Directed evolution of a synthetic phylogeny of programmable Trp repressors

Harnessing DNA computing and nanopore decoding for practical applications: from informatics to microRNA-targeting diagnostics

DNA computing represents a subfield of molecular computing with the potential to become a significant area of next-generation computation due to the high programmability inherent in the sequence-dependent molecular behaviour of DNA. Recent studies in DNA computing have extended from mathematical informatics to biomedical applications, with a particular focus on diagnostics that exploit the biocompatibility of DNA molecules. The output of DNA computing devices is encoded in nucleic acid molecules, which must then be decoded into human-recognizable signals for practical applications. Nanopore technology, which utilizes an electrical and label-free decoding approach, provides a unique platform to bridge DNA and electronic computing for practical use. In this tutorial review, we summarise the fundamental knowledge, technologies, and methodologies of DNA computing (logic gates, circuits, neural networks, and non-DNA input circuity). We then focus on nanopore-based decoding, and highlight recent advances in medical diagnostics targeting microRNAs as biomarkers. Finally, we conclude with the potential and challenges for the practical implementation of these techniques. We hope that this tutorial will provide a comprehensive insight and enable the general reader to grasp the fundamental principles and diverse applications of DNA computing and nanopore decoding, and will inspire a wide range of scientists to explore and push the boundaries of these technologies.

Architecting a Transcriptional Repressor-based Genetic Inverter for Tryptophan Derived Pathway Regulation in Escherichia coli

Efficient microbial cell factories require intricate and precise metabolic regulations for optimized production, which can be significantly aided by implementing regulatory genetic circuits with versatile functions. However, constructing functionally diverse genetic circuits in host strains is challenging. Especially, functional diversification based on transcriptional repressors has been rarely explored due to the difficulty in inverting their repression properties. To address this, we proposed a design logic to create transcriptional repressor-based genetic inverters for functional enrichment. As proof of concept, a tryptophan-inducible genetic inverter was constructed by integrating two sets of transcriptional repressors, PtrpO1-TrpR1 and PtetO1-TetR. In this genetic inverter, the repression of TetR towards PtetO1 could be alleviated by the tryptophan-TrpR1 complex in the presence of tryptophan, leading to the activated output. Subsequently, we optimized the dynamic performance of the inverter and constructed tryptophan-triggered dynamic activation systems. Further coupling of the original repression function of PtrpO1-TrpR1 with inverter variants realized the tryptophan-triggered bifunctional regulation system. Finally, the dynamic regulation systems enabled tryptophan production monitoring. These systems also remarkably increased the titers of the tryptophan derivatives tryptamine and violacein by 2.0-fold and 7.4-fold, respectively. The successful design and application of the genetic inverter enhanced the applicability of transcriptional repressors.

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.

Fluorescence-Based Screens for Engineering Enzymes Linked to Halogenated Tryptophan

Directed evolution is often limited by the throughput of accurate screening methods. Here we demonstrate the feasibility of utilizing a singular transcription factor (TF)-system that can be refactored in two ways (both as an activator and repressor). Specifically, we showcase the use of previously evolved 5-halo- or 6-halo-tryptophan-specific TF biosensors suitable for the detection of a halogenated tryptophan molecule in vivo. We subsequently validate the biosensor's utility for two halogenase-specific halo-tryptophan accumulation screens. First, we isolated 5-tryptophan-halogenase, XsHal, from a mixed pool of halogenases with 100% efficiency. Thereafter, we generated a targeted library of the catalytic residue of 6-tryptophan halogenase, Th-Hal, and isolated functioning halogenases with 100% efficiency. Lastly, we refactor the TF circuit to respond to the depletion of halogenated tryptophan and prototype a high-throughput biosensor-directed evolution scheme to screen for downstream enzyme variants capable of promiscuously converting halogenated tryptophan. Altogether, this work takes a significant step toward the rapid and higher throughput screening of halogenases and halo-tryptophan converting enzymes to further reinforce efforts to enable high-level bioproduction of halogenated chemicals.

In Vitro Enzyme Self-Selection Using Molecular Programs

Directed evolution provides a powerful route for in vitro enzyme engineering. State-of-the-art techniques functionally screen up to millions of enzyme variants using high throughput microfluidic sorters, whose operation remains technically challenging. Alternatively, in vitro self-selection methods, analogous to in vivo complementation strategies, open the way to even higher throughputs, but have been demonstrated only for a few specific activities. Here, we leverage synthetic molecular networks to generalize in vitro compartmentalized self-selection processes. We introduce a programmable circuit architecture that can link an arbitrary target enzymatic activity to the replication of its encoding gene. Microencapsulation of a bacterial expression library with this autonomous selection circuit results in the single-step and screening-free enrichment of genetic sequences coding for programmed enzymatic phenotypes. We demonstrate the potential of this approach for the nicking enzyme Nt.BstNBI (NBI). We applied autonomous selection conditions to enrich for thermostability or catalytic efficiency, manipulating up to 107 microcompartments and 5 × 105 variants at once. Full gene reads of the libraries using nanopore sequencing revealed detailed mutational activity landscapes, suggesting a key role of electrostatic interactions with DNA in the enzyme's turnover. The most beneficial mutations, identified after a single round of self-selection, provided variants with, respectively, 20 times and 3 °C increased activity and thermostability. Based on a modular molecular programming architecture, this approach does not require complex instrumentation and can be repurposed for other enzymes, including those that are not related to DNA chemistry.

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.

One-pot selective biosynthesis of Tyrian purple in Escherichia coli

Tyrian purple (6,6'-Dibromoindigo) is an ancient precious dye, which possesses remarkable properties as a biocompatible semiconductor material. Recently, biosynthesis has emerged as an alternative for the sustainable production of Tyrian purple from a natural substrate. However, the selectivity issue in enzymatic tryptophan (Trp) and bromotryptophan (6-Br-Trp) degradation was an obstacle for obtaining high-purity Tyrian purple in a single cell biosynthesis. In this study, we present a simplified one-pot process for the production of Tyrian purple from Trp in Escherichia coli (E. coli) using Trp 6-halogenase from Streptomyces toxytricini (SttH), tryptophanase from E. coli (TnaA) and a two-component indole oxygenase from Providencia Rettgeri GS-2 (GS-C and GS-D). To enhance the in vivo solubility and activity of SttH and flavin reductase (Fre) fusion enzyme (Fre-L3-SttH), a chaperone system of GroEL/GroES (pGro7) was introduced in addition to the implementation of a set of optimization strategies, including fine-tuning the expression vector, medium, concentration of bromide salt and inducer. To overcome the selectivity issue and achieve a higher conversion yield of Tyrian purple with minimal indigo formation, we applied the λpL/pR-cI857 thermoinducible system to temporally control the bifunctional fusion enzyme of TnaA and monooxygenase GS-C (TnaA-L3-GS-C). Through optimization of the fermentation process, we were able to achieve a Tyrian purple titer of 44.5 mg L-1 with minimal indigo byproduct from 500 μM Trp. To the best of our knowledge, this is the first report of the selective production of Tyrian purple in E. colivia a one-pot process.

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.

Customizing cellular signal processing by synthetic multi-level regulatory circuits

As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.

Divergent directed evolution of a TetR-type repressor towards aromatic molecules

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.

In vitro allosteric transcription factor-based biosensing

A biosensor is an analytical device that converts a biological response into a measurable output signal. Bacterial allosteric transcription factors (aTFs) have been utilized as a novel class of recognition elements for in vitro biosensing, which circumvents the limitations of aTF-based whole-cell biosensors (WCBs) and helps to meet the increasing requirement of small-molecule biosensors for diverse applications. In this review, we summarize the recent advances related to the configuration of aTF-based biosensors in vitro. Particularly, we evaluate the advantages of aTFs for in vitro biosensing and highlight their great potential for the establishment of robust and easy-to-implement biosensing strategies. We argue that key technical innovations and generalizable workflows will enhance the pipeline for facile construction of diverse aTF-based small-molecule biosensors.

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.

Transcription factor-based biosensors for screening and dynamic regulation

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.

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

The potential of LacI/Ptrc , XylS/Pm , AlkS/PalkB , CprK/PDB3 and ChnR/PchnB 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.

Engineering of a TrpR-Based Biosensor for Altered Dynamic Range and Ligand Preference

Transcriptional factors play a crucial role in regulating cellular functions. Understanding and altering the dynamic behavior of the transcriptional factor-based biosensors will expand our knowledge in investigating biomolecular interactions and facilitating biosynthetic applications. In this study, we characterized and engineered a TrpR-based tryptophan repressor system in Escherichia coli. We found that the reconstructed TrpR1-PtrpO1 biosensor system exhibited low basal expression and narrow dynamic range in the presence of tryptophan or its analogue 5-hydroxytryptophan (5-HTP). Given the application potential of the biosensor, we introduced engineering approaches in multiple levels to optimize its dynamic behavior. First, the I57 and V58 residues in the ligand-binding pocket were rationally mutated in search of variants with altered ligand specificity. Two TrpR1 variants, V58E and V58K, successfully acquired ligand preference toward tryptophan and 5-HTP, respectively. The biosensor-induced expression levels were increased up to 10-fold with those variants. Furthermore, to pursue broader operational range, we tuned the regulator-operator binding affinity by mutating the binding box of TrpR1. Collectively, we demonstrated that the biosynthesis-significant biosensor TrpR1-PtrpO1 can be engineered to acquire extended dynamic ranges and improved ligand preference. The engineered biosensor variants with remarkable dynamic behavior can serve as key genetic elements in high-throughput screening and dynamic regulation in biosynthetic scenarios.

A Versatile Transcription Factor Biosensor System Responsive to Multiple Aromatic and Indole Inducers

Allosteric transcription factor (aTF) biosensors are valuable tools for engineering microbes toward a multitude of applications in metabolic engineering, biotechnology, and synthetic biology. One of the challenges toward constructing functional and diverse biosensors in engineered microbes is the limited toolbox of identified and characterized aTFs. To overcome this, extensive bioprospecting of aTFs from sequencing databases, as well as aTF ligand-specificity engineering are essential in order to realize their full potential as biosensors for novel applications. In this work, using the TetR-family repressor CmeR from Campylobacter jejuni, we construct aTF genetic circuits that function as salicylate biosensors in the model organisms Escherichia coli and Saccharomyces cerevisiae. In addition to salicylate, we demonstrate the responsiveness of CmeR-regulated promoters to multiple aromatic and indole inducers. This relaxed ligand specificity of CmeR makes it a useful tool for detecting molecules in many metabolic engineering applications, as well as a good target for directed evolution to engineer proteins that are able to detect new and diverse chemistries.

Engineering of Synthetic Transcriptional Switches in Yeast

Transcriptional switches can be utilized for many purposes in synthetic biology, including the assembly of complex genetic circuits to achieve sophisticated cellular systems and the construction of biosensors for real-time monitoring of intracellular metabolite concentrations. Although to date such switches have mainly been developed in prokaryotes, those for eukaryotes are increasingly being reported as both rational and random engineering technologies mature. In this review, we describe yeast transcriptional switches with different modes of action and how to alter their properties. We also discuss directed evolution technologies for the rapid and robust construction of yeast transcriptional switches.

Engineering ligand-specific biosensors for aromatic amino acids and neurochemicals

Microbial biosensors have diverse applications in metabolic engineering and medicine. Specific and accurate quantification of chemical concentrations allows for adaptive regulation of enzymatic pathways and temporally precise expression of diagnostic reporters. Although biosensors should differentiate structurally similar ligands with distinct biological functions, such specific sensors are rarely found in nature and challenging to create. Using E. coli Nissle 1917, a generally regarded as safe microbe, we characterized two biosensor systems that promiscuously recognize aromatic amino acids or neurochemicals. To improve the sensors' selectivity and sensitivity, we applied rational protein engineering by identifying and mutagenizing amino acid residues and successfully demonstrated the ligand-specific biosensors for phenylalanine, tyrosine, phenylethylamine, and tyramine. Additionally, our approach revealed insights into the uncharacterized structure of the FeaR regulator, including critical residues in ligand binding. These results lay the groundwork for developing kinetically adaptive microbes for diverse applications. A record of this paper's transparent peer review process is included in the supplemental information.

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.

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.

L-valine production in Corynebacterium glutamicum based on systematic metabolic engineering: progress and prospects

L-valine is an essential branched-chain amino acid that cannot be synthesized by the human body and has a wide range of applications in food, medicine and feed. Market demand has stimulated people's interest in the industrial production of L-valine. At present, the mutagenized or engineered Corynebacterium glutamicum is an effective microbial cell factory for producing L-valine. Because the biosynthetic pathway and metabolic network of L-valine are intricate and strictly regulated by a variety of key enzymes and genes, highly targeted metabolic engineering can no longer meet the demand for efficient biosynthesis of L-valine. In recent years, the development of omics technology has promoted the upgrading of traditional metabolic engineering to systematic metabolic engineering. This whole-cell-scale transformation strategy has become a productive method for developing L-valine producing strains. This review provides an overview of the biosynthesis and regulation mechanism of L-valine, and summarizes the current metabolic engineering techniques and strategies for constructing L-valine high-producing strains. Finally, the opinion of constructing a cell factory for efficiently biosynthesizing L-valine was proposed.

A small-molecule chemical interface for molecular programs

In vitro molecular circuits, based on DNA-programmable chemistries, can perform an increasing range of high-level functions, such as molecular level computation, image or chemical pattern recognition and pattern generation. Most reported demonstrations, however, can only accept nucleic acids as input signals. Real-world applications of these programmable chemistries critically depend on strategies to interface them with a variety of non-DNA inputs, in particular small biologically relevant chemicals. We introduce here a general strategy to interface DNA-based circuits with non-DNA signals, based on input-translating modules. These translating modules contain a DNA response part and an allosteric protein sensing part, and use a simple design that renders them fully tunable and modular. They can be repurposed to either transmit or invert the response associated with the presence of a given input. By combining these translating-modules with robust and leak-free amplification motifs, we build sensing circuits that provide a fluorescent quantitative time-response to the concentration of their small-molecule input, with good specificity and sensitivity. The programmability of the DNA layer can be leveraged to perform DNA based signal processing operations, which we demonstrate here with logical inversion, signal modulation and a classification task on two inputs. The DNA circuits are also compatible with standard biochemical conditions, and we show the one-pot detection of an enzyme through its native metabolic activity. We anticipate that this sensitive small-molecule-to-DNA conversion strategy will play a critical role in the future applications of molecular-level circuitry.

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.

Molecular Evolution of Transition Metal Bioavailability at the Host-Pathogen Interface

The molecular evolution of the adaptive response at the host-pathogen interface has been frequently referred to as an 'arms race' between the host and bacterial pathogens. The innate immune system employs multiple strategies to starve microbes of metals. Pathogens, in turn, develop successful strategies to maintain access to bioavailable metal ions under conditions of extreme restriction of transition metals, or nutritional immunity. However, the processes by which evolution repurposes or re-engineers host and pathogen proteins to perform or refine new functions have been explored only recently. Here we review the molecular evolution of several human metalloproteins charged with restricting bacterial access to transition metals. These include the transition metal-chelating S100 proteins, natural resistance-associated macrophage protein-1 (NRAMP-1), transferrin, lactoferrin, and heme-binding proteins. We examine their coevolution with bacterial transition metal acquisition systems, involving siderophores and membrane-spanning metal importers, and the biological specificity of allosteric transcriptional regulatory proteins tasked with maintaining bacterial metallostasis. We also discuss the evolution of metallo-β-lactamases; this illustrates how rapid antibiotic-mediated evolution of a zinc metalloenzyme obligatorily occurs in the context of host-imposed nutritional immunity.

Robust and flexible platform for directed evolution of yeast genetic switches

A wide repertoire of genetic switches has accelerated prokaryotic synthetic biology, while eukaryotic synthetic biology has lagged in the model organism Saccharomyces cerevisiae. Eukaryotic genetic switches are larger and more complex than prokaryotic ones, complicating the rational design and evolution of them. Here, we present a robust workflow for the creation and evolution of yeast genetic switches. The selector system was designed so that both ON- and OFF-state selection of genetic switches is completed solely by liquid handling, and it enabled parallel screen/selection of different motifs with different selection conditions. Because selection threshold of both ON- and OFF-state selection can be flexibly tuned, the desired selection conditions can be rapidly pinned down for individual directed evolution experiments without a prior knowledge either on the library population. The system's utility was demonstrated using 20 independent directed evolution experiments, yielding genetic switches with elevated inducer sensitivities, inverted switching behaviours, sensory functions, and improved signal-to-noise ratio (>100-fold induction). The resulting yeast genetic switches were readily integrated, in a plug-and-play manner, into an AND-gated carotenoid biosynthesis pathway.

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.

Deploying Microbial Synthesis for Halogenating and Diversifying Medicinal Alkaloid Scaffolds

Plants produce some of the most potent therapeutics and have been used for thousands of years to treat human diseases. Today, many medicinal natural products are still extracted from source plants at scale as their complexity precludes total synthesis from bulk chemicals. However, extraction from plants can be an unreliable and low-yielding source for human therapeutics, making the supply chain for some of these life-saving medicines expensive and unstable. There has therefore been significant interest in refactoring these plant pathways in genetically tractable microbes, which grow more reliably and where the plant pathways can be more easily engineered to improve the titer, rate and yield of medicinal natural products. In addition, refactoring plant biosynthetic pathways in microbes also offers the possibility to explore new-to-nature chemistry more systematically, and thereby help expand the chemical space that can be probed for drugs as well as enable the study of pharmacological properties of such new-to-nature chemistry. This perspective will review the recent progress toward heterologous production of plant medicinal alkaloids in microbial systems. In particular, we focus on the refactoring of halogenated alkaloids in yeast, which has created an unprecedented opportunity for biosynthesis of previously inaccessible new-to-nature variants of the natural alkaloid scaffolds.

Engineered systems of inducible anti-repressors for the next generation of biological programming

Traditionally engineered genetic circuits have almost exclusively used naturally occurring transcriptional repressors. Recently, non-natural transcription factors (repressors) have been engineered and employed in synthetic biology with great success. However, transcriptional anti-repressors have largely been absent with regard to the regulation of genes in engineered genetic circuits. Here, we present a workflow for engineering systems of non-natural anti-repressors. In this study, we create 41 inducible anti-repressors. This collection of transcription factors respond to two distinct ligands, fructose (anti-FruR) or D-ribose (anti-RbsR); and were complemented by 14 additional engineered anti-repressors that respond to the ligand isopropyl β-d-1-thiogalactopyranoside (anti-LacI). In turn, we use this collection of anti-repressors and complementary genetic architectures to confer logical control over gene expression. Here, we achieved all NOT oriented logical controls (i.e., NOT, NOR, NAND, and XNOR). The engineered transcription factors and corresponding series, parallel, and series-parallel genetic architectures represent a nascent anti-repressor based transcriptional programming structure.

Transcriptional anti-repressors have been largely absent in the design of regulated genetic circuits. Here, the authors present a workflow of the engineering of non-natural anti-reperssors that can be built into NOT oriented logic gates.

Cell-free biosensors for rapid detection of water contaminants

Lack of access to safe drinking water is a global problem, and methods to reliably and easily detect contaminants could be transformative. We report the development of a cell-free in vitro transcription system that uses RNA Output Sensors Activated by Ligand Induction (ROSALIND) to detect contaminants in water. A combination of highly processive RNA polymerases, allosteric protein transcription factors and synthetic DNA transcription templates regulates the synthesis of a fluorescence-activating RNA aptamer. The presence of a target contaminant induces the transcription of the aptamer, and a fluorescent signal is produced. We apply ROSALIND to detect a range of water contaminants, including antibiotics, small molecules and metals. We also show that adding RNA circuitry can invert responses, reduce crosstalk and improve sensitivity without protein engineering. The ROSALIND system can be freeze-dried for easy storage and distribution, and we apply it in the field to test municipal water supplies, demonstrating its potential use for monitoring water quality.

Directed Evolution of the Stringency of the LuxR Vibrio fischeri Quorum Sensor without OFF-State Selection

Stringency (low leak) is one of the most important specifications required for genetic circuits and induction systems, but it is challenging to evolve without sacrificing the maximum output level. This problem also comes from the absence of truly tunable negative selection methods. This paper reports that stringently switching variants can sometimes emerge with surprising frequency upon mutations. We randomly mutated the previously generated leaky variants of LuxR, the quorum-sensing transcription activator from Vibrio fischeri, to restore the stringency. We found as much as 10-20% of the entire population exhibited significantly improved signal-to-noise ratios compared with their parents. This indicated that these mutants arose by the loss of folding capability by accumulating destabilizing mutations, not by introducing rare adaptive mutations, thereby becoming AHL-dependent folders. Only four rounds of mutagenesis and ON-state selection resulted in the domination of the entire population by the improved variants with low leak, without direct selection pressure for stringency. With this surprising frequency, conversion into the "ligand-addicted folders" should be one of the prevailing modes of evolving stringency both in the laboratory and in nature, and the workflow described here provides a rapid and versatile method of improving the signal-to-noise ratio of various genetic switches.

Development of High-Performance Whole Cell Biosensors Aided by Statistical Modeling

Whole cell biosensors are genetic systems that link the presence of a chemical, or other stimulus, to a user-defined gene expression output for applications in sensing and control. However, the gene expression level of biosensor regulatory components required for optimal performance is nonintuitive, and classical iterative approaches do not efficiently explore multidimensional experimental space. To overcome these challenges, we used a design of experiments (DoE) methodology to efficiently map gene expression levels and provide biosensors with enhanced performance. This methodology was applied to two biosensors that respond to catabolic breakdown products of lignin biomass, protocatechuic acid and ferulic acid. Utilizing DoE we systematically modified biosensor dose-response behavior by increasing the maximum signal output (up to 30-fold increase), improving dynamic range (>500-fold), expanding the sensing range (∼4-orders of magnitude), increasing sensitivity (by >1500-fold), and modulated the slope of the curve to afford biosensors designs with both digital and analogue dose-response behavior. This DoE method shows promise for the optimization of regulatory systems and metabolic pathways constructed from novel, poorly characterized parts.

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.

An autoinducible trp-T7 expression system for production of proteins and biochemicals in Escherichia coli

Inducible expression systems can be applied to control the expression of proteins or biochemical pathways in cell factories. However, several of the established systems require the addition of expensive inducers, making them unfeasible for large‐scale production. Here, we establish a genome integrated trp‐T7 expression system where tryptophan can be used to control the induction of a gene or a metabolic pathway. We show that the initiation of gene expression from low‐ and high‐copy vectors can be tuned by varying the initial concentration of tryptophan or yeast extract, and that expression is tightly regulated and homogenous when compared with the commonly used lac‐T7 system. Finally, we apply the trp‐T7 expression system for the production of l‐serine, where we reach titers of 26 g/L in fed‐batch fermentation.

Biosensing in Smart Engineered Probiotics

Engineered microbes are exciting alternatives to current diagnostics and therapeutics. Researchers have developed a wide range of genetic tools and parts to engineer probiotic and commensal microbes. Among these tools and parts, biosensors allow the microbes to sense and record or to sense and respond to chemical and environmental signals in the body, enabling them to report on health conditions of the animal host and/or deliver therapeutics in a controlled manner. This review focuses on how biosensing is applied to engineer "smart" microbes for in vivo diagnostic, therapeutic, and biocontainment goals. Hurdles that need to be overcome when transitioning from high-throughput in vitro systems to low-throughput in vivo animal models, new technologies that can be implemented to alleviate this experimental gap, and areas where future advancements can be made to maximize the utility of biosensing for medical applications are also discussed. As technologies for engineering microbes continue to be developed, these engineered organisms will be used to address many medical challenges.

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.

Contemporary Tools for Regulating Gene Expression in Bacteria

Insights from novel mechanistic paradigms in gene expression control have led to the development of new gene expression systems for bioproduction, control, and sensing applications. Coupled with a greater understanding of synthetic burden and modern creative biodesign approaches, contemporary bacterial gene expression tools and systems are emerging that permit fine-tuning of expression, enabling greater predictability and maximisation of specific productivity, while minimising deleterious effects upon cell viability. These advances have been achieved by using a plethora of regulatory tools, operating at all levels of the so-called 'central dogma' of molecular biology. In this review, we discuss these gene regulation tools in the context of their design, prototyping, integration into expression systems, and biotechnological application.

Stimulus response-based fine-tuning of polyhydroxyalkanoate pathway in Halomonas

Optimization of intracellular biosynthesis process involving regulation of multiple gene expressions is dependent on the efficient and accurate expression of each expression unit independently. However, challenges of analyzing intermediate products seriously hinder the application of high throughput assays. This study aimed to develop an engineering approach for unsterile production of poly(3-hydroxybutyrate-co-4-hydroxybutyrate) or (P3HB4HB) by recombinant Halomonas bluephagenesis (H. bluephagenesis) constructed via coupling the design of GFP-mediated transcriptional mapping and high-resolution control of gene expressions (HRCGE), which consists of two inducible systems with high- and low-dynamic ranges employed to search the exquisite transcription level of each expression module in the presence of γ-butyrolactone, the intermediate for 4-hydroxybutyrate (4HB) synthesis. It has been successful to generate a recombinant H. bluephagenesis, namely TD68-194, able to produce over 36 g/L P3HB4HB consisting of 16 mol% 4HB during a 7-L lab-scale fed-batch growth process, of which cell dry weight and PHA content reached up to 48.22 g/L and 74.67%, respectively, in 36 h cultivation. HRCGE has been found useful for metabolic pathway construction.

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.

Molecular parts and genetic circuits for metabolic engineering of microorganisms

Microbial conversion of biomass into value-added biochemicals is a highly sustainable process compared to petroleum-based production. In this regard, microorganisms have been engineered via simple overexpression or deletion of metabolic genes to facilitate the production. However, the producer microorganisms require complex regulatory circuits to maximize productivity and performance. To address this issue, diverse genetic circuits have been developed that allow cells to minimize their metabolic burden, overcome metabolic imbalances and respond to a dynamically changing environment. In this review, we briefly explain the basic strategy for constructing genetic circuits by assembling molecular parts such as input, operation and output modules. Next, we describe recent applications of the circuits in the metabolic engineering of microorganisms to improve biochemical production. Beyond those achievements, genetic circuits will facilitate more innovative approaches to future strain development through mining and engineering new genetic elements and improving the complexity of genetic circuit design.

Genetic Circuit-Assisted Smart Microbial Engineering

Rapid advances in DNA synthesis, genetic manipulation, and biosensors have greatly improved the ability to engineer microorganisms with complex functions. By accurately integrating quality biosensors and complex genetic circuits, recently emerged smart microorganisms have enabled exciting opportunities for dissecting complex signaling networks and making responses without artificial intervention. However, because of the lack of design principles, developing such smart microorganisms remains challenging. In this review, we propose the concept of smart microbial engineering (SME) and describe the general features of basic SME, including the circuit architecture, components, and design process. We also summarize the latest SME achievements, remaining challenges, and potential solutions in this growing field.

Programmable T7-based synthetic transcription factors

Despite recent progress on synthetic transcription factor generation in eukaryotes, there remains a need for high-activity bacterial versions of these systems. In synthetic biology applications, it is useful for transcription factors to have two key features: they should be orthogonal (influencing only their own targets, with minimal off-target effects), and programmable (able to be directed to a wide range of user-specified transcriptional start sites). The RNA polymerase of the bacteriophage T7 has a number of appealing properties for synthetic biological designs: it can produce high transcription rates; it is a compact, single-subunit polymerase that has been functionally expressed in a variety of organisms; and its viral origin reduces the connection between its activity and that of its host's transcriptional machinery. We have created a system where a T7 RNA polymerase is recruited to transcriptional start sites by DNA binding proteins, either directly or bridged through protein–protein interactions, yielding a modular and programmable system for strong transcriptional activation of multiple orthogonal synthetic transcription factor variants in Escherichia coli. To our knowledge this is the first exogenous, programmable activator system in bacteria.

Synthetic evolution

The combination of modern biotechnologies such as DNA synthesis, λ red recombineering, CRISPR-based editing and next-generation high-throughput sequencing increasingly enables precise manipulation of genes and genomes. Beyond rational design, these technologies also enable the targeted, and potentially continuous, introduction of multiple mutations. While this might seem to be merely a return to natural selection, the ability to target evolution greatly reduces fitness burdens and focuses mutation and selection on those genes and traits that best contribute to a desired phenotype, ultimately throwing evolution into fast forward.

Synthetic biology for evolutionary engineering: from perturbation of genotype to acquisition of desired phenotype

With the increased attention on bio-based industry, demands for techniques that enable fast and effective strain improvement have been dramatically increased. Evolutionary engineering, which is less dependent on biological information, has been applied to strain improvement. Currently, synthetic biology has made great innovations in evolutionary engineering, particularly in the development of synthetic tools for phenotypic perturbation. Furthermore, discovering biological parts with regulatory roles and devising novel genetic circuits have promoted high-throughput screening and selection. In this review, we first briefly explain basics of synthetic biology tools for mutagenesis and screening of improved variants, and then describe how these strategies have been improved and applied to phenotypic engineering. Evolutionary engineering using advanced synthetic biology tools will enable further innovation in phenotypic engineering through the development of novel genetic parts and assembly into well-designed logic circuits that perform complex tasks.

Novel Hybrid Input Part Using Riboswitch and Transcriptional Repressor for Signal Inverting Amplifier

Genetic circuits are composed of input, logic, and output parts. Construction of complex circuits for practical applications requires numerous tunable genetic parts. However, the limited diversity and complicated tuning methods used for the input parts hinders the scalability of genetic circuits. Therefore, a new type of input part is required that responds to diverse signals and enables easy tuning. Here, we developed RNA-protein hybrid input parts that combine a riboswitch and orthogonal transcriptional repressors. The hybrid inputs successfully regulated the transcription of an output in response to the input signal detected by the riboswitch and resulted in signal inversion because of the expression of transcriptional repressors. Dose-response parameters including fold-change and half-maximal effective concentration were easily modulated and amplified simply by changing the promoter strength. Furthermore, the hybrid input detected both exogenous and endogenous signals, indicating potential applications in metabolite sensing. This hybrid input part could be highly extensible considering the rich variety of components.