Signal-noise metrics for RNA binding protein identification reveal broad spectrum protein-RNA interaction frequencies and dynamics

JohnCarlo Kristofich and Christopher V. Nicchitta ()
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JohnCarlo Kristofich: Duke University School of Medicine
Christopher V. Nicchitta: Duke University School of Medicine

Nature Communications, 2023, vol. 14, issue 1, 1-20

Abstract: Abstract Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven analytically challenging and prone to error. Here we report a method termed LEAP-RBP (Liquid-Emulsion-Assisted-Purification of RNA-Bound Protein) for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. In this work, the utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.

Date: 2023
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DOI: 10.1038/s41467-023-41284-9

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