alexa Quantitative proteomic profiling of renal tissue in human chronic rejection biopsy samples after renal transplantation.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): Lin XC, Sui WG, Qi SW, Tang DE, Cong S,

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Abstract INTRODUCTION: Chronic rejection (CR) is the leading cause of late renal transplant failure and is characterized by a relatively slow but progressive loss of renal function in combination with proteinuria and hypertension >3 months after transplantation. To identify and quantify the protein profiles in renal tissues of CR patients, we used isotope tagging for relative and absolute quantification (iTRAQ)-based proteomic technology to perform global protein expression analyses in CR patients and control subjects. MATERIALS AND METHODS: After protein extraction, quantitation, and digestion, samples were labeled with iTRAQ reagents and then separated by strong cation exchange and high-performance liquid chromatography. The fractions were further analyzed by tandem mass spectrometry. ProteinPilot version 4.0 software and the Swiss-Prot human database were applied for statistical analysis and database searching, respectively. Differentially expressed proteins were subjected to bioinformatic analysis by using the Gene Ontology database and the Kyoto Encyclopedia of Genes and Genomes database to further characterize their potential functional roles and related pathways in CR. RESULTS: In total, 1857 distinct proteins (confidence >95\%, ρ < .05) were identified and quantified. Using a strict cutoff value of 1.5-fold for expressed variation, 87 proteins showed significant differences in expression between the CR and control groups; 53 were up-regulated and 34 were down-regulated. The differentially expressed proteins were mainly involved in protein binding, structural molecule activity, and extracellular matrix structural constituent. Several proteins, such as the alpha-1 chain of collagen type IV and integrin alpha-1, may play roles in the pathogenesis of CR and were implicated in the extracellular matrix-receptor interaction pathway. CONCLUSIONS: This study is the first to focus on iTRAQ-based quantitative proteomic characterization of renal tissue in CR. These insights may broaden our understanding of the molecular mechanisms underlying CR and provide potential biomarker candidates for future diagnostics. Copyright © 2015 Elsevier Inc. All rights reserved. This article was published in Transplant Proc and referenced in Journal of Computer Science & Systems Biology

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