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

Erik K R Hanko,Nigel P Minton,Naglis Malys,Matthew Abbott,Magdalena Jonczyk,Ana C Paiva

doi:10.1038/s41467-020-14941-6

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.

Highlights

Inducible gene expression systems are vital tools for the advancement of synthetic biology
In the systems that control gene clusters associated with metabolism and catabolism in particular, the level of gene expression from the inducible promoter is often controlled by the transcriptional regulators (TRs) that responds to small effector molecules, referred to as ligands
Once a complete list of annotated genes belonging to one species is retrieved from GenBank[21], including information on coding strand orientation and protein function, it is screened for TRs that are oriented in the opposite direction of operons involved in metabolism of any or specific ligands

Summary

Introduction

Inducible gene expression systems are vital tools for the advancement of synthetic biology. The number of compounds of biological interest by far exceeds the number of available biosensors We address this limitation by developing a generic genome-wide approach to identify transcription factor-based inducible gene expression systems. The reverse strategy relies on predicting the effector molecule based on genetic context[16] or comparative genomics[17,18] This approach has successfully resulted in the identification of effectors and their corresponding TR-promoter pairs, but is limited to specific families of TRs and specific classes of compounds. To facilitate forward engineering efforts, the identified inducible systems are parameterised and we demonstrate their utility for controlling orthogonal gene expression We highlight their potential to be applied for investigation of metabolism and to expand the number of biologically detectable chemical species by evaluating the cross-reactivity between the library of biosensors and a comprehensive list of selected compounds. The biosensor responding to the industrially important intermediate compound β-alanine is applied to screen a library of L-aspartate 1-decarboxylase homologues and enzymes with superior activities are identified

Methods

Results

Conclusion