Literature DB >> 24254231

Comparison of CE-MS/MS and LC-MS/MS sequencing demonstrates significant complementarity in natural peptide identification in human urine.

Julie Klein1, Theofilos Papadopoulos, Harald Mischak, William Mullen.   

Abstract

Clinical proteomics has led to the identification of biomarkers specifically associated with a clinical condition that can serve for diagnostic or prognostic purposes. Learning more about the origin of these protein fragments would lead to a better insight in the pathology, and this requires improved identification of the peptide sequences. The aim of this study is to assess the complementarity of LC-MS/MS and CE-MS/MS as techniques in peptide sequence identification of the urinary low-molecular weight proteome. A male standard human urine sample was analyzed using LC- and CE-MS/MS (n = 10 per technique), identifying 905 unique peptide sequences with high confidence, 50% of those were identified only with LC, 20% only with CE and 30% with both techniques. Higher LC coverage might be due in part to the higher amount of sample that can be loaded onto an LC column. Peptides uniquely identified in CE are generally small and highly charged, likely unable to bind to the LC column In conclusion, we showed that LC-MS/MS and CE-MS/MS are highly complementary in identifying peptide sequences. The combination of both technologies results in significantly increased sequence coverage.
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Biomarkers; Clinical proteomics; MS; Peptide sequencing

Mesh:

Substances:

Year:  2013        PMID: 24254231     DOI: 10.1002/elps.201300327

Source DB:  PubMed          Journal:  Electrophoresis        ISSN: 0173-0835            Impact factor:   3.535


  32 in total

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2.  Enrichment of Collagen Fragments Using Dimeric Collagen Hybridizing Peptide for Urinary Collagenomics.

Authors:  Julian L Kessler; Yang Li; Jaime Fornetti; Alana L Welm; S Michael Yu
Journal:  J Proteome Res       Date:  2020-06-16       Impact factor: 4.466

3.  Urine peptidomic biomarkers for diagnosis of patients with systematic lupus erythematosus.

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4.  Preparative capillary electrophoresis (CE) fractionation of protein digests improves protein and peptide identification in bottom-up proteomics.

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Journal:  Anal Methods       Date:  2022-03-17       Impact factor: 3.532

Review 5.  Urinary Proteomics for Diagnosis and Monitoring of Diabetic Nephropathy.

Authors:  G Currie; C Delles
Journal:  Curr Diab Rep       Date:  2016-11       Impact factor: 4.810

Review 6.  Biomarker discovery in mass spectrometry-based urinary proteomics.

Authors:  Samuel Thomas; Ling Hao; William A Ricke; Lingjun Li
Journal:  Proteomics Clin Appl       Date:  2016-02-11       Impact factor: 3.494

7.  A Novel Urinary Proteomics Classifier for Non-Invasive Evaluation of Interstitial Fibrosis and Tubular Atrophy in Chronic Kidney Disease.

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Journal:  Proteomes       Date:  2021-07-13

8.  Urinary signatures of Renal Cell Carcinoma investigated by peptidomic approaches.

Authors:  Clizia Chinello; Marta Cazzaniga; Gabriele De Sio; Andrew James Smith; Erica Gianazza; Angelica Grasso; Francesco Rocco; Stefano Signorini; Marco Grasso; Silvano Bosari; Italo Zoppis; Mohammed Dakna; Yuri E M van der Burgt; Giancarlo Mauri; Fulvio Magni
Journal:  PLoS One       Date:  2014-09-09       Impact factor: 3.240

9.  Identification of Symptomatic Fetuses Infected with Cytomegalovirus Using Amniotic Fluid Peptide Biomarkers.

Authors:  Cyrille Desveaux; Julie Klein; Marianne Leruez-Ville; Adela Ramirez-Torres; Chrystelle Lacroix; Benjamin Breuil; Carine Froment; Jean-Loup Bascands; Joost P Schanstra; Yves Ville
Journal:  PLoS Pathog       Date:  2016-01-25       Impact factor: 6.823

10.  Diastolic Left Ventricular Function in Relation to Urinary and Serum Collagen Biomarkers in a General Population.

Authors:  Zhen-Yu Zhang; Susana Ravassa; Wen-Yi Yang; Thibault Petit; Martin Pejchinovski; Petra Zürbig; Begoña López; Fang-Fei Wei; Claudia Pontillo; Lutgarde Thijs; Lotte Jacobs; Arantxa González; Thomas Koeck; Christian Delles; Jens-Uwe Voigt; Peter Verhamme; Tatiana Kuznetsova; Javier Díez; Harald Mischak; Jan A Staessen
Journal:  PLoS One       Date:  2016-12-13       Impact factor: 3.240

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