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Identification of proteins involved in aggregation of human dermal papilla cells by proteomics
Journal of Dermatological Science (2007) 48, 189—197
www.intl.elsevierhealth.com/journals/jods
Identification of proteins involved in aggregation of human dermal papilla cells by proteomics Xia Rushan a, Hao Fei a,*, Mou Zhirong b, Wu Yu-zhang b a
Department of Dermatology, Southwest Hospital, Third Military Medical University, Gaotanyan Road, Chongqing 400038, China b Institute of Immunology of PLA, Third Military Medical University, Gaotanyan Road, Chongqing 400038, China Received 9 February 2007; received in revised form 10 June 2007; accepted 20 June 2007
KEYWORDS Comparative proteome; Dermal papilla cells; Heat shock protein; Mitochondrial ribosomal protein S7
Summary Background: The dermal papilla is a major component of hair, which signals the follicular epithelial cells to prolong the hair growth process. To date, little is known about the significance of the specific protein(s) express in the dermal papilla cells (DPC) with regard to their aggregative behaviour. Objectives: To identify proteins involved in aggregative behaviour of DPC, we comparatively analyzed the proteome of cells with and without aggregative behaviour. Methods: A series of methods were used, including two-dimensional gel electrophoresis (2-DE), PDQuest software analysis of 2-DE gels, peptide mass fingerprinting based on matrix-assisted laser desorption/ionisation-time of flight-mass spectrometry (MALDI-TOF-MS), and NCBInr database searching, to separate and identify differentially expressed proteins. Western blotting and reverse transcriptase polymerase chain reaction (RT-PCR) were used to validate the differentially expressed proteins. Results: Image analysis revealed that averages of 618 22 and 568 47 protein spots were detected in passages 3 and 10 DPC, respectively. Twenty-four differential protein spots were measured with MALDI-TOF-MS. A total of 17 spots yielded good spectra, and 15 spots matched with known proteins after database searching. Western blotting confirmed that heat shocking protein 70 was up-regulated in passage 3 DPC. Overexpression of mitochondrial ribosomal protein S7 was confirmed by RT-PCR, indicating that they are involved in aggregation of DPC through some signaling pathway. Conclusions: The clues provided by the comparative proteome strategy utilized here will shed light on molecular mechanisms of DPC in aggregative behaviour. # 2007 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.
Abbreviations: DPC, dermal papilla cells; HSP70, heat shock protein 70; MRPS7, mitochondrial ribosomal protein S7. * Corresponding author. Fax: +86 23 68462522. E-mail addresses: [email protected] (X. Rushan), [email protected] (H. Fei). 0923-1811/$30.00 # 2007 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.jdermsci.2007.06.013
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1. Introduction The dermal papilla cells (DPC) are specialized stroma cells which are believed to be the source of the dermis-derived signaling molecules involved in hair follicle development and in postnatal hair cycling [1]. The tendency of aggregation is one of the significant properties of the DPC, and this property is associated with their biologic function and differentiating state [2—6]. Early passage dermal papilla cells have aggregative behavior and can induce hair growth in vivo, but, upon further culturing, this property is lost (Fig. 1). Generally speaking, DPC lose the aggregative behavior and the ability of regulating and controlling the hair cycle in the passage range 6—15 [7]. However, the cellular mechanisms underlying the aggregative behavior of DPC are less known. In order to study the aggregative behavior of DPC, a variety of techniques have been used to identify genes related to the aggregative property of DPC [8,9]. These methods were used to analyze mRNA expression levels of aggregation-related genes. In protein level, many growth factors produced by DPC were found to have the function of modulating the proliferation of follicular epithelium, such as insulin-like growth factor-I, bone morphogenetic proteins, transforming growth factor-beta1 and so on. Most of these factors act as a cytokine network controlling follicle development and hair cycling [10—13]. Our recent studies had
X. Rushan et al. proved that the DPC with aggregative behavior could produce soluble molecules which can help the DPC losing aggregative behavior regain to aggregative behavior [14]. These results suggest that DPC with aggregative behavior could release soluble, functional factors which stimulate the growth of DPC and maintain the aggregative behavior of DPC. Therefore, intensive screening to search for candidate proteins in low passage DPC is needed to identify proteins that play a role in the aggregation of DPC. Advances in the studies on proteomics have made it possible to compare the total proteins of cells under different conditions on a large scale [15,16]. The proteomic strategy based on 2-DE and MALDITOF-MS has been applied in a variety of studies. In this study, by using 2-DE and MALDI-TOF mass spectrometry, we examined the protein expression profile difference in passages 3 and 10 DPC and analyzed proteins involved in the aggregative behavior globally.
2. Materials and methods 2.1. Chemicals and other materials Bis, Tris, SDS, glycine, TEMED, ammonium persulfate (APS), glycerol, ultra pure urea, bromophenol blue, acrylamide, DTT, CHAPS, agarose and Immobiline
Fig. 1 Cell morphology of DPC in passages 3 and 10. (A) Passage 3 DPC with aggregative behavior. (B) Passage 10 DPC without aggregative behavior. (C) Passage 10 DPC regain aggregative behavior.
Identification of proteins involved in aggregation of human dermal papilla cells DryStrips (pH 3—10) were purchased from Amersham Biosciences (Uppsala, Sweden). Iodoacetamide (IAA), Brilliant Blue G-250 and Collagenase D (ultra pure grade) came from Sigma (St. Louis, USA). Protease inhibitor cocktail and dispase were purchased from Roche (Switzerland). Goat Anti-human HSP70 mAb and peroxidase-conjugated goat antirabbit immunoglobulin were obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Other reagents not mentioned above were domestic made.
2.2. Dermal papilla separation and cultures The dermal papilla is derived from human (six males, three females, mean age 28 years) nonbalding scalp-skin which were obtained from plastic surgery with the informed consent of donors and approval of Southwest hospital ethical committee. Dermal papilla were isolated from scalp tissues by two-step enzyme method set up previously in our laboratory [17]. Firstly, the scalp-skin of nine volunteers was sterilized and digested in 0.5% (w/v) dispase for 12—16 h at 4 8C and in 0.2% (w/v) collagenase D for 6 h at 37 8C sequentially. The digested tissue was then centrifuged at 550—850 g for 3— 5 min. The dermal papilla was sedimentated at the bottom of tube as a clump of cells, whereas other cells floated in the supernatant. After centrifuged for several times, the human dermal papilla was separated from other types of cells and was cultured in DMEM medium supplemented with 10% foetal calf serum subsequently. DPC were mixed and incubated at 37 8C in a humidified atmosphere of 95% air and 5% CO2. The passages 3 and 10 DPC were harvested at exponential growth. The cell pellet was washed three times with 0.1 M PBS, centrifuged and froze at 70 8C.
2.3. Extraction of water soluble proteins The passages 3 and 10 DPC pellets (>108 cells) were re-suspended in 100 ml of 40 mM Tris buffer (pH 7.4) and performed by supersonic wave at 40 W for 1.5 min. Cell debris were removed by centrifugation at 12,000 g for 60 min at 4 8C. The supernatant was accurately sample normalized by Bradford’s protein assay and used for 2-DE.
2.4. 2-DE The same amount of 1 mg proteins were loaded onto 13 cm, pH 3—10 IPG strips. IPG strips were rehydrated in rehydration solution (8 M urea, 1% (w/v) CHAPS, 0.2% (w/v) DTT, 0.5% (v/v) pharmalyte
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3—10, 0.002% (w/v) bromophenol blue) over night. IEF was conducted by the IPGPhor II system (Amersham-Pharmacia Biotech) for 1 h 0 V, 12 h 30 V, 2 h 60 V, 1 h 500 V, 1 h 1000 V and at 8000 V until approximately 40,000 V h were reached. Focused strips were immediately equilibrated for 2 15 min with buffer (50 mmol/l Tris—HCl, pH 6.8, 6 mol/l urea, 30% glycerol, 2% SDS and a trace of bromophenol blue). DTT (2%, w/v) was added in the first step, and iodoacetamide (2.5%, w/v) in the second step. The strips were placed on a 1.5-mm thick, 12.5% polyacrylamide gel and sealed with 0.1% (w/v) agarose in SDS-electrophoresis buffer containing 0.01% (w/v) bromophenol blue. The electrophoresis was run for 30 min at 15 W per gel followed by a further run at 25 W per gel until the bromophenol blue band reached the bottom of the gel. Gels were fixed and stained over night with colloidal Coomassie blue and destained with deionised water until the background was significantly reduced. The gels were scanned (Gel Doc 2000; BioRad, Hercules, CA, USA), and the images were processed with PDQuest software (Ver 7.0; Bio-Rad).
2.5. In-gel tryptic digest and mass spectrometry Spots were excised from the stained gel. Destained with 25 mM ammonium bicarbonate/50% acetonitrile (Sigma) and dried with a SpeedVac plus SC1 10 (Savant Holbook, HY, USA). The gel was rehydrated in trypsin solution (Promega, Madison, WI, USA). After incubation overnight at 37 8C, peptides were first eluted with 5% TFA in 40 8C for 1 h, then 2.5% TFA/50% acetonitrile at 30 8C for 1 h and removal of acetonitrile by centrifugation in a vacuum centrifuge. The peptides were concentrated by using pipette tips C18 (Millipore, Bedford, MA). Analyses were performed primarily using MALDI-TOF mass spectrometer (Burker company, German). Peptide mixtures were analyzed using a saturated solution of a-cyano-4-hydroxycinnamic acid (Sigma) in acetone containing 1% TFA. Peptides were selected in the mass range of 800—4000 Da. The peptide sequence was determined with Mascot software. Sequence homology was analyzed using Mascot program and the NCBI BLAST online search service. Peptide masses were assumed to be monoisotopic masses, and cystines to be iodoacetamided. The peptide mass tolerance was set to 100 ppm, and the maximum of missed cleavage sites was set to 1. Species was set to homo sapiens (human). Positive identification was achieved only when a 100 ppm mass accuracy met with a significant probability PROWL software score, and nearly all dominant signals of the spectrum were assigned to the
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identified protein. Candidates were further evaluated by comparison with their calculated mass and pI, using the experimental values obtained from 2-DE.
3. Results
2.6. Western blot analysis
The DPC in passage 3 demonstrated a distinctive single cell morphology and formed cell aggregates at confluence which were believed as aggregative behavior (Fig. 1A). However, passage 10 DPC were radically different from the cell morphology of passage 3 DPC and were believed to be lost this property (Fig. 1B). DPC losing aggregation regain aggregative behaviour when cultured supernantant of low passage DPC were added to them (Fig. 1C).
The indicated amounts of protein extracts obtained from DPC were separated on a 12.5% (w/v) SDSpolyacrylamide gel. Then, proteins were transferred to PVDF membrane (Roche). After blocking with TBS-Tween 20 (TBST) containing 5% skim milk, the membranes were incubated with goat antihuman HSP70 mAb diluted 1:500 in TBST for 1 h, followed by peroxidase-conjugated goat anti-rabbit immunoglobulin diluted 1:5000 in TBST for 1 h. Finally, membranes were washed three times with TBT, and blots were developed by the enhanced chemiluminescence (ECL, Roche). As control for equal protein loading, blots were re-stained using monoclonal mouse anti-glyceraldehyde-3-phosphate dehydrogease (GAPDH) (kangchen Biotech, China). The intensity of each band was measured by Quantity one (Ver 4.5, Bio-Rad).
2.7. RT-PCR experiment Total RNA was extracted from passages 3 and 10 DPC using Tripure according to the manufacturer’s instruction. Reverse transcription with oligo(dT) priming was performed to generate cDNAs from 2 mg total RNA using Superscript II following the instruction provided by the manufacturer. DNA amplification was carried out with Taq DNA polymerase (Takara, Japan) using the following primers: b-actin (618 bp), 50 -CGG GAC CTG ACT GAC TAC CTC-30 and 50 -CAA GAA AGG GTG TAA CGC AAC-30 ; MRPS7 (287 bp), 50 -AAG CCA GTG GAG GAG CTA A-30 and 50 -GCT TGA TGG AAG ATG GTG TA-30 . PCR conditions were 94 8C for 5 min and then 26 cycles of 94 8C for 30 s, 44 8C for 30 s and 72 8C for 60 s, followed by incubation at 72 8C for 5 min for MRPS7 amplification. Amplified fragments were separated by electrophoresis on 1% agarose gels and visualized by ethidium bromide staining. The intensity of each band was measured by Quantity one (Ver 4.5, Bio-Rad), and intensity of MRPS7 were corrected by the intensity of bactin.
2.8. Statistical analysis Value is expressed as mean standard deviation (S.D.). Student’s t-test and the x2-test were used for statistical analyses. Differences were considered significant at P < 0.05.
3.1. Cell morphology in passages 3 and 10 DPC
3.2. Two-dimensional electrophoresis and image analysis of human DPC To study the different proteins involved in aggregation of DPC, total proteins of DPC were subjected to 2-DE analysis. Typical Coomassie blue-stained gels are shown in Fig. 2. Several hundred spots were clearly identifiable in each gel. Image analysis of 2-D gels revealed that averages of 618 22 and 568 47 protein spots were detected in two groups, respectively, and the majority of these protein spots were matched. About 300 protein spots were matched between passages 3 and 10 DPC, and the correlation coefficient was 0.75 by correlation analysis of gels. The unmatched spots represented those related to the aggregation of DPC as new or absent proteins, which were the main alteration of proteome. We select 24 protein spots having the difference beyond five times for further study.
3.3. Identification of spots by MALDI-TOF MS The spots of proteins were spread at the side of the 2-DE map corresponding to a 4.0—9.0 pH range. However, to ensure an exact identification, an ‘‘in-gel digestion’’ of manually excised spots was carried out using trypsin with high specificity, and the peptide mixtures deriving from tryptic hydrolysis were analyzed by MALDI-TOF MS. Out of a total of 24 spots excised from the gels, 17 spots yielded nearly perfect MALDI spectra. Fifteen spots were preliminarily identified by PMF, these being the most represented, as reported in Table 1. Fig. 3 shows the typical PMF of spot 4, whose peptides matched human transgelin. Mascot Search Results are shown in Fig. 4. The detailed matching result is listed in Table 2. The identified proteins are involved in the cellular processes of intercellular junctions, antiapoptosis, metabolism, signal transduction and protein post-translational processes. One spots with
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Fig. 2 2-DE patterns of cytoplasmic protein in passage 3 DPC (A) and passage 10 DPC (B). Protein (1.0 mg) was loaded and separated in IPG strips (pI range of 3—10), and the gels were stained with Brilliant Blue G-250. Spot numbers refer to proteins summarized in Table 1.
good MALDI spectra was returned with inconclusive match results, suggesting that it might be unknown proteins.
parallel GAPDH immunoblotting. HSP70 was found significantly up-regulated in passage 3 DPC. This result confirmed our 2-DE data.
3.4. Immunoblot confirmation of the upregulation of HSP70 in passage 3 DPC
3.5. Semi-quantity RT-PCR
To confirm and extend the 2-DE results, HSP70 expression in passage 3 was compared with that of passage 10 DPC by Western blot analysis (Fig. 5). Equal protein loading was confirmed by
A specific antibody against MRPS7 is unavailable. To test if the reduced content of MRPS7 in passage 3 DPC reflected a decrease in transcription, comparative MRPS7 RT-PCR of passages 3 and 10 DPC were performed. Primers of MRPS7 were located within
Table 1 Differential displayed protein spots preliminarily identified by PMF Spot ID NCBInr code Peptides Theoretic matched pI/Mr (kDa)
Sequence Score Protein name coverage
1 2
gij45934285 gij51479152
6/39 8/36
6.04/17,298 51% 6.60/15,820 69%
66 100
3 3-1 4
gij7705738 gij48255907 gij56967119
6/20 22/43 18/55
10/28,258 23% 8.88/22,522 68% 8.32/36,631 51%
69 168 139
5 6
gij913159 gij50345982
12/25 12/61
7.42/21,027 67% 9.42/44,476 38%
111 93
10
gij67464392
20/50
8.22/60,277 49%
87
12 16 17 18 19-1 20-1 21
gij32891807 gij13921685 gij31417921 gij62897129 gij55960375 gij50845388 gij238427
11/34 4/19 9/12 12/26 21/42 26/48 9/44
7.13/22,219 10.27/4,392 8.02/50,335 5.28/71,083 8.41/24,609 8.53/40,671 8.63/30,737
65% 65% 35% 23% 91% 64% 32%
68 69 90 108 230 236 80
", Up-regulated in passage 3 DPC; –—, expressed in passage 10 DPC. a (+) Expressed in passage 3 DPC.
Globoside synthase mutant ATP synthase, H+ transporting, mitochondrial F0 complex, subunitd isoform b Mitochondrial ribosomal protein S7 Transgelin Chain B, human annexin A2 in the presence of calcium ions Neuropolypeptide h3 ATP synthase, H+ transporting, mitochondrial F1 complex, alpha subunit isoform b Chain A, human muscle pyruvate kinase (Pkm2) Biliverdin reductase B Unnamed protein product TKT protein Heat shock 70 kDa protein Transgelin 2 Annexin A2 isoform1 Porin 31HM
Alteration a + +
" " + + +
+ + + + " " " –—
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Fig. 3 Typical MALDI-TOF-MS spectrum of spot 3-1 from the 2-DE map. The MS spectrum of the peptide mixture was obtained from a typical in-gel digestion of the 2-DE separated protein. Numbers refer to peptides are listed in Table 2 and matched peptides with transgelin are listed in Fig. 4.
exon 159 (forward) and exon 445 (reverse), respectively, generating a PCR product of 287 bp. In line with the 2-DE findings, the extent of MRPS7 expression exhibited considerable decrease in passage 10 DPC (Fig. 6).
4. Discussion In the present study, we report for the first time the application of a proteomic strategy for the comparative analysis of DPC with and without aggregative characters. Our approach was based on separation of the proteins by 2-DE, computational image analysis of the resulting proteome maps, and protein identification using mass spectrometry. Usually, large scale comparative differential gene expression studies
can be addressed in terms of mRNA (transcriptome) or protein (proteome) levels. Transcriptome technology offers some technical advantages over proteomics, such as the possibility to work with minimal quantities of biological samples and well established platforms to work in a high-throughput mode [18,19]. Nevertheless, studies in yeast and mammalian cells have shown that mRNA abundance is not directly correlated to protein levels [20,21]. This lack of correlation makes us study the aggregative behavior of DPC at the post-transcriptional level. As a method to screen proteins on a large-scale, proteomics has been driven forward by the advent of the genome era, and it has advantages in analyzing total or specific proteins from cells. In this study, we preliminarily identified 15 proteins, including transgelin, MRPS7, HSP70 and so on. Except for Porin 31
Fig. 4 Mascot search results of spot 4, which is matched with transgelin. Peptides from spot 4 are shown in bold red. Number of mass values searched is 43 and number of mass values matched is 22. Sequence coverage is 68%.
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Table 2 The detailed result of database searching of spot 4 (listed in Table 1 which matched the record gij48255907 in the NCBInr database. Theoretical MW (Da)
Peptide mass M—H+ (Da)
DMass (compared with theoretical) (Da)
Start—end
Peptide
853.38 964.50 989.58 993.46 1009.49 1081.45 1203.64 1209.55 1220.64 1236.64 1243.65 1294.63 1515.84 1529.74 1545.76 2108.11 2317.10 2741.32
853.38 964.49 989.57 993.44 1009.43 1081.46 1203.60 1209.55 1220.62 1236.62 1243.63 1294.60 1515.83 1529.71 1545.70 2108.08 2317.07 2741.45
0.01 0.01 0.01 0.02 0.06 0.00 0.01 0.00 0.01 0.03 0.03 0.03 0.01 0.03 0.05 0.03 0.02 0.13
5—12 100—108 50—57 147—154 147—154 22—29 49—57 21—29 90—99 90—99 79—89 162—172 65—78 109—121 109—121 30—47 109—128 65—89
GPSYGMSR AAEDYGVIK LGFQVWLK GDPNWFMK GDPNWFMK oxidation (M) YDEELEER QMEQVAQFLK Pyro-glu (N-term Q) KYDEELEER QMEQVAQFLK QMEQVAQFLK oxidation (M) VPENPPSMVFK EFTESQLQEGK LVNSLYPDGSKPVK TDMFQTVDLFEGK TDMFQTVDLFEGK oxidation (M) LVEWIIVQCGPDVGRPDR TDMFQTVDLFEGKDMAAVQR oxidation (M) LVNSLYPDGSKPVKVPENPPSMVFK
MH, 14 identified proteins were specific or overexpresed in DPC with aggregative behaviour. The aggregative behaviour of DPC is manifested as a result of increased production of proteins species which are in line with the Stenn’s study [22]. These proteins are related to various cellular responses, such as intercellular junctions, anti-apoptosis, cellular metabolism, signaling transduction and so on. They are novel signaling molecules or targets with no previously known function in aggregative behavior of DPC. Among 14 preliminarily identified proteins, transgelin was overexpressed in DPC with aggregation. Transgelin is an actin-binding protein of an unknown function cross-linking actin filaments. This protein is transformation sensitive and gels actin, so Shapland
et al. named it transgelin [23]. Transgelin is found in fibroblasts and smooth muscle cells. It is also present in normal mesenchymal cells, secondary cultures of mouse and rat embryo fibroblasts. But they are absent in many apparently normal fibroblast cell lines. This protein is involved in various types of cell mobility and exocytosis, and can be regulated by calcium [24]. It has been shown that down-regulation of transgelin may be an important early event in tumour progression and is discussed as a diagnostic marker for breast and colon cancer development [25]. In our study, we find that transgelin is upexpressed in passage 3 DPC and down-regulated in passage 10 DPC which may reflect cell structural
Fig. 5 HSP70 immunoblotting of passages 3 and 10 DPC. Western blot analysis revealed markedly overexpression in passage 3 DPC (P3) when compared with that in passage 10 DPC (P10).
Fig. 6 Comparative MRPS7 RT-PCR of passages 3 and 10 DPC. In line with the results at the 2-DE level, the RT-PCR results revealed marked down-regulation of MRPS7 in passage 10 DPC.
196 changes from aggregation to non-aggregation. Whether it is a marker for the aggregation of DPC need to be further investigated. A significant reduction in the levels of the porin 31 HM has been observed in DPC with aggregation. Porin 31 HM is also named voltage-dependent anion-selective channel protein 1 (VDAC-1) or outer mitochondrial membrane protein porin 1. It is a pore-forming protein discovered 26 years ago in the mitochondrial outer membrane [26]. It has recently been described as being a NADH:ferricyanide reductase in the plasma membrane where it establishes a novel level of apoptosis regulation putatively via its redox activity. It regulates the cell growth and death [27]. Porin proteins are involved in the regulation of cellular metabolism with a higher level of production reported in hypoxic neuronal cells [28]. In this study, Porin 31 HM expression was decreased in passage 3 DPC. Here, we propose that the down-regulation of porin 31 HM reflects the increase of cellular metabolism in DPC with aggregative behavior. Using a proteomics strategy, we detected two interesting proteins involved in aggregative growth of DPC. One protein was heat shock proteins 70 (HSP70). Heat shock proteins (HSPs) have a physiologic function in unstressed cells, which is believed to include a role as a ‘‘molecular chaperone’’. The participation of molecular chaperones in the process of senescence and in the mechanisms of agerelated diseases is currently under investigation in many laboratories [29]. Chaperone functions mediated by HSP family constitute a fundamental mechanism that governs the life span of organisms. Among different classes of chaperones, HSP70 are now the major candidates in the gene-longevity association studies [30]. A significant association of one HSP70 haplotype gene with male longevity was observed [31]. Mortalin is the chaperone of mitochondrial HSP70 protein which is a heat-uninducible stress protein involved in immortalization and tumorigenesis. There are two mortalin alleles, mot-1 and mot-2, in mouse. Whereas an overexpression of mot-1-induced senescence in NIH 3T3 cells, overexpression of mot-2 promoted their malignant properties. So mortalin protein have differential aging phenotypes [32]. In this work, it was upregulated in DPC with aggregative behavior. The relationship between HSP70 and aggregation of DPC has not been determined before, so it is worthy of further research. Another protein identified was human MRPS7. MRPS7 is also named mitochondrial ribosomal protein S7 or 30S ribosomal protein S7 homolog [33]. It is a 28kDa protein with a pI of 10. MRPS7 is located at the head of the small (30S) subunit of the ribosome and faces into the decoding centre. It is one of the
X. Rushan et al. primary 16S rRNA-binding proteins responsible for initiating the assembly of the head of the 30S subunit. MRPS7 has been shown to be the major protein component to cross-link with tRNA molecules bound at both the aminoacyl-tRNA (A) and peptidyl-tRNA (P) sites of the ribosome. MRPs are thought to be involved in the maintenance of the mitochondrial DNA [34]. MRPS7 clearly plays an important role in ribosome function. In this study, MRPS7 was over-expressed in DPC with aggregative behavior which maybe related to synthesize more proteins to maintain the aggregative behavior of DPC. In addition, seven metabolic enzymes, neuropolypeptide h3 and annexin A2 are overexpressed in DPC with aggregation. Most of metabolic enzymes are associated with the glycolytic pathway and the tricarboxylic acid (TCA) cycle. Neuropolypeptide h3 was previously present in epithelial, muscular tissue, nervous tissue and testis [35,36]. We found that neuropolypeptide h3 was present and overexpressed in DPC with aggregation. Annexin A2 may be involved in the regulation of Ca2+-dependent exocytosis and cell—cell adhesion mechanism [37]. But, their roles in aggregative behavior of DPC are unclear and further research is needed to draw a conclusion. In brief, we compared the proteomic profile of cytoplasmic proteins in DPC with and without aggregative behavior. This strategy provided an efficient resolution to analyze aggregation-related proteins directly at the protein level. Further studies will be performed to determine the mechanism by which these proteins play a critical role in the aggregation of early passage DPC. This proteome analysis may contribute to the elucidation of molecular mechanism of aggregative behavior in DPC.
Acknowledgments This research was supported by the China Postdoctoral Science Foundation (No. 2005038477). Xia Rushan and Mou Zhirong contributed equally to the study. Part of our studies was conducted in the Institute of Immunology, the Third Military Medical University, Chongqing, China, so we thank Prof. Yu-Zhang Wu, Doctor Yu-Jun He and Wan-Ling Li.
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[21] Anderson L, Seilhamer J. A comparison of selected mRNA and protein abundances in human liver. Electrophoresis 1997;18:533—7. [22] Stenn KS, Combates NJ, Eilertsen KJ, et al. Hair follicle growth controls. Dermatol Clin 1996;14:543—58. [23] Shapland C, Hsuan JJ, Totty NF, Lawson D. Purification and properties of transgelin: a transformation and shape change sensitive actin-gelling protein. J Cell Biol 1993;121:1065—73. [24] Lawson D, Harrison M, Shapland C. Fibroblast transgelin and smooth muscle SM22alpha are the same protein, the expression of which is down-regulated in many cell lines. Cell Motil Cytoskeleton 1997;38:250—7. [25] Sitek B, Luttges J, Marcus K, et al. Application of fluorescence difference gel electrophoresis saturation labelling for the analysis of microdissected precursor lesions of pancreatic ductal adenocarcinoma. Proteomics 2005;5:2665—79. [26] Lawen A, Ly JD, Lane DJ, et al. Voltage-dependent anionselective channel 1 (VDAC1)–—a mitochondrial protein, rediscovered as a novel enzyme in the plasma membrane. Int J Biochem Cell Biol 2005;37:277—82. [27] Baker MA, Lane DJ, Ly JD, et al. VDAC1 is a transplasma membrane NADH-ferricyanide reductase. J Biol Chem 2004;279:4811—9. [28] Shinohara Y, Ishida T, Hino M, et al. Characterization of porin isoforms expressed in tumor cells. Eur J Biochem 2000;267: 6067—73. [29] Brocchieri L, Conway de Macario E, Macario AJ. Chaperonomics, a new tool to study ageing and associated diseases. Mech Ageing Dev 2007;128(1):125—36. [30] Singh R, Kolvraa S, Rattan SI. Genetics of human longevity with emphasis on the relevance of HSP70 as candidate genes. Front Biosci May 2007;12:4504—13. [31] Singh R, Kolvraa S, Bross P, Christensen K, et al. Heat-shock protein 70 genes and human longevity: a view from Denmark. Ann NY Acad Sci May 2006;1067:301—8. [32] Deocaris CC, Yamasaki K, Kaul SC, Wadhwa R. Structural and functional differences between mouse mot-1 and mot-2 proteins that differ in two amino acids. Ann NY Acad Sci 2006;1067:220—3. [33] Cavdar Koc E, Blackburn K, Burkhart W, Spremulli LL. Identification of a mammalian mitochondrial homolog of ribosomal protein S7. Biochem Biophys Res Commun 1999;266: 141—6. [34] Myers AM, Pape LK, Tzagoloff A. Mitochondrial protein synthesis is required for maintenance of intact mitochondrial genomes in Saccharomyces cerevisiae. EMBO J 1985;4: 2087—92. [35] Bollengier F, Mahler A. Localization of the novel neuropolypeptide h3 in subsets of tissues from different species. J Neurochem 1988;50:1210—4. [36] Seddiqi N, Bollengier F, Alliel PM, et al. Amino acid sequence of the Homo sapiens brain 21—23-kDa protein (neuropolypeptide h3), comparison with its counterparts from Rattus norvegicus and Bos taurus species, and expression of its mRNA in different tissues. J Mol Evol 1994;39:655—60. [37] Siever DA, Erickson HP. Extracellular annexin II. Int J Biochem Cell Biol 1997;29:1219—23.
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Identification of proteins involved in aggregation of human dermal papilla cells by proteomics Xia Rushan a, Hao Fei a,*, Mou Zhirong b, Wu Yu-zhang b a
Department of Dermatology, Southwest Hospital, Third Military Medical University, Gaotanyan Road, Chongqing 400038, China b Institute of Immunology of PLA, Third Military Medical University, Gaotanyan Road, Chongqing 400038, China Received 9 February 2007; received in revised form 10 June 2007; accepted 20 June 2007
KEYWORDS Comparative proteome; Dermal papilla cells; Heat shock protein; Mitochondrial ribosomal protein S7
Summary Background: The dermal papilla is a major component of hair, which signals the follicular epithelial cells to prolong the hair growth process. To date, little is known about the significance of the specific protein(s) express in the dermal papilla cells (DPC) with regard to their aggregative behaviour. Objectives: To identify proteins involved in aggregative behaviour of DPC, we comparatively analyzed the proteome of cells with and without aggregative behaviour. Methods: A series of methods were used, including two-dimensional gel electrophoresis (2-DE), PDQuest software analysis of 2-DE gels, peptide mass fingerprinting based on matrix-assisted laser desorption/ionisation-time of flight-mass spectrometry (MALDI-TOF-MS), and NCBInr database searching, to separate and identify differentially expressed proteins. Western blotting and reverse transcriptase polymerase chain reaction (RT-PCR) were used to validate the differentially expressed proteins. Results: Image analysis revealed that averages of 618 22 and 568 47 protein spots were detected in passages 3 and 10 DPC, respectively. Twenty-four differential protein spots were measured with MALDI-TOF-MS. A total of 17 spots yielded good spectra, and 15 spots matched with known proteins after database searching. Western blotting confirmed that heat shocking protein 70 was up-regulated in passage 3 DPC. Overexpression of mitochondrial ribosomal protein S7 was confirmed by RT-PCR, indicating that they are involved in aggregation of DPC through some signaling pathway. Conclusions: The clues provided by the comparative proteome strategy utilized here will shed light on molecular mechanisms of DPC in aggregative behaviour. # 2007 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.
Abbreviations: DPC, dermal papilla cells; HSP70, heat shock protein 70; MRPS7, mitochondrial ribosomal protein S7. * Corresponding author. Fax: +86 23 68462522. E-mail addresses: [email protected] (X. Rushan), [email protected] (H. Fei). 0923-1811/$30.00 # 2007 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.jdermsci.2007.06.013
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1. Introduction The dermal papilla cells (DPC) are specialized stroma cells which are believed to be the source of the dermis-derived signaling molecules involved in hair follicle development and in postnatal hair cycling [1]. The tendency of aggregation is one of the significant properties of the DPC, and this property is associated with their biologic function and differentiating state [2—6]. Early passage dermal papilla cells have aggregative behavior and can induce hair growth in vivo, but, upon further culturing, this property is lost (Fig. 1). Generally speaking, DPC lose the aggregative behavior and the ability of regulating and controlling the hair cycle in the passage range 6—15 [7]. However, the cellular mechanisms underlying the aggregative behavior of DPC are less known. In order to study the aggregative behavior of DPC, a variety of techniques have been used to identify genes related to the aggregative property of DPC [8,9]. These methods were used to analyze mRNA expression levels of aggregation-related genes. In protein level, many growth factors produced by DPC were found to have the function of modulating the proliferation of follicular epithelium, such as insulin-like growth factor-I, bone morphogenetic proteins, transforming growth factor-beta1 and so on. Most of these factors act as a cytokine network controlling follicle development and hair cycling [10—13]. Our recent studies had
X. Rushan et al. proved that the DPC with aggregative behavior could produce soluble molecules which can help the DPC losing aggregative behavior regain to aggregative behavior [14]. These results suggest that DPC with aggregative behavior could release soluble, functional factors which stimulate the growth of DPC and maintain the aggregative behavior of DPC. Therefore, intensive screening to search for candidate proteins in low passage DPC is needed to identify proteins that play a role in the aggregation of DPC. Advances in the studies on proteomics have made it possible to compare the total proteins of cells under different conditions on a large scale [15,16]. The proteomic strategy based on 2-DE and MALDITOF-MS has been applied in a variety of studies. In this study, by using 2-DE and MALDI-TOF mass spectrometry, we examined the protein expression profile difference in passages 3 and 10 DPC and analyzed proteins involved in the aggregative behavior globally.
2. Materials and methods 2.1. Chemicals and other materials Bis, Tris, SDS, glycine, TEMED, ammonium persulfate (APS), glycerol, ultra pure urea, bromophenol blue, acrylamide, DTT, CHAPS, agarose and Immobiline
Fig. 1 Cell morphology of DPC in passages 3 and 10. (A) Passage 3 DPC with aggregative behavior. (B) Passage 10 DPC without aggregative behavior. (C) Passage 10 DPC regain aggregative behavior.
Identification of proteins involved in aggregation of human dermal papilla cells DryStrips (pH 3—10) were purchased from Amersham Biosciences (Uppsala, Sweden). Iodoacetamide (IAA), Brilliant Blue G-250 and Collagenase D (ultra pure grade) came from Sigma (St. Louis, USA). Protease inhibitor cocktail and dispase were purchased from Roche (Switzerland). Goat Anti-human HSP70 mAb and peroxidase-conjugated goat antirabbit immunoglobulin were obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Other reagents not mentioned above were domestic made.
2.2. Dermal papilla separation and cultures The dermal papilla is derived from human (six males, three females, mean age 28 years) nonbalding scalp-skin which were obtained from plastic surgery with the informed consent of donors and approval of Southwest hospital ethical committee. Dermal papilla were isolated from scalp tissues by two-step enzyme method set up previously in our laboratory [17]. Firstly, the scalp-skin of nine volunteers was sterilized and digested in 0.5% (w/v) dispase for 12—16 h at 4 8C and in 0.2% (w/v) collagenase D for 6 h at 37 8C sequentially. The digested tissue was then centrifuged at 550—850 g for 3— 5 min. The dermal papilla was sedimentated at the bottom of tube as a clump of cells, whereas other cells floated in the supernatant. After centrifuged for several times, the human dermal papilla was separated from other types of cells and was cultured in DMEM medium supplemented with 10% foetal calf serum subsequently. DPC were mixed and incubated at 37 8C in a humidified atmosphere of 95% air and 5% CO2. The passages 3 and 10 DPC were harvested at exponential growth. The cell pellet was washed three times with 0.1 M PBS, centrifuged and froze at 70 8C.
2.3. Extraction of water soluble proteins The passages 3 and 10 DPC pellets (>108 cells) were re-suspended in 100 ml of 40 mM Tris buffer (pH 7.4) and performed by supersonic wave at 40 W for 1.5 min. Cell debris were removed by centrifugation at 12,000 g for 60 min at 4 8C. The supernatant was accurately sample normalized by Bradford’s protein assay and used for 2-DE.
2.4. 2-DE The same amount of 1 mg proteins were loaded onto 13 cm, pH 3—10 IPG strips. IPG strips were rehydrated in rehydration solution (8 M urea, 1% (w/v) CHAPS, 0.2% (w/v) DTT, 0.5% (v/v) pharmalyte
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3—10, 0.002% (w/v) bromophenol blue) over night. IEF was conducted by the IPGPhor II system (Amersham-Pharmacia Biotech) for 1 h 0 V, 12 h 30 V, 2 h 60 V, 1 h 500 V, 1 h 1000 V and at 8000 V until approximately 40,000 V h were reached. Focused strips were immediately equilibrated for 2 15 min with buffer (50 mmol/l Tris—HCl, pH 6.8, 6 mol/l urea, 30% glycerol, 2% SDS and a trace of bromophenol blue). DTT (2%, w/v) was added in the first step, and iodoacetamide (2.5%, w/v) in the second step. The strips were placed on a 1.5-mm thick, 12.5% polyacrylamide gel and sealed with 0.1% (w/v) agarose in SDS-electrophoresis buffer containing 0.01% (w/v) bromophenol blue. The electrophoresis was run for 30 min at 15 W per gel followed by a further run at 25 W per gel until the bromophenol blue band reached the bottom of the gel. Gels were fixed and stained over night with colloidal Coomassie blue and destained with deionised water until the background was significantly reduced. The gels were scanned (Gel Doc 2000; BioRad, Hercules, CA, USA), and the images were processed with PDQuest software (Ver 7.0; Bio-Rad).
2.5. In-gel tryptic digest and mass spectrometry Spots were excised from the stained gel. Destained with 25 mM ammonium bicarbonate/50% acetonitrile (Sigma) and dried with a SpeedVac plus SC1 10 (Savant Holbook, HY, USA). The gel was rehydrated in trypsin solution (Promega, Madison, WI, USA). After incubation overnight at 37 8C, peptides were first eluted with 5% TFA in 40 8C for 1 h, then 2.5% TFA/50% acetonitrile at 30 8C for 1 h and removal of acetonitrile by centrifugation in a vacuum centrifuge. The peptides were concentrated by using pipette tips C18 (Millipore, Bedford, MA). Analyses were performed primarily using MALDI-TOF mass spectrometer (Burker company, German). Peptide mixtures were analyzed using a saturated solution of a-cyano-4-hydroxycinnamic acid (Sigma) in acetone containing 1% TFA. Peptides were selected in the mass range of 800—4000 Da. The peptide sequence was determined with Mascot software. Sequence homology was analyzed using Mascot program and the NCBI BLAST online search service. Peptide masses were assumed to be monoisotopic masses, and cystines to be iodoacetamided. The peptide mass tolerance was set to 100 ppm, and the maximum of missed cleavage sites was set to 1. Species was set to homo sapiens (human). Positive identification was achieved only when a 100 ppm mass accuracy met with a significant probability PROWL software score, and nearly all dominant signals of the spectrum were assigned to the
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identified protein. Candidates were further evaluated by comparison with their calculated mass and pI, using the experimental values obtained from 2-DE.
3. Results
2.6. Western blot analysis
The DPC in passage 3 demonstrated a distinctive single cell morphology and formed cell aggregates at confluence which were believed as aggregative behavior (Fig. 1A). However, passage 10 DPC were radically different from the cell morphology of passage 3 DPC and were believed to be lost this property (Fig. 1B). DPC losing aggregation regain aggregative behaviour when cultured supernantant of low passage DPC were added to them (Fig. 1C).
The indicated amounts of protein extracts obtained from DPC were separated on a 12.5% (w/v) SDSpolyacrylamide gel. Then, proteins were transferred to PVDF membrane (Roche). After blocking with TBS-Tween 20 (TBST) containing 5% skim milk, the membranes were incubated with goat antihuman HSP70 mAb diluted 1:500 in TBST for 1 h, followed by peroxidase-conjugated goat anti-rabbit immunoglobulin diluted 1:5000 in TBST for 1 h. Finally, membranes were washed three times with TBT, and blots were developed by the enhanced chemiluminescence (ECL, Roche). As control for equal protein loading, blots were re-stained using monoclonal mouse anti-glyceraldehyde-3-phosphate dehydrogease (GAPDH) (kangchen Biotech, China). The intensity of each band was measured by Quantity one (Ver 4.5, Bio-Rad).
2.7. RT-PCR experiment Total RNA was extracted from passages 3 and 10 DPC using Tripure according to the manufacturer’s instruction. Reverse transcription with oligo(dT) priming was performed to generate cDNAs from 2 mg total RNA using Superscript II following the instruction provided by the manufacturer. DNA amplification was carried out with Taq DNA polymerase (Takara, Japan) using the following primers: b-actin (618 bp), 50 -CGG GAC CTG ACT GAC TAC CTC-30 and 50 -CAA GAA AGG GTG TAA CGC AAC-30 ; MRPS7 (287 bp), 50 -AAG CCA GTG GAG GAG CTA A-30 and 50 -GCT TGA TGG AAG ATG GTG TA-30 . PCR conditions were 94 8C for 5 min and then 26 cycles of 94 8C for 30 s, 44 8C for 30 s and 72 8C for 60 s, followed by incubation at 72 8C for 5 min for MRPS7 amplification. Amplified fragments were separated by electrophoresis on 1% agarose gels and visualized by ethidium bromide staining. The intensity of each band was measured by Quantity one (Ver 4.5, Bio-Rad), and intensity of MRPS7 were corrected by the intensity of bactin.
2.8. Statistical analysis Value is expressed as mean standard deviation (S.D.). Student’s t-test and the x2-test were used for statistical analyses. Differences were considered significant at P < 0.05.
3.1. Cell morphology in passages 3 and 10 DPC
3.2. Two-dimensional electrophoresis and image analysis of human DPC To study the different proteins involved in aggregation of DPC, total proteins of DPC were subjected to 2-DE analysis. Typical Coomassie blue-stained gels are shown in Fig. 2. Several hundred spots were clearly identifiable in each gel. Image analysis of 2-D gels revealed that averages of 618 22 and 568 47 protein spots were detected in two groups, respectively, and the majority of these protein spots were matched. About 300 protein spots were matched between passages 3 and 10 DPC, and the correlation coefficient was 0.75 by correlation analysis of gels. The unmatched spots represented those related to the aggregation of DPC as new or absent proteins, which were the main alteration of proteome. We select 24 protein spots having the difference beyond five times for further study.
3.3. Identification of spots by MALDI-TOF MS The spots of proteins were spread at the side of the 2-DE map corresponding to a 4.0—9.0 pH range. However, to ensure an exact identification, an ‘‘in-gel digestion’’ of manually excised spots was carried out using trypsin with high specificity, and the peptide mixtures deriving from tryptic hydrolysis were analyzed by MALDI-TOF MS. Out of a total of 24 spots excised from the gels, 17 spots yielded nearly perfect MALDI spectra. Fifteen spots were preliminarily identified by PMF, these being the most represented, as reported in Table 1. Fig. 3 shows the typical PMF of spot 4, whose peptides matched human transgelin. Mascot Search Results are shown in Fig. 4. The detailed matching result is listed in Table 2. The identified proteins are involved in the cellular processes of intercellular junctions, antiapoptosis, metabolism, signal transduction and protein post-translational processes. One spots with
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Fig. 2 2-DE patterns of cytoplasmic protein in passage 3 DPC (A) and passage 10 DPC (B). Protein (1.0 mg) was loaded and separated in IPG strips (pI range of 3—10), and the gels were stained with Brilliant Blue G-250. Spot numbers refer to proteins summarized in Table 1.
good MALDI spectra was returned with inconclusive match results, suggesting that it might be unknown proteins.
parallel GAPDH immunoblotting. HSP70 was found significantly up-regulated in passage 3 DPC. This result confirmed our 2-DE data.
3.4. Immunoblot confirmation of the upregulation of HSP70 in passage 3 DPC
3.5. Semi-quantity RT-PCR
To confirm and extend the 2-DE results, HSP70 expression in passage 3 was compared with that of passage 10 DPC by Western blot analysis (Fig. 5). Equal protein loading was confirmed by
A specific antibody against MRPS7 is unavailable. To test if the reduced content of MRPS7 in passage 3 DPC reflected a decrease in transcription, comparative MRPS7 RT-PCR of passages 3 and 10 DPC were performed. Primers of MRPS7 were located within
Table 1 Differential displayed protein spots preliminarily identified by PMF Spot ID NCBInr code Peptides Theoretic matched pI/Mr (kDa)
Sequence Score Protein name coverage
1 2
gij45934285 gij51479152
6/39 8/36
6.04/17,298 51% 6.60/15,820 69%
66 100
3 3-1 4
gij7705738 gij48255907 gij56967119
6/20 22/43 18/55
10/28,258 23% 8.88/22,522 68% 8.32/36,631 51%
69 168 139
5 6
gij913159 gij50345982
12/25 12/61
7.42/21,027 67% 9.42/44,476 38%
111 93
10
gij67464392
20/50
8.22/60,277 49%
87
12 16 17 18 19-1 20-1 21
gij32891807 gij13921685 gij31417921 gij62897129 gij55960375 gij50845388 gij238427
11/34 4/19 9/12 12/26 21/42 26/48 9/44
7.13/22,219 10.27/4,392 8.02/50,335 5.28/71,083 8.41/24,609 8.53/40,671 8.63/30,737
65% 65% 35% 23% 91% 64% 32%
68 69 90 108 230 236 80
", Up-regulated in passage 3 DPC; –—, expressed in passage 10 DPC. a (+) Expressed in passage 3 DPC.
Globoside synthase mutant ATP synthase, H+ transporting, mitochondrial F0 complex, subunitd isoform b Mitochondrial ribosomal protein S7 Transgelin Chain B, human annexin A2 in the presence of calcium ions Neuropolypeptide h3 ATP synthase, H+ transporting, mitochondrial F1 complex, alpha subunit isoform b Chain A, human muscle pyruvate kinase (Pkm2) Biliverdin reductase B Unnamed protein product TKT protein Heat shock 70 kDa protein Transgelin 2 Annexin A2 isoform1 Porin 31HM
Alteration a + +
" " + + +
+ + + + " " " –—
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Fig. 3 Typical MALDI-TOF-MS spectrum of spot 3-1 from the 2-DE map. The MS spectrum of the peptide mixture was obtained from a typical in-gel digestion of the 2-DE separated protein. Numbers refer to peptides are listed in Table 2 and matched peptides with transgelin are listed in Fig. 4.
exon 159 (forward) and exon 445 (reverse), respectively, generating a PCR product of 287 bp. In line with the 2-DE findings, the extent of MRPS7 expression exhibited considerable decrease in passage 10 DPC (Fig. 6).
4. Discussion In the present study, we report for the first time the application of a proteomic strategy for the comparative analysis of DPC with and without aggregative characters. Our approach was based on separation of the proteins by 2-DE, computational image analysis of the resulting proteome maps, and protein identification using mass spectrometry. Usually, large scale comparative differential gene expression studies
can be addressed in terms of mRNA (transcriptome) or protein (proteome) levels. Transcriptome technology offers some technical advantages over proteomics, such as the possibility to work with minimal quantities of biological samples and well established platforms to work in a high-throughput mode [18,19]. Nevertheless, studies in yeast and mammalian cells have shown that mRNA abundance is not directly correlated to protein levels [20,21]. This lack of correlation makes us study the aggregative behavior of DPC at the post-transcriptional level. As a method to screen proteins on a large-scale, proteomics has been driven forward by the advent of the genome era, and it has advantages in analyzing total or specific proteins from cells. In this study, we preliminarily identified 15 proteins, including transgelin, MRPS7, HSP70 and so on. Except for Porin 31
Fig. 4 Mascot search results of spot 4, which is matched with transgelin. Peptides from spot 4 are shown in bold red. Number of mass values searched is 43 and number of mass values matched is 22. Sequence coverage is 68%.
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Table 2 The detailed result of database searching of spot 4 (listed in Table 1 which matched the record gij48255907 in the NCBInr database. Theoretical MW (Da)
Peptide mass M—H+ (Da)
DMass (compared with theoretical) (Da)
Start—end
Peptide
853.38 964.50 989.58 993.46 1009.49 1081.45 1203.64 1209.55 1220.64 1236.64 1243.65 1294.63 1515.84 1529.74 1545.76 2108.11 2317.10 2741.32
853.38 964.49 989.57 993.44 1009.43 1081.46 1203.60 1209.55 1220.62 1236.62 1243.63 1294.60 1515.83 1529.71 1545.70 2108.08 2317.07 2741.45
0.01 0.01 0.01 0.02 0.06 0.00 0.01 0.00 0.01 0.03 0.03 0.03 0.01 0.03 0.05 0.03 0.02 0.13
5—12 100—108 50—57 147—154 147—154 22—29 49—57 21—29 90—99 90—99 79—89 162—172 65—78 109—121 109—121 30—47 109—128 65—89
GPSYGMSR AAEDYGVIK LGFQVWLK GDPNWFMK GDPNWFMK oxidation (M) YDEELEER QMEQVAQFLK Pyro-glu (N-term Q) KYDEELEER QMEQVAQFLK QMEQVAQFLK oxidation (M) VPENPPSMVFK EFTESQLQEGK LVNSLYPDGSKPVK TDMFQTVDLFEGK TDMFQTVDLFEGK oxidation (M) LVEWIIVQCGPDVGRPDR TDMFQTVDLFEGKDMAAVQR oxidation (M) LVNSLYPDGSKPVKVPENPPSMVFK
MH, 14 identified proteins were specific or overexpresed in DPC with aggregative behaviour. The aggregative behaviour of DPC is manifested as a result of increased production of proteins species which are in line with the Stenn’s study [22]. These proteins are related to various cellular responses, such as intercellular junctions, anti-apoptosis, cellular metabolism, signaling transduction and so on. They are novel signaling molecules or targets with no previously known function in aggregative behavior of DPC. Among 14 preliminarily identified proteins, transgelin was overexpressed in DPC with aggregation. Transgelin is an actin-binding protein of an unknown function cross-linking actin filaments. This protein is transformation sensitive and gels actin, so Shapland
et al. named it transgelin [23]. Transgelin is found in fibroblasts and smooth muscle cells. It is also present in normal mesenchymal cells, secondary cultures of mouse and rat embryo fibroblasts. But they are absent in many apparently normal fibroblast cell lines. This protein is involved in various types of cell mobility and exocytosis, and can be regulated by calcium [24]. It has been shown that down-regulation of transgelin may be an important early event in tumour progression and is discussed as a diagnostic marker for breast and colon cancer development [25]. In our study, we find that transgelin is upexpressed in passage 3 DPC and down-regulated in passage 10 DPC which may reflect cell structural
Fig. 5 HSP70 immunoblotting of passages 3 and 10 DPC. Western blot analysis revealed markedly overexpression in passage 3 DPC (P3) when compared with that in passage 10 DPC (P10).
Fig. 6 Comparative MRPS7 RT-PCR of passages 3 and 10 DPC. In line with the results at the 2-DE level, the RT-PCR results revealed marked down-regulation of MRPS7 in passage 10 DPC.
196 changes from aggregation to non-aggregation. Whether it is a marker for the aggregation of DPC need to be further investigated. A significant reduction in the levels of the porin 31 HM has been observed in DPC with aggregation. Porin 31 HM is also named voltage-dependent anion-selective channel protein 1 (VDAC-1) or outer mitochondrial membrane protein porin 1. It is a pore-forming protein discovered 26 years ago in the mitochondrial outer membrane [26]. It has recently been described as being a NADH:ferricyanide reductase in the plasma membrane where it establishes a novel level of apoptosis regulation putatively via its redox activity. It regulates the cell growth and death [27]. Porin proteins are involved in the regulation of cellular metabolism with a higher level of production reported in hypoxic neuronal cells [28]. In this study, Porin 31 HM expression was decreased in passage 3 DPC. Here, we propose that the down-regulation of porin 31 HM reflects the increase of cellular metabolism in DPC with aggregative behavior. Using a proteomics strategy, we detected two interesting proteins involved in aggregative growth of DPC. One protein was heat shock proteins 70 (HSP70). Heat shock proteins (HSPs) have a physiologic function in unstressed cells, which is believed to include a role as a ‘‘molecular chaperone’’. The participation of molecular chaperones in the process of senescence and in the mechanisms of agerelated diseases is currently under investigation in many laboratories [29]. Chaperone functions mediated by HSP family constitute a fundamental mechanism that governs the life span of organisms. Among different classes of chaperones, HSP70 are now the major candidates in the gene-longevity association studies [30]. A significant association of one HSP70 haplotype gene with male longevity was observed [31]. Mortalin is the chaperone of mitochondrial HSP70 protein which is a heat-uninducible stress protein involved in immortalization and tumorigenesis. There are two mortalin alleles, mot-1 and mot-2, in mouse. Whereas an overexpression of mot-1-induced senescence in NIH 3T3 cells, overexpression of mot-2 promoted their malignant properties. So mortalin protein have differential aging phenotypes [32]. In this work, it was upregulated in DPC with aggregative behavior. The relationship between HSP70 and aggregation of DPC has not been determined before, so it is worthy of further research. Another protein identified was human MRPS7. MRPS7 is also named mitochondrial ribosomal protein S7 or 30S ribosomal protein S7 homolog [33]. It is a 28kDa protein with a pI of 10. MRPS7 is located at the head of the small (30S) subunit of the ribosome and faces into the decoding centre. It is one of the
X. Rushan et al. primary 16S rRNA-binding proteins responsible for initiating the assembly of the head of the 30S subunit. MRPS7 has been shown to be the major protein component to cross-link with tRNA molecules bound at both the aminoacyl-tRNA (A) and peptidyl-tRNA (P) sites of the ribosome. MRPs are thought to be involved in the maintenance of the mitochondrial DNA [34]. MRPS7 clearly plays an important role in ribosome function. In this study, MRPS7 was over-expressed in DPC with aggregative behavior which maybe related to synthesize more proteins to maintain the aggregative behavior of DPC. In addition, seven metabolic enzymes, neuropolypeptide h3 and annexin A2 are overexpressed in DPC with aggregation. Most of metabolic enzymes are associated with the glycolytic pathway and the tricarboxylic acid (TCA) cycle. Neuropolypeptide h3 was previously present in epithelial, muscular tissue, nervous tissue and testis [35,36]. We found that neuropolypeptide h3 was present and overexpressed in DPC with aggregation. Annexin A2 may be involved in the regulation of Ca2+-dependent exocytosis and cell—cell adhesion mechanism [37]. But, their roles in aggregative behavior of DPC are unclear and further research is needed to draw a conclusion. In brief, we compared the proteomic profile of cytoplasmic proteins in DPC with and without aggregative behavior. This strategy provided an efficient resolution to analyze aggregation-related proteins directly at the protein level. Further studies will be performed to determine the mechanism by which these proteins play a critical role in the aggregation of early passage DPC. This proteome analysis may contribute to the elucidation of molecular mechanism of aggregative behavior in DPC.
Acknowledgments This research was supported by the China Postdoctoral Science Foundation (No. 2005038477). Xia Rushan and Mou Zhirong contributed equally to the study. Part of our studies was conducted in the Institute of Immunology, the Third Military Medical University, Chongqing, China, so we thank Prof. Yu-Zhang Wu, Doctor Yu-Jun He and Wan-Ling Li.
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