Toward systematic metabolic engineering based on the analysis of metabolic regulation by the integration of different levels of information

Modeling and simulation of the redox regulation of the metabolism in Escherichia coli at different oxygen concentrations

BACKGROUND

Microbial production of biofuels and biochemicals from renewable feedstocks has received considerable recent attention from environmental protection and energy production perspectives. Many biofuels and biochemicals are produced by fermentation under oxygen-limited conditions following initiation of aerobic cultivation to enhance the cell growth rate. Thus, it is of significant interest to investigate the effect of dissolved oxygen concentration on redox regulation in Escherichia coli, a particularly popular cellular factory due to its high growth rate and well-characterized physiology. For this, the systems biology approach such as modeling is powerful for the analysis of the metabolism and for the design of microbial cellular factories.

RESULTS

Here, we developed a kinetic model that describes the dynamics of fermentation by taking into account transcription factors such as ArcA/B and Fnr, respiratory chain reactions and fermentative pathways, and catabolite regulation. The hallmark of the kinetic model is its ability to predict the dynamics of metabolism at different dissolved oxygen levels and facilitate the rational design of cultivation methods. The kinetic model was verified based on the experimental data for a wild-type E. coli strain. The model reasonably predicted the metabolic characteristics and molecular mechanisms of fnr and arcA gene-knockout mutants. Moreover, an aerobic-microaerobic dual-phase cultivation method for lactate production in a pfl-knockout mutant exhibited promising yield and productivity.

CONCLUSIONS

It is quite important to understand metabolic regulation mechanisms from both scientific and engineering points of view. In particular, redox regulation in response to oxygen limitation is critically important in the practical production of biofuel and biochemical compounds. The developed model can thus be used as a platform for designing microbial factories to produce a variety of biofuels and biochemicals.

Web application for genetic modification flux with database to estimate metabolic fluxes of genetic mutants

Computational analysis of metabolic fluxes is essential in understanding the structure and function of a metabolic network and in rationally designing genetically modified mutants for an engineering purpose. We had presented the genetic modification flux (GMF) that predicts the flux distribution of a broad range of genetically modified mutants. To enhance the feasibility and usability of GMF, we have developed a web application with a metabolic network database to predict a flux distribution of genetically modified mutants. One hundred and twelve data sets of Escherichia coli, Corynebacterium glutamicum, Saccharomyces cerevisiae, and Chinese hamster ovary were registered as standard models.

Toward Sustainable Amino Acid Production

Because the global amino acid production industry has been growing steadily and is expected to grow even more in the future, efficient production by fermentation is of great importance from economic and sustainability viewpoints. Many systems biology technologies, such as genome breeding, omics analysis, metabolic flux analysis, and metabolic simulation, have been employed for the improvement of amino acid-producing strains of bacteria. Synthetic biological approaches have recently been applied to strain development. It is also important to use sustainable carbon sources, such as glycerol or pyrolytic sugars from cellulosic biomass, instead of conventional carbon sources, such as glucose or sucrose, which can be used as food. Furthermore, reduction of sub-raw substrates has been shown to lead to reduction of environmental burdens and cost. Recently, a new fermentation system for glutamate production under acidic pH was developed to decrease the amount of one sub-raw material, ammonium, for maintenance of culture pH. At the same time, the utilization of fermentation coproducts, such as cells, ammonium sulfate, and fermentation broth, is a useful approach to decrease waste. In this chapter, further perspectives for future amino acid fermentation from one-carbon compounds are described.

Engineering Escherichia coli to overproduce aromatic amino acids and derived compounds

The production of aromatic amino acids using fermentation processes with recombinant microorganisms can be an advantageous approach to reach their global demands. In addition, a large array of compounds with alimentary and pharmaceutical applications can potentially be synthesized from intermediates of this metabolic pathway. However, contrary to other amino acids and primary metabolites, the artificial channelling of building blocks from central metabolism towards the aromatic amino acid pathway is complicated to achieve in an efficient manner. The length and complex regulation of this pathway have progressively called for the employment of more integral approaches, promoting the merge of complementary tools and techniques in order to surpass metabolic and regulatory bottlenecks. As a result, relevant insights on the subject have been obtained during the last years, especially with genetically modified strains of Escherichia coli. By combining metabolic engineering strategies with developments in synthetic biology, systems biology and bioprocess engineering, notable advances were achieved regarding the generation, characterization and optimization of E. coli strains for the overproduction of aromatic amino acids, some of their precursors and related compounds. In this paper we review and compare recent successful reports dealing with the modification of metabolic traits to attain these objectives.

Model-driven redox pathway manipulation for improved isobutanol production in Bacillus subtilis complemented with experimental validation and metabolic profiling analysis

To rationally guide the improvement of isobutanol production, metabolic network and metabolic profiling analysis were performed to provide global and profound insights into cell metabolism of isobutanol-producing Bacillus subtilis. The metabolic flux distribution of strains with different isobutanol production capacity (BSUL03, BSUL04 and BSUL05) drops a hint of the importance of NADPH on isobutanol biosynthesis. Therefore, the redox pathways were redesigned in this study. To increase NADPH concentration, glucose-6-phosphate isomerase was inactivated (BSUL06) and glucose-6-phosphate dehydrogenase was overexpressed (BSUL07) successively. As expected, NADPH pool size in BSUL07 was 4.4-fold higher than that in parental strain BSUL05. However, cell growth, isobutanol yield and production were decreased by 46%, 22%, and 80%, respectively. Metabolic profiling analysis suggested that the severely imbalanced redox status might be the primary reason. To solve this problem, gene udhA of Escherichia coli encoding transhydrogenase was further overexpressed (BSUL08), which not only well balanced the cellular ratio of NAD(P)H/NAD(P)⁺, but also increased NADH and ATP concentration. In addition, a straightforward engineering approach for improving NADPH concentrations was employed in BSUL05 by overexpressing exogenous gene pntAB and obtained BSUL09. The performance for isobutanol production by BSUL09 was poorer than BSUL08 but better than other engineered strains. Furthermore, in fed-batch fermentation the isobutanol production and yield of BSUL08 increased by 11% and 19%, up to the value of 6.12 g/L and 0.37 C-mol isobutanol/C-mol glucose (63% of the theoretical value), respectively, compared with parental strain BSUL05. These results demonstrated that model-driven complemented with metabolic profiling analysis could serve as a useful approach in the strain improvement for higher bio-productivity in further application.

¹³C-metabolic flux analysis for Escherichia coli

(13)C-Metabolic flux analysis ((13)C-MFA) is used here to study the effects of the knockout of such genes as pgi, zwf, gnd, ppc, pck, pyk, and lpdA on the metabolic changes in Escherichia coli cultivated under aerobic condition. The metabolic regulation mechanisms were clarified by integrating such information as fermentation data, gene expression, enzyme activities, and metabolite concentrations as well the result of (13)C-MFA.

Catabolite regulation analysis of Escherichia coli for acetate overflow mechanism and co-consumption of multiple sugars based on systems biology approach using computer simulation

It is quite important to understand the basic principle embedded in the main metabolism for the interpretation of the fermentation data. For this, it may be useful to understand the regulation mechanism based on systems biology approach. In the present study, we considered the perturbation analysis together with computer simulation based on the models which include the effects of global regulators on the pathway activation for the main metabolism of Escherichia coli. Main focus is the acetate overflow metabolism and the co-fermentation of multiple carbon sources. The perturbation analysis was first made to understand the nature of the feed-forward loop formed by the activation of Pyk by FDP (F1,6BP), and the feed-back loop formed by the inhibition of Pfk by PEP in the glycolysis. Those together with the effect of transcription factor Cra caused by FDP level affected the glycolysis activity. The PTS (phosphotransferase system) acts as the feed-back system by repressing the glucose uptake rate for the increase in the glucose uptake rate. It was also shown that the increased PTS flux (or glucose consumption rate) causes PEP/PYR ratio to be decreased, and EIIA-P, Cya, cAMP-Crp decreased, where cAMP-Crp in turn repressed TCA cycle and more acetate is formed. This was further verified by the detailed computer simulation. In the case of multiple carbon sources such as glucose and xylose, it was shown that the sequential utilization of carbon sources was observed for wild type, while the co-consumption of multiple carbon sources with slow consumption rates were observed for the ptsG mutant by computer simulation, and this was verified by experiments. Moreover, the effect of a specific gene knockout such as Δpyk on the metabolic characteristics was also investigated based on the computer simulation.

Metabolic Regulation of a Bacterial Cell System with Emphasis on Escherichia coli Metabolism

It is quite important to understand the overall metabolic regulation mechanism of bacterial cells such as Escherichia coli from both science (such as biochemistry) and engineering (such as metabolic engineering) points of view. Here, an attempt was made to clarify the overall metabolic regulation mechanism by focusing on the roles of global regulators which detect the culture or growth condition and manipulate a set of metabolic pathways by modulating the related gene expressions. For this, it was considered how the cell responds to a variety of culture environments such as carbon (catabolite regulation), nitrogen, and phosphate limitations, as well as the effects of oxygen level, pH (acid shock), temperature (heat shock), and nutrient starvation.

Importance of understanding the main metabolic regulation in response to the specific pathway mutation for metabolic engineering of Escherichia coli

Recent metabolic engineering practice was briefly reviewed in particular for the useful metabolite production such as natural products and biofuel productions. With the emphasis on systems biology approach, the metabolic regulation of the main metabolic pathways in E. coli was discussed from the points of view of enzyme level (allosteric and phosphorylation/ dephosphorylation) regulation, and gene level (transcriptional) regulation. Then the effects of the specific pathway gene knockout such as pts, pgi, zwf, gnd, pyk, ppc, pckA, lpdA, pfl gene knockout on the metabolism in E. coli were overviewed from the systems biology point of view with possible application for strain improvement point.

Metabolic regulation analysis of wild-type and arcA mutant Escherichia coli under nitrate conditions using different levels of omics data

It is of practical interest to investigate the effect of nitrates on bacterial metabolic regulation of both fermentation and energy generation, as compared to aerobic and anaerobic growth without nitrates. Although gene level regulation has previously been studied for nitrate assimilation, it is important to understand this metabolic regulation in terms of global regulators. In the present study, therefore, we measured gene expression using DNA microarrays, intracellular metabolite concentrations using CE-TOFMS, and metabolic fluxes using the (13)C-labeling technique for wild-type E. coli and the ΔarcA (a global regulatory gene for anoxic response control, ArcA) mutant to compare the metabolic state under nitrate conditions to that under aerobic and anaerobic conditions without nitrates in continuous culture conditions at a dilution rate of 0.2 h(-1). In wild-type, although the measured metabolite concentrations changed very little among the three culture conditions, the TCA cycle and the pentose phosphate pathway fluxes were significantly different under each condition. These results suggested that the ATP production rate was 29% higher under nitrate conditions than that under anaerobic conditions, whereas the ATP production rate was 10% lower than that under aerobic conditions. The flux changes in the TCA cycle were caused by changes in control at the gene expression level. In ΔarcA mutant, the TCA cycle flux was significantly increased (4.4 times higher than that of the wild type) under nitrate conditions. Similarly, the intracellular ATP/ADP ratio increased approximately two-fold compared to that of the wild-type strain.

Subtoxic product levels limit the epoxidation capacity of recombinant E. coli by increasing microbial energy demands

The utilization of the cellular metabolism for cofactor regeneration is a common motivation for the application of whole cells in redox biocatalysis. Introduction of an active oxidoreductase into a microorganism has profound consequences on metabolism, potentially affecting metabolic and biotransformation efficiency. An ambitious goal of systems biotechnology is to design process-relevant and knowledge-based engineering strategies to improve biocatalyst performance. Metabolic flux analysis (MFA) has shown that the competition for NAD(P)H between redox biocatalysis and the energy metabolism becomes critical during asymmetric styrene epoxidation catalyzed by growing Escherichia coli containing recombinant styrene monooxygenase. Engineering TCA-cycle regulation allowed increased TCA-cycle activities, a delay of acetate formation, and enhanced NAD(P)H yields during batch cultivation. However, at low biomass and product concentrations, the cellular metabolism of both the mutants as well as the native host strains could cope with increased NADH demands during continuous two-liquid phase biotransformations, whereas elevated but still subtoxic product concentrations were found to cause a significantly increased NAD(P)H demand and a compromised efficiency of metabolic operation. In conclusion, operational conditions determine cellular energy and NAD(P)H demands and thus the biocatalytic efficiency of whole-cell redox biocatalysts.

Metabolic flux analysis and visualization

One of the ultimate goals of systems biology research is to obtain a comprehensive understanding of the control mechanisms of complex cellular metabolisms. Metabolic Flux Analysis (MFA) is a important method for the quantitative estimation of intracellular metabolic flows through metabolic pathways and the elucidation of cellular physiology. The primary challenge in the use of MFA is that many biological networks are underdetermined systems; it is therefore difficult to narrow down the solution space from the stoichiometric constraints alone. In this tutorial, we present an overview of Flux Balance Analysis (FBA) and (13)C-Metabolic Flux Analysis ((13)C-MFA), both of which are frequently used to solve such underdetermined systems, and we demonstrate FBA and (13)C-MFA using the genome-scale model and the central carbon metabolism model, respectively. Furthermore, because such comprehensive study of intracellular fluxes is inherently complex, we subsequently introduce various pathway mapping and visualization tools to facilitate understanding of these data in the context of the pathways. Specific visualization of MFA results using the BioCyc Omics Viewer and Pathway Projector are shown as illustrative examples.

Flight dynamics of a pterosaur-inspired aircraft utilizing a variable-placement vertical tail

Mission performance for small aircraft is often dependent on the turn radius. Various biologically inspired concepts have demonstrated that performance can be improved by morphing the wings in a manner similar to birds and bats; however, the morphing of the vertical tail has received less attention since neither birds nor bats have an appreciable vertical tail. This paper investigates a design that incorporates the morphing of the vertical tail based on the cranial crest of a pterosaur. The aerodynamics demonstrate a reduction in the turn radius of 14% when placing the tail over the nose in comparison to a traditional aft-placed vertical tail. The flight dynamics associated with this configuration has unique characteristics such as a Dutch-roll mode with excessive roll motion and a skid divergence that replaces the roll convergence.

Modeling and simulation of the main metabolism in Escherichia coli and its several single-gene knockout mutants with experimental verification

BACKGROUND

It is quite important to simulate the metabolic changes of a cell in response to the change in culture environment and/or specific gene knockouts particularly for the purpose of application in industry. If this could be done, the cell design can be made without conducting exhaustive experiments, and one can screen out the promising candidates, proceeded by experimental verification of a select few of particular interest. Although several models have so far been proposed, most of them focus on the specific metabolic pathways. It is preferred to model the whole of the main metabolic pathways in Escherichia coli, allowing for the estimation of energy generation and cell synthesis, based on intracellular fluxes and that may be used to characterize phenotypic growth.

RESULTS

In the present study, we considered the simulation of the main metabolic pathways such as glycolysis, TCA cycle, pentose phosphate (PP) pathway, and the anapleorotic pathways using enzymatic reaction models of E. coli. Once intracellular fluxes were computed by this model, the specific ATP production rate, the specific CO₂ production rate, and the specific NADPH production rate could be estimated. The specific ATP production rate thus computed was used for the estimation of the specific growth rate. The CO₂ production rate could be used to estimate cell yield, and the specific NADPH production rate could be used to determine the flux of the oxidative PP pathway. The batch and continuous cultivations were simulated where the changing patterns of extracellular and intra-cellular metabolite concentrations were compared with experimental data. Moreover, the effects of the knockout of such pathways as Ppc, Pck and Pyk on the metabolism were simulated. It was shown to be difficult for the cell to grow in Ppc mutant due to low concentration of OAA, while Pck mutant does not necessarily show this phenomenon. The slower growth rate of the Ppc mutant was properly estimated by taking into account the lower specific ATP production rate. In the case of Pyk mutant, the enzyme level regulation was made clear such that Pyk knockout caused PEP concentration to be up-regulated and activated Ppc, which caused the increase in MAL concentration and backed up reduced PYR through Mez, resulting in the phenotypic growth characteristics similar to the wild type.

CONCLUSIONS

It was shown to be useful to simulate the main metabolism of E. coli for understanding metabolic changes inside the cell in response to specific pathway gene knockouts, considering the whole main metabolic pathways. The comparison of the simulation result with the experimental data indicates that the present model could simulate the effect of the specific gene knockouts to the changes in the metabolisms to some extent.

Use of genome-scale metabolic models for understanding microbial physiology

The exploitation of microorganisms in industrial, medical, food and environmental biotechnology requires a comprehensive understanding of their physiology. The availability of genome sequences and accumulation of high-throughput data allows gaining understanding of microbial physiology at the systems level, and genome-scale metabolic models represent a valuable framework for integrative analysis of metabolism of microorganisms. Genome-scale metabolic models are reconstructed based on a combination of genome sequence information and detailed biochemical information, and these reconstructed models can be used for analyzing and simulating the operation of metabolism in response to different stimuli. Here we discuss the requirement for having detailed physiological insight in order to exploit microorganisms for production of fuels, chemicals and pharmaceuticals. We further describe the reconstruction process of genome-scale metabolic models and different algorithms that can be used to apply these models to gain improved insight into microbial physiology.