Quantitative cross-linking/mass spectrometry using isotope-labelled cross-linkers ^☆

Abstract

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].

Graphical abstract

Highlights

• •

  Quantitative cross-linking using isotope labelling is technically feasible

• •

  Commercial cross-linker BS3-d0/4 is suitable for quantitative cross-linking

• •

  XiQ, an open source script to extract quantitative data from raw files

• •

  Cross-link reference data set to test identification and quantitation software

• •

  Isotope labelling reduced the number of identified cross-links