Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry
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 to...
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Published in | Algorithms for molecular biology Vol. 5; no. 1; p. 28 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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25.06.2010
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Abstract | 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.
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.
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. |
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AbstractList | Abstract 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. 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. 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. 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. 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. BACKGROUNDMass 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. RESULTSWe 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. CONCLUSIONSFor 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. 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. 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. 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. |
ArticleNumber | 28 |
Audience | Academic |
Author | Planatscher, Hannes Poetz, Oliver Supper, Jochen Joos, Thomas Stoll, Dieter Zell, Andreas Templin, Markus F |
AuthorAffiliation | 1 University of Tübingen, Center for Bioinformatics, Sand 1, D-72076 Tübingen, Germany 3 University of Applied Sciences, Albstadt-Sigmaringen, Anton-Günther-Str 51, D-72488 Sigmaringen, Germany 2 Natural and Medical Science Institute at the University of Tübingen, Markwiesenstraße 55, D-72770 Reutlingen, Germany 4 Current address: Genomatix Software GmbH, Bayerstr. 85a, 80335 Munich, Germany |
AuthorAffiliation_xml | – name: 2 Natural and Medical Science Institute at the University of Tübingen, Markwiesenstraße 55, D-72770 Reutlingen, Germany – name: 3 University of Applied Sciences, Albstadt-Sigmaringen, Anton-Günther-Str 51, D-72488 Sigmaringen, Germany – name: 4 Current address: Genomatix Software GmbH, Bayerstr. 85a, 80335 Munich, Germany – name: 1 University of Tübingen, Center for Bioinformatics, Sand 1, D-72076 Tübingen, Germany |
Author_xml | – sequence: 1 givenname: Hannes surname: Planatscher fullname: Planatscher, Hannes email: hannes.planatscher@uni-tuebingen.de organization: University of Tübingen, Center for Bioinformatics, Sand 1, D-72076 Tübingen, Germany. hannes.planatscher@uni-tuebingen.de – sequence: 2 givenname: Jochen surname: Supper fullname: Supper, Jochen – sequence: 3 givenname: Oliver surname: Poetz fullname: Poetz, Oliver – sequence: 4 givenname: Dieter surname: Stoll fullname: Stoll, Dieter – sequence: 5 givenname: Thomas surname: Joos fullname: Joos, Thomas – sequence: 6 givenname: Markus F surname: Templin fullname: Templin, Markus F – sequence: 7 givenname: Andreas surname: Zell fullname: Zell, Andreas |
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Snippet | Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in... Background Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck... BACKGROUNDMass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck... BACKGROUND: Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One... Abstract Background Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One... |
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StartPage | 28 |
SubjectTerms | Affinity labeling Antigenic determinants Identification and classification Mass spectrometry |
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Title | Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry |
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