Systematic design and in vitro validation of novel one-carbon assimilation pathways

Novel aspects of ethylene glycol catabolism

Ethylene glycol (EG) is an industrially important two-carbon diol used as a solvent, antifreeze agent, and building block of polymers such as poly(ethylene terephthalate) (PET). Recently, the use of EG as a starting material for the production of bio-fuels or bio-chemicals is gaining attention as a sustainable process since EG can be derived from materials not competing with human food stocks including CO2, syngas, lignocellulolytic biomass, and PET waste. In order to design and construct microbial process for the conversion of EG to value-added chemicals, microbes capable of catabolizing EG such as Escherichia coli, Pseudomonas putida, Rhodococcus jostii, Ideonella sakaiensis, Paracoccus denitrificans, and Acetobacterium woodii are candidates of chassis for the construction of synthetic pathways. In this mini-review, we describe EG catabolic pathways and catabolic enzymes in these microbes, and further review recent advances in microbial conversion of EG to value-added chemicals by means of metabolic engineering. KEY POINTS: • Ethylene glycol is a potential next-generation feedstock for sustainable industry. • Microbial conversion of ethylene glycol to value-added chemicals is gaining attention. • Ethylene glycol-utilizing microbes are useful as chassis for synthetic pathways.

Unlocking the formate utilization of wild-type Yarrowia lipolytica through adaptive laboratory evolution

Synthetic biology is contributing to the advancement of the global net-negative carbon economy, with emphasis on formate as a member of the one-carbon substrate garnering substantial attention. In this study, we employed base editing tools to facilitate adaptive evolution, achieving a formate tolerance of Yarrowia lipolytica to 1 M within 2 months. This effort resulted in two mutant strains, designated as M25-70 and M25-14, both exhibiting significantly enhanced formate utilization capabilities. Transcriptomic analysis revealed the upregulation of nine endogenous genes encoding formate dehydrogenases when cultivated utilizing formate as the sole carbon source. Furthermore, we uncovered the pivotal role of the glyoxylate and threonine-based serine pathway in enhancing glycine supply to promote formate assimilation. The full potential of Y. lipolytica to tolerate and utilize formate establishing the foundation for pyruvate carboxylase-based carbon sequestration pathways. Importantly, this study highlights the existence of a natural formate metabolic pathway in Y. lipolytica.

Creating new-to-nature carbon fixation: A guide

Synthetic biology aims at designing new biological functions from first principles. These new designs allow to expand the natural solution space and overcome the limitations of naturally evolved systems. One example is synthetic CO2-fixation pathways that promise to provide more efficient ways for the capture and conversion of CO2 than natural pathways, such as the Calvin Benson Bassham (CBB) cycle of photosynthesis. In this review, we provide a practical guideline for the design and realization of such new-to-nature CO2-fixation pathways. We introduce the concept of "synthetic CO2-fixation", and give a general overview over the enzymology and topology of synthetic pathways, before we derive general principles for their design from their eight naturally evolved analogs. We provide a comprehensive summary of synthetic carbon-assimilation pathways and derive a step-by-step, practical guide from the theoretical design to their practical implementation, before ending with an outlook on new developments in the field.

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.

Enabling pathway design by multiplex experimentation and machine learning

The remarkable metabolic diversity observed in nature has provided a foundation for sustainable production of a wide array of valuable molecules. However, transferring the biosynthetic pathway to the desired host often runs into inherent failures that arise from intermediate accumulation and reduced flux resulting from competing pathways within the host cell. Moreover, the conventional trial and error methods utilized in pathway optimization struggle to fully grasp the intricacies of installed pathways, leading to time-consuming and labor-intensive experiments, ultimately resulting in suboptimal yields. Considering these obstacles, there is a pressing need to explore the enzyme expression landscape and identify the optimal pathway configuration for enhanced production of molecules. This review delves into recent advancements in pathway engineering, with a focus on multiplex experimentation and machine learning techniques. These approaches play a pivotal role in overcoming the limitations of traditional methods, enabling exploration of a broader design space and increasing the likelihood of discovering optimal pathway configurations for enhanced production of molecules. We discuss several tools and strategies for pathway design, construction, and optimization for sustainable and cost-effective microbial production of molecules ranging from bulk to fine chemicals. We also highlight major successes in academia and industry through compelling case studies.

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.

Improving pathway prediction accuracy of constraints-based metabolic network models by treating enzymes as microcompartments

Metabolic network models have become increasingly precise and accurate as the most widespread and practical digital representations of living cells. The prediction functions were significantly expanded by integrating cellular resources and abiotic constraints in recent years. However, if unreasonable modeling methods were adopted due to a lack of consideration of biological knowledge, the conflicts between stoichiometric and other constraints, such as thermodynamic feasibility and enzyme resource availability, would lead to distorted predictions. In this work, we investigated a prediction anomaly of EcoETM, a constraints-based metabolic network model, and introduced the idea of enzyme compartmentalization into the analysis process. Through rational combination of reactions, we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites. This allowed us to correct the pathway structures of l-serine and l-tryptophan. A specific analysis explains the application method of the EcoETM-like model and demonstrates its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments. Notably, this work also reveals the trade-off between product yield and thermodynamic feasibility. Our work is of great value for the structural improvement of constraints-based models.

Next-generation feedstocks methanol and ethylene glycol and their potential in industrial biotechnology

Microbial fermentation processes are expected to play an important role in reducing dependence on fossil-based raw materials for the production of everyday chemicals. In order to meet the growing demand for biotechnological products in the future, alternative carbon sources that do not compete with human nutrition must be exploited. The chemical conversion of the industrially emitted greenhouse gas CO2 into microbially utilizable platform chemicals such as methanol represents a sustainable strategy for the utilization of an abundant carbon source and has attracted enormous scientific interest in recent years. A relatively new approach is the microbial synthesis of products from the C2-compound ethylene glycol, which can also be synthesized from CO2 and non-edible biomass and, in addition, can be recovered from plastic waste. Here we summarize the main chemical routes for the synthesis of methanol and ethylene glycol from sustainable resources and give an overview of recent metabolic engineering work for establishing natural and synthetic microbial assimilation pathways. The different metabolic routes for C1 and C2 alcohol-dependent bioconversions were compared in terms of their theoretical maximum yields and their oxygen requirements for a wide range of value-added products. Assessment of the process engineering challenges for methanol and ethylene glycol-based fermentations underscores the theoretical advantages of new synthetic metabolic routes and advocates greater consideration of ethylene glycol, a C2 substrate that has received comparatively little attention to date.

Reconstruction and metabolic profiling of the genome-scale metabolic network model of Pseudomonas stutzeri A1501

Pseudomonas stutzeri A1501 is a non-fluorescent denitrifying bacteria that belongs to the gram-negative bacterial group. As a prominent strain in the fields of agriculture and bioengineering, there is still a lack of comprehensive understanding regarding its metabolic capabilities, specifically in terms of central metabolism and substrate utilization. Therefore, further exploration and extensive studies are required to gain a detailed insight into these aspects. This study reconstructed a genome-scale metabolic network model for P. stutzeri A1501 and conducted extensive curations, including correcting energy generation cycles, respiratory chains, and biomass composition. The final model, iQY1018, was successfully developed, covering more genes and reactions and having higher prediction accuracy compared with the previously published model iPB890. The substrate utilization ability of 71 carbon sources was investigated by BIOLOG experiment and was utilized to validate the model quality. The model prediction accuracy of substrate utilization for P. stutzeri A1501 reached 90 %. The model analysis revealed its new ability in central metabolism and predicted that the strain is a suitable chassis for the production of Acetyl CoA-derived products. This work provides an updated, high-quality model of P. stutzeri A1501for further research and will further enhance our understanding of the metabolic capabilities.

Design and Construction of Artificial Biological Systems for One-Carbon Utilization

The third-generation (3G) biorefinery aims to use microbial cell factories or enzymatic systems to synthesize value-added chemicals from one-carbon (C1) sources, such as CO2, formate, and methanol, fueled by renewable energies like light and electricity. This promising technology represents an important step toward sustainable development, which can help address some of the most pressing environmental challenges faced by modern society. However, to establish processes competitive with the petroleum industry, it is crucial to determine the most viable pathways for C1 utilization and productivity and yield of the target products. In this review, we discuss the progresses that have been made in constructing artificial biological systems for 3G biorefineries in the last 10 years. Specifically, we highlight the representative works on the engineering of artificial autotrophic microorganisms, tandem enzymatic systems, and chemo-bio hybrid systems for C1 utilization. We also prospect the revolutionary impact of these developments on biotechnology. By harnessing the power of 3G biorefinery, scientists are establishing a new frontier that could potentially revolutionize our approach to industrial production and pave the way for a more sustainable future.

Methanol-based biomanufacturing of fuels and chemicals using native and synthetic methylotrophs

Methanol has recently gained significant attention as a potential carbon substrate for the production of fuels and chemicals, owing to its high degree of reduction, abundance, and low price. Native methylotrophic yeasts and bacteria have been investigated for the production of fuels and chemicals. Alternatively, synthetic methylotrophic strains are also being developed by reconstructing methanol utilization pathways in model microorganisms, such as Escherichia coli. Owing to the complex metabolic pathways, limited availability of genetic tools, and methanol/formaldehyde toxicity, the high-level production of target products for industrial applications are still under development to satisfy commercial feasibility. This article reviews the production of biofuels and chemicals by native and synthetic methylotrophic microorganisms. It also highlights the advantages and limitations of both types of methylotrophs and provides an overview of ways to improve their efficiency for the production of fuels and chemicals from methanol.

Achieving net zero CO2 emission in the biobased production of reduced platform chemicals using defined co-feeding of methanol

Next-generation bioprocesses of a future bio-based economy will rely on a flexible mix of readily available feedstocks. Renewable energy can be used to generate sustainable CO₂-derived substrates. Metabolic engineering already enables the functional implementation of different pathways for the assimilation of C1 substrates in various microorganisms. In addition to feedstocks, the benchmark for all future bioprocesses will be sustainability, including the avoidance of CO₂ emissions. Here we review recent advances in the utilization of C1-compounds from different perspectives, considering both strain and bioprocess engineering technologies. In particular, we evaluate methanol as a co-feed for enabling the CO₂ emission-free production of acetyl-CoA-derived compounds. The possible metabolic strategies are analyzed using stoichiometric modeling combined with thermodynamic analysis and prospects for industrial-scale implementation are discussed.

Exploring the Feasibility of Cell-Free Synthesis as a Platform for Polyhydroxyalkanoate (PHA) Production: Opportunities and Challenges

The extensive utilization of traditional petroleum-based plastics has resulted in significant damage to the natural environment and ecological systems, highlighting the urgent need for sustainable alternatives. Polyhydroxyalkanoates (PHAs) have emerged as promising bioplastics that can compete with petroleum-based plastics. However, their production technology currently faces several challenges, primarily focused on high costs. Cell-free biotechnologies have shown significant potential for PHA production; however, despite recent progress, several challenges still need to be overcome. In this review, we focus on the status of cell-free PHA synthesis and compare it with microbial cell-based PHA synthesis in terms of advantages and drawbacks. Finally, we present prospects for the development of cell-free PHA synthesis.

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.

Construction of a synthetic metabolic pathway for biosynthesis of 2,4-dihydroxybutyric acid from ethylene glycol

Ethylene glycol is an attractive two-carbon alcohol substrate for biochemical product synthesis as it can be derived from CO2 or syngas at no sacrifice to human food stocks. Here, we disclose a five-step synthetic metabolic pathway enabling the carbon-conserving biosynthesis of the versatile platform molecule 2,4-dihydroxybutyric acid (DHB) from this compound. The linear pathway chains ethylene glycol dehydrogenase, D-threose aldolase, D-threose dehydrogenase, D-threono-1,4-lactonase, D-threonate dehydratase and 2-oxo-4-hydroxybutyrate reductase enzyme activities in succession. We screen candidate enzymes with D-threose dehydrogenase and D-threonate dehydratase activities on cognate substrates with conserved carbon-centre stereochemistry. Lastly, we show the functionality of the pathway by its expression in an Escherichia coli strain and production of 1 g L-1 and 0.8 g L-1 DHB from, respectively, glycolaldehyde or ethylene glycol.

Pickaxe: a Python library for the prediction of novel metabolic reactions

BACKGROUND

Biochemical reaction prediction tools leverage enzymatic promiscuity rules to generate reaction networks containing novel compounds and reactions. The resulting reaction networks can be used for multiple applications such as designing novel biosynthetic pathways and annotating untargeted metabolomics data. It is vital for these tools to provide a robust, user-friendly method to generate networks for a given application. However, existing tools lack the flexibility to easily generate networks that are tailor-fit for a user's application due to lack of exhaustive reaction rules, restriction to pre-computed networks, and difficulty in using the software due to lack of documentation.

RESULTS

Here we present Pickaxe, an open-source, flexible software that provides a user-friendly method to generate novel reaction networks. This software iteratively applies reaction rules to a set of metabolites to generate novel reactions. Users can select rules from the prepackaged JN1224min ruleset, derived from MetaCyc, or define their own custom rules. Additionally, filters are provided which allow for the pruning of a network on-the-fly based on compound and reaction properties. The filters include chemical similarity to target molecules, metabolomics, thermodynamics, and reaction feasibility filters. Example applications are given to highlight the capabilities of Pickaxe: the expansion of common biological databases with novel reactions, the generation of industrially useful chemicals from a yeast metabolome database, and the annotation of untargeted metabolomics peaks from an E. coli dataset.

CONCLUSION

Pickaxe predicts novel metabolic reactions and compounds, which can be used for a variety of applications. This software is open-source and available as part of the MINE Database python package ( https://pypi.org/project/minedatabase/ ) or on GitHub ( https://github.com/tyo-nu/MINE-Database ). Documentation and examples can be found on Read the Docs ( https://mine-database.readthedocs.io/en/latest/ ). Through its documentation, pre-packaged features, and customizable nature, Pickaxe allows users to generate novel reaction networks tailored to their application.

In vivo implementation of a synthetic metabolic pathway for the carbon-conserving conversion of glycolaldehyde to acetyl-CoA

Ethylene glycol (EG) derived from plastic waste or CO₂ can serve as a substrate for microbial production of value-added chemicals. Assimilation of EG proceeds though the characteristic intermediate glycolaldehyde (GA). However, natural metabolic pathways for GA assimilation have low carbon efficiency when producing the metabolic precursor acetyl-CoA. In alternative, the reaction sequence catalyzed by EG dehydrogenase, d-arabinose 5-phosphate aldolase, d-arabinose 5-phosphate isomerase, d-ribulose 5-phosphate 3-epimerase (Rpe), d-xylulose 5-phosphate phosphoketolase, and phosphate acetyltransferase may enable the conversion of EG into acetyl-CoA without carbon loss. We investigated the metabolic requirements for in vivo function of this pathway in Escherichia coli by (over)expressing constituting enzymes in different combinations. Using ¹³C-tracer experiments, we first examined the conversion of EG to acetate via the synthetic reaction sequence and showed that, in addition to heterologous phosphoketolase, overexpression of all native enzymes except Rpe was required for the pathway to function. Since acetyl-CoA could not be reliably quantified by our LC/MS-method, the distribution of isotopologues in mevalonate, a stable metabolite that is exclusively derived from this intermediate, was used to probe the contribution of the synthetic pathway to biosynthesis of acetyl-CoA. We detected strong incorporation of ¹³C carbon derived from labeled GA in all intermediates of the synthetic pathway. In presence of unlabeled co-substrate glycerol, 12.4% of the mevalonate (and therefore acetyl-CoA) was derived from GA. The contribution of the synthetic pathway to acetyl-CoA production was further increased to 16.1% by the additional expression of the native phosphate acyltransferase enzyme. Finally, we demonstrated that conversion of EG to mevalonate was feasible albeit at currently extremely small yields.

Biomanufacturing by In Vitro Biotransformation (ivBT) Using Purified Cascade Multi-enzymes

In vitro biotransformation (ivBT) refers to the use of an artificial biological reaction system that employs purified enzymes for the one-pot conversion of low-cost materials into biocommodities such as ethanol, organic acids, and amino acids. Unshackled from cell growth and metabolism, ivBT exhibits distinct advantages compared with metabolic engineering, including but not limited to high engineering flexibility, ease of operation, fast reaction rate, high product yields, and good scalability. These characteristics position ivBT as a promising next-generation biomanufacturing platform. Nevertheless, challenges persist in the enhancement of bulk enzyme preparation methods, the acquisition of enzymes with superior catalytic properties, and the development of sophisticated approaches for pathway design and system optimization. In alignment with the workflow of ivBT development, this chapter presents a systematic introduction to pathway design, enzyme mining and engineering, system construction, and system optimization. The chapter also proffers perspectives on ivBT development.

Developing methylotrophic microbial platforms for a methanol-based bioindustry

Methanol, a relatively cheap and renewable single-carbon feedstock, has gained considerable attention as a substrate for the bio-production of commodity chemicals. Conventionally produced from syngas, along with emerging possibilities of generation from methane and CO2, this C1 substrate can serve as a pool for sequestering greenhouse gases while supporting a sustainable bio-economy. Methylotrophic organisms, with the inherent ability to use methanol as the sole carbon and energy source, are competent candidates as platform organisms. Accordingly, methanol bioconversion pathways have been an attractive target for biotechnological and bioengineering interventions in developing microbial cell factories. This review summarizes the recent advances in methanol-based production of various bulk and value-added chemicals exploiting the native and synthetic methylotrophic organisms. Finally, the current challenges and prospects of streamlining these methylotrophic platforms are discussed.

Challenges and opportunities in C1-based biomanufacturing

The intensifying impact of green-house gas (GHG) emission on environment and climate change has attracted increasing attention, and biorefinery represents one of the most effective routes for reducing GHG emissions from human activities. However, this requires a shift for microbial fermentation from the current use of sugars to the use of biomass, and even better to the primary fixation of single carbon (C1) compounds. Here how microorganisms can be engineered for fixation and conversion of C1 compounds into metabolites that can serve as fuels and platform chemicals are reviewed. Meanwhile, key factors for utilization of these different pathways are discussed, followed by challenges and barriers for the development of C1-based biorefinery.

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.

Data-Driven Synthetic Cell Factories Development for Industrial Biomanufacturing

Revolutionary breakthroughs in artificial intelligence (AI) and machine learning (ML) have had a profound impact on a wide range of scientific disciplines, including the development of artificial cell factories for biomanufacturing. In this paper, we review the latest studies on the application of data-driven methods for the design of new proteins, pathways, and strains. We first briefly introduce the various types of data and databases relevant to industrial biomanufacturing, which are the basis for data-driven research. Different types of algorithms, including traditional ML and more recent deep learning methods, are also presented. We then demonstrate how these data-based approaches can be applied to address various issues in cell factory development using examples from recent studies, including the prediction of protein function, improvement of metabolic models, and estimation of missing kinetic parameters, design of non-natural biosynthesis pathways, and pathway optimization. In the last section, we discuss the current limitations of these data-driven approaches and propose that data-driven methods should be integrated with mechanistic models to complement each other and facilitate the development of synthetic strains for industrial biomanufacturing.

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Metabolic “dark matter” describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark matter of metabolism remains an open challenge that can be addressed globally and systematically by existing computational solutions. In this work, we use 489 generalized enzymatic reaction rules to map both known and unknown metabolic processes around a biochemical database of 1.5 million biological compounds. We predict over 5 million reactions and integrate nearly 2 million naturally and synthetically-derived compounds into the global network of biochemical knowledge, named ATLASx. ATLASx is available to researchers as a powerful online platform that supports the prediction and analysis of biochemical pathways and evaluates the biochemical vicinity of molecule classes (https://lcsb-databases.epfl.ch/Atlas2).

“Mapping the dark matter of metabolism remains an open challenge that can be addressed globally and systematically by existing computational solutions. Here the authors present ATLASx, a repository of known and predicted enzymatic reaction, connecting millions of compounds to help synthetic biologists and metabolic engineers to design and explore metabolic pathways.”

Unravelling Formaldehyde Metabolism in Bacteria: Road towards Synthetic Methylotrophy

Formaldehyde metabolism is prevalent in all organisms, where the accumulation of formaldehyde can be prevented through the activity of dissimilation pathways. Furthermore, formaldehyde assimilatory pathways play a fundamental role in many methylotrophs, which are microorganisms able to build biomass and obtain energy from single- and multicarbon compounds with no carbon–carbon bonds. Here, we describe how formaldehyde is formed in the environment, the mechanisms of its toxicity to the cells, and the cell’s strategies to circumvent it. While their importance is unquestionable for cell survival in formaldehyde rich environments, we present examples of how the modification of native formaldehyde dissimilation pathways in nonmethylotrophic bacteria can be applied to redirect carbon flux toward heterologous, synthetic formaldehyde assimilation pathways introduced into their metabolism. Attempts to engineer methylotrophy into nonmethylotrophic hosts have gained interest in the past decade, with only limited successes leading to the creation of autonomous synthetic methylotrophy. Here, we discuss how native formaldehyde assimilation pathways can additionally be employed as a premise to achieving synthetic methylotrophy. Lastly, we discuss how emerging knowledge on regulation of formaldehyde metabolism can contribute to creating synthetic regulatory circuits applied in metabolic engineering strategies.

Yeast synthetic biology advances biofuel production

Increasing concerns of environmental impacts and global warming calls for urgent need to switch from use of fossil fuels to renewable technologies. Biofuels represent attractive alternatives of fossil fuels and have gained continuous attentions. Through the use of synthetic biology it has become possible to engineer microbial cell factories for efficient biofuel production in a more precise and efficient manner. Here, we review advances on yeast-based biofuel production. Following an overview of synthetic biology impacts on biofuel production, we review recent advancements on the design, build, test, learn steps of yeast-based biofuel production, and end with discussion of challenges associated with use of synthetic biology for developing novel processes for biofuel production.

Cell-free chemoenzymatic starch synthesis from carbon dioxide

[Figure: see text].

Bioconversion of Methanol by Synthetic Methylotrophy

As an important building block in the chemical industry, methanol has become an attractive substrate in biorefinery owing to its abundance and low cost. With the development of synthetic biology, metabolic engineering of non-methylotrophy to construct synthetic methylotrophy has drawn increased attention. As for the metabolic construction of methanol assimilation pathway in some industrial hosts, several artificial methanol assimilation pathways have recently been designed and constructed based on the computer-aided design. Particularly, these artificial methanol assimilation pathways possess advantages of shorter reaction steps, stronger driving forces, and independence on oxygen. Accordingly, this chapter reviewed strategies of constructing synthetic methylotrophs, including introducing methanol metabolic modules derived from natural methylotrophs and designing artificial methanol assimilation pathways. Future challenges and prospects were also discussed.

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.

Physiological limitations and opportunities in microbial metabolic engineering

Metabolic engineering can have a pivotal role in increasing the environmental sustainability of the transportation and chemical manufacturing sectors. The field has already developed engineered microorganisms that are currently being used in industrial-scale processes. However, it is often challenging to achieve the titres, yields and productivities required for commercial viability. The efficiency of microbial chemical production is usually dependent on the physiological traits of the host organism, which may either impose limitations on engineered biosynthetic pathways or, conversely, boost their performance. In this Review, we discuss different aspects of microbial physiology that often create obstacles for metabolic engineering, and present solutions to overcome them. We also describe various instances in which natural or engineered physiological traits in host organisms have been harnessed to benefit engineered metabolic pathways for chemical production.

Integrating thermodynamic and enzymatic constraints into genome-scale metabolic models

Stoichiometric genome-scale metabolic network models (GEMs) have been widely used to predict metabolic phenotypes. In addition to stoichiometric ratios, other constraints such as enzyme availability and thermodynamic feasibility can also limit the phenotype solution space. Extended GEM models considering either enzymatic or thermodynamic constraints have been shown to improve prediction accuracy. In this paper, we propose a novel method that integrates both enzymatic and thermodynamic constraints in a single Pyomo modeling framework (ETGEMs). We applied this method to construct the EcoETM (E. coli metabolic model with enzymatic and thermodynamic constraints). Using this model, we calculated the optimal pathways for cellular growth and the production of 22 metabolites. When comparing the results with those of iML1515 and models with one of the two constraints, we observed that many thermodynamically unfavorable and/or high enzyme cost pathways were excluded from EcoETM. For example, the synthesis pathway of carbamoyl-phosphate (Cbp) from iML1515 is both thermodynamically unfavorable and enzymatically costly. After introducing the new constraints, the production pathways and yields of several Cbp-derived products (e.g. L-arginine, orotate) calculated using EcoETM were more realistic. The results of this study demonstrate the great application potential of metabolic models with multiple constraints for pathway analysis and phenotype prediction.

Strategies and challenges with the microbial conversion of methanol to high-value chemicals

As alternatives to traditional fermentation substrates, methanol (CH₃ OH), carbon dioxide (CO₂ ) and methane (CH₄ ) represent promising one-carbon (C1) sources that are readily available at low-cost and share similar metabolic pathway. Of these C1 compounds, methanol is used as a carbon and energy source by native methylotrophs, and can be obtained from CO₂ and CH₄ by chemical catalysis. Therefore, constructing and rewiring methanol utilization pathways may enable the use of one-carbon sources for microbial fermentations. Recent bioengineering efforts have shown that both native and nonnative methylotrophic organisms can be engineered to convert methanol, together with other carbon sources, into biofuels and other commodity chemicals. However, many challenges remain and must be overcome before industrial-scale bioprocessing can be established using these engineered cell refineries. Here, we provide a comprehensive summary and comparison of methanol metabolic pathways from different methylotrophs, followed by a review of recent progress in engineering methanol metabolic pathways in vitro and in vivo to produce chemicals. We discuss the major challenges associated with establishing efficient methanol metabolic pathways in microbial cells, and propose improved designs for future engineering.

Non-natural Aldol Reactions Enable the Design and Construction of Novel One-Carbon Assimilation Pathways in vitro

Methylotrophs utilizes cheap, abundant one-carbon compounds, offering a promising green, sustainable and economical alternative to current sugar-based biomanufacturing. However, natural one-carbon assimilation pathways come with many disadvantages, such as complicated reaction steps, the need for additional energy and/or reducing power, or loss of CO₂, resulting in unsatisfactory biomanufacturing performance. Here, we predicted eight simple, novel and carbon-conserving formaldehyde (FALD) assimilation pathways based on the extended metabolic network with non-natural aldol reactions using the comb-flux balance analysis (FBA) algorithm. Three of these pathways were found to be independent of energy/reducing equivalents, and thus chosen for further experimental verification. Then, two novel aldol reactions, condensing D-erythrose 4-phosphate and glycolaldehyde (GALD) into 2R,3R-stereo allose 6-phosphate by DeoC or 2S,3R-stereo altrose 6-phosphate by TalB^F178Y/Fsa, were identified for the first time. Finally, a novel FALD assimilation pathway proceeding via allose 6-phosphate, named as the glycolaldehyde-allose 6-phosphate assimilation (GAPA) pathway, was constructed in vitro with a high carbon yield of 94%. This work provides an elegant paradigm for systematic design of one-carbon assimilation pathways based on artificial aldolase (ALS) reactions, which could also be feasibly adapted for the mining of other metabolic pathways.

A computational workflow for the expansion of heterologous biosynthetic pathways to natural product derivatives

Plant natural products (PNPs) and their derivatives are important but underexplored sources of pharmaceutical molecules. To access this untapped potential, the reconstitution of heterologous PNP biosynthesis pathways in engineered microbes provides a valuable starting point to explore and produce novel PNP derivatives. Here, we introduce a computational workflow to systematically screen the biochemical vicinity of a biosynthetic pathway for pharmaceutical compounds that could be produced by derivatizing pathway intermediates. We apply our workflow to the biosynthetic pathway of noscapine, a benzylisoquinoline alkaloid (BIA) with a long history of medicinal use. Our workflow identifies pathways and enzyme candidates for the production of (S)-tetrahydropalmatine, a known analgesic and anxiolytic, and three additional derivatives. We then construct pathways for these compounds in yeast, resulting in platforms for de novo biosynthesis of BIA derivatives and demonstrating the value of cheminformatic tools to predict reactions, pathways, and enzymes in synthetic biology and metabolic engineering.

Rewiring the native methanol assimilation metabolism by incorporating the heterologous ribulose monophosphate cycle into Methylorubrum extorquens

Methanol is assimilated through the serine cycle to generate acetyl-CoA without carbon loss. However, a highly active serine cycle requires high consumption of reducing equivalents and ATP, thereby leading to the impaired efficiency of methanol conversion to reduced chemicals. In the present study, a genome-scale flux balance analysis (FBA) predicted that the introduction of the heterologous ribulose monophosphate (RuMP) cycle, a more energy-efficient pathway for methanol assimilation, could theoretically increase growth rate by 31.3% for the model alphaproteobacterial methylotroph Methylorubrum extorquens AM1. Based on this analysis, we constructed a novel synergistic assimilation pathway in vivo by incorporating the RuMP cycle into M. extroquens metabolism with the intrinsic serine cycle. We demonstrated that the operation of the synergistic pathway could increase cell growth rate by 16.5% and methanol consumption rate by 13.1%. This strategy rewired the central methylotrophic metabolism through adjusting core gene transcription, leading to a pool size increase of C2 to C5 central intermediates by 1.2- to 3.6-fold and an NADPH cofactor improvement by 1.3-fold. The titer of 3-hydroxypropionic acid (3-HP), a model product in the newly engineered chassis of M. extorquens AM1, was increased to 91.2 mg/L in shake-flask culture, representing a 3.1-fold increase compared with the control strain with only the serine cycle. The final titer of 3-HP was significantly improved to 0.857 g/L in the fed-batch bioreactor, which was more competitive compared with the other 3-HP producers using methane and CO₂ as C1 sources. Collectively, our current study demonstrated that engineering the synergistic methanol assimilation pathway was a promising strategy to increase the carbon assimilation and the yields of reduced chemicals in diverse host strains for C1 microbial cell factories.

A deep learning approach to evaluate the feasibility of enzymatic reactions generated by retrobiosynthesis

Retrobiosynthesis allows the designing of novel biosynthetic pathways for the production of chemicals and materials through metabolic engineering, but generates a large number of reactions beyond the experimental feasibility. Thus, an effective method that can reduce a large number of the initially predicted enzymatic reactions has been needed. Here, we present Deep learning-based Reaction Feasibility Checker (DeepRFC) to classify the feasibility of a given enzymatic reaction with high performance and speed. DeepRFC is designed to receive Simplified Molecular-Input Line-Entry System (SMILES) strings of a reactant pair, which is defined as a substrate and a product of a reaction, as an input, and evaluates whether the input reaction is feasible. A deep neural network is selected for DeepRFC as it leads to better classification performance than five other representative machine learning methods examined. For validation, the performance of DeepRFC is compared with another in-house reaction feasibility checker that uses the concept of reaction similarity. Finally, the use of DeepRFC is demonstrated for the retrobiosynthesis-based design of novel one-carbon assimilation pathways. DeepRFC will allow retrobiosynthesis to be more practical for metabolic engineering applications by efficiently screening a large number of retrobiosynthesis-derived enzymatic reactions. DeepRFC is freely available at https://bitbucket.org/kaistsystemsbiology/deeprfc.

Microbial production of multiple short-chain primary amines via retrobiosynthesis

Bio-based production of many chemicals is not yet possible due to the unknown biosynthetic pathways. Here, we report a strategy combining retrobiosynthesis and precursor selection step to design biosynthetic pathways for multiple short-chain primary amines (SCPAs) that have a wide range of applications in chemical industries. Using direct precursors of 15 target SCPAs determined by the above strategy, Streptomyces viridifaciens vlmD encoding valine decarboxylase is examined as a proof-of-concept promiscuous enzyme both in vitro and in vivo for generating SCPAs from their precursors. Escherichia coli expressing the heterologous vlmD produces 10 SCPAs by feeding their direct precursors. Furthermore, metabolically engineered E. coli strains are developed to produce representative SCPAs from glucose, including the one producing 10.67 g L-1 of iso-butylamine by fed-batch culture. This study presents the strategy of systematically designing biosynthetic pathways for the production of a group of related chemicals as demonstrated by multiple SCPAs as examples.

Engineered Methanotrophy: A Sustainable Solution for Methane-Based Industrial Biomanufacturing

Methane is a promising feedstock with high abundance and low cost for the sustainable production of biochemicals and biofuels. Methanotrophic bacteria are particularly interesting platforms for methane bioconversion as they can utilize methane as a carbon substrate. Recently, breakthroughs in the understanding of methane metabolism in methanotrophs as well as critical advances in systems metabolic engineering of methanotrophic bacteria have been reported. Here, we discuss the important gaps in the understanding of methanotrophic metabolism that have been uncovered recently and the current trends in systems metabolic engineering in both methanotrophic bacteria and non-native hosts to advance the potential of methane-based biomanufacturing.

An "energy-auxotroph" Escherichia coli provides an in vivo platform for assessing NADH regeneration systems

An efficient in vivo regeneration of the primary cellular resources NADH and ATP is vital for optimizing the production of value-added chemicals and enabling the activity of synthetic pathways. Currently, such regeneration routes are tested and characterized mainly in vitro before being introduced into the cell. However, in vitro measurements could be misleading as they do not reflect enzyme activity under physiological conditions. Here, we construct an in vivo platform to test and compare NADH regeneration systems. By deleting dihydrolipoyl dehydrogenase in Escherichia coli, we abolish the activity of pyruvate dehydrogenase and 2-ketoglutarate dehydrogenase. When cultivated on acetate, the resulting strain is auxotrophic to NADH and ATP: acetate can be assimilated via the glyoxylate shunt but cannot be oxidized to provide the cell with reducing power and energy. This strain can, therefore, serve to select for and test different NADH regeneration routes. We exemplify this by comparing several NAD-dependent formate dehydrogenases and methanol dehydrogenases. We identify the most efficient enzyme variants under in vivo conditions and pinpoint optimal feedstock concentrations that maximize NADH biosynthesis while avoiding cellular toxicity. Our strain thus provides a useful platform for comparing and optimizing enzymatic systems for cofactor regeneration under physiological conditions.

Recent progress in metabolic engineering of microbial formate assimilation

Formate can be efficiently produced via electrochemical or photochemical catalytic conversion of CO₂, and it can be directly used as an organic carbon source by microorganisms. In theory, formate can be used as the sole carbon source for the microbial production of high-value-added chemicals. Consequently, the construction of efficient formate-assimilation pathways in microorganisms is essential for the utilization of cheap, renewable one-carbon compounds. This paper summarizes new methods of formate synthesis, as well as the natural formate utilization pathways of microorganisms with their advantages and disadvantages. Furthermore, it reviews recent progress in the design of utilization pathways for formate in microbial cells through metabolic engineering and synthetic biology. Besides, we also use the pathway-prediction algorithm comb-FBA to rationally design completely new one-carbon compounds utilization pathways. The pathway with the highest efficiency, named GAA, was corroborated by the in vitro experiments showing a carbon molar yield up to 88%. Finally, it discusses the main problems and challenges presently existing in the pathway design and strain improvement for microbial utilization of formate. KEY POINTS: • Natural and artificial design pathways of formate-assimilation was summarized. • Recent progresses in different hosts and approaches of using one-carbon compounds was reviewed. • Metabolic engineering and synthetic biology methods to improve formate utilization were discussed.

Updated ATLAS of Biochemistry with New Metabolites and Improved Enzyme Prediction Power

The ATLAS of Biochemistry is a repository of both known and novel predicted biochemical reactions between biological compounds listed in the Kyoto Encyclopedia of Genes and Genomes (KEGG). ATLAS was originally compiled based on KEGG 2015, though the number of KEGG reactions has increased by almost 20 percent since then. Here, we present an updated version of ATLAS created from KEGG 2018 using an increased set of generalized reaction rules. Furthermore, we improved the accuracy of the enzymes that are predicted for catalyzing novel reactions. ATLAS now contains ∼150 000 reactions, out of which 96% are novel. In this report, we present detailed statistics on the updated ATLAS and highlight the improvements with regard to the previous version. Most importantly, 107 reactions predicted in the original ATLAS are now known to KEGG, which validates the predictive power of our approach. The updated ATLAS is available at https://lcsb-databases.epfl.ch/atlas.

Formaldehyde formation in the glycine cleavage system and its use for an aldolase-based biosynthesis of 1,3-prodanediol

Glycine cleavage system (GCS) occupies a key position in one-carbon (C1) metabolic pathway and receives great attention for the use of C1 carbons like formate and CO₂ via synthetic biology. In this work, we demonstrate that formaldehyde exists as a substantial byproduct of the GCS reaction cycle. Three causes are identified for its formation. First, the principal one is the decomposition of N⁵,N¹⁰-methylene-tetrahydrofolate (5,10-CH₂-THF) to form formaldehyde and THF. Increasing the rate of glycine cleavage promotes the formation of 5,10-CH₂-THF, thereby increasing the formaldehyde release rate. Next, formaldehyde can be produced in the GCS even in the absence of THF. The reason is that T-protein of the GCS can degrade methylamine-loaded H-protein (H_int) to formaldehyde and ammonia, accompanied with the formation of dihydrolipoyl H-protein (H_red), but the reaction rate is less than 0.16% of that in the presence of THF. Increasing T-protein concentration can speed up the release rate of formaldehyde by H_int. Finally, a certain amount of formaldehyde can be formed in the GCS due to oxidative degradation of THF. Based on a formaldehyde-dependent aldolase, we elaborated a glycine-based one carbon metabolic pathway for the biosynthesis of 1,3-propanediol (1,3-PDO) in vitro. This work provides quantitative data and mechanistic understanding of formaldehyde formation in the GCS and a new biosynthetic pathway of 1,3-PDO.

Adaptive laboratory evolution enhances methanol tolerance and conversion in engineered Corynebacterium glutamicum

Synthetic methylotrophy has recently been intensively studied to achieve methanol-based biomanufacturing of fuels and chemicals. However, attempts to engineer platform microorganisms to utilize methanol mainly focus on enzyme and pathway engineering. Herein, we enhanced methanol bioconversion of synthetic methylotrophs by improving cellular tolerance to methanol. A previously engineered methanol-dependent Corynebacterium glutamicum is subjected to adaptive laboratory evolution with elevated methanol content. Unexpectedly, the evolved strain not only tolerates higher concentrations of methanol but also shows improved growth and methanol utilization. Transcriptome analysis suggests increased methanol concentrations rebalance methylotrophic metabolism by down-regulating glycolysis and up-regulating amino acid biosynthesis, oxidative phosphorylation, ribosome biosynthesis, and parts of TCA cycle. Mutations in the O-acetyl-l-homoserine sulfhydrylase Cgl0653 catalyzing formation of l-methionine analog from methanol and methanol-induced membrane-bound transporter Cgl0833 are proven crucial for methanol tolerance. This study demonstrates the importance of tolerance engineering in developing superior synthetic methylotrophs.

Wang et al. improve the methanol tolerance for the synthetic methylotroph, Corynebacterium glutamicum. They generate 3 new strains by directed evolution and use biochemical, transcriptomic, and genetic approaches to characterize the pathways underlying the enhanced methanol metabolism. Their findings are important for biomanufacturing purposes.

An optimized methanol assimilation pathway relying on promiscuous formaldehyde-condensing aldolases in E. coli

Engineering biotechnological microorganisms to use methanol as a feedstock for bioproduction is a major goal for the synthetic metabolism community. Here, we aim to redesign the natural serine cycle for implementation in E. coli. We propose the homoserine cycle, relying on two promiscuous formaldehyde aldolase reactions, as a superior pathway design. The homoserine cycle is expected to outperform the serine cycle and its variants with respect to biomass yield, thermodynamic favorability, and integration with host endogenous metabolism. Even as compared to the RuMP cycle, the most efficient naturally occurring methanol assimilation route, the homoserine cycle is expected to support higher yields of a wide array of products. We test the in vivo feasibility of the homoserine cycle by constructing several E. coli gene deletion strains whose growth is coupled to the activity of different pathway segments. Using this approach, we demonstrate that all required promiscuous enzymes are active enough to enable growth of the auxotrophic strains. Our findings thus identify a novel metabolic solution that opens the way to an optimized methylotrophic platform.

Synthetic Methylotrophy: A Practical Solution for Methanol-Based Biomanufacturing

The increasing availability and affordability of natural gas has renewed interest in using methanol for bioproduction of useful chemicals. Engineering synthetic methylotrophy based on natural or artificial methanol assimilation pathways and genetically tractable platform microorganisms for methanol-based biomanufacturing is drawing particular attention. Recently, intensive efforts have been devoted to demonstrating the feasibility and improving the efficiency of synthetic methylotrophy. Various fuel, bulk, and fine chemicals have been synthesized using methanol as a feedstock. However, fully synthetic methylotrophs utilizing methanol as the sole carbon source and commercially viable bioproduction from methanol remain to be developed. Here, we review ongoing efforts to identify limiting factors, optimize synthetic methylotrophs, and implement methanol-based biomanufacturing. Future challenges and prospects are also discussed.