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Open Access Research article

A proteogenomic analysis of Shigella flexneri using 2D LC-MALDI TOF/TOF

Lina Zhao12, Liguo Liu1, Wenchuan Leng1, Candong Wei1* and Qi Jin1*

Author affiliations

1 State Key Laboratory for Molecular Virology and Genetic Engineering, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China

2 Department of Biological Engineering, College of Life Sciences, Hebei United University, Tangshan City, Hebei Province, P.R. China

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Citation and License

BMC Genomics 2011, 12:528  doi:10.1186/1471-2164-12-528

Published: 28 October 2011

Abstract

Background

New strategies for high-throughput sequencing are constantly appearing, leading to a great increase in the number of completely sequenced genomes. Unfortunately, computational genome annotation is out of step with this progress. Thus, the accurate annotation of these genomes has become a bottleneck of knowledge acquisition.

Results

We exploited a proteogenomic approach to improve conventional genome annotation by integrating proteomic data with genomic information. Using Shigella flexneri 2a as a model, we identified total 823 proteins, including 187 hypothetical proteins. Among them, three annotated ORFs were extended upstream through comprehensive analysis against an in-house N-terminal extension database. Two genes, which could not be translated to their full length because of stop codon 'mutations' induced by genome sequencing errors, were revised and annotated as fully functional genes. Above all, seven new ORFs were discovered, which were not predicted in S. flexneri 2a str.301 by any other annotation approaches. The transcripts of four novel ORFs were confirmed by RT-PCR assay. Additionally, most of these novel ORFs were overlapping genes, some even nested within the coding region of other known genes.

Conclusions

Our findings demonstrate that current Shigella genome annotation methods are not perfect and need to be improved. Apart from the validation of predicted genes at the protein level, the additional features of proteogenomic tools include revision of annotation errors and discovery of novel ORFs. The complementary dataset could provide more targets for those interested in Shigella to perform functional studies.