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Bacterial RNA motif in the 5′ UTR of rpsF interacts with an S6:S18 complex

Approximately half the transcripts encoding ribosomal proteins in Escherichia coli include a structured RNA motif that interacts with a specific ribosomal protein to inhibit gene expression, thus allowing stoichiometric production of ribosome components. However, many of these RNA structures are not...

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Detalles Bibliográficos
Autores principales: Fu, Yang, Deiorio-Haggar, Kaila, Soo, Mark W., Meyer, Michelle M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3895269/
https://www.ncbi.nlm.nih.gov/pubmed/24310371
http://dx.doi.org/10.1261/rna.041285.113
Descripción
Sumario:Approximately half the transcripts encoding ribosomal proteins in Escherichia coli include a structured RNA motif that interacts with a specific ribosomal protein to inhibit gene expression, thus allowing stoichiometric production of ribosome components. However, many of these RNA structures are not widely distributed across bacterial phyla. It is increasingly common for RNA motifs associated with ribosomal protein genes to be identified using comparative genomic methods, yet these are rarely experimentally validated. In this work, we characterize one such motif that precedes operons containing rpsF and rpsR, which encode ribosomal proteins S6 and S18. This RNA structure is widely distributed across many phyla of bacteria despite differences within the downstream operon, and examples are present in both E. coli and Bacillus subtilis. We demonstrate a direct interaction between an example of the RNA from B. subtilis and an S6:S18 complex using in vitro binding assays, verify our predicted secondary structure, and identify a putative protein-binding site. The proposed binding site bears a strong resemblance to the S18 binding site within the 16S rRNA, suggesting molecular mimicry. This interaction is a valuable addition to the canon of ribosomal protein mRNA interactions. This work shows how experimental verification translates computational results into concrete knowledge of biological systems.