Publications - Published papers

Please find below publications of our group. Currently, we list 563 papers. Some of the publications are in collaboration with the group of Sonja Prohaska and are also listed in the publication list for her individual group. Access to published papers (access) is restricted to our local network and chosen collaborators. If you have problems accessing electronic information, please let us know:

©NOTICE: All papers are copyrighted by the authors; If you would like to use all or a portion of any paper, please contact the author.

Beyond Plug and Pray: Context Sensitivity and in silico Design of Artificial Neomycin Riboswitches

Günzel, Christian and Kühnl, Felix and Arnold, Katharina and Findeiß, Sven and Weinberg, Christina E and Stadler, Peter F and Mörl, Mario


PREPRINT 20-005: [ PDF ]  [ Supplement ]
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Status: Published

RNA Biology


Gene regulation in prokaryotes often depends on RNA elements such as riboswitches or RNA thermometers located in the 5′ untranslated region of mRNA. Rearrangements of the RNA structure in response, e.g., to the binding of small molecules or ions control translational initiation or premature termination of transcription and thus mRNA expression. Such structural responses are amenable to computational modelling, making it possible to rationally design synthetic riboswitches for a given aptamer. Starting from an artificial aptamer, we construct the first synthetic transcriptional riboswitches that respond to the antibiotic neomycin. We show that the switching behaviour in vivo critically depends not only on the sequence of the riboswitch itself, but also on its sequence context. We therefore developed in silico methods to predict the impact of the context, making it possible to adapt the design and to rescue non-functional riboswitches. We furthermore analyse the influence of 5′ hairpins with varying stability on neomycin riboswitch activity. Our data highlight the limitations of a simple plug-and-play approach in the design of complex genetic circuits and demonstrate that detailed computational models significantly simplify, improve, and automate the design of transcriptional circuits. Our design software is available under a free licence on GitHub (