title: De novo sequencing of unique sequence tags for discovery of post-translational modifications of proteins.
abstract: De novo sequencing is a spectrum analysis approach for mass spectrometry data to discover post-translational modifications in proteins; however, such an approach is still in its infancy and is still not widely applied to proteomic practices due to its limited reliability. In this work, we describe a de novo sequencing approach for the discovery of protein modifications based on identification of the proteome UStags (Shen, Y.; Tolić, N.; Hixson, K. K.; Purvine, S. O.; Pasa-Tolić, L.; Qian, W. J.; Adkins, J. N.; Moore, R. J.; Smith, R. D. Anal. Chem. 2008, 80, 1871-1882). The de novo information was obtained from Fourier-transform tandem mass spectrometry data for peptides and polypeptides from a yeast lysate, and the de novo sequences obtained were selected based on filter levels designed to provide a limited yet high quality subset of UStags. The DNA-predicted database protein sequences were then compared to the UStags, and the differences observed across or in the UStags (i.e., the UStags' prefix and suffix sequences and the UStags themselves) were used to infer possible sequence modifications. With this de novo-UStag approach, we uncovered some unexpected variances within several yeast protein sequences due to amino acid mutations and/or multiple modifications to the predicted protein sequences. To determine false discovery rates, two random (false) databases were independently used for sequence matching, and ~3% false discovery rates were estimated for the de novo-UStag approach. The factors affecting the reliability (e.g., existence of de novo sequencing noise residues and redundant sequences) and the sensitivity of the approach were investigated and described. The combined de novo-UStag approach complements the UStag method previously reported by enabling the discovery of new protein modifications.
authors.affiliation: Biological Science Division, Pacific Northwest National Laboratory, Richland, Washington 99352, USA. Yufeng.shen@pnl.gov
authors.forename: Yufeng
authors.initials: Y
authors.lastname: Shen
authors.forename: Nikola
authors.initials: N
authors.lastname: Tolić
authors.forename: Kim K
authors.initials: KK
authors.lastname: Hixson
authors.forename: Samuel O
authors.initials: SO
authors.lastname: Purvine
authors.forename: Gordon A
authors.initials: GA
authors.lastname: Anderson
authors.forename: Richard D
authors.initials: RD
authors.lastname: Smith
mesh_terms: D000595:Amino Acid Sequence; D005583:Fourier Analysis; D016681:Genome, Fungal; D007554:Isotopes; D013058:Mass Spectrometry; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry; D011499:Protein Processing, Post-Translational; D040901:Proteomics; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry* / Q000378:metabolism*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D007554:Isotopes; D010455:Peptides; D029701:Saccharomyces cerevisiae Proteins
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