High-throughput enzyme evolution in Saccharomyces cerevisiae using a synthetic RNA switch

A hybrid RNA-protein biosensor for high-throughput screening of adenosylcobalamin biosynthesis

Genetically encoded circuits have been successfully utilized to assess and characterize target variants with desirable traits from large mutant libraries. Adenosylcobalamin is an essential coenzyme that is required in many intracellular physiological reactions and is widely used in the pharmaceutical and food industries. High-throughput screening techniques capable of detecting adenosylcobalamin productivity and selecting superior adenosylcobalamin biosynthesis strains are critical for the creation of an effective microbial cell factory for the production of adenosylcobalamin at an industrial level. In this study, we developed an RNA-protein hybrid biosensor whose input part was an endogenous RNA riboswitch to specifically respond to adenosylcobalamin, the inverter part was an orthogonal transcriptional repressor to obtain signal inversion, and the output part was a fluorescent protein to be easily detected. The hybrid biosensor could specifically and positively correlate adenosylcobalamin concentrations to green fluorescent protein expression levels in vivo. This study also improved the operating concentration and dynamic range of the hybrid biosensor by systematic optimization. An individual cell harboring the hybrid biosensor presented over 20-fold higher fluorescence intensity than the negative control. Then, using such a biosensor combined with fluorescence-activated cell sorting, we established a high-throughput screening platform for screening adenosylcobalamin overproducers. This study demonstrates that this platform has significant potential to quickly isolate high-productive strains to meet industrial demand and that the framework is acceptable for various metabolites.

A Robust Growth-Based Selection Platform to Evolve an Enzyme via Dependency on Noncanonical Tyrosine Analogues

Growth-based selections evaluate the fitness of individual organisms at a population level. In enzyme engineering, such growth selections allow for the rapid and straightforward identification of highly efficient biocatalysts from extensive libraries. However, selection-based improvement of (synthetically useful) biocatalysts is challenging, as they require highly dependable strategies that artificially link their activities to host survival. Here, we showcase a robust and scalable growth-based selection platform centered around the complementation of noncanonical amino acid-dependent bacteria. Specifically, we demonstrate how serial passaging of populations featuring millions of carbamoylase variants autonomously selects biocatalysts with up to 90,000-fold higher initial rates. Notably, selection of replicate populations enriched diverse biocatalysts, which feature distinct amino acid motifs that drastically boost carbamoylase activity. As beneficial substitutions also originated from unintended copying errors during library preparation or cell division, we anticipate that our growth-based selection platform will be applicable to the continuous, autonomous evolution of diverse biocatalysts in the future.

Biosensor-guided discovery and engineering of metabolic enzymes

A variety of chemicals have been produced through metabolic engineering approaches, and enhancing biosynthesis performance can be achieved by using enzymes with high catalytic efficiency. Accordingly, a number of efforts have been made to discover enzymes in nature for various applications. In addition, enzyme engineering approaches have been attempted to suit specific industrial purposes. However, a significant challenge in enzyme discovery and engineering is the efficient screening of enzymes with the desired phenotype from extensive enzyme libraries. To overcome this bottleneck, genetically encoded biosensors have been developed to specifically detect target molecules produced by enzyme activity at the intracellular level. Especially, the biosensors facilitate high-throughput screening (HTS) of targeted enzymes, expanding enzyme discovery and engineering strategies with advances in systems and synthetic biology. This review examines biosensor-guided HTS systems and highlights studies that have utilized these tools to discover enzymes in diverse areas and engineer enzymes to enhance their properties, such as catalytic efficiency, specificity, and stability.

A Rapid Antibody Enhancement Platform in Saccharomyces cerevisiae Using an Improved, Diversifying CRISPR Base Editor

The yeast Saccharomyces cerevisiae is commonly used to interrogate and screen protein variants and to perform directed evolution studies to develop proteins with enhanced features. While several techniques have been described that help enable the use of yeast for directed evolution, there remains a need to increase their speed and ease of use. Here we present yDBE, a yeast diversifying base editor that functions in vivo and employs a CRISPR-dCas9-directed cytidine deaminase base editor to diversify DNA in a targeted, rapid, and high-breadth manner. To develop yDBE, we enhanced the mutation rate of an initial base editor by employing improved deaminase variants and characterizing several scaffolded guide constructs. We then demonstrate the ability of the yDBE platform to improve the affinity of a displayed antibody scFv, rapidly generating diversified libraries and isolating improved binders via cell sorting. By performing high-throughput sequencing analysis of the high-activity yDBE, we show that it enables a mutation rate of 2.13 × 10-4 substitutions/bp/generation over a window of 100 bp. As yDBE functions entirely in vivo and can be easily programmed to diversify nearly any such window of DNA, we posit that it can be a powerful tool for facilitating a variety of directed evolution experiments.

Growth-coupled high throughput selection for directed enzyme evolution

Directed enzyme evolution has revolutionized the rapid development of enzymes with desired properties. However, the lack of a high-throughput method to identify the most suitable variants from a large pool of genetic diversity poses a major bottleneck. To overcome this challenge, growth-coupled in vivo high-throughput selection approaches (GCHTS) have emerged as a novel selection system for enzyme evolution. GCHTS links the survival of the host cell with the properties of the target protein, resulting in a screening system that is easily measurable and has a high throughput-scale limited only by transformation efficiency. This allows for the rapid identification of desired variants from a pool of >109 variants in each experiment. In recent years, GCHTS approaches have been extensively utilized in the directed evolution of multiple enzymes, demonstrating success in catalyzing non-native substrates, enhancing catalytic activity, and acquiring novel functions. This review introduces three main strategies employed to achieve GCHTS: the elimination of toxic compounds via desired variants, enabling host cells to thrive in hazardous conditions; the complementation of an auxotroph with desired variants, where essential genes for cell growth have been eliminated; and the control of the transcription or expression of a reporter gene related to host cell growth, regulated by the desired variants. Additionally, we highlighted the recent developments in the in vivo continuous evolution of enzyme technology, including phage-assisted continuous evolution (PACE) and orthogonal DNA Replication (OrthoRep). Furthermore, this review discusses the challenges and future prospects in the field of growth-coupled selection for protein engineering.

Genetically Encoded Biosensor Engineering for Application in Directed Evolution

Although rational genetic engineering is nowadays the favored method for microbial strain improvement, building up mutant libraries based on directed evolution for improvement is still in many cases the better option. In this regard, the demand for precise and efficient screening methods for mutants with high performance has stimulated the development of biosensor-based high-throughput screening strategies. Genetically encoded biosensors provide powerful tools to couple the desired phenotype to a detectable signal, such as fluorescence and growth rate. Herein, we review recent advances in engineering several classes of biosensors and their applications in directed evolution. Furthermore, we compare and discuss the screening advantages and limitations of two-component biosensors, transcription-factor-based biosensors, and RNA-based biosensors. Engineering these biosensors has focused mainly on modifying the expression level or structure of the biosensor components to optimize the dynamic range, specificity, and detection range. Finally, the applications of biosensors in the evolution of proteins, metabolic pathways, and genome-scale metabolic networks are described. This review provides potential guidance in the design of biosensors and their applications in improving the bioproduction of microbial cell factories through directed evolution.

Riboswitches, from cognition to transformation

Riboswitches are functional RNA elements that regulate gene expression by directly detecting metabolites. Twenty years have passed since it was first discovered, researches on riboswitches are becoming increasingly standardized and refined, which could significantly promote people's cognition of RNA function as well. Here, we focus on some representative orphan riboswitches, enumerate the structural and functional transformation and artificial design of riboswitches including the coupling with ribozymes, hoping to attain a comprehensive understanding of riboswitch research.

The Establishment of a Tobramycin-Responsive Whole-Cell Micro-Biosensor Based on an Artificial Ribozyme Switch

In this study, a tobramycin concentration-dependent whole-cell micro-biosensor (tob-HHAz) was constructed by fusing a tobramycin aptamer with a hammerhead ribozyme (HHR) from Schistosoma mansoni. The biosensor was obtained by integrating all the modules into one complete RNA sequence, which was easily introduced into E. coli without suffering from harsh external environments. Three independent tobramycin-sensitive RNA structures were identified via high-throughput screening in vivo and were further verified in vitro to undergo the desired self-cleavage reaction. The computation prediction of the RNA structure was performed to help analyze the mechanisms of various conformations by performing a qualitative and rapid detection of tobramycin in practical samples; two sensors exhibited high responsiveness to spiked milk, with a detection limit of around 40 nM, which is below the EU's antibiotic maximum residual level. One of the structures provides a linear range from 30 to 650 nM with a minimum detection limit of 30 nM and showed relatively good selectivity in spiked urine. This study is the first in which in vivo screening was combined with computation analysis to optimize the pivotal structure of sensors. This strategy enables researchers to use artificial ribozyme-based biosensors not only for antibiotic detection but also as a generally applicable method for the further detection of substances in living cells.

Real-Time Assessment of Intracellular Metabolites in Single Cells through RNA-Based Sensors

Quantification of the concentration of particular cellular metabolites reports on the actual utilization of metabolic pathways in physiological and pathological conditions. Metabolite concentration also constitutes the readout for screening cell factories in metabolic engineering. However, there are no direct approaches that allow for real-time assessment of the levels of intracellular metabolites in single cells. In recent years, the modular architecture of natural bacterial RNA riboswitches has inspired the design of genetically encoded synthetic RNA devices that convert the intracellular concentration of a metabolite into a quantitative fluorescent signal. These so-called RNA-based sensors are composed of a metabolite-binding RNA aptamer as the sensor domain, connected through an actuator segment to a signal-generating reporter domain. However, at present, the variety of available RNA-based sensors for intracellular metabolites is still very limited. Here, we go through natural mechanisms for metabolite sensing and regulation in cells across all kingdoms, focusing on those mediated by riboswitches. We review the design principles underlying currently developed RNA-based sensors and discuss the challenges that hindered the development of novel sensors and recent strategies to address them. We finish by introducing the current and potential applicability of synthetic RNA-based sensors for intracellular metabolites.

Synthetic biology-based bioreactor and its application in biochemical analysis

In the past few years, synthetic biologists have established some biological elements and bioreactors composed of nucleotides under the guidance of engineering methods. Following the concept of engineering, the common bioreactor components in recent years are introduced and compared. At present, biosensors based on synthetic biology have been applied to water pollution monitoring, disease diagnosis, epidemiological monitoring, biochemical analysis and other detection fields. In this paper, the biosensor components based on synthetic bioreactors and reporters are reviewed. In addition, the applications of biosensors based on cell system and cell-free system in the detection of heavy metal ions, nucleic acid, antibiotics and other substances are presented. Finally, the bottlenecks faced by biosensors and the direction of optimization are also discussed.

Selecting Better Biocatalysts by Complementing Recoded Bacteria

In vivo selections are powerful tools for the directed evolution of enzymes. However, the need to link enzymatic activity to cellular survival makes selections for enzymes that do not fulfill a metabolic function challenging. Here, we present an in vivo selection strategy that leverages recoded organisms addicted to non-canonical amino acids (ncAAs) to evolve biocatalysts that can provide these building blocks from synthetic precursors. We exemplify our platform by engineering carbamoylases that display catalytic efficiencies more than five orders of magnitude higher than those observed for the wild-type enzyme for ncAA-precursors. As growth rates of bacteria under selective conditions correlate with enzymatic activities, we were able to elicit improved variants from populations by performing serial passaging. By requiring minimal human intervention and no specialized equipment, we surmise that our strategy will become a versatile tool for the in vivo directed evolution of diverse biocatalysts.

Advances in riboswitch-based biosensor as food samples detection tool

Food safety has always been a hot issue of social concern, and biosensing has been widely used in the field of food safety detection. Compared with traditional aptamer-based biosensors, aptamer-based riboswitch biosensing represents higher precision and programmability. A riboswitch is an elegant example of controlling gene expression, where the target is coupled to the aptamer domain, resulting in a conformational change in the downstream expression domain and determining the signal output. Riboswitch-based biosensing can be extensively applied to the portable real-time detection of food samples. The numerous key features of riboswitch-based biosensing emphasize their sustainability, renewable, and testing, which promises to transform engineering applications in the field of food safety. This review covers recent developments in riboswitch-based biosensors. The brief history, definition, and modular design (regulatory mode, reporter, and expression platform) of riboswitch-based biosensors are explained for better insight into the design and construction. We summarize recent advances in various riboswitch-based biosensors involving theophylline, malachite green, tetracycline, neomycin, fluoride, thrombin, naringenin, ciprofloxacin, and paromomycin, aiming to provide general guidance for the design of riboswitch-based biosensors. Finally, the challenges and prospects are also summarized as a way forward stratagem and signs of progress.

Droplet Detection and Sorting System in Microfluidics: A Review

Since being invented, droplet microfluidic technologies have been proven to be perfect tools for high-throughput chemical and biological functional screening applications, and they have been heavily studied and improved through the past two decades. Each droplet can be used as one single bioreactor to compartmentalize a big material or biological population, so millions of droplets can be individually screened based on demand, while the sorting function could extract the droplets of interest to a separate pool from the main droplet library. In this paper, we reviewed droplet detection and active sorting methods that are currently still being widely used for high-through screening applications in microfluidic systems, including the latest updates regarding each technology. We analyze and summarize the merits and drawbacks of each presented technology and conclude, with our perspectives, on future direction of development.

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.

Fluorescence-Activated Cell Sorting as a Tool for Recombinant Strain Screening

Metabolic engineering of microbial cells is the discipline of optimizing microbial metabolism to enable and improve the production of target molecules ranging from biofuels and chemical building blocks to high-value pharmaceuticals. The advances in genetic engineering have eased the construction of highly engineered microbial strains and the generation of genetic libraries. Intracellular metabolite-responsive biosensors facilitate high-throughput screening of these libraries by connecting the levels of a metabolite of interest to a fluorescence output. Fluorescent-activated cell sorting (FACS) enables the isolation of highly fluorescent single cells and thus genotypes that produce higher levels of the metabolite of interest. Here, we describe a high-throughput screening method for recombinant yeast strain screening based on intracellular biosensors and FACS.

Saccharomyces cerevisiae as a Heterologous Host for Natural Products

Cell factories can provide a sustainable supply of natural products with applications as pharmaceuticals, food-additives or biofuels. Besides being an important model organism for eukaryotic systems, Saccharomyces cerevisiae is used as a chassis for the heterologous production of natural products. Its success as a cell factory can be attributed to the vast knowledge accumulated over decades of research, its overall ease of engineering and its robustness. Many methods and toolkits have been developed by the yeast metabolic engineering community with the aim of simplifying and accelerating the engineering process.In this chapter, a range of methodologies are highlighted, which can be used to develop novel natural product cell factories or to improve titer, rate and yields of an existing cell factory with the goal of developing an industrially relevant strain. The addressed topics are applicable for different stages of a cell factory engineering project and include the choice of a natural product platform strain, expression cassette design for heterologous or native genes, basic and advanced genetic engineering strategies, and library screening methods using biosensors. The many engineering methods available and the examples of yeast cell factories underline the importance and future potential of this host for industrial production of natural products.

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.

Directed Evolution Methods for Enzyme Engineering

Enzymes underpin the processes required for most biotransformations. However, natural enzymes are often not optimal for biotechnological uses and must be engineered for improved activity, specificity and stability. A rich and growing variety of wet-lab methods have been developed by researchers over decades to accomplish this goal. In this review such methods and their specific attributes are examined.

Optimization of protein trans-splicing in an inducible plasmid display system for high-throughput screening and selection of soluble proteins

Directed evolution is widely used to optimize protein folding and solubility in cells. Although the screening and selection of desired mutants is an essential step in directed evolution, it generally requires laborious optimization and/or specialized equipment. With a view toward designing a more practical procedure, we previously developed an inducible plasmid display system, in which the intein (auto-processing) and Oct-1 DNA-binding (DBD) domains were used as the protein trans-splicing domain and DNA-binding module, respectively. Specifically, the N-terminal (CfaN) and C-terminal (CfaC) domains of intein were fused to the C-terminal end of the His-tag and the N-terminal end of Oct-1 DBD to generate His₆-CfaN and CfaC-Oct-1, respectively. For such a system to be viable, the efficiency of protein trans-splicing without the protein of interest (POI) should be maximized, such that the probability of occurrence is solely dependent on the solubility of the POI. To this end, we initially prevented the degradation of l-arabinose (the inducer of the P_BAD promoter) by employing an Escherichia coli host strain deficient in the metabolism of l-arabinose. Given that a low expression of His₆-CfaN, compared with that of CfaC-Oct-1, was found to be conducive to the generation to a soluble product of the protein trans-splicing event, we designed the expression of His₆-CfaN and CfaC-Oct-1 to be inducible from the P_BAD and P_T7 promoters, respectively. The optimized system thus obtained enabled in vitro selection of the plasmid-protein complex with high yield. We believe that the inducible plasmid display system developed in this study would be applicable to high-throughput screening and/or selection of protein variants with enhanced solubility.

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.

A convolutional neural network for the prediction and forward design of ribozyme-based gene-control elements

Ribozyme switches are a class of RNA-encoded genetic switch that support conditional regulation of gene expression across diverse organisms. An improved elucidation of the relationships between sequence, structure, and activity can improve our capacity for de novo rational design of ribozyme switches. Here, we generated data on the activity of hundreds of thousands of ribozyme sequences. Using automated structural analysis and machine learning, we leveraged these large data sets to develop predictive models that estimate the in vivo gene-regulatory activity of a ribozyme sequence. These models supported the de novo design of ribozyme libraries with low mean basal gene-regulatory activities and new ribozyme switches that exhibit changes in gene-regulatory activity in the presence of a target ligand, producing functional switches for four out of five aptamers. Our work examines how biases in the model and the data set that affect prediction accuracy can arise and demonstrates that machine learning can be applied to RNA sequences to predict gene-regulatory activity, providing the basis for design tools for functional RNAs.

Applications of flow cytometry sorting in the pharmaceutical industry: A review

The article reviews applications of flow cytometry sorting in manufacturing of pharmaceuticals. Flow cytometry sorting is an extremely powerful tool for monitoring, screening and separating single cells based on any property that can be measured by flow cytometry. Different applications of flow cytometry sorting are classified into groups and discussed in separate sections as follows: (a) isolation of cell types, (b) high throughput screening, (c) cell surface display, (d) droplet fluorescent-activated cell sorting (FACS). Future opportunities are identified including: (a) sorting of particular fractions of the cell population based on a property of interest for generating inoculum that will result in improved outcomes of cell cultures and (b) the use of population balance models in combination with FACS to design and optimize cell cultures.

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.

Signal amplification and optimization of riboswitch-based hybrid inputs by modular and titratable toehold switches

BACKGROUND

Synthetic biological circuits are widely utilized to control microbial cell functions. Natural and synthetic riboswitches are attractive sensor modules for use in synthetic biology applications. However, tuning the fold-change of riboswitch circuits is challenging because a deep understanding of the riboswitch mechanism and screening of mutant libraries is generally required. Therefore, novel molecular parts and strategies for straightforward tuning of the fold-change of riboswitch circuits are needed.

RESULTS

In this study, we devised a toehold switch-based modulator approach that combines a hybrid input construct consisting of a riboswitch and transcriptional repressor and de-novo-designed riboregulators named toehold switches. First, the introduction of a pair of toehold switches and triggers as a downstream signal-processing module to the hybrid input for coenzyme B12 resulted in a functional riboswitch circuit. Next, several optimization strategies that focused on balancing the expression levels of the RNA components greatly improved the fold-change from 260- to 887-fold depending on the promoter and host strain. Further characterizations confirmed low leakiness and high orthogonality of five toehold switch pairs, indicating the broad applicability of this strategy to riboswitch tuning.

CONCLUSIONS

The toehold switch-based modulator substantially improved the fold-change compared to the previous sensors with only the hybrid input construct. The programmable RNA-RNA interactions amenable to in silico design and optimization can facilitate further development of RNA-based genetic modulators for flexible tuning of riboswitch circuitry and synthetic biosensors.

Aptamers, Riboswitches, and Ribozymes in S. cerevisiae Synthetic Biology

Among noncoding RNA sequences, riboswitches and ribozymes have attracted the attention of the synthetic biology community as circuit components for translation regulation. When fused to aptamer sequences, ribozymes and riboswitches are enabled to interact with chemicals. Therefore, protein synthesis can be controlled at the mRNA level without the need for transcription factors. Potentially, the use of chemical-responsive ribozymes/riboswitches would drastically simplify the design of genetic circuits. In this review, we describe synthetic RNA structures that have been used so far in the yeast Saccharomyces cerevisiae. We present their interaction mode with different chemicals (e.g., theophylline and antibiotics) or proteins (such as the RNase III) and their recent employment into clustered regularly interspaced short palindromic repeats–CRISPR-associated protein 9 (CRISPR-Cas) systems. Particular attention is paid, throughout the whole paper, to their usage and performance into synthetic gene circuits.

A multiplexed, automated evolution pipeline enables scalable discovery and characterization of biosensors

Biosensors are key components in engineered biological systems, providing a means of measuring and acting upon the large biochemical space in living cells. However, generating small molecule sensing elements and integrating them into in vivo biosensors have been challenging. Here, using aptamer-coupled ribozyme libraries and a ribozyme regeneration method, de novo rapid in vitro evolution of RNA biosensors (DRIVER) enables multiplexed discovery of biosensors. With DRIVER and high-throughput characterization (CleaveSeq) fully automated on liquid-handling systems, we identify and validate biosensors against six small molecules, including five for which no aptamers were previously found. DRIVER-evolved biosensors are applied directly to regulate gene expression in yeast, displaying activation ratios up to 33-fold. DRIVER biosensors are also applied in detecting metabolite production from a multi-enzyme biosynthetic pathway. This work demonstrates DRIVER as a scalable pipeline for engineering de novo biosensors with wide-ranging applications in biomanufacturing, diagnostics, therapeutics, and synthetic biology.

Biosensors are key to engineered biological systems. Here the authors demonstrate rapid de novo in vitro evolution of RNA biosensors of small molecules in a fully automated system.

High-throughput screening for high-efficiency small-molecule biosynthesis

Systems metabolic engineering faces the formidable task of rewiring microbial metabolism to cost-effectively generate high-value molecules from a variety of inexpensive feedstocks for many different applications. Because these cellular systems are still too complex to model accurately, vast collections of engineered organism variants must be systematically created and evaluated through an enormous trial-and-error process in order to identify a manufacturing-ready strain. The high-throughput screening of strains to optimize their scalable manufacturing potential requires execution of many carefully controlled, parallel, miniature fermentations, followed by high-precision analysis of the resulting complex mixtures. This review discusses strategies for the design of high-throughput, small-scale fermentation models to predict improved strain performance at large commercial scale. Established and promising approaches from industrial and academic groups are presented for both cell culture and analysis, with primary focus on microplate- and microfluidics-based screening systems.

Biosensors design in yeast and applications in metabolic engineering

Engineering microbial cell factories is a potential approach of sustainable production of chemicals, fuels and pharmaceuticals. However, testing the production of molecules in high throughput is still a time-consuming and laborious process since product synthesis usually does not confer a clear phenotype. Therefore, it is necessary to develop new techniques for fast high-producer screening. Genetically encoded biosensors are considered to be promising devices for high-throughput analysis owing to their ability to sense metabolites and couple detection to an actuator, thereby facilitating the rapid detection of small molecules at single-cell level. Here, we review recent advances in the design and engineering of biosensors in Saccharomyces cerevisiae, and their applications in metabolic engineering. Three types of biosensor are introduced in this review: transcription factor based, RNA-based and enzyme-coupled biosensors. The studies to improve the features of biosensors are also described. Moreover, we summarized their metabolic engineering applications in dynamic regulation and high producer selection. Current challenges in biosensor design and future perspectives on sensor applications are also discussed.

Developments of Riboswitches and Toehold Switches for Molecular Detection-Biosensing and Molecular Diagnostics

Riboswitches and toehold switches are considered to have potential for implementation in various fields, i.e., biosensing, metabolic engineering, and molecular diagnostics. The specific binding, programmability, and manipulability of these RNA-based molecules enable their intensive deployments in molecular detection as biosensors for regulating gene expressions, tracking metabolites, or detecting RNA sequences of pathogenic microorganisms. In this review, we will focus on the development of riboswitches and toehold switches in biosensing and molecular diagnostics. This review introduces the operating principles and the notable design features of riboswitches as well as toehold switches. Moreover, we will describe the advances and future directions of riboswitches and toehold switches in biosensing and molecular diagnostics.

The Theophylline Aptamer: 25 Years as an Important Tool in Cellular Engineering Research

The theophylline aptamer was isolated from an oligonucleotide library in 1994. Since that time, the aptamer has found wide utility, particularly in synthetic biology, cellular engineering, and diagnostic applications. The primary application of the theophylline aptamer is in the construction and characterization of synthetic riboswitches for regulation of gene expression. These riboswitches have been used to control cellular motility, regulate carbon metabolism, construct logic gates, screen for mutant enzymes, and control apoptosis. Other applications of the theophylline aptamer in cellular engineering include regulation of RNA interference and genome editing through CRISPR systems. Here we describe the uses of the theophylline aptamer for cellular engineering over the past 25 years. In so doing, we also highlight important synthetic biology applications to control gene expression in a ligand-dependent manner.

Intracellular Selection of Theophylline-Sensitive Hammerhead Aptazyme

Hammerhead ribozyme-based aptazyme (HHAz), inheriting the advantages of small size and high efficiency from the RNA-cleaving ribozyme and the specific recognition ability of aptamers to specific targets, exhibits the huge potential to be a transgene expression regulator. Herein, we report a selection strategy for HHAz by using a toxin protein IbsC as the reporter to offer a positive phenotype, thus realizing an easy-operating, time- and labor-saving selection of HHAz variants with desired properties. Based on this strategy, we obtained a new HHAz (TAP-1), which could react sensitively toward the extracellular regulatory molecule, theophylline, both in prokaryotic and eukaryotic systems. With fluorescent protein reporter, the intracellular switching efficiencies of TAP-1 and other reported theophylline-dependent HHAzs has been quantitatively evaluated, showing that TAP-1 not only exhibits the best downregulating ability at high concentration of theophylline but also maintains high activity with 0.1 mM theophylline, which is a safe concentration in the human body.

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.

5' untranslated regions: the next regulatory sequence in yeast synthetic biology

When developing industrial biotechnology processes, Saccharomyces cerevisiae (baker's yeast or brewer's yeast) is a popular choice as a microbial host. Many tools have been developed in the fields of synthetic biology and metabolic engineering to introduce heterologous pathways and tune their expression in yeast. Such tools mainly focus on controlling transcription, whereas post-transcriptional regulation is often overlooked. Herein we discuss regulatory elements found in the 5' untranslated region (UTR) and their influence on protein synthesis. We provide not only an overall picture, but also a set of design rules on how to engineer a 5' UTR. The reader is also referred to currently available models that allow gene expression to be tuned predictably using different 5' UTRs.

Adaptive walks on high-dimensional fitness landscapes and seascapes with distance-dependent statistics

The dynamics of evolution is intimately shaped by epistasis - interactions between genetic elements which cause the fitness-effect of combinations of mutations to be non-additive. Analyzing evolutionary dynamics that involves large numbers of epistatic mutations is intrinsically difficult. A crucial feature is that the fitness landscape in the vicinity of the current genome depends on the evolutionary history. A key step is thus developing models that enable study of the effects of past evolution on future evolution. In this work, we introduce a broad class of high-dimensional random fitness landscapes for which the correlations between fitnesses of genomes are a general function of genetic distance. Their Gaussian character allows for tractable computational as well as analytic understanding. We study the properties of these landscapes focusing on the simplest evolutionary process: random adaptive (uphill) walks. Conventional measures of "ruggedness" are shown to not much affect such adaptive walks. Instead, the long-distance statistics of epistasis cause all properties to be highly conditional on past evolution, determining the statistics of the local landscape (the distribution of fitness-effects of available mutations and combinations of these), as well as the global geometry of evolutionary trajectories. In order to further explore the effects of conditioning on past evolution, we model the effects of slowly changing environments. At long times, such fitness "seascapes" cause a statistical steady state with highly intermittent evolutionary dynamics: populations undergo bursts of rapid adaptation, interspersed with periods in which adaptive mutations are rare and the population waits for more new directions to be opened up by changes in the environment. Finally, we discuss prospects for studying more complex evolutionary dynamics and on broader classes of high-dimensional landscapes and seascapes.

Tools and systems for evolutionary engineering of biomolecules and microorganisms

Evolutionary approaches have been providing solutions to various bioengineering challenges in an efficient manner. In addition to traditional adaptive laboratory evolution and directed evolution, recent advances in synthetic biology and fluidic systems have opened a new era of evolutionary engineering. Synthetic genetic circuits have been created to control mutagenesis and enable screening of various phenotypes, particularly metabolite production. Fluidic systems can be used for high-throughput screening and multiplexed continuous cultivation of microorganisms. Moreover, continuous directed evolution has been achieved by combining all the steps of evolutionary engineering. Overall, modern tools and systems for evolutionary engineering can be used to establish the artificial equivalent to natural evolution for various research applications.

Genetic Selection for Small Molecule Production in Competitive Microfluidic Droplets

Biosensors can be used to screen or select for small molecule production in engineered microbes. However, mutations to the biosensor that interfere with accurate signal transduction are common, producing an excess of false positives. Strategies have been developed to avoid this limitation by physically separating the production pathway and biosensor, but these approaches have only been applied to screens, not selections. We have developed a novel biosensor-mediated selection strategy using competition between cocultured bacteria. When applied to the biosynthesis of cis,cis-muconate, we show that this strategy yields a selective advantage to producer strains that outweighs the costs of production. By encapsulating the competitive cocultures into microfluidic droplets, we successfully enriched the muconate-producing strains from a large population of control nonproducers. Facile selections for small molecule production will increase testing throughput for engineered microbes and allow for the rapid optimization of novel metabolic pathways.

Riboswitch identification using Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR)

In vitro selection of ligand-responsive ribozymes can identify rare, functional sequences from large libraries. While powerful, key caveats of this approach include lengthy and demanding experimental workflows; unpredictable experimental outcomes and unknown functionality of enriched sequences in vivo. To address the first of these limitations, we developed Ligase-Assisted Selection for the Enrichment of Responsive Ribozymes (LigASERR). LigASERR is scalable, amenable to automation and requires less time to implement compared to alternative methods. To improve the predictability of experiments, we modeled the underlying selection process, predicting experimental outcomes based on sequence and population parameters. We applied this new methodology and model to the enrichment of a known, in vitro-selected sequence from a bespoke library. Prior to implementing selection, conditions were optimized and target sequence dynamics accurately predicted for the majority of the experiment. In addition to enriching the target sequence, we identified two new, theophylline-activated ribozymes. Notably, all three sequences yielded riboswitches functional in Escherichia coli, suggesting LigASERR and similar in vitro selection methods can be utilized for generating functional riboswitches in this organism.

Synthetic biology strategies for microbial biosynthesis of plant natural products

Metabolic engineers endeavor to create a bio-based manufacturing industry using microbes to produce fuels, chemicals, and medicines. Plant natural products (PNPs) are historically challenging to produce and are ubiquitous in medicines, flavors, and fragrances. Engineering PNP pathways into new hosts requires finding or modifying a suitable host to accommodate the pathway, planning and implementing a biosynthetic route to the compound, and discovering or engineering enzymes for missing steps. In this review, we describe recent developments in metabolic engineering at the level of host, pathway, and enzyme, and discuss how the field is approaching ever more complex biosynthetic opportunities.

Caffeine-inducible gene switches controlling experimental diabetes

Programming cellular behavior using trigger-inducible gene switches is integral to synthetic biology. Although significant progress has been achieved in trigger-induced transgene expression, side-effect-free remote control of transgenes continues to challenge cell-based therapies. Here, utilizing a caffeine-binding single-domain antibody we establish a caffeine-inducible protein dimerization system, enabling synthetic transcription factors and cell-surface receptors that enable transgene expression in response to physiologically relevant concentrations of caffeine generated by routine intake of beverages such as tea and coffee. Coffee containing different caffeine concentrations dose-dependently and reversibly controlled transgene expression by designer cells with this caffeine-stimulated advanced regulators (C-STAR) system. Type-2 diabetic mice implanted with microencapsulated, C-STAR-equipped cells for caffeine-sensitive expression of glucagon-like peptide 1 showed substantially improved glucose homeostasis after coffee consumption compared to untreated mice. Biopharmaceutical production control by caffeine, which is non-toxic, inexpensive and only present in specific beverages, is expected to improve patient compliance by integrating therapy with lifestyle.

Directed evolution of the 3-hydroxypropionic acid production pathway by engineering aldehyde dehydrogenase using a synthetic selection device

3-Hydroxypropionic acid (3-HP) is an important platform chemical, and biological production of 3-HP from glycerol as a carbon source using glycerol dehydratase (GDHt) and aldehyde dehydrogenase (ALDH) has been revealed to be effective because it involves a relatively simple metabolic pathway and exhibits higher yield and productivity than other biosynthetic pathways. Despite the successful attempts of 3-HP production from glycerol, the biological process suffers from problems arising from low activity and inactivation of the two enzymes. To apply the directed evolutionary approach to engineer the 3-HP production system, we constructed a synthetic selection device using a 3-HP-responsive transcription factor and developed a selection approach for screening 3-HP-producing microorganisms. The method was applied to an ALDH library, specifically aldehyde-binding site library of alpha-ketoglutaric semialdehyde dehydrogenase (KGSADH). Only two serial cultures resulted in enrichment of strains showing increased 3-HP production, and an isolated KGSADH variant enzyme exhibited a 2.79-fold higher catalytic efficiency toward its aldehyde substrate than the wild-type one. This approach will provide the simple and efficient tool to engineer the pathway enzymes in metabolic engineering.

Synthetic biology strategies toward heterologous phytochemical production

This review summarizes the recent progress in heterologous phytochemical biosynthetic pathway reconstitution in plant, bacteria, and yeast, with a focus on the synthetic biology strategies applied in these engineering efforts.

Genetic tool development and systemic regulation in biosynthetic technology

With the increased development in research, innovation, and policy interest in recent years, biosynthetic technology has developed rapidly, which combines engineering, electronics, computer science, mathematics, and other disciplines based on classical genetic engineering and metabolic engineering. It gives a wider perspective and a deeper level to perceive the nature of life via cell mechanism, regulatory networks, or biological evolution. Currently, synthetic biology has made great breakthrough in energy, chemical industry, and medicine industries, particularly in the programmable genetic control at multiple levels of regulation to perform designed goals. In this review, the most advanced and comprehensive developments achieved in biosynthetic technology were represented, including genetic engineering as well as synthetic genomics. In addition, the superiority together with the limitations of the current genome-editing tools were summarized.

RNA-based dynamic genetic controllers: development strategies and applications

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Unique properties of RNA lead to the development of RNA-based dynamic genetic controllers.

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Natural riboswitches are re-engineered to detect new molecules.

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RNA-based regulatory mechanisms are exploited to construct novel dynamic RNA controllers.

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Computational methods and in vitro–in vivo selection enable de novo design of dynamic RNA controllers.

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Dynamic RNA controllers are utilized for metabolic engineering and synthetic biology.

Dynamic regulation of gene expression in response to various molecules is crucial for both basic science and practical applications. RNA is considered an attractive material for creating dynamic genetic controllers because of its specific binding to ligands, structural flexibility, programmability, and small size. Here, we review recent advances in strategies for developing RNA-based dynamic controllers and applications. First, we describe studies that re-engineered natural riboswitches to generate new dynamic controllers. Next, we summarize RNA-based regulatory mechanisms that have been exploited to build novel artificial dynamic controllers. We also discuss computational methods and high-throughput selection approaches for de novo design of dynamic RNA controllers. Finally, we explain applications of dynamic RNA controllers for metabolic engineering and synthetic biology.

Development of a Bacterial Biosensor for Rapid Screening of Yeast p-Coumaric Acid Production

Transcription factor-based biosensors are used to identify producer strains, a critical bottleneck in cell factory engineering. Here, we address two challenges with this methodology: transplantation of heterologous transcriptional regulators into new hosts to generate functional biosensors and biosensing of the extracellular product concentration that accurately reflects the effective cell factory production capacity. We describe the effects of different translation initiation rates on the dynamic range of a p-coumaric acid biosensor based on the Bacillus subtilis transcriptional repressor PadR by varying its ribosomal binding site. Furthermore, we demonstrate the functionality of this p-coumaric acid biosensor in Escherichia coli and Corynebacterium glutamicum. Finally, we encapsulate yeast p-coumaric acid-producing cells with E. coli-biosensing cells in picoliter droplets and, in a microfluidic device, rapidly sort droplets containing yeast cells producing high amounts of extracellular p-coumaric acid using the fluorescent E. coli biosensor signal. As additional biosensors become available, such approaches will find broad applications for screening of an extracellular product.

Pathway optimization and key enzyme evolution of N-acetylneuraminate biosynthesis using an in vivo aptazyme-based biosensor

N-acetylneuraminate (NeuAc) biosynthesis has drawn much attention owing to its wide applications in many aspects. Previously, we engineered for the first time an artificial NeuAc biosynthetic pathway in Escherichia coli using glucose as sole substrate. However, rigorous requirements for the flux and cofactor balance make subsequent strain improvement rather difficult. In this study, an in vivo NeuAc biosensor was designed and applied for genetic screening the mutant library of NeuAc producer. Its NeuAc responsive manner was demonstrated using sfgfp as a reporter and a Ni²⁺-based selection system was developed to couple the cell growth with in vivo NeuAc concentration. Employing this selection system, the NeuAc biosynthesis pathway was optimized and the key enzyme NeuAc synthase was evolved, which improved the titer by 34% and 23%, respectively. The final strain produced up to 8.31g/L NeuAc in minimal medium using glucose as sole carbon source. This work demonstrated the effectiveness of NeuAc biosensor in genetic screening and great potential in metabolic engineering of other organisms.

Enabling tools for high-throughput detection of metabolites: Metabolic engineering and directed evolution applications

Within the Design-Build-Test Cycle for strain engineering, rapid product detection and selection strategies remain challenging and limit overall throughput. Here we summarize a wide variety of modalities that transduce chemical concentrations into easily measured absorbance, luminescence, and fluorescence signals. Specifically, we cover protein-based biosensors (including transcription factors), nucleic acid-based biosensors, coupled enzyme reactions, bioorthogonal chemistry, and fluorescent and chromogenic dyes and substrates as modalities for detection. We focus on the use of these methods for strain engineering and enzyme discovery and conclude with remarks on the current and future state of biosensor development for application in the metabolic engineering field.