteins (annexin A1, S100A4, and S100A9 at the transcript level; albumin, annexins A1 and A2, macrophage capping protein, S100A4, and S100A9 at the protein level).8,11,37,39,42,44,49−53 In the present study, these proteins were found to be up-regulated in encephalitogenic CD4+ cells from both relapsing-remitting and chronic disease, which suggests that in previous global tissue analyses these factors may have been at least in part CD4+ cell-derived. In addition to these, seven novel CD4+ cell-derived proteins were found to be up-regulated during EAE disease progression, none of which have previously been associated with EAE or multiple sclerosis. (See Tables 1 and 3.) 4.3. Expression Changes Related to EAE Pathology

Dual model analyses revealed that 13 proteins were upregulated by at least two-fold by CNS-infiltrating CD4+ cells during EAE disease progression compared with naive CD4+ controls (Table 1). In addition to proteins involved in gene expression and protein translation, proteins of particular interest were those identified with previously established roles in inflammation and cell migration, two key processes necessary for EAE pathogenesis dominated by the invasion and recruitment of inflammatory cells into the CNS. Four candidate proteins, S100A4, S100A9, annexin A1, and annexin A2, were selected for validation experiments based on their previously characterized roles in inflammation, repair, and the regulation of cytoskeletal rearrangement.54−57 The transcript expression of S100A4, S100A9, and annexin A1 was confirmed by quantitative PCR to be significantly up-regulated in CNS3666



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AnxA1−/− mice display reduced EAE severity, which correlated with impaired expansion of encephalitogenic cells within secondary lymphoid organs.73 However, none of the above functional effects of AnxA1 were shown to be as a result of T cell-derived AnxA1. Therefore, our finding is the first cell-specific description of AnxA1 expression by lymphocytes implicated in disease. Here we show that AnxA1 is highly up-regulated by CNS-infiltrating CD4+ cells through the course of chronic and relapsing-remitting models of EAE progression compared with naive control CD4+ cells. Quantitative PCR data from CD4+ cells isolated from the CNS of individual EAE-diseased mice showed peak AnxA1 expression to be during the remission phase of disease where CD4+ T regulatory cells are known to be involved in the resolution of inflammation and tissue repair processes. However, the CD4+ T-helper cell subset responsible for AnxA1 production in the CNS and the cellular targets of AnxA1 are still to be elucidated and will be a future avenue of investigation. Annexin A2 (AnxA2) also belongs to the annexin superfamily, and although it is structurally closely related to annexin A1, the expression profile of AnxA2 differs as it is predominantly expressed at high levels by vascular endothelial cells and is primarily involved in membrane trafficking events and as a plasminogen receptor in complex with S100A10.56,57,77 To a lesser extent, expression of AnxA2 has been shown by immune cells during acute inflammation. While protein expression levels of AnxA2 were found to be significantly upregulated by CNS-infiltrating CD4+ cells during EAE disease, transcriptional analyses show no significant difference in mRNA levels relative to naive control cells. This suggests a degree of translational regulation that requires further elucidation.

assigns CD4+-cell derived proteins to immune system processes. Supplementary Table 3. Proteins up-regulated in PLP-induced relapsing-remitting EAE analysis Supplementary Table 4. Proteins down-regulated in PLP-induced relapsingremitting EAE analysis. Supplementary Table 5. Proteins upregulated in MOG-induced chronic EAE analysis. Supplementary Table 6. Proteins down-regulated in MOG-induced chronic EAE analysis. Supporting Information 1−4: Annotated Spectra and Extracted Ion Chromatograms. Supporting Information 1. Quadruplex up-regulated. Supporting Information 2. Quadruplex down-regulated. Supporting Information 3. Triplex up-regulated. Supporting Information 4. Triplex downregulated. This material is available free of charge via the Internet at http://pubs.acs.org. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium78 via the PRIDE partner repository with the data set identifier PXD001011 and DOI 10.6019/PXD001011.

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*P.H. (for correspondence regarding proteomics): Tel: +61 8 8313 5507. Fax: +61 8 8313 4362. E-mail: peter.hoffmann@ adelaide.edu.au. *S.R.M. (for correspondence regarding immunobiology): Tel: +61 8 8313 4259. Fax: +61 8 8313 3337. E-mail: shaun. [email protected]. Present Address #

T.K.: Institute for Experimental Medicine − Div. Systematic Proteome Research, Christian-Albrechts-Universitat, 24105 Kiel, Germany. Notes

The authors declare no competing financial interest.

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5. CONCLUDING REMARKS The present study is the first cell-specific proteomic analysis of EAE or multiple sclerosis, which compared with previous whole tissue analyses, allowed for the delineation between effects of infiltrating CD4+ T lymphocytes from resident CNS cells as well as other cells of the immune system. This detailed examination of differential protein expression changes by CNSinfiltrating autoreactive CD4+ lymphocytes during EAE pathogenesis resulted in the identification of four novel CD4+ cellderived candidate proteins, S100A4, S100A9, annexin A1, and annexin A2, where protein expression was found to be significantly up-regulated during disease in two independent models of EAE. Detailed kinetic and subset-specific analyses should be performed to determine which T helper cell subset is responsible for production of these factors to further characterize the role of these proteins in CD4+ cell function during EAE progression. Ultimately, gaining a more comprehensive understanding of CD4+ cell-driven processes that facilitate the switch from an inflammatory phenotype to an immunosuppressive population during peak through to remission phases of EAE is required if we are to successfully manipulate T-lymphocyte activity and promote neuronal repair within the CNS.

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AUTHOR INFORMATION

Corresponding Authors

ACKNOWLEDGMENTS We thank and acknowledge the contributions of the members of the Adelaide Proteomics Centre for technical advice and data processing assistance throughout the final stages of manuscript preparation and secondly the PRIDE Team for support with data set deposition. This work was funded by a Linkage Grant from the Australian Research Council and MS Research Australia.

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ABBREVIATIONS AnxA1, annexin A1; AnxA2, annexin A2; CD4, cluster of differentiation 4; CFA, complete Freund’s adjuvant; CNS, central nervous system; EAE, experimental autoimmune encephalomyelitis; ICPL, isotope-coded protein label; LC− MS/MS, liquid-chromatography tandem mass spectrometry; MOG, myelin oligodendrocyte glycoprotein; PLP, myelin proteolipid protein; RA, rheumatoid arthritis; S100A4, S100 calcium binding protein A4; S100A9, S100 calcium binding protein A9; TCR, T cell receptor; Th, T helper cell; SJL/J and C57BL/6, common inbred strains of laboratory mice.

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ASSOCIATED CONTENT

S Supporting Information *

Supplementary Table 1. Clinical disease scoring for Murine Experimental Autoimmune Encephalomyelitis. Supplementary Table 2. Gene ontology analysis of total quantified proteins 3667



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NOTE ADDED AFTER ASAP PUBLICATION The abstract graphic was replaced and the paper reposted on 7/11/14.

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Quantitative Proteome Profiling of CNS-Infiltrating Autoreactive CD4+

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