AraC Regulatory Protein Mutants with Altered Effector Specificity

Dynamics design of a non-natural transcription factor responding to androst-4-ene-3,17-dione

The production of androst-4-ene-3,17-dione (AD) by the steroidal microbial cell factory requires transcription factors (TFs) to participate in metabolic regulation. However, microbial cell factory lacks effective TFs that can respond to AD in its metabolic pathway. Additionally, finding and obtaining natural TFs that specifically respond to AD is a complex and onerous task. In this study, we devised an artificial TF that responds to AD, termed AdT, based on structure-guided molecular dynamics (MD) simulation. According to MD analysis of the conformational changes of AdT after binding to AD, an LBD in which the N- and C-termini exhibited convergence tendencies was used as a microswitch to guide the assembly of a DNA-binding domain lexA, a linker (GGGGS)2, and a transcription activation domain B42 into an artificial TF. As a proof of design, a AD biosensor was designed and constructed in yeast on the basis of the ligand-binding domain (LBD) of hormone receptor. In addition, the transcription factor activity of AdT was increased by 1.44-fold for its variant F320Y. Overall, we created non-natural TF elements for AD microbial cell factory, and expected that the design TF strategy will be applied to running in parallel to the signaling machinery of the host cell.

Identifying LasR Quorum Sensors with Improved Signal Specificity by Mapping the Sequence-Function Landscape

Programmable intercellular signaling using components of naturally occurring quorum sensing can allow for coordinated functions to be engineered in microbial consortia. LuxR-type transcriptional regulators are widely used for this purpose and are activated by homoserine lactone (HSL) signals. However, they often suffer from imperfect molecular discrimination of structurally similar HSLs, causing misregulation within engineered consortia containing multiple HSL signals. Here, we studied one such example, the regulator LasR from Pseudomonas aeruginosa. We elucidated its sequence-function relationship for ligand specificity using targeted protein engineering and multiplexed high-throughput biosensor screening. A pooled combinatorial saturation mutagenesis library (9,486 LasR DNA sequences) was created by mutating six residues in LasR's β5 sheet with single, double, or triple amino acid substitutions. Sort-seq assays were performed in parallel using cognate and noncognate HSLs to quantify each corresponding sensor's response to each HSL signal, which identified hundreds of highly specific variants. Sensor variants identified were individually assayed and exhibited up to 60.6-fold (p = 0.0013) improved relative activation by the cognate signal compared to the wildtype. Interestingly, we uncovered prevalent mutational epistasis and previously unidentified residues contributing to signal specificity. The resulting sensors with negligible signal crosstalk could be broadly applied to engineer bacteria consortia.

Directed Evolution of 4-Hydroxyphenylpyruvate Biosensors Based on a Dual Selection System

Biosensors based on allosteric transcription factors have been widely used in synthetic biology. In this study, we utilized the Acinetobacter ADP1 transcription factor PobR to develop a biosensor activating the PpobA promoter when bound to its natural ligand, 4-hydroxybenzoic acid (4HB). To screen for PobR mutants responsive to 4-hydroxyphenylpyruvate(HPP), we developed a dual selection system in E. coli. The positive selection of this system was used to enrich PobR mutants that identified the required ligands. The following negative selection eliminated or weakened PobR mutants that still responded to 4HB. Directed evolution of the PobR library resulted in a variant where PobRW177R was 5.1 times more reactive to 4-hydroxyphenylpyruvate than PobRWT. Overall, we developed an efficient dual selection system for directed evolution of biosensors.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Performance upgrade of a microbial explosives' sensor strain by screening a high throughput saturation library of a transcriptional regulator

We present a methodology for a high-throughput screening (HTS) of transcription factor libraries, based on bacterial cells and GFP fluorescence. The method is demonstrated on the Escherichia coli LysR-type transcriptional regulator YhaJ, a key element in 2,4-dinitrotuluene (DNT) detection by bacterial explosives' sensor strains. Enhancing the performance characteristics of the YhaJ transcription factor is essential for future standoff detection of buried landmines. However, conventional directed evolution methods for modifying YhaJ are limited in scope, due to the vast sequence space and the absence of efficient screening methods to select optimal transcription factor mutants. To overcome this limitation, we have constructed a focused saturation library of ca. 6.4 × 107 yhaJ variants, and have screened over 70 % of its sequence space using fluorescence-activated cell sorting (FACS). Through this screening process, we have identified YhaJ mutants exhibiting superior fluorescence responses to DNT, which were then effectively transformed into a bioluminescence-based DNT detection system. The best modified DNT reporter strain demonstrated a 7-fold lower DNT detection threshold, a 45-fold increased signal intensity, and a 40 % shorter response time compared to the parental bioreporter. The FACS-based HTS approach presented here may hold a potential for future molecular enhancement of other sensing and catalytic bioreactions.

AraC-Based Biosensor for the Detection of Isoprene in E. coli

Isoprene is a valuable platform chemical, which is produced by engineered microorganisms, albeit in low quantities. The amount of isoprene produced is usually measured by gas chromatography, which can be time-consuming and expensive. Alternatively, biosensors have evolved as a powerful tool for real-time high-throughput screening and monitoring of product synthesis. The AraC-pBAD-inducible system has been widely studied, evolved, and engineered to develop biosensors for small molecules. In our preliminary studies, the AraC-pBAD system was mildly induced at higher isoprene concentrations when arabinose was also available. Hence, in the present study, we designed and constructed a synthetic biosensor based on the AraC-pBAD system, wherein the ligand-binding domain of AraC was replaced with IsoA. On introducing this chimeric AraC-IsoA (AcIa) transcription factor with the native PBAD promoter system regulating rfp gene expression, fluorescence output was observed only when wild-type Escherichia coli cells were induced with both isoprene and arabinose. The biosensor sensitivity and dynamic range were further enhanced by removing operator sequences and by substituting the native promoter (PAraC) with the strong tac promoter (Ptac). The chimeric sensor did not work in AraC knockout strains; however, functionality was restored by reintroducing AraC. Hence, AraC is essential for the functioning of our biosensor, while AcIa provides enhanced sensitivity and specificity for isoprene. However, insights into how AraC-AcIa interacts and the possible working mechanism remain to be explored. This study provides a prototype for developing chimeric AraC-based biosensors with proteins devoid of known dimerizing domains and opens a new avenue for further study and exploration.

Latent generative landscapes as maps of functional diversity in protein sequence space

Variational autoencoders are unsupervised learning models with generative capabilities, when applied to protein data, they classify sequences by phylogeny and generate de novo sequences which preserve statistical properties of protein composition. While previous studies focus on clustering and generative features, here, we evaluate the underlying latent manifold in which sequence information is embedded. To investigate properties of the latent manifold, we utilize direct coupling analysis and a Potts Hamiltonian model to construct a latent generative landscape. We showcase how this landscape captures phylogenetic groupings, functional and fitness properties of several systems including Globins, β-lactamases, ion channels, and transcription factors. We provide support on how the landscape helps us understand the effects of sequence variability observed in experimental data and provides insights on directed and natural protein evolution. We propose that combining generative properties and functional predictive power of variational autoencoders and coevolutionary analysis could be beneficial in applications for protein engineering and design.

Directed evolution of linker helix as an efficient strategy for engineering LysR-type transcriptional regulators as whole-cell biosensors

Whole-cell biosensors based on transcriptional regulators are powerful tools for rapid measurement, high-throughput screening, dynamic metabolic regulation, etc. To optimize the biosensing performance of transcriptional regulator, its effector-binding domain is commonly engineered. However, this strategy is encumbered by the limitation of diversifying such a large domain and the risk of affecting effector specificity. Molecular dynamics simulation of effector binding of LysG (an LysR-type transcriptional regulator, LTTR) suggests the crucial role of the short linker helix (LH) connecting effector- and DNA-binding domains in protein conformational change. Directed evolution of LH efficiently produced LysG variants with extended operational range and unaltered effector specificity. The whole-cell biosensor based on the best LysG^E58V variant outperformed the wild-type LysG in enzyme high-throughput screening and dynamic regulation of l-lysine biosynthetic pathway. LH mutations are suggested to affect DNA binding and facilitate transcriptional activation upon effector binding. LH engineering was also successfully applied to optimize another LTTR BenM for biosensing. Since LTTRs represent the largest family of prokaryotic transcriptional regulators with highly conserved structures, LH engineering is an efficient and universal strategy for development and optimization of whole-cell biosensors.

Design and engineering of genetically encoded protein biosensors for small molecules

Genetically encoded protein biosensors controlled by small organic molecules are valuable tools for many biotechnology applications, including control of cellular decisions in living cells. Here, we review recent advances in protein biosensor design and engineering for binding to novel ligands. We categorize sensor architecture as either integrated or portable, where portable biosensors uncouple molecular recognition from signal transduction. Proposed advances to improve portable biosensor development include standardizing a limited set of protein scaffolds, and automating ligand-compatibility screening and ligand-protein-interface design.

Enzyme directed evolution using genetically encodable biosensors

Directed evolution has been remarkably successful in identifying enzyme variants with new or improved properties, such as altered substrate scope or novel reactivity. Genetically encodable biosensors (GEBs), which convert the concentration of a small molecule ligand into an easily detectable output signal, have seen increasing application to enzyme directed evolution in the last decade. GEBs enable the use of high-throughput methods to assess enzyme activity of very large libraries, which can accelerate the search for variants with desirable activity. Here, we review different classes of GEBs and their properties in the context of enzyme evolution, how GEBs have been integrated into directed evolution workflows, and recent examples of enzyme evolution efforts utilizing GEBs. Finally, we discuss the advantages, challenges, and opportunities for using GEBs in the directed evolution of enzymes.

Signal Amplification of araC pBAD Using a Standardised Translation Initiation Region

araC pBAD is a genetic fragment that regulates the expression of the araBAD operon in bacteria, which is required for the metabolism of L-arabinose. It is widely used in bioengineering applications because it can drive regulatable and titratable expression of genes and genetic pathways in microbial cell factories. A notable limitation of araC pBAD is that it generates a low signal when induced with high concentrations of L-arabinose (the maximum ON state). Herein we have amplified the maximum ON state of araC pBAD by coupling it to a synthetically evolved translation initiation region (TIR^EVOL). The coupling maintains regulatable and titratable expression from araC pBAD and yet increases the maximal ON state by >5-fold. The general principle demonstrated in the study can be applied to amplify the signal from similar genetic modules.

Graphical Abstract

Standardization of regulatory nodes for engineering heterologous gene expression: a feasibility study

The potential of LacI/P_trc, XylS/P_m, AlkS/P_alkB, CprK/P_DB3 and ChnR/P_chnB regulatory nodes, recruited from both Gram‐negative and Gram‐positive bacteria, as the source of parts for formatting expression cargoes following the Standard European Vector Architecture (SEVA) has been examined. The five expression devices, which cover most known regulatory configurations in bacteria were assembled within exactly the same plasmid backbone and bearing the different functional segments arrayed in an invariable DNA scaffold. Their performance was then analysed in an Escherichia coli strain of reference through the readout of a fluorescence reporter gene that contained strictly identical translation signal elements. This approach allowed us to describe and compare the cognate expression systems with quantitative detail. The constructs under scrutiny diverged considerably in their capacity, expression noise, inducibility and ON/OFF ratios. Inspection of such a variance exposed the different constraints that rule the optimal arrangement of functional DNA segments in each case. The data highlighted also the ease of standardizing inducer‐responsive devices subject to transcriptional activation as compared to counterparts based on repressors. The study resulted in a defined collection of formatted expression cargoes lacking any cross talk while offering a panoply of choices to potential users and help interoperability of the specific constructs.

Intracellular biosensor-based dynamic regulation to manipulate gene expression at the spatiotemporal level

The use of intracellular, biosensor-based dynamic regulation strategies to regulate and improve the production of useful compounds have progressed significantly over previous decades. By employing such an approach, it is possible to simultaneously realize high productivity and optimum growth states. However, industrial fermentation conditions contain a mixture of high- and low-performance non-genetic variants, as well as young and aged cells at all growth phases. Such significant individual variations would hinder the precise controlling of metabolic flux at the single-cell level to achieve high productivity at the macroscopic population level. Intracellular biosensors, as the regulatory centers of metabolic networks, can real-time sense intra- and extracellular conditions and, thus, could be synthetically adapted to balance the biomass formation and overproduction of compounds by individual cells. Herein, we highlight advances in the designing and engineering approaches to intracellular biosensors. Then, the spatiotemporal properties of biosensors associated with the distribution of inducers are compared. Also discussed is the use of such biosensors to dynamically control the cellular metabolic flux. Such biosensors could achieve single-cell regulation or collective regulation goals, depending on whether or not the inducer distribution is only intracellular.

Strategies for Improving Small-Molecule Biosensors in Bacteria

In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.

Evolving a Generalist Biosensor for Bicyclic Monoterpenes

Prokaryotic transcription factors can be repurposed as analytical and synthetic tools for precise chemical measurement and regulation. Monoterpenes encompass a broad chemical family that are commercially valuable as flavors, cosmetics, and fragrances, but have proven difficult to measure, especially in cells. Herein, we develop genetically encoded, generalist monoterpene biosensors by using directed evolution to expand the effector specificity of the camphor-responsive TetR-family regulator CamR from Pseudomonas putida. Using a novel negative selection coupled with a high-throughput positive screen (Seamless Enrichment of Ligand-Inducible Sensors, SELIS), we evolve CamR biosensors that can recognize four distinct monoterpenes: borneol, fenchol, eucalyptol, and camphene. Different evolutionary trajectories surprisingly yielded common mutations, emphasizing the utility of CamR as a platform for creating generalist biosensors. Systematic promoter optimization driving the reporter increased the system's signal-to-noise ratio to 150-fold. These sensors can serve as a starting point for the high-throughput screening and dynamic regulation of bicyclic monoterpene production strains.

Directed Evolution of Transcription Factor-Based Biosensors for Altered Effector Specificity

Transcription factor-based biosensors are important tools in Synthetic Biology for the sensing of industrially valuable molecules and clinically important metabolites, therefore presenting applications in the bioremediation, industrial biotechnology, and biomedical fields. The directed evolution of allosteric transcription factors (aTFs) with the aim of altering effector specificity has the potential for the development of new biosensors to detect natural and nonnatural molecules, expanding the scope of available aTF-based biosensors. In this chapter, we delineate a general method for the directed evolution of aTFs. The theory of library design is discussed, along with the detailed methodology for an improved transformation of combined libraries, and the experimental search space by counterselection using fluorescence-activated cell sorting (FACS) is presented.

Engineered l-Lactate Responding Promoter System Operating in Glucose-Rich and Anoxic Environments

Bacteria equipped with genetically encoded lactate biosensors are promising tools for biopharmaceutical production, diagnostics, and cellular therapies. However, many applications involve glucose-rich and anoxic environments, in which current whole-cell lactate biosensors show low performance. Here we engineer an optimized, synthetic lactate biosensor system by repurposing the natural LldPRD promoter regulated by the LldR transcriptional regulator. We removed glucose catabolite and anoxic repression by designing a hybrid promoter, containing LldR operators and tuned both regulator and reporter gene expressions to optimize biosensor signal-to-noise ratio. The resulting lactate biosensor, termed ALPaGA (A Lactate Promoter Operating in Glucose and Anoxia), can operate in glucose-rich, aerobic and anoxic conditions. We show that ALPaGA works reliably in the probiotic chassisEscherichia coliNissle 1917 and can detect endogenous l-lactate produced by 3D tumor spheroids with an improved dynamic range. In the future, the ALPaGA system could be used to monitor bioproduction processes and improve the specificity of engineered bacterial cancer therapies by restricting their activity to the lactate-rich microenvironment of solid tumors.

Development of a Transcription Factor-Based Diamine Biosensor in Corynebacterium glutamicum

Diamines serve as major platform chemicals that can be employed to a variety of industrial scenarios, particularly as monomers for polymer synthesis. High-throughput sensors for diamine biosynthesis can greatly improve the biological production of diamines. Here, we identified and characterized a transcription factor-driven biosensor for putrescine and cadaverine in Corynebacterium glutamicum. The transcriptional TetR-family regulatory protein CgmR (CGL2612) is used for the specific detection of diamine compounds. This study also improved the dynamic range and the sensitivity to putrescine by systematically optimizing genetic components of pSenPut. By a single cell-based screening strategy for a library of CgmR with random mutations, this study obtained the most sensitive variant CgmR_I152T, which possessed an experimentally determined limit of detection (LoD) of ≤0.2 mM, a K of 11.4 mM, and a utility of 720. Using this highly sensitive putrescine biosensor pSenPut_I152T, we demonstrated that CgmRI_152T can be used as a sensor to detect putrescine produced biologically in a C. glutamicum system. This high sensitivity and the range of CgmR will be an influential tool for rewiring metabolic circuits and facilitating the directed evolution of recombinant strains toward the biological synthesis of diamine compounds.

Biological signal processing filters via engineering allosteric transcription factors

As the size and complexity of genetic circuits increases, scientists and engineers need to find solutions to rapidly optimize flux and reduce the metabolic burden imposed on chassis cells. In this study, we report synthetic biology tools that imbue chassis cells with advanced signal processing functions akin to electrical devices commonly used in wireless transmitters and receivers (i.e., biological BANDPASS and BANDSTOP devices) that can simultaneously reduce metabolic burden. Moreover, this study presents a set of granular and more complete design rules for engineering allosteric transcription factors in the broader LacI/GalR topology. In addition, this study has improved our fundamental understanding of the plasticity and continuum of allosteric communication from the binding pocket to the protein–DNA interaction.

Signal processing is critical to a myriad of biological phenomena (natural and engineered) that involve gene regulation. Biological signal processing can be achieved by way of allosteric transcription factors. In canonical regulatory systems (e.g., the lactose repressor), an INPUT signal results in the induction of a given transcription factor and objectively switches gene expression from an OFF state to an ON state. In such biological systems, to revert the gene expression back to the OFF state requires the aggressive dilution of the input signal, which can take 1 or more d to achieve in a typical biotic system. In this study, we present a class of engineered allosteric transcription factors capable of processing two-signal INPUTS, such that a sequence of INPUTS can rapidly transition gene expression between alternating OFF and ON states. Here, we present two fundamental biological signal processing filters, BANDPASS and BANDSTOP, that are regulated by D-fucose and isopropyl-β-D-1-thiogalactopyranoside. BANDPASS signal processing filters facilitate OFF–ON–OFF gene regulation. Whereas, BANDSTOP filters facilitate the antithetical gene regulation, ON–OFF–ON. Engineered signal processing filters can be directed to seven orthogonal promoters via adaptive modular DNA binding design. This collection of signal processing filters can be used in collaboration with our established transcriptional programming structure. Kinetic studies show that our collection of signal processing filters can switch between states of gene expression within a few minutes with minimal metabolic burden—representing a paradigm shift in general gene regulation.

Development of Genetically Encoded Biosensors for Reporting the Methyltransferase-Dependent Biosynthesis of Semisynthetic Macrolide Antibiotics

Clarithromycin is an improved semisynthetic analogue of the naturally occurring macrolide, erythromycin. The subtle modification of a methyl group on the C-6 hydroxyl group endows the molecule with improved acid stability and results in a clinically useful antibiotic. Here, we show that the effector specificity of the biosensor protein, MphR, can be evolved to selectively recognize clarithromycin and therefore report on the production of this molecule in vivo. In addition, a crystal structure of the evolved variant reveals the molecular basis for selectivity and provides a guide for the evolution of a new metabolic function using this biosensor.

Modular tuning engineering and versatile applications of genetically encoded biosensors

Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.

Development of a Biosensor Platform for Phenolic Compounds Using a Transition Ligand Strategy

The time-consuming and laborious characterization of protein or microbial strain designs limits the development of high-performance biocatalysts for biotechnological applications. Here, transcriptional biosensors emerged as valuable tools as they allow for rapid characterization of several thousand variants within a very short time. However, for many molecules of interest, no specific transcriptional regulator determining a biosensor's specificity is available. We present an approach for rapidly engineering biosensor specificities using a semirational transition ligand approach combined with fluorescence-activated cell sorting. In this two-step approach, a biosensor is first evolved toward a more relaxed-ligand specificity before using the resulting variant as the starting point in a second round of directed evolution toward high specificity for several chemically different ligands. By following this strategy, highly specific biosensors for 4-hydroxybenzoic acid, p-coumaric acid, 5-bromoferulic acid, and 6-methyl salicylic acid were developed, starting from a biosensor for the intracellular detection of trans-cinnamic acid.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Transcription Factors as Evolvable Biosensors

One of the most prominent features of genetically encoded biosensors (GEBs) is their evolvability-the ability to invent new sensory functions using mutations. Among the GEBs, the transcription factor-based biosensors (TF-biosensors) is the focus of this review. We also discuss how this class of sensors can be highly evolvable and how we can exploit it. With an established platform for directed evolution, researchers can create, or evolve, new TF-biosensors. Directed evolution experiments have revealed the TF-biosensors' evolvability, which is based partially on their characteristic physicochemical properties.

On the way toward regulatable expression systems in acetic acid bacteria: target gene expression and use cases

Acetic acid bacteria (AAB) are valuable biocatalysts for which there is growing interest in understanding their basics including physiology and biochemistry. This is accompanied by growing demands for metabolic engineering of AAB to take advantage of their properties and to improve their biomanufacturing efficiencies. Controlled expression of target genes is key to fundamental and applied microbiological research. In order to get an overview of expression systems and their applications in AAB, we carried out a comprehensive literature search using the Web of Science Core Collection database. The Acetobacteraceae family currently comprises 49 genera. We found overall 6097 publications related to one or more AAB genera since 1973, when the first successful recombinant DNA experiments in Escherichia coli have been published. The use of plasmids in AAB began in 1985 and till today was reported for only nine out of the 49 AAB genera currently described. We found at least five major expression plasmid lineages and a multitude of further expression plasmids, almost all enabling only constitutive target gene expression. Only recently, two regulatable expression systems became available for AAB, an N-acyl homoserine lactone (AHL)-inducible system for Komagataeibacter rhaeticus and an L-arabinose-inducible system for Gluconobacter oxydans. Thus, after 35 years of constitutive target gene expression in AAB, we now have the first regulatable expression systems for AAB in hand and further regulatable expression systems for AAB can be expected. KEY POINTS: • Literature search revealed developments and usage of expression systems in AAB. • Only recently 2 regulatable plasmid systems became available for only 2 AAB genera. • Further regulatable expression systems for AAB are in sight.

Engineering Alternate Ligand Recognition in the PurR Topology: A System of Novel Caffeine Biosensing Transcriptional Antirepressors

Recent advances in synthetic biology and protein engineering have increased the number of allosteric transcription factors used to regulate independent promoters. These developments represent an important increase in our biological computing capacity, which will enable us to construct more sophisticated genetic programs for a broad range of biological technologies. However, the majority of these transcription factors are represented by the repressor phenotype (BUFFER), and require layered inversion to confer the antithetical logical function (NOT), requiring additional biological resources. Moreover, these engineered transcription factors typically utilize native ligand binding functions paired with alternate DNA binding functions. In this study, we have advanced the state-of-the-art by engineering and redesigning the PurR topology (a native antirepressor) to be responsive to caffeine, while mitigating responsiveness to the native ligand hypoxanthine-i.e., a deamination product of the input molecule adenine. Importantly, the resulting caffeine responsive transcription factors are not antagonized by the native ligand hypoxanthine. In addition, we conferred alternate DNA binding to the caffeine antirepressors, and to the PurR scaffold, creating 38 new transcription factors that are congruent with our current transcriptional programming structure. Finally, we leveraged this system of transcription factors to create integrated NOR logic and related feedback operations. This study represents the first example of a system of transcription factors (antirepressors) in which both the ligand binding site and the DNA binding functions were successfully engineered in tandem.

Whole-Cell Biosensors Aid Exploration of Vanillin Transmembrane Transport

Transcriptional regulatory protein (TRP)-based whole-cell biosensors are widely used nowadays. Here, they were demonstrated to have great potential application in screening cell efflux and influx pumps for small molecules. First, a vanillin whole-cell biosensor was developed by altering the specificity of a TRP, VanR, and strains with improved vanillin productions that were selected from a random genome mutagenesis library by using this biosensor as a high-throughput screening tool. A high intracellular vanillin concentration was found to accumulate due to the inactivation of the AcrA protein, indicating the involvement of this protein in vanillin efflux. Then, the application of this biosensor was extended to explore efflux and influx pumps, combined with directed genome evolution. Elevated intracellular vanillin levels resulting from efflux pump inactivation or influx pump overexpression could be rapidly detected by the whole-cell biosensor, markedly facilitating the identification of genome targets related to small-molecule transmembrane transport, which is of great importance in metabolic engineering.

Translating New Synthetic Biology Advances for Biosensing Into the Earth and Environmental Sciences

The rapid diversification of synthetic biology tools holds promise in making some classically hard-to-solve environmental problems tractable. Here we review longstanding problems in the Earth and environmental sciences that could be addressed using engineered microbes as micron-scale sensors (biosensors). Biosensors can offer new perspectives on open questions, including understanding microbial behaviors in heterogeneous matrices like soils, sediments, and wastewater systems, tracking cryptic element cycling in the Earth system, and establishing the dynamics of microbe-microbe, microbe-plant, and microbe-material interactions. Before these new tools can reach their potential, however, a suite of biological parts and microbial chassis appropriate for environmental conditions must be developed by the synthetic biology community. This includes diversifying sensing modules to obtain information relevant to environmental questions, creating output signals that allow dynamic reporting from hard-to-image environmental materials, and tuning these sensors so that they reliably function long enough to be useful for environmental studies. Finally, ethical questions related to the use of synthetic biosensors in environmental applications are discussed.

Engineering sensitivity and specificity of AraC-based biosensors responsive to triacetic acid lactone and orsellinic acid

We previously described the design of triacetic acid lactone (TAL) biosensor ‘AraC-TAL1’, based on the AraC regulatory protein. Although useful as a tool to screen for enhanced TAL biosynthesis, this variant shows elevated background (leaky) expression, poor sensitivity and relaxed inducer specificity, including responsiveness to orsellinic acid (OA). More sensitive biosensors specific to either TAL or OA can aid in the study and engineering of polyketide synthases that produce these and similar compounds. In this work, we employed a TetA-based dual-selection to isolate new TAL-responsive AraC variants showing reduced background expression and improved TAL sensitivity. To improve TAL specificity, OA was included as a ‘decoy’ ligand during negative selection, resulting in the isolation of a TAL biosensor that is inhibited by OA. Finally, to engineer OA-specific AraC variants, the iterative protein redesign and optimization computational framework was employed, followed by 2 rounds of directed evolution, resulting in a biosensor with 24-fold improved OA/TAL specificity, relative to AraC-TAL1.

Engineered protein switches for exogenous control of gene expression

There is an ongoing need in the synthetic biology community for novel ways to regulate gene expression. Protein switches, which sense biological inputs and respond with functional outputs, represent one way to meet this need. Despite the fact that there is already a large pool of transcription factors and signaling proteins available, the pool of existing switches lacks the substrate specificities and activities required for certain applications. Therefore, a large number of techniques have been applied to engineer switches with novel properties. Here we discuss some of these techniques by broadly organizing them into three approaches. We show how novel switches can be created through mutagenesis, domain swapping, or domain insertion. We then briefly discuss their use as biosensors and in complex genetic circuits.

Engineering and application of a biosensor with focused ligand specificity

Cell factories converting bio-based precursors to chemicals present an attractive avenue to a sustainable economy, yet screening of genetically diverse strain libraries to identify the best-performing whole-cell biocatalysts is a low-throughput endeavor. For this reason, transcriptional biosensors attract attention as they allow the screening of vast libraries when used in combination with fluorescence-activated cell sorting (FACS). However, broad ligand specificity of transcriptional regulators (TRs) often prohibits the development of such ultra-high-throughput screens. Here, we solve the structure of the TR LysG of Corynebacterium glutamicum, which detects all three basic amino acids. Based on this information, we follow a semi-rational engineering approach using a FACS-based screening/counterscreening strategy to generate an l-lysine insensitive LysG-based biosensor. This biosensor can be used to isolate l-histidine-producing strains by FACS, showing that TR engineering towards a more focused ligand spectrum can expand the scope of application of such metabolite sensors.

Transcriptional biosensors represent powerful tools for the screening of vast strain libraries, but the broad ligand specificity of some transcriptional regulators (TRs) can prohibit such applications. Here authors present the engineering of a LysG-based biosensor with a focused ligand specificity to isolate L-histidine-producing strains.

Protein Engineering for Improving and Diversifying Natural Product Biosynthesis

Proteins found in nature have traditionally been the most frequently used biocatalysts to produce numerous natural products ranging from commodity chemicals to pharmaceuticals. Protein engineering has emerged as a powerful biotechnological toolbox in the development of metabolic engineering, particularly for the biosynthesis of natural products. Recently, protein engineering has become a favored method to improve enzymatic activity, increase enzyme stability, and expand product spectra in natural product biosynthesis. This review summarizes recent advances and typical strategies in protein engineering, highlighting the paramount role of protein engineering in improving and diversifying the biosynthesis of natural products. Future prospects and research directions are also discussed.

Evolution-guided engineering of small-molecule biosensors

Allosteric transcription factors (aTFs) have proven widely applicable for biotechnology and synthetic biology as ligand-specific biosensors enabling real-time monitoring, selection and regulation of cellular metabolism. However, both the biosensor specificity and the correlation between ligand concentration and biosensor output signal, also known as the transfer function, often needs to be optimized before meeting application needs. Here, we present a versatile and high-throughput method to evolve prokaryotic aTF specificity and transfer functions in a eukaryote chassis, namely baker's yeast Saccharomyces cerevisiae. From a single round of mutagenesis of the effector-binding domain (EBD) coupled with various toggled selection regimes, we robustly select aTF variants of the cis,cis-muconic acid-inducible transcription factor BenM evolved for change in ligand specificity, increased dynamic output range, shifts in operational range, and a complete inversion-of-function from activation to repression. Importantly, by targeting only the EBD, the evolved biosensors display DNA-binding affinities similar to BenM, and are functional when ported back into a prokaryotic chassis. The developed platform technology thus leverages aTF evolvability for the development of new host-agnostic biosensors with user-defined small-molecule specificities and transfer functions.

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

Metabolic regulation of gene expression for the microbial production of fine chemicals, such as organic acids, is an important research topic in post-genomic metabolic engineering. In particular, the ability of transcription factors (TFs) to respond precisely in time and space to various small molecules, signals and stimuli from the internal and external environment is essential for metabolic pathway engineering and strain development. As a key component, TFs are used to construct many biosensors in vivo using synthetic biology methods, which can be used to monitor the concentration of intracellular metabolites in organic acid production that would otherwise remain “invisible” within the intracellular environment. TF-based biosensors also provide a high-throughput screening method for rapid strain evolution. Furthermore, TFs are important global regulators that control the expression levels of key enzymes in organic acid biosynthesis pathways, therefore determining the outcome of metabolic networks. Here we review recent advances in TF identification, engineering, and applications for metabolic engineering, with an emphasis on metabolite monitoring and high-throughput strain evolution for the organic acid bioproduction.

Switching the Ligand Specificity of the Biosensor XylS from meta to para-Toluic Acid through Directed Evolution Exploiting a Dual Selection System

The Pseudomonas putida transcriptional activator XylS induces transcription from the Pm promoter in the presence of several benzoic acid effectors, with m-toluic acid being the most effective and p-toluic acid being much less effective. To alter the effector specificity of XylS, we developed a dual selection system in Escherichia coli, which consists of (i) an artificial operon of an ampicillin resistance gene and tetR under Pm promoter control and (ii) a chloramphenicol resistance gene under tetR promoter control. This system enabled both positive selection to concentrate XylS mutants recognizing a desired ligand and negative selection to exclude undesired XylS mutants such as those recognizing undesired ligands and those that are active without effectors. Application of a random mutagenesis library of xylS to directed evolution that exploited this selection system yielded two XylS mutants that recognize p-toluic acid more effectively. Analysis of each missense mutation indicated three amino acid residues (N7, T74, and I205) important for p-toluic acid recognition. Then, a codon-randomized xylS library at these three residues was similarly screened, resulting in three XylS mutants with increased p-toluic acid-recognition specificity. Analysis of each amino acid substitution revealed that T74P attributes to both m-toluic acid sensitivity loss and subtle p-toluic acid sensitivity acquisition, and that N7R increases the overall ligand-sensitivity. Finally, the combination of these two mutations generated a desirable XylS mutant, which has a high p-toluic acid sensitivity and scarcely responds to m-toluic acid. These results demonstrate the effectiveness of the dual selection system in the directed evolution of biosensors.

Directed evolution of the PcaV allosteric transcription factor to generate a biosensor for aromatic aldehydes

Background

Transcription factor-based biosensors are useful tools for the detection of metabolites and industrially valuable molecules, and present many potential applications in biotechnology and biomedicine. However, the most common approach to develop biosensors relies on employing a limited set of naturally occurring allosteric transcription factors (aTFs). Therefore, altering the ligand specificity of aTFs towards the detection of new effectors is an important goal.

Results

Here, the PcaV repressor, a member of the MarR aTF family, was used to develop a biosensor for the detection of hydroxyl-substituted benzoic acids, including protocatechuic acid (PCA). The PCA biosensor was further subjected to directed evolution to alter its ligand specificity towards vanillin and other closely related aromatic aldehydes, to generate the Van2 biosensor. Ligand recognition of Van2 was explored in vitro using a range of biochemical and biophysical analyses, and extensive in vivo genetic-phenotypic analysis was performed to determine the role of each amino acid change upon biosensor performance.

Conclusions

This is the first study to report directed evolution of a member of the MarR aTF family, and demonstrates the plasticity of the PCA biosensor by altering its ligand specificity to generate a biosensor for aromatic aldehydes.

Genetically encoded biosensors for lignocellulose valorization

Modern society is hugely dependent on finite oil reserves for the supply of fuels and chemicals. Moving our dependence away from these unsustainable oil-based feedstocks to renewable ones is, therefore, a critical factor towards the development of a low carbon bioeconomy. Lignin derived from biomass feedstocks offers great potential as a renewable source of aromatic compounds if methods for its effective valorization can be developed. Synthetic biology and metabolic engineering offer the potential to synergistically enable the development of cell factories with novel biosynthetic routes to valuable chemicals from these sustainable sources. Pathway design and optimization is, however, a major bottleneck due to the lack of high-throughput methods capable of screening large libraries of genetic variants and the metabolic burden associated with bioproduction. Genetically encoded biosensors can provide a solution by transducing the target metabolite concentration into detectable signals to provide high-throughput phenotypic read-outs and allow dynamic pathway regulation. The development and application of biosensors in the discovery and engineering of efficient biocatalytic processes for the degradation, conversion, and valorization of lignin are paving the way towards a sustainable and economically viable biorefinery.

Metabolic engineering of l-leucine production in Escherichia coli and Corynebacterium glutamicum: a review

l-Leucine, as an essential branched-chain amino acid for humans and animals, has recently been attracting much attention because of its potential for a fast-growing market demand. The applicability ranges from flavor enhancers, animal feed additives and ingredients in cosmetic to specialty nutrients in pharmaceutical and medical fields. Microbial fermentation is the major method for producing l-leucine by using Escherichia coli and Corynebacterium glutamicum as host bacteria. This review gives an overview of the metabolic pathway of l-leucine (i.e. production, import and export systems) and highlights the main regulatory mechanisms of operons in E. coli and C. glutamicum l-leucine biosynthesis. We summarize here the current trends in metabolic engineering techniques and strategies for manipulating l-leucine producing strains. Finally, future perspectives to construct industrially advantageous strains are considered with respect to recent advances in biology.

Engineering the effector specificity of regulatory proteins for the in vitro detection of biomarkers and pesticide residues

Transcriptional regulatory proteins (TRPs)-based whole-cell biosensors are promising owing to their specificity and sensitivity, but their applications are currently limited. Herein, TRPs were adapted for the extracellular detection of a disease biomarker, uric acid, and a typical pesticide residue, carbaryl. A mutant regulatory protein that specifically recognizes carbaryl as its non-natural effector and activates transcription upon carbaryl binding was developed by engineering the regulatory protein TtgR from Pseudomonas putida. The TtgR mutant responsive to carbaryl and a regulatory protein responsive to uric acid were used for in vitro detection, based on their allosteric binding of operator DNA and inducer molecules. Based on the quantitative polymerase chain reactions (qPCRs) output, the minimum detectable concentration was between 1 nM-1 μM and 1-10 nM for uric acid and carbaryl, respectively. Our results demonstrated that engineering the effector specificity of regulatory proteins is a potential technique for generating molecular recognition elements for not only in vivo but also in vitro applications.

Biosensor-guided improvements in salicylate production by recombinant Escherichia coli

Background

Salicylate can be biosynthesized from the common metabolic intermediate shikimate and has found applications in pharmaceuticals and in the bioplastics industry. While much metabolic engineering work focused on the shikimate pathway has led to the biosynthesis of a variety of aromatic compounds, little is known about how the relative expression levels of pathway components influence salicylate biosynthesis. Furthermore, some host strain gene deletions that improve salicylate production may be impossible to predict. Here, a salicylate-responsive transcription factor was used to optimize the expression levels of shikimate/salicylate pathway genes in recombinant E. coli, and to screen a chromosomal transposon insertion library for improved salicylate production.

Results

A high-throughput colony screen was first developed based on a previously designed salicylate-responsive variant of the E. coli AraC regulatory protein (“AraC-SA”). Next, a combinatorial library was constructed comprising a series of ribosome binding site sequences corresponding to a range of predicted protein translation initiation rates, for each of six pathway genes (> 38,000 strain candidates). Screening for improved salicylate production allowed for the rapid identification of optimal gene expression patterns, conferring up to 123% improved production of salicylate in shake-flask culture. Finally, transposon mutagenesis and screening revealed that deletion of rnd (encoding RNase D) from the host chromosome further improved salicylate production by 27%.

Conclusions

These results demonstrate the effectiveness of the salicylate sensor-based screening platform to rapidly identify beneficial gene expression patterns and gene knockout targets for improving production. Such customized high-throughput tools complement other cell factory engineering strategies. This approach can be generalized for the production of other shikimate-derived compounds.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1069-1) contains supplementary material, which is available to authorized users.

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

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.

A synthetic microbial biosensor for high-throughput screening of lactam biocatalysts

Biocatalytic cyclization is highly desirable for efficient synthesis of biologically derived chemical substances, such as the commodity chemicals ε-caprolactam and δ-valerolactam. To identify biocatalysts in lactam biosynthesis, we develop a caprolactam-detecting genetic enzyme screening system (CL-GESS). The Alcaligenes faecalis regulatory protein NitR is adopted for the highly specific detection of lactam compounds against lactam biosynthetic intermediates. We further systematically optimize the genetic components of the CL-GESS to enhance sensitivity, achieving 10-fold improvement. Using this highly sensitive GESS, we screen marine metagenomes and find an enzyme that cyclizes ω-amino fatty acids to lactam. Moreover, we determine the X-ray crystal structure and catalytic residues based on mutational analysis of the cyclase. The cyclase is also used as a helper enzyme to sense intracellular ω-amino fatty acids. We expect this simple and accurate biosensor to have wide-ranging applications in rapid screening of new lactam-synthesizing enzymes and metabolic engineering for lactam bio-production.

Building a minimal and generalizable model of transcription factor-based biosensors: Showcasing flavonoids

Progress in synthetic biology tools has transformed the way we engineer living cells. Applications of circuit design have reached a new level, offering solutions for metabolic engineering challenges that include developing screening approaches for libraries of pathway variants. The use of transcription‐factor‐based biosensors for screening has shown promising results, but the quantitative relationship between the sensors and the sensed molecules still needs more rational understanding. Herein, we have successfully developed a novel biosensor to detect pinocembrin based on a transcriptional regulator. The FdeR transcription factor (TF), known to respond to naringenin, was combined with a fluorescent reporter protein. By varying the copy number of its plasmid and the concentration of the biosensor TF through a combinatorial library, different responses have been recorded and modeled. The fitted model provides a tool to understand the impact of these parameters on the biosensor behavior in terms of dose–response and time curves and offers guidelines to build constructs oriented to increased sensitivity and or ability of linear detection at higher titers. Our model, the first to explicitly take into account the impact of plasmid copy number on biosensor sensitivity using Hill‐based formalism, is able to explain uncharacterized systems without extensive knowledge of the properties of the TF. Moreover, it can be used to model the response of the biosensor to different compounds (here naringenin and pinocembrin) with minimal parameter refitting.

Molecular engineering of the salicylate-inducible transcription factor Sal7AR for orthogonal and high gene expression in Escherichia coli

I have previously identified a metagenomic fragment (~4 kb) containing the salicylate (2-hydroxybenzoate)-responsive transcriptional regulator Sal7AR. Taking advantage of the inert nature of salicylate to common genetic switches used in Escherichia coli, here I developed a salicylate-inducible high expression system in E. coli. I first applied a deletion analysis to the metagenomic fragment to identify the core region (~1 kb) necessary for the salicylate-dependent expression. Sal7AR was subjected to an error-prone PCR, and a library was screened for an enhanced expression of a reporter green fluorescent protein (GFP) gene in the presence of 1 mM salicylate, where virtually no growth inhibition was observed. Three beneficial amino acid substitutions were identified (N282K, Q292R, and V295G), each of which improved the expression of GFP relative to the wildtype by several-fold. The three sites were then completely randomized by saturation mutagenesis either individually or combinatorially to identify three variants carrying a single point mutation, N282L, V295F, or V295S; no further improvements were observed by combining these mutations. Salicylate-dependent expression of these mutants was highly repressed in its absence and escalated in response to ~10 μM salicylate, and gradually increased up to 1 mM salicylate; the induction rate was approximately 15 times greater than that achieved with a lactose promoter. Orthogonality to the lactose-based expression system was also confirmed. This salicylate-based expression system should thus be advantageously used for high-level production of recombinant proteins in combination with common lactose-dependent induction systems.

TECS: a toxin expression control strategy as a tool for optimization of inducible promoters

Background

Transcriptional control of gene expression is a widely utilized regulatory mechanism in synthetic biology, biotechnology and recombinant protein production. It is achieved by utilization of naturally occurring promoters responding to nutrients or chemicals. Despite their regulatory properties, these promoters often possess features which diminish their utility for biotechnology. High basal expression level and low induction ratio can be removed using genetic engineering techniques, although this process is often laborious and time-consuming.

Results

In order to facilitate optimization process for inducible promoters, we developed a simple method based on a conditional toxin expression which we abbreviate as toxin expression control strategy (TECS). In the presence of sucrose, SacB enzyme from Bacillus subtilis synthesizes levans which cause Eschericha coli cell lysis. However, in the absence of sucrose the enzyme does not affect the growth of the host. We utilized this feature to develop a two-step protocol allowing for efficient selection of inducible promoter variants. Using TECS we were able to modify the well-described p_BAD promoter to decrease its leakage while maintaining high activity upon induction. Furthermore, we used the method to test transcriptional interference of lambda phage-derived sequence and optimize it for higher induction levels through random mutagenesis.

Conclusions

We show that TECS is an efficient tool for optimization and development of inducible promoter systems in E. coli. Our strategy is very effective in the selection of promoter variants with improved properties. Its simplicity and short hands-on time make it an attractive method to optimize existing promoters and to construct novel, engineered genetic elements which improve properties of an inducible promoter system.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-0891-1) contains supplementary material, which is available to authorized users.