Advances in urinary proteome analysis and applications in systems biology

Bioanalysis

Volumn 6, Issue 19, 2014, Pages 2549-2569

  Filip, Szymon ^a,b   Zoidakis, Jerome ^a   Vlahou, Antonia ^a   Mischak, Harald ^c,d  

^a Academy of Athens Biomedical Research Foundation   (Greece)

^b CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^c MOSAIQUES DIAGNOSTICS GMBH   (Germany)

^d UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEOME; BIOLOGICAL MARKER;

BIOINFORMATICS; COMPUTER PROGRAM; CYTOSCAPE; DATA ANALYSIS SOFTWARE; DATABASE FOR ANNOTATION, VISUALIZATION AND INTEGRATED DISCOVERY; ELECTROSPRAY; EXOSOME; FREEZE DRYING; GEL ELECTROPHORESIS; GEL PERMEATION CHROMATOGRAPHY; GENE ONTOLOGY; GENETIC DATABASE; HUMAN; IMMOBILIZED METAL AFFINITY CHROMATOGRAPHY; IMMUNOAFFINITY CHROMATOGRAPHY; INGENUITY PATHWAY ANALYSIS; ION EXCHANGE CHROMATOGRAPHY; ISOELECTRIC FOCUSING; KYOTO ENCYCLOPEDIA OF GENE AND GENOME; LIMIT OF DETECTION; LIMIT OF QUANTITATION; MASS SPECTROMETER; MASS SPECTROMETRY; MATRIX ASSISTED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; MEASUREMENT ACCURACY; MEASUREMENT PRECISION; MOLECULAR WEIGHT; PRECIPITATION; PROTEIN ANALYSIS; PROTEIN ANALYSIS THROUGH EVOLUTIONARY RELATIONSHIP; PROTEIN DATABASE; PROTEIN DEPLETION; PROTEIN STABILITY; REVIEW; SEARCH ENGINE; SEARCH TOOL FOR THE RETRIEVAL OF INTERACTING GENE AND PROTEIN; SENSITIVITY AND SPECIFICITY; SYSTEMS BIOLOGY; TWO DIMENSIONAL GEL ELECTROPHORESIS; ULTRAFILTRATION; URINALYSIS; METABOLOMICS; PROCEDURES; PROTEOMICS; URINE;

BIOLOGICAL MARKERS; HUMANS; METABOLOMICS; PROTEOME; PROTEOMICS; SYSTEMS BIOLOGY;

EID: 84913597266     PISSN: 17576180     EISSN: 17576199     Source Type: Journal    
DOI: 10.4155/bio.14.210     Document Type: Review

References (170)

1. Barbosa EB, Vidotto A, Polachini GM, Henrique T, Marqui AB, Tajara EH. Proteomics: methodologies and applications to the study of human diseases. Rev. Assoc. Med. Bras. 58(3), 366-375 (2012).
2. Anderson NL, Anderson NG. The human plasma proteome: history, character, and diagnostic prospects. Mol. Cell. Proteomics 1(11), 845-867 (2002).
3. Wasinger VC, Zeng M, Yau Y. Current status and advances in quantitative proteomic mass spectrometry. Int. J. Proteomics 180605 (2013).
4. Nilsson T, Mann M, Aebersold R, Yates JR 3rd, Bairoch A, Bergeron JJ. Mass spectrometry in high-throughput proteomics: ready for the big time. Nat. Methods 7(9), 681-685 (2010).
5. Rodriguez-Suarez E, Siwy J, Zurbig P, Mischak H. Urine as a source for clinical proteome analysis: from discovery to clinical application. Biochim. Biophys. Acta 1844(5), 884-898 (2014).
6. Decramer S, Gonzalez De Peredo A, Breuil B et al. Urine in clinical proteomics. Mol. Cell. Proteomics 7(10), 1850-1862 (2008).
7. Guerrier L, Thulasiraman V, Castagna A et al. Reducing protein concentration range of biological samples using solid-phase ligand libraries. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 833(1), 33-40 (2006).
8. Yates JR, Ruse CI, Nakorchevsky A. Proteomics by mass spectrometry: approaches, advances, and applications. Annu. Rev. Biomed. Eng 11, 49-79 (2009).
9. Moon PG, You S, Lee JE, Hwang D, Baek MC. Urinary exosomes and proteomics. Mass Spectrom. Rev. 30(6), 1185-1202 (2011).
10. Corrado C, Raimondo S, Chiesi A, Ciccia F, De Leo G, Alessandro R. Exosomes as intercellular signaling organelles involved in health and disease: basic science and clinical applications. Int. J. Mol. Sci. 14(3), 5338-5366 (2013).
11. Chen BS, Wu CC. Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. Cells 2(4), 635-688 (2013).
12. Zurbig P, Dihazi H, Metzger J, Thongboonkerd V, Vlahou A. Urine proteomics in kidney and urogenital diseases: moving towards clinical applications. Proteomics Clin. Appl. 5(5-6), 256-268 (2011).
13. Wu J, Chen YD, Gu W. Urinary proteomics as a novel tool for biomarker discovery in kidney diseases. J. Zhejiang Univ. Sci. B 11(4), 227-237 (2010).
14. Thery C, Clayton A, Amigorena S, Raposo G. Isolation and characterization of exosomes from cell culture supernatants and biological fluids. Curr. Protoc. Cell Biol. Chapter 3, Unit 3.22, 22-29 (2006).
15. Pisitkun T, Shen RF, Knepper MA. Identification and proteomic profiling of exosomes in human urine. Proc. Natl Acad. Sci. USA 101(36), 13368-13373 (2004).
16. Raj DA, Fiume I, Capasso G, Pocsfalvi G. Urinary exosomes for protein biomarker research. In: Proteomics - Human Diseases and Protein Functions. Kwong Man T (Ed.). InTech, Rijeka, Croatia (2012).
17. Tauro BJ, Greening DW, Mathias RA et al. Comparison of ultracentrifugation, density gradient separation, and immunoaffinity capture methods for isolating human colon cancer cell line LIM1863-derived exosomes. Methods 56(2), 293-304 (2012).
18. Witwer KW, Buzas EI, Bemis LT et al. Standardization of sample collection, isolation and analysis methods in extracellular vesicle research. J. Extracell. Vesicles 27, 2 (2013).
19. Zhou H, Yuen PS, Pisitkun T et al. Collection, storage, preservation, and normalization of human urinary exosomes for biomarker discovery. Kidney Int. 69(8), 1471-1476 (2006).
20. Zubiri I, Posada-Ayala M, Sanz-Maroto A et al. Diabetic nephropathy induces changes in the proteome of human urinary exosomes as revealed by label-free comparative analysis. J. Proteomics 96, 92-102 (2014).
21. Moon PG, Lee JE, You S et al. Proteomic analysis of urinary exosomes from patients of early IgA nephropathy and thin basement membrane nephropathy. Proteomics 11(12), 2459-2475 (2011).
22. Benito-Martin A, Ucero AC, Zubiri I et al. Osteoprotegerin in exosome-like vesicles from human cultured tubular cells and urine. PLoS ONE 8(8), e72387 (2013).
23. Raj DA, Fiume I, Capasso G, Pocsfalvi G. A multiplex quantitative proteomics strategy for protein biomarker studies in urinary exosomes. Kidney Int. 81(12), 1263-1272 (2012).
24. Righetti PG, Castagna A, Antonioli P, Boschetti E. Prefractionation techniques in proteome analysis: the mining tools of the third millennium. Electrophoresis 26(2), 297-319 (2005).
25. Boschetti E, Lomas L, Citterio A, Righetti PG. Romancing the "hidden proteome", Anno Domini two zero zero seven. J. Chromatogr. A 1153(1-2), 277-290 (2007).
26. Righetti PG, Boschetti E. Sherlock Holmes and the proteome - a detective story. FEBS J. 274(4), 897-905 (2007).
27. Selvaraju S, Rassi ZE. Liquid-phase-based separation systems for depletion, prefractionation and enrichment of proteins in biological fluids and matrices for in-depth proteomics analysis-an update covering the period 2008-2011. Electrophoresis 33(1), 74-88 (2012).
28. Kushnir MM, Mrozinski P, Rockwood AL, Crockett DK. A depletion strategy for improved detection of human proteins from urine. J. Biomol. Tech. 20(2), 101-108 (2009).
29. Magistroni R, Ligabue G, Lupo V et al. Proteomic analysis of urine from proteinuric patients shows a proteolitic activity directed against albumin. Nephrol. Dial. Transplant 24(5), 1672-1681 (2009).
30. Roush DJ, Lu Y. Advances in primary recovery: centrifugation and membrane technology. Biotechnol. Prog. 24(3), 488-495 (2008).
31. Evans DR, Romero JK, Westoby M. Concentration of proteins and removal of solutes. Methods Enzymol. 463, 97-120 (2009)
32. Burgess RR. Protein precipitation techniques. Methods Enzymol. 463, 331-342 (2009).
33. Thongboonkerd V, Mcleish KR, Arthur JM, Klein JB. Proteomic analysis of normal human urinary proteins isolated by acetone precipitation or ultracentrifugation. Kidney Int. 62(4), 1461-1469 (2002).
34. Thongboonkerd V, Chutipongtanate S, Kanlaya R. Systematic evaluation of sample preparation methods for gel-based human urinary proteomics: quantity, quality, and variability. J. Proteome Res. 5(1), 183-191 (2006).
35. Sigdel TK, Lau K, Schilling J, Sarwal M. Optimizing protein recovery for urinary proteomics, a tool to monitor renal transplantation. Clin. Transplant 22(5), 617-623 (2008).
36. Hong P, Koza S, Bouvier ES. Size-Exclusion chromatography for the analysis of protein biotherapeutics and their aggregates. J. Liq. Chromatogr. Relat. Technol. 35(20), 2923-2950 (2012).
37. Stanton P. Gel filtration chromatography. Methods Mol. Biol. 251, 55-74 (2004).
38. Pisitkun T, Gandolfo MT, Das S, Knepper MA, Bagnasco SM. Application of systems biology principles to protein biomarker discovery: urinary exosomal proteome in renal transplantation. Proteomics Clin. Appl. 6(5-6), 268-278 (2012).
39. Osborne C, Brooks SA. SDS-PAGE and Western blotting to detect proteins and glycoproteins of interest in breast cancer research. Methods Mol. Med. 120, 217-229 (2006).
40. Kalantari S, Rutishauser D, Samavat S et al. Urinary prognostic biomarkers and classification of IgA nephropathy by high resolution mass spectrometry coupled with liquid chromatography. PLoS ONE 8(12), e80830 (2013).
41. Froehlich JW, Vaezzadeh AR, Kirchner M et al. An indepth comparison of the male pediatric and adult urinary proteomes. Biochim. Biophys. Acta 1844(5), 1044-1050 (2014).
42. Stoyanov A. IEF-based multidimensional applications in proteomics: toward higher resolution. Electrophoresis 33(22), 3281-3290 (2012).
43. Friedman DB, Hoving S, Westermeier R. Isoelectric focusing and two-dimensional gel electrophoresis. Methods Enzymol. 463, 515-540 (2009).
44. Kasicka V. Recent advances in CE and CEC of peptides (2007-2009). Electrophoresis 31(1), 122-146 (2010).
45. Wright CA, Howles S, Trudgian DC et al. Label-free quantitative proteomics reveals differentially regulated proteins influencing urolithiasis. Mol. Cell Proteomics 10(8), M110. 005686 (2011).
46. Smith R. Two-dimensional electrophoresis: an overview. Methods Mol. Biol. 519, 1-16 (2009).
47. Issaq H, Veenstra T. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE): advances and perspectives. Biotechniques 44(5), 697-698, 700 (2008).
48. Gorg A, Weiss W, Dunn MJ. Current two-dimensional electrophoresis technology for proteomics. Proteomics 4(12), 3665-3685 (2004).
49. Lei T, Zhao X, Jin S, Meng Q, Zhou H, Zhang M. Discovery of potential bladder cancer biomarkers by comparative urine proteomics and analysis. Clin. Genitourin. Cancer 11(1), 56-62 (2013).
50. Castagna A, Olivieri O, Milli A et al. Female urinary proteomics: New insight into exogenous and physiological hormone-dependent changes. Proteomics Clin. Appl. 5(5-6), 343-353 (2011).
51. Verhulst A, Geryl H, D'haese P. No evidence for statininduced proteinuria in healthy volunteers as assessed by proteomic analysis. J. Biomed. Biotechnol. 456076, (2011).
52. Duong-Ly KC, Gabelli SB. Gel filtration chromatography (size exclusion chromatography) of proteins. Methods Enzymol. 541, 105-114 (2014).
53. Jungbauer A, Hahn R. Ion-exchange chromatography. Methods Enzymol. 463, 349-371 (2009).
54. Edelmann MJ. Strong Cation Exchange chromatography in analysis of posttranslational modifications: innovation and perspectives. J. Biomed. Biotechnol. doi:10.1155/2011/936508 (2011) (Epub ahead of print).
55. Urh M, Simpson D, Zhao K. Affinity chromatography: general methods. Methods Enzymol. 463, 417-438 (2009).
56. Wuhrer M, Catalina MI, Deelder AM, Hokke CH. Glycoproteomics based on tandem mass spectrometry of glycopeptides. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 849(1-2), 115-128 (2007).
57. Tian Y, Zhang H. Glycoproteomics and clinical applications. Proteomics Clin. Appl. 4(2), 124-132 (2010).
58. Mechref Y, Madera M, Novotny MV. Glycoprotein enrichment through lectin affinity techniques. Methods Mol. Biol. 424, 373-396 (2008).
59. Kim YJ, Zaidi-Ainouch Z, Gallien S, Domon B. Mass spectrometry-based detection and quantification of plasma glycoproteins using selective reaction monitoring. Nat. Protoc. 7(5), 859-871 (2012).
60. Marimuthu A, O'Meally RN, Chaerkady R et al. A comprehensive map of the human urinary proteome. J. Proteome. Res. 10(6), 2734-2743 (2011).
61. Cheung RC, Wong JH, Ng TB. Immobilized metal ion affinity chromatography: a review on its applications. Appl. Microbiol. Biotechnol. 96(6), 1411-1420 (2012).
62. Frantzi M, Zoidakis J, Papadopoulos T et al. IMAC fractionation in combination with LC-MS reveals H2B and NIF-1 peptides as potential bladder cancer biomarkers. J. Proteome Res. 12(9), 3969-3979 (2013).
63. Rotilio D, Della Corte A, D'Imperio M et al. Proteomics: bases for protein complexity understanding. Thromb. Res. 129(3), 257-262 (2012).
64. Kolch W, Mischak H, Pitt AR. The molecular make-up of a tumour: proteomics in cancer research. Clin. Sci. (Lond.) 108(5), 369-383 (2005).
65. Fliser D, Novak J, Thongboonkerd V et al. Advances in urinary proteome analysis and biomarker discovery. J. Am. Soc. Nephrol. 18(4), 1057-1071 (2007).
66. Stoll DR, Li X, Wang X, Carr PW, Porter SE, Rutan SC. Fast, comprehensive two-dimensional liquid chromatography. J. Chromatogr. A 1168(1-2), 3-43 (2007).
67. Delahunty CM, Yates JR 3rd. MudPIT: multidimensional protein identification technology. Biotechniques 43(5), 563-567, (2007).
68. Principe S, Kim Y, Fontana S et al. Identification of prostate-enriched proteins by in-depth proteomic analyses of expressed prostatic secretions in urine. J. Proteome Res. 11(4), 2386-2396 (2012).
69. Su L, Zhou R, Liu C et al. Urinary proteomics analysis for sepsis biomarkers with iTRAQ labeling and twodimensional liquid chromatography-tandem mass spectrometry. J. Trauma Acute Care Surg. 74(3), 940-945 (2013).
70. Stalmach A, Albalat A, Mullen W, Mischak H. Recent advances in capillary electrophoresis coupled to mass spectrometry for clinical proteomic applications. Electrophoresis 34(11), 1452-1464 (2013).
71. Latosinska A, Frantzi M, Vlahou A, Mischak H. Clinical applications of capillary electrophoresis coupled to mass spectrometry in biomarker discovery: Focus on Bladder Cancer. Proteomics Clin. Appl. doi:10.1002prca.201300038 (2013) (Epub ahead of print).
72. Coon JJ, Zurbig P, Dakna M et al. CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics. Proteomics Clin. Appl. 2(7-8), 964 (2008).
73. Banerjee S, Mazumdar S. Electrospray ionization mass spectrometry: a technique to access the information beyond the molecular weight of the analyte. Int. J. Anal. Chem. doi:10.1155/2012/282574 (2012).
74. Wilm M. Principles of electrospray ionization. Mol. Cell. Proteomics 10(7), M111.009407 (2011).
75. Ho CS, Lam CW, Chan MH et al. Electrospray ionisation mass spectrometry: principles and clinical applications. Clin. Biochem. Rev. 24(1), 3-12 (2003).
76. Yang N, Feng S, Shedden K et al. Urinary glycoprotein biomarker discovery for bladder cancer detection using LC/MS-MS and label-free quantification. Clin. Cancer Res. 17(10), 3349-3359 (2011).
77. Li Y, Zhang Y, Qiu F, Qiu Z. Proteomic identification of exosomal LRG1: a potential urinary biomarker for detecting NSCLC. Electrophoresis 32(15), 1976-1983 (2011).
78. Lemaire R, Tabet JC, Ducoroy P, Hendra JB, Salzet M, Fournier I. Solid ionic matrixes for direct tissue analysis and MALDI imaging. Anal. Chem. 78(3), 809-819 (2006).
79. Lewis KJ, Wei J, Siuzdak G. Matrix-assisted laser desorption/ionization mass spectrometry in peptide and protein analysis. In: Encyclopedia of Analytical Chemistry: Applications, Theory and Instrumentation. Meyers RA (Ed.). Wiley-Blackwell, NJ, USA, 5880-5994 (2000).
80. Debois D, Smargiasso N, Demeure K et al. MALDI in-source decay, from sequencing to imaging. Top. Curr. Chem. 331, 117-141 (2013).
81. He Q, Shao L, Yu J et al. Urinary proteome analysis by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry with magnetic beads for identifying the pathologic presentation of clinical early IgA nephropathy. J. Biomed. Nanotechnol. 8(1), 133-139 (2012).
82. Zubarev RA, Makarov A. Orbitrap mass spectrometry. Anal. Chem. 85(11), 5288-5296 (2013).
83. Metzger J, Negm AA, Plentz RR et al. Urine proteomic analysis differentiates cholangiocarcinoma from primary sclerosing cholangitis and other benign biliary disorders. Gut 62(1), 122-130 (2013).
84. Parker CE, Warren MR, Mocanu V. Mass spectrometry for proteomics. In: Neuroproteomics. Alzate O (Ed.). Taylor and Francis Group, FL, USA (2010).
85. Glauser G, Veyrat N, Rochat B, Wolfender JL, Turlings TC. Ultra-high pressure liquid chromatography-mass spectrometry for plant metabolomics: a systematic comparison of highresolution quadrupole-time-of-flight and single stage Orbitrap mass spectrometers. J. Chromatogr. A 1292, 151-159 (2013).
86. Colangelo CM, Chung L, Bruce C, Cheung KH. Review of software tools for design and analysis of large scale MRM proteomic data sets. Methods 61(3), 287-298 (2013).
87. Chen YT, Chen HW, Domanski D et al. Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers. J. Proteomics 75(12), 3529-3545 (2012).
88. Edwards NJ. Protein identification from tandem mass spectra by database searching. Methods Mol. Biol. 694, 119-138 (2011).
89. Dongre AR, Eng JK, Yates JR 3rd. Emerging tandemmassspectrometry techniques for the rapid identification of proteins. Trends Biotechnol. 15(10), 418-425 (1997).
90. Xu C, Ma B. Software for computational peptide identification from MS-MS data. Drug Discov. Today 11(13-14), 595-600 (2006).
91. Craig R, Beavis RC. A method for reducing the time required to match protein sequences with tandem mass spectra. Rapid Commun. Mass Spectrom. 17(20), 2310-2316 (2003).
92. Eng JK, McCormack AL, Yates JR. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 5(11), 976-989 (1994).
93. Perkins DN, Pappin DJ, Creasy DM, Cottrell JS. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20(18), 3551-3567 (1999).
94. Kall L, Storey JD, Maccoss MJ, Noble WS. Posterior error probabilities and false discovery rates: two sides of the same coin. J. Proteome Res. 7(1), 40-44 (2008).
95. Perez-Riverol Y, Wang R, Hermjakob H, Muller M, Vesada V, Vizcaino JA. Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective. Biochim. Biophys. Acta 1844(1 Pt A), 63-76 (2014).
96. Ma ZQ, Polzin KO, Dasari S et al. QuaMeter: multivendor performance metrics for LC-MS/MS proteomics instrumentation. Anal. Chem. 84(14), 5845-5850 (2012).
97. Chalmers MJ, Mackay CL, Hendrickson CL et al. Combined top-down and bottom-up mass spectrometric approach to characterization of biomarkers for renal disease. Anal. Chem. 77(22), 7163-7171 (2005).
98. Mischak H, Coon JJ, Novak J, Weissinger EM, Schanstra JP, Dominiczak AF. Capillary electrophoresis-mass spectrometry as a powerful tool in biomarker discovery and clinical diagnosis: an update of recent developments. Mass Spectrom. Rev. 28(5), 703-724 (2009).
99. Lilley KS, Friedman DB. All about DIGE: quantification technology for differential-display 2D-gel proteomics. Expert Rev. Proteomics 1(4), 401-409 (2004).
100. Mueller LN, Brusniak MY, Mani DR, Aebersold R. An assessment of software solutions for the analysis of mass spectrometry based quantitative proteomics data. J. Proteome Res. 7(1), 51-61 (2008).
101. Bantscheff M, Lemeer S, Savitski MM, Kuster B. Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present. Anal. Bioanal. Chem. 404(4), 939-965 (2012).
102. Mischak H, Vlahou A, Ioannidis JP. Technical aspects and inter-laboratory variability in native peptide profiling: the CE-MS experience. Clin. Biochem. 46(6), 432-443 (2013).
103. Karpievitch YV, Dabney AR, Smith RD. Normalization and missing value imputation for label-free LC-MS analysis. BMC Bioinformatics 13 (Suppl. 16), S5 (2012).
104. Jantos-Siwy J, Schiffer E, Brand K et al. Quantitative urinary proteome analysis for biomarker evaluation in chronic kidney disease. J. Proteome Res. 8(1), 268-281 (2009).
105. Dakna M, Harris K, Kalousis A et al. Addressing the challenge of defining valid proteomic biomarkers and classifiers. BMC Bioinformatics 11, 594 (2010).
106. Protein Analysis for Clinical Diagnosis and Pharmaceutical Research. www.mosaiques-diagnostics.de/diapatpcms/mosaiquescms/front-content.php
107. Good DM, Zurbig P, Argiles A et al. Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease. Mol. Cell Proteomics 9(11), 2424-2437 (2010).
108. Siwy J, Mullen W, Golovko I, Franke J, Zurbig P. Human urinary peptide database for multiple disease biomarker discovery. Proteomics Clin. Appl. 5(5-6), 367-374 (2011).
109. Magrane M, Consortium U. UniProt Knowledgebase: a hub of integrated protein data. Database (Oxford), doi:10.1093/database/bar009 (2011) (Epub).
110. Shao C, Li M, Li X et al. A tool for biomarker discovery in the urinary proteome: a manually curated human and animal urine protein biomarker database. Mol. Cell. Proteomics 10(11), M111.010975 (2011).
111. Mathivanan S, Fahner CJ, Reid GE, Simpson RJ. ExoCarta 2012: database of exosomal proteins, RNA and lipids. Nucleic Acids Res. 40(Database issue), D1241-D1244 (2012).
112. Simpson RJ, Kalra H, Mathivanan S. ExoCarta as a resource for exosomal research. J. Extracell. Vesicles 1, 18374 (2012).
113. Kalra H, Simpson RJ, Ji H et al. Vesiclepedia: a compendium for extracellular vesicles with continuous community annotation. PLoS Biol. 10(12), e1001450 (2012).
114. Mischak H, Allmaier G, Apweiler R et al. Recommendations for biomarker identification and qualification in clinical proteomics. Sci. Transl. Med. 2(46), 46ps42 (2010).
115. Mischak H, Vlahou A, Righetti PG, Calvete JJ. Putting value in biomarker research and reporting. J. Proteomics 96, A1-A3 (2014).
116. Mischak H, Ioannidis JP, Argiles A et al. Implementation of proteomic biomarkers: making it work. Eur. J. Clin. Invest. 42(9), 1027-1036 (2012).
117. Fuzery AK, Levin J, Chan MM, Chan DW. Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges. Clin. Proteomics 10(1), 13 (2013).
118. Mischak H. How to get proteomics to the clinic? Issues in clinical proteomics, exemplified by CE-MS. Proteomics Clin. Appl. 6(9-10), 437-442 (2012).
119. Ho J, Dart A, Rigatto C. Proteomics in acute kidney injury - current status and future promise. Pediatr. Nephrol. 29(2), 163-171 (2014).
120. Su L, Cao L, Zhou R et al. Identification of novel biomarkers for sepsis prognosis via urinary proteomic analysis using iTRAQ labeling and 2D-LC-MS/MS. PLoS ONE 8(1), e54237 (2013).
121. Chen CL, Lin TS, Tósai CH et al. Identification of potential bladder cancer markers in urine by abundant-protein depletion coupled with quantitative proteomics. J. Proteomics 85, 28-43 (2013).
122. Linden M, Lind SB, Mayrhofer C et al. Proteomic analysis of urinary biomarker candidates for nonmuscle invasive bladder cancer. Proteomics 12(1), 135-144 (2012).
123. Mischak H, Kolch W, Aivaliotis M et al. Comprehensive human urine standards for comparability and standardization in clinical proteome analysis. Proteomics Clin. Appl. 4(4), 464-478 (2010).
124. Sylvester KG, Ling XB, Liu GY et al. Urine protein biomarkers for the diagnosis and prognosis of necrotizing enterocolitis in infants. J. Pediatr. 164(3), 607-612; e601-e607 (2014).
125. Carty DM, Siwy J, Brennand JE et al. Urinary proteomics for prediction of pre-eclampsia. Hypertension 57(3), 561-569 (2011).
126. Metzger J, Chatzikyrkou C, Broecker V et al. Diagnosis of subclinical and clinical acute T-cell-mediated rejection in renal transplant patients by urinary proteome analysis. Proteomics Clin. Appl. 5(5-6), 322-333 (2011).
127. Official Journal of the International Society of Nephrology. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. 3(1), 5-9 (2013).
128. Zurbig P, Jerums G, Hovind P et al. Urinary proteomics for early diagnosis in diabetic nephropathy. Diabetes 61(12), 3304-3313 (2012)
129. Roscioni SS, De Zeeuw D, Hellemons ME et al. A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus. Diabetologia 56(2), 259-267 (2013).
130. Argiles A, Siwy J, Duranton F et al. CKD273, a new proteomics classifier assessing CKD and its prognosis. PLoS ONE 8(5), e62837 (2013).
131. Schiffer E, Bick C, Grizelj B, Pietzker S, Schofer W. Urinary proteome analysis for prostate cancer diagnosis: cost-effective application in routine clinical practice in Germany. Int. J. Urol. 19(2), 118-125 (2012).
132. Wang Z, Hill S, Luther JM, Hachey DL, Schey KL. Proteomic analysis of urine exosomes by multidimensional protein identification technology (MudPIT). Proteomics 12(2), 329-338 (2012).
133. Moore JB, Weeks ME. Proteomics and systems biology: current and future applications in the nutritional sciences. Adv. Nutr. 2(4), 355-364 (2011).
134. Brazma A, Krestyaninova M, Sarkans U. Standards for systems biology. Nat. Rev. Genet. 7(8), 593-605 (2006).
135. Aderem A. Systems biology: its practice and challenges. Cell 121(4), 511-513 (2005).
136. Sullivan DE, Gabbard JL Jr, Shukla M, Sobral B. Data integration for dynamic and sustainable systems biology resources: challenges and lessons learned. Chem. Biodivers. 7(5), 1124-1141 (2010).
137. He JC, Chuang PY, Ma'ayan A, Iyengar R. Systems biology of kidney diseases. Kidney Int. 81(1), 22-39 (2012).
138. Starkey JM, Tilton RG. Proteomics and systems biology for understanding diabetic nephropathy. J. Cardiovasc. Transl. Res. 5(4), 479-490 (2012).
139. Cao YH, Lu LL, Zhang JD, Liu BC. Application of systems biology to the study of chronic kidney disease. Chin. Med. J. (Engl.) 125(14), 2603-2609 (2012).
140. Jiang S, Chuang PY, Liu ZH, He JC. The primary glomerulonephritides: a systems biology approach. Nat. Rev. Nephrol. 9(9), 500-512 (2013).
141. Komorowsky CV, Brosius FC, 3rd, Pennathur S, Kretzler M. Perspectives on systems biology applications in diabetic kidney disease. J. Cardiovasc. Transl. Res. 5(4), 491-508 (2012).
142. Chuang HY, Hofree M, Ideker T. A decade of systems biology. Annu. Rev. Cell Dev. Biol. 26, 721-744 (2010).
143. Bader GD, Cary MP, Sander C. Pathguide: a pathway resource list. Nucleic Acids Res. 34(Database issue), D504-D506 (2006).
144. Keshava Prasad TS, Goel R, Kandasamy K et al. Human Protein Reference Database-2009 update. Nucleic Acids Res. 37(Database issue), D767-D772 (2009).
145. Franceschini A, Szklarczyk D, Frankild S et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 41(Database issue), D808-D815 (2013).
146. Mi H, Muruganujan A, Thomas PD. PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic Acids Res. 41(Database issue), D377-D386 (2013).
147. Tanabe M, Kanehisa M. Using the KEGG database resource. Curr. Protoc. Bioinformatics Chapter 1, Unit 1, 12 (2012).
148. Wrzodek C, Buchel F, Ruff M, Drager A, Zell A. Precise generation of systems biology models from KEGG pathways. BMC Syst. Biol. 7, 15 (2013).
149. Leonelli S, Diehl AD, Christie KR, Harris MA, Lomax J. How the gene ontology evolves. BMC Bioinformatics 12, 325 (2011).
150. Du Plessis L, Skunca N, Dessimoz C. The what, where, how and why of gene ontology-a primer for bioinformaticians. Brief Bioinform. 12(6), 723-735 (2011).
151. Lotia S, Montojo J, Dong Y, Bader GD, Pico AR. Cytoscape app store. Bioinformatics 29(10), 1350-1351 (2013).
152. Bindea G, Mlecnik B, Hackl H et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25(8), 1091-1093 (2009).
153. Bindea G, Galon J, Mlecnik B. CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data. Bioinformatics 29(5), 661-663 (2013).
154. Zuberi K, Franz M, Rodriguez H et al. GeneMANIA prediction server 2013 update. Nucleic Acids Res. 41(Web Server issue), W115-W122 (2013).
155. Maere S, Heymans K, Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21(16), 3448-3449 (2005).
156. Kramer A, Green J, Pollard J, Jr., Tugendreich S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics 30(4), 523-530 (2014).
157. Huang Da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4(1), 44-57 (2009).
158. Jiao X, Sherman BT, Huang Da W et al. DAVID-WS. a stateful web service to facilitate gene/protein list analysis. Bioinformatics 28(13), 1805-1806 (2012).
159. Chance MR, Chang J, Liu S et al. Proteomics, bioinformatics and targeted gene expression analysis reveals up-regulation of cochlin and identifies other potential biomarkers in the mouse model for deafness in Usher syndrome type 1F. Hum. Mol. Genet. 19(8), 1515-1527 (2010).
160. He W, Huang C, Luo G et al. A stable panel comprising 18 urinary proteins in the human healthy population. Proteomics 12(7), 1059-1072 (2012).
161. Zhang Y, Zhang Y, Adachi J et al. MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes. Nucleic Acids Res. 35(Database issue), D771-D779 (2007).
162. Zoidakis J, Makridakis M, Zerefos PG et al. Profilin 1 is a potential biomarker for bladder cancer aggressiveness. Mol. Cell. Proteomics 11(4), M111.009449 (2012).
163. Nagaraj N, Mann M. Quantitative analysis of the intra- and inter-individual variability of the normal urinary proteome. J. Proteome Res. 10(2), 637-645 (2011).
164. Adachi J, Kumar C, Zhang Y, Olsen JV, Mann M. The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins. Genome Biol. 7(9), R80 (2006).
165. Chen G, Zhang Y, Jin X et al. Urinary proteomics analysis for renal injury in hypertensive disorders of pregnancy with iTRAQ labeling and LC-MS/MS. Proteomics Clin. Appl. 5(5-6), 300-310 (2011).
166. Gonzales PA, Pisitkun T, Hoffert JD et al. Large-scale proteomics and phosphoproteomics of urinary exosomes. J. Am. Soc. Nephrol. 20(2), 363-379 (2009).
167. Illig T, Gieger C, Zhai G et al. A genome-wide perspective of genetic variation in human metabolism. Nat. Genet. 42(2), 137-141 (2010).
168. Nkuipou-Kenfack E, Duranton F, Gayrard N et al. Assessment of metabolomic and proteomic biomarkers in detection and prognosis of progression of renal function in chronic kidney disease. PLoS ONE 9(5), e96955 (2014).
169. Vlahou A. Back to the future in bladder cancer research. Expert Rev. Proteomics 8(3), 295-297 (2011).
170. Siwy J, Schanstra JP, Argiles A et al. Multicentre prospective validation of a urinary peptidome-based classifier for the diagnosis of type 2 diabetic nephropathy. Nephrol. Dial. Transplant. 29(8), 1563-1570 (2014).