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Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()

Dynamic proteins and multi-protein complexes govern most biological processes. Cross-linking/mass spectrometry (CLMS) is increasingly successful in providing residue-resolution data on static proteinaceous structures. Here we investigate the technical feasibility of recording dynamic processes using...

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Detalles Bibliográficos
Autores principales: Fischer, Lutz, Chen, Zhuo Angel, Rappsilber, Juri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3714596/
https://www.ncbi.nlm.nih.gov/pubmed/23541715
http://dx.doi.org/10.1016/j.jprot.2013.03.005
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author Fischer, Lutz
Chen, Zhuo Angel
Rappsilber, Juri
author_facet Fischer, Lutz
Chen, Zhuo Angel
Rappsilber, Juri
author_sort Fischer, Lutz
collection PubMed
description Dynamic proteins and multi-protein complexes govern most biological processes. Cross-linking/mass spectrometry (CLMS) is increasingly successful in providing residue-resolution data on static proteinaceous structures. Here we investigate the technical feasibility of recording dynamic processes using isotope-labelling for quantitation. We cross-linked human serum albumin (HSA) with the readily available cross-linker BS3-d0/4 in different heavy/light ratios. We found two limitations. First, isotope labelling reduced the number of identified cross-links. This is in line with similar findings when identifying proteins. Second, standard quantitative proteomics software was not suitable for work with cross-linking. To ameliorate this we wrote a basic open source application, XiQ. Using XiQ we could establish that quantitative CLMS was technically feasible. BIOLOGICAL SIGNIFICANCE: Cross-linking/mass spectrometry (CLMS) has become a powerful tool for providing residue-resolution data on static proteinaceous structures. Adding quantitation to CLMS will extend its ability of recording dynamic processes. Here we introduce a cross-linking specific quantitation strategy by using isotope labelled cross-linkers. Using a model system, we demonstrate the principle and feasibility of quantifying cross-linking data and discuss challenges one may encounter while doing so. We then provide a basic open source application, XiQ, to carry out automated quantitation of CLMS data. Our work lays the foundations of studying the molecular details of biological processes at greater ease than this could be done so far. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012].
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spelling pubmed-37145962013-08-02 Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers() Fischer, Lutz Chen, Zhuo Angel Rappsilber, Juri J Proteomics Article Dynamic proteins and multi-protein complexes govern most biological processes. Cross-linking/mass spectrometry (CLMS) is increasingly successful in providing residue-resolution data on static proteinaceous structures. Here we investigate the technical feasibility of recording dynamic processes using isotope-labelling for quantitation. We cross-linked human serum albumin (HSA) with the readily available cross-linker BS3-d0/4 in different heavy/light ratios. We found two limitations. First, isotope labelling reduced the number of identified cross-links. This is in line with similar findings when identifying proteins. Second, standard quantitative proteomics software was not suitable for work with cross-linking. To ameliorate this we wrote a basic open source application, XiQ. Using XiQ we could establish that quantitative CLMS was technically feasible. BIOLOGICAL SIGNIFICANCE: Cross-linking/mass spectrometry (CLMS) has become a powerful tool for providing residue-resolution data on static proteinaceous structures. Adding quantitation to CLMS will extend its ability of recording dynamic processes. Here we introduce a cross-linking specific quantitation strategy by using isotope labelled cross-linkers. Using a model system, we demonstrate the principle and feasibility of quantifying cross-linking data and discuss challenges one may encounter while doing so. We then provide a basic open source application, XiQ, to carry out automated quantitation of CLMS data. Our work lays the foundations of studying the molecular details of biological processes at greater ease than this could be done so far. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012]. Elsevier 2013-08-02 /pmc/articles/PMC3714596/ /pubmed/23541715 http://dx.doi.org/10.1016/j.jprot.2013.03.005 Text en © 2013 Elsevier B.V. https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license
spellingShingle Article
Fischer, Lutz
Chen, Zhuo Angel
Rappsilber, Juri
Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()
title Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()
title_full Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()
title_fullStr Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()
title_full_unstemmed Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()
title_short Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()
title_sort quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3714596/
https://www.ncbi.nlm.nih.gov/pubmed/23541715
http://dx.doi.org/10.1016/j.jprot.2013.03.005
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