The use of human urine as a diagnostic tool has many advantages, such as ease of sample acquisition and noninvasiveness. However, the discovery of novel biomarkers, as well as biomarker patterns, in urine is hindered mainly by a lack of comparable datasets. To fill this gap, we assembled a new urinary fingerprint database. Here, we report the establishment of a human urinary proteomic fingerprint database using urine from 200 individuals analysed by SELDI-TOF (surface enhanced laser desorption ionisation-time of flight) mass spectrometry (MS) on several chip surfaces (SEND, HP50, NP20, Q10, CM10, and IMAC30). The database currently lists 2490 unique peaks/ion species from 1172 nonredundant SELDI analyses in the mass range of 1500 to 150000. All unprocessed mass spectrometric scans are available as “.xml” data files. Additionally, 1384 peaks were included from external studies using CE (capillary electrophoresis)-MS, MALDI (matrix assisted laser desorption/ionisation), and CE-MALDI hybrids. We propose to use this platform as a global resource to share and exchange primary data derived from MS analyses in urinary research. 1. Introduction Screening of human tissues and biofluids for disease biomarkers is an important task in healthcare and disease prevention but is often hindered by the complexity of the system studied, for example, plasma. A substantially less complex system such as urine, which contains approximately 3000 proteins [1, 2], would be a preferred medium to screen for protein or peptide biomarkers as sampling is both simple and noninvasive, and unrestricted quantities are obtainable. Urine is relatively stable in terms of protein/peptide composition and fragmentation state compared with other body fluids such as serum, where proteolytic degradation by endogenous proteases has been shown to occur during or after sample collection [3]. Several investigations have been published describing the urinary peptidome and proteome [4, 5], including biomarker discoveries for several disease processes [6–10]. These studies have used methodologies ranging from traditional 2D gel electrophoresis alone [11] or coupled with mass spectrometry (2-DE-MS) [12], immunohistochemistry [13], liquid chromatography mass spectrometry (LC-MS) [14], and surface enhanced laser desorption ionisation-time of flight mass spectrometry (SELDI-TOF-MS) [15–17]. In complex disease processes, the identification of biomarkers is key to developing novel therapeutic target molecules. Identification of the most robust urinary biomarkers will be enhanced by collating and correlating
References
[1]
J. Adachi, C. Kumar, Y. Zhang, J. V. Olsen, and M. Mann, “The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins,” Genome Biology, vol. 7, no. 9, pp. R80.1–R80.16, 2006.
[2]
H. Husi, N. A. Stephens, A. Cronshaw, et al., “Proteomic analysis of urinary upper gastrointestinal cancer markers,” Proteomics, vol. 5, no. 5-6, pp. 289–299, 2011.
[3]
D. M. Good, V. Thongboonkerd, J. Novak et al., “Body fluid proteomics for biomarker discovery: lessons from the past hold the key to success in the future,” Journal of Proteome Research, vol. 6, no. 12, pp. 4549–4555, 2007.
[4]
T. Pisitkun, R.-F. Shen, and M. A. Knepper, “Identification and proteomic profiling of exosomes in human urine,” Proceedings of the National Academy of Sciences of the United States of America, vol. 101, no. 36, pp. 13368–13373, 2004.
[5]
V. Thongboonkerd, K. R. McLeish, J. M. Arthur, and J. B. Klein, “Proteomic analysis of normal human urinary proteins isolated by acetone precipitation or ultracentrifugation,” Kidney International, vol. 62, no. 4, pp. 1461–1469, 2002.
[6]
J. Wu, N. Wang, J. Wang et al., “Identification of a uromodulin fragment for diagnosis of IgA nephropathy,” Rapid Communications in Mass Spectrometry, vol. 24, no. 14, pp. 1971–1978, 2010.
[7]
S. Schaub, D. Rush, J. Wilkins et al., “Proteomic-based detection of urine proteins associated with acute renal allograft rejection,” Journal of the American Society of Nephrology, vol. 15, no. 1, pp. 219–227, 2004.
[8]
Z. K. Shihabi, J. C. Konen, and M. L. O'Connor, “Albuminuria vs urinary total protein for detecting chronic renal disorders,” Clinical Chemistry, vol. 37, no. 5, pp. 621–624, 1991.
[9]
J. S. Yudkin, R. D. Forrest, and C. A. Jackson, “Microalbuminuria as predictor of vascular disease in non-diabetic subjects. Islington Diabetes Survey,” The Lancet, vol. 2, no. 8610, pp. 530–533, 1988.
[10]
H. H.-Y. Ngai, W.-H. Sit, P.-P. Jiang, R.-J. Xu, J. M.-F. Wan, and V. Thongboonkerd, “Serial changes in urinary proteome profile of membranous nephropathy: implications for pathophysiology and biomarker discovery,” Journal of Proteome Research, vol. 5, no. 11, pp. 3038–3047, 2006.
[11]
T. Marshall and K. Williams, “Two-dimensional electrophoresis of human urinary proteins following concentration by dye precipitation,” Electrophoresis, vol. 17, no. 7, pp. 1265–1272, 1996.
[12]
R. Pieper, C. L. Gatlin, A. M. McGrath et al., “Characterization of the human urinary proteome: a method for high-resolution display of urinary proteins on two-dimensional electrophoresis gels with a yield of nearly 1400 distinct protein spots,” Proteomics, vol. 4, no. 4, pp. 1159–1174, 2004.
[13]
M. R. Bueler, F. Wiederkehr, and D. J. Vonderschmitt, “Electrophoretic, chromatographic and immunological studies of human urinary proteins,” Electrophoresis, vol. 16, no. 1, pp. 124–134, 1995.
[14]
C. Spahr, M. Davis, M. D. McGinley et al., “Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry I. Profiling an unfractionated tryptic digest,” Proteomics, vol. 1, no. 1, pp. 93–107, 2001.
[15]
P. A. Cadieux, D. T. Beiko, J. D. Watterson et al., “Surface-Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (SELDI-TOF-MS): a new proteomic urinary test for patients with urolithiasis,” Journal of Clinical Laboratory Analysis, vol. 18, no. 3, pp. 170–175, 2004.
[16]
H. Roelofsen, G. Alvarez-Llamas, M. Schepers, K. Landman, and R. J. Vonk, “Proteomics profiling of urine with surface enhanced laser desorption/ionization time of flight mass spectrometry,” Proteome Science, vol. 5, article 2, 2007.
[17]
K. J. A. Vanhoutte, C. Laarakkers, E. Marchiori et al., “Biomarker discovery with SELDI-TOF MS in human urine associated with early renal injury: evaluation with computational analytical tools,” Nephrology Dialysis Transplantation, vol. 22, no. 10, pp. 2932–2943, 2007.
[18]
Y. Zhang, Y. Zhang, J. Adachi et al., “MAPU: max-planck unified database of organellar, cellular, tissue and body fluid proteomes,” Nucleic Acids Research, vol. 35, no. 1, pp. D771–D779, 2007.
[19]
S.-J. Li, M. Peng, H. Li et al., “Sys-BodyFluid: a systematical database for human body fluid proteome research,” Nucleic Acids Research, vol. 37, no. 1, pp. D907–D912, 2009.
[20]
I. A. Agron, D. M. Avtonomov, A. S. Kononikhin, I. A. Popov, S. A. Moshkovskii, and E. N. Nikolaev, “Accurate mass tag retention time database for urine proteome analysis by chromatography-mass spectrometry,” Biochemistry, vol. 75, no. 5, pp. 636–641, 2010.
[21]
J. J. Coon, P. Zürbig, M. Dakna et al., “CE-MS analysis of the human urinary proteome for biomarker discovery and disease diagnostics,” Proteomics, vol. 2, no. 7-8, pp. 964–973, 2008.
[22]
D. M. Good, P. Zürbig, à. Argilés et al., “Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease,” Molecular and Cellular Proteomics, vol. 9, no. 11, pp. 2424–2437, 2010.
[23]
R. Bakry, M. Rainer, C. W. Huck, and G. K. Bonn, “Protein profiling for cancer biomarker discovery using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and infrared imaging: a review,” Analytica Chimica Acta, vol. 690, no. 1, pp. 26–34, 2011.
[24]
M. Rainer, C. Sajdik, and G. K. Bonn, “Mass spectrometric profiling of low-molecular-weight proteins,” Methods in Molecular Biology, vol. 1023, pp. 83–95, 2013.
[25]
L. Chen, S. Fatima, J. Peng, and X. Leng, “SELDI protein chip technology for the detection of serum biomarkers for liver disease,” Protein and Peptide Letters, vol. 16, no. 5, pp. 467–472, 2009.
[26]
T. Gemoll, U. J. Roblick, G. Auer, H. J？rnvall, and J. K. Habermann, “SELDI-TOF serum proteomics and colorectal cancer: a current overview,” Archives of Physiology and Biochemistry, vol. 116, no. 4-5, pp. 188–196, 2010.
[27]
A. K. Callesen, O. Mogensen, A. K. Jensen et al., “Reproducibility of mass spectrometry based protein profiles for diagnosis of ovarian cancer across clinical studies: a systematic review,” Journal of Proteomics, vol. 75, no. 10, pp. 2758–2772, 2012.
