Email updates

Keep up to date with the latest news and content from BMC Research Notes and BioMed Central.

Open Access Data Note

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

Jenna Kenyani1, J Alberto Medina-Aunon2, Salvador Martinez-Bartolomé2, Juan-Pablo Albar2, Jonathan M Wastling1 and Andrew R Jones3*

Author Affiliations

1 Institute of Infection and Global Health, University of Liverpool, Crown Street, Liverpool, UK

2 Spanish Institute for Proteomics (ProteoRed), Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas, Madrid, Spain

3 Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, Liverpool, UK

For all author emails, please log on.

BMC Research Notes 2011, 4:86  doi:10.1186/1756-0500-4-86

Published: 28 March 2011

Abstract

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.