Proteome-wide structural probing of low-abundant protein interactions by crosslinking

Abstract

Proteome-wide crosslinking studies have spurred great interest as they facilitate structural probing of protein interactions in living cells and organisms. However, current studies have a bias for high-abundant proteins. In a paradigm shift, we demonstrate both experimentally and by a kinetic model that this bias is caused by the propensity of crosslinks to preferentially form on high abundant proteins and not by the inability to detect crosslinks due to limitations in current technology. We further show, by using both an in-vitro mimic of a crowded cellular environment and eukaryotic cell lysates, that parameters optimized towards a pseudo 1 st order kinetics model result in a significant 3 to 10-fold overall increase in the detection of lower-abundant proteins on a proteome-wide scale. Our study therefore explains the cause of a major limitation in current proteome-wide crosslinking studies and demonstrates how to address a larger part of the proteome by crosslinking.

A comprehensive landscape of 60S ribosome biogenesis factors

“…Here, we took a different approach and used the expected distribution of monolinks, intralinks, and interlinks in our sample to filter out false-positive PPIs: If a protein is present at high enough quantities to be detectable by XL-MS, monolinks and intraprotein crosslinks will be generated at higher rates than interlinks (monolinks are formed when only one of the two active groups of the crosslinker is able to react with a lysine side chain) (Fursch et al, 2020). The mi-filter in our workflow stipulates that only proteins identified with at least one monolink or intraprotein crosslink within our dataset can be considered a bona fide interlink representing a legitimate PPI.…”

Fast and highly efficient affinity enrichment of Azide-A-DSBSO cross-linked peptides

“…A bottleneck in cross-linking studies regarding complex systems remains, in that coverage is almost exclusively restricted to the most abundant proteins (e.g. 11,14 ). To alleviate this issue, cross-linkers with an affinity tag are used, aiming to get a deeper proteome coverage.…”