Design, Optimization and Application of Small Molecule Biosensor in Metabolic Engineering

Self-controlled in silico gene knockdown strategies to enhance the sustainable production of heterologous terpenoid by Saccharomyces cerevisiae

Microbial bioengineering is a growing field for producing plant natural products (PNPs) in recent decades, using heterologous metabolic pathways in host cells. Once heterologous metabolic pathways have been introduced into host cells, traditional metabolic engineering techniques are employed to enhance the productivity and yield of PNP biosynthetic routes, as well as to manage competing pathways. The advent of computational biology has marked the beginning of a novel epoch in strain design through in silico methods. These methods utilize genome-scale metabolic models (GEMs) and flux optimization algorithms to facilitate rational design across the entire cellular metabolic network. However, the implementation of in silico strategies can often result in an uneven distribution of metabolic fluxes due to the rigid knocking out of endogenous genes, which can impede cell growth and ultimately impact the accumulation of target products. In this study, we creatively utilized synthetic biology to refine in silico strain design for efficient PNPs production. OptKnock simulation was performed on the GEM of Saccharomyces cerevisiae OA07, an engineered strain for oleanolic acid (OA) bioproduction that has been reported previously. The simulation predicted that the single deletion of fol1, fol2, fol3, abz1, and abz2, or a combined knockout of hfd1, ald2 and ald3 could improve its OA production. Consequently, strains EK1∼EK7 were constructed and cultivated. EK3 (OA07△fol3), EK5 (OA07△abz1), and EK6 (OA07△abz2) had significantly higher OA titers in a batch cultivation compared to the original strain OA07. However, these increases were less pronounced in the fed-batch mode, indicating that gene deletion did not support sustainable OA production. To address this, we designed a negative feedback circuit regulated by malonyl-CoA, a growth-associated intermediate whose synthesis served as a bypass to OA synthesis, at fol3, abz1, abz2, and at acetyl-CoA carboxylase-encoding gene acc1, to dynamically and autonomously regulate the expression of these genes in OA07. The constructed strains R_3A, R_5A and R_6A had significantly higher OA titers than the initial strain and the responding gene-knockout mutants in either batch or fed-batch culture modes. Among them, strain R_3A stand out with the highest OA titer reported to date. Its OA titer doubled that of the initial strain in the flask-level fed-batch cultivation, and achieved at 1.23 ± 0.04 g L-1 in 96 h in the fermenter-level fed-batch mode. This indicated that the integration of optimization algorithm and synthetic biology approaches was efficiently rational for PNP-producing strain design.

One-step electrodeposited hybrid nanofilms in amperometric biosensor development

This review summarizes recent developments in amperometric biosensors, based on one-step electrodeposited organic-inorganic hybrid layers, used for analysis of low molecular weight compounds. The factors affecting self-assembly of one-step electrodeposited films, methods for verifying their composition, advantages, limitations and approaches affecting the electroanalytical performance of amperometric biosensors based on organic-inorganic hybrid layers were systemized. Moreover, issues related to the formation of one-step organic-inorganic hybrid functional layers with different structures in biosensors produced under the same electrodeposition parameters are discussed. The systemized dependencies can support the preliminary choice of functional sensing layers with architectures tuned for specific biotechnology and life science applications. Finally, the capabilities of one-step electrodeposition of organic-inorganic hybrid functional films beyond amperometric biosensors were highlighted.

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

Engineering of a Substrate Affinity Reduced S-Adenosyl-methionine Synthetase as a Novel Biosensor for Growth-Coupling Selection of L-Methionine Overproducers

Biosensors are powerful tools for monitoring specific metabolites or controlling metabolic flux towards the products in a single cell, which play important roles in microbial cell factory construction. Despite their potential role in metabolic flux monitoring, the development of biosensors for small molecules is still limited. Reported biosensors often exhibit bottlenecks of poor specificity and a narrow dynamic range. Moreover, fine-tuning the substrate binding affinity of a crucial enzyme can decrease its catalytic activity, which ultimately results in the repression of the corresponding essential metabolite biosynthesis and impairs cell growth. However, increasing intracellular substrate concentration can elevate the availability of the essential metabolite and may lead to restore cellular growth. Herein, a new strategy was proposed for constructing whole-cell biosensors based on enzyme encoded by essential gene that offer inherent specificity and universality. Specifically, S-adenosyl-methionine synthetase (MetK) in E. coli was chosen as the crucial enzyme, and a series of MetK variants were identified that were sensitive to L-methionine concentration. This occurrence enabled the engineered cell to sense L-methionine and exhibit L-methionine dose-dependent cell growth. To improve the biosensor's dynamic range, an S-adenosyl-methionine catabolic enzyme was overexpressed to reduce the intracellular availability of S-adenosyl-methionine. The resulting whole-cell biosensor effectively coupled the intracellular concentration of L-methionine with growth and was successfully applied to select strains with enhanced L-methionine biosynthesis from random mutagenesis libraries. Overall, our study presents a universal strategy for designing and constructing growth-coupled biosensors based on crucial enzyme, which can be applied to select strains overproducing high value-added metabolites in cellular metabolism.

Plant Life with and without Oxygen: A Metabolomics Approach

Oxygen deficiency is an environmental challenge which affects plant growth, the development and distribution in land and aquatic ecosystems, as well as crop yield losses worldwide. The capacity to exist in the conditions of deficiency or the complete lack of oxygen depends on a number of anatomic, developmental and molecular adaptations. The lack of molecular oxygen leads to an inhibition of aerobic respiration, which causes energy starvation and the acceleration of glycolysis passing into fermentations. We focus on systemic metabolic alterations revealed with the different approaches of metabolomics. Oxygen deprivation stimulates the accumulation of glucose, pyruvate and lactate, indicating the acceleration of the sugar metabolism, glycolysis and lactic fermentation, respectively. Among the Krebs-cycle metabolites, only the succinate level increases. Amino acids related to glycolysis, including the phosphoglycerate family (Ser and Gly), shikimate family (Phe, Tyr and Trp) and pyruvate family (Ala, Leu and Val), are greatly elevated. Members of the Asp family (Asn, Lys, Met, Thr and Ile), as well as the Glu family (Glu, Pro, Arg and GABA), accumulate as well. These metabolites are important members of the metabolic signature of oxygen deficiency in plants, linking glycolysis with an altered Krebs cycle and allowing alternative pathways of NAD(P)H reoxidation to avoid the excessive accumulation of toxic fermentation products (lactate, acetaldehyde, ethanol). Reoxygenation induces the downregulation of the levels of major anaerobically induced metabolites, including lactate, succinate and amino acids, especially members of the pyruvate family (Ala, Leu and Val), Tyr and Glu family (GABA and Glu) and Asp family (Asn, Met, Thr and Ile). The metabolic profiles during native and environmental hypoxia are rather similar, consisting in the accumulation of fermentation products, succinate, fumarate and amino acids, particularly Ala, Gly and GABA. The most intriguing fact is that metabolic alterations during oxidative stress are very much similar, with plant response to oxygen deprivation but not to reoxygenation.

Biosensor-based high-throughput screening enabled efficient adipic acid production

Adipic acid is an industrially important chemical, but the current approach to synthesize it can be of serious pollution to the environment. Rencently, bio-based production of adipic acid has significantly advanced with the development of metabolic engineering and synthetic biology. However, genetic heterogeneity-caused decrease of product titer has largely limited the industrialization of chemicals like adipic acid. Therefore, in the attempt to overcome this challenge, we constitutively expressed the reverse adipate degradation pathway, designed and optimized an adipic acid biosensor, and established a high-throughput screening platform to screen for high-performance strains based on the optimized biosensor. Using this platform, we successfully screened a strain with an adipic acid titer of 188.08 mg·L^-1. Coupling the screening platform with fermentation optimization, the titer of adipic acid reached 531.88 mg·L^-1 under shake flask fermentation, which achieved an 18.78-fold improvement comparing to the initial strain. Scale-up fermentation in a 5-L fermenter utilizing the screened high-performance strain was eventually conducted, in which the adipic acid titer reached 3.62 g·L^-1. Overall, strategies developed in this study proved to be a potentially efficient method in reducing the genetic heterogeneity and was expected to provide guidance in helping to build a more efficient industrial screening process. KEY POINTS: • Developed a fine-tuned adipic acid biosensor. • Established a high-throughput screening platform to screen high-performance strains. • The titer of adipic acid reached 3.62 g·L^-1 in a 5-L fermenter.

Transcription factor-based biosensors for screening and dynamic regulation

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.

In vivo protein-based biosensors: seeing metabolism in real time

Biological homeostasis is a dynamic and elastic equilibrium of countless interlinked biochemical reactions. A key goal of life sciences is to understand these dynamics; bioengineers seek to reconfigure such networks. Both goals require the ability to monitor the concentration of individual intracellular metabolites with sufficient spatiotemporal resolution. To achieve this, a range of protein or protein/DNA signalling circuits with optical readouts have been constructed. Protein biosensors can provide quantitative information at subsecond temporal and suborganelle spatial resolution. However, their construction is fraught with difficulties related to integrating the affinity- and selectivity-endowing components with the signal reporters. We argue that development of efficient approaches for construction of chemically induced dimerisation systems and reporter domains with large dynamic ranges will solve these problems.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

The bright frontiers of microbial metabolic optogenetics

In recent years, light-responsive systems from the field of optogenetics have been applied to several areas of metabolic engineering with remarkable success. By taking advantage of light's high tunability, reversibility, and orthogonality to host endogenous processes, optogenetic systems have enabled unprecedented dynamical controls of microbial fermentations for chemical production, metabolic flux analysis, and population compositions in co-cultures. In this article, we share our opinions on the current state of this new field of metabolic optogenetics.We make the case that it will continue to impact metabolic engineering in increasingly new directions, with the potential to challenge existing paradigms for metabolic pathway and strain optimization as well as bioreactor operation.

Highly multiplexed selection of RNA aptamers against a small molecule library

Applications of synthetic biology spanning human health, industrial bioproduction, and ecosystem monitoring often require small molecule sensing capabilities, typically in the form of genetically encoded small molecule biosensors. Critical to the deployment of greater numbers of these systems are methods that support the rapid development of such biosensors against a broad range of small molecule targets. Here, we use a previously developed method for selection of RNA biosensors against unmodified small molecules (DRIVER) to perform a selection against a densely multiplexed mixture of small molecules, representative of those employed in high-throughput drug screening. Using a mixture of 5,120 target compounds randomly sampled from a large diversity drug screening library, we performed a 95-round selection and then analyzed the enriched RNA biosensor library using next generation sequencing (NGS). From our analysis, we identified RNA biosensors with at least 2-fold change in signal in the presence of at least 217 distinct target compounds with sensitivities down to 25 nM. Although many of these biosensors respond to multiple targets, clustering analysis indicated at least 150 different small-molecule sensing patterns. We also built a classifier that was able to predict whether the biosensors would respond to a new compound with an average precision of 0.82. Since the target compound library was designed to be representative of larger diversity compound libraries, we expect that the described approach can be used with similar compound libraries to identify aptamers against other small molecules with a similar success rate. The new RNA biosensors (or their component aptamers) described in this work can be further optimized and used in applications such as biosensing, gene control, or enzyme evolution. In addition, the data presented here provide an expanded compendium of new RNA aptamers compared to the 82 small molecule RNA aptamers published in the literature, allowing further bioinformatic analyses of the general classes of small molecules for which RNA aptamers can be found.

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.

Emerging Biosensors for Oral Cancer Detection and Diagnosis—A Review Unravelling Their Role in Past and Present Advancements in the Field of Early Diagnosis

Oral cancer is a serious concern to people all over the world because of its high mortality rate and metastatic spread to other areas of the body. Despite recent advancements in biomedical research, OC detection at an early stage remains a challenge and is complex and inaccurate with conventional diagnostics procedures. It is critical to study innovative approaches that can enable a faster, easier, non-invasive, and more precise diagnosis of OC in order to increase the survival rate of patients. In this paper, we conducted a review on how biosensors might be an excellent tool for detecting OC. This review covers the strategies that use different biosensors to target various types of biomarkers and focuses on biosensors that function at the molecular level viz. DNA biosensors, RNA biosensors, and protein biosensors. In addition, we reviewed non-invasive electrochemical methods, optical methods, and nano biosensors to analyze the OC biomarkers present in body fluids such as saliva and serum. As a result, this review sheds light on the development of ground-breaking biosensors for the early detection and diagnosis of OC.

Recent Advances, Challenges and Metabolic Engineering Strategies in the Biosynthesis of 3-Hydroxypropionic Acid

As an attractive and valuable platform chemical, 3-hydroxypropionic acid (3-HP) can be used to produce a variety of industrially important commodity chemicals and biodegradable polymers. Moreover, the biosynthesis of 3-HP has drawn much attention in recent years due to its sustainability and environmental friendliness. Here, we focus on recent advances, challenges and metabolic engineering strategies in the biosynthesis of 3-HP. While glucose and glycerol are major carbon sources for its production of 3-HP via microbial fermentation, other carbon sources have also been explored. To increase yield and titer, synthetic biology and metabolic engineering strategies have been explored, including modifying pathway enzymes, eliminating flux blockages due to byproduct synthesis, eliminating toxic byproducts, and optimizing via genome-scale models. This review also provides insights on future directions for 3-HP biosynthesis. This article is protected by copyright. All rights reserved.

Large scale, single-cell FRET-based glucose uptake measurements within heterogeneous populations

Fluorescent biosensors are powerful tools allowing the concentration of metabolites and small molecules, and other properties such as pH and molecular crowding to be measured inside live single cells. The technology has been hampered by lack of simple software to identify cells and quantify biosensor signals in single cells. We have developed a new software package, FRETzel, to address this gap and demonstrate its use by measuring insulin-stimulated glucose uptake in individual fat cells of varying sizes for the first time. Our results support the long-standing hypothesis that larger fat cells are less sensitive to insulin than smaller ones, a finding that has important implications for the battle against type 2 diabetes. FRETzel has been optimized using the messy and crowded environment of cultured adipocytes, demonstrating its utility for quantification of FRET biosensors in a wide range of other cell types, including fibroblasts and yeast via a simple user-friendly quantitative interface.

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FRETzel is a new software package for easy analysis of FRET signals in cells

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FRETzel is used to quantify glucose uptake in adipocytes of different sizes

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Reduced glucose uptake suggests that larger adipocytes have lower insulin sensitivity

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FRETzel is demonstrated on a range of cell types: yeast, fibroblasts, and adipocytes

Strategies for Improving Small-Molecule Biosensors in Bacteria

In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.

Toward improved terpenoids biosynthesis: strategies to enhance the capabilities of cell factories

Terpenoids form the most diversified class of natural products, which have gained application in the pharmaceutical, food, transportation, and fine and bulk chemical industries. Extraction from naturally occurring sources does not meet industrial demands, whereas chemical synthesis is often associated with poor enantio-selectivity, harsh working conditions, and environmental pollutions. Microbial cell factories come as a suitable replacement. However, designing efficient microbial platforms for isoprenoid synthesis is often a challenging task. This has to do with the cytotoxic effects of pathway intermediates and some end products, instability of expressed pathways, as well as high enzyme promiscuity. Also, the low enzymatic activity of some terpene synthases and prenyltransferases, and the lack of an efficient throughput system to screen improved high-performing strains are bottlenecks in strain development. Metabolic engineering and synthetic biology seek to overcome these issues through the provision of effective synthetic tools. This review sought to provide an in-depth description of novel strategies for improving cell factory performance. We focused on improving transcriptional and translational efficiencies through static and dynamic regulatory elements, enzyme engineering and high-throughput screening strategies, cellular function enhancement through chromosomal integration, metabolite tolerance, and modularization of pathways.

Biotechnology Applications of Cell-Free Expression Systems

Cell-free systems are a rapidly expanding platform technology with an important role in the engineering of biological systems. The key advantages that drive their broad adoption are increased efficiency, versatility, and low cost compared to in vivo systems. Traditionally, in vivo platforms have been used to synthesize novel and industrially relevant proteins and serve as a testbed for prototyping numerous biotechnologies such as genetic circuits and biosensors. Although in vivo platforms currently have many applications within biotechnology, they are hindered by time-constraining growth cycles, homeostatic considerations, and limited adaptability in production. Conversely, cell-free platforms are not hindered by constraints for supporting life and are therefore highly adaptable to a broad range of production and testing schemes. The advantages of cell-free platforms are being leveraged more commonly by the biotechnology community, and cell-free applications are expected to grow exponentially in the next decade. In this study, new and emerging applications of cell-free platforms, with a specific focus on cell-free protein synthesis (CFPS), will be examined. The current and near-future role of CFPS within metabolic engineering, prototyping, and biomanufacturing will be investigated as well as how the integration of machine learning is beneficial to these applications.

Synthetic cellular communication-based screening for strains with improved 3-hydroxypropionic acid secretion

Although cellular secretion is important in industrial biotechnology, its assessment is difficult due to the lack of efficient analytical methods. This study describes a synthetic cellular communication-based microfluidic platform for screening strains with the improved secretion of 3-hydroxypropionic acid (3-HP), an industry-relevant platform chemical. 3-HP-secreting cells were compartmentalized in droplets, with receiving cells equipped with a genetic circuit that converts the 3-HP secretion level into an easily detectable signal. This platform was applied to identify Escherichia coli genes that enhance the secretion of 3-HP. As a result, two genes (setA, encoding a sugar exporter, and yjcO, encoding a Sel1 repeat-containing protein) found by this platform enhance the secretion of 3-HP and its production. Given the increasing design capability for chemical-detecting cells, this platform has considerable potential in identifying efflux pumps for not only 3-HP but also many important chemicals.

Evolving Small-Molecule Biosensors with Improved Performance and Reprogrammed Ligand Preference Using OrthoRep

Genetically encoded biosensors are valuable for the optimization of small-molecule biosynthesis pathways, because they transduce the production of small-molecule ligands into a readout compatible with high-throughput screening or selection in vivo. However, engineering biosensors with appropriate response functions and ligand preferences remains challenging. Here, we show that the continuous hypermutation system, OrthoRep, can be effectively applied to evolve biosensors with a high dynamic range, reprogrammed activity toward desired noncognate ligands, and proper operational range for coupling to biosynthetic pathways. In particular, we encoded the allosteric transcriptional factor, BenM, on OrthoRep such that the propagation of host yeast cells resulted in BenM's rapid and continuous diversification. When these cells were subjected to cycles of culturing and sorting on BenM activity in the presence and absence of its cognate ligand, muconic acid, or the noncognate ligand, adipic acid, we obtained multiple BenM variants that respond to their corresponding ligands. These biosensors outperform previously engineered BenM-based biosensors by achieving a substantially greater dynamic range (up to ∼180-fold induction) and broadened operational range. The expression of select BenM variants in the presence of a muconic acid biosynthetic pathway demonstrated sensitive biosensor activation without saturating response, which should enable pathway and host engineering for higher production of muconic and adipic acids. Given the streamlined manner in which high-performance and versatile biosensors were evolved using OrthoRep, this study provides a template for generating custom biosensors for metabolic pathway engineering and other biotechnology goals.

Phage-Assisted Continuous Evolution and Selection of Enzymes for Chemical Synthesis

Ligand-dependent biosensors are valuable tools for coupling the intracellular concentrations of small molecules to easily detectable readouts such as absorbance, fluorescence, or cell growth. While ligand-dependent biosensors are widely used for monitoring the production of small molecules in engineered cells and for controlling or optimizing biosynthetic pathways, their application to directed evolution for biocatalysts remains underexplored. As a consequence, emerging continuous evolution technologies are rarely applied to biocatalyst evolution. Here, we develop a panel of ligand-dependent biosensors that can detect a range of small molecules. We demonstrate that these biosensors can link enzymatic activity to the production of an essential phage protein to enable biocatalyst-dependent phage-assisted continuous evolution (PACE) and phage-assisted continuous selection (PACS). By combining these phage-based evolution and library selection technologies, we demonstrate that we can evolve enzyme variants with improved and expanded catalytic properties. Finally, we show that the genetic diversity resulting from a highly mutated PACS library is enriched for active enzyme variants with altered substrate scope. These results lay the foundation for using phage-based continuous evolution and selection technologies to engineer biocatalysts with novel substrate scope and reactivity.

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.

Synthetic biology as driver for the biologization of materials sciences

Materials in nature have fascinating properties that serve as a continuous source of inspiration for materials scientists. Accordingly, bio-mimetic and bio-inspired approaches have yielded remarkable structural and functional materials for a plethora of applications. Despite these advances, many properties of natural materials remain challenging or yet impossible to incorporate into synthetic materials. Natural materials are produced by living cells, which sense and process environmental cues and conditions by means of signaling and genetic programs, thereby controlling the biosynthesis, remodeling, functionalization, or degradation of the natural material. In this context, synthetic biology offers unique opportunities in materials sciences by providing direct access to the rational engineering of how a cell senses and processes environmental information and translates them into the properties and functions of materials. Here, we identify and review two main directions by which synthetic biology can be harnessed to provide new impulses for the biologization of the materials sciences: first, the engineering of cells to produce precursors for the subsequent synthesis of materials. This includes materials that are otherwise produced from petrochemical resources, but also materials where the bio-produced substances contribute unique properties and functions not existing in traditional materials. Second, engineered living materials that are formed or assembled by cells or in which cells contribute specific functions while remaining an integral part of the living composite material. We finally provide a perspective of future scientific directions of this promising area of research and discuss science policy that would be required to support research and development in this field.

A navigation guide of synthetic biology tools for Pseudomonas putida

Pseudomonas putida is a microbial chassis of huge potential for industrial and environmental biotechnology, owing to its remarkable metabolic versatility and ability to sustain difficult redox reactions and operational stresses, among other attractive characteristics. A wealth of genetic and in silico tools have been developed to enable the unravelling of its physiology and improvement of its performance. However, the rise of this microbe as a promising platform for biotechnological applications has resulted in diversification of tools and methods rather than standardization and convergence. As a consequence, multiple tools for the same purpose have been generated, whilst most of them have not been embraced by the scientific community, which has led to compartmentalization and inefficient use of resources. Inspired by this and by the substantial increase in popularity of P. putida, we aim herein to bring together and assess all currently available (wet and dry) synthetic biology tools specific for this microbe, focusing on the last 5 years. We provide information on the principles, functionality, advantages and limitations, with special focus on their use in metabolic engineering. Additionally, we compare the tool portfolio for P. putida with those for other bacterial chassis and discuss potential future directions for tool development. Therefore, this review is intended as a reference guide for experts and new 'users' of this promising chassis.

Recent Advances in Nano-Bio-Sensing Fabrication Technology for the Detection of Oral Cancer

Nanotechnology-based miniaturized devices have been a breakthrough in the pre-clinical and clinical research areas, e.g. drug delivery, personalized medicine. They have revolutionized the discovery and development of biomarker-based diagnostic devices for detection of various diseases such as tuberculosis, malaria and cancer. Nanomaterials (NMs) hold tremendous diagnostic potential due to their high surface-to-volume ratio and quantum confinement phenomenon, improving the detection limit of clinically relevant biomolecules in bio-fluids. Thus, they are helpful in the translation of bench-on platform to point-of-care (POC) screening device. The nanomaterial-based biosensor fabrication technology has also simplified and improved oral cancer (OC) or oral squamous cell carcinomas (OSCC) diagnosis. The fabrication of nano-bio sensors involves application specific modifications of NMs. The unique properties functionalized NMs have augmented their application on the nano-biosensing platform for the detection of clinically relevant biomolecules in bio-fluids. Therefore, this article summarizes the recent advancements in the process of fabrication of nano-biosensors for detection of OC.

Inhibition of growth and virulence of Vibrio cholerae by carvacrol, an essential oil component of Origanum spp

AIMS

In the age where bacterial resistance to conventional antibiotics is increasing at an alarming rate, the use of the traditional plant, herb extracts or other bioactive constituents is gradually becoming popular as an anti-virulence agent to treat pathogenic diseases. Carvacrol, a major essential oil fraction of Oregano, possesses a wide range of bioactivities. Therefore, we aimed to study the effect of sub-inhibitory concentrations of carvacrol on major virulence traits of Vibrio cholerae.

METHODS AND RESULTS

We have used in vitro as well as ex vivo models to access the anti-pathogenic role of carvacrol. We found that the sub-inhibitory concentration of carvacrol significantly repressed bacterial mucin penetrating ability. Carvacrol also reduced the adherence and fluid accumulation in the rabbit ileal loop model. Reduction in virulence is associated with the downregulated expression of tcpA, ctxB, hlyA and toxT. Furthermore, carvacrol inhibits flagellar synthesis by downregulating the expression of flrC and most of the class III genes.

CONCLUSIONS

Carvacrol exhibited anti-virulence activity against V. cholerae, which involved many events including the inhibition of mucin penetration, adhesion, reduced expression of virulence-associated genes culminating in reduced fluid accumulation.

SIGNIFICANCE AND IMPACT OF THE STUDY

These findings indicate that carvacrol possesses inhibitory activity against V. cholerae pathogenesis and might be considered as a potential bio-active therapeutic alternative to combat cholera.

Macrolide Biosensor Optimization through Cellular Substrate Sequestration

Developing and optimizing small-molecule biosensors is a central goal of synthetic biology. Here we incorporate additional cellular components to improve biosensor sensitivity by preventing target molecules from diffusing out of cells. We demonstrate that trapping erythromycin within Escherichia coli through phosphorylation increases the sensitivity of its biosensor (MphR) by approximately 10-fold. When combined with prior engineering efforts, our optimized biosensor can detect erythromycin concentrations as low as 13 nM. We show that this strategy works with a range of macrolide substrates, enabling the potential usage of our optimized system for drug development and metabolic engineering. This strategy can be extended in future studies to improve the sensitivity of other biosensors. Our findings further suggest that many naturally evolved genes involved in resistance to multiple classes of antibiotics may increase intracellular drug concentrations to modulate their own expression, acting as a form of regulatory feedback.

Corynebacterium glutamicum CrtR and Its Orthologs in Actinobacteria: Conserved Function and Application as Genetically Encoded Biosensor for Detection of Geranylgeranyl Pyrophosphate

Carotenoid biosynthesis in Corynebacteriumglutamicum is controlled by the MarR-type regulator CrtR, which represses transcription of the promoter of the crt operon (PcrtE) and of its own gene (PcrtR). Geranylgeranyl pyrophosphate (GGPP), and to a lesser extent other isoprenoid pyrophosphates, interfere with the binding of CrtR to its target DNA in vitro, suggesting they act as inducers of carotenoid biosynthesis. CrtR homologs are encoded in the genomes of many other actinobacteria. In order to determine if and to what extent the function of CrtR, as a metabolite-dependent transcriptional repressor of carotenoid biosynthesis genes responding to GGPP, is conserved among actinobacteria, five CrtR orthologs were characterized in more detail. EMSA assays showed that the CrtR orthologs from Corynebacteriumcallunae, Acidipropionibacteriumjensenii, Paenarthrobacternicotinovorans, Micrococcusluteus and Pseudarthrobacterchlorophenolicus bound to the intergenic region between their own gene and the divergently oriented gene, and that GGPP inhibited these interactions. In turn, the CrtR protein from C. glutamicum bound to DNA regions upstream of the orthologous crtR genes that contained a 15 bp DNA sequence motif conserved between the tested bacteria. Moreover, the CrtR orthologs functioned in C. glutamicum in vivo at least partially, as they complemented the defects in the pigmentation and expression of a PcrtE_gfpuv transcriptional fusion that were observed in a crtR deletion mutant to varying degrees. Subsequently, the utility of the PcrtE_gfpuv transcriptional fusion and chromosomally encoded CrtR from C. glutamicum as genetically encoded biosensor for GGPP was studied. Combined FACS and LC-MS analysis demonstrated a correlation between the sensor fluorescent signal and the intracellular GGPP concentration, and allowed us to monitor intracellular GGPP concentrations during growth and differentiate between strains engineered to accumulate GGPP at different concentrations.

A novel biodegradable film based on κ-carrageenan activated with olive leaves extract

This research focused on the development of carrageenan based biodegradable films incorporated with olive leaves extract (OLE). OLE microbial inhibition and its total phenolics (TP) were evaluated. Carrageenan films were produced by casting technique and were characterized by thickness, water vapor permeability (WVP), color, mechanical properties, and infrared spectroscopy. In order to apply as lamb meat packaging, the antimicrobial effect of the films was investigated. Results showed that OLE inhibited E. coli growth and presented excellent TP (41.40 mgGAE/g). Thicknesses of the film with OLE (CAR-OLE) were approximately 28% higher than film without OLE. Addition of OLE reduced the WVP by approximately 54%. CAR-OLE was less resistant to breakage and more flexible showing darker color. FTIR showed interaction of carrageenan with OLE. Results revealed that CAR-OLE promoted 167-fold reduction in initial count of aerobic mesophiles indicating shelf-life extension of lamb meat and promising use as antimicrobial food packaging.

Development and optimization of N-acetylneuraminic acid biosensors in Bacillus subtilis

Transcriptional factor (TF)-based metabolite-responsive biosensors are important tools for screening engineered enzymes with desired properties and for the dynamic regulation of biosynthetic pathways. However, TF-based biosensor construction is often constrained by undesired effects of TF-binding site sequence insertion on gene expression and unpredictable optimal TF expression levels. In the present study, a stepwise TF-based biosensor construction approach was developed using an N-acetylneuraminic acid (NeuAc) biosensor for Bacillus subtilis, as a case study. Specifically, 12 promoters with various strengths were selected as the first promoter library. Next, binding site sequences for the NanR were inserted into various positions of the selected promoter sequences to develop the second promoter library, resulting in 6 engineered promoters containing TF-binding site sequences (NanO), without major effects on promoter strength. NanR expression cassettes with different expression levels were further integrated to construct the biosensor library, yielding 9 NeuAc biosensors with efficient repression in the absence of NeuAc. Finally, biosensor activation was characterized by testing fold changes in expression levels of the green fluorescent protein reporter in the presence of NeuAc in vivo, which revealed 61-fold activation when NeuAc was present. The NeuAc biosensor developed in this study can be used for screening engineered enzymes for enhanced NeuAc biosynthesis in B. subtilis.

Transcription Factor Engineering for High-Throughput Strain Evolution and Organic Acid Bioproduction: A Review

Metabolic regulation of gene expression for the microbial production of fine chemicals, such as organic acids, is an important research topic in post-genomic metabolic engineering. In particular, the ability of transcription factors (TFs) to respond precisely in time and space to various small molecules, signals and stimuli from the internal and external environment is essential for metabolic pathway engineering and strain development. As a key component, TFs are used to construct many biosensors in vivo using synthetic biology methods, which can be used to monitor the concentration of intracellular metabolites in organic acid production that would otherwise remain “invisible” within the intracellular environment. TF-based biosensors also provide a high-throughput screening method for rapid strain evolution. Furthermore, TFs are important global regulators that control the expression levels of key enzymes in organic acid biosynthesis pathways, therefore determining the outcome of metabolic networks. Here we review recent advances in TF identification, engineering, and applications for metabolic engineering, with an emphasis on metabolite monitoring and high-throughput strain evolution for the organic acid bioproduction.

Development of a Biosensor for Detection of Benzoic Acid Derivatives in Saccharomyces cerevisiae

4-hydroxybenzoic acid (pHBA) is an important industrial precursor of muconic acid and liquid crystal polymers whose production is based on the petrochemical industry. In order to decrease our dependency on fossil fuels and improve sustainability, microbial engineering is a particularly appealing approach for replacing traditional chemical techniques. The optimization of microbial strains, however, is still highly constrained by the screening stage. Biosensors have helped to alleviate this problem by decreasing the screening time as well as enabling higher throughput. In this paper, we constructed a synthetic biosensor, named sBAD, consisting of a fusion of the pHBA-binding domain of HbaR from R. palustris, the LexA DNA binding domain at the N-terminus and the transactivation domain B112 at the C-terminus. The response of sBAD was tested in the presence of different benzoic acid derivatives, with cell fluorescence output measured by flow cytometry. The biosensor was found to be activated by the external addition of pHBA in the culture medium, in addition to other carboxylic acids including p-aminobenzoic acid (pABA), salicylic acid, anthranilic acid, aspirin, and benzoic acid. Furthermore, we were able to show that this biosensor could detect the in vivo production of pHBA in a genetically modified yeast strain. A good linearity was observed between the biosensor fluorescence and pHBA concentration. Thus, this biosensor would be well-suited as a high throughput screening tool to produce, via metabolic engineering, benzoic acid derivatives.

A Versatile High Throughput Screening Platform for Plant Metabolic Engineering Highlights the Major Role of ABI3 in Lipid Metabolism Regulation

Traditional functional genetic studies in crops are time consuming, complicated and cannot be readily scaled up. The reason is that mutant or transformed crops need to be generated to study the effect of gene modifications on specific traits of interest. However, many crop species have a complex genome and a long generation time. As a result, it usually takes several months to over a year to obtain desired mutants or transgenic plants, which represents a significant bottleneck in the development of new crop varieties. To overcome this major issue, we are currently establishing a versatile plant genetic screening platform, amenable to high throughput screening in almost any crop species, with a unique workflow. This platform combines protoplast transformation and fluorescence activated cell sorting. Here we show that tobacco protoplasts can accumulate high levels of lipid if transiently transformed with genes involved in lipid biosynthesis and can be sorted based on lipid content. Hence, protoplasts can be used as a predictive tool for plant lipid engineering. Using this newly established strategy, we demonstrate the major role of ABI3 in plant lipid accumulation. We anticipate that this workflow can be applied to numerous highly valuable metabolic traits other than storage lipid accumulation. This new strategy represents a significant step toward screening complex genetic libraries, in a single experiment and in a matter of days, as opposed to years by conventional means.

High-Throughput Screening of a 2-Keto-L-Gulonic Acid-Producing Gluconobacter oxydans Strain Based on Related Dehydrogenases

High-throughput screening is a powerful tool for discovering strains in the natural environment that may be suitable for target production. Herein, a novel enzyme-based high-throughput screening method was developed for rapid screening of strains overproducing 2-keto-L-gulonic acid (2-KLG). The screening method detects changes in the fluorescence of reduced nicotinamide adenine dinucleotide (NADH) at 340 nm using a microplate reader when 2-KLG is degraded by 2-KLG reductase. In this research, three different 2-KLG reductases were expressed, purified, and studied. The 2-KLG reductase from Aspergillus niger were selected as the best appropriate reductase to establishment the method for its high activity below pH 7. Using the established method, and coupled with fluorescence-activated cell sorting, we achieved a high 2-KLG-producing strain of Gluconobacter oxydans WSH-004 from soil. When cultured with D-sorbitol as the substrate, the 2-KLG yield was 2.5 g/L from 50 g/L D-sorbitol without any side products. Compared with other reported screening methods, our enzyme-based method is more efficient and accurate for obtaining high-producing 2-KLG strains, and it is also convenient and cost-effective. The method is broadly applicable for screening keto acids and other products that can be oxidized via nicotinamide adenine dinucleotide (NAD⁺) or nicotinamide adenine dinucleotide phosphate (NADP⁺).

Biosensor-based enzyme engineering approach applied to psicose biosynthesis

Bioproduction of chemical compounds is of great interest for modern industries, as it reduces their production costs and ecological impact. With the use of synthetic biology, metabolic engineering and enzyme engineering tools, the yield of production can be improved to reach mass production and cost-effectiveness expectations. In this study, we explore the bioproduction of D-psicose, also known as D-allulose, a rare non-toxic sugar and a sweetener present in nature in low amounts. D-psicose has interesting properties and seemingly the ability to fight against obesity and type 2 diabetes. We developed a biosensor-based enzyme screening approach as a tool for enzyme selection that we benchmarked with the Clostridium cellulolyticum D-psicose 3-epimerase for the production of D-psicose from D-fructose. For this purpose, we constructed and characterized seven psicose responsive biosensors based on previously uncharacterized transcription factors and either their predicted promoters or an engineered promoter. In order to standardize our system, we created the Universal Biosensor Chassis, a construct with a highly modular architecture that allows rapid engineering of any transcription factor-based biosensor. Among the seven biosensors, we chose the one displaying the most linear behavior and the highest increase in fluorescence fold change. Next, we generated a library of D-psicose 3-epimerase mutants by error-prone PCR and screened it using the biosensor to select gain of function enzyme mutants, thus demonstrating the framework's efficiency.

Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor

Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional output of metabolic activity, on the single-cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics, and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells. Therefore, drawing on the robust cell-intrinsic correlation between glycolytic flux and levels of fructose-1,6-bisphosphate (FBP), we transplanted the B. subtilis FBP-binding transcription factor CggR into yeast. With the developed biosensor, we robustly identified cell subpopulations with different FBP levels in mixed cultures, when subjected to flow cytometry and microscopy. Employing microfluidics, we were also able to assess the temporal FBP/glycolytic flux dynamics during the cell cycle. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.

Emerging molecular biology tools and strategies for engineering natural product biosynthesis

Natural products and their related derivatives play a significant role in drug discovery and have been the inspiration for the design of numerous synthetic bioactive compounds. With recent advances in molecular biology, numerous engineering tools and strategies were established to accelerate natural product synthesis in both academic and industrial settings. However, many obstacles in natural product biosynthesis still exist. For example, the native pathways are not appropriate for research or production; the key enzymes do not have enough activity; the native hosts are not suitable for high-level production. Emerging molecular biology tools and strategies have been developed to not only improve natural product titers but also generate novel bioactive compounds. In this review, we will discuss these emerging molecular biology tools and strategies at three main levels: enzyme level, pathway level, and genome level, and highlight their applications in natural product discovery and development.

Genetically encoded biosensors for lignocellulose valorization

Modern society is hugely dependent on finite oil reserves for the supply of fuels and chemicals. Moving our dependence away from these unsustainable oil-based feedstocks to renewable ones is, therefore, a critical factor towards the development of a low carbon bioeconomy. Lignin derived from biomass feedstocks offers great potential as a renewable source of aromatic compounds if methods for its effective valorization can be developed. Synthetic biology and metabolic engineering offer the potential to synergistically enable the development of cell factories with novel biosynthetic routes to valuable chemicals from these sustainable sources. Pathway design and optimization is, however, a major bottleneck due to the lack of high-throughput methods capable of screening large libraries of genetic variants and the metabolic burden associated with bioproduction. Genetically encoded biosensors can provide a solution by transducing the target metabolite concentration into detectable signals to provide high-throughput phenotypic read-outs and allow dynamic pathway regulation. The development and application of biosensors in the discovery and engineering of efficient biocatalytic processes for the degradation, conversion, and valorization of lignin are paving the way towards a sustainable and economically viable biorefinery.

A FRET-based biosensor for the quantification of glucose in culture supernatants of mL scale microbial cultivations

BACKGROUND

In most microbial cultivations D-glucose is the main carbon and energy source. However, quantification of D-glucose especially in small scale is still challenging. Therefore, we developed a FRET-based glucose biosensor, which can be applied in microbioreactor-based cultivations. This sensor consists of a glucose binding protein sandwiched between two fluorescent proteins, constituting a FRET pair. Upon D-glucose binding the sensor undergoes a conformational change which is translated into a FRET-ratio change.

RESULTS

The selected sensor shows an apparent Kd below 1.5 mM D-glucose and a very high sensitivity of up to 70% FRET-ratio change between the unbound and the glucose-saturated state. The soluble sensor was successfully applied online to monitor the glucose concentration in an Escherichia coli culture. Additionally, this sensor was utilized in an at-line process for a Corynebacterium glutamicum culture as an example for a process with cell-specific background (e.g. autofluorescence) and medium-induced quenching. Immobilization of the sensor via HaloTag® enabled purification and covalent immobilization in one step and increased the stability during application, significantly.

CONCLUSION

A FRET-based glucose sensor was used to quantify D-glucose consumption in microtiter plate based cultivations. To the best of our knowledge, this is the first method reported for online quantification of D-glucose in microtiter plate based cultivations. In comparison to D-glucose analysis via an enzymatic assay and HPLC, the sensor performed equally well, but enabled much faster measurements, which allowed to speed up microbial strain development significantly.