Comparative Proteomic Analysis of Primary Schwann Cells and a

Article pubs.acs.org/jpr

Comparative Proteomic Analysis of Primary Schwann Cells and a Spontaneously Immortalized Schwann Cell Line RSC 96: A Comprehensive Overview with a Focus on Cell Adhesion and Migration Related Proteins Yuhua Ji,‡,§,† Mi Shen,‡,† Xin Wang,‡ Shuqiang Zhang,‡ Shu Yu,‡ Gang Chen,‡ Xiaosong Gu,‡ and Fei Ding*,‡ ‡

Jiangsu Key Laboratory of Neuroregeneration, Nantong University, 19 Qixiu Road, Nantong, JS 226001, P. R. China Institute of Tissue Transplantation and Immunology, College of Life Science and Technology, Jinan University, Guangzhou, Guangdong, 510632, P. R. China

§

S Supporting Information *

ABSTRACT: Schwann cells (SCs) are the principal glial cells of the peripheral nervous system (PNS). As a result of tissue heterogeneity and difficulties in the isolation and culture of primary SCs, a considerable understanding of SC biology is obtained from SC lines. However, the differences between the primary SCs and SC lines remain uncertain. In the present study, quantitative proteomic analysis based on isobaric tags for relative and absolute quantitation (iTRAQ) labeling was conducted to obtain an unbiased view of the proteomic profiles of primary rat SCs and RSC96, a spontaneously immortalized rat SC line. Out of 1757 identified proteins (FDR < 1%), 1702 were quantified, while 61 and 78 were found to be, respectively, up- or down-regulated (90% confidence interval) in RSC96. Bioinformatics analysis indicated the unique features of spontaneous immortalization, illustrated the dedifferentiated state of RSC96, and highlighted a panel of novel proteins associated with cell adhesion and migration including CADM4, FERMT2, and MCAM. Selected proteomic data and the requirement of these novel proteins in SC adhesion and migration were properly validated. Taken together, our data collectively revealed proteome differences between primary SCs and RSC96, validated several differentially expressed proteins with potential biological significance, and generated a database that may serve as a useful resource for studies of SC biology and pathology. KEYWORDS: Schwann cells, RSC96, spontaneous immortalization, dedifferentiation, quantitative proteomics, iTRAQ, adhesion, migration

■

INTRODUCTION Schwann cells (SCs), derived from neural crest cells, are the myelin-forming glial cells of the peripheral nervous system (PNS).1 During the past several decades, the complex, multifaceted, and crucial roles of SCs in the PNS have been revealed, including the conduction of nervous impulses along axons, nerve development and regeneration, trophic support for neurons, production of the nerve extracellular matrix (ECM), modulation of neuromuscular synaptic activity, and presentation of antigens to T-lymphocytes.2,3 Moreover, SCs are the direct and/or indirect targets of many hereditary and acquired peripheral myelin diseases, and there is a heightened interest in better understanding the biology and pathology of SCs.4 Cell lines are indispensable tools in biological research as they are readily available, free of genetic variations, and can be expanded without limitations. SCs are not an exception in this regard. Because of tissue heterogeneity and difficulties in the isolation and culture of primary SCs, many SC lines have been © 2012 American Chemical Society

established and employed successfully in many studies and much of our knowledge about SC properties comes from such research.5,6 Unfortunately, cell lines are prone to lose their original phenotype, which significantly affects experimental results and influences subsequent data interpretation. It is therefore necessary to determine to what extent cell lines may differ from their corresponding primary cells in cellular compositions and functions. Some unique features of SC lines that distinguish them from their cognate primary SCs have been already revealed, such as the overexpressed plateletderived growth factor receptors (PDGFRs) in neruofibrosarcoma-derived SC lines7 and the significant differences in expression of mature SC markers between primary SCs and SC lines.8 To our knowledge, however, the proteomic profile Received: December 13, 2011 Published: April 23, 2012 3186

dx.doi.org/10.1021/pr201221u | J. Proteome Res. 2012, 11, 3186−3198

Journal of Proteome Research

Article

DMEM containing 10% FBS, at 37 °C, with 95% air and 5% CO2. All media and supplements were obtained from GibcoInvitrogen (Carlsbad, CA).

differences between primary SCs and SC lines have not been investigated. The comprehensive analysis and comparison of the proteome of cell lines and their cognate primary cells has been greatly facilitated by the rapid development of mass spectrometry (MS)-based proteomic technologies and various stable isotope labeling techniques. For example, in the representative study by Mann and co-workers,9 a metaboliclabeling strategy, stable isotope labeling by amino acids in cell culture (SILAC), was used for quantitative proteomic comparison of the hepatoma cell line Hepa1-6 with primary hepatocytes. To date, however, the majority of such studies have been mostly confined to tumor-derived cell lines. RSC96 is a spontaneously immortalized SC line derived from the longterm culture of rat primary SCs that has been used as an important supplement to primary SCs in many studies on peripheral nerve injury and regeneration.10,11 In the present study, we aimed to compare the protein profile of RSC96 to that of its cognate primary SCs by using a quantitative proteomic strategy based on isobaric tags for relative and absolute quantitation (iTRAQ) labeling and online twodimensional nanoscale liquid chromatography coupled with tandem mass spectrometry (2D nano LC/MS/MS). The present proteomic study and subsequent bioinformatics analysis showed substantial differences between primary SCs and the derived cell line RSC96, as well as the unique features of this spontaneous immortalized SC line. More importantly, in addition to the proteins that could participate in the immortalization of RSC96, a number of proteins that are potentially involved in the biological functions of normal SCs were identified. The expression and/or function of several such proteins in primary SCs were properly validated, especially three cell adhesion and migration related molecules. The database generated by the present study could therefore serve as a useful resource for future studies of SC biology and pathology.

■

Immunofluorescent Staining

The cell cultures were fixed in 4% paraformaldehyde (pH 7.4) for 15 min, permeabilized with 0.3% Triton X-100, blocked with 10% goat serum in 0.01 M phosphate buffered saline (PBS) (pH 7.2) for 60 min at 37 °C, and allowed to incubate with the corresponding primary antibody at 4 °C overnight. Afterward, the cells were reacted with FITC-conjugated secondary antibody (Molecular Probes, The Netherlands) for 2 h, and stained with 5 μg/mL Hoechst 33342 at 37 °C for additional 10 min. The fluorescence was visualized under a TCS SP2 confocal microscope (Leica Microsystems, Wetzlar, Germany). The following primary antibodies were used for immunofluorescence staining: S100β, NDRG2 (Abcam, Cambridge, MA), TUBB3 (Santa Cruz Biotechnology, Inc., Santa Cruz, CA), and GAS7 (1:1000) (Proteintech Group, Inc., Chicago, IL). RNA Extraction and Quantitative Real Time RT-PCR (qPCR)

Total RNA of each group was extracted using Trizol (Invitrogen, Carlsbad, CA). Reverse transcription was carried out with SuperScript First-Strand Synthesis System (Invitrogen, Carlsbad, CA). Gene products were analyzed using Fast EvaGreen qPCR Master Mix (Biotium, Hayward, CA) and specific primers in StepOne Real-Time PCR System (Applied Biosystems). Reaction components in each well were composed of 2× Fast EvaGreen Master Mix, 10 μL; primers, 1 μL each; template, 1 μL; ROX, 2 μL; and H2O, 5 μL. Threestep fast cycling protocol was performed. Relative gene expression levels were calculated as ratios of the mRNA levels normalized against those of β-actin mRNA. All the results were expressed as the mean ± SD of three independent experiments. Primer sequences are provided in Supporting Information Table 1. Protein Extraction

MATERIALS AND METHODS

RSC96 and primary cultured SCs were washed thoroughly with ice-cold PBS and lysed in a buffer containing 50 mM Tris-HCl (pH 7.6), 5 mM EDTA, 50 mM NaCl, 30 mM sodium pyrophosphate, 50 mM NaF, 0.1 mM Na3VO4, 1% (v/v) Triton X-100, 1 mM PMSF, and protease inhibitor mixture (Roche Applied Science). The lysates were then clarified by centrifugation at 15 000g for 20 min at 4 °C, the supernatant was collected, and Bradford Method (Bio-Rad, Richmond, CA) was used to determine the protein concentration.

Cell Culture

The rat SCs were isolated and purified as previously described12 with minor modifications. Briefly, sciatic nerves were harvested from Sprague−Dawley rats (0−3 d) and enzymatically dissociated by incubation at 37 °C sequentially with 1% collagenase and 0.125% trypsin for 30 and 10 min, respectively. The mixture was then triturated and centrifuged. The obtained cell pellets were resuspended in Dulbecco's Modified Eagle Medium (DMEM) containing 10% fetal bovine serum (FBS) and plated onto poly-L-lysine precoated dishes. On the following day, 10 μM cytosine arabinoside was added and allowed to incubate for 48 h to selectively remove fibroblasts. Afterward, the cells were maintained in DMEM supplemented with 10% FBS, 2 μM forskolin (Sigma, St Louis, MO), and 2 ng/mL heregulin (HRG, Sigma) to stimulate SC proliferation. For further purification, the cells were gently trypsinized, pelleted, and incubated with anti-Thy1 antibody (AbD Serotec, Raleigh, NC) on ice for 2 h, followed by incubation in complement (Jackson Immuno, West Grove, PA) for an additional 2 h. For biological replication, primary SCs were isolated and purified from three batches of rats separately. RSC96, a spontaneously immortalized rat SC line derived from the long-term culture of rat primary SCs, was obtained from the American Type Culture Collection (ATCC) and cultured in

Western Blot

Samples containing 15 μg of total protein were separated by 12% (w/v) SDS-PAGE and transferred onto a PVDF membrane (Millipore, Bedford, MA). After incubating for 1 h with blocking buffer (5% (w/v) nonfat milk in 0.05% (v/v) TBS-T (Tween 20 in Tris-buffered saline)), the membrane was probed with the indicated primary antibodies diluted in blocking buffer overnight at 4 °C. After extensive washing with TBS-T, the membrane was incubated with IRDye 800conjugated secondary antibody diluted in a blocking buffer (1:5000, Odyssey) for 1 h at room temperature. The images were scanned with Odyssey Infrared Imaging System (LI-COR Bioscience, Inc.) and the optical density (OD) was analyzed using Quantity One software (v4.5.0, Bio-Rad). The following antibodies were used: rabbit polyclonal antibody to TUBB3 (1:1000) (Santa Cruz Biotechnology, Inc., Santa Cruz, CA), 3187



Article

fragmented in MS/MS scan, they were allowed one repetition before a dynamic exclusion for a period of 120 s. Because of iTRAQ tags, the parameters for rolling collision energy (automatically set according to the precursor m/z and charge state) were manually optimized. External calibration of the mass spectrometer was conducted routinely using reserpine and trypsinized bovine serum albumin (BSA).

GAS7, MCAM, FERMT2 (1:1000) (Proteintech Group, Inc., Chicago, IL), and CADM4, NDRG2 (Abcam) (1:1000), mouse monoclonal antibody to β-actin (1: 4000, Sigma Aldrich, St. Loius, MO). iTRAQ Labeling, Sample Cleaning, and Desalting

iTRAQ labeling and sample cleaning were performed as described.13 In brief, 100 μg of proteins from primary SCs and RSC96 were precipitated with ice-cold acetone overnight at −20 °C. The pellets were dissolved, denatured, alkylated, and digested with trypsin 1:20 (w/w), at 37 °C for 18 h. The peptides were then labeled according to the manufacturer’s protocol (Applied Biosystems, Foster City, CA). In this study, SCs and RSC96 were labeled with 116 and 117 iTRAQ reagents, respectively, and three independent biological replications were performed. Prior to online 2D nano LC/ MS/MS analysis, iTRAQ-labeled samples were cleaned and desalted. A cation exchange cartridge system (Applied Biosystems) was used to remove the reducing reagent, SDS, excess iTRAQ reagents, undigested proteins, and trypsin in the labeled sample mixture, as these would interfere with LC/MS/ MS analysis. Eluates from strong cation exchange (SCX) column (PolyLC, Inc.) were desalted on a C18 reversed-phase column (4.6-mm-inner diameter × 150-mm, 5 μm, 80 Å; Agilent, Waldbronn, Germany).

Protein Identification and Relative Quantitation

The MS raw data were analyzed essentially as described.13 In brief, ProteinPilot Software 3.0.1 (Applied Biosystems, Software Revision Number: 67476; Applied Biosystems) was used to identify and quantify peptides and proteins. The complete set of raw data files (*.wiff) were searched against the nonredundant International Protein Index (IPI) database (rat v3.62, 40 041 entries) using the Paragon and ProGroup algorithms (Applied Biosystems). In this study, a protein with a confidence threshold of 95% (unused confidence threshold Protscore >1.3) was reported and the corresponding False Discovery Rate (FDR) was less than 1%. The relative abundance of proteins was calculated by the ProteinPilot Software based on individual peptide ratios. In this study, the threshold of differential expression was the mean ± 1.64 SD (90% confidence interval). Bioinformatics Analysis of Differentially Expressed Proteins

Online 2D Nano LC/MS/MS

The bioinformatics analysis of the differentially expressed proteins was performed with Ingenuity Pathways Analysis (IPA) software (version 6.3, Ingenuity Systems, Redwood City, CA, http://www.ingenuity.com). The differentially expressed proteins and the corresponding expression values were uploaded into the software and assigned to different molecular and cellular functional classes based upon the underlying biological evidence from the curated Ingenuity Pathways Knowledge Base. Functional networks of these proteins were algorithmically generated based on their connectivity, and ranked in terms of relevancy to the proteins in the input data set. The p-value was calculated by using the right-tailed Fisher Exact Test. In addition, to obtain a more detailed and precise view of the biological significance of the altered proteins, these differently expressed proteins were further categorized according to their main biological functions collected from the Uniprot protein knowledge database (http://www.uniprot. org) and PubMed (http://www.ncbi.nlm.nih.gov).

Online 2D nano LC-MS/MS experiments were performed essentially as described,13 2D nano-LC/MS/MS analysis was conducted on a nano-HPLC system (Agilent, Waldbronn, Germany) coupled to a hybrid Q-TOF mass spectrometer (QSTAR XL, Applied Biosystems) equipped with a nano-ESI source (Applied Biosystems) and a nano-ESI tip (Picotip, New Objective, Inc., Woburn, MA). Analyst 1.1 software was used to control QSTAR XL mass spectrometry and the nano-HPLC system as well as to acquire mass spectral data. Vacuum-dried, iTRAQ-labeled, and purified peptides were reconstituted in phase A and injected at a flow rate of 10 μL/min onto a highresolution SCX column (Bio-SCX, 300-μm inner diameter × 35 mm; Agilent, Wilmington, DE), which was on line with a C18 precolumn (PepMap, 300-μm inner diameter × 5 mm; LC Packings). After loading, the SCX column and C18 precolumn were flushed with a 16-step gradient sodium chloride solution (0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 125, 150, 200, 300, and 400 mM) for 5 min and phase A, for 10 min at a flow rate of 10 μL/min. Afterward, the precolumn was switched on line with a nanoflow reversed-phase column (100 μm i.d. 150 mm, 3.5 μm, 100 Å, Agilent Technologies), and the peptides concentrated and desalted on the precolumn were separated on the nanoflow C18 column at a flow rate of 300 nL/min; the gradient induced a linear increase of 4−40% acetonitrile in 0.5% acetic acid over 90 min. Eluted peptides were electrosprayed through a noncoated silica tip (Picotip, New Objective, Inc., Woburn, MA). The Q-TOF was operated in positive-ion mode with ion spray voltage (IS) typically maintained at 2.0 kV. Mass spectra of iTRAQ-labeled samples were acquired in an informationdependent acquisition (IDA) mode. The analytical cycle consisted of a 0.7 s MS survey scan (400−1600 m/z) followed by three 2 s MS/MS scans (100−2000 m/z) of the three most abundant peaks (i.e., precursor ions) which were selected from the MS survey scan. Precursor ions selection was based upon ion intensity (peptide signal intensity above 25 CPS (counts per second)) and charge state (+2 to +5). Once the ions were

siRNA Transfection

According to the manufacturer’s protocol (Sigma-Aldrich), SCs cultured in 24-well plates or 6-cm dishes were transfected at 50−70% confluence with siRNAs targeting rat CADM4, FERMT2, and MCAM by means of the siRNA transfection reagent RNAiMAX (Invitrogen, Carlsbad, CA). Nontargeting control (NTC) siRNA was transfected simultaneously as negative control. After 48 h transfection, the efficiency of siRNA-mediated mRNA and protein degradation was assessed by RT-PCR and WB, respectively. Cell Adhesion and Migration Assay

Untreated 96-well plates were coated with 10 μg/mL collagen type I or laminin (Sigma-Aldrich) overnight at 37 °C, then 1% BSA was applied to block nonspecific adhesion. SCs transfected with siRNAs and NTC siRNA were seeded into triplicate wells at 1 × 105 cells/well and allowed to attach for 60 min at 37 °C. After a careful wash with prewarmed PBS, cells were fixed with 2% formaldehyde and stained by Crystal Violet (Sigma3188



Article

Detailed information on the identified proteins of three independent biological replications is provided in Supporting Information Table 2. Subsequently, proteins identified from three independent analyses were grouped and proteins with identical IPI accession numbers were merged. The total number of proteins was 1970 (Supporting Information Table 2), among which 673 (37.6%) were shared by all three experiments and 490 (24.9%) by two experiments. Thus, more than 60% (1162 of 1970) of the proteins were detected in at least two of the three experiments (Figure 2A), showing good reproducibility of the adopted proteomics platform in protein identification.

Aldrich). To compare the number of attached cells, the stained cells were lysed by 1% SDS and the OD value at 570 nm was recorded. The effect of siRNA transfecteion on SC migration was measured using a modified Boyden chamber assay. Two days after transfection, 2 × 104 cells in serum-free DMEM were plated on the upper chamber of each transwell with 8 μm pores (Costar, Corning, Inc., NY). The lower surface of transwell membranes were coated with laminin and the lower chamber contained 800 μL of completed medium. Transfected cells were incubated for 6 h at 37 °C in 5% CO2. Nonmigrating cells were removed from the upper surface of the membrane with cotton swabs. Membranes were stained with Crystal Violet and mounted onto glass slides, and migration was quantified by counting cells in four fields. Each condition was produced in triplicate and the number of migrated cells was normalized to the total number of cells on an unscraped filter to normalize the total number of cells plated. Statistical Analysis

Data were presented as the mean ± SD. Comparison between means was assessed by unpaired Student’s t-test or one-way ANOVA using SPSS10.0 software, and statistical significance was set at p < 0.05.

■

Figure 2. (A) Venn diagram depicting the overlap of proteins identified in three independent iTRAQ experiments. Number in parentheses indicates the number of identified proteins for each sample. (B) Distribution of mean ratios of 1757 identified proteins, as measured by three independent iTRAQ experiments. Ratios were calculated as RSC96 (117) versus SCs (116). The 90% confidence intervals are indicated by vertical lines in the plot.

RESULTS

Isolation, Purification, and Characterization of Primary SCs

To avoid the contamination of fibroblasts in the primary culture of SCs, a modified method for purification and expansion of SCs was adopted.12 Figure 1A,B shows the typical morphology

To evaluate the quantitative reproducibility of the present proteomics analysis, linear regressions were performed on Log2-transformed ratios of the three replicated analyses. Pearson correlation coefficients (r-value) were 0.94 between experiments 1 and 2, 0.92 between experiments 1 and 3, and 0.93 between experiments 2 and 3, respectively, with the average RSD at 14.99%, indicating good biological reproducibility (Supporting Information Figure 1 and Supporting Information Table 2). To average ratios and exclude redundancy in the three independent searches, raw data from three biological replications were combined and searched against the same IPI database using the same searching parameters. With a false discovery rate (FDR) of less than 1%, a total of 1757 proteins were identified, among which about 97% (1702/1757) were quantified. Detailed information on identified peptides and proteins is provided in Supporting Information Table 3. This data set was used for the following analysis. To characterize the differences between primary SCs and RSC96, altered proteins were determined according to their relative protein expressions (117/116 ratio). Unlike the cutoffs ranging from 1.3- to 2.0-fold, frequently used in similar quantitative proteomic studies, more stringent criteria derived from a statistical analysis of the distribution of the ratios of 1702 proteins were adopted and the threshold values for downand up-regulated proteins were ≤0.30 and ≥3.32 (90% confidence interval), respectively (Figure 2B). Therefore, compared with the primary SCs, 61 (Table 1) and 78 (Table 2) proteins were found to be significantly up- or downregulated in RSC96.

Figure 1. Characterization of primary cultured SCs and RSC96. The typical cell morphology of primary cultured SCs (A) and RSC96 (B) under phase-contrast microscopy (magnification 200× ). (C) A representative FCA histogram showed the percentage of S-100βpositive cells (M2) of primary SCs. Immunofluorescent staining showed the expression of S-100β in primary SCs, (D) S-100β staining (red), (E) Hoechst 33342 staining (blue), (F) overlay (magnification 200× ).

of primary SCs and RSC96. With the use of an antibody against S100β, a marker of mature SCs, the purity of primary SCs was quantitatively and qualitatively confirmed by flow cytometric analysis (FCA) (Figure 1C) and immunofluorescent staining (Figure 1D−F), respectively. iTRAQ Analysis of Primary SCs and RSC 96

According to the criteria for protein identification mentioned in Materials and Methods, more than 1000 proteins were identified in each of the three independent biological replicates. 3189



Article

Table 1. List of Up-Regulated Proteins in RSC96 Cell Linea accession

gene symbol

name

peptides (95%)

117:116 (RSC96/SCs)

2 2 7 1 2

4.35 9.16 4.28 6.61 4.07

6 4 3 3

4.65 3.70 3.75 5.31

14 3 5 11

4.27 5.24 3.52 6.31

2 3 8 2 1 7

4.37 3.43 3.80 3.99 4.84 3.83

3 4 2

4.00 4.05 4.60

2 8 1 6 1 3 6 3 6

4.01 5.22 5.16 9.99 15.22 15.59 4.26 4.11 4.13

4 4 12 1 1

3.92 4.45 3.59 3.69 3.56

27 1 1

4.68 3.85 3.88

11 5

3.47 3.70

2 8 1 2 1 1 1 1 2

6.12 3.32 3.56 7.89 6.66 3.96 5.12 4.68 5.89

Cell Proliferation and Growth IPI00869848.2 IPI00476171.5 IPI00369397.5 IPI00949630.1 IPI00208213.1

Akt1s1 Csf1 H2afx Mdk Zwint

IPI00950239.1 IPI00952410.1 IPI00563876.3 IPI00400725.1

Bsg Tpd52 Enah Cfdp1

IPI00203974.2 IPI00202109.3 IPI00359074.1 IPI00569885.2

Bag3 Bid Ciapin1 Hspb1

IPI00204993.1 IPI00952326.1 IPI00480820.4 IPI00952139.1 IPI00187901.1 IPI00855220.1

Vasn Dab2 Pgrmc1 PVR Fosl1 RT1-EC2

IPI00559745.1 IPI00845873.1 IPI00199726.5

Rnps1 Zranb2 Slc7a6os

IPI00195961.1 IPI00951973.1 IPI00365262.2 IPI00203725.2 IPI00212599.1 IPI00656454.2 IPI00213638.3 IPI00914200.1 IPI00373045.1

Nolc1 Csda Znf593 Hmga1 Hmga2 Hmga1 Psip1 Nsbp1 Eif4b

IPI00561560.1 IPI00326155.2 IPI00768104.1 IPI00952444.1 IPI00190202.2

Ldlr Phax Eea1 Tf S100a13

IPI00187731.4 IPI00870478.1 IPI00388137.1

Tpm2 Ppl Wipf2

IPI00362791.3 IPI00190431.5

Ubqln2 Ubap2


Cdh3 Hpcal1 Gfer Hspb8 Ccdc126 Fam3c Xtp3tpa Mgmt Ssna1

AKT1 substrate 1 Macrophage colony-stimulating factor 1 RCG57928 Midkine ZW10 interactor Differentiation 30 kDa protein (Basigin) Putative uncharacterized protein Tpd52 Putative uncharacterized protein Enah Craniofacial development protein 1 Apoptosis Bcl-2-interacting death suppressor BH3-interacting domain death agonist Anamorsin Putative uncharacterized protein Hspb1 Signal Transduction RCG49849 Protein Membrane-associated progesterone receptor component 1 Poliovirus receptor Fos-related antigen 1 MHC class Ia protein mRNA Processing mRNA Splicing Putative uncharacterized protein Rnps1 zinc finger, RAN-binding domain containing 2 solute carrier family 7, member 6 opposite strand Transcription/Transcription Regulation Nucleolar and coiled-body phosphoprotein 1 29 kDa protein Zinc finger protein 593 (Predicted), isoform CRA_a Isoform HMG-I of High mobility group protein HMG-I/HMG-Y Nonhistone chromosomal architectural protein HMGI-C Isoform HMG-Y of High mobility group protein HMG-I/HMG-Y Isoform 1 of PC4 and SFRS1-interacting protein predicted High mobility group nucleosome-binding domain-containing protein 5 Eukaryotic translation initiation factor 4B Transport Putative uncharacterized protein Ldlr Phosphorylated adapter RNA export protein early endosome antigen 1 107 kDa protein Putative uncharacterized protein S100a13 Cytoskeleton Isoform 2 of Tropomyosin beta chain Putative uncharacterized protein Ppl Putative uncharacterized protein Wipf2 Ubiquitin Related Ubiquilin 2 Putative uncharacterized protein Ubap2 Others cadherin 3 Hippocalcin-like protein 1 FAD-linked sulfhydryl oxidase ALR Heat shock protein beta-8 Ccdc126 protein FAM3C-like protein dCTP pyrophosphatase 1 Putative uncharacterized protein Mgmt Ssna1 protein

3190



Article

Table 1. continued accession IPI00764230.2 IPI00565758.1 IPI00767035.1 IPI00949944.1 IPI00555275.1 IPI00777351.2 IPI00372469.2 IPI00958017.1 IPI00188173.2 IPI00202842.1 IPI00563982.3

gene symbol LOC682920 LOC315970 LOC684934 RGD1561149

LOC687183 Rpo1−3 RGD1564093 Zc3h18

name Uncharacterized phosphatase and actin regulator 4-like Protein CDV3 homologue similar to coiled-coil domain containing 9 isoform 2 Putative uncharacterized protein RGD1561149 Putative uncharacterized protein ENSRNOP00000041060 Putative uncharacterized protein ENSRNOP00000056207 Putative uncharacterized protein ENSRNOP00000037874 Protein KRI1 homologue RCG42593, isoform CRA_b RCG51149 Putative uncharacterized protein ENSRNOP00000048376

peptides (95%)

117:116 (RSC96/SCs)

5 9 1 1 1 0 1 1 1 4 1

5.82 4.46 6.76 6.79 6.04 4.37 3.78 3.33 3.44 3.44 4.93

a The table contains the 61 proteins displaying more than 3.32-fold up-regulation (90% confidence interval) in RSC96 in 3 independent experiments. The International Protein Index (IPI) accession number, gene symbol, the name of each protein, the number of peptides identified above 95% (Peptides (95%)) and the mean iTRAQ ratios (117:116 (RSC96/SCs)) are provided here. For detailed information of these proteins, please refer to Supporting Information Table 2.

Bioinformatics Analysis of Differentially Expressed Proteins

or down-regulated proteins (Figure 3). The up-regulated proteins within unique categories were associated with cell proliferation and growth (5 proteins), apoptosis (4 proteins), ubiquitin related (2 proteins), and mRNA processing and mRNA splicing (3 proteins), whereas the down-regulated proteins within unique categories were related to neurogenesis and SC related (12 proteins), lipid metabolism (8 proteins), energy metabolism (7 proteins), cell adhesion (5 proteins), and chaperone (3 proteins). In short, both the IPA analysis and functional categorization indicated the immortalization and dedifferentiated phenotype of RSC96.

Upon the basis of the underlying biological evidence from the curated IPA literature database, the altered proteins were assigned to different molecular and cellular functional categories. As highlighted by IPA analysis, the top 5 categories of proteins overexpressed in RSC96 were directly or indirectly associated with cell proliferation and growth, including cell death (24 proteins; 1.27 × 10−6 to 2.66 × 10−2), cell growth and proliferation (22 proteins; 1.53 × 10−6 to 2.64 × 10−2), protein synthesis (6 proteins; 1.89 × 10−4 to 9.46 × 10−3), cell cycle (10 proteins; 2.48 × 10−4 to 2.38 × 10−2), and cellular development (19 proteins; 2.82 × 10−4 to 2.67 × 10−2) (Supporting Information Figure 2A). The top 5 categories of proteins suppressed in RSC96 were associated with cell morphology (20 proteins, 1.76 × 10−7 to 2.59 × 10−2), cellular assembly and organization (21 proteins; 1.76 × 10−7 to 2.58 × 10−2), cellular development (16 proteins; 1.81 × 10−5 to 2.89 × 10−2), lipid metabolism (20 proteins; 4.32 × 10−5 to 2.58 × 10−2), and small molecular biochemistry (26 proteins; 4.32 × 10−5 to 2.63 × 10−2) (Supporting Information Figure 2B). Pathway analysis was used to group proteins into different functional networks and to determine whether different cellular activities were altered in RSC96. The top network of the downregulated proteins was nervous system development and function (Supporting Information Figure 3A). These pathways were linked by NF-kB, Akt, and PDGFBB, which were not identified in our proteomic analysis. The corresponding top network of up-regulated proteins in RSC96 was primarily involved in cancer and cell death (Supporting Information Figure 3B). Although IPA analyses obtained an overview of the differences between RSC96 and primary SCs, they could not specifically demonstrate the unique features of primary SCs, a common limitation of current bioinformatics software. To achieve a precise view of the phenotypic changes, these differentially expressed proteins were further categorized according to their main biological functions collected from the UniProt protein knowledge database and relevant literature in PubMed. In this way, the differentially expressed proteins were grouped into 16 categories (Figure 3, Tables 1 and 2). The most remarkable characteristic of the functional categorization was that some categories merely contained either up-

Validation of Quantitative Proteomic Results

Although we chose stringent criteria for protein identification and used a statistical approach for determining the differentially expressed proteins, a group of proteins were selected and subjected to further confirmatory tests. In addition to the SC markers, our study identified a panel of proteins previously reported as related to neurogenesis, including growth arrest-specific protein 7 (GAS7), N-myc downstream regulated gene 2 (NDRG2), and class III β-tubulin (TUBB3), among which TUBB3 is a well-known neuronspecific marker. This study provided the first report for the identification of these proteins in primary SCs, and the differential expressions of these proteins between primary SCs and RSC96 was thoroughly validated (Figure 4). An intriguing finding was the different subcellular localization of TUBB3, which was expressed predominantly in the cytoplasm of primary SCs, while nuclear localization of this protein was observed in RSC96 (Figure 4C). Furthermore, up- or down-regulation of 28 proteins was further validated by qPCR. Despite the different magnitude of changes between protein and gene expressions, their variation trends were consistent with each other (Supporting Information Table 4). Requirement of CADM4, FERMT2 and MCAM in SCs Adhesion and Migration

SCs migrate extensively during development, which constitutes a crucial and limiting step in recovery from PNS injuries and neuropathies.14 The present study identified a number of proteins involved in cell adhesion and migration, such as cell adhesion molecule 4 (CADM4), fermitin family homologue 2 (FERMT2), and melanoma cell adhesion molecule (MCAM), whose expression levels in RSC96 were, respectively, sup3191



Article

Table 2. List of Down-Regulated Proteins in RSC96 Cell Linea accession

gene symbol

IPI00332042.9 IPI00870112.1 IPI00231058.1 IPI00231537.4 IPI00210399.1 IPI00326923.3 IPI00382069.1 IPI00325609.4 IPI00201261.2 IPI00204445.1 IPI00475835.3 IPI00231771.5

Aldh1a1 Dpysl2 Entpd2 Gas7 Gfra1 Mpz Ndrg2 Nefm Nes Ngfr Phgdh S100b

IPI00362243.7 IPI00326305.3 IPI00206977.1 IPI00780824.1 IPI00558791.3 IPI00197711.1 IPI00209908.1

Ak3 Atp1a1 Cs Dld Idh1 Ldha Mt-co2

IPI00382233.1 IPI00359688.3 IPI00951644.1 IPI00948650.1 IPI00882405.1 IPI00213659.3 IPI00948716.1 IPI00327830.3

Acat2 Abhd4 Fdps Cyp11a1 Dci Decr1 Ppt1 Fabp5


Rbp1 Bcap31 Ap2m1 Kpna5 Cse1l Sar1a Slc25a3 Tmed10 Tmem43

IPI00210257.1 IPI00421857.1 IPI00896761.2 IPI00197786.3 IPI00362927.1 IPI00655259.1 IPI00362160.1

Dynlt1 Krt1 LOC683788 Shroom2 Tuba4a Tubb2b Tubb3


Plat Serpinh1 Col5a1 Fermt2 Cadm4 Mcam Vtn Flot2

IPI00230981.1 IPI00364932.2 IPI00208154.1

Vac14 Rsu1 Cd81

protein name Neurogenesis and Schwann Cell Related Retinal dehydrogenase 1 Dihydropyrimidinase-related protein 2 Isoform 2 of Ectonucleoside triphosphate diphosphohydrolase 2 Growth arrest-specific protein 7 GDNF family receptor alpha-1 Myelin protein P0 Isoform 1 of Protein NDRG2 Neurofilament medium polypeptide Isoform 2 of Nestin Tumor necrosis factor receptor superfamily member 16 D-3-phosphoglycerate dehydrogenase Protein S100−B Energy Metabolism GTP:AMP phosphotransferase mitochondrial Sodium/potassium-transporting ATPase subunit alpha-1 Citrate synthase, mitochondrial Putative uncharacterized protein Dld 47 kDa protein L-lactate dehydrogenase A chain Cytochrome c oxidase subunit 2 Lipid Metabolism Ab2-076 Putative uncharacterized protein Abhd4 Ac2-125 61 kDa protein Dodecenoyl-coenzyme A delta isomerase 2,4-dienoyl-CoA reductase, mitochondrial 32 kDa protein Fatty acid-binding protein, epidermal Transport Retinol-binding protein 1 B-cell receptor-associated protein 31 Putative uncharacterized protein Ap2m1 Importin subunit alpha-6 Putative uncharacterized protein Cse1l SAR1 homologue A Solute carrier family 25 (Mitochondrial carrier Transmembrane emp24 domain-containing protein 10 Transmembrane protein 43 Cytoskeleton Dynein light chain Tctex-type 1 Keratin, type II cytoskeletal 1 Fascin Protein Shroom2 Tubulin alpha-4A chain Tubulin beta-2B chain Tubulin beta-3 chain ECM and Cell Adhesion Tissue-type plasminogen activator Serpin H1 Collagen alpha-1(V) chain RCG61183, isoform CRA_b Cell adhesion molecule 4 Isoform 2 of Cell surface glycoprotein MUC18 Aa1018 50 kDa protein Signal Transduction Protein VAC14 homologue RCG55799, isoform CRA_a CD81 antigen 3192

peptides (95%)

117:116 (RSC96/SCs)

8 11 4 2 1 8 3 5 35 5 3 14

0.22 0.26 0.25 0.22 0.17 0.25 0.22 0.10 0.26 0.20 0.23 0.15

1 8 1 3 11 23 4

0.28 0.28 0.18 0.20 0.25 0.28 0.24

1 1 4 3 2 1 1 5

0.23 0.26 0.27 0.13 0.23 0.29 0.18 0.29

3 2 1 1 2 1 2 5 2

0.19 0.24 0.22 0.16 0.25 0.31 0.26 0.27 0.20

1 1 4 1 30 87 48

0.22 0.27 0.25 0.27 0.26 0.12 0.19

1 32 6 4 4 10 3 1

0.25 0.25 0.25 0.30 0.21 0.25 0.19 0.29

1 6 3

0.20 0.27 0.21



Article

Table 2. continued accession

gene symbol

protein name

peptides (95%)

117:116 (RSC96/SCs)

15 8

0.25 0.26

3 3 2 2 1

0.25 0.28 0.30 0.28 0.22

1 3 15

0.25 0.28 0.14

9 2 1 7 3 1 7 1

0.24 0.21 0.25 0.22 0.20 0.14 0.27 0.27

1 3 2 4 1 2

0.12 0.17 0.25 0.27 0.23 0.20

Signal Transduction IPI00325135.3 IPI00230835.5

Ywhae Ywhag

IPI00192140.2 IPI00190557.2 IPI00231474.5 IPI00421451.5 IPI00360075.2

Fam129a Phb2 Rps15a Rps16 Lrpprc

IPI00421326.3 IPI00370815.4 IPI00207355.4

Dnajb11 Cct8 Hspa2


Tkt Ahcy Ctsc Gbp2 Gstm1 Hsdl2 Ppp2r1a Ppp2r4

IPI00189490.3 IPI00950560.1 IPI00958425.1 IPI00959848.1 IPI00765663.1 IPI00957208.1

Osap RGD1563532 RGD1565416 LOC683099 LOC683313

14-3-3 protein epsilon 14-3-3 protein gamma Transcription and Translation Protein Niban Prohibitin-2 40S ribosomal protein S15a ribosomal protein S16 Leucine-rich PPR motif-containing protein, mitochondrial Chaperone DnaJ homologue subfamily B member 11 Putative uncharacterized protein Cct8 Heat shock-related 70 kDa protein 2 Others transketolase Adenosylhomocysteinase Putative uncharacterized protein Ctsc Guanylate nucleotide binding protein 2 Glutathione S-transferase Mu 1 54 kDa protein Protein phosphatase 2 (Formerly 2A), regulatory subunit A, alpha isoform Protein phosphatase 2A, regulatory subunit B Uncharacterized RCG50000, isoform CRA_c Putative uncharacterized protein ENSRNOP00000058924 rCG31687-like isoform 2 similar to talin 2 isoform 4 similar to zinc finger protein 341 isoform 1 keratin 6A-like

a

The table contains the 78 proteins displaying more than 0.31-fold down-regulation (90% confidence interval) in RSC96 in 3 independent experiments. The International Protein Index (IPI) accession number, gene symbol, the name of each protein, the number of peptides identified above 95% (Peptides (95%)) and the mean iTRAQ ratios (117:116 (RSC96/SCs)) are provided here. For detailed information of these proteins, please refer to Supporting Information Table 2.

components of PNS, were investigated by cell adhesion assay. No significant differences were observed between normal and NTC control; however, compared with NTC control, the binding of SCs to both collagen type I and laminin was mildly suppressed by CADM4, MCAM, or FERMT2-siRNA transfection, and there were no significant differences among them (Figure 5D). Moreover, knockdown of CADM4, MCAM, and FERMT2 also significantly inhibited SC migration, and the inhibitory effect of FERMT2 knockdown on SC migration was stronger than CADM4 and MCAM knockdown (Figure 5E,F). These data indicated that knockdown of CADM4, FERMT2, and MCAM by siRNA transfection could partially block primary SC adhesion and migration. To our knowledge, this was the first demonstration of the involvement of these three proteins in SC adhesion and migration.

pressed to 0.30, 0.21, and 0.25 of that in primary SCs (Table 2). Consistent with quantitative proteomic analysis, both qPCR (Supporting Information Table 4) and Western blot (Figure 5A) confirmed the significant down-regulation of these proteins in RSC96. Despite CADM4 expression in SCs and its mediation of SC−axon interaction during myelination,15 the expression of other 2 proteins in SCs was first evidenced by the present study. To gain further insights into the roles of these three proteins in SC adhesion and migration, their expression was selectively suppressed by siRNAs transfection. The qPCR analysis showed that as compared with untransfected or mock-transfected SCs, no changes in the mRNA level of CADM4, FERMT2, and MCAM were observed in cells transfected with NTC siRNA (Figure 5B showing only the representative data for MCAM). The rationally designed siRNAs were functional, with more than 80% CADM4, MCAM, and FERMT2 mRNAs inhibited by 3# CADM4-siRNA, 2# MCAM-siRNA, and 3# FERMT2siRNA in SCs, respectively (Figure 5B). Subsequently, the knockdown efficiencies of these three siRNAs on protein levels were validated by Western blot (Figure 5C). These data demonstrated the effective suppression of CADM4, MCAM, and FERMT2 expression by siRNA transfection. The following experiments were carried out by using the most effective siRNAs. The effects of CADM4, MCAM, and FERMT2 knockdown on collagen type I and laminin binding, two major ECM

■

DISCUSSION

A Proteomic View of the Spontaneous Immortalization of RSC96

In line with the immortalizing property of RSC96, an enriched functional category of up-regulated proteins in RSC96 was related to cellular growth and proliferation. Moreover, another enriched functional category of down-regulated proteins in RSC96 proteins was involved in energy metabolism, especially TCA, suggesting a general change from oxidative metabolism to less efficient anaerobic metabolism. Thus, like the shift toward 3193



Article

Figure 3. Functional categories of differentially expressed proteins between RSC96 and primary SCs. In total, 61 up- and 78 down-regulated proteins (90% confidence interval) were classified into 16 groups according to their main biological functions collected from the UniProt protein knowledge database and relevant literature in PubMed.

Figure 4. Confirmation of the differential expression of GAS7, NDRG2, and TUBB3 in SCs and RSC96. Primary SCs and RSC96 grown on coverslips were immunofluorescently stained with anti-GAS7 (A), anti-NDRG2 (B), and anti-TUBB3 (C) (green), and nuclei were counterstained with Hochest (blue), bar = 100 μm. Total RNA and whole-cell protein lysates were obtained from primary SCs and RSC96, and the gene (D) and protein (E) levels of GAS 7, NDRG2, and TUBB3 were probed by primers or antibodies against the specific gene or proteins, respectively. β-Actin was used as a loading control. 3194



Article

Figure 5. CADM4, MCAM, and FERMT2 were required for SC adhesion and migration. (A) Down-regulation of CADM4, FERMT2, and MCAM in RSC96 was confirmed by Western blot. (B) Knockdown efficiency of CADM4, MCAM, and FERMT2-targeting siRNAs was evaluated in primary SCs, three siRNAs for each target. Primary SCs were transfected with CADM4, MCAM, and FERMT2-specific siRNA or with NTC siRNA. Fortyeight hours after transfection, their mRNA levels were determined by qPCR (n = 3/group). (C) siRNA-mediated suppression of target gene expression in SCs. SCs were transfected with CADM4, FERMT2, and MCAM-specific siRNA or with NTC siRNA for 48 h. The cell extracts were subjected to Western blot to detect the levels of these endogenous proteins; the same blots were probed for β-actin as a loading control. Each blot represents three independent experiments. (D) Knockdown of CADM4, MCAM, and FERMT2 by siRNA transfection suppressed the adhesion of SCs. siRNAs transfected SCs were plated on wells coated with collagen type I (upper), and laminin (lower); adhesion was allowed to proceed for 1 h; *p < 0.01 compared with NTC cells. (E) CADM4, MCAM, and FERMT2 were required for SC migration. Representative images of SCs transfected with siRNAs that migrated to the underside of Transwell membranses. (F) Quantitative results of cell migration. Data are expressed as mean ± SD (n = 3); *p < 0.01 compared with NTC cells.

number of proteins that may be responsible for the immortalization of RSC96. Wallerian degeneration (WD) is the inflammatory response of peripheral nerves to injury. Evidence shows that granulocyte macrophage colony stimulating factor (GM-CSF) contributes to the initiation and progression of WD by activating macrophages and SCs.21 In the present study, through functional category analysis and literature review, we found that several proteins directly participating in CSF signaling transduction were significantly up-regulated in RSC96, including CSF1, disabled homologue 2 (DAB2), and cold shock domain-containing protein A (CSDA). DAB2 is a component of the CSF-1 signaling pathway22 and CSDA is a binding protein of the GM-CSF promoter.23 We also noted the up-regulation of midkine (MDK), a heparin-binding cytokine, in RSC96. Since it has been evidenced that either gene transferinduced overexpression of MDK or exogenous administration of MDK promotes the growth, survival, and migration of SCs as well as inhibits neuronal cell death,24−26 we rationally assumed that MDK could be another contributor to stimulation of RSC96 proliferation. In addition to the aforementioned growth factors, overexpression of growth factor receptors could also contribute to the immortalization of RSC96. Progesterone receptor mem-

the glycolytic metabolic pathways of cancer cells, referred to as the Warburg effect,16,17 the spontaneously immortalized RSC96 showed similar metabolic features. These two prominent features of RSC96, consistent with the features of a tumorderived cell line,9 probably represented the common characteristics of all immortalized cell lines. Unlike immortalization by oncogene transfection or virus infection, spontaneous immortalization is the ability of normal diploid cells to overcome senescence in the absence of deliberately added exogenous agents. Our study also disclosed a conspicuous discrepancy between Hepa1-6, a tumorogenic cell line, and RSC96, a spontaneous immortalization cell line: the asymmetric distribution of the expression ratios of proteins identified in Hepa1-69 versus the symmetric distribution of those in RSC96. Thus, except for some common mechanisms, the spontaneous immortalized cell lines should have their own unique features. To date, however, the molecular mechanisms underlying spontaneous immortalization remain largely unknown.18,19 It has been postulated that environmental and/or endogenous DNA-damaging events may be potential contributors to spontaneous immortalization. The enhanced expression of vascular endothelial growth factor (VEGF), for example, is associated with spontaneous immortalization of murine fibroblasts.20 In the present study, we identified a 3195



Article

The most interesting finding of the present study was the identification of a number of novel proteins involved in cell adhesion and migration, such as CADM4, FERMT2, and MCAM. CADMs are a small group of the Ig-CAM superfamily. Members of this superfamily are often regarded as key components of intercellular adhesion, such as NCAM, ICAMs, and nectins. Until now, four members of this group, CADM1−4, have been identified. It has been reported that neurons and SCs express distinct sets of CADM proteins: axons highly express CADM1 and CADM3, and SCs express CADM4.15,33 More importantly, CADMs mediate axon−SC interaction along the internode and are indispensable for myelination.15 Consistent with previous reports, CADM4 was identified in primary SCs, and its roles in the adhesion and migration of SCs were revealed by knockdown experiments. Although interactions between ECM proteins and integrins are critical to radial sorting, ensheathment, and myelination, the downstream signaling pathways are still poorly understood.34 FERMT2 (also called Kindlin-2, PLEKHC1, or Mig-2) is a novel integrin-interacting focal adhesion protein belonging to the FERMT family. The structural hallmark of FERMTs is a FERM (band 4.1/ezrin/radixin/moesin) domain, and FERMT1 and 2 can directly bind the C-terminal region of integrin cytoplasmic tails and exert integrin-specific activation effects.35 A newly published report demonstrates that FERMT2 deficient cells are unable to activate their integrins, and thus, FERMT2 is required for integrin outside-in signaling to enable firm adhesion and spreading.36 The present study identified and validated the expression of FERMT2 in SCs and its downregulation in RSC96, as well as the necessity of FERMT2 in SC adhesion and migration. MCAM was originally reported to be involved in the invasion and progression of melanoma and is regarded as a critical marker of melanoma metastasis.37 Many studies indicate that MCAM is widely expressed in many different cell types and tissues, including activated T lymphocytes38 and normal human CNS.39 The roles of MCAM in tumorigenesis and metastasis have been well established and the acquisition of the metastatic phenotype is associated with overexpression of MCAM.40 Although previous studies validated the expression of MCAM in normal human SCs41 and schwannomas,42 the biological functions of this protein in SCs are unclear. According to previous studies and the down-regulation of MCAM in the dedifferentiated RSC96 cell line, we assumed and confirmed the roles of MCAM in the adhesion and migration of SCs. Compared with CADM4 and FERMT2, however, MCAM knockdown exerted weaker effects on the adhesion and migration of SCs. Finally, the present study demonstrates that proteomic strategies are beneficial to our understanding of SC biology. Unlike the complicated signal-sequence trap technique15 or generating a panel of monoclonal antibodies against SC surface antigens31 to identify novel cell surface proteins expressed by SCs, the present study exemplified the power of the quantitative proteomic technique based on iTRAQ labeling and LC/MS/MS in identifying novel proteins of SCs. The obtained proteomic profile would be useful for exploring the molecular events governing the onset and progression of myelination.

brane components 1 (PGRMC1) is a membrane-associated progesterone receptor component. A recent study revealed that PGRMC1/2 mediates the proliferative effect of progesterone on rat neural progenitor cell.27 Our results were the first to demonstrate the expression of PGRMC1 in SCs and the overexpression of PGRMC1 could contribute to the immortalization of RSC96. Moreover, immortalization of RSC96 needs to overcome apoptosis. In the present study, an enriched category of upregulated proteins was involved in apoptosis, including Bcl-2interacting death suppressor (BAG3), BH3-interacting domain death agonist (BID), cytokine-induced apoptosis inhibitor 1/ anamorsin (CIAPIN1), and heat shock protein beta-1 (HSPB1). Except for BID, these proteins exert antiapoptotic activities, among which CIAPIN1 is a newly identified antiapoptotic protein overexpressed in hepatocellular carcinoma.28 The influences of its overexpression on the immortalization of RSC96 was worthy of further investigation. Taken together, our results suggested that the immortalization of RSC96 could be attributed to the coordinated upregulation of cell proliferation associated proteins, growth factor receptors, antiapoptotic proteins, and the simultaneous up-regulation of proteins involved in mRNA processing, mRNA splicing, transcription, and translation. Identification of Cell Adhesion and Migration Related Proteins in Primary SCs

The formation of myelinated fibers requires reciprocal communication between SCs and their associated axons, and SCs express elevated levels of ECM and adhesion molecules during development and regeneration of PNS. Accordingly, the present study identified a group of proteins related to cell adhesion and migration, and their expression was significantly suppressed in RSC96. Collagens and laminins, two major ECM proteins, provide the substrate on which SCs reside, influence the behavior of SCs through receptor interaction, and trigger different intracellular signals to regulate SC proliferation and differentiation.14 As could be expected, collagens and laminins, including collagen alpha-1(I) chain (COL1a1), collagen alpha1(V) chain (COL5a1), collagen type V alpha 2 (COL5a2), laminin beta 1 (LAMB1), and laminin gamma 1 (LAMC1), were down-regulated in RSC96, although their ratios were below the adopted threshold. The pivotal roles of LAMC1 and COL5a in PNS development have been well studied.14 Mouse SCs lacking the lamc1 completely lose all laminin subunit expression, and mice carrying this mutation show a severe phenotype, exhibiting impaired proliferation and differentiation as well as undergoing apoptosis.29,30 Disruption of laminin in PNS impedes nonmyelinating SC development and impairs nociceptive sensory function.29 In addition, several other proteins that have been reported as participating in SC adhesion and migration were also down-regulated in the present study, such as CD9 (0.36-fold)31 and glypican 1 (0.47fold).32 Glypican 1 is one of the two main cell surface HSproteoglycans expressed by SCs and the main type V collagen receptor in SCs. Suppressed expression of glypican-1 significantly inhibits myelination.32 Thus, down-regulation of these proteins not only manifested the phenotypic drift or the dedifferentiated state of RSC96, but also suggested the importance of these altered proteins in normal SC biology and PNS development.

■

CONCLUSIONS In the present study, iTRAQ coupled with 2D LC−MS/MS was performed to analyze the global proteomic profile and 3196



Article

(2) Patricia, A. The Biology of Schwann Cells-Development, Differentiation and Immunomodulation; Cambridge University Press: Cambridge, U.K., 2007 (3) Jessen, K. R.; Mirsky, R. Control of Schwann cell myelination. F1000 Biol. Rep. 2010, 2, No. 19. (4) Lehmann, H. C.; Hoke, A. Schwann cells as a therapeutic target for peripheral neuropathies. CNS. Neurol. Disord. Drug Targets 2010, 9, 801−806. (5) Kimura, H.; Fischer, W. H.; Schubert, D. Structure, expression and function of a schwannoma-derived growth factor. Nature 1990, 348, 257−260. (6) Frohnert, P. W.; Stonecypher, M. S.; Carroll, S. L. Constitutive activation of the neuregulin-1/ErbB receptor signaling pathway is essential for the proliferation of a neoplastic Schwann cell line. Glia 2003, 43, 104−118. (7) Badache, A.; De Vries, G. H. Neurofibrosarcoma-derived Schwann cells overexpress platelet-derived growth factor (PDGF) receptors and are induced to proliferate by PDGF BB. J. Cell Physiol. 1998, 177, 334−342. (8) Hai, M.; Muja, N.; DeVries, G. H.; Quarles, R. H.; Patel, P. I. Comparative analysis of Schwann cell lines as model systems for myelin gene transcription studies. J. Neurosci. Res. 2002, 69, 497−508. (9) Pan, C.; Kumar, C.; Bohl, S.; Klingmueller, U.; Mann, M. Comparative proteomic phenotyping of cell lines and primary cells to assess preservation of cell type-specific functions. Mol. Cell. Proteomics 2009, 8, 443−450. (10) Lin, T. Y.; Kuo, C. D. Bovine lactoferrin protects RSC96 Schwann cells from tumor necrosis factor-alpha-induced growth arrest via extracellular-signal-regulated kinase 1/2. Neuroscience 2008, 151, 396−402. (11) Chang, C. Y.; Lee, Y. H.; Jiang-Shieh, Y. F.; Chien, H. F.; Pai, M. H.; Chen, H. M.; Fong, T. H.; Wu, C. H. Novel distribution of cluster of differentiation 200 adhesion molecule in glial cells of the peripheral nervous system of rats and its modulation after nerve injury. Neuroscience 2011, 183, 32−46. (12) Weinstein, D. E.; Wu, R. Isolation and purification of primary Schwann cells. Curr. Protoc. Neurosci. 2001, 3, No. Unit 3.17. (13) Ji, Y. H.; Ji, J. L.; Sun, F. Y.; Zeng, Y. Y.; He, X. H.; Zhao, J. X.; Yu, Y.; Yu, S. H.; Wu, W. Quantitative proteomics analysis of chondrogenic differentiation of C3H10T1/2 mesenchymal stem cells by iTRAQ labeling coupled with on-line two-dimensional LC/MS/ MS. Mol. Cell. Proteomics 2010, 9, 550−564. (14) Chernousov, M. A.; Yu, W. M.; Chen, Z. L.; Carey, D. J.; Strickland, S. Regulation of Schwann cell function by the extracellular matrix. Glia 2008, 56, 1498−1507. (15) Spiegel, I.; Adamsky, K.; Eshed, Y.; Milo, R.; Sabanay, H.; SarigNadir, O.; Horresh, I.; Scherer, S. S.; Rasband, M. N.; Peles, E. A central role for Necl4 (SynCAM4) in Schwann cell-axon interaction and myelination. Nat. Neurosci. 2007, 10, 861−869. (16) Ferreira, L. M. Cancer metabolism: the Warburg effect today. Exp. Mol. Pathol. 2010, 89, 372−380. (17) Hsu, P. P.; Sabatini, D. M. Cancer cell metabolism: Warburg and beyond. Cell 2008, 134, 703−707. (18) Cukusic, A.; Skrobot, V. N.; Sopta, M.; Rubelj, I. Telomerase regulation at the crossroads of cell fate. Cytogenet. Genome Res. 2008, 122, 263−272. (19) Wewetzer, K.; Radtke, C.; Kocsis, J.; Baumgartner, W. Speciesspecific control of cellular proliferation and the impact of large animal models for the use of olfactory ensheathing cells and Schwann cells in spinal cord repair. Exp. Neurol. 2011, 229, 80−87. (20) Sugihara, T.; Kaul, S. C.; Mitsui, Y.; Wadhwa, R. Enhanced expression of multiple forms of VEGF is associated with spontaneous immortalization of murine fibroblasts. Biochim. Biophys. Acta 1994, 1224 (3), 365−370. (21) Be’eri, H.; Reichert, F.; Saada, A.; Rotshenker, S. The cytokine network of wallerian degeneration: IL-10 and GM-CSF. Eur. J. Neurosci 1998, 10, 2707−2713. (22) Sheng, Z.; Smith, E. R.; He, J.; Tuppen, J. A.; Martin, W. D.; Dong, F. B.; Xu, X. X. Chromosomal location of murine disabled-2

determine 139 differentially expressed proteins between primary SCs and the immortalized RSC96 cell line. Bioinformatics analysis of these altered proteins provided an overview of the immortalization of RSC96, revealed significant differences between primary SCs and RSC96, and illustrated the dedifferentiation of RSC96. Since RSC96 basically lost the SC phenotype, it was not an ideal in vitro model for the biological study of SCs and necessitated a more prudent interpretation of experimental data obtained from such cell lines. More importantly, the present study identified a group of proteins closely related to the biological functions of normal SCs. The expression and roles of selected proteins were biologically validated. Identification and further analyses of these proteins will enhance our understanding of their importance in the biology and pathology of SCs. Moreover, our data also provided further evidence that iTRAQ labeling coupled with online 2D LC/MS/MS is a robust and reliable proteomic technology, suitable for biological studies of SCs.

■

ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

■

AUTHOR INFORMATION

Corresponding Author

*Tel: +86-513-85051802. Fax: +86-513-85511585. E-mail: [email protected]. Author Contributions †

These authors contributed equally to this paper.

Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This research was supported by a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, the National Natural Foundation of China (Grant Nos. 81130080, 81171180, 30600587, 30800315 and 81071483), the Nature Science Foundation of Jiangsu Province (Grant No. BK2008010), the Education Department of Jiangsu Province, China (Grant Nos. 08KJA310002 and 10KJB180006) and the Fundamental Research Funds for the Central Universities. We are highly grateful to Professor Jie Liu for his critical review.

■

ABBREVIATIONS 2D nano LC/MS/MS, two-dimensional nano scale liquid chromatography coupled with Tandem Mass Spectrometry; CADM4, cell adhesion molecule 4; CNS, central nervous system; ECM, extracellular matrix; FDR, false discovery rate; FERMT2, fermitin family homologue 2; GAS7, growth arrestspecific protein 7; iTRAQ, isobaric tags for relative and absolute quantitation; MCAM, melanoma cell adhesion molecule; MS. mass spectrometry; NDRG2, N-myc downstream regulated gene 2; PBS, phosphate buffered saline; PNS, peripheral nervous system; qPCR, quantitative real time RT-PCR; SCs, Schwann cells; TUBB3, class III β-tubulin

■

REFERENCES

(1) Jessen, K. R.; Mirsky, R.; Salzer, J. Introduction. Schwann cell biology. Glia 2008, 56, 1479−1480. 3197



Article

gene and structural comparison with its human ortholog. Gene 2001, 268, 31−39. (23) Coles, L. S.; Diamond, P.; Occhiodoro, F.; Vadas, M. A.; Shannon, M. F. Cold shock domain proteins repress transcription from the GM-CSF promoter. Nucleic Acids Res. 1996, 24, 2311−2317. (24) Mashour, G. A.; Ratner, N.; Khan, G. A.; Wang, H. L.; Martuza, R. L.; Kurtz, A. The angiogenic factor midkine is aberrantly expressed in NF1-deficient Schwann cells and is a mitogen for neurofibromaderived cells. Oncogene 2001, 20, 97−105. (25) Muramatsu, T. Midkine: a promising molecule for drug development to treat diseases of the central nervous system. Curr. Pharm. Des 2011, 17, 410−423. (26) Friedrich, C.; Holtkamp, N.; Cinatl, J., Jr.; Sakuma, S.; Mautner, V. F.; Wellman, S.; Michaelis, M.; Henze, G.; Kurtz, A.; Driever, P. H. Overexpression of Midkine in malignant peripheral nerve sheath tumor cells inhibits apoptosis and increases angiogenic potency. Int. J. Oncol. 2005, 27, 1433−1440. (27) Liu, L.; Wang, J.; Zhao, L.; Nilsen, J.; McClure, K.; Wong, K.; Brinton, R. D. Progesterone increases rat neural progenitor cell cycle gene expression and proliferation via extracellularly regulated kinase and progesterone receptor membrane components 1 and 2. Endocrinology 2009, 150, 3186−3196. (28) Li, X.; Wu, K.; Fan, D. CIAPIN1 as a therapeutic target in cancer. Expert Opin. Ther. Targets 2010, 14, 603−610. (29) Yu, W. M.; Yu, H.; Chen, Z. L.; Strickland, S. Disruption of laminin in the peripheral nervous system impedes nonmyelinating Schwann cell development and impairs nociceptive sensory function. Glia 2009, 57, 850−859. (30) Yu, W. M.; Yu, H.; Chen, Z. L. Laminins in peripheral nerve development and muscular dystrophy. Mol. Neurobiol. 2007, 35, 288− 297. (31) Anton, E. S.; Hadjiargyrou, M.; Patterson, P. H.; Matthew, W. D. CD9 plays a role in Schwann cell migration in vitro. J. Neurosci. 1995, 15, 584−595. (32) Chernousov, M. A.; Rothblum, K.; Stahl, R. C.; Evans, A.; Prentiss, L.; Carey, D. J. Glypican-1 and alpha4(V) collagen are required for Schwann cell myelination. J. Neurosci. 2006, 26, 508−517. (33) Maurel, P.; Einheber, S.; Galinska, J.; Thaker, P.; Lam, I.; Rubin, M. B.; Scherer, S. S.; Murakami, Y.; Gutmann, D. H.; Salzer, J. L. Nectin-like proteins mediate axon Schwann cell interactions along the internode and are essential for myelination. J. Cell Biol. 2007, 178, 861−874. (34) Nodari, A.; Zambroni, D.; Quattrini, A.; Court, F. A.; D’Urso, A.; Recchia, A.; Tybulewicz, V. L.; Wrabetz, L.; Feltri, M. L. Beta1 integrin activates Rac1 in Schwann cells to generate radial lamellae during axonal sorting and myelination. J. Cell Biol. 2007, 177, 1063− 1075. (35) Harburger, D. S.; Bouaouina, M.; Calderwood, D. A. Kindlin-1 and -2 directly bind the C-terminal region of beta integrin cytoplasmic tails and exert integrin-specific activation effects. J. Biol. Chem. 2009, 284, 11485−11497. (36) Montanez, E.; Ussar, S.; Schifferer, M.; Bosl, M.; Zent, R.; Moser, M.; Fassler, R. Kindlin-2 controls bidirectional signaling of integrins. Genes Dev. 2008, 22, 1325−1330. (37) Xie, S.; Luca, M.; Huang, S.; Gutman, M.; Reich, R.; Johnson, J. P.; Bar-Eli, M. Expression of MCAM/MUC18 by human melanoma cells leads to increased tumor growth and metastasis. Cancer Res. 1997, 57, 2295−2303. (38) Pickl, W. F.; Majdic, O.; Fischer, G. F.; Petzelbauer, P.; Fae, I.; Waclavicek, M.; Stockl, J.; Scheinecker, C.; Vidicki, T.; Aschauer, H.; Johnson, J. P.; Knapp, W. MUC18/MCAM (CD146), an activation antigen of human T lymphocytes. J. Immunol. 1997, 158, 2107−2115. (39) Schulz, C.; Petrig, V.; Wolf, K.; Kratzel, K.; Kohler, M.; Becker, B.; Pfeifer, M. Upregulation of MCAM in primary bronchial epithelial cells from patients with COPD. Eur. Respir. J. 2003, 22, 450−456. (40) Wu, G. J.; Fu, P.; Wang, S. W.; Wu, M. W. Enforced expression of MCAM/MUC18 increases in vitro motility and invasiveness and in vivo metastasis of two mouse melanoma K1735 sublines in a syngeneic mouse model. Mol. Cancer Res. 2008, 6, 1666−1677.

(41) Shih, I. M.; Nesbit, M.; Herlyn, M.; Kurman, R. J. A new MelCAM (CD146)-specific monoclonal antibody, MN-4, on paraffinembedded tissue. Mod. Pathol. 1998, 11, 1098−1106. (42) Shih, I. M.; Wang, T. L.; Westra, W. H. Diagnostic and biological implications of mel-CAM expression in mesenchymal neoplasms. Clin. Cancer Res. 1996, 2, 569−575.

3198


Comparative Proteomic Analysis of Primary Schwann Cells and a

Recommend Documents