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Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites

The data described here provide a systematic performance evaluation of popular data-dependent (DDA) and independent (DIA) mass spectrometric (MS) workflows currently used in quantitative proteomics. We assessed the limits of identification, quantification and detection for each method by analyzing a...

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Autores principales: Bauer, Manuel, Ahrné, Erik, Baron, Anna P., Glatter, Timo, Fava, Luca L., Santamaria, Anna, Nigg, Erich A., Schmidt, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4596922/
https://www.ncbi.nlm.nih.gov/pubmed/26550600
http://dx.doi.org/10.1016/j.dib.2015.08.015
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author Bauer, Manuel
Ahrné, Erik
Baron, Anna P.
Glatter, Timo
Fava, Luca L.
Santamaria, Anna
Nigg, Erich A.
Schmidt, Alexander
author_facet Bauer, Manuel
Ahrné, Erik
Baron, Anna P.
Glatter, Timo
Fava, Luca L.
Santamaria, Anna
Nigg, Erich A.
Schmidt, Alexander
author_sort Bauer, Manuel
collection PubMed
description The data described here provide a systematic performance evaluation of popular data-dependent (DDA) and independent (DIA) mass spectrometric (MS) workflows currently used in quantitative proteomics. We assessed the limits of identification, quantification and detection for each method by analyzing a dilution series of 20 unmodified and 10 phosphorylated synthetic heavy labeled reference peptides, respectively, covering six orders of magnitude in peptide concentration with and without a complex human cell digest background. We found that all methods performed very similarly in the absence of background proteins, however, when analyzing whole cell lysates, targeted methods were at least 5–10 times more sensitive than directed or DDA methods. In particular, higher stage fragmentation (MS3) of the neutral loss peak using a linear ion trap increased dynamic quantification range of some phosphopeptides up to 100-fold. We illustrate the power of this targeted MS3 approach for phosphopeptide monitoring by successfully quantifying 9 phosphorylation sites of the kinetochore and spindle assembly checkpoint component Mad1 over different cell cycle states from non-enriched pull-down samples. The data are associated to the research article ‘Evaluation of data-dependent and data-independent mass spectrometric workflows for sensitive quantification of proteins and phosphorylation sites׳ (Bauer et al., 2014) [1]. The mass spectrometry and the analysis dataset have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD000964.
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spelling pubmed-45969222015-11-06 Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites Bauer, Manuel Ahrné, Erik Baron, Anna P. Glatter, Timo Fava, Luca L. Santamaria, Anna Nigg, Erich A. Schmidt, Alexander Data Brief Data Article The data described here provide a systematic performance evaluation of popular data-dependent (DDA) and independent (DIA) mass spectrometric (MS) workflows currently used in quantitative proteomics. We assessed the limits of identification, quantification and detection for each method by analyzing a dilution series of 20 unmodified and 10 phosphorylated synthetic heavy labeled reference peptides, respectively, covering six orders of magnitude in peptide concentration with and without a complex human cell digest background. We found that all methods performed very similarly in the absence of background proteins, however, when analyzing whole cell lysates, targeted methods were at least 5–10 times more sensitive than directed or DDA methods. In particular, higher stage fragmentation (MS3) of the neutral loss peak using a linear ion trap increased dynamic quantification range of some phosphopeptides up to 100-fold. We illustrate the power of this targeted MS3 approach for phosphopeptide monitoring by successfully quantifying 9 phosphorylation sites of the kinetochore and spindle assembly checkpoint component Mad1 over different cell cycle states from non-enriched pull-down samples. The data are associated to the research article ‘Evaluation of data-dependent and data-independent mass spectrometric workflows for sensitive quantification of proteins and phosphorylation sites׳ (Bauer et al., 2014) [1]. The mass spectrometry and the analysis dataset have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD000964. Elsevier 2015-09-04 /pmc/articles/PMC4596922/ /pubmed/26550600 http://dx.doi.org/10.1016/j.dib.2015.08.015 Text en © 2015 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Bauer, Manuel
Ahrné, Erik
Baron, Anna P.
Glatter, Timo
Fava, Luca L.
Santamaria, Anna
Nigg, Erich A.
Schmidt, Alexander
Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
title Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
title_full Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
title_fullStr Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
title_full_unstemmed Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
title_short Assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
title_sort assessment of current mass spectrometric workflows for the quantification of low abundant proteins and phosphorylation sites
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4596922/
https://www.ncbi.nlm.nih.gov/pubmed/26550600
http://dx.doi.org/10.1016/j.dib.2015.08.015
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