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BMC Genomics. 2011 Aug 25;12:433. doi: 10.1186/1471-2164-12-433.

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium.

Author information

1
Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA.

Abstract

BACKGROUND:

Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function.

RESULTS:

We experimentally annotated the bacterial pathogen Salmonella Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in Salmonella and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in Salmonella pathogenesis. We also characterized post-translational features in the Salmonella genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our in vivo proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.

CONCLUSION:

This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of Salmonella as a resource for systems analysis.

PMID:
21867535
PMCID:
PMC3174948
DOI:
10.1186/1471-2164-12-433
[Indexed for MEDLINE]
Free PMC Article

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