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Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data
Protein turnover is a well-controlled process in which polypeptides are constantly being degraded and subsequently replaced with newly synthesized copies. Extraction of composite spectral envelopes from complex LC/MS shotgun proteomics data can be a challenging task, due to the inherent complexity o...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3988089/ https://www.ncbi.nlm.nih.gov/pubmed/24736476 http://dx.doi.org/10.1371/journal.pone.0094692 |
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author | Lyon, David Castillejo, Maria Angeles Staudinger, Christiana Weckwerth, Wolfram Wienkoop, Stefanie Egelhofer, Volker |
author_facet | Lyon, David Castillejo, Maria Angeles Staudinger, Christiana Weckwerth, Wolfram Wienkoop, Stefanie Egelhofer, Volker |
author_sort | Lyon, David |
collection | PubMed |
description | Protein turnover is a well-controlled process in which polypeptides are constantly being degraded and subsequently replaced with newly synthesized copies. Extraction of composite spectral envelopes from complex LC/MS shotgun proteomics data can be a challenging task, due to the inherent complexity of biological samples. With partial metabolic labeling experiments this complexity increases as a result of the emergence of additional isotopic peaks. Automated spectral extraction and subsequent protein turnover calculations enable the analysis of gigabytes of data within minutes, a prerequisite for systems biology high throughput studies. Here we present a fully automated method for protein turnover calculations from shotgun proteomics data. The approach enables the analysis of complex shotgun LC/MS (15)N partial metabolic labeling experiments. Spectral envelopes of 1419 peptides can be extracted within an hour. The method quantifies turnover by calculating the Relative Isotope Abundance (RIA), which is defined as the ratio between the intensity sum of all heavy ((15)N) to the intensity sum of all light ((14)N) and heavy peaks. To facilitate this process, we have developed a computer program based on our method, which is freely available to download at http://promex.pph.univie.ac.at/protover. |
format | Online Article Text |
id | pubmed-3988089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39880892014-04-21 Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data Lyon, David Castillejo, Maria Angeles Staudinger, Christiana Weckwerth, Wolfram Wienkoop, Stefanie Egelhofer, Volker PLoS One Research Article Protein turnover is a well-controlled process in which polypeptides are constantly being degraded and subsequently replaced with newly synthesized copies. Extraction of composite spectral envelopes from complex LC/MS shotgun proteomics data can be a challenging task, due to the inherent complexity of biological samples. With partial metabolic labeling experiments this complexity increases as a result of the emergence of additional isotopic peaks. Automated spectral extraction and subsequent protein turnover calculations enable the analysis of gigabytes of data within minutes, a prerequisite for systems biology high throughput studies. Here we present a fully automated method for protein turnover calculations from shotgun proteomics data. The approach enables the analysis of complex shotgun LC/MS (15)N partial metabolic labeling experiments. Spectral envelopes of 1419 peptides can be extracted within an hour. The method quantifies turnover by calculating the Relative Isotope Abundance (RIA), which is defined as the ratio between the intensity sum of all heavy ((15)N) to the intensity sum of all light ((14)N) and heavy peaks. To facilitate this process, we have developed a computer program based on our method, which is freely available to download at http://promex.pph.univie.ac.at/protover. Public Library of Science 2014-04-15 /pmc/articles/PMC3988089/ /pubmed/24736476 http://dx.doi.org/10.1371/journal.pone.0094692 Text en © 2014 Lyon et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Lyon, David Castillejo, Maria Angeles Staudinger, Christiana Weckwerth, Wolfram Wienkoop, Stefanie Egelhofer, Volker Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data |
title | Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data |
title_full | Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data |
title_fullStr | Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data |
title_full_unstemmed | Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data |
title_short | Automated Protein Turnover Calculations from (15)N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data |
title_sort | automated protein turnover calculations from (15)n partial metabolic labeling lc/ms shotgun proteomics data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3988089/ https://www.ncbi.nlm.nih.gov/pubmed/24736476 http://dx.doi.org/10.1371/journal.pone.0094692 |
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