Synthetic metabolism: metabolic engineering meets enzyme design

Spiers Memorial Lecture: Engineering biocatalysts

Enzymes are being engineered to catalyze chemical reactions for many practical applications in chemistry and biotechnology. The approaches used are surveyed in this short review, emphasizing methods for accessing reactivities not expressed by native protein scaffolds. The successful generation of completely de novo enzymes that rival the rates and selectivities of their natural counterparts highlights the potential role that designer enzymes may play in the coming years in research, industry, and medicine. Some challenges that need to be addressed to realize this ambitious dream are considered together with possible solutions.

Enzymatic synthesis of mono- and trifluorinated alanine enantiomers expands the scope of fluorine biocatalysis

Fluorinated amino acids serve as an entry point for establishing new-to-Nature chemistries in biological systems, and novel methods are needed for the selective synthesis of these building blocks. In this study, we focused on the enzymatic synthesis of fluorinated alanine enantiomers to expand fluorine biocatalysis. The alanine dehydrogenase from Vibrio proteolyticus and the diaminopimelate dehydrogenase from Symbiobacterium thermophilum were selected for in vitro production of (R)-3-fluoroalanine and (S)-3-fluoroalanine, respectively, using 3-fluoropyruvate as the substrate. Additionally, we discovered that an alanine racemase from Streptomyces lavendulae, originally selected for setting an alternative enzymatic cascade leading to the production of these non-canonical amino acids, had an unprecedented catalytic efficiency in β-elimination of fluorine from the monosubstituted fluoroalanine. The in vitro enzymatic cascade based on the dehydrogenases of V. proteolyticus and S. thermophilum included a cofactor recycling system, whereby a formate dehydrogenase from Pseudomonas sp. 101 (either native or engineered) coupled formate oxidation to NAD(P)H formation. Under these conditions, the reaction yields for (R)-3-fluoroalanine and (S)-3-fluoroalanine reached >85% on the fluorinated substrate and proceeded with complete enantiomeric excess. The selected dehydrogenases also catalyzed the conversion of trifluoropyruvate into trifluorinated alanine as a first-case example of fluorine biocatalysis with amino acids carrying a trifluoromethyl group.

A pilot oral history of plant synthetic biology

The whole field of synthetic biology (SynBio) is only about 20 years old, and plant SynBio is younger still. Nevertheless, within that short time, SynBio in general has drawn more scientific, philosophical, government, and private-sector interest than anything in biology since the recombinant DNA revolution. Plant SynBio, in particular, is now drawing more and more interest in relation to plants' potential to help solve planetary problems such as carbon capture and storage and replacing fossil fuels and feedstocks. As plant SynBio is so young and so fast-developing, we felt it was too soon to try to analyze its history. Instead, we set out to capture the essence of plant SynBio's origins and early development through interviews with 8 of the field's founders, representing 5 countries and 3 continents. We then distilled these founders' personal recollections and reflections into this review, centering the narrative on timelines for pivotal events, articles, funding programs, and quoting from interviews. We have archived the interview recordings and documented timeline entries. This work provides a resource for future historical scholarship.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

Photosynthesis 2.0: Realizing New-to-Nature CO2-Fixation to Overcome the Limits of Natural Metabolism

Synthetic biology provides opportunities to realize new-to-nature CO2-fixation metabolisms to overcome the limitations of natural photosynthesis. Two different strategies are currently being pursued: One is to realize engineered plants that feature carbon-neutral or carbon-negative (i.e., CO2-fixing) photorespiration metabolism, such as the tatronyl-CoA (TaCo) pathway, to boost CO2-uptake rates of photosynthesis between 20% and 60%. Another (arguably more radical) is to create engineered plants in which natural photosynthesis is fully replaced by an alternative CO2-fixation metabolism, such as the CETCH cycle, which carries the potential to improve CO2 uptake rates between 20% and 200%. These efforts could revolutionize plant engineering by expanding the capabilities of plant metabolism beyond the constraints of natural evolution to create highly improved crops addressing the challenges of climate change in the future.

Artificial carbon assimilation: From unnatural reactions and pathways to synthetic autotrophic systems

Synthetic biology is being increasingly used to establish novel carbon assimilation pathways and artificial autotrophic strains that can be used in low-carbon biomanufacturing. Currently, artificial pathway design has made significant progress from advocacy to practice within a relatively short span of just over ten years. However, there is still huge scope for exploration of pathway diversity, operational efficiency, and host suitability. The accelerated research process will bring greater opportunities and challenges. In this paper, we provide a comprehensive summary and interpretation of representative one-carbon assimilation pathway designs and artificial autotrophic strain construction work. In addition, we propose some feasible design solutions based on existing research results and patterns to promote the development and application of artificial autotrophy.

Engineering a synthetic energy-efficient formaldehyde assimilation cycle in Escherichia coli

One-carbon (C1) substrates, such as methanol or formate, are attractive feedstocks for circular bioeconomy. These substrates are typically converted into formaldehyde, serving as the entry point into metabolism. Here, we design an erythrulose monophosphate (EuMP) cycle for formaldehyde assimilation, leveraging a promiscuous dihydroxyacetone phosphate dependent aldolase as key enzyme. In silico modeling reveals that the cycle is highly energy-efficient, holding the potential for high bioproduct yields. Dissecting the EuMP into four modules, we use a stepwise strategy to demonstrate in vivo feasibility of the modules in E. coli sensor strains with sarcosine as formaldehyde source. From adaptive laboratory evolution for module integration, we identify key mutations enabling the accommodation of the EuMP reactions with endogenous metabolism. Overall, our study demonstrates the proof-of-concept for a highly efficient, new-to-nature formaldehyde assimilation pathway, opening a way for the development of a methylotrophic platform for a C1-fueled bioeconomy in the future.

Genetically encoded ATP and NAD(P)H biosensors: potential tools in metabolic engineering

To date, many metabolic engineering tools and strategies have been developed, including tools for cofactor engineering, which is a common strategy for bioproduct synthesis. Cofactor engineering is used for the regulation of pyridine nucleotides, including NADH/NAD+ and NADPH/NADP+, and adenosine triphosphate/adenosine diphosphate (ATP/ADP), which is crucial for maintaining redox and energy balance. However, the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP cannot be monitored in real time using traditional methods. Recently, many biosensors for detecting, monitoring, and regulating the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP have been developed. Although cofactor biosensors have been mainly developed for use in mammalian cells, the potential application of cofactor biosensors in metabolic engineering in bacterial and yeast cells has received recent attention. Coupling cofactor biosensors with genetic circuits is a promising strategy in metabolic engineering for optimizing the production of biochemicals. In this review, we focus on the development of biosensors for NADH/NAD+, NADPH/NADP+, and ATP/ADP and the potential application of these biosensors in metabolic engineering. We also provide critical perspectives, identify current research challenges, and provide guidance for future research in this promising field.

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.

Adapting enzymes to improve their functionality in plants: why and how

Synthetic biology creates new metabolic processes and improves existing ones using engineered or natural enzymes. These enzymes are often sourced from cells that differ from those in the target plant organ with respect to, e.g. redox potential, effector levels, or proteostasis machinery. Non-native enzymes may thus need to be adapted to work well in their new plant context ('plantized') even if their specificity and kinetics in vitro are adequate. Hence there are two distinct ways in which an enzyme destined for use in plants can require improvement: In catalytic properties such as substrate and product specificity, kcat, and KM; and in general compatibility with the milieu of cells that express the enzyme. Continuous directed evolution systems can deliver both types of improvement and are so far the most broadly effective way to deliver the second type. Accordingly, in this review we provide a short account of continuous evolution methods, emphasizing the yeast OrthoRep system because of its suitability for plant applications. We then cover the down-to-earth and increasingly urgent issues of which enzymes and enzyme properties can - or cannot - be improved in theory, and which in practice are the best to target for crop improvement, i.e. those that are realistically improvable and important enough to warrant deploying continuous directed evolution. We take horticultural crops as examples because of the opportunities they present and to sharpen the focus.

Synergistic investigation of natural and synthetic C1-trophic microorganisms to foster a circular carbon economy

A true circular carbon economy must upgrade waste greenhouse gases. C1-based biomanufacturing is an attractive solution, in which one carbon (C1) molecules (e.g. CO2, formate, methanol, etc.) are converted by microbial cell factories into value-added goods (i.e. food, feed, and chemicals). To render C1-based biomanufacturing cost-competitive, we must adapt microbial metabolism to perform chemical conversions at high rates and yields. To this end, the biotechnology community has undertaken two (seemingly opposing) paths: optimizing natural C1-trophic microorganisms versus engineering synthetic C1-assimilation de novo in model microorganisms. Here, we pose how these approaches can instead create synergies for strengthening the competitiveness of C1-based biomanufacturing as a whole.

Synthesis of Metabolites and Metabolite-like Compounds Using Biocatalytic Systems

Methodologies for the synthesis and purification of metabolites, which have been developed following their discovery, analysis, and structural identification, have been involved in numerous life science milestones. The renewed focus on the small molecule domain of biological cells has also created an increasing awareness of the rising gap between the metabolites identified and the metabolites which have been prepared as pure compounds. The design and engineering of resource-efficient and straightforward synthetic methodologies for the production of the diverse and numerous metabolites and metabolite-like compounds have attracted much interest. The variety of metabolic pathways in biological cells provides a wonderful blueprint for designing simplified and resource-efficient synthetic routes to desired metabolites. Therefore, biocatalytic systems have become key enabling tools for the synthesis of an increasing number of metabolites, which can then be utilized as standards, enzyme substrates, inhibitors, or other products, or for the discovery of novel biological functions.

Improving photosynthetic efficiency toward food security: Strategies, advances, and perspectives

Photosynthesis in crops and natural vegetation allows light energy to be converted into chemical energy and thus forms the foundation for almost all terrestrial trophic networks on Earth. The efficiency of photosynthetic energy conversion plays a crucial role in determining the portion of incident solar radiation that can be used to generate plant biomass throughout a growth season. Consequently, alongside the factors such as resource availability, crop management, crop selection, maintenance costs, and intrinsic yield potential, photosynthetic energy use efficiency significantly influences crop yield. Photosynthetic efficiency is relevant to sustainability and food security because it affects water use efficiency, nutrient use efficiency, and land use efficiency. This review focuses specifically on the potential for improvements in photosynthetic efficiency to drive a sustainable increase in crop yields. We discuss bypassing photorespiration, enhancing light use efficiency, harnessing natural variation in photosynthetic parameters for breeding purposes, and adopting new-to-nature approaches that show promise for achieving unprecedented gains in photosynthetic efficiency.

Integrating multiple regulations on enzyme activity: the case of phosphoenolpyruvate carboxykinases

Data on protein post-translational modifications (PTMs) increased exponentially in the last years due to the refinement of mass spectrometry techniques and the development of databases to store and share datasets. Nevertheless, these data per se do not create comprehensive biochemical knowledge. Complementary studies on protein biochemistry are necessary to fully understand the function of these PTMs at the molecular level and beyond, for example, designing rational metabolic engineering strategies to improve crops. Phosphoenolpyruvate carboxykinases (PEPCKs) are critical enzymes for plant metabolism with diverse roles in plant development and growth. Multiple lines of evidence showed the complex regulation of PEPCKs, including PTMs. Herein, we present PEPCKs as an example of the integration of combined mechanisms modulating enzyme activity and metabolic pathways. PEPCK studies strongly advanced after the production of the recombinant enzyme and the establishment of standardized biochemical assays. Finally, we discuss emerging open questions for future research and the challenges in integrating all available data into functional biochemical models.

Designing artificial pathways for improving chemical production

Metabolic engineering exploits manipulation of catalytic and regulatory elements to improve a specific function of the host cell, often the synthesis of interesting chemicals. Although naturally occurring pathways are significant resources for metabolic engineering, these pathways are frequently inefficient and suffer from a series of inherent drawbacks. Designing artificial pathways in a rational manner provides a promising alternative for chemicals production. However, the entry barrier of designing artificial pathway is relatively high, which requires researchers a comprehensive and deep understanding of physical, chemical and biological principles. On the other hand, the designed artificial pathways frequently suffer from low efficiencies, which impair their further applications in host cells. Here, we illustrate the concept and basic workflow of retrobiosynthesis in designing artificial pathways, as well as the most currently used methods including the knowledge- and computer-based approaches. Then, we discuss how to obtain desired enzymes for novel biochemistries, and how to trim the initially designed artificial pathways for further improving their functionalities. Finally, we summarize the current applications of artificial pathways from feedstocks utilization to various products synthesis, as well as our future perspectives on designing artificial pathways.

Respiratory energy demands and scope for demand expansion and destruction

Nonphotosynthetic plant metabolic processes are powered by respiratory energy, a limited resource that metabolic engineers—like plants themselves—must manage prudently.

Reshaping the 2-Pyrone Synthase Active Site for Chemoselective Biosynthesis of Polyketides

Engineering enzymes with novel reactivity and applying them in metabolic pathways to produce valuable products are quite challenging due to the intrinsic complexity of metabolic networks and the need for high in vivo catalytic efficiency. Triacetic acid lactone (TAL), naturally generated by 2-pyrone synthase (2PS), is a platform molecule that can be produced via microbial fermentation and further converted into value-added products. However, these conversions require extra synthetic steps under harsh conditions. We herein report a biocatalytic system for direct generation of TAL derivatives under mild conditions with controlled chemoselectivity by rationally engineering the 2PS active site and then rewiring the biocatalytic pathway in the metabolic network of E. coli to produce high-value products, such as kavalactone precursors, with yields up to 17 mg/L culture. Computer modeling indicates sterics and hydrogen-bond interactions play key roles in tuning the selectivity, efficiency and yield.

Enzymatic Conversion of CO2: From Natural to Artificial Utilization

Enzymatic carbon dioxide fixation is one of the most important metabolic reactions as it allows the capture of inorganic carbon from the atmosphere and its conversion into organic biomass. However, due to the often unfavorable thermodynamics and the difficulties associated with the utilization of CO₂, a gaseous substrate that is found in comparatively low concentrations in the atmosphere, such reactions remain challenging for biotechnological applications. Nature has tackled these problems by evolution of dedicated CO₂-fixing enzymes, i.e., carboxylases, and embedding them in complex metabolic pathways. Biotechnology employs such carboxylating and decarboxylating enzymes for the carboxylation of aromatic and aliphatic substrates either by embedding them into more complex reaction cascades or by shifting the reaction equilibrium via reaction engineering. This review aims to provide an overview of natural CO₂-fixing enzymes and their mechanistic similarities. We also discuss biocatalytic applications of carboxylases and decarboxylases for the synthesis of valuable products and provide a separate summary of strategies to improve the efficiency of such processes. We briefly summarize natural CO₂ fixation pathways, provide a roadmap for the design and implementation of artificial carbon fixation pathways, and highlight examples of biocatalytic cascades involving carboxylases. Additionally, we suggest that biochemical utilization of reduced CO₂ derivates, such as formate or methanol, represents a suitable alternative to direct use of CO₂ and provide several examples. Our discussion closes with a techno-economic perspective on enzymatic CO₂ fixation and its potential to reduce CO₂ emissions.

Climate change challenges, plant science solutions

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

Application of GeneCloudOmics: Transcriptomic Data Analytics for Synthetic Biology

Research in synthetic biology and metabolic engineering require a deep understanding on the function and regulation of complex pathway genes. This can be achieved through gene expression profiling which quantifies the transcriptome-wide expression under any condition, such as a cell development stage, mutant, disease, or treatment with a drug. The expression profiling is usually done using high-throughput techniques such as RNA sequencing (RNA-Seq) or microarray. Although both methods are based on different technical approaches, they provide quantitative measures of the expression levels of thousands of genes. The expression levels of the genes are compared under different conditions to identify the differentially expressed genes (DEGs), the genes with different expression levels under different conditions. DEGs, usually involving thousands in number, are then investigated using bioinformatics and data analytic tools to infer and compare their functional roles between conditions. Dealing with such large datasets, therefore, requires intensive data processing and analyses to ensure its quality and produce results that are statistically sound. Thus, there is a need for deep statistical and bioinformatics knowledge to deal with high-throughput gene expression data. This represents a barrier for wet biologists with limited computational, programming, and data analytic skills that prevent them from getting the full potential of the data. In this chapter, we present a step-by-step protocol to perform transcriptome analysis using GeneCloudOmics, a cloud-based web server that provides an end-to-end platform for high-throughput gene expression analysis.

Programmable Synthesis of Biobased Materials Using Cell-Free Systems

Motivated by the intricate mechanisms underlying biomolecule syntheses in cells that chemistry is currently unable to mimic, researchers have harnessed biological systems for manufacturing novel materials. Cell-free systems (CFSs) utilizing the bioactivity of transcriptional and translational machineries in vitro are excellent tools that allow supplementation of exogenous materials for production of innovative materials beyond the capability of natural biological systems. Herein, recent studies that have advanced the ability to expand the scope of biobased materials using CFS are summarized and approaches enabling the production of high-value materials, prototyping of genetic parts and modules, and biofunctionalization are discussed. By extending the reach of chemical and enzymatic reactions complementary to cellular materials, CFSs provide new opportunities at the interface of materials science and synthetic biology.

Synthetic anaplerotic modules for the direct synthesis of complex molecules from CO2

Anaplerosis is an essential feature of metabolism that allows the continuous operation of natural metabolic networks, such as the citric acid cycle, by constantly replenishing drained intermediates. However, this concept has not been applied to synthetic in vitro metabolic networks, thus far. Here we used anaplerotic strategies to directly access the core sequence of the CETCH cycle, a new-to-nature in vitro CO₂-fixation pathway that features several C₃-C₅ biosynthetic precursors. We drafted four different anaplerotic modules that use CO₂ to replenish the CETCH cycle's intermediates and validated our designs by producing 6-deoxyerythronolide B (6-DEB), the C₂₁-macrolide backbone of erythromycin. Our best design allowed the carbon-positive synthesis of 6-DEB via 54 enzymatic reactions in vitro at yields comparable to those with isolated 6-DEB polyketide synthase (DEBS). Our work showcases how new-to-nature anaplerotic modules can be designed and tailored to enhance and expand the synthetic capabilities of complex catalytic in vitro reaction networks.

Mechanism of Action of Flavin-Dependent Halogenases

To rationally engineer the substrate scope and selectivity of flavin-dependent halogenases (FDHs), it is essential to first understand the reaction mechanism and substrate interactions in the active site. FDHs have long been known to achieve regioselectivity through an electrophilic aromatic substitution at C7 of the natural substrate Trp, but the precise role of a key active-site Lys residue remains ambiguous. Formation of hypochlorous acid (HOCl) at the cofactor-binding site is achieved by the direct reaction of molecular oxygen and a single chloride ion with reduced FAD and flavin hydroxide, respectively. HOCl is then guided 10 Å into the halogenation active site. Lys79, located in this site, has been proposed to direct HOCl toward Trp C7 through hydrogen bonding or a direct reaction with HOCl to form an -NH₂Cl⁺ intermediate. Here, we present the most likely mechanism for halogenation based on molecular dynamics (MD) simulations and active-site density functional theory "cluster" models of FDH PrnA in complex with its native substrate l-tryptophan, hypochlorous acid, and the FAD cofactor. MD simulations with different protonation states for key active-site residues suggest that Lys79 directs HOCl through hydrogen bonding, which is confirmed by calculations of the reaction profiles for both proposed mechanisms.

Optimizing microbial networks through metabolic bypasses

Metabolism has long been considered as a relatively stiff set of biochemical reactions. This somewhat outdated and dogmatic view has been challenged over the last years, as multiple studies exposed unprecedented plasticity of metabolism by exploring rational and evolutionary modifications within the metabolic network of cell factories. Of particular importance is the emergence of metabolic bypasses, which consist of enzymatic reaction(s) that support unnatural connections between metabolic nodes. Such novel topologies can be generated through the introduction of heterologous enzymes or by upregulating native enzymes (sometimes relying on promiscuous activities thereof). Altogether, the adoption of bypasses resulted in an expansion in the capacity of the host's metabolic network, which can be harnessed for bioproduction. In this review, we discuss modifications to the canonical architecture of central carbon metabolism derived from such bypasses towards six optimization purposes: stoichiometric gain, overcoming kinetic limitations, solving thermodynamic barriers, circumventing toxic intermediates, uncoupling product synthesis from biomass formation, and altering redox cofactor specificity. The metabolic costs associated with bypass-implementation are likewise discussed, including tailoring their design towards improving bioproduction.

Synthetic Biology: Bottom-Up Assembly of Molecular Systems

The bottom-up assembly of biological and chemical components opens exciting opportunities to engineer artificial vesicular systems for applications with previously unmet requirements. The modular combination of scaffolds and functional building blocks enables the engineering of complex systems with biomimetic or new-to-nature functionalities. Inspired by the compartmentalized organization of cells and organelles, lipid or polymer vesicles are widely used as model membrane systems to investigate the translocation of solutes and the transduction of signals by membrane proteins. The bottom-up assembly and functionalization of such artificial compartments enables full control over their composition and can thus provide specifically optimized environments for synthetic biological processes. This review aims to inspire future endeavors by providing a diverse toolbox of molecular modules, engineering methodologies, and different approaches to assemble artificial vesicular systems. Important technical and practical aspects are addressed and selected applications are presented, highlighting particular achievements and limitations of the bottom-up approach. Complementing the cutting-edge technological achievements, fundamental aspects are also discussed to cater to the inherently diverse background of the target audience, which results from the interdisciplinary nature of synthetic biology. The engineering of proteins as functional modules and the use of lipids and block copolymers as scaffold modules for the assembly of functionalized vesicular systems are explored in detail. Particular emphasis is placed on ensuring the controlled assembly of these components into increasingly complex vesicular systems. Finally, all descriptions are presented in the greater context of engineering valuable synthetic biological systems for applications in biocatalysis, biosensing, bioremediation, or targeted drug delivery.

A versatile active learning workflow for optimization of genetic and metabolic networks

Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, we describe METIS, a versatile active machine learning workflow with a simple online interface for the data-driven optimization of biological targets with minimal experiments. We demonstrate our workflow for various applications, including cell-free transcription and translation, genetic circuits, and a 27-variable synthetic CO₂-fixation cycle (CETCH cycle), improving these systems between one and two orders of magnitude. For the CETCH cycle, we explore 10²⁵ conditions with only 1,000 experiments to yield the most efficient CO₂-fixation cascade described to date. Beyond optimization, our workflow also quantifies the relative importance of individual factors to the performance of a system identifying unknown interactions and bottlenecks. Overall, our workflow opens the way for convenient optimization and prototyping of genetic and metabolic networks with customizable adjustments according to user experience, experimental setup, and laboratory facilities.

Optimization of biological networks is often limited by wet lab labor and cost, and the lack of convenient computational tools. Here, aimed at democratization and standardization, the authors describe METIS, a modular and versatile active machine learning workflow with a simple online interface for the optimization of biological target functions with minimal experimental datasets.

From a Hetero- to a Methylotrophic Lifestyle: Flash Back on the Engineering Strategies to Create Synthetic Methanol-User Strains

Engineering microorganisms to grow on alternative feedstocks is crucial not just because of the indisputable biotechnological applications but also to deepen our understanding of microbial metabolism. One-carbon (C1) substrate metabolism has been the focus of extensive research for the prominent role of C1 compounds in establishing a circular bioeconomy. Methanol in particular holds great promise as it can be produced directly from greenhouse gases methane and carbon dioxide using renewable resources. Synthetic methylotrophy, i.e. introducing a non-native methanol utilization pathway into a model host, has therefore been the focus of long-time efforts and is perhaps the pinnacle of metabolic engineering. It entails completely changing a microorganism's lifestyle, from breaking up multi-carbon nutrients for growth to building C-C bonds from a single-carbon molecule to obtain all metabolites necessary to biomass formation as well as energy. The frontiers of synthetic methylotrophy have been pushed further than ever before and in this review, we outline the advances that paved the way for the more recent accomplishments. These include optimizing the host's metabolism, "copy and pasting" naturally existing methylotrophic pathways, "mixing and matching" enzymes to build new pathways, and even creating novel enzymatic functions to obtain strains that are able to grow solely on methanol. Finally, new approaches are contemplated to further advance the field and succeed in obtaining a strain that efficiently grows on methanol and allows C1-based production of added-value compounds.

Mining for allelic gold: finding genetic variation in photosynthetic traits in crops and wild relatives

Improvement of photosynthetic traits in crops to increase yield potential and crop resilience has recently become a major breeding target. Synthetic biology and genetic technologies offer unparalleled opportunities to create new genetics for photosynthetic traits driven by existing fundamental knowledge. However, large 'gene bank' collections of germplasm comprising historical collections of crop species and their relatives offer a wealth of opportunities to find novel allelic variation in the key steps of photosynthesis, to identify new mechanisms and to accelerate genetic progress in crop breeding programmes. Here we explore the available genetic resources in food and fibre crops, strategies to selectively target allelic variation in genes underpinning key photosynthetic processes, and deployment of this variation via gene editing in modern elite material.

Activating Silent Glycolysis Bypasses in Escherichia coli

All living organisms share similar reactions within their central metabolism to provide precursors for all essential building blocks and reducing power. To identify whether alternative metabolic routes of glycolysis can operate in E. coli, we complementarily employed in silico design, rational engineering, and adaptive laboratory evolution. First, we used a genome-scale model and identified two potential pathways within the metabolic network of this organism replacing canonical Embden-Meyerhof-Parnas (EMP) glycolysis to convert phosphosugars into organic acids. One of these glycolytic routes proceeds via methylglyoxal and the other via serine biosynthesis and degradation. Then, we implemented both pathways in E. coli strains harboring defective EMP glycolysis. Surprisingly, the pathway via methylglyoxal seemed to immediately operate in a triosephosphate isomerase deletion strain cultivated on glycerol. By contrast, in a phosphoglycerate kinase deletion strain, the overexpression of methylglyoxal synthase was necessary to restore growth of the strain. Furthermore, we engineered the "serine shunt" which converts 3-phosphoglycerate via serine biosynthesis and degradation to pyruvate, bypassing an enolase deletion. Finally, to explore which of these alternatives would emerge by natural selection, we performed an adaptive laboratory evolution study using an enolase deletion strain. Our experiments suggest that the evolved mutants use the serine shunt. Our study reveals the flexible repurposing of metabolic pathways to create new metabolite links and rewire central metabolism.

Single-particle combinatorial multiplexed liposome fusion mediated by DNA

Combinatorial high-throughput methodologies are central for both screening and discovery in synthetic biochemistry and biomedical sciences. They are, however, often reliant on large-scale analyses and thus limited by a long running time and excessive materials cost. We here present a single-particle combinatorial multiplexed liposome fusion mediated by DNA for parallelized multistep and non-deterministic fusion of individual subattolitre nanocontainers. We observed directly the efficient (>93%) and leakage free stochastic fusion sequences for arrays of surface-tethered target liposomes with six freely diffusing populations of cargo liposomes, each functionalized with individual lipidated single-stranded DNA and fluorescently barcoded by a distinct ratio of chromophores. The stochastic fusion resulted in a distinct permutation of fusion sequences for each autonomous nanocontainer. Real-time total internal reflection imaging allowed the direct observation of >16,000 fusions and 566 distinct fusion sequences accurately classified using machine learning. The high-density arrays of surface-tethered target nanocontainers (~42,000 containers per mm²) offers entire combinatorial multiplex screens using only picograms of material.

Metabolic stimulation-elicited transcriptional responses and biosynthesis of acylated triterpenoids precursors in the medicinal plant Helicteres angustifolia

BACKGROUND

Helicteres angustifolia has long been used in Chinese traditional medicine. It has multiple pharmacological benefits, including anti-inflammatory, anti-viral and anti-tumor effects. Its main active chemicals include betulinic acid, oleanolic acid, helicteric acid, helicterilic acid, and other triterpenoid saponins. It is worth noting that some acylated triterpenoids, such as helicteric acid and helicterilic acid, are characteristic components of Helicteres and are relatively rare among other plants. However, reliance on natural plants as the only sources of these is not enough to meet the market requirement. Therefore, the engineering of its metabolic pathway is of high research value for enhancing the production of secondary metabolites. Unfortunately, there are few studies on the biosynthetic pathways of triterpenoids in H. angustifolia, hindering its further investigation.

RESULTS

Here, the RNAs of different groups treated by metabolic stimulation were sequenced with an Illumina high-throughput sequencing platform, resulting in 121 gigabases of data. A total of 424,824 unigenes were obtained after the trimming and assembly of the raw data, and 22,430 unigenes were determined to be differentially expressed. In addition, three oxidosqualene cyclases (OSCs) and four Cytochrome P450 (CYP450s) were screened, of which one OSC (HaOSC1) and one CYP450 (HaCYPi3) achieved functional verification, suggesting that they could catalyze the production of lupeol and oleanolic acid, respectively.

CONCLUSION

In general, the transcriptomic data of H. angustifolia was first reported and analyzed to study functional genes. Three OSCs, four CYP450s and three acyltransferases were screened out as candidate genes to perform further functional verification, which demonstrated that HaOSC1 and HaCYPi3 encode for lupeol synthase and β-amyrin oxidase, which produce corresponding products of lupeol and oleanolic acid, respectively. Their successful identification revealed pivotal steps in the biosynthesis of acylated triterpenoids precursors, which laid a foundation for further study on acylated triterpenoids. Overall, these results shed light on the regulation of acylated triterpenoids biosynthesis.

Kinetic characterization and modelling of sequentially entrapped enzymes in 3D-printed PMMA microfluidic reactors for the synthesis of amorphadiene via the isopentenol utilization pathway

The development of cascade cell-free systems reduces the requirement for extensive metabolic engineering and optimization to increase in vivo pathway flux. For continuous operation and increased stability, direct enzyme entrapment during reactor fabrication by 3D-printing allows for simple immobilization procedures without enzyme-specific optimization. In this work, the isopentenol utilization pathway (IUP) was selected for the synthesis of amorphadiene, an anti-malaria drug precursor, using a 3D-printed, sequentially immobilized, microfluidic reactor. As an initial proof-of-concept, alkaline phosphatase (ALP) was entrapped in a poly(methyl methacrylate) (PMMA)-based matrix during stereolithographic 3D-printing and was kinetically characterized. No significant shift of the kinetically modelled substrate binding affinity was observed during immobilization and continuous operation of an entrapped ALP microfluidic reactor displayed high stability. The IUP enzymes retained moderate activity during entrapment (6.6-9.6 %) relative to the free enzyme solutions, however the sequentially immobilized IUP microfluidic reactor was severely limited by low pathway flux due to the use of stereolithographic 3D-printing which significantly diluted enzyme concentrations for printing. Although this study demonstrated the use of additive manufacturing for the synthesis of amorphadiene using a complex five-enzyme cascade microfluidic reactor, stereolithographic enzyme entrapment remains limited in scope and dependent on advancements to additive manufacturing technologies. This article is protected by copyright. All rights reserved.

Two-Tiered Selection and Screening Strategy to Increase Functional Enzyme Production in E. coli

Development of recombinant enzymes as industrial biocatalysts or metabolic pathway elements requires soluble expression of active protein. Here we present a two-step strategy, combining a directed evolution selection with an enzyme activity screen, to increase the soluble production of enzymes in the cytoplasm of E. coli. The directed evolution component relies on the innate quality control of the twin-arginine translocation pathway coupled with antibiotic selection to isolate point mutations that promote intracellular solubility. A secondary screen is applied to ensure the solubility enhancement has not compromised enzyme activity. This strategy has been successfully applied to increase the soluble production of a fungal endocellulase by 30-fold in E. coli without change in enzyme specific activity through two rounds of directed evolution.

Combining novel technologies with interdisciplinary basic research to enhance horticultural crops

Horticultural crops mainly include fruits, vegetables, ornamental trees and flowers, and tea trees (Melaleuca alternifolia). They produce a variety of nutrients for the daily human diet in addition to the nutrition provided by staple crops, and some of them additionally possess ornamental and medicinal features. As such, horticultural crops make unique and important contributions to both food security and a colorful lifestyle. Under the current climate change scenario, the growing population and limited arable land means that agriculture, and especially horticulture, has been facing unprecedented challenges to meet the diverse demands of human daily life. Breeding horticultural crops with high quality and adaptability and establishing an effective system that combines cultivation, post-harvest handling, and sales becomes increasingly imperative for horticultural production. This review discusses characteristic and recent research highlights in horticultural crops, focusing on the breeding of quality traits and the mechanisms that underpin them. It additionally addresses challenges and potential solutions in horticultural production and post-harvest practices. Finally, we provide a prospective as to how emerging technologies can be implemented alongside interdisciplinary basic research to enhance our understanding and exploitation of horticultural crops.

Synthetic metabolism for biohalogenation

The pressing need for novel bioproduction approaches faces a limitation in the number and type of molecules accessed through synthetic biology. Halogenation is widely used for tuning physicochemical properties of molecules and polymers, but traditional halogenation chemistry often lacks specificity and generates harmful by-products. Here, we pose that deploying synthetic metabolism tailored for biohalogenation represents an unique opportunity towards economically attractive and environmentally friendly organohalide production. On this background, we discuss growth-coupled selection of functional metabolic modules that harness the rich repertoire of biosynthetic and biodegradation capabilities of environmental bacteria for in vivo biohalogenation. By rationally combining these approaches, the chemical landscape of living cells can accommodate bioproduction of added-value organohalides which, as of today, are obtained by traditional chemistry.

Biological Parts for Plant Biodesign to Enhance Land-Based Carbon Dioxide Removal

A grand challenge facing society is climate change caused mainly by rising CO2 concentration in Earth's atmosphere. Terrestrial plants are linchpins in global carbon cycling, with a unique capability of capturing CO2 via photosynthesis and translocating captured carbon to stems, roots, and soils for long-term storage. However, many researchers postulate that existing land plants cannot meet the ambitious requirement for CO2 removal to mitigate climate change in the future due to low photosynthetic efficiency, limited carbon allocation for long-term storage, and low suitability for the bioeconomy. To address these limitations, there is an urgent need for genetic improvement of existing plants or construction of novel plant systems through biosystems design (or biodesign). Here, we summarize validated biological parts (e.g., protein-encoding genes and noncoding RNAs) for biological engineering of carbon dioxide removal (CDR) traits in terrestrial plants to accelerate land-based decarbonization in bioenergy plantations and agricultural settings and promote a vibrant bioeconomy. Specifically, we first summarize the framework of plant-based CDR (e.g., CO2 capture, translocation, storage, and conversion to value-added products). Then, we highlight some representative biological parts, with experimental evidence, in this framework. Finally, we discuss challenges and strategies for the identification and curation of biological parts for CDR engineering in plants.

SCONES: Self-Consistent Neural Network for Protein Stability Prediction Upon Mutation

Engineering proteins to have desired properties by mutating amino acids at specific sites is commonplace. Such engineered proteins must be stable to function. Experimental methods used to determine stability at throughputs required to scan the protein sequence space thoroughly are laborious. To this end, many machine learning based methods have been developed to predict thermodynamic stability changes upon mutation. These methods have been evaluated for symmetric consistency by testing with hypothetical reverse mutations. In this work, we propose transitive data augmentation, evaluating transitive consistency with our new S^transitive data set, and a new machine learning based method, the first of its kind, that incorporates both symmetric and transitive properties into the architecture. Our method, called SCONES, is an interpretable neural network that predicts small relative protein stability changes for missense mutations that do not significantly alter the structure. It estimates a residue's contributions toward protein stability (ΔG) in its local structural environment, and the difference between independently predicted contributions of the reference and mutant residues is reported as ΔΔG. We show that this self-consistent machine learning architecture is immune to many common biases in data sets, relies less on data than existing methods, is robust to overfitting, and can explain a substantial portion of the variance in experimental data.

Utilization of a Wheat Sidestream for 5-Aminovalerate Production in Corynebacterium glutamicum

Production of plastics from petroleum-based raw materials extensively contributes to global pollution and CO2 emissions. Biotechnological production of functionalized monomers can reduce the environmental impact, in particular when using industrial sidestreams as feedstocks. Corynebacterium glutamicum, which is used in the million-ton-scale amino acid production, has been engineered for sustainable production of polyamide monomers. In this study, wheat sidestream concentrate (WSC) from industrial starch production was utilized for production of l-lysine-derived bifunctional monomers using metabolically engineered C. glutamicum strains. Growth of C. glutamicum on WSC was observed and could be improved by hydrolysis of WSC. By heterologous expression of the genes xylA Xc B Cg (xylA from Xanthomonas campestris) and araBAD Ec from E. coli, xylose, and arabinose in WSC hydrolysate (WSCH), in addition to glucose, could be consumed, and production of l-lysine could be increased. WSCH-based production of cadaverine and 5-aminovalerate (5AVA) was enabled. To this end, the lysine decarboxylase gene ldcC Ec from E. coli was expressed alone or for conversion to 5AVA cascaded either with putrescine transaminase and dehydrogenase genes patDA Ec from E. coli or with putrescine oxidase gene puo Rq from Rhodococcus qingshengii and patD Ec . Deletion of the l-glutamate dehydrogenase-encoding gene gdh reduced formation of l-glutamate as a side product for strains with either of the cascades. Since the former cascade (ldcC Ec -patDA Ec ) yields l-glutamate, 5AVA production is coupled to growth by flux enforcement resulting in the highest 5AVA titer obtained with WSCH-based media.

Getting the Most Out of Enzyme Cascades: Strategies to Optimize In Vitro Multi-Enzymatic Reactions

In vitro enzyme cascades possess great benefits, such as their synthetic capabilities for complex molecules, no need for intermediate isolation, and the shift of unfavorable equilibria towards the products. Their performance, however, can be impaired by, for example, destabilizing or inhibitory interactions between the cascade components or incongruous reaction conditions. The optimization of such systems is therefore often inevitable but not an easy task. Many parameters such as the design of the synthesis route, the choice of enzymes, reaction conditions, or process design can alter the performance of an in vitro enzymatic cascade. Many strategies to tackle this complex task exist, ranging from experimental to in silico approaches and combinations of both. This review collates examples of various optimization strategies and their success. The feasibility of optimization goals, the influence of certain parameters and the usage of algorithm-based optimizations are discussed.

Cell-free chemoenzymatic starch synthesis from carbon dioxide

[Figure: see text].

Growth-coupled selection of synthetic modules to accelerate cell factory development

Synthetic biology has brought about a conceptual shift in our ability to redesign microbial metabolic networks. Combining metabolic pathway-modularization with growth-coupled selection schemes is a powerful tool that enables deep rewiring of the cell factories’ biochemistry for rational bioproduction.

In-Depth Computational Analysis of Natural and Artificial Carbon Fixation Pathways

In the recent years, engineering new-to-nature CO2- and C1-fixing metabolic pathways made a leap forward. New, artificial pathways promise higher yields and activity than natural ones like the Calvin-Benson-Bassham (CBB) cycle. The question remains how to best predict their in vivo performance and what actually makes one pathway "better" than another. In this context, we explore aerobic carbon fixation pathways by a computational approach and compare them based on their specific activity and yield on methanol, formate, and CO2/H2 considering the kinetics and thermodynamics of the reactions. Besides pathways found in nature or implemented in the laboratory, this included two completely new cycles with favorable features: the reductive citramalyl-CoA cycle and the 2-hydroxyglutarate-reverse tricarboxylic acid cycle. A comprehensive kinetic data set was collected for all enzymes of all pathways, and missing kinetic data were sampled with the Parameter Balancing algorithm. Kinetic and thermodynamic data were fed to the Enzyme Cost Minimization algorithm to check for respective inconsistencies and calculate pathway-specific activities. The specific activities of the reductive glycine pathway, the CETCH cycle, and the new reductive citramalyl-CoA cycle were predicted to match the best natural cycles with superior product-substrate yield. However, the CBB cycle performed better in terms of activity compared to the alternative pathways than previously thought. We make an argument that stoichiometric yield is likely not the most important design criterion of the CBB cycle. Still, alternative carbon fixation pathways were paretooptimal for specific activity and product-substrate yield in simulations with C1 substrates and CO2/H2 and therefore hold great potential for future applications in Industrial Biotechnology and Synthetic Biology.

GeneReg: a constraint-based approach for design of feasible metabolic engineering strategies at the gene level

Motivation

Large-scale metabolic models are widely used to design metabolic engineering strategies for diverse biotechnological applications. However, the existing computational approaches focus on alteration of reaction fluxes and often neglect the manipulations of gene expression to implement these strategies.

Results

Here, we find that the association of genes with multiple reactions leads to infeasibility of engineering strategies at the flux level, since they require contradicting manipulations of gene expression. Moreover, we identify that all of the existing approaches to design gene knockout strategies do not ensure that the resulting design may also require other gene alterations, such as up- or downregulations, to match the desired flux distribution. To address these issues, we propose a constraint-based approach, termed GeneReg, that facilitates the design of feasible metabolic engineering strategies at the gene level and that is readily applicable to large-scale metabolic networks. We show that GeneReg can identify feasible strategies to overproduce ethanol in Escherichia coli and lactate in Saccharomyces cerevisiae, but overproduction of the TCA cycle intermediates is not feasible in five organisms used as cell factories under default growth conditions. Therefore, GeneReg points at the need to couple gene regulation and metabolism to design rational metabolic engineering strategies.

Availability and implementation

https://github.com/MonaRazaghi/GeneReg

Supplementary information

Supplementary data are available at Bioinformatics online.

Bio-conversion of CO2 into biofuels and other value-added chemicals via metabolic engineering

Carbon dioxide (CO₂) occurs naturally in the atmosphere as a trace gas, which is produced naturally as well as by anthropogenic activities. CO₂ is a readily available source of carbon that in principle can be used as a raw material for the synthesis of valuable products. The autotrophic organisms are naturally equipped to convert CO₂ into biomass by obtaining energy from sunlight or inorganic electron donors. This autotrophic CO₂ fixation has been exploited in biotechnology, and microbial cell factories have been metabolically engineered to convert CO₂ into biofuels and other value-added bio-based chemicals. A variety of metabolic engineering efforts for CO₂ fixation ranging from basic copy, paste, and fine-tuning approaches to engineering and testing of novel synthetic CO₂ fixing pathways have been demonstrated. In this paper, we review the current advances and innovations in metabolic engineering for bio-conversion of CO₂ into bio biofuels and other value-added bio-based chemicals.