Literature DB >> 25585130

Combinatorial Peptide Ligand Library and two dimensional electrophoresis: new frontiers in the study of peritoneal dialysis effluent in pediatric patients.

Maurizio Bruschi1, Giovanni Candiano2, Laura Santucci2, Chiara D'Ambrosio3, Andrea Scaloni3, Marco Bonsano4, Gian Marco Ghiggeri4, Enrico Verrina4.   

Abstract

Peritoneal dialysis effluent (PDE) is a fluid resulting from the close contact of peritoneal dialysis (PD) solutions with the peritoneal membrane (PM) and represents a readily available material for the search of biomarkers of PM function or damage. Our laboratory has developed a method for the in-depth proteomic characterization of PDE, which involves Combinatorial Peptides Ligand Library (CPLL) to reduce the dynamic range of protein concentration in PDE, followed by two-dimensional electrophoresis (2-DE). In this study we applied this method to the analysis of PDE proteome obtained from 19 pediatric patients on automated peritoneal dialysis (APD) with glucose-based PD solutions. The combined use of this proteomic approach highlighted a mean of 700 new proteins. Differences in PDE proteome profile were observed in relation with the duration of APD treatment. In particular, in patients on long-term APD, we observed an increase of intelectin-1, and a decrease of gelsolin. These changes were also observed by in vitro treatment of mesothelial cells with oxidative or pro-fibrotic stimulus which supported the biological role of these proteins' changes. In order to clarify the biological meaning of the observed differences, further step of our study will consist of the longitudinal evaluation of PDE proteome. BIOLOGICAL SIGNIFICANCE: The in-depth proteomic characterization of peritoneal dialysis effluent (PDE) in pediatric patients by the combined use of Combinatorial Peptide Ligand Library (CPLL) and two dimensional electrophoresis allowed to detect 1788 spots, a relevant part (724) of which were previously undetected in sample untreated with CPLL. In patients on long-term automated peritoneal dialysis, this proteomic approach allowed to identify 29 potential biomarkers that could be of help to identify patients with subclinical inflammation and/or developing peritoneal membrane fibrosis, thus adapting dialysis treatment accordingly.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Automated peritoneal dialysis; Combinatorial Peptide Ligand Library; Gelsolin; Intelectin-1; Peritoneal dialysis effluent; Two dimensional electrophoresis

Mesh:

Substances:

Year:  2015        PMID: 25585130     DOI: 10.1016/j.jprot.2015.01.003

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  4 in total

Review 1.  Proteomics and Extracellular Vesicles as Novel Biomarker Sources in Peritoneal Dialysis in Children.

Authors:  Chiara Trincianti; Vincenzo Meleca; Edoardo La Porta; Maurizio Bruschi; Giovanni Candiano; Andrea Garbarino; Xhuliana Kajana; Alberto Preda; Francesca Lugani; Gian Marco Ghiggeri; Andrea Angeletti; Pasquale Esposito; Enrico Verrina
Journal:  Int J Mol Sci       Date:  2022-05-18       Impact factor: 6.208

2.  Effects of Alanyl-Glutamine Treatment on the Peritoneal Dialysis Effluent Proteome Reveal Pathomechanism-Associated Molecular Signatures.

Authors:  Rebecca Herzog; Michael Boehm; Markus Unterwurzacher; Anja Wagner; Katja Parapatics; Peter Májek; André C Mueller; Anton Lichtenauer; Keiryn L Bennett; Seth L Alper; Andreas Vychytil; Christoph Aufricht; Klaus Kratochwill
Journal:  Mol Cell Proteomics       Date:  2017-12-04       Impact factor: 5.911

3.  Yinchenhao Decoction Ameliorates Alpha-Naphthylisothiocyanate Induced Intrahepatic Cholestasis in Rats by Regulating Phase II Metabolic Enzymes and Transporters.

Authors:  Ya-Xiong Yi; Yue Ding; Yong Zhang; Ning-Hui Ma; Feng Shi; Ping Kang; Zhen-Zhen Cai; Tong Zhang
Journal:  Front Pharmacol       Date:  2018-05-15       Impact factor: 5.810

Review 4.  Proteomic Research in Peritoneal Dialysis.

Authors:  Mario Bonomini; Francesc E Borras; Maribel Troya-Saborido; Laura Carreras-Planella; Lorenzo Di Liberato; Arduino Arduini
Journal:  Int J Mol Sci       Date:  2020-07-31       Impact factor: 5.923

  4 in total

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