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  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Clinical Research Nurse
  • Clinician Researcher
  • Department Manager
  • Dual-education Student
  • Full Professor
  • Honorary Professor
  • Lab assistant
  • Master Student
  • Non-permanent Researcher
  • Nursing Staff
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Prize
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
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Published in Analytical chemistry - 13 Feb 2024

Nouchikian L, Fernandez-Martinez D, Renard PY, Sabot C, Duménil G, Rey M, Chamot-Rooke J

Link to Pubmed [PMID] – 38294351

Link to DOI – 10.1021/acs.analchem.3c04682

Anal Chem 2024 Feb; 96(6): 2506-2513

Cross-linking mass spectrometry (XL-MS) has become a very useful tool for studying protein complexes and interactions in living systems. It enables the investigation of many large and dynamic assemblies in their native state, providing an unbiased view of their protein interactions and restraints for integrative modeling. More researchers are turning toward trying XL-MS to probe their complexes of interest, especially in their native environments. However, due to the presence of other potentially higher abundant proteins, sufficient cross-links on a system of interest may not be reached to achieve satisfactory structural and interaction information. There are currently no rules for predicting whether XL-MS experiments are likely to work or not; in other words, if a protein complex of interest will lead to useful XL-MS data. Here, we show that a simple iBAQ (intensity-based absolute quantification) analysis performed from trypsin digest data can provide a good understanding of whether proteins of interest are abundant enough to achieve successful cross-linking data. Comparing our findings to large-scale data on diverse systems from several other groups, we show that proteins of interest should be at least in the top 20% abundance range to expect more than one cross-link found per protein. We foresee that this guideline is a good starting point for researchers who would like to use XL-MS to study their protein of interest and help ensure a successful cross-linking experiment from the beginning. Data are available via ProteomeXchange with identifier PXD045792.