Nucleotide-amino acid π-stacking interactions initiate photo cross-linking in RNA-protein complexes

Anna Knörlein, Chris P. Sarnowski, Tebbe Vries, Moritz Stoltz, Michael Götze, Ruedi Aebersold, Frédéric H.-T. Allain, Alexander Leitner and Jonathan Hall ()
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Anna Knörlein: Institute of Pharmaceutical Sciences, ETH Zurich
Chris P. Sarnowski: Institute of Molecular Systems Biology, ETH Zurich
Tebbe Vries: Institute of Biochemistry, ETH Zurich
Moritz Stoltz: Institute of Pharmaceutical Sciences, ETH Zurich
Michael Götze: Institute of Molecular Systems Biology, ETH Zurich
Ruedi Aebersold: Institute of Molecular Systems Biology, ETH Zurich
Frédéric H.-T. Allain: Institute of Biochemistry, ETH Zurich
Alexander Leitner: Institute of Molecular Systems Biology, ETH Zurich
Jonathan Hall: Institute of Pharmaceutical Sciences, ETH Zurich

Nature Communications, 2022, vol. 13, issue 1, 1-12

Abstract: Abstract Photo-induced cross-linking is a mainstay technique to characterize RNA-protein interactions. However, UV-induced cross-linking between RNA and proteins at “zero-distance” is poorly understood. Here, we investigate cross-linking of the RBFOX alternative splicing factor with its hepta-ribonucleotide binding element as a model system. We examine the influence of nucleobase, nucleotide position and amino acid composition using CLIR-MS technology (crosslinking-of-isotope-labelled-RNA-and-tandem-mass-spectrometry), that locates cross-links on RNA and protein with site-specific resolution. Surprisingly, cross-linking occurs only at nucleotides that are π-stacked to phenylalanines. Notably, this π-stacking interaction is also necessary for the amino-acids flanking phenylalanines to partake in UV-cross-linking. We confirmed these observations in several published datasets where cross-linking sites could be mapped to a high resolution structure. We hypothesize that π-stacking to aromatic amino acids activates cross-linking in RNA-protein complexes, whereafter nucleotide and peptide radicals recombine. These findings will facilitate interpretation of cross-linking data from structural studies and from genome-wide datasets generated using CLIP (cross-linking-and-immunoprecipitation) methods.

Date: 2022
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DOI: 10.1038/s41467-022-30284-w

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