Cargando…

Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry

Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisit...

Descripción completa

Detalles Bibliográficos
Autores principales: Müller, Fränze, Kolbowski, Lars, Bernhardt, Oliver M., Reiter, Lukas, Rappsilber, Juri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Biochemistry and Molecular Biology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442367/
https://www.ncbi.nlm.nih.gov/pubmed/30651306
http://dx.doi.org/10.1074/mcp.TIR118.001276
_version_ 1783407696526966784
author Müller, Fränze
Kolbowski, Lars
Bernhardt, Oliver M.
Reiter, Lukas
Rappsilber, Juri
author_facet Müller, Fränze
Kolbowski, Lars
Bernhardt, Oliver M.
Reiter, Lukas
Rappsilber, Juri
author_sort Müller, Fränze
collection PubMed
description Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisition (DDA) and increased throughput over targeted methods. Therefore, here we introduce DIA to QCLMS by extending a widely used DIA software, Spectronaut, to also accommodate cross-link data. A mixture of seven proteins cross-linked with bis[sulfosuccinimidyl] suberate (BS(3)) was used to evaluate this workflow. Out of the 414 identified unique residue pairs, 292 (70%) were quantifiable across triplicates with a coefficient of variation (CV) of 10%, with manual correction of peak selection and boundaries for PSMs in the lower quartile of individual CV values. This compares favorably to DDA where we quantified cross-links across triplicates with a CV of 66%, for a single protein. We found DIA-QCLMS to be capable of detecting changing abundances of cross-linked peptides in complex mixtures, despite the ratio compression encountered when increasing sample complexity through the addition of E. coli cell lysate as matrix. In conclusion, the DIA software Spectronaut can now be used in cross-linking and DIA is indeed able to improve QCLMS.
format Online
Article
Text
id pubmed-6442367
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher The American Society for Biochemistry and Molecular Biology
record_format MEDLINE/PubMed
spelling pubmed-64423672019-04-02 Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry Müller, Fränze Kolbowski, Lars Bernhardt, Oliver M. Reiter, Lukas Rappsilber, Juri Mol Cell Proteomics Technological Innovation and Resources Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisition (DDA) and increased throughput over targeted methods. Therefore, here we introduce DIA to QCLMS by extending a widely used DIA software, Spectronaut, to also accommodate cross-link data. A mixture of seven proteins cross-linked with bis[sulfosuccinimidyl] suberate (BS(3)) was used to evaluate this workflow. Out of the 414 identified unique residue pairs, 292 (70%) were quantifiable across triplicates with a coefficient of variation (CV) of 10%, with manual correction of peak selection and boundaries for PSMs in the lower quartile of individual CV values. This compares favorably to DDA where we quantified cross-links across triplicates with a CV of 66%, for a single protein. We found DIA-QCLMS to be capable of detecting changing abundances of cross-linked peptides in complex mixtures, despite the ratio compression encountered when increasing sample complexity through the addition of E. coli cell lysate as matrix. In conclusion, the DIA software Spectronaut can now be used in cross-linking and DIA is indeed able to improve QCLMS. The American Society for Biochemistry and Molecular Biology 2019-04 2019-01-16 /pmc/articles/PMC6442367/ /pubmed/30651306 http://dx.doi.org/10.1074/mcp.TIR118.001276 Text en © 2019 Müller et al. Published by The American Society for Biochemistry and Molecular Biology, Inc. Author's Choice—Final version open access under the terms of the Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0) .
spellingShingle Technological Innovation and Resources
Müller, Fränze
Kolbowski, Lars
Bernhardt, Oliver M.
Reiter, Lukas
Rappsilber, Juri
Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry
title Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry
title_full Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry
title_fullStr Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry
title_full_unstemmed Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry
title_short Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry
title_sort data-independent acquisition improves quantitative cross-linking mass spectrometry
topic Technological Innovation and Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442367/
https://www.ncbi.nlm.nih.gov/pubmed/30651306
http://dx.doi.org/10.1074/mcp.TIR118.001276
work_keys_str_mv AT mullerfranze dataindependentacquisitionimprovesquantitativecrosslinkingmassspectrometry
AT kolbowskilars dataindependentacquisitionimprovesquantitativecrosslinkingmassspectrometry
AT bernhardtoliverm dataindependentacquisitionimprovesquantitativecrosslinkingmassspectrometry
AT reiterlukas dataindependentacquisitionimprovesquantitativecrosslinkingmassspectrometry
AT rappsilberjuri dataindependentacquisitionimprovesquantitativecrosslinkingmassspectrometry