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Comparative proteome analysis of peripheral blood mononuclear cells in systemic lupus erythematosus with iTRAQ quantitative proteomics

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Abstract

To identify and quantify protein profiles from peripheral blood mononuclear cells (PBMC) of systemic lupus erythematosus (SLE) patients with isobaric Tagging for Relative and Absolute protein Quantification (iTRAQ)–based proteomic technology and to find differentially expressed proteins in SLE. PBMC were collected from patients of six stable SLE, six active SLE, six rheumatoid arthritis (RA), and six healthy donors. After protein extraction and concentration, the pooled protein content was labeled with iTRAQ reagents and then subjected to multiple chromatographic fractionation and tandem mass spectrometry. ProteinPilot™ 3.0 software and a database of IPI (International Protein Index) human 3.62 were used for database searching and statistical analysis. A total of 452 proteins were identified. Of these, 67 unique proteins were observed twofold or more alteration in levels across groups. The proteins determined support existing knowledge and uncover novel biomarker candidates. These results indicate that iTRAQ-based technology can serve as a useful aid for identification and quantification proteins from PBMC.

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References

  1. Ghirardello A, Villalta D, Morozzi G, Afeltra A, Galeazzi M, Gerli R et al (2007) Evaluation of current methods for the measurement of serum anti double-stranded DNA antibodies. Ann N Y Acad Sci 1109:401–406

    Article  PubMed  CAS  Google Scholar 

  2. Alvarado-Sánchez B, Hernández-Castro B, Portales-Pérez D, Baranda L, Layseca-Espinosa E, Abud-Mendoza C et al (2007) Regulatory T cells in patients with systemic lupus erythematosus. J Autoimmun 27:110–118

    Article  Google Scholar 

  3. Gibson DS, Blelock S, Curry J, Finnegan S, Healy A, Scaife C et al (2009) Comparative analysis of synovial fluid and plasma proteomes in juvenile arthritis–proteomic patterns of joint inflammation in early stage disease. J Proteomics 72:656–676

    Article  PubMed  CAS  Google Scholar 

  4. Chang X, Cui Y, Zong M, Zhao Y, Yan X, Chen Y et al (2009) Identification of proteins with increased expression in rheumatoid arthritis synovial tissues. J Rheumatol 36:872–880

    Article  PubMed  CAS  Google Scholar 

  5. Dai Y, Hu C, Huang Y, Huang H, Liu J, Lv T (2008) A proteomic study of peripheral blood mononuclear cells in systemic lupus erythematosus. Lupus 17:799–804

    Article  PubMed  CAS  Google Scholar 

  6. Ross PL, Huang YN, Marchese JN, Williamson B, Parker K, Hattan S et al (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 3:1154–1169

    Article  PubMed  CAS  Google Scholar 

  7. DeSouza LV, Grigull J, Ghanny S, Dubé V, Romaschin AD, Colgan TJ et al (2007) Endometrial carcinoma biomarker discovery and verification using differentially tagged clinical samples with multidimensional liquid chromatography and tandem mass spectrometry. Mol Cell Proteomics 6:1170–1182

    Article  PubMed  CAS  Google Scholar 

  8. Al Badaai Y, DiFalco MR, Tewfik MA, Samaha M (2009) Quantitative proteomics of nasal mucus in chronic sinusitis with nasal polyposis. J Otolaryngol Head Neck Surg 38:381–389

    PubMed  Google Scholar 

  9. Zhou L, Beuerman RW, Chan CM, Zhao SZ, Li XR, Yang H et al (2009) Identification of tear fluid biomarkers in dry eye syndrome using iTRAQ quantitative proteomics. J Proteome Res 8:4889–4905

    Article  PubMed  CAS  Google Scholar 

  10. Hergenroeder G, Redell JB, Moore AN, Dubinsky WP, Funk RT, Crommett J et al (2008) Identification of serum biomarkers in brain-injured adults: potential for predicting elevated intracranial pressure. J Neurotrauma 25:79–93

    Article  PubMed  Google Scholar 

  11. Tan EM, Cohen AS, Fries JF, Masi AT, McShane DJ, Rothfield NF et al (1982) The 1982 revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 25:1271–1277

    Article  PubMed  CAS  Google Scholar 

  12. Gladman DD, Ibanez D, Urowitz MB (2002) Systemic lupus erythematosus disease activity index 2000. J Rheumatol 29:288–291

    PubMed  Google Scholar 

  13. Arnett FC, Edworthy SM, Bloch DA, McShane DJ, Fries JF, Cooper NS et al (1988) The American rheumatism association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Rheum 31:315–324

    Article  PubMed  CAS  Google Scholar 

  14. Abdi F, Quinn JF, Jankovic J, McIntosh M, Leverenz JB, Peskind E et al (2006) Detection of biomarkers with a multiplex quantitative proteomic platform in cerebrospinal fluid of patients with neurodegenerative disorders. J Alzheimers Dis 9:293–348

    PubMed  CAS  Google Scholar 

  15. Kersey PJ, Duarte J, Williams A, Karavidopoulou Y, Birney E, Apweiler R (2004) The international protein index: an integrated database for proteomics experiments. Proteomics 4:1985–1988

    Article  PubMed  CAS  Google Scholar 

  16. Kobayashi S, Ikari K, Kaneko H, Kochi Y, Yamamoto K, Shimane K et al (2008) Association of STAT4 with susceptibility to rheumatoid arthritis and systemic lupus erythematosus in the Japanese population. Arthritis Rheum 58:1940–1946

    Article  PubMed  Google Scholar 

  17. Matta A, DeSouza LV, Shukla NK, Gupta SD, Ralhan R, Siu KW (2008) Prognostic significance of head-and-neck cancer biomarkers previously discovered and identified using iTRAQ-labeling and multidimensional liquid chromatography-tandem mass spectrometry. J Proteome Res 7:2078–2087

    Article  PubMed  CAS  Google Scholar 

  18. Almehed K, d’Elia HF, Bokarewa M, Carlsten H (2008) Role of resistin as a marker of inflammation in systemic lupus erythematosus. Arthritis Res Ther 10:R15

    Article  PubMed  Google Scholar 

  19. Perera C, McNeil HP, Geczy CL (2010) S100 calgranulins in inflammatory arthritis. Immunol Cell Bio 88:41–49

    Article  CAS  Google Scholar 

  20. Yang XY, Lin J, Lu XY, Zhao XY (2008) Expression of S100B protein levels in serum and cerebrospinal fluid with different forms of neuropsychiatric systemic lupus erythematosus. Clin Rheumatol 27:353–357

    Article  PubMed  Google Scholar 

  21. Dolores Sanchez-Niño M, Sanz AB, Lorz C, Gnirke A, Rastaldi MP, Nair V et al (2010) BASP1 promotes apoptosis in diabetic nephropathy. J Am Soc Nephro 21:610–621

    Article  Google Scholar 

  22. Yi L, Zeng X, Tan H, Ge L, Ji XX, Lin M et al (2009) Proteomics analysis of apoptosis initiation induced by diallyl disulfide in human leukemia HL-60 cells. Chin J Cancer 28:33–37

    Google Scholar 

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Acknowledgments

We thank the patients and healthy volunteers who participated in this study and Shuiming Li for his technical assistance. This work was supported by grants from the Key Project for Science and Technology of Shenzhen (project no. 201001001).

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The authors declare that they have no conflict of interest.

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Correspondence to Zhiguang Tu.

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Wang, L., Dai, Y., Qi, S. et al. Comparative proteome analysis of peripheral blood mononuclear cells in systemic lupus erythematosus with iTRAQ quantitative proteomics. Rheumatol Int 32, 585–593 (2012). https://doi.org/10.1007/s00296-010-1625-9

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  • DOI: https://doi.org/10.1007/s00296-010-1625-9

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