Cargando…
Automated Selected Reaction Monitoring Software for Accurate Label-Free Protein Quantification
[Image: see text] Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted a...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2012
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3426189/ https://www.ncbi.nlm.nih.gov/pubmed/22658081 http://dx.doi.org/10.1021/pr300256x |
_version_ | 1782241479687667712 |
---|---|
author | Teleman, Johan Karlsson, Christofer Waldemarson, Sofia Hansson, Karin James, Peter Malmström, Johan Levander, Fredrik |
author_facet | Teleman, Johan Karlsson, Christofer Waldemarson, Sofia Hansson, Karin James, Peter Malmström, Johan Levander, Fredrik |
author_sort | Teleman, Johan |
collection | PubMed |
description | [Image: see text] Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5–19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology. |
format | Online Article Text |
id | pubmed-3426189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | American Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-34261892012-08-24 Automated Selected Reaction Monitoring Software for Accurate Label-Free Protein Quantification Teleman, Johan Karlsson, Christofer Waldemarson, Sofia Hansson, Karin James, Peter Malmström, Johan Levander, Fredrik J Proteome Res [Image: see text] Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5–19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology. American Chemical Society 2012-06-04 2012-07-06 /pmc/articles/PMC3426189/ /pubmed/22658081 http://dx.doi.org/10.1021/pr300256x Text en Copyright © 2012 American Chemical Society http://pubs.acs.org This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org. |
spellingShingle | Teleman, Johan Karlsson, Christofer Waldemarson, Sofia Hansson, Karin James, Peter Malmström, Johan Levander, Fredrik Automated Selected Reaction Monitoring Software for Accurate Label-Free Protein Quantification |
title | Automated Selected Reaction
Monitoring Software for Accurate Label-Free Protein Quantification |
title_full | Automated Selected Reaction
Monitoring Software for Accurate Label-Free Protein Quantification |
title_fullStr | Automated Selected Reaction
Monitoring Software for Accurate Label-Free Protein Quantification |
title_full_unstemmed | Automated Selected Reaction
Monitoring Software for Accurate Label-Free Protein Quantification |
title_short | Automated Selected Reaction
Monitoring Software for Accurate Label-Free Protein Quantification |
title_sort | automated selected reaction
monitoring software for accurate label-free protein quantification |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3426189/ https://www.ncbi.nlm.nih.gov/pubmed/22658081 http://dx.doi.org/10.1021/pr300256x |
work_keys_str_mv | AT telemanjohan automatedselectedreactionmonitoringsoftwareforaccuratelabelfreeproteinquantification AT karlssonchristofer automatedselectedreactionmonitoringsoftwareforaccuratelabelfreeproteinquantification AT waldemarsonsofia automatedselectedreactionmonitoringsoftwareforaccuratelabelfreeproteinquantification AT hanssonkarin automatedselectedreactionmonitoringsoftwareforaccuratelabelfreeproteinquantification AT jamespeter automatedselectedreactionmonitoringsoftwareforaccuratelabelfreeproteinquantification AT malmstromjohan automatedselectedreactionmonitoringsoftwareforaccuratelabelfreeproteinquantification AT levanderfredrik automatedselectedreactionmonitoringsoftwareforaccuratelabelfreeproteinquantification |