Analysis of the pancreatic low molecular weight proteome in an animal model of acute pancreatitis.

Autor: Lassout O; Clinical Proteomics Laboratory, Department of Genetics and Laboratory Medicine, Geneva University Hospitals, Biomedical Proteomics Research Group, Department of Bioinformatics and Structural Biology, Geneva Faculty of Medicine, Geneva, Switzerland., Pastor CM, Fétaud-Lapierre V, Hochstrasser DF, Frossard JL, Lescuyer P
Jazyk: angličtina
Zdroj: Journal of proteome research [J Proteome Res] 2010 Sep 03; Vol. 9 (9), pp. 4535-44.
DOI: 10.1021/pr1002627
Abstrakt: We used a peptidomic approach for the analysis of the low molecular weight proteome in rat pancreatic tissue extracts. The goal was to develop a method that allows identifying endogenous peptides produced in the pancreas in the course of acute pancreatitis. The workflow combines peptides enrichment by centrifugal ultrafiltration, fractionation by isoelectric focusing, and LC-MS/MS analysis without prior enzymatic digestion. The method was assessed on pancreatic extracts from 3 rats with caerulein-induced pancreatitis and 3 healthy controls. A qualitative analysis of the peptide patterns obtained from the different samples was performed to determine the main biological processes associated to the identified peptides. Comparison of peptidomic and immunoblot data for alpha-tubulin, beta-tubulin and coatomer gamma showed that the correlation between the number of identified peptides and the protein abundance was variable. Nevertheless, peptidomic analysis highlighted inflammatory and stress proteins, which peptide pattern was related to acute pancreatitis pathobiology. For these proteins, the higher number of peptides in pancreatitis samples reflected an increase in protein abundance. Moreover, for murinoglobulin-1 or carboxypeptidase B, peptide pattern could be related to protein function. These data suggest that peptidomic analysis is a complementary approach to proteomics for investigating pathobiological processes involved in acute pancreatitis.
Databáze: MEDLINE