Do Not Waste TimeEnsure Success in Your Cross-Linking Mass Spectrometry Experiments before You Begin

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.