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.     

Biotechnological production of γ-decalactone,a peach like aroma,by <Emphasis Type="Italic">Yarrowia lipolytica</Emphasis>

The request for new flavourings increases every year. Consumer perception that everything natural is better is causing an increase demand for natural aroma additives. Biotechnology has become a way to get natural products. γ-Decalactone is a peach-like aroma widely used in dairy products, beverages and others food industries. In more recent years, more and more studies and industrial processes were endorsed to cost-effect this compound production. One of the best-known methods to produce γ-decalactone is from ricinoleic acid catalyzed by Yarrowia lipolytica, a generally regarded as safe status yeast. As yet, several factors affecting γ-decalactone production remain to be fully understood and optimized. In this review, we focus on the aromatic compound γ-decalactone and its production by Y. lipolytica. The metabolic pathway of lactone production and degradation are addressed. Critical analysis of novel strategies of bioprocess engineering, metabolic and genetic engineering and other strategies for the enhancement of the aroma productivity are presented.     

Biochemical production capabilities of Escherichia coli

Microbial metabolism provides at mechanism for the conversion of substrates into useful biochemicals. Utilization of microbes in industrial processes requires a modification of their natural metabolism in order to increase the efficiency of the desired conversion. Redirection of metabolic fluxes forms the basis of the newly defined field of metabolic engineering. In this study we use a flux balance based approach to study the biosynthesis of the 20 amino acids and 4 nucleotides as biochemical products. These amino acids and nucleotides are primary products of biosynthesis as well as important industrial products and precursors for the production of other biochemicals. The biosynthetic reactions of the bacterium Escherichia coli have been formulated into a metabolic network, and growth has been defined as a balanced drain on the metabolite pools corresponding to the cellular composition. Theoretical limits on the conversion of glucose, glycerol, and acetate substrates to biomass as well as the biochemical products have been computed. The substrate that results in the maximal carbon conversion to a particular product is identified. Criteria have been developed to identify metabolic constraints in the optimal solutions. The constraints of stoichiometry, energy, and redox have been determined in the conversions of glucose, glycerol, and acetate substrates into the biochemicals. Flux distributions corresponding to the maximal production of the biochemicals are presented. The goals of metabolic engineering are the optimal redirection of fluxes from generating biomass toward producing the desired biochemical. Optimal biomass generation is shown to decrease in a piecewise linear manner with increasing product formation. In some cases, synergy is observed between biochemical production and growth, leading to an increased overall carbon conversion. Balanced growth and product formation are important in a bioprocess, particularly for nonsecreted products. (c) 1993 John Wiley & Sons, Inc.     

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.     

The role of metabolic engineering in the production of secondary metabolites

In the production of secondary metabolites yield and productivity are the most important design parameters. The focus is therefore to direct the carbon fluxes towards the product of interest, and this can be obtained through metabolic engineering whereby directed genetic changes are introduced into the production strain. In this process it is, however, important to analyze the metabolic network through measurement of the intracellular metabolites and the flux distributions. Besides playing an important role in the optimization of existing processes, metabolic engineering also offers the possibility to construct strains that produce novel metabolites, either through the recruitment of heterologous enzyme activities or through introduction of specific mutations in catalytic activities.     

Metabolic flux analysis for serine alkaline protease fermentation by Bacillus licheniformis in a defined medium: effects of the oxygen transfer rate.

The metabolic fluxes through the central carbon pathways in the bioprocess for serine alkaline protease (SAP) production by Bacillus licheniformis were calculated by the metabolic flux-based stoichiometric model based on the proposed metabolic network that contains 102 metabolites and 133 reaction fluxes using the time profiles of citrate, dry cell, organic acids, amino acids, and SAP as the constraints. The model was solved by minimizing the SAP accumulation rate in the cell. The effects of the oxygen-transfer rate (OTR) on the metabolic fluxes were investigated in a defined medium where citrate was used as the sole carbon source. The central pathways were active for the growth and the SAP synthesis in all the periods of the bioprocess at low (LOT), medium (MOT), and high (HOT) oxygen-transfer conditions. The flux partitioning in the TCA cycle at alpha-ketoglutarate towards glutamate group and at oxalacetate (OA) toward aspartic acid group amino acids were dependent on the OTR. The flux of the anaplerotic reaction that connects the TCA cycle either from malate or OA to the gluconeogenesis pathway via the main branch point pyruvate (Pyr) was also influenced by the OTR. With the decrease in the OTR, the intracellular flux values after glycerate 3-phosphate (PG3) in the gluconeogenesis pathway and the specific growth rate decreased. The total ATP-generation rate increased with the increase in OTR. The pathway towards the aspartic acid family amino acids which is important for sporulation that precedes the SAP synthesis were all active throughout the bioprocess. Metabolic flux analysis results at LOT, MOT, and HOT conditions encourage the design of an oxygen-transfer strategy in the bioreactor; moreover, asparagine synthetase or aspartate kinase could be the potential metabolic engineering sites due to the low value of the flux from the branch point aspartate toward asparagine.     

Dynamic modeling of the central carbon metabolism of Escherichia coli

Application of metabolic engineering principles to the rational design of microbial production processes crucially depends on the ability to describe quantitatively the systemic behavior of the central carbon metabolism to redirect carbon fluxes to the product-forming pathways. Despite the importance for several production processes, development of an essential dynamic model for central carbon metabolism of Escherichia coli has been severely hampered by the current lack of kinetic information on the dynamics of the metabolic reactions. Here we present the design and experimental validation of such a dynamic model, which, for the first time, links the sugar transport system (i.e., phosphotransferase system [PTS]) with the reactions of glycolysis and the pentose-phosphate pathway. Experimental observations of intracellular concentrations of metabolites and cometabolites at transient conditions are used to validate the structure of the model and to estimate the kinetic parameters. Further analysis of the detailed characteristics of the system offers the possibility of studying important questions regarding the stability and control of metabolic fluxes.     

Physiology of microbial cells and metabolic engineering

This review is devoted to the problems of the physiology and cell biology of microorganisms in relation to metabolic engineering. The latter is considered as a branch of fundamental and applied biotechnology aimed at controlling microbial metabolism by methods of genetic engineering and classical genetics and based on intimate knowledge of cell metabolism. Attention is also given to the problems associated with the metabolic limitation of microbial biosyntheses, analysis and control of metabolic fluxes, rigidity of metabolic pathways, the role of pleiotropic (global) regulatory systems in the control of metabolic fluxes, and prospects of physiological and evolutionary approaches in metabolic engineering.     

Physiology of microbial cell and metabolic engineering

This review is devoted to the problems of the physiology and cell biology of microorganisms in relation to metabolic engineering. The latter is considered as a branch of fundamental and applied biotechnology aimed at controlling microbial metabolism by methods of genetic engineering and classical genetics and based on intimate knowledge of cell metabolism. Attention is also given to the problems associated with the metabolic limitation of microbial biosyntheses, analysis and control of metabolic fluxes, rigidity of metabolic pathways, the role of pleiotropic (global) regulatory systems in the control of metabolic fluxes, and prospects of physiological and evolutionary approaches in metabolic engineering.     

应用最大熵原理通过酶控制通量预测突变体的通量分布

在代谢工程和系统生物学领域, 计算机模拟比以往更为有效的应用于生物过程的分析和优化。胞内代谢通量可以用代谢通量分析和基元模式分析来估算。由于测定数据的不足和误差, 以及基元途径的冗余, 经常很难得到准确的代谢通量分布数据。本研究提出一种基于最大熵原理的算法来计算基元模式系数。欠定和不确定条件下, 通过胞外代谢通量数据估算胞内代谢通量分布。为了检验算法的可行性, 对杂交瘤细胞、枯草芽孢杆菌和大肠杆菌的胞内代谢通量分布做了估算。本研究提出的基于最大熵原理的优化算法避免了对细胞状态的生理学假设。与其他目标函数相比, 可以更为可靠和可行的估算胞内代谢通量分布。     

Prediction of dynamic behavior of mutant strains from limited wild-type data

Metabolic engineering is the field of introducing genetic changes in organisms so as to modify their function towards synthesizing new products of high impact to society. However, engineered cells frequently have impaired growth rates thus seriously limiting the rate at which such products are made. The problem is attributable to inadequate understanding of how a metabolic network functions in a dynamic sense. Predictions of mutant strain behavior in the past have been based on steady state theories such as flux balance analysis (FBA), minimization of metabolic adjustment (MOMA), and regulatory on/off minimization (ROOM). Such predictions are restricted to product yields and cannot address productivity, which is of focal interest to applications. We demonstrate that our framework ( [Song and Ramkrishna, 2010] and [Song and Ramkrishna, 2011]), based on a “cybernetic” view of metabolic systems, makes predictions of the dynamic behavior of mutant strains of Escherichia coli from a limited amount of data obtained from the wild-type. Dynamic frameworks must necessarily address the issue of metabolic regulation, which the cybernetic approach does by postulating that metabolism is an optimal dynamic response of the organism to the environment in driving reactions towards ensuring survival. The predictions made in this paper are without parallel in the literature and lay the foundation for rational metabolic engineering.     

Plasmid maintenance and physiology of a genetically engineered <Emphasis Type="Italic">Escherichia coli</Emphasis> strain during continuous <Emphasis Type="SmallCaps">l</Emphasis>-carnitine production

The effect of immobilization on cell physiology and how this determines cell metabolic performance is an important concern for developing bioprocess. This is particularly true for genetically modified microorganisms and their genetic stability. For this reason the stability and physiological state of plasmid-bearing E. coli cells were ascertained by flow cytometry. Differences in the cellular DNA and protein content (15-20%) permit discrimination of control and plasmid-bearing cells, as well as adaptation to continuous cultivation conditions in both freely suspended and immobilized states to be monitored. Moreover, the observed metabolic burden due to maintenance and over-expression of plasmid-coded genetic material and slow cell growth in poorly-viable immobilized cells were found to be the main factors contributing to strain stabilization.     

Metabolic flux analysis of Escherichia coli K12 grown on 13C-labeled acetate and glucose using GC-MS and powerful flux calculation method

A new algorithm was developed for the estimation of the metabolic flux distribution based on GC-MS data of proteinogenic amino acids. By using a sensitive GC-MS protocol as well as by combining the global search algorithm such as the genetic algorithm with the local search algorithm such as the Levenberg-Marquardt algorithm, not only the distribution of the net fluxes in the entire network, but also certain exchange fluxes which contribute significantly to the isotopomer distribution could be quantified. This mass isotopomer analysis could identify the biochemical changes involved in the regulation where acetate or glucose was used as a main carbon source. The metabolic flux analysis clearly revealed that when the specific growth rate increased, only a slight change in flux distribution was observed for acetate metabolism, indicating that subtle regulation mechanism exists in certain key junctions of this network system. Different from acetate metabolism, when glucose was used as a carbon source, as the growth rate increased, a significant increase in relative pentose phosphate pathway (PPP) flux was observed for Escherichia coli K12 at the expense of the citric acid cycle, suggesting that when growing on glucose, the flux catalyzed by isocitrate dehydrogenase could not fully fulfill the NADPH demand for cell growth, causing the oxidative PPP to be utilized to a larger extent so as to complement the NADPH demand. The GC-MS protocol as well as the new algorithm demonstrated here proved to be a powerful tool for characterizing metabolic regulation and can be utilized for strain improvement and bioprocess optimization.     

Metabolic and bioprocess engineering for production of selenized yeast with increased content of seleno-methylselenocysteine

Specific Se-metabolites have been recognized to be the main elements responsible for beneficial effects of Se-enriched diet, and Se-methylselenocysteine (SeMCys) is thought to be among the most effective ones. Here we show that an engineered Saccharomyces cerevisiae strain, expressing a codon optimized heterologous selenocysteine methyltransferase and endowed with high intracellular levels of S-adenosyl-methionine, was able to accumulate SeMCys at levels higher than commercial selenized yeasts. A fine tuned carbon- and sulfate-limited fed-batch bioprocess was crucial to achieve good yields of biomass and SeMCys. Through the coupling of metabolic and bioprocess engineering we achieved a ～24-fold increase in SeMCys, compared to certified reference material of selenized yeast. In addition, we investigated the interplay between sulfur and selenium metabolism and the possibility that redox imbalance occurred along with intracellular accumulation of Se. Collectively, our data show how the combination of metabolic and bioprocess engineering can be used for the production of selenized yeast enriched with beneficial Se-metabolites.     

Altered regulation of pyruvate kinase or co-overexpression of phosphofructokinase increases glycolytic fluxes in resting Escherichia coli

Glycolytic fluxes in resting Escherichia coli were enhanced by overexpression of heterologous pyruvate kinases (Pyk) from Bacillus stearothermophilus and Zymomonas mobilis, but not homologous Pyk. Compared to the control, an increase of 10% in specific glucose consumption and of 15% in specific ethanol production rates was found in anaerobic resting cells, expressing the heterologous Pyks, that were harvested from exponentially growing aerobic cultures. A further increase in glycolytic flux was achieved by simultaneous overexpression of E. coli phosphofructokinase (Pfk) and Pyk with specific glucose consumption and ethanol production rates of 25% and 35% greater, respectively, than the control. Fluxes to lactate were not significantly affected, contrary to previous observations with resting cells harvested from anaerobically growing cultures. To correlate the physiology of resting cells with the physiology of cells prior to harvest, we determined the relevant growth parameters from aerobic and anaerobic precultures. We conclude that glycolytic fluxes in E. coli with submaximal (aerobic) metabolic activity can be increased by overexpression of pyruvate kinases which do not require allosteric activation or co-overexpression with Pfk. However, such improvements require more extensive engineering in E. coli with near maximal (anaerobic) metabolic activity.     

Metabolic modeling and response surface analysis of an Escherichia coli strain engineered for shikimic acid production

Background

Classic metabolic engineering strategies often induce significant flux imbalances to microbial metabolism, causing undesirable outcomes such as suboptimal conversion of substrates to products. Several mathematical frameworks have been developed to understand the physiological and metabolic state of production strains and to identify genetic modification targets for improved bioproduct formation. In this work, a modeling approach was applied to describe the physiological behavior and the metabolic fluxes of a shikimic acid overproducing Escherichia coli strain lacking the major glucose transport system, grown on complex media.

Results

The obtained flux distributions indicate the presence of high fluxes through the pentose phosphate and Entner-Doudoroff pathways, which could limit the availability of erythrose-4-phosphate for shikimic acid production even with high flux redirection through the pentose phosphate pathway. In addition, highly active glyoxylate shunt fluxes and a pyruvate/acetate cycle are indicators of overflow glycolytic metabolism in the tested conditions. The analysis of the combined physiological and flux response surfaces, enabled zone allocation for different physiological outputs within variant substrate conditions. This information was then used for an improved fed-batch process designed to preserve the metabolic conditions that were found to enhance shikimic acid productivity. This resulted in a 40% increase in the shikimic acid titer (60 g/L) and 70% increase in volumetric productivity (2.45 gSA/L*h), while preserving yields, compared to the batch process.

Conclusions

The combination of dynamic metabolic modeling and experimental parameter response surfaces was a successful approach to understand and predict the behavior of a shikimic acid producing strain under variable substrate concentrations. Response surfaces were useful for allocating different physiological behavior zones with different preferential product outcomes. Both model sets provided information that could be applied to enhance shikimic acid production on an engineered shikimic acid overproducing Escherichia coli strain.

     

Effect of overexpression of a soluble pyridine nucleotide transhydrogenase (UdhA) on the production of poly(3-hydroxybutyrate) in Escherichia coli

A soluble pyridine nucleotide transhydrogenase (UdhA) has been used to increase the productivity and yield of PHB in vivo. By inducing a high level of UdhA, which can transfer reducing equivalents between NAD and NADP, we have increased NADPH availability, resulting in high yield and productivity of PHB in Escherichia coli. Coexpression of the phb operon from Alcaligenes eutrophus H16 and the native udhA from E. coli from high copy plasmids resulted in an increase in PHB yield from 49 to 66% g of PHB per gram of total cell dry weight and an increase in final concentration from 3.52 to 6.42 g/L; the PHB concentration of the udhA carrying strain is almost twice that of the control strain expressing only the phb operon. The results of this study demonstrate the effectiveness of cofactor manipulation and its application as a tool in metabolic engineering.     

Optimization of industrial microorganisms: recent advances in synthetic dynamic regulators

Production of biochemicals by industrial fermentation using microorganisms requires maintaining cellular production capacity, because maximal productivity is economically important. High-productivity microbial strains can be developed using static engineering, but these may not maintain maximal productivity throughout the culture period as culture conditions and cell states change dynamically. Additionally, economic reasons limit heterologous protein expression using inducible promoters to prevent metabolic burden for commodity chemical and biofuel production. Recently, synthetic and systems biology has been used to design genetic circuits, precisely controlling gene expression or influencing genetic behavior toward a desired phenotype. Development of dynamic regulators can maintain cellular phenotype in a maximum production state in response to factors including cell concentration, oxygen, temperature, pH, and metabolites. Herein, we introduce dynamic regulators of industrial microorganism optimization and discuss metabolic flux fine control by dynamic regulators in response to metabolites or extracellular stimuli, robust production systems, and auto-induction systems using quorum sensing.     

Applications of metabolic modeling to drive bioprocess development for the production of value-added chemicals

Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput ‘omics’ data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.     

Modification of central metabolic pathway in escherichia coli to reduce acetate accumulation by heterologous expression of the bacillus subtilis acetolactate synthase gene

A novel metabolic engineering technique involving the redirection ofcellular carbon fluxes was employed to reduce acetate production in an Escherichia coli culture. Metabolic engineering was achieved by cloning E. coli the gene for the Bacillus subtilis acetolactate synthase (ALS), an enzyme capable of catalyzing the conversion of pyruvate to nonacidic and less harmful species. The heterologous expression of the ALS catabolic enzyme in Escherichia coli drastically modified the cellular glycolytic fluxes. In particular, acetate excretion, which is a common characteristic of E. coli, as well as a physiological burden, was minimized. The residual acetate level was kept under control and maintained at a level that was below the toxic threshold. The expression of the biologically active ALS enzyme in E. coli did not result in any detectable changes on either cell growth rate or cell yields. The alternative product, acetoin, was shown to be 50 times less harmful than acetate. Similarities in the growth pattern of two different E. coli strains, RR1 and GJT001, under all cultivation conditions suggested that the ability of ALS to reduce acetate accumulation is generic and not strain-specific. (c) 1994 John Wiley & Sons, Inc.