Optimization of a genetic assay for detection of expanded RNA-Hfq interactions
Date
2020-06-08
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Abstract
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.
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Keywords
RNA, Hfq, assay optimization, molecular genetics, RNA-protein interactions