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Joshi N, Garapati K, Ghose V, Kandasamy RK, Pandey A. Recent progress in mass spectrometry-based urinary proteomics. Clin Proteomics 2024; 21:14. [PMID: 38389064 PMCID: PMC10885485 DOI: 10.1186/s12014-024-09462-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 02/12/2024] [Indexed: 02/24/2024] Open
Abstract
Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.
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Affiliation(s)
- Neha Joshi
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Kishore Garapati
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Vivek Ghose
- Manipal Academy of Higher Education (MAHE), Manipal, 576104, India
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India
| | - Richard K Kandasamy
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Akhilesh Pandey
- Institute of Bioinformatics, International Technology Park, Bangalore, 560066, India.
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
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Abstract
The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.
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Affiliation(s)
- Pey Yee Lee
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
| | - Rahman Jamal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
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Belczacka I, Pejchinovski M, Krochmal M, Magalhães P, Frantzi M, Mullen W, Vlahou A, Mischak H, Jankowski V. Urinary Glycopeptide Analysis for the Investigation of Novel Biomarkers. Proteomics Clin Appl 2018; 13:e1800111. [PMID: 30334612 DOI: 10.1002/prca.201800111] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 08/16/2018] [Indexed: 12/20/2022]
Abstract
PURPOSE Urine is a rich source of potential biomarkers, including glycoproteins. Glycoproteomic analysis remains difficult due to the high heterogeneity of glycans. Nevertheless, recent advances in glycoproteomics software solutions facilitate glycopeptide identification and characterization. The aim is to investigate intact glycopeptides in the urinary peptide profiles of normal subjects using a novel PTM-centric software-Byonic. EXPERIMENTAL DESIGN The urinary peptide profiles of 238 normal subjects, previously analyzed using CE-MS and CE-MS/MS and/or LC-MS/MS, are subjected to glycopeptide analysis. Additionally, glycopeptide distribution is assessed in a set of 969 patients with five different cancer types: bladder, prostate and pancreatic cancer, cholangiocarcinoma, and renal cell carcinoma. RESULTS A total of 37 intact O-glycopeptides and 23 intact N-glycopeptides are identified in the urinary profiles of 238 normal subjects. Among the most commonly identified O-glycoproteins are Apolipoprotein C-III and insulin-like growth factor II, while titin among the N-glycoproteins. Further statistical analysis reveals that three O-glycopeptides and five N-glycopeptides differed significantly in their abundance among the different cancer types, comparing to normal subjects. CONCLUSIONS AND CLINICAL RELEVANCE Through the established glycoproteomics workflow, intact O- and N-glycopeptides in human urine are identified and characterized, providing novel insights for further exploration of the glycoproteome with respect to specific diseases.
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Affiliation(s)
- Iwona Belczacka
- Mosaiques Diagnostics GmbH, 30659 Hannover, Germany.,University Hospital RWTH Aachen, Institute for Molecular Cardiovascular Research (IMCAR), 52074 Aachen, Germany
| | | | | | | | | | - William Mullen
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, G128QQ Glasgow, UK
| | - Antonia Vlahou
- Biotechnology Division, Biomedical Research Foundation Academy of Athens (BRFAA), 11527 Athens, Greece
| | | | - Vera Jankowski
- University Hospital RWTH Aachen, Institute for Molecular Cardiovascular Research (IMCAR), 52074 Aachen, Germany
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Candidate Urine Peptide Biomarkers for IgA Nephropathy: Where Are We Now? DISEASE MARKERS 2018; 2018:5205831. [PMID: 29606986 PMCID: PMC5827886 DOI: 10.1155/2018/5205831] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Revised: 11/29/2017] [Accepted: 12/12/2017] [Indexed: 12/24/2022]
Abstract
Early detection, prognosis, and management of IgA nephropathy (IgAN) remain a challenge. Histological examination of renal tissue still comprises the only way to confirm an IgAN diagnosis. It is of great importance to establish noninvasive diagnostic, prognostic, and predictive biomarkers that would improve the clinical care and outcome of patients suffering from IgAN. This review summarises the findings from previous mass spectrometry- (MS-) based studies dedicated to the discovery of urinary peptide profiles specific to IgAN. There is a substantial number of urinary peptides that have been discovered to date, which show promise as biomarkers of IgAN; however, all of them require further, rigorous validation in well-planned studies, involving a large number of subjects who represent diverse and numerous populations.
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Methodology for Urine Peptidome Analysis Based on Nano-HPLC Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Methods Mol Biol 2018; 1719:311-318. [PMID: 29476520 DOI: 10.1007/978-1-4939-7537-2_20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Urine is a sample of choice for noninvasive biomarkers search because it is easily available in large amounts and its molecular composition provides information on processes in the organism. The high potential of urine peptidomics has been demonstrated for clinical purpose. Several mass spectrometry based approaches have been successfully applied for urine peptidome analysis and potential biomarkers search. Summarizing literature data and our own experience we developed a protocol for comprehensive urine peptidome analysis. The technology includes several stages and consists of urine sample preparation by size exclusion chromatography and identification of featured peptides by nano-HPLC coupled to Fourier transform ion cyclotron resonance mass spectrometry, semiquantitative and statistical data analysis.
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Recent advances in sample pre-treatment for emerging methods in proteomic analysis. Talanta 2017; 174:738-751. [DOI: 10.1016/j.talanta.2017.06.056] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2017] [Revised: 06/14/2017] [Accepted: 06/19/2017] [Indexed: 12/21/2022]
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Di Meo A, Batruch I, Yousef AG, Pasic MD, Diamandis EP, Yousef GM. An integrated proteomic and peptidomic assessment of the normal human urinome. Clin Chem Lab Med 2017; 55:237-247. [PMID: 27394047 DOI: 10.1515/cclm-2016-0390] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Accepted: 06/09/2016] [Indexed: 01/05/2023]
Abstract
BACKGROUND Urine represents an ideal source of clinically relevant biomarkers as it contains a large number of proteins and low molecular weight peptides. The comprehensive characterization of the normal urinary proteome and peptidome can serve as a reference for future biomarker discovery. Proteomic and peptidomic analysis of urine can also provide insight into normal physiology and disease pathology, especially for urogenital diseases. METHODS We developed an integrated proteomic and peptidomic analytical protocol in normal urine. We employed ultrafiltration to separate protein and peptide fractions, which were analyzed separately using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) on the Q-Exactive mass spectrometer. RESULTS By analyzing six urines from healthy individuals with advanced age, we identified 1754 proteins by proteomic analysis and 4543 endogenous peptides, arising from 566 proteins by peptidomic analysis. Overall, we identified 2091 non-redundant proteins by this integrated approach. In silico protease activity analysis indicated that metalloproteases are predominantly involved in the generation of the endogenous peptide signature. In addition, a number of proteins that were detected in normal urine have previously been implicated in various urological malignancies, including bladder cancer and renal cell carcinoma (RCC). CONCLUSIONS We utilized a highly sensitive proteomics approach that enabled us to identify one of the largest sets of protein identifications documented in normal human urine. The raw proteomics and peptidomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD003595.
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Ahmadi M, Elmongy H, Madrakian T, Abdel-Rehim M. Nanomaterials as sorbents for sample preparation in bioanalysis: A review. Anal Chim Acta 2017; 958:1-21. [DOI: 10.1016/j.aca.2016.11.062] [Citation(s) in RCA: 177] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 11/24/2016] [Accepted: 11/27/2016] [Indexed: 01/02/2023]
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Jansen BC, Reiding KR, Bondt A, Hipgrave Ederveen AL, Palmblad M, Falck D, Wuhrer M. MassyTools: A High-Throughput Targeted Data Processing Tool for Relative Quantitation and Quality Control Developed for Glycomic and Glycoproteomic MALDI-MS. J Proteome Res 2015; 14:5088-98. [PMID: 26565759 DOI: 10.1021/acs.jproteome.5b00658] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The study of N-linked glycosylation has long been complicated by a lack of bioinformatics tools. In particular, there is still a lack of fast and robust data processing tools for targeted (relative) quantitation. We have developed modular, high-throughput data processing software, MassyTools, that is capable of calibrating spectra, extracting data, and performing quality control calculations based on a user-defined list of glycan or glycopeptide compositions. Typical examples of output include relative areas after background subtraction, isotopic pattern-based quality scores, spectral quality scores, and signal-to-noise ratios. We demonstrated MassyTools' performance on MALDI-TOF-MS glycan and glycopeptide data from different samples. MassyTools yielded better calibration than the commercial software flexAnalysis, generally showing 2-fold better ppm errors after internal calibration. Relative quantitation using MassyTools and flexAnalysis gave similar results, yielding a relative standard deviation (RSD) of the main glycan of ~6%. However, MassyTools yielded 2- to 5-fold lower RSD values for low-abundant analytes than flexAnalysis. Additionally, feature curation based on the computed quality criteria improved the data quality. In conclusion, we show that MassyTools is a robust automated data processing tool for high-throughput, high-performance glycosylation analysis. The package is released under the Apache 2.0 license and is freely available on GitHub ( https://github.com/Tarskin/MassyTools ).
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Affiliation(s)
- Bas C Jansen
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Karli R Reiding
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Albert Bondt
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands.,Department of Rheumatology, Erasmus University Medical Center , 3000 CA Rotterdam, The Netherlands
| | - Agnes L Hipgrave Ederveen
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Magnus Palmblad
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - David Falck
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands
| | - Manfred Wuhrer
- Center for Proteomics and Metabolomics, Leiden University Medical Center , 2300 RC Leiden, The Netherlands.,Division of BioAnalytical Chemistry, VU University Amsterdam , 1081 HV Amsterdam, The Netherlands
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Pejchinovski M, Klein J, Ramírez-Torres A, Bitsika V, Mermelekas G, Vlahou A, Mullen W, Mischak H, Jankowski V. Comparison of higher energy collisional dissociation and collision-induced dissociation MS/MS sequencing methods for identification of naturally occurring peptides in human urine. Proteomics Clin Appl 2015; 9:531-42. [DOI: 10.1002/prca.201400163] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2014] [Revised: 02/27/2015] [Accepted: 03/23/2015] [Indexed: 01/11/2023]
Affiliation(s)
- Martin Pejchinovski
- Charite-Universitätsmedizin Berlin; Berlin Germany
- Mosaiques Diagnostics GmbH; Hanover Germany
| | | | | | - Vasiliki Bitsika
- Biotechnology Division; Biomedical Research Foundation; Academy of Athens; Athens Greece
| | - George Mermelekas
- Biotechnology Division; Biomedical Research Foundation; Academy of Athens; Athens Greece
| | - Antonia Vlahou
- Biotechnology Division; Biomedical Research Foundation; Academy of Athens; Athens Greece
| | - William Mullen
- Institute of Cardiovascular and Medical Sciences; University of Glasgow; Glasgow UK
| | - Harald Mischak
- Mosaiques Diagnostics GmbH; Hanover Germany
- Institute of Cardiovascular and Medical Sciences; University of Glasgow; Glasgow UK
| | - Vera Jankowski
- Universitätsklinikum RWTH Aachen; Institute of Molecular Cardiovascular Research; Aachen Germany
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Cao W, Hu SS, Ying XZ, Ye LH, Cao J. Surfactant-coated graphitized multiwalled carbon nanotubes as the pseudostationary phase in electrokinetic chromatography for the analysis of phytochemical compounds in biological fluids. Electrophoresis 2015; 36:1055-63. [DOI: 10.1002/elps.201400542] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2014] [Revised: 12/18/2014] [Accepted: 01/07/2015] [Indexed: 11/09/2022]
Affiliation(s)
- Wan Cao
- Department of Pharmaceutical Engineering, College of Material Chemistry and Chemical Engineering; Hangzhou Normal University; Hangzhou P. R. China
| | - Shuai-Shuai Hu
- Department of Pharmaceutical Engineering, College of Material Chemistry and Chemical Engineering; Hangzhou Normal University; Hangzhou P. R. China
| | - Xue-zhen Ying
- Department of Pharmaceutical Engineering, College of Material Chemistry and Chemical Engineering; Hangzhou Normal University; Hangzhou P. R. China
| | - Li-Hong Ye
- Department of Traditional Chinese Medicine, Integrated Chinese and Western Medicine Hospital of Zhejiang Province; Hangzhou P. R. China
| | - Jun Cao
- Department of Pharmaceutical Engineering, College of Material Chemistry and Chemical Engineering; Hangzhou Normal University; Hangzhou P. R. China
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