Transcription factor-based biosensors: a molecular-guided approach for natural product engineering

Mitchler, Melissa M; Garcia, Jessie M; Montero, Nichole E; Williams, Gavin J.

doi:10.1016/j.copbio.2021.01.008

Cited by 70 publications

(46 citation statements)

References 66 publications

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“…Overall, TFs seem a particularly useful target for intelligent host engineering (e.g. [432][433][434], including in biosensors [435][436][437][438][439][440][441][442][443][444]).…”

Section: Transcription Factor Engineeringmentioning

confidence: 99%

Intelligent host engineering for metabolic flux optimisation in biotechnology

Munro

Kell

2021

Biochemical Journal

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Optimising the function of a protein of length N amino acids by directed evolution involves navigating a ‘search space’ of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is ‘making such biology predictable’. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

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“…Overall, TFs seem a particularly useful target for intelligent host engineering (e.g. [432][433][434], including in biosensors [435][436][437][438][439][440][441][442][443][444]).…”

Section: Transcription Factor Engineeringmentioning

confidence: 99%

Intelligent host engineering for metabolic flux optimisation in biotechnology

Munro

Kell

2021

Biochemical Journal

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“…Inducible gene expression systems, composed of inducer-responsive TR and associated genetic elements including promoter and operator sequences, have increasingly been used for developing genetically encoded biosensors. Some inducible systems respond to distinct chemical ligands and they can be used for real-time monitoring of these compounds extracellularly and intracellularly, including applications such as a high-throughput screening of mutant libraries, dynamic pathway control, and adaptive laboratory evolution 17 , 18 . For L-lactate, an inducible gene expression system from E. coli has been previously applied for monitoring mammalian cell cultures 19 .…”

Section: Introductionmentioning

confidence: 99%

Identification and characterization of L- and D-lactate-inducible systems from Escherichia coli MG1655, Cupriavidus necator H16 and Pseudomonas species

Augustiniene

Malys

2022

Sci Rep

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Lactic acid is an important platform chemical used for the production of various compounds including polylactic acid (PLA). Optically pure L- and D-lactic acids are required to obtain high quality PLA. To advance the development and selection of microbial strains for improved production of lactic acid enantiomers, a high-throughput screening, dynamic pathway control, or real-time monitoring are often applied. Inducible gene expression systems and their application in the genetically encoded biosensors contribute to the development of these techniques and are important devices for the advancement of lactic acid biotechnology. Here, we identify and characterize eleven lactate-inducible systems from Escherichia coli, Cupriavidus necator, and Pseudomonas spp. The specificity and dynamics of these systems in response to L- and D-lactate, or structurally similar compounds are investigated. We demonstrate that the inducible systems EcLldR/PlldP and CnGntR/PH16_RS19190 respond only to the L-lactate, exhibiting approximately 19- and 24-fold induction, respectively. Despite neither of the examined bacteria possess the D-lactate-specific inducible system, the PaPdhR/PlldP and PfPdhR/PlldP are induced approximately 37- and 366-fold, respectively, by D-lactate and can be used for developing biosensor with improved specificity. The findings of this study provide an insight into understanding of L- and D-lactate-inducible systems that can be employed as sensing and tuneable devices in synthetic biology.

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“…As a result, aTF-based biosensors are used in a multitude of applications including but not limited to: screening for environmental contaminants 10,11 , screening metagenomic libraries to identify genes encoding functional enzymes 12 , point-of-care disease diagnostics 13 , as well as controlling synthetic bacterial consortia 14 and bacterial behaviour in situ 15 . As well, aTFs are used in metabolic engineering, which aims to precisely engineer native and heterologous metabolism to produce value-added chemicals 16,17 .…”

Section: Introductionmentioning

confidence: 99%

Divergent Directed Evolution of a TetR-type Repressor Towards Aromatic Molecules

Nasr¹,

Martin²,

Kwan³

2022

Preprint

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Reprogramming cellular behaviour is one of the hallmarks of synthetic biology. To this end, prokaryotic allosteric transcription factors (aTF) have been repurposed as versatile tools for processing small molecule signals into cellular responses. Expanding the toolbox of aTFs that recognize new inducer molecules is of considerable interest in many applications. Here, we first establish a resorcinol responsive aTF-based biosensor in Escherichia coli using the TetR-family repressor RolR from Corynebacterium glutamicum. We then perform an iterative walk along the fitness landscape of RolR to identify new inducer specificities, namely catechol, methyl catechol, caffeic acid, protocatechuate, L-DOPA, and the tumour biomarker homovanillic acid. Finally, we demonstrate the versatility of these engineered aTFs by transplanting them into the model eukaryote Saccharomyces cerevisiae. This work provides a framework for efficient aTF engineering to expand ligand specificity towards novel molecules on laboratory timescales, which, more broadly, is invaluable across a wide range of applications such as protein and metabolic engineering, as well as point-of-care diagnostics.

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Transcription factor-based biosensors: a molecular-guided approach for natural product engineering

Cited by 70 publications

References 66 publications

Intelligent host engineering for metabolic flux optimisation in biotechnology

Intelligent host engineering for metabolic flux optimisation in biotechnology

Identification and characterization of L- and D-lactate-inducible systems from Escherichia coli MG1655, Cupriavidus necator H16 and Pseudomonas species

Divergent Directed Evolution of a TetR-type Repressor Towards Aromatic Molecules

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