Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress

Horvath, Attila and Janapala, Yoshika and Woodward, Katrina and Mahmud, Shafi and Cleynen, Alice and Gardiner, Elizabeth E and Hannan, Ross D and Eyras, Eduardo and Preiss, Thomas and Shirokikh, Nikolay E (2024) Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress. Nucleic Acids Research, 52 (13). pp.7925-7946. ISSN 0305-1048

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Link to published document: http://doi.org/10.1093/nar/gkae365

Abstract

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

Item Type: Article
Subjects: R Medicine > R Medicine (General)
Depositing User: Repository Administrator
Date Deposited: 23 Dec 2024 03:45
Last Modified: 23 Dec 2024 03:45
URI: https://eprints.victorchang.edu.au/id/eprint/1558

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