PLoS ONE (Jan 2016)

A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.

  • Juan D Chavez,
  • Jimmy K Eng,
  • Devin K Schweppe,
  • Michelle Cilia,
  • Keith Rivera,
  • Xuefei Zhong,
  • Xia Wu,
  • Terrence Allen,
  • Moshe Khurgel,
  • Akhilesh Kumar,
  • Athanasios Lampropoulos,
  • Mårten Larsson,
  • Shuvadeep Maity,
  • Yaroslav Morozov,
  • Wimal Pathmasiri,
  • Mathew Perez-Neut,
  • Coriness Pineyro-Ruiz,
  • Elizabeth Polina,
  • Stephanie Post,
  • Mark Rider,
  • Dorota Tokmina-Roszyk,
  • Katherine Tyson,
  • Debora Vieira Parrine Sant'Ana,
  • James E Bruce

DOI
https://doi.org/10.1371/journal.pone.0167547
Journal volume & issue
Vol. 11, no. 12
p. e0167547

Abstract

Read online

Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.