Edinburgh Research Explorer

Quantitative cross-linking/mass spectrometry using isotope-labeled cross-linkers and MaxQuant: QCLMS by isotope labeling and MaxQuant

Research output: Contribution to journalArticle

Related Edinburgh Organisations

Open Access permissions



Original languageEnglish
Pages (from-to)2769-2778
Number of pages10
JournalMolecular and Cellular Proteomics
Issue number8
Early online date14 Jun 2016
Publication statusPublished - 1 Aug 2016


The conceptually simple step from cross-linking/mass spectrometry (CLMS) to quantitative cross-linking/mass spectrometry (QCLMS) is compounded by technical challenges. Currently, quantitative proteomics software is tightly integrated with the protein identification workflow. This prevents automatically quantifying other m/z features in a targeted manner including those associated with cross-linked peptides. Here we present a new release of MaxQuant that permits starting the quantification process from an m/z feature list. Comparing the automated quantification to a carefully manually curated test set of cross-linked peptides obtained by cross-linking C3 and C3b with BS3 and isotope-labeled BS3-d4 revealed a number of observations: 1) Fully automated process using MaxQuant can quantify cross-links in our reference dataset with 68% recall rate and 88% accuracy. 2) Hidden quantification errors can be converted into exposed failures by label-swap replica, which makes label-swap replica an essential part of QCLMS. 3) Cross-links that failed during automated quantification can be recovered by semi-automated re-quantification. The integrated workflow of MaxQuant and semiautomated assessment provides the maximum of quantified cross-links. In contrast, work on larger data sets or by less experienced users will benefit from full automation in MaxQuant.

Download statistics

No data available

ID: 26886729