Multi-spectra peptide sequencing and its applications to multistage mass spectrometry.

Full Abstract

Despite a recent surge of interest in database-independent peptide identifications, accurate de novo peptide sequencing remains an elusive goal. While the recently introduced spectral network approach resulted in accurate peptide sequencing in low-complexity samples, its success depends on the chance of presence of spectra from overlapping peptides. On the other hand, while multistage mass spectrometry (collecting multiple MS 3 spectra from each MS 2 spectrum) can be applied to all spectra in a complex sample, there are currently no software tools for de novo peptide sequencing by multistage mass spectrometry. We describe a rigorous probabilistic framework for analyzing spectra of overlapping peptides and show how to apply it for multistage mass spectrometry. Our software results in both accurate de novo peptide sequencing from multistage mass spectra (despite the inferior quality of MS 3 spectra) and improved interpretation of spectral networks. We further study the problem of de novo peptide sequencing with accurate parent mass (but inaccurate fragment masses), the protocol that may soon become the dominant mode of spectral acquisition. Most existing peptide sequencing algorithms (based on the spectrum graph approach) do not track the accurate parent mass and are thus not equipped for solving this problem. We describe a de novo peptide sequencing algorithm aimed at this experimental protocol and show that it improves the sequencing accuracy on both tandem and multistage mass spectrometry.

Author information

Author/s: Bandeira, Nuno (N); Olsen, Jesper V (JV); Mann, Jesper V (JV); Mann, Matthias (M); Pevzner, Pavel A (PA);

Affiliation: Department of Computer Science and Engineering, University of California, San Diego, USA. bandeira(-atsign-)ucsd.edu

Grants: 1-R01-RR16522 (Agency:NCRR NIH HHS)

Journal and publication information

Publication Type: Journal Article; Research Support, N.I.H., Extramural

Journal: Bioinformatics (Oxford, England) (Bioinformatics), published in England. (Language: eng)

Reference: 2008-Jul; vol 24 (issue 13) : pp i416-23

Dates: Created 2008/09/10; Completed 2008/09/11; Revised 2009/11/04;

PMID: 18785330, status: MEDLINE (last retrieval date: 11/4/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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