Thermodynamic limitations of PHB production from formate and fructose in Cupriavidus necator

The chemolithotroph Cupriavidus necator H16 is known as a natural producer of the bioplastic-polymer PHB, as well as for its metabolic versatility to utilize different substrates, including formate as the sole carbon and energy source. Depending on the entry point of the substrate, this versatility requires adjustment of the thermodynamic landscape to maintain sufficiently high driving forces for biological processes. Here we employed a model of the core metabolism of C. necator H16 to analyze the thermodynamic driving forces and PHB yields from formate for different metabolic engineering strategies. For this, we enumerated elementary flux modes (EFMs) of the network and evaluated their PHB yields as well as thermodynamics via Max-min driving force (MDF) analysis and random sampling of driving forces. A heterologous ATP:citrate lyase reaction was predicted to increase driving force for producing acetyl-CoA. A heterologous phosphoketolase reaction was predicted to increase maximal PHB yields as well as driving forces. These enzymes were then verified experimentally to enhance PHB titers between 60 and 300% in select conditions. The EFM analysis also revealed that PHB production from formate may be limited by low driving forces through citrate lyase and aconitase, as well as cofactor balancing, and identified additional reactions associated with low and high PHB yield. Proteomics analysis of the engineered strains confirmed an increased abundance of aconitase and cofactor balancing. The findings of this study aid in understanding metabolic adaptation. Furthermore, the outlined approach will be useful in designing metabolic engineering strategies in other non-model bacteria.     

A guide to metabolic flux analysis in metabolic engineering: Methods,tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, “Metabolic fluxes and metabolic engineering” (Metabolic Engineering, 1: 1–11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.     

Microbial production of riboflavin: Biotechnological advances and perspectives

Riboflavin is an essential nutrient for humans and animals, and its derivatives flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD) are cofactors in the cells. Therefore, riboflavin and its derivatives are widely used in the food, pharmaceutical, nutraceutical and cosmetic industries. Advances in biotechnology have led to a complete shift in the commercial production of riboflavin from chemical synthesis to microbial fermentation. In this review, we provide a comprehensive review of biotechnologies that enhance riboflavin production in microorganisms, as well as representative examples. Firstly, the synthesis pathways and metabolic regulatory processes of riboflavin in microorganisms; and the current strategies and methods of metabolic engineering for riboflavin production are systematically summarized and compared. Secondly, the using of systematic metabolic engineering strategies to enhance riboflavin production is discussed, including laboratory evolution, histological analysis and high-throughput screening. Finally, the challenges for efficient microbial production of riboflavin and the strategies to overcome these challenges are prospected.     

Phenotypic characterization of <Emphasis Type="Italic">Corynebacterium glutamicum</Emphasis> using elementary modes towards synthesis of amino acids

Elementary flux mode (EFM) analysis is a powerful tool to represent the metabolic network structure and can be further utilized for flux analysis. The method enables characterization and quantification of feasible phenotypes in microbes. EFM analysis was employed to characterize the phenotype of Corynebacterium glutamicum to yield various amino acids. The metabolic network of C. glutamicum yielded 62 elementary modes by incorporating the accumulation of amino acids namely, lysine, alanine, valine, glutamine and glutamate. The analysis also allowed us to compute the maximum theoretical yield for the synthesis of various amino acids. These 62 elementary modes were further used to obtain optimal phenotypic space towards accumulation of biomass and lysine. The study indicated that the optimal solution space from 62 elementary modes forms a super space which incorporates various mutants including lysine producing strain of C. glutamicum. The analysis was also extended to obtain sensitivity of the network to variation in the stoichiometry of NADP in the definition of biomass.     

Metabolic engineering in dark fermentative hydrogen production; theory and practice

Dark fermentation is an attractive option for hydrogen production since it could use already existing reactor technology and readily available substrates without requiring a direct input of solar energy. However, a number of improvements are required before the rates and yields of such a process approach those required for a practical process. Among the options for achieving the required advances, metabolic engineering offers some powerful tools for remodeling microbes to increase product production rates and molar yields. Here we review the current metabolic engineering tool box that is available, discuss the current status of engineering efforts as applied to dark hydrogen production, and suggest areas for future improvements.     

1H-NMR-based metabolomics for cancer targeting and metabolic engineering –A review

Nuclear magnetic resonance (NMR) spectroscopy acts as the best tool that can be used in tissue engineering scaffolds to investigate unknown metabolites. Moreover, metabolomics is a systems approach for examining in vivo and in vitro metabolic profiles, which promises to provide data on cancer metabolic alterations. However, metabolomic profiling allows for the activity of small molecules and metabolic alterations to be measured. Furthermore, metabolic profiling also provides high-spectral resolution, which can then be linked to potential metabolic relationships. An altered metabolism is a hallmark of cancer that can control many malignant properties to drive tumorigenesis. Metabolite targeting and metabolic engineering contribute to carcinogenesis by proliferation, and metabolic differentiation. The resulting the metabolic differences are examined with traditional chemometric methods such as principal component analysis (PCA), and partial least squares-discriminate analysis (PLS-DA). In this review, we examine NMR-based activity metabolomic platforms that can be used to analyze various fluxomics and for multivariant statistical analysis in cancer. We also aim to provide the reader with a basic understanding of NMR spectroscopy, cancer metabolomics, target profiling, chemometrics, and multifunctional tools for metabolomics discrimination, with a focus on metabolic phenotypic diversity for cancer therapeutics.     

Engineering of carboligase activity reaction in Candida glabrata for acetoin production

Utilization of Candida glabrata overproducing pyruvate is a promising strategy for high-level acetoin production. Based on the known regulatory and metabolic information, acetaldehyde and thiamine were fed to identify the key nodes of carboligase activity reaction (CAR) pathway and provide a direction for engineering C. glabrata. Accordingly, alcohol dehydrogenase, acetaldehyde dehydrogenase, pyruvate decarboxylase, and butanediol dehydrogenase were selected to be manipulated for strengthening the CAR pathway. Following the rational metabolic engineering, the engineered strain exhibited increased acetoin biosynthesis (2.24 g/L). In addition, through in silico simulation and redox balance analysis, NADH was identified as the key factor restricting higher acetoin production. Correspondingly, after introduction of NADH oxidase, the final acetoin production was further increased to 7.33 g/L. By combining the rational metabolic engineering and cofactor engineering, the acetoin-producing C. glabrata was improved stepwise, opening a novel pathway for rational development of microorganisms for bioproduction.     

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms

Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and ¹³C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering.     

Systems metabolic engineering: Genome-scale models and beyond

The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches – based on the data collected with high throughput technologies – to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.     

Metabolic engineering for valorization of macroalgae biomass

Marine macroalgae have huge potential as feedstocks for production of a wide spectrum of chemicals used in biofuels, biomaterials, and bioactive compounds. Harnessing macroalgae in these ways could promote wellbeing for people while mitigating climate change and environmental destruction linked to use of fossil fuels. Microorganisms play pivotal roles in converting macroalgae into valuable products, and metabolic engineering technologies have been developed to extend their native capabilities. This review showcases current achievements in engineering the metabolisms of various microbial chassis to convert red, green, and brown macroalgae into bioproducts. Unique features of macroalgae, such as seasonal variation in carbohydrate content and salinity, provide the next challenges to advancing macroalgae-based biorefineries. Three emerging engineering strategies are discussed here: (1) designing dynamic control of metabolic pathways, (2) engineering strains of halophilic (salt-tolerant) microbes, and (3) developing microbial consortia for conversion. This review illuminates opportunities for future research communities by elucidating current approaches to engineering microbes so they can become cell factories for the utilization of macroalgae feedstocks.     

13C metabolic flux analysis of three divergent extremely thermophilic bacteria: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252

Thermophilic organisms are being increasingly investigated and applied in metabolic engineering and biotechnology. The distinct metabolic and physiological characteristics of thermophiles, including broad substrate range and high uptake rates, coupled with recent advances in genetic tool development, present unique opportunities for strain engineering. However, poor understanding of the cellular physiology and metabolism of thermophiles has limited the application of systems biology and metabolic engineering tools to these organisms. To address this concern, we applied high resolution ¹³C metabolic flux analysis to quantify fluxes for three divergent extremely thermophilic bacteria from separate phyla: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252. We performed 18 parallel labeling experiments, using all singly labeled glucose tracers for each strain, reconstructed and validated metabolic network models, measured biomass composition, and quantified precise metabolic fluxes for each organism. In the process, we resolved many uncertainties regarding gaps in pathway reconstructions and elucidated how these organisms maintain redox balance and generate energy. Overall, we found that the metabolisms of the three thermophiles were highly distinct, suggesting that adaptation to growth at high temperatures did not favor any particular set of metabolic pathways. All three strains relied heavily on glycolysis and TCA cycle to generate key cellular precursors and cofactors. None of the investigated organisms utilized the Entner-Doudoroff pathway and only one strain had an active oxidative pentose phosphate pathway. Taken together, the results from this study provide a solid foundation for future model building and engineering efforts with these and related thermophiles.     

平台化学品短链支链脂肪酸和短链支链醇的微生物代谢工程

短链支链脂肪酸和短链支链醇均为重要的平台化学品,是合成多种高附加值产品的前体物质,市场需求巨大。目前两者的生产主要是利用基于石化原料的化学合成法。化学合成法存在着严重依赖化石燃料、反应效率低以及极易造成环境污染等缺点。微生物代谢工程的快速发展为这些平台化学品的生产提供了一条极具潜力的生物合成路线。利用微生物代谢工程技术构建生产这些平台化学品的微生物细胞工厂具有绿色清洁、可持续发展和经济效益好等独特优势。本文系统综述了近年来微生物代谢工程技术在短链支链脂肪酸和短链支链醇合成方面的研究进展,包括所涉及的宿主菌株、关键酶、代谢途径及其改造等,并探讨了未来的发展前景。     

Expanding the metabolic engineering toolbox with directed evolution

Cellular systems can be engineered into factories that produce high-value chemicals from renewable feedstock. Such an approach requires an expanded toolbox for metabolic engineering. Recently, protein engineering and directed evolution strategies have started to play a growing and critical role within metabolic engineering. This review focuses on the various ways in which directed evolution can be applied in conjunction with metabolic engineering to improve product yields. Specifically, we discuss the application of directed evolution on both catalytic and non-catalytic traits of enzymes, on regulatory elements, and on whole genomes in a metabolic engineering context. We demonstrate how the goals of metabolic pathway engineering can be achieved in part through evolving cellular parts as opposed to traditional approaches that rely on gene overexpression and deletion. Finally, we discuss the current limitations in screening technology that hinder the full implementation of a metabolic pathway-directed evolution approach.     

代谢转基因植物的研究现状与展望

代谢转基因是通过基因工程技术对细胞内的代谢途径进行遗传修饰,进而完成细胞特性改造。代谢修饰转基因植物是一个极具商业前景的领域,在医药、环境、农业等方面已有许多成功应用的实例。综合调控代谢的基因工程策略,讨论了代谢转基因植物的研究现状,我国农业生产中存在的主要问题和代谢转基因技术对我国农业发展的意义和前景。     

代谢工程及其在产苯丙氨酸基因工程菌构建中的应用

本文对代谢工程的发展状况从研究方法,在医药、农业及环保中应用等几方面做了概括地介绍;从宿主的选择,加速限速反应,改变代谢流和生产程序的优化几方面较为详细地评述了代谢工程在苯丙氨酸基因工程菌构建方面的应用,并对代谢工程的未来发展进行了展望。     

The bright frontiers of microbial metabolic optogenetics

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

微生物代谢工程原理与应用

代谢工程是利用分子生物学原理系统分析细胞代谢网络,并通过DNA重组技术和应用分析生物学相关的遗传学手段对细胞进行有精确目标的基因操作,改变微生物原有的代谢或调节系统,实现目的产物代谢活性的提高。代谢工程综合了生物化学、化学工程、数学分析等多学科内容,是当前国内外学者研究热点之一。论述了微生物代谢工程的理论基础及其应用进展和前景。     

Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism

Elementary mode analysis is a useful metabolic pathway analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering.     

Metabolic engineering of bacteria

Yield and productivity are critical for the economics and viability of a bioprocess. In metabolic engineering the main objective is the increase of a target metabolite production through genetic engineering. Metabolic engineering is the practice of optimizing genetic and regulatory processes within cells to increase the production of a certain substance. In the last years, the development of recombinant DNA technology and other related technologies has provided new tools for approaching yields improvement by means of genetic manipulation of biosynthetic pathway. Industrial microorganisms like Escherichia coli, Actinomycetes, etc. have been developed as biocatalysts to provide new or to optimize existing processes for the biotechnological production of chemicals from renewable plant biomass. The factors like oxygenation, temperature and pH have been traditionally controlled and optimized in industrial fermentation in order to enhance metabolite production. Metabolic engineering of bacteria shows a great scope in industrial application as well as such technique may also have good potential to solve certain metabolic disease and environmental problems in near future.