PDF(Pubmed)
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.
摘要：
平移控制在所有生活中都很重要，但准确量化仍然是一个挑战。当核糖体将信使（m）RNA翻译成蛋白质时，它们串联连接到mRNA上，形成聚(ribo)体，并且可以共同定位。这里,我们对mRNA上的新型共定位核糖体复合物进行了计算建模，并使用基于体内快速交联的增强翻译复合物谱测序（eTCP-seq）对其进行了鉴定。我们在非随机延伸区域之外检测到了长的基因组足迹，并表明这些足迹与翻译起始和蛋白质生物合成速率有关。我们将失语症和其他翻译复合体的足迹进行人工智能(AI)分析，并构建一个新的,翻译的准确和自归一化度量，称为随机翻译效率(STE)。然后我们应用STE来研究经历葡萄糖消耗的酵母中mRNA翻译的快速变化。重要的是,我们证明，远远超出了标记伸长失速，共同定位核糖体的足迹提供了对翻译机制的丰富见解，多体动力学和拓扑。在给定条件下，STEAI通过绝对翻译率对细胞mRNA进行排名，可以帮助识别其控制元件，并将促进下一代合成生物学设计和基于mRNA的疗法的开发。
