DOI QR코드

DOI QR Code

Optimization of SELDI-TOF MS for Peptide Profiling of Sorghum Seed

수수종자의 펩타이드 분석을 위한 SELDI-TOF MS 최적화 연구

  • Park, Sei Joon (Institute of Ecological Phytochemistry, Hankyong National University) ;
  • Park, June Young (Department of Plant Life and Environmental Science, Hankyong National University) ;
  • Lee, Yong Ho (Institute of Ecological Phytochemistry, Hankyong National University) ;
  • Hwang, Su Min (Department of Plant Life and Environmental Science, Hankyong National University) ;
  • Kim, A Ram (Department of Plant Life and Environmental Science, Hankyong National University) ;
  • Ko, Jee-Yeon (Department of Functional Crop, NICS, RDA) ;
  • Kim, Tae Wan (Institute of Ecological Phytochemistry, Hankyong National University)
  • 박세준 (국립한경대학교 식물생태화학연구소) ;
  • 박준영 (국립한경대학교 식물생명환경과학과) ;
  • 이용호 (국립한경대학교 식물생태화학연구소) ;
  • 황수민 (국립한경대학교 식물생명환경과학과) ;
  • 김아람 (국립한경대학교 식물생명환경과학과) ;
  • 고지연 (농촌진흥청 국립식량과학원 기능성작물부) ;
  • 김태완 (국립한경대학교 식물생태화학연구소)
  • Received : 2012.10.15
  • Accepted : 2013.01.21
  • Published : 2013.03.31

Abstract

For accurate analysis of low molecular peptides using SELDI-TOF MS (surface enhanced laser desorption/ionization time of flight mass spectrometry), the optimized analytical conditions should be established for a specific biological sample. This study was conducted to optimize SELDI-TOF MS analytical conditions for profiling low molecular peptide below 10 kDa presented in sorghum seeds. Analytical conditions were as follows; (1) protein chips: CM10 (weak cation exchanger) and Q10 (strong anion exchanger), (2) dilution factors of binding buffer: 1/2, 1/5, 1/10, 1/20, 1/50, 1/100, and 1/200, (3) the stringency of Q10 binding buffer: 10 mM and 100 mM, and (4) protein extraction buffers: sodium borate, sodium borate + acetone, phenol, and TCA buffers. Optimum dilution factors were selected as 1/20 and 1/50 in both protein chips, CM10 and Q10. Low stringency of Q10 binding buffer (10mM) detected more peptide peaks than high stringency (100 mM). Selected protein extraction buffers of sorghum seed for SELDI-TOF MS analysis was the sodium borate buffer in the range of 2~10 kDa, while the phenol buffer was more suitable in the range of 10~20 kDa.

SELDI-TOF MS를 활용한 저분자 펩타이드 분석을 위해서는 분석시료에 대한 최적화 분석조건을 확립하는 것이 필수적으로 선행되어야 한다. 본 연구는 수수 종자 내 존재하는 10 kDa 이하의 저분자 펩타이드를 프로파일링하기 위하여 활용된 SELDI-TOF MS의 최적화 분석조건을 확립하는데 있다. 분석조건은 (1) 프로테인 칩: CM10(weak cation exchanger), Q10(strong anion exchanger), (2) 바인딩 버퍼의 희석배수: 1/2, 1/5, 1/10, 1/20, 1/50, 1/100, 1/200, (3) Q10의 바인딩 버퍼 강도: 10 mM, 100 mM, (4) 단백질 추출버퍼: sodium borate, sodium borate + acetone, phenol, TCA 버퍼로 하였다. 1. 바인딩 버퍼의 희석배수는 CM10과 Q10 모두 1/20과 1/50이 최적화로 나타났다. 2. Q10의 바인딩 버퍼 강도는 농도가 약한 10 mM에서 더 많은 피크가 검출되었다. 3. SELDI-TOF MS 분석에 적합한 수수 종자단백질 추출 버퍼로는 2~10 kDa 범위에서는 sodium borate 버퍼와 10~20 kDa 범위에서는 phenol 버퍼로 분석되었다.

Keywords

References

  1. Akashi T. and T. Yamori. 2007. A novel method for analyzing phosphoproteins using SELDI-TOF MS in combination with a series of recombinant proteins. Proteomics 7 : 2350-2354. https://doi.org/10.1002/pmic.200700157
  2. Badri M. A., D. Rivard, K. Coenen, L. P. Vaillancourt, C. Goulet, and D. Michaud. 2009. A SELDI-TOF MS procedure for the detection, quantitation, and preliminary characterization of low-molecular-weight recombinant proteins expressed in transgenic plants. Proteomics 9 : 233-41. https://doi.org/10.1002/pmic.200700233
  3. Baggerly K. A., J. S. Morris, and K. R. Coombes. 2004. Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments. Bioinformatics 20 : 777-85. https://doi.org/10.1093/bioinformatics/btg484
  4. Bradford M. M. 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72 : 248-54. https://doi.org/10.1016/0003-2697(76)90527-3
  5. Dijkstra M., R. J. Vonk, and R. C. Jansen. 2007. SELDI-TOF mass spectra : A view on sources of variation. Journal of Chromatography B 847 : 12-23. https://doi.org/10.1016/j.jchromb.2006.11.004
  6. Ebert B., C. Melle, E. Lieckfeldt, D. Zoller, F. von Eggeling, and J. Fisahn. 2008. Protein profiling of single epidermal cell types from Arabidopsis thaliana using surface-enhanced laser desorption and ionization technology. J Plant Physiol 165 : 1227-37. https://doi.org/10.1016/j.jplph.2008.01.006
  7. Emami K., N. J. Morris, S. J. Cockell, G. Golebiowska, Q. Y. Shu, and A. M. Gatehouse. 2010. Changes in protein expression profiles between a low phytic acid rice (Oryza sativa L. Ssp. japonica) line and its parental line : a proteomic and bioinformatic approach. J Agric Food Chem 58 : 6912-22. https://doi.org/10.1021/jf904082b
  8. Farrokhi N., J. P. Whitelegge, and J. A. Brusslan. 2008. Plant peptides and peptidomics. Plant Biotechnol J 6 : 105-34. https://doi.org/10.1111/j.1467-7652.2007.00315.x
  9. Gomiero A., D. M. Pampanin, A. Bjornstad, B. K. Larsen, F. Provan, E. Lyng, and O. K. Andersen. 2006. An ecotoxicoproteomic approach (SELDI-TOF mass spectrometry) to biomarker discovery in crab exposed to pollutants under laboratory conditions. Aquatic Toxicology 78, Supplement : S34-S41. https://doi.org/10.1016/j.aquatox.2006.02.013
  10. Hamaker B. R., A. A. Mohamed, J. E. Habben, C. P. Huang, and B. A. Larkins. 1995. Efficient procedure for extracting maize and sorghum kernel proteins reveals higher prolamin contents than the conventional method. Cereal chemistry. 72 : 583-588.
  11. Hartmann R. and H. Meisel. 2007. Food-derived peptides with biological activity : from research to food applications. Curr Opin Biotechnol 18 : 163-9. https://doi.org/10.1016/j.copbio.2007.01.013
  12. Hu L., M. Ye, and H. Zou. 2009. Recent advances in mass spectrometry-based peptidome analysis. Expert Rev Proteomics 6 : 433-47. https://doi.org/10.1586/epr.09.55
  13. Huang F., J. Clifton, X. Yang, T. Rosenquist, D. Hixson, S. Kovac, and D. Josic. 2009. SELDI-TOF as a method for biomarker discovery in the urine of aristolochic-acid-treated mice. ELECTROPHORESIS 30 : 1168-1174. https://doi.org/10.1002/elps.200800548
  14. Isaacson T., C. M. Damasceno, R. S. Saravanan, Y. He, C. Catala, M. Saladie, and J. K. Rose. 2006. Sample extraction techniques for enhanced proteomic analysis of plant tissues. Nat Protoc 1 : 769-74. https://doi.org/10.1038/nprot.2006.102
  15. Issaq H. J., T. D. Veenstra, T. P. Conrads, and D. Felschow. 2002. The SELDI-TOF MS approach to proteomics: protein profiling and biomarker identification. Biochem Biophys Res Commun 292 : 587-92. https://doi.org/10.1006/bbrc.2002.6678
  16. Ndao M., A. Rainczuk, M. -C. Rioux, T. W. Spithill, and B. J. Ward. 2010. Is SELDI-TOF a valid tool for diagnostic biomarkers? Trends in Parasitology 26 : 561-567. https://doi.org/10.1016/j.pt.2010.07.004
  17. Panicker G., D. R. Lee, and E. R. Unger. 2009. Optimization of SELDI-TOF protein profiling for analysis of cervical mucous. J Proteomics 71 : 637-46. https://doi.org/10.1016/j.jprot.2008.11.004
  18. Petricoin E. F. and L. A. Liotta. 2004. SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer. Curr Opin Biotechnol 15 : 24-30. https://doi.org/10.1016/j.copbio.2004.01.005
  19. Povero G., M. Papale, G. Loreto, A. Alpi, P. Perata, and E. Loreti. 2010. Identification of Grapevine Cultivar Biomarkers Using Surface-Enhanced Laser Desorption and Ionization (SELDI- TOF-MS). Am. J. Enol. Vitic. 61 : 492-497. https://doi.org/10.5344/ajev.2010.10010
  20. Rollin D., T. Whistler, and S. D. Vernon. 2007. Laboratory methods to improve SELDI peak detection and quantitation. Proteome Sci 5 : 9. https://doi.org/10.1186/1477-5956-5-9
  21. Zhong L., D. L. Taylor, and R. J. Whittington. 2010. Proteomic profiling of ovine serum by SELDI-TOF MS: optimisation, reproducibility and feasibility of biomarker discovery using routinely collected samples. Comp Immunol Microbiol Infect Dis 33 : 47-63. https://doi.org/10.1016/j.cimid.2008.07.009

Cited by

  1. Peptide Profiling and Selection of Specific-Expressed Peptides in Hypoglycemic Sorghum Seed using SELDI-TOF MS vol.59, pp.3, 2014, https://doi.org/10.7740/kjcs.2014.59.3.252