title: High accuracy mass spectrometry analysis as a tool to verify and improve gene annotation using Mycobacterium tuberculosis as an example.
abstract: BACKGROUND
  While 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.
  
  
  RESULTS
  With 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.
  
  
  CONCLUSIONS
  Our 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.
authors.affiliation: Section for Microbiology and Immunology, The Gade Institute, University of Bergen, Bergen, Norway. gustavo.souza@gades.uib.no
authors.forename: Gustavo A
authors.initials: GA
authors.lastname: de Souza
authors.forename: Hiwa
authors.initials: H
authors.lastname: Målen
authors.forename: Tina
authors.initials: T
authors.lastname: Søfteland
authors.forename: Gisle
authors.initials: G
authors.lastname: Saelensminde
authors.forename: Swati
authors.initials: S
authors.lastname: Prasad
authors.forename: Inge
authors.initials: I
authors.lastname: Jonassen
authors.forename: Harald G
authors.initials: HG
authors.lastname: Wiker
mesh_terms: D000595:Amino Acid Sequence; D020029:Base Pairing; D018387:Codon, Initiator; D016208:Databases, Factual; D005798:Genes, Bacterial; D006801:Humans; D013058:Mass Spectrometry / Q000295:instrumentation / Q000379:methods*; D008969:Molecular Sequence Data; D009169:Mycobacterium tuberculosis / Q000235:genetics*; D010455:Peptides / Q000737:chemistry; D020543:Proteome / Q000032:analysis; D040901:Proteomics; D015203:Reproducibility of Results; D014357:Trypsin / Q000494:pharmacology
chemical_list: D018387:Codon, Initiator; D010455:Peptides; D020543:Proteome; D014357:Trypsin