請用此 Handle URI 來引用此文件: http://hdl.handle.net/11455/22198
標題: Development of an efficient strategy for purification of plasma membrane proteins
作者: Chen, Hsiang-Ju
關鍵字: 細胞膜蛋白質
Plasma membrane proteins
Sucrose gradient
出版社: 分子生物學研究所
引用: 1. Stevens, T. J. & Arkin, I. T. (2000). Do more complex organisms have a greater proportion of membrane proteins in their genomes? Proteins: Structure, Function, and Bioinformatics 39, 417-420. 2. Leth-Larsen, R., Lund, R. R. & Ditzel, H. J. (2010). Plasma membrane proteomics and its application in clinical cancer biomarker discovery. Mol Cell Proteomics 9, 1369-82. 3. Bast, R. C., Thigpen, J. T., Arbuck, S. G., Basen-Engquist, K., Burke, L. B., Freedman, R., Horning, S. J., Ozols, R., Rustin, G. J., Spriggs, D., Wenzel, L. B. & Pazdur, R. (2007). Clinical trial endpoints in ovarian cancer: report of an FDA/ASCO/AACR Public Workshop. Gynecol Oncol 107, 173-6. 4. Liu, X., Zhang, M., Go, V. L. & Hu, S. (2010). Membrane proteomic analysis of pancreatic cancer cells. J Biomed Sci 17, 74. 5. Lu, D., Kuhn, E., Bristow, R. E., Giuntoli, R. L., 2nd, Kjaer, S. K., Shih, I. M. & Roden, R. B. (2011). Comparison of candidate serologic markers for type I and type II ovarian cancer. Gynecol Oncol. 6. Bast, R. C., Jr., Xu, F. J., Yu, Y. H., Barnhill, S., Zhang, Z. & Mills, G. B. (1998). CA 125: the past and the future. Int J Biol Markers 13, 179-87. 7. Walker, F., Abramowitz, L., Benabderrahmane, D., Duval, X., Descatoire, V., Henin, D., Lehy, T. & Aparicio, T. (2009). Growth factor receptor expression in anal squamous lesions: modifications associated with oncogenic human papillomavirus and human immunodeficiency virus. Hum Pathol 40, 1517-27. 8. Blonder, J., Goshe, M. B., Moore, R. J., Pasa-Tolic, L., Masselon, C. D., Lipton, M. S. & Smith, R. D. (2002). Enrichment of integral membrane proteins for proteomic analysis using liquid chromatography-tandem mass spectrometry. J Proteome Res 1, 351-60. 9. Tan, S., Tan, H. T. & Chung, M. C. (2008). Membrane proteins and membrane proteomics. Proteomics 8, 3924-32. 10. Cao, R., Li, X., Liu, Z., Peng, X., Hu, W., Wang, X., Chen, P., Xie, J. & Liang, S. (2006). Integration of a two-phase partition method into proteomics research on rat liver plasma membrane proteins. J Proteome Res 5, 634-42. 11. Schindler, J., Lewandrowski, U., Sickmann, A., Friauf, E. & Nothwang, H. G. (2006). Proteomic analysis of brain plasma membranes isolated by affinity two-phase partitioning. Mol Cell Proteomics 5, 390-400. 12. Lawson, E. L., Clifton, J. G., Huang, F., Li, X., Hixson, D. C. & Josic, D. (2006). Use of magnetic beads with immobilized monoclonal antibodies for isolation of highly pure plasma membranes. Electrophoresis 27, 2747-58. 13. Zhang, W., Zhou, G., Zhao, Y. & White, M. A. (2003). Affinity enrichment of plasma membrane for proteomics analysis. Electrophoresis 24, 2855-63. 14. Yu, M. J., Pisitkun, T., Wang, G., Shen, R. F. & Knepper, M. A. (2006). LC-MS/MS analysis of apical and basolateral plasma membranes of rat renal collecting duct cells. Mol Cell Proteomics 5, 2131-45. 15. Zhao, Y., Zhang, W. & Kho, Y. (2004). Proteomic analysis of integral plasma membrane proteins. Anal Chem 76, 1817-23. 16. Adam, P. J., Boyd, R., Tyson, K. L., Fletcher, G. C., Stamps, A., Hudson, L., Poyser, H. R., Redpath, N., Griffiths, M., Steers, G., Harris, A. L., Patel, S., Berry, J., Loader, J. A., Townsend, R. R., Daviet, L., Legrain, P., Parekh, R. & Terrett, J. A. (2003). Comprehensive proteomic analysis of breast cancer cell membranes reveals unique proteins with potential roles in clinical cancer. J Biol Chem 278, 6482-9. 17. Mellgren, R. L. (2008). Detergent-resistant membrane subfractions containing proteins of plasma membrane, mitochondrial, and internal membrane origins. J Biochem Biophys Methods 70, 1029-36. 18. Dudkina, N. V., Eubel, H., Keegstra, W., Boekema, E. J. & Braun, H. P. (2005). Structure of a mitochondrial supercomplex formed by respiratory-chain complexes I and III. Proc Natl Acad Sci U S A 102, 3225-9. 19. Foster, L. J., de Hoog, C. L., Zhang, Y., Xie, X., Mootha, V. K. & Mann, M. (2006). A mammalian organelle map by protein correlation profiling. Cell 125, 187-99. 20. Schnolzer, M., Jedrzejewski, P. & Lehmann, W. D. (1996). Protease-catalyzed incorporation of 18O into peptide fragments and its application for protein sequencing by electrospray and matrix-assisted laser desorption/ionization mass spectrometry. Electrophoresis 17, 945-53. 21. Ye, X., Luke, B., Andresson, T. & Blonder, J. (2009). 18O stable isotope labeling in MS-based proteomics. Brief Funct Genomic Proteomic 8, 136-44. 22. Zhang, H., Brown, R. N., Qian, W. J., Monroe, M. E., Purvine, S. O., Moore, R. J., Gritsenko, M. A., Shi, L., Romine, M. F., Fredrickson, J. K., Pasa-Tolic, L., Smith, R. D. & Lipton, M. S. (2010). Quantitative analysis of cell surface membrane proteins using membrane-impermeable chemical probe coupled with 18O labeling. J Proteome Res 9, 2160-9. 23. Hood, B. L., Lucas, D. A., Kim, G., Chan, K. C., Blonder, J., Issaq, H. J., Veenstra, T. D., Conrads, T. P., Pollet, I. & Karsan, A. (2005). Quantitative analysis of the low molecular weight serum proteome using 18O stable isotope labeling in a lung tumor xenograft mouse model. J Am Soc Mass Spectrom 16, 1221-30. 24. Ong, S. E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A. & Mann, M. (2002). Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics 1, 376-86. 25. Chavez, J. D., Hoopmann, M. R., Weisbrod, C. R., Takara, K. & Bruce, J. E. (2011). Quantitative Proteomic and Interaction Network Analysis of Cisplatin Resistance in HeLa Cells. PLoS One 6, e19892. 26. Gruhler, A., Schulze, W. X., Matthiesen, R., Mann, M. & Jensen, O. N. (2005). Stable isotope labeling of Arabidopsis thaliana cells and quantitative proteomics by mass spectrometry. Mol Cell Proteomics 4, 1697-709. 27. Calamia, V., Rocha, B., Mateos, J., Fernandez-Puente, P., Ruiz-Romero, C. & Blanco, F. J. (2011). Metabolic labeling of chondrocytes for the quantitative analysis of the interleukin-1-beta-mediated modulation of their intracellular and extracellular proteomes. J Proteome Res. 28. Liang, X., Zhao, J., Hajivandi, M., Wu, R., Tao, J., Amshey, J. W. & Pope, R. M. (2006). Quantification of membrane and membrane-bound proteins in normal and malignant breast cancer cells isolated from the same patient with primary breast carcinoma. J Proteome Res 5, 2632-41. 29. Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H. & Aebersold, R. (1999). Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat Biotechnol 17, 994-9. 30. Lin, B., White, J. T., Wu, J., Lele, S., Old, L. J., Hood, L. & Odunsi, K. (2009). Deep depletion of abundant serum proteins reveals low-abundant proteins as potential biomarkers for human ovarian cancer. Proteomics Clin Appl 3, 853-861. 31. Zhang, L., Jia, X., Feng, Y., Peng, X., Zhang, Z., Zhou, W., Ma, F., Liu, X., Zheng, Y., Yang, P. & Yuan, Z. (2011). Plasma membrane proteome analysis of the early effect of alcohol on liver: implications for alcoholic liver disease. Acta Biochim Biophys Sin (Shanghai) 43, 19-29. 32. Bantscheff, M., Schirle, M., Sweetman, G., Rick, J. & Kuster, B. (2007). Quantitative mass spectrometry in proteomics: a critical review. Anal Bioanal Chem 389, 1017-31. 33. Malen, H., De Souza, G. A., Pathak, S., Softeland, T. & Wiker, H. G. (2011). Comparison of membrane proteins of Mycobacterium tuberculosis H37Rv and H37Ra strains. BMC Microbiol 11, 18. 34. Niittyla, T., Fuglsang, A. T., Palmgren, M. G., Frommer, W. B. & Schulze, W. X. (2007). Temporal analysis of sucrose-induced phosphorylation changes in plasma membrane proteins of Arabidopsis. Mol Cell Proteomics 6, 1711-26. 35. Kota, U. & Goshe, M. B. (2011). Advances in qualitative and quantitative plant membrane proteomics. Phytochemistry 72, 1040-60. 36. Han, C. L., Chen, J. S., Chan, E. C., Wu, C. P., Yu, K. H., Chen, K. T., Tsou, C. C., Tsai, C. F., Chien, C. W., Kuo, Y. B., Lin, P. Y., Yu, J. S., Hsueh, C., Chen, M. C., Chan, C. C., Chang, Y. S. & Chen, Y. J. (2011). An informatics-assisted label-free approach for personalized tissue membrane proteomics: case study on colorectal cancer. Mol Cell Proteomics 10, M110 003087. 37. Kersey, P. J., Duarte, J., Williams, A., Karavidopoulou, Y., Birney, E. & Apweiler, R. (2004). The International Protein Index: an integrated database for proteomics experiments. Proteomics 4, 1985-8. 38. Tsou, C. C., Tsai, C. F., Tsui, Y. H., Sudhir, P. R., Wang, Y. T., Chen, Y. J., Chen, J. Y., Sung, T. Y. & Hsu, W. L. (2010). IDEAL-Q, an automated tool for label-free quantitation analysis using an efficient peptide alignment approach and spectral data validation. Mol Cell Proteomics 9, 131-44. 39. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., Harris, M. A., Hill, D. P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J. C., Richardson, J. E., Ringwald, M., Rubin, G. M. & Sherlock, G. (2000). Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25, 25-9. 40. Zeeberg, B. R., Feng, W., Wang, G., Wang, M. D., Fojo, A. T., Sunshine, M., Narasimhan, S., Kane, D. W., Reinhold, W. C., Lababidi, S., Bussey, K. J., Riss, J., Barrett, J. C. & Weinstein, J. N. (2003). GoMiner: a resource for biological interpretation of genomic and proteomic data. Genome Biol 4, R28. 41. Damaraju, S., Zhang, N., Li, N., Tao, L., Damaraju, V. L., Dufour, J., Santos, C., Sun, X. J., Mackey, J., Wishart, D. S., Cass, C. E. & Li, L. (2010). Evidence for copurification of micronuclei in sucrose density gradient-enriched plasma membranes from cell lines. Anal Biochem 396, 69-75. 42. Berk, S. G., Guerry, P. & Colwell, R. R. (1976). Separation of small ciliate protozoa from bacteria by sucrose gradient centrifugation. Appl Environ Microbiol 31, 450-2. 43. Santacroce, M., Orsini, F., Mari, S. A., Marinone, M., Lenardi, C., Bette, S., Sacchi, V. F. & Poletti, G. (2008). Atomic force microscopy imaging of Xenopus laevis oocyte plasma membrane purified by ultracentrifugation. Microsc Res Tech 71, 397-402. 44. Lewandrowski, U., Wortelkamp, S., Lohrig, K., Zahedi, R. P., Wolters, D. A., Walter, U. & Sickmann, A. (2009). Platelet membrane proteomics: a novel repository for functional research. Blood 114, e10-9. 45. Smale, G. & Sasse, J. (1992). RNA isolation from cartilage using density gradient centrifugation in cesium trifluoroacetate: an RNA preparation technique effective in the presence of high proteoglycan content. Anal Biochem 203, 352-6. 46. Nielsen, P. A., Olsen, J. V., Podtelejnikov, A. V., Andersen, J. R., Mann, M. & Wisniewski, J. R. (2005). Proteomic mapping of brain plasma membrane proteins. Mol Cell Proteomics 4, 402-8.
摘要: Many plasma membrane proteins are linked to diseases and are often targets of therapeutic drugs. However, analysis of plasma membrane proteins from cancer tissues or cells is far from satisfaction due to their water-insoluble and low abundant natures. The enrichment of plasma membrane proteins is always contaminated by other intracellular organelles. To perform a sensitive and specific analysis of plasma membrane proteome, it is important to develop a better method to improve the extraction efficiency for plasma membrane proteins. We aim to develop an efficient purification strategy to increase the plasma membrane protein identification coverage by mass spectrometry. We expect that this strategy can help us to probe the under-represented membrane proteome. We used our two-step centrifugation method in combination with the conventional ultracentrifugation method to improve the purity of plasma membrane proteins. Using HeLa cells as experiment model, under the same protein identification threshold the purification efficiency between the two-step method and the combined method was compared. 1077 and 1002 proteins were identified in two-step method and combined method, of which 550 (51.1%) and 601 (60%) proteins were annotated as membrane proteins, 353 (32.8%) and 359 (35.8%) were annotated as plasma membrane proteins by Gene Ontology database. The combined method showed better purity and higher identified number of plasma membrane proteins than two-step method. To application on mouse liver tissues, 1398 and 1214 proteins were identified in two-step method and combined method, of which 813 (58.1%) and 723 (59.6%) proteins were annotated as membrane proteins, 343 (24.5%) and 304 (25%) were annotated as plasma membrane proteins. The purification efficiency of combined method apply on cell lines was better than tissue samples. For the reproducibility of combined method, there were 1157, 1269 and 1217 proteins identified in three replicates in mouse liver tissues. Among them, 274 (23.7%), 330 (26%) and 310 (25.5%) proteins were annotated as plasma membrane proteins, which more than 70% (227) plasma membrane proteins were appeared in all of three replicates. The low recovery (10%) often limits the application of ultracentrifugation method on trace amount of starting materials. The combined method can improve the recovery and the purity of identified plasma membrane proteins, indicating that this combined method may have better efficiency for extraction of plasma membrane proteins. To further improve the yield of the plasma membrane proteins by centrifugation, we modified the volume of 20% to 25% sucrose gradients used in ultracentrifugation. Three different types of gradient preparation, including original, expanded, and condensed sucrose gradient, were tested. A total of 91 plasma membrane proteins were identified using condensed gradient, which is higher than using expanded gradient (53 plasma membrane proteins) and original gradient (61 plasma membrane proteins). The condensed gradient had smaller volume (2 ml) of 20% ~ 25% sucrose solutions for ultracentrifugation and thus improved the recovery of plasma membrane proteins. For other organelle proteins, mitochondria membrane protein-rich region were concentrated in 25% ~ 40% sucrose solutions The ER membrane protein-rich region is in 25% ~ 30% sucrose solutions. The nucleus protein-rich region is in 40% solution. The 20% sucrose solution has the highest purity (42.1%) of plasma membrane proteins and lowest contamination from other organelle membrane proteins.
許多細胞膜蛋白扮演著與疾病相互關聯的角色,常成為藥物治療的標的蛋白,然而分析癌症組織或細胞中細胞膜蛋白質仍極富挑戰,例如細胞膜蛋白質具高疏水特性,在細胞膜蛋白質純化的過程中也容易夾雜細胞胞器膜而造成干擾。為了針對細胞膜蛋白進行靈敏且高專一性的分析,我們需要發展一個更有效率的萃取策略,以提升質譜分析所鑑定到的細胞膜蛋白數量,我們也希望這個萃取策略可以鑑定出尚未被發現的細胞膜蛋白。 我們將目前常用的兩步驟離心法 (two-step centrifugation)結合傳統的超高速離心法來提升所萃取的細胞膜蛋白純度,我們比較了兩步驟離心法和結合離心法 (combined method)的純化效率。利用子宮頸癌細胞 (HeLa cells)為測試模式,在參數條件相同的分析中,兩步驟離心法與結合離心法在結果中依序鑑定到平均各1077與1002個蛋白質,其中以Gene Ontology資料庫分類後呈現出所鑑定到的總體膜蛋白數量550 (51.1%)與601 (60%)個,細胞膜蛋白數量為353 (32.8%)、359 (35.8%)個。結果中結合離心法所分離出的細胞膜蛋白純度與鑑定到的細胞膜蛋白數量皆較兩步驟離心法高。若應用於老鼠肝臟組織上,兩步驟離心法與結合離心法依序可鑑定到1398與1214個蛋白質,分類後總體膜蛋白數量為813 (58.1%)與723 (59.6%)個,細胞膜蛋白數量為343 (24.5%)與304 (25%)個,相較於cell line,組織應用上使用結合離心法所提升的純化效率較有限。於結合離心法之重複性測試中,使用老鼠肝臟組織於三重複中可鑑定到1157, 1269, 1217個蛋白質,274 (23.7%), 330 (26%), 310 (25.5%)個蛋白被分類為細胞膜蛋白質,其中大於七成 (227)的細胞膜蛋白質於三重複中皆被鑑定到。 由於低回收率 (10%)是傳統超高速離心法不易進行微量樣品分析的限制,因此使用結合離心法可提升回收率以及鑑定到的細胞膜蛋白純度,顯現了結合離心法能更有效率的萃取細胞膜蛋白質以進行分析。為了將細胞膜蛋白進行有效濃縮,我們調整了超高速離心步驟中蔗糖梯度20%到25%溶液的體積,測試了三種不同的蔗糖梯度配置方式包含原始梯度、延展梯度和壓縮梯度。在壓縮梯度中一個梯度區段最高可鑑定到91個細胞膜蛋白,高於延展梯度所鑑定到的53個和原始梯度的61個細胞膜蛋白。使用壓縮梯度以僅兩毫升的20%至25%蔗糖溶液來進行超高速離心亦可提升細胞膜蛋白量的回收率。於其他胞器蛋白的分佈方面,粒線體膜蛋白傾向集中在25%至40%蔗糖溶液中,內質網膜蛋白則傾向位於25%至30%蔗糖溶液中,細胞核蛋白傾向位在40%蔗糖溶液中。超高速離心後20%蔗糖溶液內含有最高純度的細胞膜蛋白質 (42.1%),同時也避開了其他胞器膜蛋白的干擾。
URI: http://hdl.handle.net/11455/22198
其他識別: U0005-0702201214490300
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-0702201214490300


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