A high-throughput approach to identify genomic variants of bacterial metabolite producers at the single-cell level

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.

Ligify: Automated Genome Mining for Ligand-Inducible Transcription Factors

Prokaryotic transcription factors can be repurposed into biosensors for the ligand-inducible control of gene expression, but the landscape of chemical ligands for which biosensors exist is extremely limited. To expand this landscape, we developed Ligify, a web application that leverages information in enzyme reaction databases to predict transcription factors that may be responsive to user-defined chemicals. Candidate transcription factors are then incorporated into automatically generated plasmid sequences that are designed to express GFP in response to the target chemical. Our benchmarking analyses demonstrated that Ligify correctly predicted 31/100 previously validated biosensors and highlighted strategies for further improvement. We then used Ligify to build a panel of genetic circuits that could induce a 47-fold, 5-fold, 9-fold, and 27-fold change in fluorescence in response to D-ribose, L-sorbose, isoeugenol, and 4-vinylphenol, respectively. Ligify should enhance the ability of researchers to quickly develop biosensors for an expanded range of chemicals and is publicly available at https://ligify.groov.bio.

Culture-free identification of fast-growing cyanobacteria cells by Raman-activated gravity-driven encapsulation and sequencing

By directly converting solar energy and carbon dioxide into biobased products, cyanobacteria are promising chassis for photosynthetic biosynthesis. To make cyanobacterial photosynthetic biosynthesis technology economically feasible on industrial scales, exploring and engineering cyanobacterial chassis and cell factories with fast growth rates and carbon fixation activities facing environmental stresses are of great significance. To simplify and accelerate the screening for fast-growing cyanobacteria strains, a method called Individual Cyanobacteria Vitality Tests and Screening (iCyanVS) was established. We show that the 13C incorporation ratio of carotenoids can be used to measure differences in cell growth and carbon fixation rates in individual cyanobacterial cells of distinct genotypes that differ in growth rates in bulk cultivations, thus greatly accelerating the process screening for fastest-growing cells. The feasibility of this approach is further demonstrated by phenotypically and then genotypically identifying individual cyanobacterial cells with higher salt tolerance from an artificial mutant library via Raman-activated gravity-driven encapsulation and sequencing. Therefore, this method should find broad applications in growth rate or carbon intake rate based screening of cyanobacteria and other photosynthetic cell factories.

Mechanisms and biotechnological applications of transcription factors

Transcription factors play an indispensable role in maintaining cellular viability and finely regulating complex internal metabolic networks. These crucial bioactive functions rely on their ability to respond to effectors and concurrently interact with binding sites. Recent advancements have brought innovative insights into the understanding of transcription factors. In this review, we comprehensively summarize the mechanisms by which transcription factors carry out their functions, along with calculation and experimental-based methods employed in their identification. Additionally, we highlight recent achievements in the application of transcription factors in various biotechnological fields, including cell engineering, human health, and biomanufacturing. Finally, the current limitations of research and provide prospects for future investigations are discussed. This review will provide enlightening theoretical guidance for transcription factors engineering.

Biosensors in microalgae: A roadmap for new opportunities in synthetic biology and biotechnology

Biosensors are powerful tools to investigate, phenotype, improve and prototype microbial strains, both in fundamental research and in industrial contexts. Genetic and biotechnological developments now allow the implementation of synthetic biology approaches to novel different classes of microbial hosts, for example photosynthetic microalgae, which offer unique opportunities. To date, biosensors have not yet been implemented in phototrophic eukaryotic microorganisms, leaving great potential for novel biological and technological advancements untapped. Here, starting from selected biosensor technologies that have successfully been implemented in heterotrophic organisms, we project and define a roadmap on how these could be applied to microalgae research. We highlight novel opportunities for the development of new biosensors, identify critical challenges, and finally provide a perspective on the impact of their eventual implementation to tackle research questions and bioengineering strategies. From studying metabolism at the single-cell level to genome-wide screen approaches, and assisted laboratory evolution experiments, biosensors will greatly impact the pace of progress in understanding and engineering microalgal metabolism. We envision how this could further advance the possibilities for unraveling their ecological role, evolutionary history and accelerate their domestication, to further drive them as resource-efficient production hosts.

L-lysine production by systems metabolic engineering of an NADPH auto-regulated Corynebacterium glutamicum

Here, the systems metabolic engineering of L-lysine-overproducing Corynebacterium glutamicum is described to create a highly efficient microorganism producer. The key chromosomal mutations associated with L-lysine synthesis were identified based on whole-genome sequencing. The carbon flux was subsequently redirected into the L-lysine synthesis pathway and increased the availability of energy and product transport systems required for L-lysine synthesis. In addition, a promoter library sensitive to intracellular L-lysine concentration was constructed and applied to regulate the NADPH pool dynamically. In the fed-batch fermentation experiment, the L-lysine titer of the final engineered strain was 223.4 ± 6.5 g/L. This study is the first to improve L-lysine production by enhancing ATP supply and NADPH self-regulation to improve the intracellular environment.

Growth-coupled high throughput selection for directed enzyme evolution

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

Genetically Encoded Biosensor Engineering for Application in Directed Evolution

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

Design and application of artificial rare L-lysine codons in Corynebacterium glutamicum

Background: L-lysine is widely used in the feed, food, and pharmaceutical industries, and screening for high L-lysine-producing strains has become a key goal for the industry. Methods: We constructed the rare L-lysine codon AAA by corresponding tRNA promoter replacement in C. glutamicum. Additionally, a screening marker related to the intracellular L-lysine content was constructed by converting all L-lysine codons of enhanced green fluorescent protein (EGFP) into the artificial rare codon AAA. The artificial EGFP was then ligated into pEC-XK99E and transformed into competent Corynebacterium glutamicum 23604 cells with the rare L-lysine codon. After atmospheric and room-temperature plasma mutation and induction culture, 55 mutants (0.01% of total cells) with stronger fluorescence were sorted using flow cytometry, and further screened by fermentation in a 96-deep-well plate and 500 mL shaker. Results: The fermentation results showed that the L-lysine production was increased by up to 9.7% in the mutant strains with higher fluorescence intensities, and that the highest screening positive rate was 69%, compared with that in the wild-type strain. Conclusion: The application of artificially constructed rare codons in this study represents an efficient, accurate, and simple method for screening other amino acid-producing microorganisms.

Applications and Tuning Strategies for Transcription Factor-Based Metabolite Biosensors

Transcription factor (TF)-based biosensors are widely used for the detection of metabolites and the regulation of cellular pathways in response to metabolites. Several challenges hinder the direct application of TF-based sensors to new hosts or metabolic pathways, which often requires extensive tuning to achieve the optimal performance. These tuning strategies can involve transcriptional or translational control depending on the parameter of interest. In this review, we highlight recent strategies for engineering TF-based biosensors to obtain the desired performance and discuss additional design considerations that may influence a biosensor's performance. We also examine applications of these sensors and suggest important areas for further work to continue the advancement of small-molecule biosensors.

Rapid combinatorial rewiring of metabolic networks for enhanced poly(3-hydroxybutyrate) production in Corynebacterium glutamicum

BACKGROUND

The disposal of plastic waste is a major environmental challenge. With recent advances in microbial genetic and metabolic engineering technologies, microbial polyhydroxyalkanoates (PHAs) are being used as next-generation biomaterials to replace petroleum-based synthetic plastics in a sustainable future. However, the relatively high production cost of bioprocesses hinders the production and application of microbial PHAs on an industrial scale.

RESULTS

Here, we describe a rapid strategy to rewire metabolic networks in an industrial microorganism, Corynebacterium glutamicum, for the enhanced production of poly(3-hydroxybutyrate) (PHB). A three-gene PHB biosynthetic pathway in Rasltonia eutropha was refactored for high-level gene expression. A fluorescence-based quantification assay for cellular PHB content using BODIPY was devised for the rapid fluorescence-activated cell sorting (FACS)-based screening of a large combinatorial metabolic network library constructed in C. glutamicum. Rewiring metabolic networks across the central carbon metabolism enabled highly efficient production of PHB up to 29% of dry cell weight with the highest cellular PHB productivity ever reported in C. glutamicum using a sole carbon source.

CONCLUSIONS

We successfully constructed a heterologous PHB biosynthetic pathway and rapidly optimized metabolic networks across central metabolism in C. glutamicum for enhanced production of PHB using glucose or fructose as a sole carbon source in minimal media. We expect that this FACS-based metabolic rewiring framework will accelerate strain engineering processes for the production of diverse biochemicals and biopolymers.

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

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

Development of a Transcriptional Factor PuuR-Based Putrescine-Specific Biosensor in Corynebacterium glutamicum

Corynebacterium glutamicum is regarded as an industrially important microbial cell factory and is widely used to produce various value-added chemicals. Because of the importance of C. glutamicum applications, current research is increasingly focusing on developing C. glutamicum synthetic biology platforms. Because of its ability to condense with adipic acid to synthesize the industrial plastic nylon-46, putrescine is an important platform compound of industrial interest. Developing a high-throughput putrescine biosensor can aid in accelerating the design-build-test cycle of cell factories (production strains) to achieve high putrescine-generating strain production in C. glutamicum. This study developed a putrescine-specific biosensor (pSenPuuR) in C. glutamicum using Escherichia coli-derived transcriptional factor PuuR. The response characteristics of the biosensor to putrescine were further improved by optimizing the genetic components of pSenPuuR, such as the response promoter, reporter protein, and promoter for controlling PuuR expression. According to the findings of the study, pSenPuuR has the potential to be used to assess putrescine production in C. glutamicum and is suitable for high-throughput genetic variant screening.

Microbial lifelines in bioprocesses: From concept to application

Bioprocesses are scaled up for the production of large product quantities. With larger fermenter volumes, mixing becomes increasingly inefficient and environmental gradients get more prominent than in smaller scales. Environmental gradients have an impact on the microorganism's metabolism, which makes the prediction of large-scale performance difficult and can lead to scale-up failure. A promising approach for improved understanding and estimation of dynamics of microbial populations in large-scale bioprocesses is the analysis of microbial lifelines. The lifeline of a microbe in a bioprocess is the experience of environmental gradients from a cell's perspective, which can be described as a time series of position, environment and intracellular condition. Currently, lifelines are predominantly determined using models with computational fluid dynamics, but new technical developments in flow-following sensor particles and microfluidic single-cell cultivation open the door to a more interdisciplinary concept. We critically review the current concepts and challenges in lifeline determination and application of lifeline analysis, as well as strategies for the integration of these techniques into bioprocess development. Lifelines can contribute to a successful scale-up by guiding scale-down experiments and identifying strain engineering targets or bioreactor optimisations.

Synthetic biology tools for engineering Corynebacterium glutamicum

Corynebacterium glutamicum is a promising organism for the industrial production of amino acids, fuels, and various value-added chemicals. From the whole genome sequence release, C. glutamicum has been valuable in the field of industrial microbiology and biotechnology. Continuous discovery of genetic manipulations and regulation mechanisms has developed C. glutamicum as a synthetic biology platform chassis. This review summarized diverse genomic manipulation technologies and gene expression tools for static, dynamic, and multiplex control at transcription and translation levels. Moreover, we discussed the current challenges and applicable tools to C. glutamicum for future advancements.

An enzymatic colorimetric whole-cell biosensor for high-throughput identification of lysine overproducers

L-lysine is a crucial nutrient for both humans and animals, and its main commercial use is as a supplement in animal feed to promote chicken and other animal growth. Fluorescence biosensors based on the transcriptional regulator have been developed for high-throughput screening of L-lysine producers. However, due to its inability to specifically detect lysine, this fluorescent biosensor cannot be employed to screen high-yielding strains. Here, we present a novel technique for observing L-lysine concentrations within individual Corynebacterium glutamicum cells. The transcriptional regulator LysG and its binding site, as well as the phytoene desaturase that catalyzes the synthesis of the red pigment, make up the functional core of the biosensor. The lysine-sensitive mutant LysG^{(E123Y, E125A)}, which improved the sensitivity of biosensors, was generated by site-directed saturation mutagenesis. In addition, we increased the lysine-induced chromogenic biosensor response to 320 mM by optimizing the L-lysine export mechanism and the pathway for the synthesis of lycopene precursors. The direct identification of producers with elevated L-lysine accumulation is thus made straightforward by colorimetric screening. Lys-8, a lysine producer with a maximum lysine titer of 316.2 mM, was sorted out based on the biosensor. The enzymatic colorimetric biosensor constructed here is a simple tool with great potential for the development of high-level lysine-producing C. glutamicum.

Genetic Circuit Design in Rhizobacteria

Genetically engineered plants hold enormous promise for tackling global food security and agricultural sustainability challenges. However, construction of plant-based genetic circuitry is constrained by a lack of well-characterized genetic parts and circuit design rules. In contrast, advances in bacterial synthetic biology have yielded a wealth of sensors, actuators, and other tools that can be used to build bacterial circuitry. As root-colonizing bacteria (rhizobacteria) exert substantial influence over plant health and growth, genetic circuit design in these microorganisms can be used to indirectly engineer plants and accelerate the design-build-test-learn cycle. Here, we outline genetic parts and best practices for designing rhizobacterial circuits, with an emphasis on sensors, actuators, and chassis species that can be used to monitor/control rhizosphere and plant processes.

Advances in Single-Cell Toxicogenomics in Environmental Toxicology

The toxicity evaluation system of environmental pollutants has undergone numerous changes due to the application of new technologies. Single-cell toxicogenomics is rapidly changing our view on environmental toxicology by increasing the resolution of our analysis to the level of a single cell. Applications of this technology in environmental toxicology have begun to emerge and are rapidly expanding the portfolio of existing technologies and applications. Here, we first summarized different methods involved in single-cell isolation and amplification in single-cell sequencing process, compared the advantages and disadvantages of different methods, and analyzed their development trends. Then, we reviewed the main advances of single-cell toxicogenomics in environmental toxicology, emphatically analyzed the application prospects of this technology in identifying the target cells of pollutants in early embryos, clarifying the heterogeneous response of cell subtypes to pollutants, and finding pathogenic bacteria in unknown microbes, and highlighted the unique characteristics of this approach with high resolution, high throughput, and high specificity by examples. We also offered a prediction of the further application of this technology and the revolution it brings in environmental toxicology. Overall, these advances will provide practical solutions for controlling or mitigating exogenous toxicological effects that threaten human and ecosystem health, contribute to improving our understanding of the physiological processes affected by pollutants, and lead to the emergence of new methods of pollution control.

Single cell mutant selection for metabolic engineering of actinomycetes

Actinomycetes are important producers of pharmaceuticals and industrial enzymes. However, wild type strains require laborious development prior to industrial usage. Here we present a generally applicable reporter-guided metabolic engineering tool based on random mutagenesis, selective pressure, and single-cell sorting. We developed fluorescence-activated cell sorting (FACS) methodology capable of reproducibly identifying high-performing individual cells from a mutant population directly from liquid cultures. Actinomycetes are an important source of catabolic enzymes, where product yields determine industrial viability. We demonstrate 5-fold yield improvement with an industrial cholesterol oxidase ChoD producer Streptomyces lavendulae to 20.4 U g^-1 in three rounds. Strain development is traditionally followed by production medium optimization, which is a time-consuming multi-parameter problem that may require hard to source ingredients. Ultra-high throughput screening allowed us to circumvent medium optimization and we identified high ChoD yield production strains directly from mutant libraries grown under preset culture conditions. Genome-mining based drug discovery is a promising source of bioactive compounds, which is complicated by the observation that target metabolic pathways may be silent under laboratory conditions. We demonstrate our technology for drug discovery by activating a silent mutaxanthene metabolic pathway in Amycolatopsis. We apply the method for industrial strain development and increase mutaxanthene yields 9-fold to 99 mg l^-1 in a second round of mutant selection. In summary, the ability to screen tens of millions of mutants in a single cell format offers broad applicability for metabolic engineering of actinomycetes for activation of silent metabolic pathways and to increase yields of proteins and natural products.

Rational Metabolic Engineering Combined with Biosensor-Mediated Adaptive Laboratory Evolution for l-Cysteine Overproduction from Glycerol in Escherichia coli

l-Cysteine is an important sulfur-containing amino acid with numerous applications in the pharmaceutical and cosmetic industries. The microbial production of l-cysteine has received substantial attention, and the supply of the precursor l-serine is important in l-cysteine biosynthesis. In this study, to achieve l-cysteine overproduction, we first increased l-serine production by deleting genes involved in the pathway of l-serine degradation to glycine (serine hydroxymethyl transferase, SHMT, encoded by glyA genes) in strain 4W (with l-serine titer of 1.1 g/L), thus resulting in strain 4WG with l-serine titer of 2.01 g/L. Second, the serine-biosensor based on the transcriptional regulator NCgl0581 of C. glutamicum was constructed in E. coli, and the validity and sensitivity of the biosensor were demonstrated in E. coli. Then 4WG was further evolved through adaptive laboratory evolution (ALE) combined with serine-biosensor, thus yielding the strain 4WGX with 4.13 g/L l-serine production. Moreover, the whole genome of the evolved strain 4WGX was sequenced, and ten non-synonymous mutations were found in the genome of strain 4WGX compared with strain 4W. Finally, 4WGX was used as the starting strain, and deletion of the l-cysteine desulfhydrases (encoded by tnaA), overexpression of serine acetyltransferase (encoded by cysE) and the key enzyme of transport pathway (encoded by ydeD) were performed in strain 4WGX. The recombinant strain 4WGX-∆tnaA-cysE-ydeD can produce 313.4 mg/L of l-cysteine using glycerol as the carbon source. This work provides an efficient method for the biosynthesis of value-added commodity products associated with glycerol conversion.

l-Serine Biosensor-Controlled Fermentative Production of l-Tryptophan Derivatives by Corynebacterium glutamicum

Simple Summary

l-tryptophan is an amino acid found in proteins. Its derivatives, such as hydroxylated or halogenated l-tryptophans, find applications in the chemical and pharmaceutical industries, for example, in therapeutic peptides. Biotechnology provides a sustainable way for the production of l-tryptophan and its derivatives. In the final reaction of l-tryptophan biosynthesis in bacteria, such as Corynebacterium glutamicum, another amino acid, l-serine, is incorporated. Here, we show that C. glutamicum TrpB is able to convert indole derivatives, which were added to cells synthesizing l-serine, to the corresponding l-tryptophan derivatives. The gene trpB was expressed under the control of the l-serine-responsive transcriptional activator SerR in the C. glutamicum cells engineered for this fermentation process.

Abstract

l-Tryptophan derivatives, such as hydroxylated or halogenated l-tryptophans, are used in therapeutic peptides and agrochemicals and as precursors of bioactive compounds, such as serotonin. l-Tryptophan biosynthesis depends on another proteinogenic amino acid, l-serine, which is condensed with indole-3-glycerophosphate by tryptophan synthase. This enzyme is composed of the α-subunit TrpA, which catalyzes the retro-aldol cleavage of indole-3-glycerol phosphate, yielding glyceraldehyde-3-phosphate and indole, and the β-subunit TrpB that catalyzes the β-substitution reaction between indole and l-serine to water and l-tryptophan. TrpA is reported as an allosteric actuator, and its absence severely attenuates TrpB activity. In this study, however, we showed that Corynebacterium glutamicum TrpB is catalytically active in the absence of TrpA. Overexpression of C. glutamicumtrpB in a trpBA double deletion mutant supported growth in minimal medium only when exogenously added indole was taken up into the cell and condensed with intracellularly synthesized l-serine. The fluorescence reporter gene of an l-serine biosensor, which was based on the endogenous transcriptional activator SerR and its target promoter P_serE, was replaced by trpB. This allowed for l-serine-dependent expression of trpB in an l-serine-producing strain lacking TrpA. Upon feeding of the respective indole derivatives, this strain produced the l-tryptophan derivatives 5-hydroxytryptophan, 7-bromotryptophan, and 5-fluorotryptophan.

Whole-Cell Biosensor and Producer Co-cultivation-Based Microfludic Platform for Screening Saccharopolyspora erythraea with Hyper Erythromycin Production

Actinomycetes are versatile secondary metabolite producers with great application potential in industries. However, industrial strain engineering has long been limited by the inefficient and labor-consuming plate/flask-based screening process, resulting in an urgent need for product-driven high-throughput screening methods for actinomycetes. Here, we combine a whole-cell biosensor and microfluidic platform to establish the whole-cell biosensor and producer co-cultivation-based microfluidic platform for screening actinomycetes (WELCOME). In WELCOME, we develop an MphR-based Escherichia coli whole-cell biosensor sensitive to erythromycin and co-cultivate it with Saccharopolyspora erythraea in droplets for high-throughput screening. Using WELCOME, we successfully screen out six erythromycin hyper-producing S. erythraea strains starting from an already high-producing industrial strain within 3 months, and the best one represents a 50% improved yield. WELCOME completely circumvents a major problem of industrial actinomycetes, which is usually genetic-intractable, and this method will revolutionize the field of industrial actinomycete engineering.

Refactoring transcription factors for metabolic engineering

Due to the ability to regulate target metabolic pathways globally and dynamically, metabolic regulation systems composed of transcription factors have been widely used in metabolic engineering and synthetic biology. This review introduced the categories, action principles, prediction strategies, and related databases of transcription factors. Then, the application of global transcription machinery engineering technology and the transcription factor-based biosensors and quorum sensing systems are overviewed. In addition, strategies for optimizing the transcriptional regulatory tools' performance by refactoring transcription factors are summarized. Finally, the current limitations and prospects of constructing various regulatory tools based on transcription factors are discussed. This review will provide theoretical guidance for the rational design and construction of transcription factor-based metabolic regulation systems.

Application of an Escherichia coli triple reporter strain for at-line monitoring of single-cell physiology during L-phenylalanine production

Biotechnological production processes are sustainable approaches for the production of biobased components such as amino acids for food and feed industry. Scale-up from ideal lab-scale bioreactors to large-scale processes is often accompanied by loss in productivity. This may be related to population heterogeneities of cells originating from isogenic cultures that arise due to dynamic non-ideal conditions in the bioreactor. To better understand this phenomenon, deeper insights into single-cell physiologies in bioprocesses are mandatory before scale-up. Here, a triple reporter strain (3RP) was developed by chromosomally integrating the fluorescent proteins mEmerald, CyOFP1, and mTagBFP2 into the L-phenylalanine producing Escherichia coli strain FUS4 (pF81_kan) to allow monitoring of growth, oxygen availability, and general stress response of the single cells. Functionality of the 3RP was confirmed in well-mixed lab-scale fed-batch processes with glycerol as carbon source in comparison to the strain without fluorescent proteins, leading to no difference in process performance. Fluorescence levels could successfully reflect the course of related process state variables, revealed population heterogeneities during the transition between different process phases and potentially subpopulations that exhibit superior process performance. Furthermore, indications were found for noise in gene expression as regulation strategy against environmental perturbation.

Improvement of 3-hydroxypropionic acid tolerance in Klebsiella pneumoniae by novel transporter YohJK

3-Hydroxypropionic acid (3-HP) is a platform chemical which has potential applications in cosmetic and polymer industries. Microbial production of 3-HP is hampered by its toxic effect when its concentration is high (>300 mM). In this study, the effect of yohJK overexpression (via yieP deletion or episomal overexpression) on 3-HP tolerance was investigated in Klebsiella pneumoniae, Pseudomonas denitrificans and P. asiatica. The deletion of yieP homolog could improve 3-HP tolerance in K. pneumoniae. Transcriptional analysis suggested that, among the two yohJK homologs of K. pneumoniae, expression of yohJK1, not yohJK2, was under the negative control of YieP. Furthermore, deletion of yieP significantly reduced cytoplasmic 3-HP concentration when determined by 3-HP biosensor and enhanced 3-HP tolerance and 3-HP production. This study demonstrates that the YohJK1 functions as 3-HP transporter in K. pneumoniae and their overexpression by the yieP deletion is a good strategy to enhance 3-HP tolerance and its production.

Effective use of biosensors for high-throughput library screening for metabolite production

The development of fast and affordable microbial production from recombinant pathways is a challenging endeavor, with targeted improvements difficult to predict due to the complex nature of living systems. To address the limitations in biosynthetic pathways, much work has been done to generate large libraries of various genetic parts (promoters, RBSs, enzymes, etc.) to discover library members that bring about significantly improved levels of metabolite production. To evaluate these large libraries, high throughput approaches are necessary, such as those that rely on biosensors. There are various modes of operation to apply biosensors to library screens that are available at different scales of throughput. The effectiveness of each biosensor-based method is dependent on the pathway or strain to which it is applied, and all approaches have strengths and weaknesses to be carefully considered for any high throughput library screen. In this review, we discuss the various approaches used in biosensor screening for improved metabolite production, focusing on transcription factor-based biosensors.

How to Perform a Microfluidic Cultivation Experiment—A Guideline to Success

As a result of the steadily ongoing development of microfluidic cultivation (MC) devices, a plethora of setups is used in biological laboratories for the cultivation and analysis of different organisms. Because of their biocompatibility and ease of fabrication, polydimethylsiloxane (PDMS)-glass-based devices are most prominent. Especially the successful and reproducible cultivation of cells in microfluidic systems, ranging from bacteria over algae and fungi to mammalians, is a fundamental step for further quantitative biological analysis. In combination with live-cell imaging, MC devices allow the cultivation of small cell clusters (or even single cells) under defined environmental conditions and with high spatio-temporal resolution. Yet, most setups in use are custom made and only few standardised setups are available, making trouble-free application and inter-laboratory transfer tricky. Therefore, we provide a guideline to overcome the most frequently occurring challenges during a MC experiment to allow untrained users to learn the application of continuous-flow-based MC devices. By giving a concise overview of the respective workflow, we give the reader a general understanding of the whole procedure and its most common pitfalls. Additionally, we complement the listing of challenges with solutions to overcome these hurdles. On selected case studies, covering successful and reproducible growth of cells in MC devices, we demonstrate detailed solutions to solve occurring challenges as a blueprint for further troubleshooting. Since developer and end-user of MC devices are often different persons, we believe that our guideline will help to enhance a broader applicability of MC in the field of life science and eventually promote the ongoing advancement of MC.

Biosensor-based isolation of amino acid-producing Vibrio natriegens strains

The marine bacterium Vibrio natriegens has recently been demonstrated to be a promising new host for molecular biology and next generation bioprocesses. V. natriegens is a Gram-negative, non-pathogenic slight-halophilic bacterium, with a high nutrient versatility and a reported doubling time of under 10 min. However, V. natriegens is not an established model organism yet, and further research is required to promote its transformation into a microbial workhorse.

In this work, the potential of V. natriegens as an amino acid producer was investigated. First, the transcription factor-based biosensor LysG, from Corynebacterium glutamicum, was adapted for expression in V. natriegens to facilitate the detection of positively charged amino acids. A set of different biosensor variants were constructed and characterized, using the expression of a fluorescent protein as sensor output. After random mutagenesis, one of the LysG-based sensors was used to screen for amino acid producer strains. Here, fluorescence-activated cell sorting enabled the selective sorting of highly fluorescent cells, i.e. potential producer cells. Using this approach, individual L-lysine, L-arginine and L-histidine producers could be obtained producing up to 1 mM of the effector amino acid, extracellularly. Genome sequencing of the producer strains provided insight into the amino acid production metabolism of V. natriegens.

This work demonstrates the successful expression and application of transcription factor-based biosensors in V. natriegens and provides insight into the underlying physiology, forming a solid basis for further development of this promising microbe.

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Vibrio natriegens is a promising new host for biotechnology.

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Transcription factor-based biosensors were expressed in V. natriegens.

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Mutagenesis and screening using FACS provided amino acid producing mutants.

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Genome sequencing revealed several causal mutations leading to amino acid production.

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These results will support further efforts to develop V. natriegens as a production host.

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

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

Microscopy imaging of living cells in metabolic engineering

Microscopy imaging of living cells is becoming a pivotal, noninvasive, and highly specific tool in metabolic engineering to visualize molecular dynamics in industrial microorganisms. This review describes the different microscopy methods, from fluorescence to super resolution, with application in microbial bioengineering. Firstly, the role and importance of microscopy imaging is analyzed in the context of strain design. Then, the advantages and disadvantages of different microscopy technologies are discussed, including confocal laser scanning microscopy (CLSM), spatial light interference microscopy (SLIM), and super-resolution microscopy, followed by their applications in synthetic biology. Finally, the future perspectives of live-cell imaging and their potential to transform microbial systems are analyzed. This review provides theoretical guidance and highlights the importance of microscopy in understanding and engineering microbial metabolism.

Directed evolution of biofuel-responsive biosensors for automated optimization of branched-chain alcohol biosynthesis

The biosynthesis of short-chain alcohols is a carbon-neutral alternative to petroleum-derived production, but strain screening operations are encumbered by laborious analytics. Here, we built, characterized and applied whole cell biosensors by directed evolution of the transcription factor AlkS for screening microbial strain libraries producing industrially relevant alcohols. A selected AlkS variant was applied for in situ product detection in two screening applications concerning key steps in alcohol production. Further, the biosensor strains enabled the implementation of an automated, robotic platform-based workflow with data clustering, which readily allowed the identification of significantly improved strain variants for isopentanol production.

Improvement of a synthetic live bacterial therapeutic for phenylketonuria with biosensor-enabled enzyme engineering

In phenylketonuria (PKU) patients, a genetic defect in the enzyme phenylalanine hydroxylase (PAH) leads to elevated systemic phenylalanine (Phe), which can result in severe neurological impairment. As a treatment for PKU, Escherichia coli Nissle (EcN) strain SYNB1618 was developed under Synlogic's Synthetic Biotic™ platform to degrade Phe from within the gastrointestinal (GI) tract. This clinical-stage engineered strain expresses the Phe-metabolizing enzyme phenylalanine ammonia lyase (PAL), catalyzing the deamination of Phe to the non-toxic product trans-cinnamate (TCA). In the present work, we generate a more potent EcN-based PKU strain through optimization of whole cell PAL activity, using biosensor-based high-throughput screening of mutant PAL libraries. A lead enzyme candidate from this screen is used in the construction of SYNB1934, a chromosomally integrated strain containing the additional Phe-metabolizing and biosafety features found in SYNB1618. Head-to-head, SYNB1934 demonstrates an approximate two-fold increase in in vivo PAL activity compared to SYNB1618.

Biosensor-based growth-coupling and spatial separation as an evolution strategy to improve small molecule production of Corynebacterium glutamicum

Evolutionary engineering is a powerful method to improve the performance of microbial cell factories, but can typically not be applied to enhance the production of chemicals due to the lack of an appropriate selection regime. We report here on a new strategy based on transcription factor-based biosensors, which directly couple production to growth. The growth of Corynebacterium glutamicum was coupled to the intracellular concentration of branched-chain amino acids, by integrating a synthetic circuit based on the Lrp biosensor upstream of two growth-regulating genes, pfkA and hisD. Modelling and experimental data highlight spatial separation as key strategy to limit the selection of 'cheater' strains that escaped the evolutionary pressure. This approach facilitated the isolation of strains featuring specific causal mutations enhancing amino acid production. We envision that this strategy can be applied with the plethora of known biosensors in various microbes, unlocking evolution as a feasible strategy to improve production of chemicals.

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.

Exploring the Tunability and Dynamic Properties of MarR-PmarO Sensor System in Escherichia coli

Transcriptional factor-based biosensors (TFBs) have been widely used in dynamic pathway control or high-throughput screening. Here, we systematically explored the tunability of a salicylic acid responsive regulator MarR from Escherichia coli aiming to explore its engineering potential. The effect of endogenous MarR in E. coli on the MarR-PmarO biosensor system was investigated. Furthermore, to investigate the function of marO binding boxes in this biosensor system, a series of hybrid promoters were constructed by placing the marO binding boxes in the strong constitutive pL promoter. The engineered hybrid promoters became responsive to MarR and salicylic acid. To further study the influence of each nucleotide in the marO box on MarR binding, we employed dynamic modeling to simulate the interaction and binding energy between each nucleotide in the marO boxes with the corresponding residues on MarR. Guided by the results of the simulation, we introduced mutations to key positions on the hybrid promoters and investigated corresponding dynamic performance. Two promoter variants I12AII4T and I12AII14T that exhibited improved responsive strengths and shifted dynamic ranges were obtained, which can be beneficial for future metabolic engineering research.

SorTn-seq: a high-throughput functional genomics approach to discovering regulators of bacterial gene expression

We recently developed a high-throughput functional genomics approach, named 'SorTn-seq', to identify factors affecting expression of any gene of interest in bacteria. Our approach facilitates high-throughput screening of complex mutant pools, a task previously hindered by a lack of suitable techniques. SorTn-seq combines high-density, Tn5-like transposon mutagenesis with fluorescence-activated cell sorting of a strain harboring a promoter-fluorescent reporter fusion, to isolate mutants with altered gene expression. The transposon mutant pool is sorted into different bins on the basis of fluorescence, and mutants are deep-sequenced to identify transposon insertions. DNA is prepared for sequencing by using commercial kits augmented with custom primers, enhancing ease of use and reproducibility. Putative regulators are identified by comparing the number of insertions per genomic feature in the different sort bins, by using existing bioinformatic pipelines and software packages. SorTn-seq can be completed in 1-2 weeks and requires general microbiology skills and basic flow cytometry experience.

Unraveling the roles of plant specialized metabolites: using synthetic biology to design molecular biosensors

Plants are a rich source of specialized metabolites with a broad range of bioactivities and many applications in human daily life. Over the past decades significant progress has been made in identifying many such metabolites in different plant species and in elucidating their biosynthetic pathways. However, the biological roles of plant specialized metabolites remain elusive and proposed functions lack an identified underlying molecular mechanism. Understanding the roles of specialized metabolites frequently is hampered by their dynamic production and their specific spatiotemporal accumulation within plant tissues and organs throughout a plant's life cycle. In this review, we propose the employment of strategies from the field of Synthetic Biology to construct and optimize genetically encoded biosensors that can detect individual specialized metabolites in a standardized and high-throughput manner. This will help determine the precise localization of specialized metabolites at the tissue and single-cell levels. Such information will be useful in developing complete system-level models of specialized plant metabolism, which ultimately will demonstrate how the biosynthesis of specialized metabolites is integrated with the core processes of plant growth and development.

Advances in metabolic engineering of Corynebacterium glutamicum to produce high-value active ingredients for food, feed, human health, and well-being

The soil microbe Corynebacterium glutamicum is a leading workhorse in industrial biotechnology and has become famous for its power to synthetise amino acids and a range of bulk chemicals at high titre and yield. The product portfolio of the microbe is continuously expanding. Moreover, metabolically engineered strains of C. glutamicum produce more than 30 high value active ingredients, including signature molecules of raspberry, savoury, and orange flavours, sun blockers, anti-ageing sugars, and polymers for regenerative medicine. Herein, we highlight recent advances in engineering of the microbe into novel cell factories that overproduce these precious molecules from pioneering proofs-of-concept up to industrial productivity.

Development of a Hyperosmotic Stress Inducible Gene Expression System by Engineering the MtrA/MtrB-Dependent NCgl1418 Promoter in Corynebacterium glutamicum

Corynebacterium glutamicum is an important workhorse for industrial production of diversiform bioproducts. Precise regulation of gene expression is crucial for metabolic balance and enhancing production of target molecules. Auto-inducible promoters, which can be activated without expensive inducers, are ideal regulatory tools for industrial-scale application. However, few auto-inducible promoters have been identified and applied in C. glutamicum. Here, a hyperosmotic stress inducible gene expression system was developed and used for metabolic engineering of C. glutamicum. The promoter of NCgl1418 (P _NCgl1418 ) that was activated by the two-component signal transduction system MtrA/MtrB was found to exhibit a high inducibility under hyperosmotic stress conditions. A synthetic promoter library was then constructed by randomizing the flanking and space regions of P _NCgl1418 , and mutant promoters exhibiting high strength were isolated via fluorescence activated cell sorting (FACS)-based high-throughput screening. The hyperosmotic stress inducible gene expression system was applied to regulate the expression of lysE encoding a lysine exporter and repress four genes involved in lysine biosynthesis (gltA, pck, pgi, and hom) by CRISPR interference, which increased the lysine titer by 64.7% (from 17.0 to 28.0 g/L) in bioreactors. The hyperosmotic stress inducible gene expression system developed here is a simple and effective tool for gene auto-regulation in C. glutamicum and holds promise for metabolic engineering of C. glutamicum to produce valuable chemicals and fuels.

Engineering of a Biosensor in Response to Malate in Bacillus licheniformis

Malate is an essential intermediate in the tricarboxylic acid (TCA) cycle; it also has valuable uses in medicine and food. The production of malate with a microbial synthesis method is still in its early stages. One of the key problems in metabolic engineering is that the dynamic and subtle changes in malate are difficult to detect. It remains critical to develop techniques with direct and precise detection of malate in microbial metabolism, which facilitates high-throughput screening of the engineered strains. In this study, a genetically encoded biosensor in response to malate was constructed in B. licheniformis. Key regulator MalR and the action site of the biosensor were first identified. Then, the output of the reporter gene expression was amplified by introducing a strong constitutive promoter and iteratively tuning the action sites. The engineered biosensor can respond to malate from 5 to 15 g/L; within this range, it shows a linear correlation between eGFP fluorescence and malate concentration. This biosensor enrich our toolbox of synthetic biology in pathway engineering for malate production in microorganisms.

(Optochemical) Control of Synthetic Microbial Coculture Interactions on a Microcolony Level

Synthetic microbial cocultures carry enormous potential for applied biotechnology and are increasingly the subject of fundamental research. So far, most cocultures have been designed and characterized based on bulk cultivations without considering the potentially highly heterogeneous and diverse single-cell behavior. However, an in-depth understanding of cocultures including their interacting single cells is indispensable for the development of novel cultivation approaches and control of cocultures. We present the development, validation, and experimental characterization of an optochemically controllable bacterial coculture on a microcolony level consisting of two Corynebacterium glutamicum strains. Our coculture combines an l-lysine auxotrophic strain together with a l-lysine-producing variant carrying the genetically IPTG-mediated induction of l-lysine production. We implemented two control approaches utilizing IPTG as inducer molecule. First, unmodified IPTG was supplemented to the culture enabling a medium-based control of the production of l-lysine, which serves as the main interacting component. Second, optochemical control was successfully performed by utilizing photocaged IPTG activated by appropriate illumination. Both control strategies were validated studying cellular growth on a microcolony level. The novel microfluidic single-cell cultivation strategies applied in this work can serve as a blueprint to validate cellular control strategies of synthetic mono- and cocultures with single-cell resolution at defined environmental conditions.

Dynamic Control of Metabolism

Metabolic engineering reprograms cells to synthesize value-added products. In doing so, endogenous genes are altered and heterologous genes can be introduced to achieve the necessary enzymatic reactions. Dynamic regulation of metabolic flux is a powerful control scheme to alleviate and overcome the competing cellular objectives that arise from the introduction of these production pathways. This review explores dynamic regulation strategies that have demonstrated significant production benefits by targeting the metabolic node corresponding to a specific challenge. We summarize the stimulus-responsive control circuits employed in these strategies that determine the criterion for actuating a dynamic response and then examine the points of control that couple the stimulus-responsive circuit to a shift in metabolic flux.

Programming adaptive laboratory evolution of 4-hydroxyisoleucine production driven by a lysine biosensor in Corynebacterium glutamicum

4-Hydroxyisoleucine (4-HIL) is a promising drug for treating diabetes. In our previous study, 4-HIL was synthesized from self-produced L-isoleucine (Ile) in Corynebacterium glutamicum by expressing an Ile dioxygenase gene. Although the 4-HIL production of recombinant strain SZ06 increased significantly, a by-product, L-lysine (Lys) was accumulated because of the share of the first several enzymes in Ile and Lys biosynthetic pathways. In this study, programming adaptive laboratory evolution (ALE) was designed and conducted in SZ06 to promote 4-HIL biosynthesis. At first, a programming evolutionary system pMK was constructed, which contains a Lys biosensor LysG-P_lysE and an evolutionary actuator composed of a mutagenesis gene and a fluorescent protein gene. The evolutionary strain SZ06/pMK was then let to be evolved programmatically and spontaneously by sensing Lys concentration. After successive rounds of evolution, nine mutant strains K1 - K9 with significantly increased 4-HIL production and growth performance were obtained. The maximum 4-HIL titer was 152.19 ± 14.60 mM, 28.4% higher than that in SZ06. This titer was higher than those of all the metabolic engineered C. glutamicum strains ever constructed. The whole genome sequencing of the nine evolved strains revealed approximately 30 genetic mutations in each strain. Only one mutation was directly related to the Lys biosynthetic pathway. Therefore, programming ALE driven by Lys biosensor can be used as an effective strategy to increase 4-HIL production in C. glutamicum.

Isoleucyl-tRNA synthetase mutant based whole-cell biosensor for high-throughput selection of isoleucine overproducers

Whole-cell amino acid biosensors can sense the concentrations of certain amino acids and output easily detectable signals, which are important for construction of microbial producers. However, many reported biosensors have poor specificity because they also sense non-target amino acids. Besides, biosensors for many amino acids are still unavailable. In this study, we proposed a new strategy for constructing whole-cell biosensors based on aminoacyl-tRNA synthetases (aaRSs), which take the advantage of their universality and intrinsically specific binding ability to corresponding amino acids. Taking isoleucine biosensor as an example, we first mutated the isoleucyl-tRNA synthetase in Escherichia coli to dramatically decrease its affinity to isoleucine. The engineered cells specifically sensed isoleucine and output isoleucine dose-dependent cell growth as an easily detectable signal. To further expand the sensing range, an isoleucine exporter was overexpressed to enhance excretion of intracellular isoleucine. Since cells equipped with the optimized whole-cell biosensor showed accelerated growth when cells produced higher concentrations of isoleucine, the biosensor was successfully applied in high-throughput selection of isoleucine overproducers from random mutation libraries. This work demonstrates the feasibility of engineering aaRSs to construct a new kind of whole-cell biosensors for amino acids. Considering all twenty proteinogenic and many non-canonical amino acids have their specific aaRSs, this strategy should be useful for developing biosensors for various amino acids.

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.

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

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

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Biosensor response in a heterologous host can be restored.

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

Systems evaluation reveals novel transporter YohJK renders 3-hydroxypropionate tolerance in Escherichia coli

Previously, we have reported that 3-hydroxypropionate (3-HP) tolerance in Escherichia coli W is improved by deletion of yieP, a less-studied transcription factor. Here, through systems analyses along with physiological and functional studies, we suggest that the yieP deletion improves 3-HP tolerance by upregulation of yohJK, encoding putative 3-HP transporter(s). The tolerance improvement by yieP deletion was highly specific to 3-HP, among various C2-C4 organic acids. Mapping of YieP binding sites (ChIP-exo) coupled with transcriptomic profiling (RNA-seq) advocated seven potential genes/operons for further functional analysis. Among them, the yohJK operon, encoding for novel transmembrane proteins, was the most responsible for the improved 3-HP tolerance; deletion of yohJK reduced 3-HP tolerance regardless of yieP deletion, and their subsequent complementation fully restored the tolerance in both the wild-type and yieP deletion mutant. When determined by 3-HP-responsive biosensor, a drastic reduction of intracellular 3-HP was observed upon yieP deletion or yohJK overexpression, suggesting that yohJK encodes for novel 3-HP exporter(s).

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

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