Literature DB >> 17443642

Implications of 15N-metabolic labeling for automated peptide identification in Arabidopsis thaliana.

Clark J Nelson1, Edward L Huttlin, Adrian D Hegeman, Amy C Harms, Michael R Sussman.   

Abstract

We report the first metabolic labeling of Arabidopsis thaliana for proteomic investigation, demonstrating efficient and complete labeling of intact plants. Using a reversed-database strategy, we evaluate the performance of the MASCOT search engine in the analysis of combined natural abundance and 15N-labeled samples. We find that 15N-metabolic labeling appears to increase the ambiguity associated with peptide identifications due in part to changes in the number of isobaric amino acids when the isotopic label is introduced. This is reflected by changes in the distributions of false positive identifications with respect to MASCOT score. However, by determining the nitrogen count from each pair of labeled and unlabeled peptides we may improve our confidence in both heavy and light identifications.

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Year:  2007        PMID: 17443642     DOI: 10.1002/pmic.200600832

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  30 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2008-01-22       Impact factor: 11.205

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Journal:  Anal Chem       Date:  2008-06-04       Impact factor: 6.986

3.  Precision, proteome coverage, and dynamic range of Arabidopsis proteome profiling using (15)N metabolic labeling and label-free approaches.

Authors:  Borjana Arsova; Henrik Zauber; Waltraud X Schulze
Journal:  Mol Cell Proteomics       Date:  2012-05-05       Impact factor: 5.911

4.  Quantitative proteomics reveals a dynamic association of proteins to detergent-resistant membranes upon elicitor signaling in tobacco.

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Journal:  Mol Cell Proteomics       Date:  2009-06-13       Impact factor: 5.911

5.  Quantitative proteomics by metabolic labeling of model organisms.

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Journal:  Mol Cell Proteomics       Date:  2009-11-19       Impact factor: 5.911

6.  Quantitative phosphoproteomics after auxin-stimulated lateral root induction identifies an SNX1 protein phosphorylation site required for growth.

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Journal:  Mol Cell Proteomics       Date:  2013-01-17       Impact factor: 5.911

7.  Techniques to study autophagy in plants.

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8.  Matching isotopic distributions from metabolically labeled samples.

Authors:  Sean McIlwain; David Page; Edward L Huttlin; Michael R Sussman
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

9.  Stable isotope metabolic labeling with a novel N-enriched bacteria diet for improved proteomic analyses of mouse models for psychopathologies.

Authors:  Elisabeth Frank; Melanie S Kessler; Michaela D Filiou; Yaoyang Zhang; Giuseppina Maccarrone; Stefan Reckow; Mirjam Bunck; Hermann Heumann; Christoph W Turck; Rainer Landgraf; Boris Hambsch
Journal:  PLoS One       Date:  2009-11-13       Impact factor: 3.240

10.  Definition of Arabidopsis sterol-rich membrane microdomains by differential treatment with methyl-beta-cyclodextrin and quantitative proteomics.

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Journal:  Mol Cell Proteomics       Date:  2008-11-25       Impact factor: 5.911

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