Browsing by Subject "In vivo interaction detection"
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Item Developing novel tools to characterize regulatory RNA-protein networks in vivo(2016-12-06) Gelderman, Grant Michael; Contreras, Lydia M.; Alper, Hal; Georgiou, George; Ellington, Andrew; Payne, ShelleyThis work focuses on the design and implementation of tools to characterize a regulatory RNA-protein network in vivo. As such, this work developed techniques to detect RNA-protein interactions, characterize repression of translation, and model the RNA-protein interaction as a means of target identification. We specifically focused on the RNA-protein interactions of the post transcriptional regulatory protein, CsrA, of the Carbon storage regulator system. A fluorescence based technique, named Tri molecular Fluorescent Complementation (TriFC), was developed to detect RNA-protein interactions in vivo and demonstrated using CsrA and the sRNA, CsrB. This tool showed sensitivity to mutations in CsrA that affect the affinity of the interaction. A modified version of this tool was later implemented to characterize mRNA-CsrA interactions as a means of identifying targets of CsrA. A translational assay was developed to detect the effect that CsrA has on the translational activity of mRNAs. This assay tested 241 different mRNA targets and identified 94 mRNAs that displayed inhibition by CsrA. Using modifications to the TriFC system, 32 mRNAs were observed directly interacting with CsrA. The evidence from the TriFC system and the translational assay revealed 19 previously uncharacterized mRNAs as targets of CsrA regulation, with the most important of these genes being the sigma factor rpoS. Lastly, a model was developed using the primary principles of CsrA interactions that predicts the affinity an mRNA sequence has for CsrA and the effect that CsrA would have on the translational activity of the mRNA. Experimental data established that mRNA targets with a sufficiently a high prediction of CsrA affinity are very likely to be true CsrA targets. The predictions for the binding site affinity were evaluated using a novel in vivo titration technique, and it was demonstrated that the affinity predictions have physical significance in describing the interaction of CsrA and the RNA. With this model, it will be possible to evaluate the genome of E. coli to predict CsrA’s regulatory effect on mRNA targets. In total, this work demonstrated generalizable tools to characterize RNA-protein interactions, and the specific focus on the CsrA protein makes these tools immediately useful for the characterization of this significant regulatory system.