Genome-scale proteome quantification by DEEP SEQ mass spectrometry

Nature Communications

Volumn 4, Issue , 2013, Pages

  Zhou, Feng ^a,b   Lu, Yu ^a,b   Ficarro, Scott B ^a,b   Adelmant, Guillaume ^a,b   Jiang, Wenyu ^c   Luckey, C John ^c   Marto, Jarrod A ^a,b  

^a DANA FARBER CANCER INSTITUTE   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DETERGENT; PROTEOME; PEPTIDE FRAGMENT; TRYPSIN;

AMINO ACID SEQUENCE; ANIMAL CELL; ARTICLE; AUTOMATION; CONTROLLED STUDY; DEEP EFFICIENT PEPTIDE SEQUENCING AND QUANTIFICATION MASS SPECTROMETRY; ECTODERM; FACTUAL DATABASE; GENE EXPRESSION PROFILING; GENE PRODUCT; GENOME ANALYSIS; HIGH THROUGHPUT SEQUENCING; ISOTOPE LABELING; LIQUID CHROMATOGRAPHY; MASS SPECTROMETER; MASS SPECTROMETRY; MEASUREMENT ACCURACY; MOUSE; MOUSE EMBRYONIC STEM CELL; NONHUMAN; PROTEIN ANALYSIS; PROTEIN DEGRADATION; PROTEIN EXPRESSION ASSAY; PROTEIN PROCESSING; PROTEOMICS; QUANTITATIVE ANALYSIS; RNA SEQUENCE; SEQUENCE ANALYSIS; TANDEM MASS SPECTROMETRY; ANIMAL; CELL DIFFERENTIATION; CHEMISTRY; CYTOLOGY; EMBRYONIC STEM CELL; GENE EXPRESSION REGULATION; GENETICS; GENOME; GERM LAYER; METABOLISM; METHODOLOGY; PROTEIN SYNTHESIS; PROCEDURES;

MURINAE;

ANIMALS; CELL DIFFERENTIATION; CHROMATOGRAPHY, LIQUID; EMBRYONIC STEM CELLS; GENE EXPRESSION REGULATION, DEVELOPMENTAL; GENOME; GERM LAYERS; MICE; PEPTIDE FRAGMENTS; PROTEIN BIOSYNTHESIS; PROTEOME; SEQUENCE ANALYSIS, PROTEIN; TANDEM MASS SPECTROMETRY; TRYPSIN;

EID: 84893169526     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms3171     Document Type: Article

References (60)

1. Lander, E. S. Initial impact of the sequencing of the human genome. Nature 470, 187-197 (2011).
2. Ecker, J. R. et al. Genomics: ENCODE explained. Nature 489, 52-55 (2012).
3. Rizzo, J. M. & Buck, M. J. Key principles and clinical applications of 'next-generation' DNA sequencing. Cancer Prev. Res. (Phila) 5, 887-900 (2012).
4. Dunham, I. et al. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74 (2012).
5. Cravatt, B. F., Simon, G. M. & Yates, 3rd J. R. The biological impact of mass-spectrometry-based proteomics. Nature 450, 991-1000 (2007).
6. Aebersold, R. & Mann, M. Mass spectrometry-based proteomics. Nature 422, 198-207 (2003).
7. Schwanhausser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337-342 (2011).
8. Bendall, S. C. et al. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332, 687-696 (2011).
9. Ingolia, N. T., Lareau, L. F. & Weissman, J. S. Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes. Cell 147, 789-802 (2011).
10. Evans, C. et al. An insight into iTRAQ: where do we stand now? Anal. Bioanal. Chem. 404, 1011-1027 (2012).
11. Ow, S. Y. et al. iTRAQ underestimation in simple and complex mixtures:"the good, the bad and the ugly". J. Proteome Res. 8, 5347-5355 (2009).
12. Ting, L., Rad, R., Gygi, S. P. & Haas, W. MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat. Methods 8, 937-940 (2011).
13. Wenger, C. D. et al. Gas-phase purification enables accurate, multiplexed proteome quantification with isobaric tagging. Nat. Methods 8, 933-935 (2011).
14. Askenazi, M., Parikh, J. R. & Marto, J. A. mzAPI: a new strategy for efficiently sharing mass spectrometry data. Nat. Methods 6, 240-242 (2009).
15. Parikh, J. R. et al. multiplierz: an extensible API based desktop environment for proteomics data analysis. BMC Bioinformatics 10, 364 (2009).
16. Ficarro, S. B. et al. Online nanoflow multi-dimensional fractionation strategies for high efficiency phosphopeptide analysis. Mol. Cell. Proteomics 10, doi:10.1074/mcp.O111.011064 (2011).
17. Qeli, E. & Ahrens, C. H. PeptideClassifier for protein inference and targeted quantitative proteomics. Nat. Biotechnol. 28, 647-650 (2010).
18. Graumann, J. et al. Stable isotope labeling by amino acids in cell culture (SILAC) and proteome quantitation of mouse embryonic stem cells to a depth of 5111 proteins. Mol. Cell Proteomics 7, 672-683 (2008).
19. Li, Q. R. et al. Large scale phosphoproteome profiles comprehensive features of mouse embryonic stem cells. Mol. Cell. Proteomics 10, doi:10.1074/mcp.M110.001750 (2011).
20. Wirt, S. E. et al. G1 arrest and differentiation can occur independently of Rb family function. J. Cell. Biol. 191, 809-825 (2010).
21. Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S. & Weissman, J. S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324, 218-223 (2009).
22. Ivanova, N. et al. Dissecting self-renewal in stem cells with RNA interference. Nature 442, 533-538 (2006).
23. Hu, G. et al. A genome-wide RNAi screen identifies a new transcriptional module required for self-renewal. Genes Dev. 23, 837-848 (2009).
24. Wang, J. et al. A protein interaction network for pluripotency of embryonic stem cells. Nature 444, 364-368 (2006).
25. van den Berg, D. L. et al. An Oct4-centered protein interaction network in embryonic stem cells. Cell Stem Cell 6, 369-381 (2010).
26. Pardo, M. et al. An expanded Oct4 interaction network: implications for stem cell biology, development, and disease. Cell Stem Cell 6, 382-395 (2010).
27. Guttman, M. et al. Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat. Biotechnol. 28, 503-510 (2010).
28. Lu, J. et al. MicroRNA expression profiles classify human cancers. Nature 435, 834-838 (2005).
29. Wilkins, M. R. et al. Progress with proteome projects: Why all proteins expressed by a genome should be identified and how to do it. Biotechnol. Genet. Eng. Rev. 13, 19-50 (1996).
30. Zhou, F., Sikorski, T. W., Ficarro, S. B., Webber, J. T. & Marto, J. A. Online nanoflow reversed phase-strong anion exchange-reversed phase liquid chromatography-tandem mass spectrometry platform for efficient and in-depth proteome sequence analysis of complex organisms. Anal. Chem. 83, 6996-7005 (2011).
31. Zhou, F., Lu, Y., Ficarro, S. B., Webber, J. T. & Marto, J. A. Nanoflow low pressure high peak capacity single dimension LC-MS/MS platform for high-throughput, in-depth analysis of mammalian proteomes. Anal. Chem. 84, 5133-5139 (2012).
32. Ficarro, S. B. et al. Improved electrospray ionization efficiency compensates for diminished chromatographic resolution and enables proteomics analysis of tyrosine signaling in embryonic stem cells. Anal. Chem. 81, 3440-3447 (2009).
33. Shen, Y. F. et al. High-efficiency nanoscale liquid chromatography coupled online with mass spectrometry using nanoelectrospray ionization for proteomics. Anal. Chem. 74, 4235-4249 (2002).
34. Nagaraj, N. et al. Deep proteome and transcriptome mapping of a human cancer cell line. Mol. Syst. Biol. 7, 548 (2011).
35. Ingolia, N. T., Brar, G. A., Rouskin, S., McGeachy, A. M. & Weissman, J. S. The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat. Protoc. 7, 1534-1550 (2012).
36. Mertins, P. et al. iTRAQ labeling is superior to mTRAQ for quantitative global proteomics and phosphoproteomics. Mol. Cell Proteomics 11, doi:10.1074/mcp.M111.014423 (2012).
37. Dephoure, N. & Gygi, S. P. Hyperplexing: a method for higher-order multiplexed quantitative proteomics provides a map of the dynamic response to rapamycin in yeast. Sci. Signal 5, doi:10.1126/scisignal.2002548 (2012).
38. Everley, R. A., Kunz, R. C., McAllister, F. E. & Gygi, S. P. Increasing throughput in targeted proteomics assays: 54-plex quantitation in a single mass spectrometry run. Anal. Chem. 85, 5340-5346 (2013).
39. Sun, L., Zhu, G. & Dovichi, N. J. Comparison of the LTQ-orbitrap velos and the q-exactive for proteomic analysis of 1-1000 ng RAW 264.7 cell lysate digests. Rapid Commun. Mass Spectrom. 27, 157-162 (2013).
40. Ding, C. et al. A fast workflow for identification and quantification of proteomes. Mol. Cell. Proteomics doi:10.1074/mcp.O112.025023 (2013).
41. De Jong, E. P. & Griffin, T. J. Online nanoscale ERLIC-MS outperforms RPLC-MS for shotgun proteomics in complex mixtures. J. Proteome Res. 11, 5059-5064 (2012).
42. Luo, Q., Gu, Y., Wu, S. L., Rejtar, T. & Karger, B. L. Two-dimensional strong cation exchange/porous layer open tubular/mass spectrometry for ultratrace proteomic analysis using a 10 microm id poly(styrene- divinylbenzene) porous layer open tubular column with an on-line triphasic trapping column. Electrophoresis 29, 1604-1611 (2008).
43. Ritorto, M. S., Cook, K., Tyagi, K., Pedrioli, P. G. & Trost, M. Hydrophilic strong anion exchange (hSAX) chromatography for highly orthogonal peptide separation of complex proteomes. J. Proteome Res. 12, 2449-2457 (2013).
44. Zhu, G., Sun, L., Yan, X. & Dovichi, N. J. Single-shot proteomics using capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry with production of more than 1250 Escherichia coli peptide identifications in a 50 min separation. Anal. Chem. 85, 2569-2573 (2013).
45. Heemskerk, A. A. et al. Ultra-low flow electrospray ionization-mass spectrometry for improved ionization efficiency in phosphoproteomics. Anal. Chem. 84, 4552-4559 (2012).
46. Wang, Y., Fonslow, B. R., Wong, C. C., Nakorchevsky, A. & Yates, 3rd J. R. Improving the comprehensiveness and sensitivity of sheathless capillary electrophoresis-tandem mass spectrometry for proteomic analysis. Anal. Chem. 84, 8505-8513 (2012).
47. Nichols, J. & Smith, A. Naive and primed pluripotent states. Cell Stem Cell 4, 487-492 (2009).
48. Niwa, H., Ogawa, K., Shimosato, D. & Adachi, K. A parallel circuit of LIF signalling pathways maintains pluripotency of mouse ES cells. Nature 460, 118-122 (2009).
49. Hall, J. et al. Oct4 and LIF/Stat3 additively induce Kruppel factors to sustain embryonic stem cell self-renewal. Cell Stem Cell 5, 597-609 (2009).
50. Huang, C. & Qin, D. Role of Lef1 in sustaining self-renewal in mouse embryonic stem cells. J. Genet. Genomics 37, 441-449 (2010).
51. Martello, G. et al. Esrrb is a pivotal target of the Gsk3/Tcf3 axis regulating embryonic stem cell self-renewal. Cell Stem Cell 11, 491-504 (2012).
52. Matsuo, I., Kuratani, S., Kimura, C., Takeda, N. & Aizawa, S. Mouse Otx2 functions in the formation and patterning of rostral head. Genes Dev. 9, 2646-2658 (1995).
53. Jaegle, M. et al. The POU factor Oct-6 is required for the progression of Schwann cell differentiation in peripheral nerves. Science 273, 507-510 (1996).
54. Le Naour, F., Rubinstein, E., Jasmin, C., Prenant, M. & Boucheix, C. Severely reduced female fertility in CD9-deficient mice. Science 287, 319-321 (2000).
55. Miyado, K. et al. Requirement of CD9 on the egg plasma membrane for fertilization. Science 287, 321-324 (2000).
56. Li, J. Y. et al. Synergistic function of DNA methyltransferases Dnmt3a and Dnmt3b in the methylation of Oct4 and Nanog. Mol. Cell. Biol. 27, 8748-8759 (2007).
57. Ying, Q. L. et al. The ground state of embryonic stem cell self-renewal. Nature 453, 519-523 (2008).
58. Wray, J. et al. Inhibition of glycogen synthase kinase-3 alleviates Tcf3 repression of the pluripotency network and increases embryonic stem cell resistance to differentiation. Nat. Cell Biol. 13, 838-845 (2011).
59. van der Heeft, E. et al. A microcapillary column switching HPLC-electrospray ionization MS system for the direct identification of peptides presented by major histocompatibility complex class I molecules. Anal. Chem. 70, 3742-3751 (1998).
60. Licklider, L. J., Thoreen, C. C., Peng, J. & Gygi, S. P. Automation of nanoscale microcapillary liquid chromatography-tandem mass spectrometry with a vented column. Anal. Chem. 74, 3076-3083 (2002).