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Validation of endogenous peptide identifications using a database of tandem mass spectra
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
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2008 (English)In: Journal of Proteome Research, ISSN 1535-3893, Vol. 7, no 7, 3049-3053 p.Article in journal (Refereed) Published
Abstract [en]

The SwePep database is designed for endogenous peptides and mass spectrometry. It contains information about the peptides such as mass, p/, precursor protein and potential post-translational modifications. Here, we have improved and extended the SwePep database with tandem mass spectra, by adding a locally curated version of the global proteome machine database (GPMDB). In peptidomic experiment practice, many peptide sequences contain multiple tandem mass spectra with different quality. The new tandem mass spectra database in SwePep enables validation of low quality spectra using high quality tandem mass spectra. The validation is performed by comparing the fragmentation patterns of the two spectra using algorithms for calculating the correlation coefficient between the spectra. The present study is the first step in developing a tandem spectrum database for endogenous peptides that can be used for spectrum-to-spectrum identifications instead of peptide identifications using traditional protein sequence database searches.

Place, publisher, year, edition, pages
2008. Vol. 7, no 7, 3049-3053 p.
Keyword [en]
bioinformatics, neuropeptides, peptidomics, peptide identification, MS/MS database
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-97818DOI: 10.1021/pr800036dISI: 000257449500045OAI: oai:DiVA.org:uu-97818DiVA: diva2:172900
Available from: 2008-11-20 Created: 2008-11-20 Last updated: 2009-10-28Bibliographically approved
In thesis
1. Improved Neuropeptide Identification: Bioinformatics and Mass Spectrometry
Open this publication in new window or tab >>Improved Neuropeptide Identification: Bioinformatics and Mass Spectrometry
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Bioinformatic methods were developed for improved identification of endogenous peptides using mass spectrometry. As a framework for these methods, a database for endogenous peptides, SwePep, was created. It was designed for storing information about endogenous peptides including tandem mass spectra. SwePep can be used for identification and validation of endogenous peptides by comparing experimentally derived masses of peptides and their fragments with information in the database. To improve automatic peptide identification of neuropeptides, targeted sequence collections that better mimic the peptidomic sample was derived from the SwePep database. Three sequence collections were created: SwePep precursors, SwePep peptides, and SwePep predicted. The searches for neuropeptides performed against these three sequence collections were compared with searches performed against the entire mouse proteome, and it was observed that three times as many peptides were identified with the targeted SwePep sequence collections. Applying the targeted SwePep sequence collections to identification of previously uncharacterized peptides yielded 27 novel potentially bioactive neuropeptides.

Two fragmentations studies were performed using high mass accuracy tandem mass spectra of tryptic peptides. For this purpose, two databases were created: SwedCAD and SwedECD for CID and ECD tandem mass spectra, respectively. In the first study, fragmentation pattern of peptides with missed cleaved sites was studied using SwedCAD. It was observed that peptides with two arginines positioned next to each other have the same ability to immobilize two protons as peptides with two distant arginines. In the second study, SwedECD was used for studying small neutral losses from the reduced species in ECD fragmentation. The neutral losses were characterized with regard to their specificity and sensitivity to function as reporter ions for revealing the presence of specific amino acids in the peptide sequence. The results from these two studies can be used to improve identification of both tryptic and endogenous peptides.

In summary, a collection of methods was developed that greatly improved the sensitivity of mass spectrometry peptide identification.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2008. 49 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 86
Keyword
bioinformatics, neuropepides, database, peptide identification, peptide fragmentation, mass spectrometry, tandem mass spectromerty
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:uu:diva-9400 (URN)978-91-554-7351-8 (ISBN)
Public defence
2008-12-12, B7:101a, B7, Husargatan 3, Uppsala, 10:15
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Available from: 2008-11-20 Created: 2008-11-20Bibliographically approved

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