Development and application of a transcriptional sensor for detection of heterologous acrylic acid production in E. coli

Genetically encoded biosensors for the circular plastics bioeconomy

Current plastic production and consumption routes are unsustainable due to impact upon climate change and pollution, and therefore reform across the entire value chain is required. Biotechnology offers solutions for production from renewable feedstocks, and to aid end of life recycling/upcycling of plastics. Biology sequence/design space is complex requiring high-throughput analytical methods to facilitate the iterative optimisation, design-build, test-learn (DBTL), cycle of Synthetic Biology. Furthermore, genetic regulatory tools can enable harmonisation between biotechnological demands and the physiological constraints of the selected production host. Genetically encoded biosensors offer a solution for both requirements to facilitate the circular plastic bioeconomy. In this review we present a summary of biosensors developed to date reported to be responsive to plastic precursors/monomers. In addition, we provide a summary of the demonstrated and prospective applications of these biosensors for the construction and deconstruction of plastics. Collectively, this review provides a valuable resource of biosensor tools and enabled applications to support the development of the circular plastics bioeconomy.

A new concept of biocatalytic synthesis of acrylic monomers for obtaining water-soluble acrylic heteropolymers

Rhodococcus strains were designed as model biocatalysts (BCs) for the production of acrylic acid and mixtures of acrylic monomers consisting of acrylamide, acrylic acid, and N-alkylacrylamide (N-isopropylacrylamide). To obtain BC strains, we used, among other approaches, adaptive laboratory evolution (ALE), based on the use of the metabolic pathway of amide utilization. Whole genome sequencing of the strains obtained after ALE, as well as subsequent targeted gene disruption, identified candidate genes for three new amidases that are promising for the development of BCs for the production of acrylic acid from acrylamide. New BCs had two types of amidase activities, acrylamide-hydrolyzing and acrylamide-transferring, and by varying the ratio of these activities in BCs, it is possible to influence the ratio of monomers in the resulting mixtures. Based on these strains, a prototype of a new technological concept for the biocatalytic synthesis of acrylic monomers was developed for the production of water-soluble acrylic heteropolymers containing valuable N-alkylacrylamide units. In addition to the possibility of obtaining mixtures of different compositions, the advantages of the concept are a single starting reagent (acrylamide), more unification of processes (all processes are based on the same type of biocatalyst), and potentially greater safety for personnel and the environment compared to existing chemical technologies.

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.

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

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

Receptor-based detection of microplastics and nanoplastics: Current and future

Plastic pollution is an emerging environmental concern, gaining significant attention worldwide. They are classified into microplastics (MP; defined from 1 μm to 5 mm) and smaller nanoplastics (NP; <1 μm). NPs may pose higher ecological risks than MPs. Various microscopic and spectroscopic techniques have been used to detect MPs, and the same methods have occasionally been used for NPs. However, they are not based on receptors, which provide high specificity in most biosensing applications. Receptor-based micro/nanoplastics (MNP) detection can provide high specificity, distinguishing MNPs from the environmental samples and, more importantly, identifying the plastic types. It can also offer a low limit of detection (LOD) required for environmental screening. Such receptors are expected to detect NPs specifically at the molecular level. This review categorizes the receptors into cells, proteins, peptides, fluorescent dyes, polymers, and micro/nanostructures. Detection techniques used with these receptors are also summarized and categorized. There is plenty of room for future research to test for broader classes of environmental samples and many plastic types, to lower the LOD, and to apply the current techniques for NPs. Portable and handheld MNP detection should also be demonstrated for field use since the current demonstrations primarily utilized laboratory instruments. Detection on microfluidic platforms will also be crucial in miniaturizing and automating the assay and, eventually, collecting an extensive database to support machine learning-based classification of MNP types.

Enzyme directed evolution using genetically encodable biosensors

Directed evolution has been remarkably successful in identifying enzyme variants with new or improved properties, such as altered substrate scope or novel reactivity. Genetically encodable biosensors (GEBs), which convert the concentration of a small molecule ligand into an easily detectable output signal, have seen increasing application to enzyme directed evolution in the last decade. GEBs enable the use of high-throughput methods to assess enzyme activity of very large libraries, which can accelerate the search for variants with desirable activity. Here, we review different classes of GEBs and their properties in the context of enzyme evolution, how GEBs have been integrated into directed evolution workflows, and recent examples of enzyme evolution efforts utilizing GEBs. Finally, we discuss the advantages, challenges, and opportunities for using GEBs in the directed evolution of enzymes.

Engineering Transcription Factor XylS for Sensing Phthalic Acid and Terephthalic Acid: An Application for Enzyme Evolution

Poly(ethylene terephthalate) (PET) and phthalate esters (PAEs) are used extensively as plastics and plasticizers. Enzymatic degradation of PET and PAEs has drawn great attention in recent years; however, evolution of PET- and PAE-degrading enzymes is still a big challenge, partly because of the lack of an effective screening method to detect phthalic acid (PA) and terephthalic acid (TPA), which are the main hydrolysis products of PAEs and PET. Here, by directed evolution of a promiscuous transcription factor, XylS from Pseudomonas putida, we created two novel variants, XylS-K38R-L224Q and XylS-W88C-L224Q, that are able to bind PA and TPA and activate the downstream expression of a fluorescent reporter protein. Based on these elements, whole-cell biosensors were constructed, which enabled the fluorimetric detection of as little as 10 μM PA or TPA. A PAE hydrolase, GoEst15, was preliminarily engineered using this new biosensor, yielding a mutant GoEst15-V3 whose activity toward dibutyl phthalate (DBP) and p-nitrophenyl butyrate was enhanced 2.0- and 2.5-fold, respectively. It was shown that 96.5% DBP (5 mM) was degraded by GoEst15-V3 in 60 min, while the wild-type enzyme degraded only 55% DBP. This study provides an effective screening tool for directed evolution of PAE-/PET-degrading enzymes.

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.

Functional display of bioactive peptides on the vGFP scaffold

Grafting bioactive peptides into recipient protein scaffolds can often increase their activities by conferring enhanced stability and cellular longevity. Here, we describe use of vGFP as a novel scaffold to display peptides. vGFP comprises GFP fused to a bound high affinity Enhancer nanobody that potentiates its fluorescence. We show that peptides inserted into the linker region between GFP and the Enhancer are correctly displayed for on-target interaction, both in vitro and in live cells by pull-down, measurement of target inhibition and imaging analyses. This is further confirmed by structural studies highlighting the optimal display of a vGFP-displayed peptide bound to Mdm2, the key negative regulator of p53 that is often overexpressed in cancer. We also demonstrate a potential biosensing application of the vGFP scaffold by showing target-dependent modulation of intrinsic fluorescence. vGFP is relatively thermostable, well-expressed and inherently fluorescent. These properties make it a useful scaffold to add to the existing tool box for displaying peptides that can disrupt clinically relevant protein–protein interactions.

Microbial engineering for the production of C2-C6 organic acids

Covering: up to the end of 2020Organic acids, as building block compounds, have been widely used in food, pharmaceutical, plastic, and chemical industries. Until now, chemical synthesis is still the primary method for industrial-scale organic acid production. However, this process encounters some inevitable challenges, such as depletable petroleum resources, harsh reaction conditions and complex downstream processes. To solve these problems, microbial cell factories provide a promising approach for achieving the sustainable production of organic acids. However, some key metabolites in central carbon metabolism are strictly regulated by the network of cellular metabolism, resulting in the low productivity of organic acids. Thus, multiple metabolic engineering strategies have been developed to reprogram microbial cell factories to produce organic acids, including monocarboxylic acids, hydroxy carboxylic acids, amino carboxylic acids, dicarboxylic acids and monomeric units for polymers. These strategies mainly center on improving the catalytic efficiency of the enzymes to increase the conversion rate, balancing the multi-gene biosynthetic pathways to reduce the byproduct formation, strengthening the metabolic flux to promote the product biosynthesis, optimizing the metabolic network to adapt the environmental conditions and enhancing substrate utilization to broaden the substrate spectrum. Here, we describe the recent advances in producing C₂-C₆ organic acids by metabolic engineering strategies. In addition, we provide new insights as to when, what and how these strategies should be taken. Future challenges are also discussed in further advancing microbial engineering and establishing efficient biorefineries.

l-arginine production in Corynebacterium glutamicum: manipulation and optimization of the metabolic process

As an important semi-essential amino acid, l-arginine is extensively used in the food and pharmaceutical fields. At present, l-arginine production depends on cost-effective, green, and sustainable microbial fermentation by using a renewable carbon source. To enhance its fermentative production, various metabolic engineering strategies have been employed, which provide valid paths for reducing the cost of l-arginine production. This review summarizes recent advances in molecular biology strategies for the optimization of l-arginine-producing strains, including manipulating the principal metabolic pathway, modulating the carbon metabolic pathway, improving the intracellular biosynthesis of cofactors and energy usage, manipulating the assimilation of ammonia, improving the transportation and membrane permeability, and performing biosensor-assisted high throughput screening, providing useful insight into the current state of l-arginine production.

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.