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An Automated Method for Scanning LC−MS Data Sets for Significant Peptides and Proteins, Including Quantitative Profiling and Interactive Confirmation: An Automated Method for Scanning LC−MS Data Sets for Significant Peptides and Proteins, Including Quantitative Profiling and Interactive Confirmation
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, MMS, Medical Mass Spectrometry.
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2007 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 6, no 7, 2888-2895 p.Article in journal (Refereed) Published
Abstract [en]

Differential quantification of proteins and peptides by LC-MS is a promising method to acquire knowledge about biological processes, and for finding drug targets and biomarkers. However, differential protein analysis using LC-MS has been held back by the lack of suitable software tools. Large amounts of experimental data are easily generated in protein and peptide profiling experiments, but data analysis is time-consuming and labor-intensive. Here, we present a fully automated method for scanning LC-MS/MS data for biologically significant peptides and proteins, including support for interactive confirmation and further profiling. By studying peptide mixtures of known composition, we demonstrate that peptides present in different amounts in different groups of samples can be automatically screened for using statistical tests. A linear response can be obtained over almost 3 orders of magnitude, facilitating further profiling of peptides and proteins of interest. Furthermore, we apply the method to study the changes of endogenous peptide levels in mouse brain striatum after administration of reserpine, a classical model drug for inducing Parkinson disease symptoms.

Place, publisher, year, edition, pages
2007. Vol. 6, no 7, 2888-2895 p.
Keyword [en]
LC-MS; quantitation; differential display; neuropeptides; DeCyder MS; label-free quantitation
National Category
Pharmaceutical Sciences
URN: urn:nbn:se:uu:diva-95136DOI: 10.1021/pr060676eISI: 000247792300049OAI: oai:DiVA.org:uu-95136DiVA: diva2:169228
Available from: 2006-11-17 Created: 2006-11-17 Last updated: 2011-02-02Bibliographically approved
In thesis
1. Neuropeptidomics – Methods and Applications
Open this publication in new window or tab >>Neuropeptidomics – Methods and Applications
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The sequencing of genomes has caused a growing demand for functional analysis of gene products. This research field named proteomics is derived from the term proteome, which by analogy to genome is defined as all proteins expressed by a cell or a tissue. Proteomics is however methodologically restricted to the analysis of proteins with higher molecular weights. The development of a technology which includes peptides with low molecular weight and small proteins is needed, since peptides play a central role in many biological processes.

To study endogenous peptides and hormones, the peptidome, an improved method comprising rapid deactivation in combination with nano-flow liquid chromatography (LC) and mass spectrometry (MS) was developed. The method has been used to investigate endogenous peptides in brains of mouse and rat. Several novel peptides have been discovered together with known neuropeptides.

To elucidate the post mortem time influence on peptides and proteins, a time course study was performed using peptidomics and proteomics technologies. Already after three minutes a substantial amount of protein fragments emerged in the peptidomics study and some endogenous peptides were drastically reduced with increasing post mortem time. Of about 1500 proteins investigated, 53 were found to be significantly changed at 10 minutes post mortem as compared to control. Moreover, using western blot the level of MAPK phosphorylation was shown to decrease by 95% in the 10 minutes post mortem sample.

A database, SwePep (a repository of endogenous peptides, hormones and small proteins), was constructed to facilitate identification using MS. The database also contains additional information concerning the peptides such as physical properties. A method for analysis of LC-MS data, including scanning for, and further profiling of, biologically significant peptides was developed. We show that peptides present in different amounts in groups of samples can be automatically detected.

The peptidome approach was used to investigate levels of peptides in two animal models of Parkinson’s disease. PEP-19, was found to be significantly decreased in the striatum of MPTP lesioned parkinsonian mice. The localization and expression was further investigated by imaging MALDI MS and by in situ hybridization. The brain peptidome of reserpine treated mice was investigated and displayed a number of significantly altered peptides. This thesis demonstrates that the peptidomics approach allows for the study of complex biochemical processes.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2006. 57 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 42
Pharmaceutical pharmacology, mass spectrometry, proteomics, peptidomics, neuropeptide, bioinformatics, Farmaceutisk farmakologi
urn:nbn:se:uu:diva-7276 (URN)91-554-6717-2 (ISBN)
Public defence
2006-12-08, B42, BMC, Husargatan 3, Uppsala, 10:00
Available from: 2006-11-17 Created: 2006-11-17Bibliographically approved

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