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Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry
BACKGROUND: Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples,...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2911453/ https://www.ncbi.nlm.nih.gov/pubmed/20579369 http://dx.doi.org/10.1186/1748-7188-5-28 |
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author | Planatscher, Hannes Supper, Jochen Poetz, Oliver Stoll, Dieter Joos, Thomas Templin, Markus F Zell, Andreas |
author_facet | Planatscher, Hannes Supper, Jochen Poetz, Oliver Stoll, Dieter Joos, Thomas Templin, Markus F Zell, Andreas |
author_sort | Planatscher, Hannes |
collection | PubMed |
description | BACKGROUND: Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency. RESULTS: We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties. CONCLUSIONS: For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics. |
format | Text |
id | pubmed-2911453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29114532010-07-29 Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry Planatscher, Hannes Supper, Jochen Poetz, Oliver Stoll, Dieter Joos, Thomas Templin, Markus F Zell, Andreas Algorithms Mol Biol Research BACKGROUND: Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency. RESULTS: We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties. CONCLUSIONS: For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics. BioMed Central 2010-06-25 /pmc/articles/PMC2911453/ /pubmed/20579369 http://dx.doi.org/10.1186/1748-7188-5-28 Text en Copyright ©2010 Planatscher et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Planatscher, Hannes Supper, Jochen Poetz, Oliver Stoll, Dieter Joos, Thomas Templin, Markus F Zell, Andreas Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry |
title | Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry |
title_full | Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry |
title_fullStr | Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry |
title_full_unstemmed | Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry |
title_short | Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry |
title_sort | optimal selection of epitopes for txp-immunoaffinity mass spectrometry |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2911453/ https://www.ncbi.nlm.nih.gov/pubmed/20579369 http://dx.doi.org/10.1186/1748-7188-5-28 |
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