Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways

Controlled exchange of protein and nucleic acid signals from and between synthetic minimal cells

Synthetic minimal cells are a class of bioreactors that have some, but not all, functions of live cells. Here, we report a critical step toward the development of a bottom-up minimal cell: cellular export of functional protein and RNA products. We used cell-penetrating peptide tags to translocate payloads across a synthetic cell vesicle membrane. We demonstrated efficient transport of active enzymes and transport of nucleic acid payloads by RNA-binding proteins. We investigated influence of a concentration gradient alongside other factors on the efficiency of the translocation, and we show a method to increase product accumulation in one location. We demonstrate the use of this technology to engineer molecular communication between different populations of synthetic cells, to exchange protein and nucleic acid signals. The synthetic minimal cell production and export of proteins or nucleic acids allows experimental designs that approach the complexity and relevancy of natural biological systems. A record of this paper's transparent peer review process is included in the supplemental information.

Genetic Circuits for Feedback Control of Gamma-Aminobutyric Acid Biosynthesis in Probiotic Escherichia coli Nissle 1917

Engineered microorganisms such as the probiotic strain Escherichia coli Nissle 1917 (EcN) offer a strategy to sense and modulate the concentration of metabolites or therapeutics in the gastrointestinal tract. Here, we present an approach to regulate the production of the depression-associated metabolite gamma-aminobutyric acid (GABA) in EcN using genetic circuits that implement negative feedback. We engineered EcN to produce GABA by overexpressing glutamate decarboxylase and applied an intracellular GABA biosensor to identify growth conditions that improve GABA biosynthesis. We next employed characterized genetically encoded NOT gates to construct genetic circuits with layered feedback to control the rate of GABA biosynthesis and the concentration of GABA produced. Looking ahead, this approach may be utilized to design feedback control of microbial metabolite biosynthesis to achieve designable smart microbes that act as living therapeutics.

Bacterial glycobiotechnology: A biosynthetic route for the production of biopharmaceutical glycans

The recent advancement in the human glycome and progress in the development of an inclusive network of glycosylation pathways allow the incorporation of suitable machinery for protein modification in non-natural hosts and explore novel opportunities for constructing next-generation tailored glycans and glycoconjugates. Fortunately, the emerging field of bacterial metabolic engineering has enabled the production of tailored biopolymers by harnessing living microbial factories (prokaryotes) as whole-cell biocatalysts. Microbial catalysts offer sophisticated means to develop a variety of valuable polysaccharides in bulk quantities for practical clinical applications. Glycans production through this technique is highly efficient and cost-effective, as it does not involve expensive initial materials. Metabolic glycoengineering primarily focuses on utilizing small metabolite molecules to alter biosynthetic pathways, optimization of cellular processes for glycan and glycoconjugate production, characteristic to a specific organism to produce interest tailored glycans in microbes, using preferably cheap and simple substrate. However, metabolic engineering faces one of the unique challenges, such as the need for an enzyme to catalyze desired substrate conversion when natural native substrates are already present. So, in metabolic engineering, such challenges are evaluated, and different strategies have been developed to overcome them. The generation of glycans and glycoconjugates via metabolic intermediate pathways can still be supported by glycol modeling achieved through metabolic engineering. It is evident that modern glycans engineering requires adoption of improved strain engineering strategies for creating competent glycoprotein expression platforms in bacterial hosts, in the future. These strategies include logically designing and introducing orthogonal glycosylation pathways, identifying metabolic engineering targets at the genome level, and strategically improving pathway performance (for example, through genetic modification of pathway enzymes). Here, we highlight current strategies, applications, and recent progress in metabolic engineering for producing high-value tailored glycans and their applications in biotherapeutics and diagnostics.

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

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

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.

Mass Spectrometry-Based High-Throughput Quantification of Bioproducts in Liquid Culture

To meet the ever-increasing need for high-throughput screening in metabolic engineering, information-rich, fast screening methods are needed. Mass spectrometry (MS) provides an efficient and general approach for metabolite screening and offers the capability of characterizing a broad range of analytes in a label-free manner, but often requires a range of sample clean-up and extraction steps. Liquid extraction surface analysis (LESA) coupled MS is an image-guided MS surface analysis approach that directly samples and introduces metabolites from a surface to MS. Here, we combined the advantages of LESA-MS and an acoustic liquid handler with stable isotope-labeled internal standards. This approach provides absolute quantitation of target chemicals from liquid culture-dried droplets and enables high-throughput quantitative screening for microbial metabolites. In this study, LESA-MS was successfully applied to quantify several different metabolites (itaconic acid, triacetic acid lactone, and palmitic acid) from different yeast strains in different mediums, demonstrating its versatility, accuracy, and efficiency across a range of microbial engineering applications.

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.

Adaptive Optimization Boosted the Production of Moenomycin A in the Microbial Chassis Streptomyces albus J1074

Great efforts have been made to improve Streptomyces chassis for efficient production of targeted natural products. Moenomycin family antibiotics, represented by moenomycin (Moe) and nosokomycin, are phosphoglycolipid antibiotics that display extraordinary inhibition against Gram-positive bacteria. Herein, we assembled a completed 34 kb hybrid biosynthetic gene cluster (BGC) of moenomycin A (moe-BGC) based on a 24 kb nosokomycin analogue biosynthetic gene cluster (noso-BGC). The heterologous expression of the hybrid moe-BGC in Streptomyces albus J1074 achieved the production of moenomycin A in the recombinant strain LX01 with a yield of 12.1 ± 2 mg/L. Further strong promoter refactoring to improve the transcriptional levels of all of the functional genes in strain LX02 enhanced the production of moenomycin A by 58%. However, the yield improvement of moenomycin A resulted in a dramatic 38% decrease in the chassis biomass compared with the control strain. To improve the weak physiological tolerance to moenomycin A of the chassis, another copy of the gene salb-PBP2 (P238N&F200D), encoding peptidoglycan biosynthetic protein PBP2, was introduced into the chassis strain, producing strain LX03. Cell growth was restored, and the fermentation titer of moenomycin A was 130% higher than that of LX01. Additionally, the production of moenomycin A in strain LX03 was further elevated by 45% to 40.0 ± 3 mg/L after media optimization. These results suggested that the adaptive optimization strategy of strong promoter refactoring in the BGC plus physiological tolerance in the chassis was an efficient approach for obtaining the desired natural products with high titers.

Synthetic biology-inspired strategies and tools for engineering of microbial natural product biosynthetic pathways

Microbial-derived natural products (NPs) and their derivative products are of great importance and used widely in many fields, especially in pharmaceutical industries. However, there is an immediate need to establish innovative approaches, strategies, and techniques to discover new NPs with novel or enhanced biological properties, due to the less productivity and higher cost on traditional drug discovery pipelines from natural bioresources. Revealing of untapped microbial cryptic biosynthetic gene clusters (BGCs) using DNA sequencing technology and bioinformatics tools makes genome mining possible for NP discovery from microorganisms. Meanwhile, new approaches and strategies in the area of synthetic biology offer great potentials for generation of new NPs by engineering or creating synthetic systems with improved and desired functions. Development of approaches, strategies and tools in synthetic biology can facilitate not only exploration and enhancement in supply, and also in the structural diversification of NPs. Here, we discussed recent advances in synthetic biology-inspired strategies, including bioinformatics and genetic engineering tools and approaches for identification, cloning, editing/refactoring of candidate biosynthetic pathways, construction of heterologous expression hosts, fitness optimization between target pathways and hosts and detection of NP production.

Recent progress in natural product-based inhibitor screening with enzymatic fluorescent probes

Drug discovery is a complex process in which many challenges need to be overcome, from the discovery of a drug candidate to ensuring the efficacy and safety of the candidate in humans. Modern analytical methods allow tens of thousands of drug candidates to be screened for their inhibition of specific enzymes or receptors. In recent years, fluorescent probes have been used for the detection and diagnosis of human pathogens as well as high-throughput screening. This review focuses on recent progress in organic small-molecule based enzyme-activated fluorescent probes for screening of inhibitors from natural products. The contents include the construction of fluorescent probes, working mechanism and the process of inhibitor screening. The progress suggests that fluorescent probes are a vital and rapidly growing technology for inhibitor screening of enzymes, in particular, inhibitor screening in situ.

Cell-based high-throughput screening of polysaccharide biosynthesis hosts

Valuable polysaccharides are usually produced using wild-type or metabolically-engineered host microbial strains through fermentation. These hosts act as cell factories that convert carbohydrates, such as monosaccharides or starch, into bioactive polysaccharides. It is desirable to develop effective in vivo high-throughput approaches to screen cells that display high-level synthesis of the desired polysaccharides. Uses of single or dual fluorophore labeling, fluorescence quenching, or biosensors are effective strategies for cell sorting of a library that can be applied during the domestication of industrial engineered strains and metabolic pathway optimization of polysaccharide synthesis in engineered cells. Meanwhile, high-throughput screening strategies using each individual whole cell as a sorting section are playing growing roles in the discovery and directed evolution of enzymes involved in polysaccharide biosynthesis, such as glycosyltransferases. These enzymes and their mutants are in high demand as tool catalysts for synthesis of saccharides in vitro and in vivo. This review provides an introduction to the methodologies of using cell-based high-throughput screening for desired polysaccharide-biosynthesizing cells, followed by a brief discussion of potential applications of these approaches in glycoengineering.

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.

Engineering an Optogenetic CRISPRi Platform for Improved Chemical Production

Microbial synthesis of chemicals typically requires the redistribution of metabolic flux toward the synthesis of targeted products. Dynamic control is emerging as an effective approach for solving the hurdles mentioned above. As light could control the cell behavior in a spatial and temporal manner, the optogenetic-CRISPR interference (opto-CRISPRi) technique that allocates the metabolic resources according to different optical signal frequencies will enable bacteria to be controlled between the growth phase and the production stage. In this study, we applied a blue light-sensitive protein EL222 to regulate the expression of the dCpf1-mediated CRISPRi system that turns off the competitive pathways and redirects the metabolic flux toward the heterologous muconic acid synthesis in Escherichia coli. We found that the opto-CRISPRi system dynamically regulating the suppression of the central metabolism and competitive pathways could increase the muconic acid production by 130%. These results demonstrated that the opto-CRISPRi platform is an effective method for enhancing chemical synthesis with broad utilities.

An overview and future prospects of sialic acids

Sialic acids (Sias) are negatively charged functional monosaccharides present in a wide variety of natural sources (plants, animals and microorganisms). Sias play an important role in many life processes, which are widely applied in the medical and food industries as intestinal antibacterials, antivirals, anti-oxidative agents, food ingredients, and detoxification agents. Most Sias are composed of N-acetylneuraminic acid (Neu5Ac, >99%), and Sia is its most commonly used name. In this article, we review Sias in terms of their structures, applications, determination methods, metabolism, and production strategies. In particular, we summarise and compare different production strategies, including extraction from natural sources, chemical synthesis, polymer decomposition, enzymatic synthesis, whole-cell catalysis, and de novo biosynthesis via microorganism fermentation. We also discuss research on their physiological functions and applications, barriers to efficient production, and strategies for overcoming these challenges. We focus on efficient de novo biosynthesis strategies for Neu5Ac via microbial fermentation using novel synthetic biology tools and methods that may be applied in future. This work provides a comprehensive overview of recent advances on Sias, and addresses future challenges regarding their functions, applications, and production.

Synthetic protein switches: Combinatorial linker engineering with iFLinkC

Linker engineering constitutes a critical, yet frequently underestimated aspect in the construction of synthetic protein switches and sensors. Notably, systematic strategies to engineer linkers by predictive means remain largely elusive to date. This is primarily due to our insufficient understanding how the biophysical properties that underlie linker functions mediate the conformational transitions in artificially engineered protein switches and sensors. The construction of synthetic protein switches and sensors therefore heavily relies on experimental trial-and-error. Yet, methods for effectively generating linker diversity at the genetic level are scarce. Addressing this technical shortcoming, iterative functional linker cloning (iFLinkC) enables the combinatorial assembly of linker elements with functional domains from sequence verified repositories that are developed and stored in-house. The assembly process is highly scalable and given its recursive nature generates linker diversity in a combinatorial and exponential fashion based on a limited number of linker elements.

A synthetic biosensor to detect peroxisomal acetyl-CoA concentration for compartmentalized metabolic engineering

Background

Sub-cellular compartmentalization is used by cells to create favorable microenvironments for various metabolic reactions. These compartments concentrate enzymes, separate competing metabolic reactions, and isolate toxic intermediates. Such advantages have been recently harnessed by metabolic engineers to improve the production of various high-value chemicals via compartmentalized metabolic engineering. However, measuring sub-cellular concentrations of key metabolites represents a grand challenge for compartmentalized metabolic engineering.

Methods

To this end, we developed a synthetic biosensor to measure a key metabolite, acetyl-CoA, in a representative compartment of yeast, the peroxisome. This synthetic biosensor uses enzyme re-localization via PTS1 signal peptides to construct a metabolic pathway in the peroxisome which converts acetyl-CoA to polyhydroxybutyrate (PHB) via three enzymes. The PHB is then quantified by HPLC.

Results

The biosensor demonstrated the difference in relative peroxisomal acetyl-CoA availability under various culture conditions and was also applied to screening a library of single knockout yeast mutants. The screening identified several mutants with drastically reduced peroxisomal acetyl-CoA and one with potentially increased levels. We expect our synthetic biosensors can be widely used to investigate sub-cellular metabolism and facilitate the “design-build-test” cycle of compartmentalized metabolic engineering.

Engineering transcription factor-based biosensors for repressive regulation through transcriptional deactivation design in Saccharomyces cerevisiae

Background

With the development of engineering the microbial cell factories, biosensors have been used widely for regulation of cellular metabolism and high-throughput screening. However, most of the biosensors constructed in Saccharomyces cerevisiae are designed for transcriptional activation. Very few studies have dedicated to the development of genetic circuit for repressive regulation, which is also indispensable for the dynamic control of metabolism.

Results

In this study, through transcriptional deactivation design, we developed transcription-factor-based biosensors to allow repressive regulation in response to ligand. Using a malonyl-CoA sensing system as an example, the biosensor was constructed and systematically engineered to optimize the dynamic range by comparing transcriptional activity of the activators, evaluating the positions and numbers of the operators in the promoter and comparing the effects of different promoters. A biosensor with 82% repression ratio was obtained. Based on this design principle, another two biosensors, which sense acyl-CoA or xylose and downregulate gene expression, were also successfully constructed.

Conclusions

Our work systematically optimized the biosensors for repressive regulation in yeast for the first time. It provided useful framework to construct similar biosensors. Combining the widely reported biosensors for transcriptional activation with the biosensors developed here, it is now possible to construct biosensors with opposing transcriptional activities in yeast.

Branch point control at malonyl-CoA node: A computational framework to uncover the design principles of an ideal genetic-metabolic switch

Living organism is an intelligent system coded by hierarchically-organized information to perform precisely-controlled biological functions. Biophysical models are important tools to uncover the design rules underlying complex genetic-metabolic circuit interactions. Based on a previously engineered synthetic malonyl-CoA switch (Xu et al., PNAS, 2014), we have formulated nine differential equations to unravel the design principles underlying an ideal metabolic switch to improve fatty acids production in E. coli. By interrogating the physiologically accessible parameter space, we have determined the optimal controller architecture to configure both the metabolic source pathway and metabolic sink pathway. We determined that low protein degradation rate, medium strength of metabolic inhibitory constant, high metabolic source pathway induction rate, strong binding affinity of the transcriptional activator toward the metabolic source pathway, weak binding affinity of the transcriptional repressor toward the metabolic sink pathway, and a strong cooperative interaction of transcriptional repressor toward metabolic sink pathway benefit the accumulation of the target molecule (fatty acids). The target molecule (fatty acid) production is increased from 50% to 10-folds upon application of the autonomous metabolic switch. With strong metabolic inhibitory constant, the system displays multiple steady states. Stable oscillation of metabolic intermediate is the driving force to allow the system deviate from its equilibrium state and permits bidirectional ON-OFF gene expression control, which autonomously compensates enzyme level for both the metabolic source and metabolic sink pathways. The computational framework may facilitate us to design and engineer predictable genetic-metabolic switches, quest for the optimal controller architecture of the metabolic source/sink pathways, as well as leverage autonomous oscillation as a powerful tool to engineer cell function.

Organism Engineering for the Bioproduction of the Triaminotrinitrobenzene (TATB) Precursor Phloroglucinol (PG)

Organism engineering requires the selection of an appropriate chassis, editing its genome, combining traits from different source species, and controlling genes with synthetic circuits. When a strain is needed for a new target objective, for example, to produce a chemical-of-need, the best strains, genes, techniques, software, and expertise may be distributed across laboratories. Here, we report a project where we were assigned phloroglucinol (PG) as a target, and then combined unique capabilities across the United States Army, Navy, and Air Force service laboratories with the shared goal of designing an organism to produce this molecule. In addition to the laboratory strain Escherichia coli, organisms were screened from soil and seawater. Putative PG-producing enzymes were mined from a strain bank of bacteria isolated from aircraft and fuel depots. The best enzyme was introduced into the ocean strain Marinobacter atlanticus CP1 with its genome edited to redirect carbon flux from natural fatty acid ester (FAE) production. PG production was also attempted in Bacillus subtilis and Clostridium acetobutylicum. A genetic circuit was constructed in E. coli that responds to PG accumulation, which was then ported to an in vitro paper-based system that could serve as a platform for future low-cost strain screening or for in-field sensing. Collectively, these efforts show how distributed biotechnology laboratories with domain-specific expertise can be marshalled to quickly provide a solution for a targeted organism engineering project, and highlights data and material sharing protocols needed to accelerate future efforts.

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.

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.

Bacterial Metabolism and Antibiotic Efficacy

Antibiotics target energy-consuming processes. As such, perturbations to bacterial metabolic homeostasis are significant consequences of treatment. Here, we describe three postulates that collectively define antibiotic efficacy in the context of bacterial metabolism: (1) antibiotics alter the metabolic state of bacteria, which contributes to the resulting death or stasis; (2) the metabolic state of bacteria influences their susceptibility to antibiotics; and (3) antibiotic efficacy can be enhanced by altering the metabolic state of bacteria. Altogether, we aim to emphasize the close relationship between bacterial metabolism and antibiotic efficacy as well as propose areas of exploration to develop novel antibiotics that optimally exploit bacterial metabolic networks.

Engineering metabolite-responsive transcriptional factors to sense small molecules in eukaryotes: current state and perspectives

Nature has evolved exquisite sensing mechanisms to detect cellular and environmental signals surrounding living organisms. These biosensors have been widely used to sense small molecules, detect environmental cues and diagnose disease markers. Metabolic engineers and synthetic biologists have been able to exploit metabolites-responsive transcriptional factors (MRTFs) as basic tools to rewire cell metabolism, reprogram cellular activity as well as boost cell’s productivity. This is commonly achieved by integrating sensor-actuator systems with biocatalytic functions and dynamically allocating cellular resources to drive carbon flux toward the target pathway. Up to date, most of identified MRTFs are derived from bacteria. As an endeavor to advance intelligent biomanufacturing in yeast cell factory, we will summarize the opportunities and challenges to transfer the bacteria-derived MRTFs to expand the small-molecule sensing capability in eukaryotic cells. We will discuss the design principles underlying MRTF-based biosensors in eukaryotic cells, including the choice of reliable reporters and the characterization tools to minimize background noise, strategies to tune the sensor dynamic range, sensitivity and specificity, as well as the criteria to engineer activator and repressor-based biosensors. Due to the physical separation of transcription and protein expression in eukaryotes, we argue that nuclear import/export mechanism of MRTFs across the nuclear membrane plays a critical role in regulating the MRTF sensor dynamics. Precisely-controlled MRTF response will allow us to repurpose the vast majority of transcriptional factors as molecular switches to achieve temporal or spatial gene expression in eukaryotes. Uncovering this knowledge will inform us fundamental design principles to deliver robust cell factories and enable the design of reprogrammable and predictable biological systems for intelligent biomanufacturing, smart therapeutics or precision medicine in the foreseeable future.

Development of a Synthetic 3-Dehydroshikimate Biosensor in Escherichia coli for Metabolite Monitoring and Genetic Screening

Biosensors for target metabolites provide powerful high-throughput screening tools to obtain high-performing strains. However, well-characterized metabolite-sensing modules are often unavailable and limit rapid access to the robust biosensors with successful applications. In this study, we developed a strategy of transcriptome-assisted metabolite-sensing (TAMES) to identify the target metabolite-sensing module based on selectively comparative transcriptome analysis between the target metabolite producing and nonproducing strains and a subsequent quantative reverse transcription (RT-qPCR) evaluation. The strategy was applied to identify the sensing module cusR that responds positively to the metabolite 3-dehydroshikimate (DHS) and proved it was effective to narrow down the candidates. We further constructed the cusR-based synthetic biosensor and established the DHS biosensor-based high-throughput screening (HTS) platform to screen higher DHS-producing strains and successfully increased DHS production by more than 90%. This study demonstrated that the TAMES strategy was effective at exploiting the metabolite-sensing transcriptional regulator, and this could likely be extended to develop the biosensor-based HTS platforms for other molecules.

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

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

Dynamic control of endogenous metabolism with combinatorial logic circuits

Controlling gene expression during a bioprocess enables real-time metabolic control, coordinated cellular responses, and staging order-of-operations. Achieving this with small molecule inducers is impractical at scale and dynamic circuits are difficult to design. Here, we show that the same set of sensors can be integrated by different combinatorial logic circuits to vary when genes are turned on and off during growth. Three Escherichia coli sensors that respond to the consumption of feedstock (glucose), dissolved oxygen, and by-product accumulation (acetate) are constructed and optimized. By integrating these sensors, logic circuits implement temporal control over an 18-h period. The circuit outputs are used to regulate endogenous enzymes at the transcriptional and post-translational level using CRISPRi and targeted proteolysis, respectively. As a demonstration, two circuits are designed to control acetate production by matching their dynamics to when endogenous genes are expressed (pta or poxB) and respond by turning off the corresponding gene. This work demonstrates how simple circuits can be implemented to enable customizable dynamic gene regulation.

A Yeast-Based Biosensor for Screening of Short- and Medium-Chain Fatty Acid Production

Short- and medium-chain fatty acids (SMCFA) are important platform chemicals currently produced from nonsustainable resources. The engineering of microbial cells to produce SMCFA, however, lacks high-throughput methods to screen for best performing cells. Here, we present the development of a whole-cell biosensor for easy and rapid detection of SMCFA. The biosensor is based on a multicopy yeast plasmid containing the SMCFA-responsive PDR12 promoter coupled to GFP as the reporter gene. The sensor detected hexanoic, heptanoic and octanoic acid over a linear range up to 2, 1.5, and 0.75 mM, respectively, but did not show a linear response to decanoic and dodecanoic acid. We validated the functionality of the biosensor with culture supernatants of a previously engineered Saccharomyces cerevisiae octanoic acid producer strain and derivatives thereof. The biosensor signal correlated strongly with the octanoic acid concentrations as determined by gas chromatography. Thus, this biosensor enables the high-throughput screening of SMCFA producers and has the potential to drastically speed up the engineering of diverse SMCFA producing cell factories.

Discovering novel hydrolases from hot environments

Novel hydrolases from hot and other extreme environments showing appropriate performance and/or novel functionalities and new approaches for their systematic screening are of great interest for developing new processes, for improving safety, health and environment issues. Existing processes could benefit as well from their properties. The workflow, based on the HotZyme project, describes a multitude of technologies and their integration from discovery to application, providing new tools for discovering, identifying and characterizing more novel thermostable hydrolases with desired functions from hot terrestrial and marine environments. To this end, hot springs worldwide were mined, resulting in hundreds of environmental samples and thousands of enrichment cultures growing on polymeric substrates of industrial interest. Using high-throughput sequencing and bioinformatics, 15 hot spring metagenomes, as well as several sequenced isolate genomes and transcriptomes were obtained. To facilitate the discovery of novel hydrolases, the annotation platform Anastasia and a whole-cell bioreporter-based functional screening method were developed. Sequence-based screening and functional screening together resulted in about 100 potentially new hydrolases of which more than a dozen have been characterized comprehensively from a biochemical and structural perspective. The characterized hydrolases include thermostable carboxylesterases, enol lactonases, quorum sensing lactonases, gluconolactonases, epoxide hydrolases, and cellulases. Apart from these novel thermostable hydrolases, the project generated an enormous amount of samples and data, thereby allowing the future discovery of even more novel enzymes.

Blueprints for Biosensors: Design, Limitations, and Applications

Biosensors are enabling major advances in the field of analytics that are both facilitating and being facilitated by advances in synthetic biology. The ability of biosensors to rapidly and specifically detect a wide range of molecules makes them highly relevant to a range of industrial, medical, ecological, and scientific applications. Approaches to biosensor design are as diverse as their applications, with major biosensor classes including nucleic acids, proteins, and transcription factors. Each of these biosensor types has advantages and limitations based on the intended application, and the parameters that are required for optimal performance. Specifically, the choice of biosensor design must consider factors such as the ligand specificity, sensitivity, dynamic range, functional range, mode of output, time of activation, ease of use, and ease of engineering. This review discusses the rationale for designing the major classes of biosensor in the context of their limitations and assesses their suitability to different areas of biotechnological application.

Tetramethylpyrazine-Inducible Promoter Region from Rhodococcus jostii TMP1

An inducible promoter region, P_TTMP (tetramethylpyrazine [TTMP]), has been identified upstream of the tpdABC operon, which contains the genes required for the initial degradation of 2,3,5,6-tetramethylpyrazine in Rhodococcus jostii TMP1 bacteria. In this work, the promoter region was fused with the gene for the enhanced green fluorescent protein (EGFP) to investigate the activity of P_TTMP by measuring the fluorescence of bacteria. The highest promoter activity was observed when bacteria were grown in a nutrient broth (NB) medium supplemented with 5 mM 2,3,5,6-tetramethylpyrazine for 48 h. Using a primer extension reaction, two transcriptional start sites for tpdA were identified, and the putative −35 and −10 promoter motifs were determined. The minimal promoter along with two 15 bp long direct repeats and two 7 bp inverted sequences were identified. Also, the influence of the promoter elements on the activity of P_TTMP were determined using site-directed mutagenesis. Furthermore, P_TTMP was shown to be induced by pyrazine derivatives containing methyl groups in the 2- and 5-positions of the heterocyclic ring, in the presence of the LuxR family transcriptional activator TpdR.

Synthetic addiction extends the productive life time of engineered Escherichia coli populations

Bioproduction of chemicals offers a sustainable alternative to petrochemical synthesis routes by using genetically engineered microorganisms to convert waste and simple substrates into higher-value products. However, efficient high-yield production commonly introduces a metabolic burden that selects for subpopulations of nonproducing cells in large fermentations. To postpone such detrimental evolution, we have synthetically addicted production cells to production by carefully linking signals of product presence to expression of nonconditionally essential genes. We addict Escherichia coli cells to their engineered biosynthesis of mevalonic acid by fine-tuned control of essential genes using a product-responsive transcription factor. Over the course of a long-term fermentation equivalent to industrial 200-m³ bioreactors such addicted cells remained productive, unlike the control, in which evolution fully terminated production.

Bio-production of chemicals is an important driver of the societal transition toward sustainability. However, fermentations with heavily engineered production organisms can be challenging to scale to industrial volumes. Such fermentations are subject to evolutionary pressures that select for a wide range of genetic variants that disrupt the biosynthetic capacity of the engineered organism. Synthetic product addiction that couples high-yield production of a desired metabolite to expression of nonconditionally essential genes could offer a solution to this problem by selectively favoring cells with biosynthetic capacity in the population without constraining the medium. We constructed such synthetic product addiction by controlling the expression of two nonconditionally essential genes with a mevalonic acid biosensor. The product-addicted production organism retained high-yield mevalonic acid production through 95 generations of cultivation, corresponding to the number of cell generations required for >200-m³ industrial-scale production, at which time the nonaddicted strain completely abolished production. Using deep DNA sequencing, we find that the product-addicted populations do not accumulate genetic variants that compromise biosynthetic capacity, highlighting how synthetic networks can be designed to control genetic population heterogeneity. Such synthetic redesign of evolutionary forces with endogenous processes may be a promising concept for realizing complex cellular designs required for sustainable bio-manufacturing.

New Intracellular Shikimic Acid Biosensor for Monitoring Shikimate Synthesis in Corynebacterium glutamicum

The quantitative monitoring of intracellular metabolites with in vivo biosensors provides an efficient means of identifying high-yield strains and observing product accumulation in real time. In this study, a shikimic acid (SA) biosensor was constructed from a LysR-type transcriptional regulator (ShiR) of Corynebacterium glutamicum. The SA biosensor specifically responded to the increase of intracellular SA concentration over a linear range of 19.5 ± 3.6 to 120.9 ± 1.2 fmole at the single-cell level. This new SA biosensor was successfully used to (1) monitor the SA production of different C. glutamicum strains; (2) develop a novel result-oriented high-throughput ribosome binding site screening and sorting strategy that was used for engineering high-yield shikimate-producing strains; and (3) engineer a whole-cell biosensor through the coexpression of the SA sensor and a shikimate transporter shiA gene in C. glutamicum RES167. This work demonstrated that a new intracellular SA biosensor is a valuable tool facilitating the fast development of microbial SA producer.

Rapid evolution of regulatory element libraries for tunable transcriptional and translational control of gene expression

Engineering cell factories for producing biofuels and pharmaceuticals has spurred great interests to develop rapid and efficient synthetic biology tools customized for modular pathway engineering. Along the way, combinatorial gene expression control through modification of regulatory element offered tremendous opportunity for fine-tuning gene expression and generating digital-like genetic circuits. In this report, we present an efficient evolutionary approach to build a range of regulatory control elements. The reported method allows for rapid construction of promoter, 5'UTR, terminator and trans-activating RNA libraries. Synthetic overlapping oligos with high portion of degenerate nucleotides flanking the regulatory element could be efficiently assembled to a vector expressing fluorescence reporter. This approach combines high mutation rate of the synthetic DNA with the high assembly efficiency of Gibson Mix. Our constructed library demonstrates broad range of transcriptional or translational gene expression dynamics. Specifically, both the promoter library and 5'UTR library exhibits gene expression dynamics spanning across three order of magnitude. The terminator library and trans-activating RNA library displays relatively narrowed gene expression pattern. The reported study provides a versatile toolbox for rapidly constructing a large family of prokaryotic regulatory elements. These libraries also facilitate the implementation of combinatorial pathway engineering principles and the engineering of more efficient microbial cell factory for various biomanufacturing applications.

Small molecule signaling, regulation, and potential applications in cellular therapeutics

Small molecules have many important roles across the tree of life: they regulate processes from metabolism to transcription, they enable signaling within and between species, and they serve as the biochemical building blocks for cells. They also represent valuable phenotypic endpoints that are promising for use as biomarkers of disease states. In the context of engineering cell-based therapeutics, they hold particularly great promise for enabling finer control over the therapeutic cells and allowing them to be responsive to extracellular cues. The natural signaling and regulatory functions of small molecules can be harnessed and rewired to control cell activity and delivery of therapeutic payloads, potentially increasing efficacy while decreasing toxicity. To that end, this review considers small molecule-mediated regulation and signaling in bacteria. We first discuss some of the most prominent applications and aspirations for responsive cell-based therapeutics. We then describe the transport, signaling, and regulation associated with three classes of molecules that may be exploited in the engineering of therapeutic bacteria: amino acids, fatty acids, and quorum-sensing signaling molecules. We also present examples of existing engineering efforts to generate cells that sense and respond to levels of different small molecules. Finally, we discuss future directions for how small molecule-mediated regulation could be harnessed for therapeutic applications, as well as some critical considerations for the ultimate success of such endeavors. WIREs Syst Biol Med 2018, 10:e1405. doi: 10.1002/wsbm.1405 This article is categorized under: Biological Mechanisms > Cell Signaling Biological Mechanisms > Metabolism Translational, Genomic, and Systems Medicine > Therapeutic Methods.

Fluorescence Polarization Assay for Small Molecule Screening of FK506 Biosynthesized in 96-Well Microtiter Plates

The fluorescence polarization (FP) assay has been widely used to study enzyme kinetics, antibody-antigen interactions, and other biological interactions. We propose that the FP assay can be adapted as a high-throughput and potentially widely applicable screen for small molecules. This is useful in metabolic engineering, which is a promising approach to synthesizing compounds of pharmaceutical, agricultural, and industrial importance using bioengineered strains. There, the development of high-yield strains is often a costly and time-consuming process. This problem can be addressed by generating and testing large mutant strain libraries. However, a current key bottleneck is the lack of high-throughput screens to detect the small molecule products. The FP assay is quantitative, sensitive, fast, and cheap. As a proof of principle, we established the FP assay to screen for FK506 (tacrolimus) produced by Streptomyces tsukubaensis, which was cultivated in 96-well plates. An ultraviolet mutagenized library of 160 colonies was screened to identify strains showing higher FK506 productivities. The FP assay has the potential to be generalized to detect a wide range of other small molecules.

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.

Assessing glycolytic flux alterations resulting from genetic perturbations in E. coli using a biosensor

We describe the development of an optimized glycolytic flux biosensor and its application in detecting altered flux in a production strain and in a mutant library. The glycolytic flux biosensor is based on the Cra-regulated ppsA promoter of E. coli controlling fluorescent protein synthesis. We validated the glycolytic flux dependency of the biosensor in a range of different carbon sources in six different E. coli strains and during mevalonate production. Furthermore, we studied the flux-altering effects of genome-wide single gene knock-outs in E. coli in a multiplex FlowSeq experiment. From a library consisting of 2126 knock-out mutants, we identified 3 mutants with high-flux and 95 mutants with low-flux phenotypes that did not have severe growth defects. This approach can improve our understanding of glycolytic flux regulation improving metabolic models and engineering efforts.

Riboswitch-Based Reversible Dual Color Sensor

Riboswitches are RNA-based "sensors" that utilize chemically induced structural changes in the 5'-untranslated region of mRNA to regulate expression of downstream genes. Coupling a specific riboswitch with a reporter gene system translates chemical detection by the cell into a quantifiable reporter protein signal. For the majority of reporter gene systems, the readout signal is only expressed in the presence of the target analyte. This makes it difficult to determine the viability and localization of the uninduced biosensor when it is used for "real-word" applications. To address this problem, we developed a dual-color reporter comprising elements of the E. coli fimbriae phase variation system: recombinase FimE controlled by a synthetic riboswitch and an invertible DNA segment (fimS) containing a constitutively active promoter placed between two fluorescent protein genes. Without an analyte, the fluorescent reporter constitutively expressed green fluorescent protein (GFPa1). Addition of the analyte initiated translation of fimE causing unidirectional inversion of the fimS segment and constitutive expression of red fluorescent protein (mKate2). Thus, the sensor is always fluorescent, but its color is determined by detection of a specific analyte. We demonstrate that the recombinase-based dual-color reporter can be successfully applied to monitor the activation of a theophylline synthetic riboswitch that was used as our model system. To show the feasibility of the FimE recombinase-based system to serve as a reporter for monitoring activation of multiple synthetic riboswitches and, therefore, expand the applicability of the system, we tested a number of previously developed synthetic riboswitches responsive to different analytes. We show that the dual-color reporter system can be successfully used to monitor activation of M6 and M6″ riboswitches responsive to ammeline and pyrimido[4,5-d]pyrimidine-2,4-diamine, respectively, and a 2,4,6-trinitrotoluene-responsive riboswitch developed in this study. We also demonstrate that the system can be reversed by HbiF recombinase-mediated fimS inversion to the initial state of the fluorescent reporter, creating a resettable and reusable cell-based sensor.

Characterisation of a 3-hydroxypropionic acid-inducible system from Pseudomonas putida for orthogonal gene expression control in Escherichia coli and Cupriavidus necator

3-hydroxypropionic acid (3-HP) is an important platform chemical used as a precursor for production of added-value compounds such as acrylic acid. Metabolically engineered yeast, Escherichia coli, cyanobacteria and other microorganisms have been developed for the biosynthesis of 3-HP. Attempts to overproduce this compound in recombinant Pseudomonas denitrificans revealed that 3-HP is consumed by this microorganism using the catabolic enzymes encoded by genes hpdH, hbdH and mmsA. 3-HP-inducible systems controlling the expression of these genes have been predicted in proteobacteria and actinobacteria. In this study, we identify and characterise 3-HP-inducible promoters and their corresponding LysR-type transcriptional regulators from Pseudomonas putida KT2440. A newly-developed modular reporter system proved possible to demonstrate that PpMmsR/P_mmsA and PpHpdR/P_hpdH are orthogonal and highly inducible by 3-HP in E. coli (12.3- and 23.3-fold, respectively) and Cupriavidus necator (51.5- and 516.6-fold, respectively). Bioinformatics and mutagenesis analyses revealed a conserved 40-nucleotide sequence in the hpdH promoter, which plays a key role in HpdR-mediated transcription activation. We investigate the kinetics and dynamics of the PpHpdR/P_hpdH switchable system in response to 3-HP and show that it is also induced by both enantiomers of 3-hydroxybutyrate. These findings pave the way for use of the 3-HP-inducible system in synthetic biology and biotechnology applications.

Engineering genetic circuit interactions within and between synthetic minimal cells

Genetic circuits and reaction cascades are of great importance for synthetic biology, biochemistry and bioengineering. An open question is how to maximize the modularity of their design to enable the integration of different reaction networks and to optimize their scalability and flexibility. One option is encapsulation within liposomes, which enables chemical reactions to proceed in well-isolated environments. Here we adapt liposome encapsulation to enable the modular, controlled compartmentalization of genetic circuits and cascades. We demonstrate that it is possible to engineer genetic circuit-containing synthetic minimal cells (synells) to contain multiple-part genetic cascades, and that these cascades can be controlled by external signals as well as inter-liposomal communication without crosstalk. We also show that liposomes that contain different cascades can be fused in a controlled way so that the products of incompatible reactions can be brought together. Synells thus enable a more modular creation of synthetic biology cascades, an essential step towards their ultimate programmability.