Literature DB >> 22246922

Combinatorial peptide ligand libraries for the analysis of low-expression proteins: Validation for normal urine and definition of a first protein MAP.

Laura Santucci1, Giovanni Candiano, Maurizio Bruschi, Chiara D'Ambrosio, Andrea Petretto, Andrea Scaloni, Andrea Urbani, Pier G Righetti, Gian M Ghiggeri.   

Abstract

In this review, we report the evolution on experimental conditions for the analysis of normal urine based on combinatorial peptide ligand library (CPLL) treatment and successive 2-DE and 2-DE/MS analysis. The main topics are (i) definition of the urine sample requirements, (ii) optimization of the urine/ligand ratio, (iii) essay conditions, (iv) en bloc elution. Overall, normal urine protein composition as studied by 2-DE includes over 2600 spots. Relevant data on inter and intraessay reproducibility obtained by the analysis of different normal urines repeated several times are also here presented. We found a 73% reproducibility upon analysis of the same sample and 68% correspondence of protein composition among different normal urine samples. Based on the above results, we are completing the characterization with LC-MS of 249 spots. The composition of normal urine proteins after CPLLs is finally shown with the indication of those spots which are currently under identification. This map will be completed in a near future; in the meantime this would represent the basic reference sample for newly developed studies on human diseases.
Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2012        PMID: 22246922     DOI: 10.1002/pmic.201100404

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  7 in total

1.  Capturing and identification of differentially expressed fucome by a gel free and label free approach.

Authors:  Chanida Puangpila; Ziad El Rassi
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2015-03-14       Impact factor: 3.205

Review 2.  Current state of the art for enhancing urine biomarker discovery.

Authors:  Michael Harpole; Justin Davis; Virginia Espina
Journal:  Expert Rev Proteomics       Date:  2016-06       Impact factor: 3.940

Review 3.  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 2011-2014.

Authors:  Chanida Puangpila; Erandi Mayadunne; Ziad El Rassi
Journal:  Electrophoresis       Date:  2014-11-24       Impact factor: 3.535

4.  Exploring the five-paced viper (Deinagkistrodon acutus) venom proteome by integrating a combinatorial peptide ligand library approach with shotgun LC-MS/MS.

Authors:  Xuekui Nie; Qiyi He; Bin Zhou; Dachun Huang; Junbo Chen; Qianzi Chen; Shuqing Yang; Xiaodong Yu
Journal:  J Venom Anim Toxins Incl Trop Dis       Date:  2021-10-25

5.  Weighted Gene Co-Expression Network Analysis and Support Vector Machine Learning in the Proteomic Profiling of Cerebrospinal Fluid from Extraventricular Drainage in Child Medulloblastoma.

Authors:  Maurizio Bruschi; Xhuliana Kajana; Andrea Petretto; Martina Bartolucci; Marco Pavanello; Gian Marco Ghiggeri; Isabella Panfoli; Giovanni Candiano
Journal:  Metabolites       Date:  2022-08-05

6.  From hundreds to thousands: Widening the normal human Urinome.

Authors:  Laura Santucci; Giovanni Candiano; Andrea Petretto; Maurizio Bruschi; Chiara Lavarello; Elvira Inglese; Pier Giorgio Righetti; Gian Marco Ghiggeri
Journal:  Data Brief       Date:  2014-08-22

7.  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

  7 in total

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