Development of novel metabolite-responsive transcription factors via transposon-mediated protein fusion

Abstract

Naturally evolved metabolite-responsive biosensors enable applications in metabolic engineering, ranging from screening large genetic libraries to dynamically regulating biosynthetic pathways. However, there are many metabolites for which a natural biosensor does not exist. To address this need, we developed a general method for converting metabolite-binding proteins into metabolite-responsive transcription factors-Biosensor Engineering by Random Domain Insertion (BERDI). This approach takes advantage of an in vitro transposon insertion reaction to generate all possible insertions of a DNA-binding domain into a metabolite-binding protein, followed by fluorescence activated cell sorting to isolate functional biosensors. To develop and evaluate the BERDI method, we generated a library of candidate biosensors in which a zinc finger DNA-binding domain was inserted into maltose binding protein, which served as a model well-studied metabolite-binding protein. Library diversity was characterized by several methods, a selection scheme was deployed, and ultimately several distinct and functional maltose-responsive transcriptional biosensors were identified. We hypothesize that the BERDI method comprises a generalizable strategy that may ultimately be applied to convert a wide range of metabolite-binding proteins into novel biosensors for applications in metabolic engineering and synthetic biology.

Transcription Factor Engineering for High-Throughput Strain Evolution and Organic Acid Bioproduction: A Review

“…Biosensor engineering by random domain insertion (BERDI) is another technique that can be used to generate new metabolite-responsive TFs. In this case, in vitro transposon-mediated mutagenesis was used to construct a TF library, followed by fluorescence-activated cell sorting (FACS) to isolate functional biosensors (Younger et al, 2017). Recently, MphR was found to bind promiscuously to macrolides, and was then engineered to improve its sensitivity, specificity, and selectivity for these small molecules (Kasey et al, 2017).…”

Transcriptional factor engineering in microbes for industrial biotechnology

“…The authors demonstrated the design of a maltose-responsive transcriptional biosensor based on the zinc-finger DNA-binding domain. 54 By employing the P sal promoter and SalR regulation system originally from A. baylyi ADP1, an inducible system responding to aspirin was developed. Without effector binding, the SalR was also capable of binding to the promoter to repress the transcription.…”

Plant Synthetic Biology: Quantifying the “Known Unknowns” and Discovering the “Unknown Unknowns”

“…Fortunately, there is a wealth of literature containing numerous case studies (recently reviewed in Bolbat and Schultz, 2017; Sanford and Palmer, 2017), because of early work on engineering of direct biosensors and protein switches (Siegel and Isacoff, 1997;Doi and Yanagawa, 1999;Prehoda et al, 2000;Tucker and Fields, 2001;Dueber et al, 2003;Guntas and Ostermeier, 2004). Ideally the design space of structurally reasonable fusions is thoroughly explored using protein engineering techniques to vary insertional position, linker residues between the modalities, and possibly circular permutation of one or both modalities (Kanwar et al, 2013;Younger et al, 2018). Recently, advances in bioinformatics and decreasing costs of next-generation sequencing have facilitated prediction and experimental determination of sites of potential allosteric regulation (Nadler et al, 2016;Rivoire et al, 2016;Pincus et al, 2017).…”

“…Transcription factors are an interesting alternative for connecting input and output modalities of direct or indirect biosensors, by allowing recognition of the species of interest to drive expression of any of the above output domains or another genetic circuit (Feng et al, 2015;Khakhar et al, 2016Khakhar et al, , 2018Younger et al, 2016Younger et al, , 2018. The amplification provided by transcription and translation may result in a wider dynamic range.…”