Optimization of a genetic assay for detection of expanded RNA-Hfq interactions



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Non-coding small RNAs (sRNAs) contribute to bacterial biofilm formation, antibiotic resistance, pathogenesis, and virulence by regulating gene expression. However, there is much we do not understand about their molecular mechanisms, which often involve facilitation by a chaperone protein. Hfq is the best-studied bacterial RNA chaperone protein and has become the paradigmatic example for how RNA-binding proteins facilitate sRNA-based gene regulation. An in vivo bacterial three-hybrid assay for genetic detection of RNA-protein interactions has previously been established using interactions using Escherichia coli Hfq and its sRNA substrates. In order to broaden the utility of the assay to provide a deep understanding of varied RNA-protein interactions, I have focused on expanding the B3H assay to detect mRNA-Hfq interactions and on understanding the energetic implications of the data provided by the assay. In this work, I demonstrate that the B3H assay is capable of detecting Hfq’s interactions with sequence elements typical for mRNA-Hfq binding. Expansion from minimal binding elements to native sequences has involved exploration of the impacts of translation and turnover via mRNA surveillance pathways. While these factors complicate the detection of interactions with 5’ UTRs and coding sequences, I have refined the B3H assay to detect the interaction between Hfq and its mRNA target sodB , demonstrating the potential of the assay to detect a wider variety of RNA-protein interactions. Just as it is useful to detect a wide variety of interactions using this method, it is also imperative to understand what the assay’s data truly indicates about these interactions. I have therefore compared B3H and in vitro binding data for a set of Hfq-interacting RNAs and Hfq variants to work toward a model for the relationship between B3H data and binding energetics. My results suggest that high B3H signal typically reflects strong binding affinity, and that B3H optimization efforts have resulted in data that is increasingly consistent with binding energetics. The work I present here represents significant steps forward in both the assay’s detection capacity and our understanding of that capacity, developing it as a more broadly useful and informative method for studying RNA-protein interactions.



RNA, Hfq, assay optimization, molecular genetics, RNA-protein interactions