henhaobio
Sign in

bioRxivBiochemistry

A highly sensitive protein-RNA cross-linking mass spectrometry workflow with enhanced structural modelling potential

C. P. Sarnowski, A. Knörlein, T. de Vries, M. Götze, I. Beusch, R. Aebersold, F. H.- T. Allain, J. Hall, A. Leitner

PDFDOIPreprint

Abstract

Protein-RNA interactions underpin many critical biological processes, demanding the development of technologies to precisely characterize their nature and functions. Many such technologies depend upon cross-linking under mild irradiation conditions to stabilize contacts between amino acids and nucleobases; for example, the cross-linking of stable isotope labelled RNA coupled to mass spectrometry (CLIR-MS) method. A deeper understanding of the CLIR-MS workflow is required to maximize its impact for structural biology, particularly addressing the low abundance of cross-linking products and the information content of spatial/geometric restraints reflected by a cross-link. Here, we present a vastly improved CLIR-MS pipeline that features enhanced sample preparation, data acquisition and interpretation. These advances significantly increase the number of detected cross-link products per sample. We demonstrate that the procedure is robust against variation of key experimental parameters, including irradiation energy and temperature. Using this improved protocol on four protein-RNA complexes representing canonical and non-canonical RNA-binding domains, we propose for the first time the distances encoded by protein-RNA cross-links, enabling their use as structural restraints. We also compared the cross-linking of canonical RNA with 4-thiouracil-labeled counterparts, showing slight, but noticeable differences. The improved understanding of protein-RNA cross-links refines the structural interpretation of complexes and facilitates the adoption of the method in integrative/hybrid structural biology.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSmok '26Welp '25Birklbauer '26Sha '25Feng '22Lee '25
79% semantic matchBiophysics
Izabela Smok, Aurélie Zbinden, Johannes Osterroth+5 more·bioRxiv·Oct 19, 2026