Engineering an Acinetobacter regulon for biosensing and high-throughput enzyme screening in E. coli via flow cytometry

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.

Efficient production of protocatechuic acid using systems engineering of Escherichia coli

Protocatechuic acid (3, 4-dihydroxybenzoic acid, PCA) is widely used in the pharmaceuticals, health food, and cosmetics industries owing to its diverse biological activities. However, the inhibition of 3-dehydroshikimate dehydratase (AroZ) by PCA and its toxicity to cells limit the efficient production of PCA in Escherichia coli. In this study, a high-level strain of 3-dehydroshikimate, E. coli DHS01, was developed by blocking the carbon flow from the shikimate-overproducing strain E. coli SA09. Additionally, the PCA biosynthetic pathway was established in DHS01 by introducing the high-activity ApAroZ. Subsequently, the protein structure and catalytic mechanism of 3-dehydroshikimate dehydratase from Acinetobacter pittii PHEA-2 (ApAroZ) were clarified. The variant ApAroZR363A, achieved by modulating the conformational dynamics of ApAroZ, effectively relieved product inhibition. Additionally, the tolerance of the strain E. coli PCA04 to PCA was enhanced by adaptive laboratory evolution, and a biosensor-assisted high-throughput screening method was designed and implemented to expedite the identification of high-performance PCA-producing strains. Finally, in a 5 L bioreactor, the final strain PCA05 achieved the highest PCA titer of 46.65 g/L, a yield of 0.23 g/g, and a productivity of 1.46 g/L/h for PCA synthesis from glucose using normal fed-batch fermentation. The strategies described herein serve as valuable guidelines for the production of other high-value and toxic products.

High-Throughput Screening Techniques for the Selection of Thermostable Enzymes

The acquisition of a thermostable enzyme is an indispensable prerequisite for its successful implementation in industrial applications and the development of novel functionalities. Various protein engineering approaches, including rational design, semirational design, and directed evolution, have been employed to enhance thermostability. However, all of these approaches require sensitive and reliable high-throughput screening (HTS) technologies to efficiently and rapidly identify variants with improved properties. While numerous reviews focus on modification strategies for enhancing enzyme thermostability, there is a dearth of literature reviewing HTS methods specifically aimed at this objective. Herein, we present a comprehensive overview of various HTS methods utilized for modifying enzyme thermostability across different screening platforms. Additionally, we highlight significant recent examples that demonstrate the successful application of these methods. Furthermore, we address the technical challenges associated with HTS technologies used for screening thermostable enzyme variants and discuss valuable perspectives to promote further advancements in this field. This review serves as an authoritative reference source offering theoretical support for selecting appropriate screening strategies tailored to specific enzymes with the aim of improving their thermostability.

Nutrient limitation and oxidative stress induce the promoter of acetate operon in Salmonella Typhimurium

Glyoxylate shunt is an important pathway for microorganisms to survive under multiple stresses. One of its enzymes, malate synthase (encoded by aceB gene), has been widely speculated for its contribution to both the pathogenesis and virulence of various microorganisms. We have previously demonstrated that malate synthase (MS) is required for the growth of Salmonella Typhimurium (S. Typhimurium) under carbon starvation and survival under oxidative stress conditions. The aceB gene is encoded by the acetate operon in S. Typhimurium. We attempted to study the activity of acetate promoter under both the starvation and oxidative stress conditions in a heterologous system. The lac promoter of the pUC19 plasmid was substituted with the putative promoter sequence of the acetate operon of S. Typhimurium upstream to the lacZ gene and transformed the vector construct into E. coli NEBα cells. The transformed cells were subjected to the stress conditions mentioned above. We observed a fourfold increase in the β-galactosidase activity in these cells resulting from the upregulation of the lacZ gene in the stationary phase of cell growth (nutrient deprived) as compared to the mid-log phase. Following exposure of stationary phase cells to hypochlorite-induced oxidative stress, we further observed a 1.6-fold increase in β galactosidase activity. These data suggest the induction of promoter activity of the acetate operon under carbon starvation and oxidative stress conditions. Thus, these observations corroborate our previous findings regarding the upregulation of aceB expression under stressful environments.

Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments

Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness. Such genotype relationships result in mutational fitness landscapes with multiple local fitness maxima and valleys. Traversing local maxima to find a global maximum often requires an individual or sub-population of cells to traverse fitness valleys. Traversing involves gaining mutations that are not adaptive for a given local maximum but are necessary to 'peak shift' to another local maximum, or eventually a global maximum. Despite these relatively well understood evolutionary principles, and the combinatorial genotypes that underlie most metabolic phenotypes, the majority of applied ALE experiments are conducted using constant selection pressures. The use of constant pressure can result in populations becoming trapped within local maxima, and often precludes the attainment of optimum phenotypes associated with global maxima. Here, we argue that oscillating selection pressures is an easily accessible mechanism for traversing fitness landscapes in ALE experiments, and provide theoretical and practical frameworks for implementation.

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.

Targeted mutagenesis and high-throughput screening of diversified gene and promoter libraries for isolating gain-of-function mutations

Targeted mutagenesis of a promoter or gene is essential for attaining new functions in microbial and protein engineering efforts. In the burgeoning field of synthetic biology, heterologous genes are expressed in new host organisms. Similarly, natural or designed proteins are mutagenized at targeted positions and screened for gain-of-function mutations. Here, we describe methods to attain complete randomization or controlled mutations in promoters or genes. Combinatorial libraries of one hundred thousands to tens of millions of variants can be created using commercially synthesized oligonucleotides, simply by performing two rounds of polymerase chain reactions. With a suitably engineered reporter in a whole cell, these libraries can be screened rapidly by performing fluorescence-activated cell sorting (FACS). Within a few rounds of positive and negative sorting based on the response from the reporter, the library can rapidly converge to a few optimal or extremely rare variants with desired phenotypes. Library construction, transformation and sequence verification takes 6-9 days and requires only basic molecular biology lab experience. Screening the library by FACS takes 3-5 days and requires training for the specific cytometer used. Further steps after sorting, including colony picking, sequencing, verification, and characterization of individual clones may take longer, depending on number of clones and required experiments.

Tackling the Catch-22 Situation of Optimizing a Sensor and a Transporter System in a Whole-Cell Microbial Biosensor Design for an Anthropogenic Small Molecule

Whole-cell biosensors provide a convenient detection tool for the high-throughput screening of genetically engineered biocatalytic activity. But establishing a biosensor for an anthropogenic molecule requires both a custom transporter and a transcription factor. This results in an unavoidable "Catch-22" situation in which transporter activity cannot be easily confirmed without a biosensor and a biosensor cannot be established without a functional transporter in a host organism. We overcame this type of circular problem while developing an adipic acid (ADA) sensor. First, leveraging an established cis,cis-muconic acid (ccMA) sensor, an annotated ccMA transporter MucK, which is expected to be broadly responsive to dicarboxylates, was stably expressed in the genome of Pseudomonas putida to function as a transporter for ADA, and then a PcaR transcription factor (endogenous to the strain and naturally induced by β-ketoadipic acid, BKA) was diversified and selected to detect the ADA molecule. While MucK expression is otherwise very unstable in P. putida under strong promoter expression, our optimized mucK expression was functional for over 70 generations without loss of function, and we selected an ADA sensor that showed a specificity switch of over 35-fold from BKA at low concentrations (typically <0.1 mM of inducers). Our ADA and BKA biosensors show high sensitivity (low detection concentration <10 μM) and dynamic range (∼50-fold) in an industrially relevant organism and will open new avenues for high throughput discovery and optimization of enzymes and metabolic pathways for the biomanufacture of these molecules. In particular, the novel ADA sensor will aid the discovery and evolution of efficient biocatalysts for the biological recycling of ADA from the degradation of nylon-6,6 waste.

Identification of acetic acid sensitive strains through biosensor-based screening of a Saccharomyces cerevisiae CRISPRi library

Background

Acetic acid tolerance is crucial for the development of robust cell factories for conversion of lignocellulosic hydrolysates that typically contain high levels of acetic acid. Screening mutants for growth in medium with acetic acid is an attractive way to identify sensitive variants and can provide novel insights into the complex mechanisms regulating the acetic acid stress response.

Results

An acetic acid biosensor based on the Saccharomyces cerevisiae transcription factor Haa1, was used to screen a CRISPRi yeast strain library where dCas9-Mxi was set to individually repress each essential or respiratory growth essential gene. Fluorescence-activated cell sorting led to the enrichment of a population of cells with higher acetic acid retention. These cells with higher biosensor signal were demonstrated to be more sensitive to acetic acid. Biosensor-based screening of the CRISPRi library strains enabled identification of strains with increased acetic acid sensitivity: strains with gRNAs targeting TIF34, MSN5, PAP1, COX10 or TRA1.

Conclusions

This study demonstrated that biosensors are valuable tools for screening and monitoring acetic acid tolerance in yeast. Fine-tuning the expression of essential genes can lead to altered acetic acid tolerance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01938-7.

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.

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

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

Modular tuning engineering and versatile applications of genetically encoded biosensors

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

A unified design allows fine-tuning of biosensor parameters and application across bacterial species

In recent years, transcriptional biosensors have become valuable tools in metabolic engineering as they allow semiquantitative determination of metabolites in single cells. Although being perfectly suitable tools for high-throughput screenings, application of transcriptional biosensors is often limited by the intrinsic characteristics of the individual sensor components and their interplay. In addition, biosensors often fail to work properly in heterologous host systems due to signal saturation at low intracellular metabolite concentrations, which typically limits their use in high-level producer strains at advanced engineering stages.

We here introduce a biosensor design, which allows fine-tuning of important sensor parameters and restores the sensor response in a heterologous expression host. As a key feature of our design, the regulator activity is controlled through the expression level of the respective gene by different (synthetic) constitutive promoters selected for the used expression host. In this context, we constructed biosensors responding to basic amino acids or ring-hydroxylated phenylpropanoids for applications in Corynebacterium glutamicum and Escherichia coli. Detailed characterization of these biosensors in liquid cultures and during single-cell analysis using flow cytometry showed that the presented sensor design enables customization of important biosensor parameters as well as application of these sensors in relevant heterologous hosts.

•

Development of a unified biosensor design for C. glutamicum and E. coli.

•

Gradual expression of the regulator gene allows for biosensor fine-tuning.

•

Biosensor response in a heterologous host can be restored.

•

Biosensor characterization on the single-cell level prior to FACS is mandatory.

Biosensors and Sensing Systems for Rapid Analysis of Phenolic Compounds from Plants: A Comprehensive Review

Phenolic compounds are secondary metabolites frequently found in plants that exhibit many different effects on human health. Because of the relevant bioactivity, their identification and quantification in agro-food matrices as well as in biological samples are a fundamental issue in the field of quality control of food and food supplements, and clinical analysis. In this review, a critical selection of sensors and biosensors for rapid and selective detection of phenolic compounds is discussed. Sensors based on electrochemistry, photoelectrochemistry, fluorescence, and colorimetry are discussed including devices with or without specific recognition elements, such as biomolecules, enzymes and molecularly imprinted materials. Systems that have been tested on real matrices are prevalently considered but also techniques that show potential development in the field.

Advances and Prospects of Phenolic Acids Production, Biorefinery and Analysis

Biotechnological production of phenolic acids is attracting increased interest due to their superior antioxidant activity, as well as other antimicrobial, dietary, and health benefits. As secondary metabolites, primarily found in plants and fungi, they are effective free radical scavengers due to the phenolic group available in their structure. Therefore, phenolic acids are widely utilised by pharmaceutical, food, cosmetic, and chemical industries. A demand for phenolic acids is mostly satisfied by utilising chemically synthesised compounds, with only a low quantity obtained from natural sources. As an alternative to chemical synthesis, environmentally friendly bio-based technologies are necessary for development in large-scale production. One of the most promising sustainable technologies is the utilisation of microbial cell factories for biosynthesis of phenolic acids. In this paper, we perform a systematic comparison of the best known natural sources of phenolic acids. The advances and prospects in the development of microbial cell factories for biosynthesis of these bioactive compounds are discussed in more detail. A special consideration is given to the modern production methods and analytics of phenolic acids.

Engineering glucose metabolism for enhanced muconic acid production in Pseudomonas putida KT2440

Pseudomonas putida KT2440 has received increasing attention as an important biocatalyst for the conversion of diverse carbon sources to multiple products, including the olefinic diacid, cis,cis-muconic acid (muconate). P. putida has been previously engineered to produce muconate from glucose; however, periplasmic oxidation of glucose causes substantial 2-ketogluconate accumulation, reducing product yield and selectivity. Deletion of the glucose dehydrogenase gene (gcd) prevents 2-ketogluconate accumulation, but dramatically slows growth and muconate production. In this work, we employed adaptive laboratory evolution to improve muconate production in strains incapable of producing 2-ketogluconate. Growth-based selection improved growth, but reduced muconate titer. A new muconate-responsive biosensor was therefore developed to enable muconate-based screening using fluorescence activated cell sorting. Sorted clones demonstrated both improved growth and muconate production. Mutations identified by whole genome resequencing of these isolates indicated that glucose metabolism may be dysregulated in strains lacking gcd. Using this information, we used targeted engineering to recapitulate improvements achieved by evolution. Deletion of the transcriptional repressor gene hexR improved strain growth and increased the muconate production rate, and the impact of this deletion was investigated using transcriptomics. The genes gntZ and gacS were also disrupted in several evolved clones, and deletion of these genes further improved strain growth and muconate production. Together, these targets provide a suite of modifications that improve glucose conversion to muconate by P. putida in the context of gcd deletion. Prior to this work, our engineered strain lacking gcd generated 7.0 g/L muconate at a productivity of 0.07 g/L/h and a 38% yield (mol/mol) in a fed-batch bioreactor. Here, the resulting strain with the deletion of hexR, gntZ, and gacS achieved 22.0 g/L at 0.21 g/L/h and a 35.6% yield (mol/mol) from glucose in similar conditions. These strategies enabled enhanced muconic acid production and may also improve production of other target molecules from glucose in P. putida.

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

Background

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

Results

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

Conclusions

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

Promoter engineering strategies for the overproduction of valuable metabolites in microbes

Promoter engineering is an enabling technology in metabolic engineering and synthetic biology. As an indispensable part of synthetic biology, the promoter is a key factor in regulating genetic circuits and in coordinating multi-gene biosynthetic pathways. In this review, we summarized the recent progresses in promoter engineering in microbes. Specifically, the endogenous promoters are firstly discussed, followed by the statement of the influence of nucleotides exchange on the strength of promoters explored by site-selective mutagenesis. We then introduced the promoter libraries with a wide range of strength, which are constructed focusing on core promoter regions and upstream activating sequences by rational designs. Finally, the application of promoter libraries in the optimization of multi-gene metabolic pathways for high-yield production of metabolites was illustrated with a couple of recent examples.

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.

Development of a Vanillate Biosensor for the Vanillin Biosynthesis Pathway in E. coli

The engineered de novo vanillin biosynthesis pathway constructed in Escherichia coli is industrially relevant but limited by the reaction catalyzed by catechol O-methyltransferase, which is intended to catalyze the conversion of protocatechuate to vanillate. To identify alternative O-methyltransferases, we constructed a vanillate sensor based on the Caulobacter crescentus VanR-VanO system. Using an E. coli promoter library, we achieved greater than 14-fold dynamic range in our best rationally constructed sensor. We found that this construct and an evolved variant demonstrate remarkable substrate selectivity, exhibiting no detectable response to the regioisomer byproduct isovanillate and minimal response to structurally similar pathway intermediates. We then harnessed the evolved biosensor to conduct rapid bioprospecting of natural catechol O-methyltransferases and identified three previously uncharacterized but active O-methyltransferases. Collectively, these efforts enrich our knowledge of how biosensing can aid metabolic engineering and constitute the foundation for future improvements in vanillin pathway productivity.

Displaced by Deceivers: Prevention of Biosensor Cross-Talk Is Pivotal for Successful Biosensor-Based High-Throughput Screening Campaigns

Transcriptional biosensors emerged as powerful tools for protein and strain engineering as they link inconspicuous production phenotypes to easily measurable output signals such as fluorescence. When combined with fluorescence-activated cell sorting, transcriptional biosensors enable high throughput screening of vast mutant libraries. Interestingly, even though many published manuscripts describe the construction and characterization of transcriptional biosensors, only very few studies report the successful application of transcriptional biosensors in such high-throughput screening campaigns. Here, we describe construction and characterization of the trans-cinnamic acid responsive transcriptional biosensor pSenCA for Escherichia coli and its application in a FACS based screen. In this context, we focus on essential methodological challenges during the development of such biosensor-guided high-throughput screens such as biosensor cross-talk between producing and nonproducing cells, which could be minimized by optimization of expression and cultivation conditions. The optimized conditions were applied in a five-step FACS campaign and proved suitable to isolate phenylalanine ammonia lyase variants with improved activity in E. coli and in vitro. Findings from this study will help researchers who want to profit from the unmatched throughput of fluorescence-activated cell sorting by using transcriptional biosensors for their enzyme and strain engineering campaigns.

Sensor-Enabled Alleviation of Product Inhibition in Chorismate Pyruvate-Lyase

Product inhibition is a frequent bottleneck in industrial enzymes, and testing mutations to alleviate product inhibition via traditional methods remains challenging as many variants need to be tested against multiple substrate and product concentrations. Further, traditional screening methods are conducted in vitro, and resulting enzyme variants may perform differently in vivo in the context of whole-cell metabolism and regulation. In this study, we address these two problems by establishing a high-throughput screening method to alleviate product inhibition in an industrially relevant enzyme, chorismate pyruvate-lyase (UbiC). First, we engineered a highly specific, genetically encoded biosensor for 4-hydroxybenzoate (4HB) in an industrially relevant host, Pseudomonas putida KT2440. We subsequently applied the biosensor to detect the activity of a heterologously expressed UbiC that converts chorismate into 4HB and pyruvate. By using benzoate as a product surrogate that inhibits UbiC without activating the biosensor, we were able to efficiently create and screen a diversified library for UbiC variants with reduced product inhibition. Introduction of the improved UbiC enzyme variant into an experimental production strain for the industrial precursor cis,cis-muconic acid (muconate), enabled a >2-fold yield improvement for glucose to muconate conversion when the new UbiC variant was expressed from a plasmid and a 60% yield increase when the same UbiC variant was genomically integrated into the strain. Overall, this work demonstrates that by coupling a library of enzyme variants to whole-cell catalysis and biosensing, variants with reduced product inhibition can be identified, and that this improved enzyme can result in increased titers of a downstream molecule of interest.

A Genetically Encoded Biosensor for Monitoring Isoprene Production in Engineered Escherichia coli

Isoprene is a valuable precursor for synthetic rubber and a signature product of terpenoid pathways. Here, we developed an isoprene biosensor by employing a TbuT transcriptional regulator of Ralstonia pickettii to express a fluorescent reporter gene in response to intracellular isoprene in engineered Escherichia coli. The TbuT regulator recognizes isoprene as its less-preferred effector molecule; thus, we amplified the reporter gene expression using a T7 RNA polymerase-mediated transcriptional cascade and iteratively tuned the promoter transcribing tbuT to improve the sensitivity for detecting isoprene. When the engineered E. coli cells expressed heterologous genes for isoprene biosynthesis, the intracellular isoprene was expelled and the tbuT transcription factor was subsequently activated, leading to gfp expression. The chromosomal isoprene biosensor showed a linear correlation between GFP fluorescence and intracellular isoprene concentration. Using this chromosomal isoprene biosensor, we successfully identified the highest isoprene producer among four different E. coli strains producing different amounts of isoprene. The isoprene biosensor presented here can enable high-throughput screening of isoprene synthases and metabolic pathways for efficient and sustainable production of bioisoprene in engineered microbes.

An E. coli biosensor for screening of cDNA libraries for isochorismate pyruvate lyase-encoding cDNAs

Salicylic acid (SA) is an essential hormone for development and induced defense against biotrophic pathogens in plants. The formation of SA mainly derives from chorismate via demonstrated isochorismate synthase (ICS) and presumed isochorismate pyruvate lyase (IPL)-mediated steps in Arabidopsis thaliana, but so far no plant enzyme displaying IPL activity has been identified. Here, we developed an E. coli SA biosensor to screen for IPL activity based on the SalR regulator/salA promoter combination from Acinetobacter sp ADP1, to control the expression of the reporter luxCDABE. The biosensor was responsive to micromolar concentrations of exogenous SA, and to endogenous SA produced after transformation with a plasmid permitting IPTG-inducible expression of bacterial IPL in this biosensor strain. After screening a cDNA library constructed from turnip crinkle virus (TCV)-infected Arabidopsis ecotype Di-17, we identified an enzyme, PRXR1, as a putative IPL that converts isochorismate into SA. Our results provide a new experimental approach to identify IPL and new insights into the SA biosynthesis pathway in Arabidopsis.

In vivo biosensors: mechanisms, development, and applications

In vivo biosensors can recognize and respond to specific cellular stimuli. In recent years, biosensors have been increasingly used in metabolic engineering and synthetic biology, because they can be implemented in synthetic circuits to control the expression of reporter genes in response to specific cellular stimuli, such as a certain metabolite or a change in pH. There are many types of natural sensing devices, which can be generally divided into two main categories: protein-based and nucleic acid-based. Both can be obtained either by directly mining from natural genetic components or by engineering the existing genetic components for novel specificity or improved characteristics. A wide range of new technologies have enabled rapid engineering and discovery of new biosensors, which are paving the way for a new era of biotechnological progress. Here, we review recent advances in the design, optimization, and applications of in vivo biosensors in the field of metabolic engineering and synthetic biology.

Engineering a vitamin B12 high-throughput screening system by riboswitch sensor in Sinorhizobium meliloti

Background

As a very important coenzyme in the cell metabolism, Vitamin B₁₂ (cobalamin, VB₁₂) has been widely used in food and medicine fields. The complete biosynthesis of VB₁₂ requires approximately 30 genes, but overexpression of these genes did not result in expected increase of VB₁₂ production. High-yield VB₁₂-producing strains are usually obtained by mutagenesis treatments, thus developing an efficient screening approach is urgently needed.

Result

By the help of engineered strains with varied capacities of VB₁₂ production, a riboswitch library was constructed and screened, and the btuB element from Salmonella typhimurium was identified as the best regulatory device. A flow cytometry high-throughput screening system was developed based on the btuB riboswitch with high efficiency to identify positive mutants. Mutation of Sinorhizobium meliloti (S. meliloti) was optimized using the novel mutation technique of atmospheric and room temperature plasma (ARTP). Finally, the mutant S. meliloti MC5–2 was obtained and considered as a candidate for industrial applications. After 7 d’s cultivation on a rotary shaker at 30 °C, the VB₁₂ titer of S. meliloti MC5–2 reached 156 ± 4.2 mg/L, which was 21.9% higher than that of the wild type strain S. meliloti 320 (128 ± 3.2 mg/L). The genome of S. meliloti MC5–2 was sequenced, and gene mutations were identified and analyzed.

Conclusion

To our knowledge, it is the first time that a riboswitch element was used in S. meliloti. The flow cytometry high-throughput screening system was successfully developed and a high-yield VB₁₂ producing strain was obtained. The identified and analyzed gene mutations gave useful information for developing high-yield strains by metabolic engineering. Overall, this work provides a useful high-throughput screening method for developing high VB₁₂-yield strains.

Electronic supplementary material

The online version of this article (10.1186/s12896-018-0441-2) contains supplementary material, which is available to authorized users.

Electrically-receptive and thermally-responsive paper-based sensor chip for rapid detection of bacterial cells

Although significant technological advancements have been made in the development of analytical biosensor chips for detecting bacterial strains (E. coli, S. Mutans and B. Subtilis), critical requirements i.e. limit of detection (LOD), fast time of response, ultra-sensitivity with high reproducibility and good shelf-life with robust sensing capability have yet to be met within a single sensor chip. In order to achieve these criteria, we present an electrically-receptive thermally-responsive (ER-TR) sensor chip comprised of simple filter paper used as substrate coated with composite of poly(N-isopropylacrylamide) polymer (PNIPAm) - graphene nanoplatelet (GR) followed by evaporation of Au electrodes for capturing both Gram-positive (S. mutans and B. subtilis) and Gram-negative (E. coli) bacterial cells in real-time. Autoclave water, tap water, lake water and milk samples were tested with ER-TR chip with and without bacterial strains at varying concentration range 10¹-10⁵ cells/mL. The sensor was integrated with in-house built printed circuit board (PCB) to transmit/receive electrical signals. The interaction of E. coli, S. mutans and B. subtilis cells with fibers of PNIPAm-GR resulted in a change of electrical resistance and the readout was monitored wirelessly in real-time using MATLAB algorithm. Finally, prepared ER-TR chip exhibited the reproducibility of 85-97% with shelf-life of up to four weeks after testing with lake water sample.

A protocatechuate biosensor for Pseudomonas putida KT2440 via promoter and protein evolution

Robust fluorescence-based biosensors are emerging as critical tools for high-throughput strain improvement in synthetic biology. Many biosensors are developed in model organisms where sophisticated synthetic biology tools are also well established. However, industrial biochemical production often employs microbes with phenotypes that are advantageous for a target process, and biosensors may fail to directly transition outside the host in which they are developed. In particular, losses in sensitivity and dynamic range of sensing often occur, limiting the application of a biosensor across hosts. Here we demonstrate the optimization of an Escherichia coli-based biosensor in a robust microbial strain for the catabolism of aromatic compounds, Pseudomonas putida KT2440, through a generalizable approach of modulating interactions at the protein-DNA interface in the promoter and the protein-protein dimer interface. The high-throughput biosensor optimization approach demonstrated here is readily applicable towards other allosteric regulators.

•

A biosensor optimized for a robust, industrially useful P. putida strain.

•

Modulation of protein-DNA and protein-protein interactions pursued.

•

Offers a generalized optimization protocol for transcription factor-based sensors.

•

Intracellular metabolite production and detection made possible in P. putida.

•

Functional biosensor in P. putida will allow high throughput strain evolution.

An Improved Whole-Cell Biosensor for the Discovery of Lignin-Transforming Enzymes in Functional Metagenomic Screens

The discovery and utilization of biocatalysts that selectively valorize lignocellulose is critical to the profitability of next-generation biorefineries. Here, we report the development of a refactored, whole-cell, GFP-based biosensor for high-throughput identification of biocatalysts that transform lignin into specialty chemicals from environmental DNA of uncultivable archaea and bacteria. The biosensor comprises the transcriptional regulator and promoter of the emrRAB operon of E. coli, and the configuration of the biosensor was tuned with the aid of mathematical model. The biosensor sensitively and selectively detects vanillin and syringaldehyde, and responds linearly over a wide detection range. We employed the biosensor to screen 42 520 fosmid clones comprising environmental DNA isolated from two coal beds and successfully identified 147 clones that transform hardwood kraft lignin to vanillin and syringaldehyde.

Evolution of enzymes with new specificity by high-throughput screening using DmpR-based genetic circuits and multiple flow cytometry rounds

Genetic circuit-based biosensors are useful in detecting target metabolites or in vivo enzymes using transcription factors (Tx) as a molecular switch to express reporter signals, such as cellular fluorescence and antibiotic resistance. Herein, a phenol-detecting Tx (DmpR) was employed as a critical tool for enzyme engineering, specifically for the rapid analysis of numerous mutants with multiple mutations at the active site of tryptophan-indole lyase (TIL, EC 4.1.99.1). Cellular fluorescence was monitored cell-by-cell using flow cytometry to detect the creation of phenolic compounds by a new tyrosine-phenol-lyase (TPL, EC 4.1.99.2). In the TIL scaffold, target amino acids near the indole ring (Asp¹³⁷, Phe³⁰⁴, Val³⁹⁴, Ile³⁹⁶ and His⁴⁶³) were mutated randomly to construct a large diversity of specificity variations. Collection of candidate positives by cell sorting using flow cytometry and subsequent shuffling of beneficial mutations identified a critical hit with four mutations (D137P, F304D, V394L, and I396R) in the TIL sequence. The variant displayed one-thirteenth the level of TPL activity, compared with native TPLs, and completely lost the original TIL activity. The findings demonstrate that hypersensitive, Tx-based biosensors could be useful critically to generate new activity from a related template, which would alleviate the current burden to high-throughput screening.

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.

A growth- and bioluminescence-based bioreporter for the in vivo detection of novel biocatalysts

The use of bioreporters in high-throughput screening for small molecules is generally laborious and/or expensive. The technology can be simplified by coupling the generation of a desired compound to cell survival, causing only positive cells to stay in the pool of generated variants. Here, a dual selection/screening system was developed for the in vivo detection of novel biocatalysts. The sensor part of the system is based on the transcriptional regulator AraC, which controls expression of both a selection reporter (LeuB or KmR; enabling growth) for rapid reduction of the initially large library size and a screening reporter (LuxCDABE; causing bioluminescence) for further quantification of the positive variants. Of four developed systems, the best system was the medium copy system with KmR as selection reporter. As a proof of principle, the system was tested for the selection of cells expressing an l-arabinose isomerase derived from mesophilic Escherichia coli or thermophilic Geobacillus thermodenitrificans. A more than a millionfold enrichment of cells with l-arabinose isomerase activity was demonstrated by selection and exclusion of false positives by screening. This dual selection/screening system is an important step towards an improved detection method for small molecules, and thereby for finding novel biocatalysts.

Rapid Thermostabilization of Bacillus thuringiensis Serovar Konkukian 97-27 Dehydroshikimate Dehydratase through a Structure-Based Enzyme Design and Whole Cell Activity Assay

Thermostabilization of an enzyme with complete retention of catalytic efficiency was demonstrated on recombinant 3-dehydroshikimate dehydratase (DHSase or wtAsbF) from Bacillus thuringiensis serovar konkukian 97-27 (hereafter, B. thuringiensis 97-27). The wtAsbF is relatively unstable at 37 °C, in vitro (t_1/2³⁷ = 15 min), in the absence of divalent metal. We adopted a structure-based design to identify stabilizing mutations and created a combinatorial library based upon predicted mutations at specific locations on the enzyme surface. A diversified asbF library (∼2000 variants) was expressed in E. coli harboring a green fluorescent protein (GFP) reporter system linked to the product of wtAsbF activity (3,4-dihydroxybenzoate, DHB). Mutations detrimental to DHSase function were rapidly eliminated using a high throughput fluorescence activated cell sorting (FACS) approach. After a single sorting round and heat screen at 50 °C, a triple AsbF mutant (Mut1), T61N, H135Y, and H257P, was isolated and characterized. The half-life of Mut1 at 37 °C was >10-fold higher than the wtAsbF (t_1/2³⁷ = 169 min). Further, the second-order rate constants for both wtAsbF and Mut1 were approximately equal (9.9 × 10⁵ M^-1 s^-1, 7.8 × 10⁵ M^-1 s^-1, respectively), thus demonstrating protein thermostability did not come at the expense of enzyme thermophilicity. In addition, in vivo overexpression of Mut1 in E. coli resulted in a ∼60-fold increase in functional enzyme when compared to the wild-type enzyme under the identical expression conditions. Finally, overexpression of the thermostable AsbF resulted in an approximate 80-120% increase in DHB accumulation in the media relative to the wild-type enzyme.

Tailor-made transcriptional biosensors for optimizing microbial cell factories

Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today's metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature's richness. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

A microbial sensor for organophosphate hydrolysis exploiting an engineered specificity switch in a transcription factor

A whole-cell biosensor utilizing a transcription factor (TF) is an effective tool for sensitive and selective detection of specialty chemicals or anthropogenic molecules, but requires access to an expanded repertoire of TFs. Using homology modeling and ligand docking for binding pocket identification, assisted by conservative mutations in the pocket, we engineered a novel specificity in an Acinetobacter TF, PobR, to ‘sense’ a chemical p-nitrophenol (pNP) and measured the response via a fluorescent protein reporter expressed from a PobR promoter. Out of 10⁷ variants of PobR, four were active when dosed with pNP, with two mutants showing a specificity switch from the native effector 4-hydroxybenzoate (4HB). One of the mutants, pNPmut1 was then used to create a smart microbial cell responding to pNP production from hydrolysis of an insecticide, paraoxon, in a coupled assay involving phosphotriesterase (PTE) enzyme expressed from a separate promoter. We show the fluorescence of the cells correlated with the catalytic efficiency of the PTE variant expressed in each cell. High selectivity between similar molecules (4HB versus pNP), high sensitivity for pNP detection (∼2 μM) and agreement of apo- and holo-structures of PobR scaffold with predetermined computational models are other significant results presented in this work.

Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System

The recent development of a high-throughput single-cell assay technique enables the screening of novel enzymes based on functional activities from a large-scale metagenomic library(1). We previously proposed a genetic enzyme screening system (GESS) that uses dimethylphenol regulator activated by phenol or p-nitrophenol. Since a vast amount of natural enzymatic reactions produce these phenolic compounds from phenol deriving substrates, this single genetic screening system can be theoretically applied to screen over 200 different enzymes in the BRENDA database. Despite the general applicability of GESS, applying the screening process requires a specific procedure to reach the maximum flow cytometry signals. Here, we detail the developed screening process, which includes metagenome preprocessing with GESS and the operation of a flow cytometry sorter. Three different phenolic substrates (p-nitrophenyl acetate, p-nitrophenyl-β-D-cellobioside, and phenyl phosphate) with GESS were used to screen and to identify three different enzymes (lipase, cellulase, and alkaline phosphatase), respectively. The selected metagenomic enzyme activities were confirmed only with the flow cytometry but DNA sequencing and diverse in vitro analysis can be used for further gene identification.

Biosensor-based engineering of biosynthetic pathways

Biosynthetic pathways provide an enzymatic route from inexpensive renewable resources to valuable metabolic products such as pharmaceuticals and plastics. Designing these pathways is challenging due to the complexities of biology. Advances in the design and construction of genetic variants has enabled billions of cells, each possessing a slightly different metabolic design, to be rapidly generated. However, our ability to measure the quality of these designs lags by several orders of magnitude. Recent research has enabled cells to report their own success in chemical production through the use of genetically encoded biosensors. A new engineering discipline is emerging around the creation and application of biosensors. Biosensors, implemented in selections and screens to identify productive cells, are paving the way for a new era of biotechnological progress.

High-throughput evaluation of synthetic metabolic pathways

A central challenge in the field of metabolic engineering is the efficient identification of a metabolic pathway genotype that maximizes specific productivity over a robust range of process conditions. Here we review current methods for optimizing specific productivity of metabolic pathways in living cells. New tools for library generation, computational analysis of pathway sequence-flux space, and high-throughput screening and selection techniques are discussed.

Genetically encoded sensors enable real-time observation of metabolite production

Engineering cells to produce valuable metabolic products is hindered by the slow and laborious methods available for evaluating product concentration. Consequently, many designs go unevaluated, and the dynamics of product formation over time go unobserved. In this work, we develop a framework for observing product formation in real time without the need for sample preparation or laborious analytical methods. We use genetically encoded biosensors derived from small-molecule responsive transcription factors to provide a fluorescent readout that is proportional to the intracellular concentration of a target metabolite. Combining an appropriate biosensor with cells designed to produce a metabolic product allows us to track product formation by observing fluorescence. With individual cells exhibiting fluorescent intensities proportional to the amount of metabolite they produce, high-throughput methods can be used to rank the quality of genetic variants or production conditions. We observe production of several renewable plastic precursors with fluorescent readouts and demonstrate that higher fluorescence is indeed an indicator of higher product titer. Using fluorescence as a guide, we identify process parameters that produce 3-hydroxypropionate at 4.2 g/L, 23-fold higher than previously reported. We also report, to our knowledge, the first engineered route from glucose to acrylate, a plastic precursor with global sales of $14 billion. Finally, we monitor the production of glucarate, a replacement for environmentally damaging detergents, and muconate, a renewable precursor to polyethylene terephthalate and nylon with combined markets of $51 billion, in real time, demonstrating that our method is applicable to a wide range of molecules.

Novel technologies provide more engineering strategies for amino acid-producing microorganisms

Traditionally, amino acid-producing strains were obtained by random mutagenesis and subsequent selection. With the development of genetic and metabolic engineering techniques, various microorganisms with high amino acid production yields are now constructed by rational design of targeted biosynthetic pathways. Recently, novel technologies derived from systems and synthetic biology have emerged and open a new promising avenue towards the engineering of amino acid production microorganisms. In this review, these approaches, including rational engineering of rate-limiting enzymes, real-time sensing of end-products, pathway optimization on the chromosome, transcription factor-mediated strain improvement, and metabolic modeling and flux analysis, were summarized with regard to their application in microbial amino acid production.