Collecting and organizing systematic sets of protein data

Nature Reviews Molecular Cell Biology

Volumn 7, Issue 11, 2006, Pages 803-812

  Albeck, John G ^a,b   MacBeath, Gavin ^c   White, Forest M ^a   Sorger, Peter K ^a,b   Lauffenburger, Douglas A ^a   Gaudet, Suzanne ^a,b  

^a Massachusetts Institute of Technology Cambridge   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c HARVARD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENZYME ACTIVITY; ENZYME LINKED IMMUNOSORBENT ASSAY; ERRORS, ARTIFACTS AND QUALITY CONTROL PROCEDURES; FLOW CYTOMETRY; FLUORESCENCE MICROSCOPY; HUMAN; IMMUNOBLOTTING; INFORMATION SYSTEM; ISOTOPE LABELING; MICROARRAY ANALYSIS; MICROFLUIDIC ANALYSIS; MODEL; NONHUMAN; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN DATABASE; PROTEIN EXPRESSION; PROTEIN INTERACTION; PROTEIN MICROARRAY; REVIEW; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY; VALIDATION PROCESS;

ANIMALS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; GENE EXPRESSION REGULATION; HUMANS; IMMUNOASSAY; MODELS, BIOLOGICAL; PROTEIN PROCESSING, POST-TRANSLATIONAL;

MAMMALIA;

EID: 33750314698     PISSN: 14710072     EISSN: 14710080     Source Type: Journal    
DOI: 10.1038/nrm2042     Document Type: Review

References (68)

1. Mockler, T. C. et al. Applications of DNA tiling arrays for whole-genome analysis. Genomics 85, 1-15 (2005).
2. Fan, J. B., Chee, M. S. & Gunderson, K. L. Highly parallel genomic assays. Nature Rev. Genet. 7, 632-644 (2006).
3. Joyce, A. R. & Palsson, B. O. The model organism as a system: integrating 'omics' data sets. Nature Rev. Mol. Cell Biol. 7, 198-210 (2006).
4. Kim, T. H. & Ren, B. Genome-wide analysis of protein-DNA interactions. Annu. Rev. Genomics Hum. Genet. 7, 81-102 (2006).
5. Ness, S. A. Basic microarray analysis: strategies for successful experiments. Methods Mol. Biol. 316, 13-33 (2006).
6. Quackenbush, J. Microarray data normalization and transformation. Nature Genet. 32 (Suppl.), 496-501 (2002).
7. Morris, M. & Watkins, S. M. Focused metabolomic profiling in the drug development process: advances from lipid profiling. Curr. Opin. Chem. Biol. 9, 407-412 (2005).
8. Nielsen, J. & Oliver, S. The next wave in metabolome analysis. Trends Biotechnol. 23, 544-546 (2005).
9. Gaudet, S. et al. A compendium of signals and responses triggered by prodeath and prosurvival cytokines. Mol. Cell. Proteomics 4, 1569-1590 (2005). An example of data-compendium assembly from a data set of ∼7,000 heterogeneous protein measurements. Shows the critical importance of appropriate data normalization and scaling techniques in building predictive models.
10. Sasagawa, S., Ozaki, Y., Fujita, K. & Kuroda, S. Prediction and validation of the distinct dynamics of transient and sustained ERK activation. Nature Cell Biol. 7, 365-373 (2005). A mechanistic modelling effort is driven by an impressive data set of immunoblots and GTPase assays. An excellent example of a model carefully matched to experimental data.
11. Schweitzer, B. et al. Immunoassays with rolling circle DNA amplification: a versatile platform for ultrasensitive antigen detection. Proc. Natl Acad. Sci. USA 97, 10113-10119 (2000).
12. Debad, J. D., Glezer, E. N., Wohlstadter, J. N. & Sigal, G. B. in Electrogenerated Chemiluminescence (ed. Bard, A. J.) 43-78 (Marcel Dekker, New York, 2004).
13. Vignali, D. A. Multiplexed particle-based flow cytometric assays. J. Immunol. Methods 243, 243-255 (2000).
14. Kortum, R. L. et al. The molecular scaffold kinase suppressor of Ras1 (KSR1) regulates adipogenesis. Mol. Cell. Biol. 25, 7592-7604 (2005).
15. Haab, B. B. Advances in protein microarray technology for protein expression and interaction profiling. Curr. Opin. Drug Discov. Devel. 4, 116-123 (2001).
16. MacBeath, G. Protein microarrays and proteomics. Nature Genet. 32 (Suppl.), 526-532 (2002).
17. Wang, C. C. et al. Array-based multiplexed screening and quantitation of human cytokines and chemokines. J. Proteome Res. 1, 337-343 (2002).
18. Olle, E. W. et al. Development of an internally controlled antibody microarray. Mol. Cell. Proteomics 4, 1664-1672 (2005).
19. Jones, R. B., Gordus, A., Krall, J. A. & MacBeath, G. A quantitative protein interaction network for the ErbB receptors using protein microarrays. Nature 439, 168-174 (2006). Protein microarrays were used to measure the synoptic binding profile of all human SH2 and PTB domains for 61 phosphotyrosine sites in the ERBB1-4 receptors.
20. Ptacek, J. et al. Global analysis of protein phosphorylation in yeast. Nature 438, 679-684 (2005).
21. Hermann, T. & Patel, D. J. Adaptive recognition by nucleic acid aptamers. Science 287, 820-825 (2000).
22. Tombelli, S., Minunni, M. & Mascini, M. Analytical applications of aptamers. Biosens. Bioelectron. 20, 2424-2434 (2005).
23. Harlow, E. & Lane, D. Antibodies: a Laboratory Manual. (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, 1988).
24. Colby, D. W. et al. Engineering antibody affinity by yeast surface display. Methods Enzymol. 388, 348-358 (2004).
25. Aebersold, R. & Mann, M. Mass spectrometry-based proteomics. Nature 422, 198-207 (2003).
26. Ong, S. E. et al. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 1, 376-386 (2002).
27. Zieske, L. R. A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies. J. Exp. Bot. 57, 1501-1508 (2006).
28. Zhang, Y. et al. Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules. Mol. Cell. Proteomics 4, 1240-1250 (2005).
29. Schmelzle, K. & White, F. M. Phosphoproteomic approaches to elucidate cellular signaling networks. Curr. Opin. Biotechnol. 17, 406-414 (2006).
30. Beausoleil, S. A. et al. Large-scale characterization of HeLa cell nuclear phosphoproteins. Proc. Natl Acad. Sci. USA 101, 12130-12135 (2004).
31. Moser, K. & White, F. M. Phosphoproteomic analysis of rat liver by high capacity IMAC and LC-MS/MS. J. Proteome Res. 5, 98-104 (2006).
32. Nousiainen, M., Sillje, H. H., Sauer, G., Nigg, E. A. & Korner, R. Phosphoproteome analysis of the human mitotic spindle. Proc. Natl Acad. Sci. USA 103, 5391-5396 (2006).
33. Janes, K. A. et al. A high-throughput quantitative multiplex kinase assay for monitoring information flow in signaling networks: application to sepsis-apoptosis. Mol. Cell. Proteomics 2, 463-473 (2003).
34. Janes, K. A. et al. The response of human epithelial cells to TNF involves an inducible autocrine cascade. Cell 124, 1225-1239 (2006).
35. Shults, M. D. & Imperiali, B. Versatile fluorescence probes of protein kinase activity. J. Am. Chem. Soc. 125, 14248-14249 (2003).
36. Shults, M. D., Pearce, D. A. & Imperiali, B. Modular and tunable chemosensor scaffold for divalent zinc. J. Am. Chem. Soc. 125, 10591-10597 (2003).
37. Shults, M. D., Janes, K. A., Lauffenburger, D. A. & Imperiali, B. A multiplexed homogeneous fluorescence-based assay for protein kinase activity in cell lysates. Nature Methods 2, 277-283 (2005).
38. Evans, M. J. & Cravatt, B. F. Mechanism-based profiling of enzyme families. Chem. Rev. 106, 3279-3301 (2006).
39. Jessani, N. et al. Carcinoma and stromal enzyme activity profiles associated with breast tumor growth in vivo. Proc. Natl Acad. Sci. USA 101, 13756-13761 (2004).
40. Perfetto, S. P., Chattopadhyay, P. K. & Roederer, M. Seventeen-colour flow cytometry: unravelling the immune system. Nature Rev. Immunol. 4, 648-655 (2004).
41. Ecker, R. C. & Steiner, G. E. Microscopy-based multicolor tissue cytometry at the single-cell level. Cytometry A 59, 182-190 (2004).
42. Lahav, G. et al. Dynamics of the p53-Mdm2 feedback loop in individual cells. Nature Genet. 36, 147-150 (2004).
43. Nair, V. D., Yuen, T., Olanow, C. W. & Sealfon, S. C. Early single cell bifurcation of pro- and antiapoptotic states during oxidative stress. J. Biol. Chem. 279, 27494-27501 (2004).
44. Nelson, D. E. et al. Oscillations in NF-κB signaling control the dynamics of gene expression. Science 306, 704-708 (2004). Live-cell imaging and computational modelling are combined to link pulses of NF-κB nuclear translocation to the level of transcriptional activity.
45. Eissing, T. et al. Bistability analyses of a caspase activation model for receptor-induced apoptosis. J. Biol. Chem. 279, 36892-36897 (2004).
46. Geva-Zatorsky, N. et al. Oscillations and variability in the p53 system. Mol. Syst. Biol. 2, 2006.0033 (2006). An intensive effort in which live-cell measurements of p53 and MDM2 translocation dynamics in ∼1,000 single cells are used to constrain mechanistic network models and identify sources of cell-to-cell variability.
47. Rossi, F. M., Kringstein, A. M., Spicher, A., Guicherit, O. M. & Blau, H. M. Transcriptional control: rheostat converted to on/off switch. Mol. Cell 6, 723-728 (2000).
48. Tyas, L., Brophy, V. A., Pope, A., Rivett, A. J. & Tavare, J. M. Rapid caspase-3 activation during apoptosis revealed using fluorescence- resonance energy transfer. EMBO Rep. 1, 266-270 (2000).
49. Krutzik, P. O. & Nolan, G. P. Intracellular phosphoprotein staining techniques for flow cytometry: monitoring single cell signaling events. Cytometry A 55, 61-70 (2003).
50. Sachs, K., Perez, O., Pe'er, D., Lauffenburger, D. A. & Nolan, G. P. Causal protein-signaling networks derived from multiparameter single-cell data. Science 308, 523-529 (2005). A novel method for using flow cytometry data to automatically generate network topology models.
51. Irish, J. M. et al. Single cell profiling of potentiated phospho-protein networks in cancer cells. Cell 118, 217-228 (2004).
52. Perlman, Z. E. et al. Multidimensional drug profiling by automated microscopy. Science 306, 1194-1198 (2004).
53. Soen, Y., Mori, A., Palmer, T. D. & Brown, P. O. Exploring the regulation of human neural precursor cell differentiation using arrays of signaling microenvironments. Mol. Syst. Biol. 2, 37 (2006).
54. Wu, J. Q. & Pollard, T. D. Counting cytokinesis proteins globally and locally in fission yeast. Science 310, 310-314 (2005). Fluorescence microscopy and flow cytometry of yellow-FP-tagged genes was used to determine the absolute global and local concentrations of ∼40 proteins in the yeast cytokinesis network. This is the largest survey of absolute endogenous-protein concentrations so far.
55. Newman, J. R. et al. Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441, 840-846 (2006).
56. Bar-Even, A. et al. Noise in protein expression scales with natural protein abundance. Nature Genet. 38, 636-643 (2006).
57. Danuser, G. & Waterman-Storer, C. M. Quantitative fluorescent speckle microscopy of cytoskeleton dynamics. Annu. Rev. Biophys. Biomol. Struct. 35, 361-387 (2006).
58. Ponti, A., Machacek, M., Gupton, S. L., Waterman-Storer, C. M. & Danuser, G. Two distinct actin networks drive the protrusion of migrating cells. Science 305, 1782-1786 (2004). Statistical modelling of high-resolution live-cell microscopy data reveals remarkable kinetic differences between subsets of the actin network in migrating cells.
59. Sasik, R., Calvo, E. & Corbeil, J. Statistical analysis of high-density oligonucleotide arrays: a multiplicative noise model. Bioinformatics 18, 1633-1640 (2002).
60. Mashima, T., Naito, M., Fujita, N., Noguchi, K. & Tsuruo, T. Identification of actin as a substrate of ICE and an ICE-like protease and involvement of an ICE-like protease but not ICE in VP-16-induced U937 apoptosis. Biochem. Biophys. Res. Commun. 217, 1185-1192 (1995).
61. Sreekumar, A. et al. Profiling of cancer cells using protein microarrays: discovery of novel radiation-regulated proteins. Cancer Res. 61, 7585-7593 (2001).
62. Knezevic, V. et al. Proteomic profiling of the cancer microenvironment by antibody arrays. Proteomics 1, 1271-1278 (2001).
63. Schweitzer, B. et al. Multiplexed protein profiling on microarrays by rolling-circle amplification. Nature Biotechnol. 20, 359-365 (2002).
64. Nielsen, U. B., Cardone, M. H., Sinskey, A. J., MacBeath, G. & Sorger, P. K. Profiling receptor tyrosine kinase activation by using Ab microarrays. Proc. Natl Acad. Sci. USA 100, 9330-9335 (2003).
65. Paweletz, C. P. et al. Reverse phase protein microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front. Oncogene 20, 1981-1989 (2001).
66. Chan, S. M., Ermann, J., Su, L., Fathman, C. G. & Utz, P. J. Protein microarrays for multiplex analysis of signal transduction pathways. Nature Med. 10, 1390-1296 (2004).
67. Schweitzer, B. et al. Multiplexed protein profiling on microarrays by rolling circle amplification. Nature Biotechnol. 20, 359-365 (2002).
68. El-Ali, J., Sorger, P. K. & Jenson, K. F. Cells on chips. Nature 442, 403-411 (2006).