A DIGE study on the effects of salbutamol on the rat muscle proteome - An exemplar of best practice for data sharing in proteomics

被引:4
作者
Kenyani J. [1 ]
Medina-Aunon J.A. [2 ]
Martinez-Bartolomé S. [2 ]
Albar J.-P. [2 ]
Wastling J.M. [1 ]
Jones A.R. [3 ]
机构
[1] Institute of Infection and Global Health, University of Liverpool, Liverpool, Crown Street
[2] Spanish Institute for Proteomics (ProteoRed), Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas, Madrid
[3] Institute of Integrative Biology, University of Liverpool, Biosciences Building, Liverpool, Crown Street
基金
英国生物技术与生命科学研究理事会;
关键词
Salbutamol; Identification File; Data Exchange Format; Enrich Functional Category; Proteomics Standard Initiative;
D O I
10.1186/1756-0500-4-86
中图分类号
学科分类号
摘要
Background: Proteomic techniques allow researchers to perform detailed analyses of cellular states and many studies are published each year, which highlight large numbers of proteins quantified in different samples. However, currently few data sets make it into public databases with sufficient metadata to allow other groups to verify findings, perform data mining or integrate different data sets. The Proteomics Standards Initiative has released a series of "Minimum Information About a Proteomics Experiment" guideline documents (MIAPE modules) and accompanying data exchange formats. This article focuses on proteomic studies based on gel electrophoresis and demonstrates how the corresponding MIAPE modules can be fulfilled and data deposited in public databases, using a new experimental data set as an example. Findings. We have performed a study of the effects of an anabolic agent (salbutamol) at two different time points on the protein complement of rat skeletal muscle cells, quantified by difference gel electrophoresis. In the DIGE study, a total of 31 non-redundant proteins were identified as being potentially modulated at 24 h post treatment and 110 non redundant proteins at 96 h post-treatment. Several categories of function have been highlighted as strongly enriched, providing candidate proteins for further study. We also use the study as an example of best practice for data deposition. Conclusions: We have deposited all data sets from this study in public databases for further analysis by the community. We also describe more generally how gel-based protein identification data sets can now be deposited in the PRoteomics IDEntifications database (PRIDE), using a new software tool, the PRIDESpotMapper, which we developed to work in conjunction with the PRIDE Converter application. We also demonstrate how the ProteoRed MIAPE generator tool can be used to create and share a complete and compliant set of MIAPE reports for this experiment and others. © 2011 Jones et al; licensee BioMed Central Ltd.
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