ArticleBMC genomics2008
High accuracy mass spectrometry analysis as a tool to verify and improve gene annotation using Mycobacterium tuberculosis as an example.
Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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28 citing papers in PubMed.
- Comparative genomics and transcriptomics of rough and smooth Mycobacterium marinum focusing on ESX-1, ESX-6 and LOS genes.Scientific reports · 2026Article
- PPE51 modulates membrane integrity inmBio · 2025Article
- The PeptideAtlas of a widely cultivated fish Labeo rohita: A resource for the Aquaculture Community.Scientific data · 2022Article
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- On the Impact of the Pangenome and Annotation Discrepancies While Building Protein Sequence Databases for Bacteria Proteogenomics.Frontiers in microbiology · 2019Article
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- A Multistage Subunit Vaccine Effectively Protects Mice Against Primary Progressive Tuberculosis, Latency and Reactivation.EBioMedicine · 2017Article
- SpectroGene: A Tool for Proteogenomic Annotations Using Top-Down Spectra.Journal of proteome research · 2016Article
- A note on the false discovery rate of novel peptides in proteogenomics.Bioinformatics (Oxford, England) · 2015Article
- Differential in vivo expression of mycobacterial antigens in Mycobacterium tuberculosis infected lungs and lymph node tissues.BMC infectious diseases · 2014Article
- Proteogenomic analysis of pathogenic yeast Cryptococcus neoformans using high resolution mass spectrometry.Clinical proteomics · 2014Article
- Deep coverage of the Escherichia coli proteome enables the assessment of false discovery rates in simple proteogenomic experiments.Molecular & cellular proteomics : MCP · 2013Article
- Analysis of the secretome and identification of novel constituents from culture filtrate of bacillus Calmette-Guerin using high-resolution mass spectrometry.Molecular & cellular proteomics : MCP · 2013Article
- Influence of allosteric regulators on individual steps in the reaction catalyzed by Mycobacterium tuberculosis 2-hydroxy-3-oxoadipate synthase.The Journal of biological chemistry · 2013Article
- Reannotation of translational start sites in the genome of Mycobacterium tuberculosis.Tuberculosis (Edinburgh, Scotland) · 2013Article
- Article
- Proteogenomic analysis of Mycobacterium tuberculosis by high resolution mass spectrometry.Molecular & cellular proteomics : MCP · 2011Article
- Proteomic profile of culture filtrate from the Brazilian vaccine strain Mycobacterium bovis BCG Moreau compared to M. bovis BCG Pasteur.BMC microbiology · 2011Article
- Proteogenomic analysis of polymorphisms and gene annotation divergences in prokaryotes using a clustered mass spectrometry-friendly database.Molecular & cellular proteomics : MCP · 2011Article
- Using a label-free proteomics method to identify differentially abundant proteins in closely related hypo- and hypervirulent clinical Mycobacterium tuberculosis Beijing isolates.Molecular & cellular proteomics : MCP · 2010Article
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7 authors.
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Abstract
backgroundWhile the genomic annotations of diverse lineages of the Mycobacterium tuberculosis complex are available, divergences between gene prediction methods are still a challenge for unbiased protein dataset generation. M. tuberculosis gene annotation is an example, where the most used datasets from two independent institutions (Sanger Institute and Institute of Genomic Research-TIGR) differ up to 12% in the number of annotated open reading frames, and 46% of the genes contained in both annotations have different start codons. Such differences emphasize the importance of the identification of the sequence of protein products to validate each gene annotation including its sequence coding area.
resultsWith this objective, we submitted a culture filtrate sample from M. tuberculosis to a high-accuracy LTQ-Orbitrap mass spectrometer analysis and applied refined N-terminal prediction to perform comparison of two gene annotations. From a total of 449 proteins identified from the MS data, we validated 35 tryptic peptides that were specific to one of the two datasets, representing 24 different proteins. From those, 5 proteins were only annotated in the Sanger database. In the remaining proteins, the observed differences were due to differences in annotation of transcriptional start sites.
conclusionOur results indicate that, even in a less complex sample likely to represent only 10% of the bacterial proteome, we were still able to detect major differences between different gene annotation approaches. This gives hope that high-throughput proteomics techniques can be used to improve and validate gene annotations, and in particular for verification of high-throughput, automatic gene annotations.
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