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Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as is...

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Autores principales: Schilling, Birgit, Rardin, Matthew J., MacLean, Brendan X., Zawadzka, Anna M., Frewen, Barbara E., Cusack, Michael P., Sorensen, Dylan J., Bereman, Michael S., Jing, Enxuan, Wu, Christine C., Verdin, Eric, Kahn, C. Ronald, MacCoss, Michael J., Gibson, Bradford W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Biochemistry and Molecular Biology 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418851/
https://www.ncbi.nlm.nih.gov/pubmed/22454539
http://dx.doi.org/10.1074/mcp.M112.017707
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author Schilling, Birgit
Rardin, Matthew J.
MacLean, Brendan X.
Zawadzka, Anna M.
Frewen, Barbara E.
Cusack, Michael P.
Sorensen, Dylan J.
Bereman, Michael S.
Jing, Enxuan
Wu, Christine C.
Verdin, Eric
Kahn, C. Ronald
MacCoss, Michael J.
Gibson, Bradford W.
author_facet Schilling, Birgit
Rardin, Matthew J.
MacLean, Brendan X.
Zawadzka, Anna M.
Frewen, Barbara E.
Cusack, Michael P.
Sorensen, Dylan J.
Bereman, Michael S.
Jing, Enxuan
Wu, Christine C.
Verdin, Eric
Kahn, C. Ronald
MacCoss, Michael J.
Gibson, Bradford W.
author_sort Schilling, Birgit
collection PubMed
description Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.
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spelling pubmed-34188512012-08-22 Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION Schilling, Birgit Rardin, Matthew J. MacLean, Brendan X. Zawadzka, Anna M. Frewen, Barbara E. Cusack, Michael P. Sorensen, Dylan J. Bereman, Michael S. Jing, Enxuan Wu, Christine C. Verdin, Eric Kahn, C. Ronald MacCoss, Michael J. Gibson, Bradford W. Mol Cell Proteomics Technological Innovation and Resources Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models. The American Society for Biochemistry and Molecular Biology 2012-05 2012-03-26 /pmc/articles/PMC3418851/ /pubmed/22454539 http://dx.doi.org/10.1074/mcp.M112.017707 Text en © 2012 by The American Society for Biochemistry and Molecular Biology, Inc. Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) applies to Author Choice Articles
spellingShingle Technological Innovation and Resources
Schilling, Birgit
Rardin, Matthew J.
MacLean, Brendan X.
Zawadzka, Anna M.
Frewen, Barbara E.
Cusack, Michael P.
Sorensen, Dylan J.
Bereman, Michael S.
Jing, Enxuan
Wu, Christine C.
Verdin, Eric
Kahn, C. Ronald
MacCoss, Michael J.
Gibson, Bradford W.
Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION
title Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION
title_full Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION
title_fullStr Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION
title_full_unstemmed Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION
title_short Platform-independent and Label-free Quantitation of Proteomic Data Using MS1 Extracted Ion Chromatograms in Skyline: APPLICATION TO PROTEIN ACETYLATION AND PHOSPHORYLATION
title_sort platform-independent and label-free quantitation of proteomic data using ms1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation
topic Technological Innovation and Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3418851/
https://www.ncbi.nlm.nih.gov/pubmed/22454539
http://dx.doi.org/10.1074/mcp.M112.017707
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