Quantitative RNA pseudouridine landscape reveals dynamic modification patterns and evolutionary conservation across bacterial species

作者：Letong Xu, Shenghai Shen, Yizhou Zhang, Zhihao Guo, Beifang Lu, Jiadai Huang, Runsheng Li, Yitong Shen, Li-Sheng Zhang, Xin Deng · 发表于：eLife · 年份：2026 · DOI：10.7554/elife.107545.3 · 被引用次数：2 · 研究领域：RNA modifications and cancer、Genomics and Phylogenetic Studies、RNA and protein synthesis mechanisms

Abstract Pseudouridine (Ψ) modifications are the most abundant RNA modifications; however, their distribution and functional significance in bacteria remain largely unexplored compared to eukaryotic systems. In this study, we present the first transcriptome-wide and quantitative mapping of Ψ modifications across five diverse bacterial species ( Bacillus cereus, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa , and Pseudomonas syringae ) at single-base resolution, utilizing the optimized BID-seq method for bacterial RNA. Our analysis revealed growth phase-dependent dynamics of pseudouridylation in bacterial tRNA and mRNA, particularly in genes enriched in core metabolic pathways. Comparative analysis demonstrated evolutionarily conserved features of Ψ modifications, such as dominant motif contexts, Ψ clustering within operons, etc. Functional analysis indicated Ψ modifications influence bacterial mRNA stability, translation, and interactions with specific RNA-binding proteins (RBPs) in response to changing cellular demands during growth phase transitions. The integrated computational analysis on local RNA architecture was conducted to elucidate the structure-dependent Ψ modifications in bacterial RNA. Furthermore, we developed an integrated deep learning framework, combining Transformer-GNN-based neural networks (pseU_NN) to capture both RNA sequence and structural features for effective prediction of Ψ-modified sites. Overall, our study provides valuable insig...