ArticleNature chemical biology2025
An unbiased proteomic platform for ATE1-based arginylation profiling.
Article in Nature chemical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Reconstitution of protein arginylation pathways in bacteria for robust identification and quantification.Communications biology · 2026Article
- Trypsin exhibits exopeptidase-like activity toward N-terminal arginine that biases proteomic analyses.bioRxiv : the preprint server for biology · 2026Article
- Review
- Implementing N-terminomics and machine learning to probe Nt-arginylation.Nature communications · 2025Article
- Method Overview for Discovering ATE1 Substrates and their Arginylation Sites.Chembiochem : a European journal of chemical biology · 2025Review
- At the roots of resistance.Nature chemical biology · 2025Article
- Top-Down Proteomics for the Characterization and Quantification of Calreticulin Arginylation.Analytical chemistry · 2025Article
- Establishing a Top-Down Proteomics Platform on a Time-of-Flight Instrument with Electron-Activated Dissociation.Journal of proteome research · 2025Article
- Top-down Proteomics for the Characterization and Quantification of Calreticulin Arginylation.bioRxiv : the preprint server for biology · 2024Article
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Abstract
Protein arginylation is an essential post-translational modification catalyzed by arginyl-tRNA-protein transferase 1 (ATE1) in mammalian systems. Arginylation features a post-translational conjugation of an arginyl to a protein, making it extremely challenging to differentiate from translational arginine residues with the same mass. Here we present a general ATE1-based arginylation profiling platform for the unbiased discovery of arginylation substrates and their precise modification sites. This method integrates isotopic arginine labeling into an ATE1 assay utilizing biological lysates (ex vivo) rather than live cells, thus eliminating ribosomal bias and enabling bona fide arginylation identification. The method has been successfully applied to peptide, protein, cell, patient and mouse samples, with 235 unique arginylation sites revealed from human proteomes using 20 µg of input. Representative sites were validated and followed up for their biological functions. This global platform, applicable to various sample types, paves the way for functional studies of this difficult-to-characterize protein modification.
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