High-throughput metabolic engineering: advances in small-molecule screening and selection

Unlocking the potential of Shewanella in metabolic engineering: Current status, challenges, and opportunities

Shewanella species are facultative anaerobes with distinctive electrochemical properties, making them valuable for applications in energy conversion and environmental bioremediation. Due to their well-characterized electron transfer mechanisms and ease of genetic manipulation, Shewanella spp. have emerged as a promising chassis for metabolic engineering. In this review, we provide a comprehensive overview of the advancements in Shewanella-based metabolic engineering. We begin by discussing the physiological characteristics of Shewanella, with a particular focus on its extracellular electron transfer (EET) capability. Next, we outline the use of Shewanella as a metabolic engineering chassis, presenting a general framework for strain construction based on the Design-Build-Test-Learn (DBTL) cycle and summarizing key advancements in the engineering of Shewanella's metabolic modules. Finally, we offer a perspective on the future development of Shewanella chassis, highlighting the need for deeper mechanistic insights, rational strain design, and interdisciplinary collaboration to drive further progress.

Antibiofilm activity of exopolysaccharide-mediated ZnO nanoparticle against Pseudomonas aeruginosa biofilm

Exopolysaccharides (EPSs) are the group of biological macromolecules those play a potent role in protecting the bacteria from any sorts of stress. They exhibit multifunctional roles in natural and bioactive product science hence exhibits various types of medical and biochemical applications. EPS ensures the storage of nutrients, produce antigens to create defense mechanism during infection, and is also responsible for the formation of biofilm and cell adhesion. Green synthesis of ZnO nanoparticle mediated by EPS from Lactobacillus sp. which is a type of lactic acid bacteria (LAB) is a novel approach for its application in the food industry as it exhibits antimicrobial and antibiofilm potential. In this study, Lactobacillus sp. was cultivated in Lactobacillus broth media (LBM) and glucose mineral salt media (GMSM) to identify the best suitable media that would provide maximum amount of EPS, and it was observed that the two media exhibited maximum yield of 0.8 g/L and 0.6 g/L respectively after 48-h incubation. SEM, EDS, and XRD were used for characterizing the green synthesized ZnONPs from the EPS and was observed that the NPs were synthesized. 62.6% and 67.6% ZnONPs were observed in LBM-ZnONP and GMSM-ZnONP respectively from XRD analysis. UV spectroscopic detection showed corresponding peak of the nanoparticle formed at 349 nm which confirmed the production of ZnO NPs. Scanning electron microscopic (SEM) images and Fourier transform infrared spectroscopy (FT-IR) established the average size, shape, and composition of the nanoparticles. The peaks of the FT-IR also revealed the presence of the C = H and N-H stretching (1 H). It was also observed that the average size of LBM ZnONPs were 60.578 nm whereas GMSM ZnONPs were 53.09 nm. Viability studies exhibited that the NPs brought considerable reduction of the sessile cells of P. aeuginosa. It was further observed that the cells treated with NPs did not show revival. The NPs were able to inhibit the quorum sensing (QS) mechanism of Pseudomonas aeruginosa thereby preventing the development of virulence. Out of the two NPs, it was observed that GMSM ZnONPs showed better efficacy in comparison to LBM ZnONPs. Thus, the study concludes that EPS-mediated NPs can be used effectively in the process of treating the biofilm.

Engineering a cpGFP-based biosensor for enhanced quantification of glycolate production in Escherichia coli

The growing demand for glycolate, fueled by economic development, requires the advancement of production methods. Escherichia coli (E. coli), a preferred host for glycolate production, has undergone extensive metabolic engineering to improve yield. Developing rapid and precise methods for quantifying glycolate concentration is essential for screening high-yielding strains. Here, we present the engineering of a novel circularly permuted green fluorescent protein (cpGFP)-based glycolate sensor, termed GLYCO. GLYCO exhibits high specificity (minimal interference from other metabolites), stability (no decrease in performance after 15 days at -80 °C), and ease of detection via fluorescence measurement, enabling effective in vitro glycolate quantification. GLYCO spans a quantification range from 10 μM to 1 mM, facilitating effective monitoring of glycolate production in metabolically engineered E. coli strains. This biosensor represents a significant advancement in the metabolic engineering toolkit, facilitating efficient detection and optimization of glycolate production in E. coli, with potential applications in industrial biotechnology.

Hyperspectral reporters for long-distance and wide-area detection of gene expression in living bacteria

Genetically encoded reporters are suitable for short-distance imaging in the laboratory but not for scanning wide outdoor areas from a distance. Here we introduce hyperspectral reporters (HSRs) designed for hyperspectral imaging cameras that are commonly mounted on unmanned aerial vehicles and satellites. HSR genes encode enzymes that produce a molecule with a unique absorption signature that can be reliably distinguished in hyperspectral images. Quantum mechanical simulations of 20,170 metabolites identified candidate HSRs, leading to the selection of biliverdin IXα and bacteriochlorophyll a for their distinct absorption spectra and biosynthetic feasibility. These genes were integrated into chemical sensor circuits in soil (Pseudomonas putida) and aquatic (Rubrivivax gelatinosus) bacteria. The bacteria were detectable outdoors under ambient light from up to 90 m in a single 4,000-m2 hyperspectral image taken using fixed and unmanned aerial vehicle-mounted cameras. The dose-response functions of the chemical sensors were measured remotely. HSRs enable large-scale studies and applications in ecology, agriculture, environmental monitoring, forensics and defense.

Computation-guided transcription factor biosensor specificity engineering for adipic acid detection

Transcription factor (TF)-based biosensors that connect small-molecule sensing with readouts such as fluorescence have proven to be useful synthetic biology tools for applications in biotechnology. However, the development of specific TF-based biosensors is hindered by the limited repertoire of TFs specific for molecules of interest since current construction methods rely on a limited set of characterized TFs. In this study, we present an approach for engineering the specificity of TFs through a computation-based workflow using molecular docking that enables targeted alteration of TF ligand specificity. Using this method, we engineer the LysR family BenM TF to alter its specificity from its cognate ligand cis,cis-muconic acid to adipic acid through a single amino acid substitution identified by our computational workflow. When implemented in a cell-free system, the engineered biosensor shows higher ligand sensitivity, expanding the potential applications of this circuit. We further investigate ligand binding through molecular dynamics to analyze the substitution, elucidating the impact of modulating a single amino acid position on the mechanism of BenM ligand binding. This study represents the first application of biomolecular modeling methods for altering BenM specificity and for gaining insights into how mutations influence the structural dynamics of BenM. Such methods can potentially be applied to other TFs to alter specificity and analyze the dynamics responsible for these changes, highlighting the applicability of computational tools for informing experiments. In addition, our developed adipic acid biosensor can be applied for the identification and engineering of enzymes to produce adipic acid.

Highly multiplexed design of an allosteric transcription factor to sense new ligands

Allosteric transcription factors (aTF) regulate gene expression through conformational changes induced by small molecule binding. Although widely used as biosensors, aTFs have proven challenging to design for detecting new molecules because mutation of ligand-binding residues often disrupts allostery. Here, we develop Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screen a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures - four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone - as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identifies biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design shows shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we develop cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid and scalable design of new biosensors, overcoming constraints of natural biosensors.

Fundamentals and Exceptions of the LysR-type Transcriptional Regulators

LysR-type transcriptional regulators (LTTRs) are emerging as a promising group of macromolecules for the field of biosensors. As the largest family of bacterial transcription factors, the LTTRs represent a vast and mostly untapped repertoire of sensor proteins. To fully harness these regulators for transcription factor-based biosensor development, it is crucial to understand their underlying mechanisms and functionalities. In the first part, this Review discusses the established model and features of LTTRs. As dual-function regulators, these inducible transcription factors exude precise control over their regulatory targets. In the second part of this Review, an overview is given of the exceptions to the "classic" LTTR model. While a general regulatory mechanism has helped elucidate the intricate regulation performed by LTTRs, it is essential to recognize the variations within the family. By combining this knowledge, characterization of new regulators can be done more efficiently and accurately, accelerating the expansion of transcriptional sensors for biosensor development. Unlocking the pool of LTTRs would significantly expand the currently limited range of detectable molecules and regulatory functions available for the implementation of novel synthetic genetic circuitry.

A versatile microbial platform as a tunable whole-cell chemical sensor

Biosensors are used to detect and quantify chemicals produced in industrial microbiology with high specificity, sensitivity, and portability. Most biosensors, however, are limited by the need for transcription factors engineered to recognize specific molecules. In this study, we overcome the limitations typically associated with traditional biosensors by engineering Pseudomonas putida for whole-cell sensing of a variety of chemicals. Our approach integrates fluorescent reporters with synthetic auxotrophies within central metabolism that can be complemented by target analytes in growth-coupled setups. This platform enables the detection of a wide array of structurally diverse chemicals under various conditions, including co-cultures of producer cell factories and sensor strains. We also demonstrate the applicability of this versatile biosensor platform for monitoring complex biochemical processes, including plastic degradation by either purified hydrolytic enzymes or engineered bacteria. This microbial system provides a rapid, sensitive, and readily adaptable tool for monitoring cell factory performance and for environmental analyzes.

Design, construction and optimization of formaldehyde growth biosensors with broad application in biotechnology

Formaldehyde is a key metabolite in natural and synthetic one-carbon metabolism. To facilitate the engineering of formaldehyde-producing enzymes, the development of sensitive, user-friendly, and cost-effective detection methods is required. In this study, we engineered Escherichia coli to serve as a cellular biosensor capable of detecting a broad range of formaldehyde concentrations. Using both natural and promiscuous formaldehyde assimilation enzymes, we designed three distinct E. coli growth biosensor strains that depend on formaldehyde for cell growth. These strains were engineered to be auxotrophic for one or several essential metabolites that could be produced through formaldehyde assimilation. The respective assimilating enzyme was expressed from the genome to compensate the auxotrophy in the presence of formaldehyde. We first predicted the formaldehyde dependency of the biosensors by flux balance analysis and then analysed it experimentally. Subsequent to strain engineering, we enhanced the formaldehyde sensitivity of two biosensors either through adaptive laboratory evolution or modifications at metabolic branch points. The final set of biosensors demonstrated the ability to detect formaldehyde concentrations ranging approximately from 30 μM to 13 mM. We demonstrated the application of the biosensors by assaying the in vivo activity of different methanol dehydrogenases in the most sensitive strain. The fully genomic nature of the biosensors allows them to be deployed as "plug-and-play" devices for high-throughput screenings of extensive enzyme libraries. The formaldehyde growth biosensors developed in this study hold significant promise for advancing the field of enzyme engineering, thereby supporting the establishment of a sustainable one-carbon bioeconomy.

Highly multiplexed design of an allosteric transcription factor to sense novel ligands

Allosteric transcription factors (aTF), widely used as biosensors, have proven challenging to design for detecting novel molecules because mutation of ligand-binding residues often disrupts allostery. We developed Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screened a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures - four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone - as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identified novel biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design showed shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we developed cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid, scalable design of new biosensors, overcoming constraints of natural biosensors.

Microbial production of branched chain amino acids: Advances and perspectives

Branched-chain amino acids (BCAAs) such as L-valine, L-leucine, and L-isoleucine are widely used in food and feed. To comply with sustainable development goals, commercial production of BCAAs has been completely replaced with microbial fermentation. However, the efficient production of BCAAs by microorganisms remains a serious challenge due to their staggered metabolic networks and cell growth. To overcome these difficulties, systemic metabolic engineering has emerged as an effective and feasible strategy for the biosynthesis of BCAA. This review firstly summarizes the research advances in the microbial synthesis of BCAAs and representative engineering strategies. Second, systematic methods, such as high-throughput screening, adaptive laboratory evolution, and omics analysis, can be used to analyses the synthesis of BCAAs at the whole-cell level and further improve the titer of target chemicals. Finally, new tools and engineering strategies that may increase the production output and development direction of the microbial production of BCAAs are discussed.

Random mutagenesis as a tool for industrial strain improvement for enhanced production of antibiotics: a review

Secondary metabolites are produced by microbes in minimal quantities in the natural environment out of necessity. However, in the pharmaceutical industry, their overproduction becomes essential. To achieve higher yields, genetic modifications are employed to create strains that surpass the productivity of the initially isolated strains. While rational screening and genetic engineering have emerged as valuable practices in recent years, the cost-effective technique of mutagenesis and selection, known as "random screening," remains a preferred method for efficient short-term strain development. This review aims to comprehensively explore all aspects of strain improvement, focusing on why random mutagenesis continues to be widely adopted.

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.

Workflow for High-throughput Screening of Enzyme Mutant Libraries Using Matrix-assisted Laser Desorption/Ionization Mass Spectrometry Analysis of Escherichia coli Colonies

High-throughput molecular screening of microbial colonies and DNA libraries are critical procedures that enable applications such as directed evolution, functional genomics, microbial identification, and creation of engineered microbial strains to produce high-value molecules. A promising chemical screening approach is the measurement of products directly from microbial colonies via optically guided matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Measuring the compounds from microbial colonies bypasses liquid culture with a screen that takes approximately 5 s per sample. We describe a protocol combining a dedicated informatics pipeline and sample preparation method that can prepare up to 3,000 colonies in under 3 h. The screening protocol starts from colonies grown on Petri dishes and then transferred onto MALDI plates via imprinting. The target plate with the colonies is imaged by a flatbed scanner and the colonies are located via custom software. The target plate is coated with MALDI matrix, MALDI-MS analyzes the colony locations, and data analysis enables the determination of colonies with the desired biochemical properties. This workflow screens thousands of colonies per day without requiring additional automation. The wide chemical coverage and the high sensitivity of MALDI-MS enable diverse screening projects such as modifying enzymes and functional genomics surveys of gene activation/inhibition libraries. Key features • Mass spectrometry analyzes a range of compounds from E. coli colonies as a proxy for liquid culture testing enzyme mutant libraries. • Colonies are transferred to a MALDI target plate by a simple imprinting method. • The screen compares the ratio among several products or searches for the qualitative presence of specific compounds. • The protocol requires a MALDI mass spectrometer.

Design, combinatorial synthesis and cytotoxic activity of 2-substituted furo[2,3-d]pyrimidinone and pyrrolo[2,3-d]pyrimidinone library

A facile protocol was developed for the combinatorial synthesis of furo[2,3-d]pyrimidinone and pyrrolo[2,3-d]pyrimidinone library via a one-pot condensation, from 2-amino furans/pyrroles. Herein reported process required a similar reaction condition, providing mild access to two diverse series of natural product-like heterocycles. Both furo[2,3-d]pyrimidinones and pyrrolo[2,3-d]pyrimidinones were evaluated in vitro against a panel of human cancer cell lines including against human cancer HeLa (cervical), MCF-7 (breast) and HT-29 (colon) cell lines. Derivative 12n ((2-(4-chlorophenyl)-1-methyl-6,7,8,9-tetrahydropyrido[1,2-a]pyrrolo[2,3-d]pyrimidin-4(1H)-one)) showed high activity (IC50 = 6.55 ± 0.31 µM) against the HeLa cell line. These products could be subjected to a various modification and therefore represent important skeletons for the anticancer drug discovery.

Dispersive phase microscopy incorporated with droplet-based microfluidics for biofactory-on-a-chip

Biomolecular imaging of intracellular structures of a single cell and subsequent screening of the cells are of high demand in metabolic engineering to develop strains with the desired phenotype. However, the capability of current methods is limited to population-scale identification of cell phenotyping. To address this challenge, we propose to utilize dispersive phase microscopy incorporated with a droplet-based microfluidic system that combines droplet volume-on-demand generation, biomolecular imaging, and droplet-on-demand sorting, to achieve high-throughput screening of cells with an identified phenotype. Particularly, cells are encapsulated in homogeneous environments with microfluidic droplet formation, and the biomolecule-induced dispersive phase can be investigated to indicate the biomass of a specific metabolite in a single cell. The retrieved biomass information consequently guides the on-chip droplet sorting unit to screen cells with the desired phenotype. To demonstrate the proof of concept, we showcase the method by promoting the evolution of the Haematococcus lacustris strain toward a high production of natural antioxidant astaxanthin. The validation of the proposed system with on-chip single-cell imaging and droplet manipulation functionalities reveals the high-throughput single-cell phenotyping and selection potential that applies to many other biofactory scenarios, such as biofuel production, critical quality attribute control in cell therapy, etc.

Glucometer-based biosensor for the determination of ractopamine in animal-derived foods using rolling circle amplification

Screening for persistent organic pollutants (POPs) in food is a complex and challenging process, as POPs can be present in very low levels and can be difficult to detect. Herein, we developed an ultrasensitive biosensor based on a rolling circle amplification (RCA) platform using a glucometer to determine POP. The biosensor was constructed using gold nanoparticle probes modified with antibodies and dozens of primers, magnetic microparticle probes conjugated with haptens, and targets. After competition, RCA reactions are triggered, numerous RCA products hybridize with the ssDNA-invertase, and the target is successfully transformed into glucose. Using ractopamine as a model analyte, this strategy obtained a linear detection range of 0.038-5.00 ng mL^-1 and a detection limit of 0.0158 ng mL^-1, which was preliminarily verified by screening in real samples. Compared with conventional immunoassays, this biosensor utilizes the high efficiency of RCA and the portable properties of a glucometer, which effectively improves the sensitivity and simplifies the procedures using magnetic separation technology. Moreover, it has been successfully applied to ractopamine determination in animal-derived foods, revealing its potential as a promising tool for POP screening.

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

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

Genetically Encoded Detection of Biosynthetic Protease Inhibitors

Proteases are an important class of drug targets that continue to drive inhibitor discovery. These enzymes are prone to resistance mutations, yet their promise for treating viral diseases and other disorders continues to grow. This study develops a general approach for detecting microbially synthesized protease inhibitors and uses it to screen terpenoid pathways for inhibitory compounds. The detection scheme relies on a bacterial two-hybrid (B2H) system that links protease inactivation to the transcription of a swappable reporter gene. This system, which can accomodate multiple biochemical outputs (i.e., luminescence and antibiotic resistance), permitted the facile incorporation of four disease-relevant proteases. A B2H designed to detect the inactivation of the main protease of severe acute respiratory syndrome coronavirus 2 enabled the identification of a terpenoid inhibitor of modest potency. An analysis of multiple pathways that make this terpenoid, however, suggested that its production was necessary but not sufficient to confer a survival advantage in growth-coupled assays. This finding highlights an important challenge associated with the use of genetic selection to search for inhibitors─notably, the influence of pathway toxicity─and underlines the value of including multiple pathways with overlapping product profiles in pathway screens. This study provides a detailed experimental framework for using microbes to screen libraries of biosynthetic pathways for targeted protease inhibitors.

PicoShells: Hollow Hydrogel Microparticles for High-Throughput Screening of Clonal Libraries

Microfluidics enables the creation of monodisperse, micron-scale aqueous droplets, or other compartments. These droplets serve as picolitre-volume reaction chambers which can be utilized for various chemical assays or reactions. Here we describe the use of a microfluidic droplet generator to encapsulate single cells within hollow hydrogel microparticles called PicoShells. The PicoShell fabrication utilizes a mild pH-based crosslinking modality of an aqueous two-phase prepolymer system, avoiding the cell death and unwanted genomic modifications that accompany more typical, ultraviolet light crosslinking techniques. The cells are grown inside of these PicoShells into monoclonal colonies in any number of environments, including scaled production environments using commercially relevant incubation methods. Colonies can be phenotypically analyzed and/or sorted using standard, high-throughput laboratory techniques, namely, fluorescence-activated cell sorting (FACS). Cell viability is maintained throughout particle fabrication and analysis, and cells exhibiting a desired phenotype can be selected and released for re-culturing and downstream analysis. Large-scale cytometry runs are of particular use when measuring the protein expression of heterogeneous cells in response to environmental stimuli, notably to identify targets early in the drug discovery process. The sorted cells can also be encapsulated multiple times to direct the evolution of a cell line to a desired phenotype.

Challenges to Ensure a Better Translation of Metabolic Engineering for Industrial Applications

Metabolic engineering has evolved towards creating cell factories with increasingly complex pathways as economic criteria push biotechnology to higher value products to provide a sustainable source of speciality chemicals. Optimization of such pathways often requires high combinatory exploration of best pathway balance, and this has led to increasing use of high-throughput automated strain construction platforms or novel optimization techniques. In addition, the low catalytic efficiency of such pathways has shifted emphasis from gene expression strategies towards novel protein engineering to increase specific activity of the enzymes involved so as to limit the metabolic burden associated with excessively high pressure on ribosomal machinery when using massive overexpression systems. Metabolic burden is now generally recognized as a major hurdle to be overcome with consequences on genetic stability but also on the intensified performance needed industrially to attain the economic targets for successful product launch. Increasing awareness of the need to integrate novel genetic information into specific sites within the genome which not only enhance genetic stability (safe harbors) but also enable maximum expression profiles has led to genome-wide assessment of best integration sites, and bioinformatics will facilitate the identification of most probable landing pads within the genome.To facilitate the transfer of novel biotechnological potential to industrial-scale production, more attention, however, has to be paid to engineering metabolic fitness adapted to the specific stress conditions inherent to large-scale fermentation and the inevitable heterogeneity that will occur due to mass transfer limitations and the resulting deviation away from ideal conditions as seen in laboratory-scale validation of the engineered cells. To ensure smooth and rapid transfer of novel cell lines to industry with an accelerated passage through scale-up, better coordination is required form the onset between the biochemical engineers involved in process technology and the genetic engineers building the new strain so as to have an overall strategy able to maximize innovation at all levels. This should be one of our key objectives when building fermentation-friendly chassis organisms.

Construction of automated high-throughput screening method for finding efficient 3-ketosteroid 1,2-dehydrogenating strains

Dehydrogenation reaction at C1(2) positions is typical and representative of industrial production of steroid drugs. Anti-inflammatory activity can be doubled when the nucleus of the anti-inflammatory steroid hormone drug introduces double bonds at the C1(2) positions. Arthrobacter simplex is currently the most widely studied and used strain for C1(2) dehydrogenation. Therefore, breeding Arthrobacter simplex with high-efficiency dehydrogenation ability is of great significance. In order to obtain high-efficiency strains, the research proposed a new screening strategy based on image process technique: firstly, a color reaction between 2,4-dinitrophenylhydrazine (DNPH) and 9α-hydroxyandrost-4-ene-3,17-dione (9α-OH-AD) was established to characterize the dehydrogenation ability of the strain; secondly, the color data of strains mutated by atmospheric and room temperature plasma (ARTP) in the "color reaction" were automated and analyzed for dehydrogenation ability prediction using optimized support vector machine model. Result showed that the prediction accuracy reached as high as 96% in verification experiments. After a series of mutagenesis, including breaking the bottleneck of a single mutation in ARTP, the dominant strain ARLU-146 was finally obtained from 5168 strains. Its initial conversion rate was 0.8059 g/L/h, with a conversion of 94.41% at 24 h, compared to the original strain ASP which increased the transformation rate by more than 10%. By further process optimization, a high conversion (94.34% within 20 h) with high substrate (85 g/L cortisone acetate) was achieved. According to literature research, it is the highest conversion at this substrate concentration. KEY POINTS: • A high-throughput screening method was developed by using image processing and machine learning technique. • "Mutation bottleneck" of single ARTP mutagenesis was surpassed by complex mutagenesis. • A high substrate (85 g/L CA) and high transformation rate craft (94.34% within 20 h) were built.

Engineering whole-cell microbial biosensors: Design principles and applications in monitoring and treatment of heavy metals and organic pollutants

Biosensors have been widely used as cost-effective, rapid, in situ, and real-time analytical tools for monitoring environments. The development of synthetic biology has enabled emergence of genetically engineered whole-cell microbial biosensors. This review updates the design and optimization principles for a diverse array of whole-cell biosensors based on transcription factors (TF) including activators or repressors derived from heavy metal resistance systems, alkanes, and aromatics metabolic pathways of bacteria. By designing genetic circuits, the whole-cell biosensors could be engineered to intelligently sense heavy metals (Hg²⁺, Zn²⁺, Pb²⁺, Au³⁺, Cd²⁺, As³⁺, Ni²⁺, Cu²⁺, and UO₂²⁺) or organic compounds (alcohols, alkanes, phenols, and benzenes) through one-component or two-component system-based TFs, transduce signals through genetic amplifiers, and response as various outputs such as cell fluorescence and bioelectricity for monitoring heavy metals and organic pollutants in real conditions, synthetic curli and surface metal-binding peptides for in situ bio-sorption of heavy metals. We further review strategies that have been implemented to optimize the selectivity and correlation between ligand concentration and output signal of the TF-based biosensors, so as to meet requirements of practical applications. The optimization strategies include protein engineering to change specificities, promoter engineering to improve sensitivities, and genetic circuit-based amplification to enhance dynamic ranges via designing transcriptional amplifiers, logic gates, and feedback loops. At last, we outlook future trends in developing novel forms of biosensors.

Recent advances in high-throughput metabolic engineering: Generation of oligonucleotide-mediated genetic libraries

The preparation of genetic libraries is an essential step to evolve microorganisms and study genotype-phenotype relationships by high-throughput screening/selection. As the large-scale synthesis of oligonucleotides becomes easy, cheap, and high-throughput, numerous novel strategies have been developed in recent years to construct high-quality oligo-mediated libraries, leveraging state-of-art molecular biology tools for genome editing and gene regulation. This review presents an overview of recent advances in creating and characterizing in vitro and in vivo genetic libraries, based on CRISPR/Cas, regulatory RNAs, and recombineering, primarily for Escherichia coli and Saccharomyces cerevisiae. These libraries' applications in high-throughput metabolic engineering, strain evolution and protein engineering are also discussed.

Biosensor and chemo-enzymatic one-pot cascade applications to detect and transform PET-derived terephthalic acid in living cells

Plastic waste imposes a serious problem to the environment and society. Hence, strategies for a circular plastic economy are demanded. One strategy is the engineering of polyester hydrolases toward higher activity for the biotechnological recycling of polyethylene terephthalate (PET). To provide tools for the rapid characterization of PET hydrolases and the detection of degradation products like terephthalic acid (TPA), we coupled a carboxylic acid reductase (CAR) and the luciferase LuxAB. CAR converted TPA into the corresponding aldehydes in Escherichia coli, which yielded bioluminescence that not only semiquantitatively reflected amounts of TPA in hydrolysis samples but is suitable as a high-throughput screening assay to assess PET hydrolase activity. Furthermore, the CAR-catalyzed synthesis of terephthalaldehyde was combined with a reductive amination cascade in a one-pot setup yielding the corresponding diamine, suggesting a new strategy for the transformation of TPA as a product obtained from PET biodegradation.

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First bioreduction of terephthalic acid (TPA) by a carboxylic acid reductase in vivo

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Real-time, high-throughput detection of TPA-derived aldehydes by luciferase LuxAB

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Bioluminescence reflects TPA amounts, assessing (engineered) PET hydrolase activity

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Transformation of TPA into the diamine through chemo-enzymatic one-pot cascade

Plasmonically-enhanced competitive assay for ultrasensitive and multiplexed detection of small molecules

Novel methods that enable facile, ultrasensitive and multiplexed detection of low molecular weight organic compounds such as metabolites, drugs, additives, and organic pollutants are valuable in biomedical research, clinical diagnosis, food safety and environmental monitoring. Here, we demonstrate a simple, rapid, and ultrasensitive method for detection and quantification of small molecules by implementing a competitive immunoassay with an ultrabright fluorescent nanolabel, plasmonic fluor. Plasmonic-fluor is comprised of a polymer-coated gold nanorod and bovine serum albumin conjugated with molecular fluorophores and biotin. The synthesis steps and fluorescence emission of plasmonic-fluor was characterized by UV-vis spectroscopy, transmission electron microscopy, and fluorescence microscopy. Plasmon-enhanced competitive assay can be completed within 20 min and exhibited more than 30-fold lower limit-of-detection for cortisol compared to conventional competitive ELISA. The plasmon-enhanced competitive immunoassay when implemented as partition-free digital assay enabled further improvement in sensitivity. Further, spatially multiplexed plasmon-enhanced competitive assay enabled the simultaneous detection of two analytes (cortisol and fluorescein). This simple, rapid, and ultrasensitive method can be broadly employed for multiplexed detection of various small molecules in research, in-field and clinical settings.

Elucidation of Sequence-Function Relationships for an Improved Biobutanol In Vivo Biosensor in E. coli

Transcription factor (TF)–promoter pairs have been repurposed from native hosts to provide tools to measure intracellular biochemical production titer and dynamically control gene expression. Most often, native TF–promoter systems require rigorous screening to obtain desirable characteristics optimized for biotechnological applications. High-throughput techniques may provide a rational and less labor-intensive strategy to engineer user-defined TF–promoter pairs using fluorescence-activated cell sorting and deep sequencing methods (sort-seq). Based on the designed promoter library’s distribution characteristics, we elucidate sequence–function interactions between the TF and DNA. In this work, we use the sort-seq method to study the sequence–function relationship of a σ⁵⁴-dependent, butanol-responsive TF–promoter pair, BmoR-P_BMO derived from Thauera butanivorans, at the nucleotide level to improve biosensor characteristics, specifically an improved dynamic range. Activities of promoters from a mutagenized P_BMO library were sorted based on gfp expression and subsequently deep sequenced to correlate site-specific sequences with changes in dynamic range. We identified site-specific mutations that increase the sensor output. Double mutant and a single mutant, CA(129,130)TC and G(205)A, in P_BMO promoter increased dynamic ranges of 4-fold and 1.65-fold compared with the native system, respectively. In addition, sort-seq identified essential sites required for the proper function of the σ⁵⁴-dependent promoter biosensor in the context of the host. This work can enable high-throughput screening methods for strain development.

Cheating the Cheater: Suppressing False-Positive Enrichment during Biosensor-Guided Biocatalyst Engineering

Transcription factor (TF)-based biosensors are very desirable reagents for high-throughput enzyme and strain engineering campaigns. Despite their potential, they are often difficult to deploy effectively as the small molecules being detected can leak out of high-producer cells, into low-producer cells, and activate the biosensor therein. This crosstalk leads to the overrepresentation of false-positive/cheater cells in the enriched population. While the host cell can be engineered to minimize crosstalk (e.g., by deleting responsible transporters), this is not easily applicable to all molecules of interest, particularly those that can diffuse passively. One such biosensor recently reported for trans-cinnamic acid (tCA) suffers from crosstalk when used for phenylalanine ammonia-lyase (PAL) enzyme engineering by directed evolution. We report that desensitizing the biosensor (i.e., increasing the limit of detection) suppresses cheater population enrichment. Furthermore, we show that, if we couple the biosensor-based screen with an orthogonal prescreen that eliminates a large fraction of true negatives, we can successfully reduce the cheater population during the fluorescence-activated cell sorting. Using the approach developed here, we were successfully able to isolate PAL variants with ∼70% higher k_cat after a single sort. These mutants have tremendous potential in phenylketonuria (PKU) treatment and flavonoid production.

Engineering of the Ligand Specificity of Transcriptional Regulator XylS by Deep Mutational Scanning

Deep mutational scanning is a method for protein engineering. Here, we applied it to alter the ligand specificity of the transcriptional regulator XylS from Pseudomonas putida to recognize p-toluic acid instead of the native ligand m-toluic acid. For this purpose, we used an antibiotic resistance gene-based dual screening system, which was constructed for the directed evolution of XylS toward the above-mentioned ligand specificity. We constructed a xylS mutant library in which each codon for the amino acid residue of the putative ligand-binding domain (residues 1-213, except 7th residue) was randomized to generate all possible single amino acid-substituted XylS variants and introduced it into Escherichia coli harboring the selection plasmid for the screening system. The cells were cultured in the presence of appropriate antibiotics and m-toluic acid or p-toluic acid, and the frequency of each mutation present in the library was examined using a next-generation sequencer before and after cultivation. Heatmaps showing the enrichment score of each XylS variant were obtained. By searching for a p-toluic-acid-specific heatmap pattern, we focused on G71 and H77. Analysis of the ligand specificities of G71- or H77-substituted XylS variants revealed that several G71-substituted XylS variants responded specifically to p-toluic acid. Thus, the 71st residue was found to be an unprecedented residue that is important for switching ligand specificity. Our study demonstrated the usefulness of deep mutational scanning in engineering the ligand specificity of a transcriptional regulator without structural information. We also discussed the advantages and disadvantages of deep mutational scanning compared with directed evolution.

Enhancing Saccharomyces cerevisiae Taxane Biosynthesis and Overcoming Nutritional Stress-Induced Pseudohyphal Growth

The recent technological advancements in synthetic biology have demonstrated the extensive potential socio-economic benefits at laboratory scale. However, translations of such technologies to industrial scale fermentations remains a major bottleneck. The existence and lack of understanding of the major discrepancies in cultivation conditions between scales often leads to the selection of suboptimal bioprocessing conditions, crippling industrial scale productivity. In this study, strategic design of experiments approaches were coupled with state-of-the-art bioreactor tools to characterize and overcome nutritional stress for the enhanced production of precursors to the blockbuster chemotherapy drug, Taxol, in S. cerevisiae cell factories. The batch-to-batch variation in yeast extract composition was found to trigger nutritional stress at a mini-bioreactor scale, resulting in profound changes in cellular morphology and the inhibition of taxane production. The cells shifted from the typical budding morphology into striking pseudohyphal cells. Doubling initial yeast extract and peptone concentrations (2×YP) delayed filamentous growth, and taxane accumulation improved to 108 mg/L. Through coupling a statistical definitive screening design approach with the state-of-the-art high-throughput micro-bioreactors, the total taxane titers were improved a further two-fold, compared to the 2×YP culture, to 229 mg/L. Filamentous growth was absent in nutrient-limited microscale cultures, underlining the complex and multifactorial nature of yeast stress responses. Validation of the optimal microscale conditions in 1L bioreactors successfully alleviated nutritional stress and improved the titers to 387 mg/L. Production of the key Taxol precursor, T5αAc, was improved two-fold to 22 mg/L compared to previous maxima. The present study highlights the importance of following an interdisciplinary approach combining synthetic biology and bioprocessing technologies for effective process optimization and scale-up.

Development of Synthetic Riboswitches to Guide the Evolution of Metabolite Production in Microorganisms

The untranslated region (UTR) of prokaryotic mRNA contains riboswitches, which are gene regulating modules. Riboswitches can be used as biosensors to regulate the expression of a gene or an operon depending on the intracellular level of a target molecule and consequently modulate the cellular responses. In evolutionary engineering, riboswitch-based biosensors have been widely applied for high-throughput screening or selection of target phenotypes. Evolutionary approaches can overcome the limitations of rational approaches in metabolic engineering. Previous studies have reported synthetic riboswitches equipped with novel aptamers and marker genes based on a deep understanding of the operation mechanism of the riboswitch. Here, we introduce the development process of novel synthetic riboswitches for applications in metabolic engineering.

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.

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.

Biosensor Technologies in Medicine: from Detection of Biochemical Markers to Research into Molecular Targets (Review)

Infections are a major cause of premature death. Fast and accurate laboratory diagnostics of infectious diseases is a key condition for the timely initiation and success of treatment. Potentially, it can reduce morbidity, as well as prevent the outbreak and spread of dangerous epidemics. The traditional methods of laboratory diagnostics of infectious diseases are quite time- and labour-consuming, require expensive equipment and trained personnel, which is crucial within limited resources. The fast biosensor-based methods that combine the diagnostic capabilities of biomedicine with modern technological advances in microelectronics, optoelectronics, and nanotechnology make an alternative.

The modern achievements in the development of label-free biosensors make them promising diagnostic tools that combine rapid detection of specific molecular markers, simplicity, ease-of-use, efficiency, accuracy, and cost-effectiveness with the tendency to the development of portable platforms. These qualities exceed the generally accepted standards of microbiological and immunological diagnostics and open up broad prospects for using these analytical systems in clinical practice directly at the site of medical care provision (point-of-care, POC concept).

A wide variety of modern biosensor designs are based on the use of diverse formats of analytical and technological strategies, identification of various regulatory and functional molecular markers associated with infectious pathogens. The solution to the existing problems in biosensing will open up great prospects for these rapidly developing diagnostic biotechnologies.

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.

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.

Microbial production of advanced biofuels

Concerns over climate change have necessitated a rethinking of our transportation infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced by engineered microorganisms that use a renewable carbon source. Two biofuels, ethanol and biodiesel, have made inroads in displacing petroleum-based fuels, but their uptake has been limited by the amounts that can be used in conventional engines and by their cost. Advanced biofuels that mimic petroleum-based fuels are not limited by the amounts that can be used in existing transportation infrastructure but have had limited uptake due to costs. In this Review, we discuss engineering metabolic pathways to produce advanced biofuels, challenges with substrate and product toxicity with regard to host microorganisms and methods to engineer tolerance, and the use of functional genomics and machine learning approaches to produce advanced biofuels and prospects for reducing their costs.

Synthetic biosensor accelerates evolution by rewiring carbon metabolism toward a specific metabolite

Proper carbon flux distribution between cell growth and production of a target compound is important for biochemical production because improper flux reallocation inhibits cell growth, thus adversely affecting production yield. Here, using a synthetic biosensor to couple production of a specific metabolite with cell growth, we spontaneously evolve cells under the selective condition toward the acquisition of genotypes that optimally reallocate cellular resources. Using 3-hydroxypropionic acid (3-HP) production from glycerol in Escherichia coli as a model system, we determine that mutations in the conserved regions of proteins involved in global transcriptional regulation alter the expression of several genes associated with central carbon metabolism. These changes rewire central carbon flux toward the 3-HP production pathway, increasing 3-HP yield and reducing acetate accumulation by alleviating overflow metabolism. Our study provides a perspective on adaptive laboratory evolution (ALE) using synthetic biosensors, thereby supporting future efforts in metabolic pathway optimization.

LuxAB-Based Microbial Cell Factories for the Sensing, Manufacturing and Transformation of Industrial Aldehydes

The application of genetically encoded biosensors enables the detection of small molecules in living cells and has facilitated the characterization of enzymes, their directed evolution and the engineering of (natural) metabolic pathways. In this work, the LuxAB biosensor system from Photorhabdus luminescens was implemented in Escherichia coli to monitor the enzymatic production of aldehydes from primary alcohols and carboxylic acid substrates. A simple high-throughput assay utilized the bacterial luciferase—previously reported to only accept aliphatic long-chain aldehydes—to detect structurally diverse aldehydes, including aromatic and monoterpene aldehydes. LuxAB was used to screen the substrate scopes of three prokaryotic oxidoreductases: an alcohol dehydrogenase (Pseudomonas putida), a choline oxidase variant (Arthrobacter chlorophenolicus) and a carboxylic acid reductase (Mycobacterium marinum). Consequently, high-value aldehydes such as cinnamaldehyde, citral and citronellal could be produced in vivo in up to 80% yield. Furthermore, the dual role of LuxAB as sensor and monooxygenase, emitting bioluminescence through the oxidation of aldehydes to the corresponding carboxylates, promises implementation in artificial enzyme cascades for the synthesis of carboxylic acids. These findings advance the bio-based detection, preparation and transformation of industrially important aldehydes in living cells.

High-throughput optofluidic screening for improved microbial cell factories via real-time micron-scale productivity monitoring

The industrial synthetic biology sector has made huge investments to achieve relevant miniaturized screening systems for scalable fermentation. Here we present the first example of a high-throughput (>10³ genotypes per week) perfusion-based screening system to improve small-molecule secretion from microbial strains. Using the Berkeley Lights Beacon® system, the productivity of each strain could be directly monitored in real time during continuous culture, yielding phenotypes that correlated strongly (r² > 0.8, p < 0.0005) with behavior in industrially relevant bioreactor processes. This method allows a much closer approximation of a typical fed-batch fermentation than conventional batch-like droplet or microplate culture models, in addition to rich time-dependent data on growth and productivity. We demonstrate these advantages by application to the improvement of high-productivity strains using whole-genome random mutagenesis, yielding mutants with substantially improved (by up to 85%) peak specific productivities in bioreactors. Each screen of ∼5 × 10³ mutants could be completed in under 8 days (including 5 days involving user intervention), saving ∼50-75% of the time required for conventional microplate-based screening methods.

Recent trends in biocatalysis

Biocatalysis has undergone revolutionary progress in the past century. Benefited by the integration of multidisciplinary technologies, natural enzymatic reactions are constantly being explored. Protein engineering gives birth to robust biocatalysts that are widely used in industrial production. These research achievements have gradually constructed a network containing natural enzymatic synthesis pathways and artificially designed enzymatic cascades. Nowadays, the development of artificial intelligence, automation, and ultra-high-throughput technology provides infinite possibilities for the discovery of novel enzymes, enzymatic mechanisms and enzymatic cascades, and gradually complements the lack of remaining key steps in the pathway design of enzymatic total synthesis. Therefore, the research of biocatalysis is gradually moving towards the era of novel technology integration, intelligent manufacturing and enzymatic total synthesis.

Biosensor-Assisted Adaptive Laboratory Evolution for Violacein Production

Violacein is a naturally occurring purple pigment, widely used in cosmetics and has potent antibacterial and antiviral properties. Violacein can be produced from tryptophan, consequently sufficient tryptophan biosynthesis is the key to violacein production. However, the complicated biosynthetic pathways and regulatory mechanisms often make the tryptophan overproduction challenging in Escherichia coli. In this study, we used the adaptive laboratory evolution (ALE) strategy to improve violacein production using galactose as a carbon source. During the ALE, a tryptophan-responsive biosensor was employed to provide selection pressure to enrich tryptophan-producing cells. From the biosensor-assisted ALE, we obtained an evolved population of cells capable of effectively catabolizing galactose to tryptophan and subsequently used the population to obtain the best violacein producer. In addition, whole-genome sequencing of the evolved strain identified point mutations beneficial to the overproduction. Overall, we demonstrated that the biosensor-assisted ALE strategy could be used to rapidly and selectively evolve the producers to yield high violacein production.

Antibiofilm and anti-quorum sensing activities of eugenol and linalool from Ocimum tenuiflorum against Pseudomonas aeruginosa biofilm

AIMS

The aim of this study is to determine the ability of two bioactive compounds, namely, eugenol and linalool, purified from leaves of Ocimum tenuiflorum for eradication of biofilm produced by Pseudomonas aeruginosa.

METHODS AND RESULTS

The phytoextract of O. tenuiflorum (KT), a common ethno-botanical plant of India, was purified through high-performance liquid chromatography and was analysed using ultraviolet (UV) spectroscopy and gas chromatography-mass spectrometry (GC-MS). Eugenol and linalool were found to be the most active amongst all phytocompounds present in phytoextract and showed a significant reduction in the viability of sessile cells of P. aeruginosa and the minimum revival after withdrawal of phyto-challenge. They could bring about notable reduction in the protein and carbohydrate content of exopolysaccharide of biofilm. Eugenol and linalool could affect the synthesis of quorum sensing (QS) proteins like LasA and LasB as well as virulence factors such as pyocyanin, and rhamnolipids, which seriously hamper the formation of biofilm. The biofilm framework was extremely affected by the phytocompounds through the reduction of protein and carbohydrate content of extracellular polymeric substance (EPS). Another interesting found out was that they brought about maximum inhibition to the genomic DNA and RNA content. The studies were supported by in silico interaction between eugenol and linalool with the QS proteins. The antibiofilm efficacies of eugenol, linalool and phytoextract (KT) were further confirmed by microscopic studies with scanning electron microscopy (SEM), atomic force microscopy and fluorescence confocal microscopy microscopic studies.

CONCLUSIONS

The phytocompounds are proved to be more effective than conventional antibiotics in inhibiting the biofilm forming sessile cells and can be used as a replacement for antibiotic.

SIGNIFICANCE AND IMPACT OF THE STUDY

Pure eugenol extracted from common basil leaves can be used as a safe substitute for common antibiotic for treatment of chronic infections caused by P. aeruginosa. It will be cost effective, devoid of notable side effects and will not generate antibiotic resistance in host body.

Biosensor-Based Multigene Pathway Optimization for Enhancing the Production of Glycolate

Glycolate is widely used in industry, especially in the fields of chemical cleaning, cosmetics, and medical materials, and has broad market prospects for the future. Recent advances in metabolic engineering and synthetic biology have significantly improved the titer and yield of glycolate. However, an expensive inducer was used in previous studies, which is not feasible for use in large-scale industrial fermentations. To constitutively biosynthesize glycolate, the expression level of each gene of the glycolate synthetic pathway needs to be systemically optimized. The main challenge of multigene pathway optimization is being able to select or screen the optimum strain from the randomly assembled library by an efficient high-throughput method within a short time. To overcome these challenges, we firstly established a glycolate-responsive biosensor and developed agar plate- and 48-well deep-well plate-scale high-throughput screening methods for the rapid screening of superior glycolate producers from a large library. A total of 22 gradient-strength promoter-5'-untranslated region (UTR) complexes were randomly cloned upstream of the genes of the glycolate synthetic pathway, generating a large random assembled library. After rounds of screening, the optimum strain was obtained from 6 × 10⁵ transformants in a week, and it achieved a titer of 40.9 ± 3.7 g/liter glycolate in a 5-liter bioreactor. Furthermore, high expression levels of the enzymes YcdW and GltA were found to promote glycolate production, whereas AceA has no obvious impact on glycolate production. Overall, the glycolate biosensor-based pathway optimization strategy presented in this work provides a paradigm for other multigene pathway optimizations. IMPORTANCE The use of strong promoters, such as pTrc and T7, to control gene expression not only needs the addition of expensive inducers but also results in excessive protein expression that may result in unbalanced metabolic flux and the waste of cellular building blocks and energy. To balance the metabolic flux of glycolate biosynthesis, the expression level of each gene needs to be systemically optimized in a constitutive manner. However, the lack of high-throughput screening methods restricted glycolate synthetic pathway optimization. Our work firstly established a glycolate-response biosensor, and agar plate- and 48-well plate-scale high-throughput screening methods were then developed for the rapid screening of optimum pathways from a large library. Finally, we obtained a glycolate-producing strain with good biosynthetic performance, and the use of the expensive inducer isopropyl-β-d-thiogalactopyranoside (IPTG) was avoided, which broadens our understanding of the mechanism of glycolate synthesis.

Advanced strategies and tools to facilitate and streamline microbial adaptive laboratory evolution

Adaptive laboratory evolution (ALE) has served as a historic microbial engineering method that mimics natural selection to obtain desired microbes. The past decade has witnessed improvements in all aspects of ALE workflow, in terms of growth coupling, genotypic diversification, phenotypic selection, and genotype-phenotype mapping. The developing growth-coupling strategies facilitate ALE to a wider range of appealing traits. In vivo mutagenesis methods and multiplexed automated culture platforms open new gates to streamline its execution. Meanwhile, the application of multi-omics analyses and multiplexed genetic engineering promote efficient knowledge mining. This article provides a comprehensive and updated review of these advances, highlights newest significant applications, and discusses future improvements, aiming to provide a practical guide for implementation of novel, effective, and efficient ALE experiments.

Development and application of a high throughput assay system for the detection of Rieske dioxygenase activity

Herein we report the development of a new periodate-based reactive assay system for the fluorescent detection of the cis-diol metabolites produced by Rieske dioxygenases. This sensitive and diastereoselective assay system successfully evaluates the substrate scope of Rieske dioxygenases and determines the relative activity of a rationally designed Rieske dioxygenase variant library. The high throughput capacity of the assay system enables rapid and efficient substrate scope investigations and screening of large dioxygenase variant libraries.

Screening of Beauveria bassiana with high biocontrol potential based on ARTP mutagenesis and high-throughput FACS

Beauveria bassiana is a promising biocontrol agent due to its entomopathogenic activities and residue-free characteristics. However, its susceptibility to abiotic stresses and naturally low virulence limit the effective application of this fungus. To effectively obtain fungal strains with high biocontrol potential, fluorescence-activated cell sorting (FACS) was used to screen mutant libraries generated by atmospheric and room temperature plasma (ARTP). Among about 8000 mutants obtained by ARTP mutagenesis, six candidate mutants were selected according to the forward scatter (FSC) signal readings of FACS. B6, with a 37.4% higher FSC reading than wild-type (WT), showed a 32.6% increase in virulence. It also presented a 13.5% decrease in median germinating time (GT₅₀) and a 12.1% increase in blastospore production. Comparative analysis between insect transcriptional responses to B6 and WT infection showed that the immune response coupled with protein digestion and absorption progress was highly activated in B6-infected Galleria mellonella larvae, while fatty acid synthesis was suppressed after 3 days of infection. Our results confirmed the feasibility of sorting B. bassiana with high biocontrol potential via the combination of ARTP and FACS and facilitated the understanding of insect-pathogen interactions, highlighting a new strategy for modifying entomopathogenic fungi to improve the efficiency of biological control.

Site-Directed Mutagenesis of Modular Polyketide Synthase Ketoreductase Domains for Altered Stereochemical Control

Bacterial modular type I polyketide synthases (PKSs) are complex multidomain assembly line proteins that produce a range of pharmaceutically relevant molecules with a high degree of stereochemical control. Due to their colinear properties, they have been considerable targets for rational biosynthetic pathway engineering. Among the domains harbored within these complex assembly lines, ketoreductase (KR) domains have been extensively studied with the goal of altering their stereoselectivity by site-directed mutagenesis, as they confer much of the stereochemical complexity present in pharmaceutically active reduced polyketide scaffolds. Here we review all efforts to date to perform site-directed mutagenesis on PKS KRs, most of which have been done in the context of excised KR domains on model diffusible substrates such as β-keto N-acetyl cysteamine thioesters. We also discuss the challenges around translating the findings of these studies to alter stereocontrol in the context of a complex multidomain enzymatic assembly line.

Dietary Change Enables Robust Growth-Coupling of Heterologous Methyltransferase Activity in Yeast

Genetic modifications of living organisms and proteins are made possible by a catalogue of molecular and synthetic biology tools, yet proper screening assays for genetic variants of interest continue to lag behind. Synthetic growth-coupling (GC) of enzyme activities offers a simple, inexpensive way to track such improvements. In this follow-up study we present the optimization of a recently established GC design for screening of heterologous methyltransferases (MTases) and related pathways in the yeast Saccharomyces cerevisiae. Specifically, upon testing different media compositions and genetic backgrounds, improved GC of different heterologous MTase activities is obtained. Furthermore, we demonstrate the strength of the system by screening a library of catechol O-MTase variants converting protocatechuic acid into vanillic acid. We demonstrated high correlation (R² = 0.775) between vanillic acid and cell density as a proxy for MTase activity. We envision that the improved MTase GC can aid evolution-guided optimization of biobased production processes for methylated compounds with yeast in the future.