A genome-wide approach for identification and characterisation of metabolite-inducible systems

Erik K. R. Hanko, Ana C. Paiva, Magdalena Jonczyk, Matthew Abbott, Nigel P. Minton and Naglis Malys ()
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Erik K. R. Hanko: The University of Nottingham
Ana C. Paiva: The University of Nottingham
Magdalena Jonczyk: The University of Nottingham
Matthew Abbott: The University of Nottingham
Nigel P. Minton: The University of Nottingham
Naglis Malys: The University of Nottingham

Nature Communications, 2020, vol. 11, issue 1, 1-14

Abstract: Abstract Inducible gene expression systems are vital tools for the advancement of synthetic biology. Their application as genetically encoded biosensors has the potential to contribute to diagnostics and to revolutionise the field of microbial cell factory development. Currently, the number of compounds of biological interest by far exceeds the number of available biosensors. Here, we address this limitation by developing a generic genome-wide approach to identify transcription factor-based inducible gene expression systems. We construct and validate 15 functional biosensors, provide a characterisation workflow to facilitate forward engineering efforts, exemplify their broad-host-range applicability, and demonstrate their utility in enzyme screening. Previously uncharacterised interactions between sensors and compounds of biological relevance are identified by employing the largest reported library of metabolite-responsive biosensors in an automated high-throughput screen. With the rapidly growing genomic data these innovative capabilities offer a platform to vastly increase the number of biologically detectable molecules.

Date: 2020
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DOI: 10.1038/s41467-020-14941-6

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