Analysis of Escherichia coli anaplerotic metabolism and its regulation mechanisms from the metabolic responses to altered dilution rates and phosphoenolpyruvate carboxykinase knockout

Balancing biomass reaction stoichiometry and measured fluxes in flux balance analysis

MOTIVATION

Flux balance analysis (FBA) is widely recognized as an important method for studying metabolic networks. When incorporating flux measurements of certain reactions into an FBA problem, it is possible that the underlying linear program may become infeasible, e.g. due to measurement or modeling inaccuracies. Furthermore, while the biomass reaction is of central importance in FBA models, its stoichiometry is often a rough estimate and a source of high uncertainty.

RESULTS

In this work, we present a method that allows modifications to the biomass reaction stoichiometry as a means to (i) render the FBA problem feasible and (ii) improve the accuracy of the model by corrections in the biomass composition. Optionally, the adjustment of the biomass composition can be used in conjunction with a previously introduced approach for balancing inconsistent fluxes to obtain a feasible FBA system. We demonstrate the value of our approach by analyzing realistic flux measurements of E.coli. In particular, we find that the growth-associated maintenance (GAM) demand of ATP, which is typically integrated with the biomass reaction, is likely overestimated in recent genome-scale models, at least for certain growth conditions. In light of these findings, we discuss issues related to the determination and inclusion of GAM values in constraint-based models. Overall, our method can uncover potential errors and suggest adjustments in the assumed biomass composition in FBA models based on inconsistencies between the model and measured fluxes.

AVAILABILITY AND IMPLEMENTATION

The developed method has been implemented in our software tool CNApy available from https://github.com/cnapy-org/CNApy.

Metabolic engineering of Halomonas elongata: Ectoine secretion is increased by demand and supply driven approaches

The application of naturally-derived biomolecules in everyday products, replacing conventional synthetic manufacturing, is an ever-increasing market. An example of this is the compatible solute ectoine, which is contained in a plethora of treatment formulations for medicinal products and cosmetics. As of today, ectoine is produced in a scale of tons each year by the natural producer Halomonas elongata. In this work, we explore two complementary approaches to obtain genetically improved producer strains for ectoine production. We explore the effect of increased precursor supply (oxaloacetate) on ectoine production, as well as an implementation of increased ectoine demand through the overexpression of a transporter. Both approaches were implemented on an already genetically modified ectoine-excreting strain H. elongata KB2.13 (ΔteaABC ΔdoeA) and both led to new strains with higher ectoine excretion. The supply driven approach led to a 45% increase in ectoine titers in two different strains. This increase was attributed to the removal of phosphoenolpyruvate carboxykinase (PEPCK), which allowed the conversion of 17.9% of the glucose substrate to ectoine. For the demand driven approach, we investigated the potential of the TeaBC transmembrane proteins from the ectoine-specific Tripartite ATP-Independent Periplasmic (TRAP) transporter as export channels to improve ectoine excretion. In the absence of the substrate-binding protein TeaA, an overexpression of both subunits TeaBC facilitated a three-fold increased excretion rate of ectoine. Individually, the large subunit TeaC showed an approximately five times higher extracellular ectoine concentration per dry weight compared to TeaBC shortly after its expression was induced. However, the detrimental effect on growth and ectoine titer at the end of the process hints toward a negative impact of TeaC overexpression on membrane integrity and possibly leads to cell lysis. By using either strategy, the ectoine synthesis and excretion in H. elongata could be boosted drastically. The inherent complementary nature of these approaches point at a coordinated implementation of both as a promising strategy for future projects in Metabolic Engineering. Moreover, a wide variation of intracelllular ectoine levels was observed between the strains, which points at a major disruption of mechanisms responsible for ectoine regulation in strain KB2.13.

Genome-Scale Metabolic Model's multi-objective solving algorithm based on the inflexion point of Pareto front including maximum energy utilization and its application in A.niger DS03043

The solution of genome-scale metabolic model (GSMM) directly affects the simulation accuracy of the metabolic process in digital cells. Single-objective optimization methods, such as Flux Balance Analysis (FBA) which is widely used in solving GSMM, have limitations when simulating actual biological processes, which leads to unrealistic results due to other biological constraints being ignored. A novel multi-objective Differential Evolution algorithm based on general FBA (i.e., DEFBA) is hence proposed to solve GSMM. First, in accordance with to the assumption that cells minimize resource consumption and maximize resource utilization, the maximum specific growth rate and the minimum cellular production rate of ATP, NADPH, and NADH are defined as the multi-objective functions of DEFBA. Second, FBA is used to produce the initial individuals of DEFBA by changing the upper bound of biomass reaction in GSMM. Third, mutation and selection operations help in generating new individuals in the solution space to search the Pareto front. Finally, the optimal solution is selected by analyzing the inflexion point of the Pareto front. In DEFBA, multi-objective technology and optimal solution judging technology can introduce the biological constraints into the GSMM solving method, such that the solution can be more consistent with the essential biological mechanism. DEFBA is applied to solve Aspergillus niger's GSMM. The improved results show that DEFBA can be an effective general solving algorithm for GSMM. This article is protected by copyright. All rights reserved.

Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions

Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and ¹³C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between ¹³C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed.

Biotechnology has benefitted from the development of high throughput methods characterising living systems at different levels (e.g. concerning genes or proteins), allowing the industrial production of chemical commodities. Recently, focus has been placed on determining reaction rates (or metabolic fluxes) in the metabolic network of certain microorganisms, in order to identify bottlenecks hindering their exploitation. Two main approaches are commonly used, termed metabolic flux analysis (MFA) and flux balance analysis (FBA), based on measuring and estimating fluxes, respectively. While the influence of thermodynamics in living systems was accepted several decades ago, its application to study biochemical networks has only recently been enabled. In this sense, a multitude of different approaches constraining well-established modelling methods with thermodynamics has been suggested. However, physicochemical parameters are generally not properly adjusted to the experimental conditions, which might affect their predictive capabilities. In this study, we have explored the reliability of currently available tools by investigating the impact of varying said parameters in the simulation of metabolic fluxes and metabolite concentration values. Additionally, our in-depth analysis allowed us to highlight limitations and potential solutions that should be considered in future studies.

In silico co-factor balance estimation using constraint-based modelling informs metabolic engineering in Escherichia coli

In the growing field of metabolic engineering, where cells are treated as ‘factories’ that synthesize industrial compounds, it is essential to consider the ability of the cells’ native metabolism to accommodate the demands of synthetic pathways, as these pathways will alter the homeostasis of cellular energy and electron metabolism. From the breakdown of substrate, microorganisms activate and reduce key co-factors such as ATP and NAD(P)H, which subsequently need to be hydrolysed and oxidized, respectively, in order to restore cellular balance. A balanced supply and consumption of such co-factors, here termed co-factor balance, will influence biotechnological performance. To aid the strain selection and design process, we used stoichiometric modelling (FBA, pFBA, FVA and MOMA) and the Escherichia coli (E.coli) core stoichiometric model to investigate the network-wide effect of butanol and butanol precursor production pathways differing in energy and electron demand on product yield. An FBA-based co-factor balance assessment (CBA) algorithm was developed to track and categorise how ATP and NAD(P)H pools are affected in the presence of a new pathway. CBA was compared to the balance calculations proposed by Dugar et al. (Nature Biotechnol. 29 (12), 1074–1078). Predicted solutions were compromised by excessively underdetermined systems, displaying greater flexibility in the range of reaction fluxes than experimentally measured by ¹³C-metabolic flux analysis (MFA) and the appearance of unrealistic futile co-factor cycles. With the assumption that futile cycles are tightly regulated in reality, the FBA models were manually constrained in a step-wise manner. Solutions with minimal futile cycling diverted surplus energy and electrons towards biomass formation. As an alternative, the use of loopless FBA or constraining the models with measured flux ranges were tried but did not prevent futile co-factor cycles. The results highlight the need to account for co-factor imbalance and confirm that better-balanced pathways with minimal diversion of surplus towards biomass formation present the highest theoretical yield. The analysis also suggests that ATP and NAD(P)H balancing cannot be assessed in isolation from each other, or even from the balance of additional co-factors such as AMP and ADP. We conclude that, through revealing the source of co-factor imbalance CBA can facilitate pathway and host selection when designing new biocatalysts for implementation by metabolic engineering.

The chemicals industry is a major contributor to greenhouse gas emissions and desperately requires more sustainable alternatives. Genetically engineered microorganisms can be used as ‘bio-factories’ to manufacture chemicals, replacing those currently sourced from fossil fuels or unsustainable tropical plant agriculture. However, due to the complexity of biology, the features that render one bio-factory design more efficient than others are difficult to identify. Computational modelling of such designs can enable the selection of optimally performing designs, but it remains challenging as biology is complex and not fully understood. Microorganisms require energy for their own growth and maintenance, but also to convert molecules into desired target products. The supply and consumption of such energy is through co-factors, and the balance of such co-factors influences the performance of the engineered bio-factories. This study developed a computer-aided approach for quantification of the co-factor balance of bio-factories. Using the chemical n-butanol as a case study, our study explores the impact of variant bio-factory designs with differing co-factor balance on the potential efficiency of biomanufacturing. We provide insights into the relative balance of different designs and provide a computational framework to select the best-performing designs.

Escherichia coli metabolism under short-term repetitive substrate dynamics: adaptation and trade-offs

Background

Microbial metabolism is highly dependent on the environmental conditions. Especially, the substrate concentration, as well as oxygen availability, determine the metabolic rates. In large-scale bioreactors, microorganisms encounter dynamic conditions in substrate and oxygen availability (mixing limitations), which influence their metabolism and subsequently their physiology. Earlier, single substrate pulse experiments were not able to explain the observed physiological changes generated under large-scale industrial fermentation conditions.

Results

In this study we applied a repetitive feast–famine regime in an aerobic Escherichia coli culture in a time-scale of seconds. The regime was applied for several generations, allowing cells to adapt to the (repetitive) dynamic environment. The observed response was highly reproducible over the cycles, indicating that cells were indeed fully adapted to the regime. We observed an increase of the specific substrate and oxygen consumption (average) rates during the feast–famine regime, compared to a steady-state (chemostat) reference environment. The increased rates at same (average) growth rate led to a reduced biomass yield (30% lower). Interestingly, this drop was not followed by increased by-product formation, pointing to the existence of energy-spilling reactions. During the feast–famine cycle, the cells rapidly increased their uptake rate. Within 10 s after the beginning of the feeding, the substrate uptake rate was higher (4.68 μmol/g_CDW/s) than reported during batch growth (3.3 μmol/g_CDW/s). The high uptake led to an accumulation of several intracellular metabolites, during the feast phase, accounting for up to 34% of the carbon supplied. Although the metabolite concentrations changed rapidly, the cellular energy charge remained unaffected, suggesting well-controlled balance between ATP producing and ATP consuming reactions.

Conclusions

The adaptation of the physiology and metabolism of E. coli under substrate dynamics, representative for large-scale fermenters, revealed the existence of several cellular mechanisms coping with stress. Changes in the substrate uptake system, storage potential and energy-spilling processes resulted to be of great importance. These metabolic strategies consist a meaningful step to further tackle reduced microbial performance, observed under large-scale cultivations.

Metabolic engineering of Escherichia coli for shikimate pathway derivative production from glucose-xylose co-substrate

Glucose and xylose are the major components of lignocellulose. Effective utilization of both sugars can improve the efficiency of bioproduction. Here, we report a method termed parallel metabolic pathway engineering (PMPE) for producing shikimate pathway derivatives from glucose–xylose co-substrate. In this method, we seek to use glucose mainly for target chemical production, and xylose for supplying essential metabolites for cell growth. Glycolysis and the pentose phosphate pathway are completely separated from the tricarboxylic acid (TCA) cycle. To recover cell growth, we introduce a xylose catabolic pathway that directly flows into the TCA cycle. As a result, we can produce 4.09 g L⁻¹cis,cis-muconic acid using the PMPE Escherichia coli strain with high yield (0.31 g g⁻¹ of glucose) and produce l-tyrosine with 64% of the theoretical yield. The PMPE strategy can contribute to the development of clean processes for producing various valuable chemicals from lignocellulosic resources.

In lignocellulose biomass, microbes prefer consuming glucose over xylose, which affects target compound production. Here, the authors achieve simultaneous utilization of glucose and xylose for target chemical production and cell growth, respectively, and realize high-level production of shikimate pathway derivatives.

The phosphoenolpyruvate-pyruvate-oxaloacetate node genes and enzymes in Streptomyces coelicolor M-145

The phosphoenolpyruvate-pyruvate-oxaloacetate node is a major branch within the central carbon metabolism and acts as a connection point between glycolysis, gluconeogenesis, and the TCA cycle. Phosphoenolpyruvate carboxylase, pyruvate carboxylase, phosphoenolpyruvate carboxykinase, malic enzymes, and pyruvate kinase, among others, are enzymes included in this node. We determined the mRNA levels and specific activity profiles of some of these genes and enzymes in Streptomyces coelicolor M-145. The results obtained in the presence of glucose demonstrated that all genes studied of the phosphoenolpyruvate-pyruvate-oxaloacetate node were expressed, although at different levels, with 10- to 100-fold differences. SCO3127 (phosphoenolpyruvate carboxylase gene) and SCO5261 (NADP⁺-dependent malic enzyme gene) showed the highest expression in the rapid growth phase, and the mRNA levels corresponding to SCO5896 (phosphoenolpyruvate-utilizing enzyme gene), and SCO0546 (pyruvate carboxylase gene) increased 5- to 10-fold towards the stationary phase. In casamino acids, in general mRNA levels of S. coelicolor were lower than in glucose, however, results showed greater mRNA expression of SCO4979 (PEP carboxykinase), SCO0208 (pyruvate phosphate dikinase gene), and SCO5261 (NADP⁺-dependent malic enzyme). These results suggest that PEP carboxylase (SCO3127) is an important enzyme during glucose catabolism and oxaloacetate replenishment. On the other hand, phosphoenolpyruvate carboxykinase, pyruvate phosphate dikinase, and NADP⁺-malic enzyme could have an important role in gluconeogenesis in S. coelicolor.

Microbial energy management-A product of three broad tradeoffs

Wherever thermodynamics allows, microbial life has evolved to transform and harness energy. Microbial life thus abounds in the most unexpected places, enabled by profound metabolic diversity. Within this diversity, energy is transformed primarily through variations on a few core mechanisms. Energy is further managed by the physiological processes of cell growth and maintenance that use energy. Some aspects of microbial physiology are streamlined for energetic efficiency while other aspects seem suboptimal or even wasteful. We propose that the energy that a microbe harnesses and devotes to growth and maintenance is a product of three broad tradeoffs: (i) economic, trading enzyme synthesis or operational cost for functional benefit, (ii) environmental, trading optimization for a single environment for adaptability to multiple environments, and (iii) thermodynamic, trading energetic yield for forward metabolic flux. Consideration of these tradeoffs allows one to reconcile features of microbial physiology that seem to opposingly promote either energetic efficiency or waste.

Systematic analysis of the effects of different nitrogen source and ICDH knockout on glycolate synthesis in Escherichia coli

BACKGROUND

Glycolate is an important α-hydroxy carboxylic acid widely used in industrial and consumer applications. The production of glycolate from glucose in Escherichia coli is generally carried out by glycolysis and glyoxylate shunt pathways, followed by reduction to glycolate. Glycolate accumulation was significantly affected by nitrogen sources and isocitrate dehydrogenase (ICDH), which influenced carbon flux distribution between the tricarboxylic acid (TCA) cycle and the glyoxylate shunt, however, the mechanism was unclear.

RESULTS

Herein, we used RNA-Seq to explore the effects of nitrogen sources and ICDH knockout on glycolate production. The Mgly534 strain and the Mgly624 strain (with the ICDH deletion in Mgly534), displaying different phenotypes on organic nitrogen sources, were also adopted for the exploration. Though the growth of Mgly534 was improved on organic nitrogen sources, glycolate production decreased and acetate accumulated, while Mgly624 achieved a balance between cell growth and glycolate production, reaching 0.81 g glycolate/OD (2.6-fold higher than Mgly534). To further study Mgly624, the significant changed genes related to N-regulation, oxidative stress response and iron transport were analyzed. Glutamate and serine were found to increase the biomass and productivity respectively. Meanwhile, overexpressing the arginine transport gene argT accelerated the cell growth rate and increased the biomass. Further, the presence of Fe2+ also speeded up the cells growth and compensated for the lack of reducing equivalents.

CONCLUSION

Our studies identified that ICDH knockout strain was more suitable for glycolate production. RNA-Seq provided a better understanding of the ICDH knockout on cellular physiology and glycolate production.

Metabolic engineering of Escherichia coli carrying the hybrid acetone-biosynthesis pathway for efficient acetone biosynthesis from acetate

Background

The shortage of food based feedstocks has been one of the stumbling blocks in industrial biomanufacturing. The acetone bioproduction from the traditional acetone–butanol–ethanol fermentation is limited by the non-specificity of products and competitive utilization of food-based substrates. Using genetically modified Escherichia coli to produce acetone as sole product from the cost-effective non-food based substrates showed great potential to overcome these problems.

Results

A novel acetone biosynthetic pathway were constructed based on genes from Clostridium acetobutylicum (thlA encoding for thiolase, adc encoding for acetoacetate decarboxylase, ctfAB encoding for coenzyme A transferase) and Escherichia coli MG1655 (atoB encoding acetyl-CoA acetyltransferase, atoDA encoding for acetyl-CoA: acetoacetyl-CoA transferase subunit α and β). Among these constructs, one recombinant MG1655 derivative containing the hybrid pathway consisting of thlA, atoDA, and adc, produced the highest level of acetone from acetate. Reducing the gluconeogenesis pathway had little effect on acetone production, while blocking the TCA cycle by knocking out the icdA gene enhanced the yield of acetone significantly. As a result, acetone concentration increased up to 113.18 mM in 24 h by the resting cell culture coupling with gas-stripping methods.

Conclusions

An engineered E. coli strain with optimized hybrid acetone biosynthetic pathway can utilize acetate as substrate efficiently to synthesize acetone without other non-gas byproducts. It provides a potential method for industrial biomanufacturing of acetone by engineered E. coli strains from non-food based substrate.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1054-8) contains supplementary material, which is available to authorized users.

Regulation of glycolytic flux and overflow metabolism depending on the source of energy generation for energy demand

Overflow metabolism is a common phenomenon observed at higher glycolytic flux in many bacteria, yeast (known as Crabtree effect), and mammalian cells including cancer cells (known as Warburg effect). This phenomenon has recently been characterized as the trade-offs between protein costs and enzyme efficiencies based on coarse-graining approaches. Moreover, it has been recognized that the glycolytic flux increases as the source of energy generation changes from energetically efficient respiration to inefficient respiro-fermentative or fermentative metabolism causing overflow metabolism. It is highly desired to clarify the metabolic regulation mechanisms behind such phenomena. Metabolic fluxes are located on top of the hierarchical regulation systems, and represent the outcome of the integrated response of all levels of cellular regulation systems. In the present article, we discuss about the different levels of regulation systems for the modulation of fluxes depending on the growth rate, growth condition such as oxygen limitation that alters the metabolism towards fermentation, and genetic perturbation affecting the source of energy generation from respiration to respiro-fermentative metabolism in relation to overflow metabolism. The intracellular metabolite of the upper glycolysis such as fructose 1,6-bisphosphate (FBP) plays an important role not only for flux sensing, but also for the regulation of the respiratory activity either directly or indirectly (via transcription factors) at higher growth rate. The glycolytic flux regulation is backed up (enhanced) by unphosphorylated EIIA and HPr of the phosphotransferase system (PTS) components, together with the sugar-phosphate stress regulation, where the transcriptional regulation is further modulated by post-transcriptional regulation via the degradation of mRNA (stability of mRNA) in Escherichia coli. Moreover, the channeling may also play some role in modulating the glycolytic cascade reactions.

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.

Lipidomics and RNA-Seq Study of Lipid Regulation in Aphis gossypii parasitized by Lysiphlebia japonica

The cotton-melon aphid, Aphis gossypii Glover, is a major insect pest worldwide. Lysiphlebia japonica (Ashmead) is an obligate parasitic wasp of A. gossypii, and has the ability to regulate lipid metabolism of the cotton-melon aphid. Lipids are known to play critical roles in energy homeostasis, membrane structure, and signaling. However, the parasitoid genes that regulate fat metabolism and lipid composition in aphids are not known. 34 glycerolipids and 248 glycerophospholipids were identified in this study. We have shown that a 3-day parasitism of aphids can induce significant changes in the content and acyl chain composition of triacylglycerols (TAGs) and subspecies composition of glycerophospholipids content and acyl chains. It also upregulate the expression of several genes involved in triacylglycerol synthesis and glycerophospholipid metabolism. Pathway analysis showed that a higher expression of genes involved in the tricarboxylic acid cycle and glycolysis pathways may contribute to TAGs synthesis in parasitized aphids. Interestingly, the higher expression of genes in the sphingomyelin pathway and reduced sphingomyelin content may be related to the reproductive ability of A. gossypii. We provide a comprehensive resource describing the molecular signature of parasitized A. gossypii particularly the changes associated with the lipid metabolism and discuss the biological and ecological significance of this change.

Hydrolysis of nicosulfuron under acidic environment caused by oxalate secretion of a novel Penicillium oxalicum strain YC-WM1

A novel Penicillium oxalicum strain YC-WM1, isolated from activated sludge, was found to be capable of completely degrading 100 mg/L of nicosulfuron within six days when incubated in GSM at 33 °C. Nicosulfuron degradation rates were affected by GSM initial pH, nicosulfuron initial concentration, glucose initial concentration, and carbon source. After inoculation, the medium pH was decreased from 7.0 to 4.5 within one day and remained at around 3.5 during the next few days, in which nicosulfuron degraded quickly. Besides, 100 mg/L of nicosulfuron were completely degraded in GSM medium at pH of 3.5 without incubation after 4 days. So, nicosulfuron degradation by YC-WM1 may be acidolysis. Based on HPLC analysis, GSM medium acidification was due to oxalate accumulation instead of lactic acid and oxalate, which was influenced by different carbon sources and had no relationship to nicosulfuron initial concentration. Furthermore, nicosulfuron broke into aminopyrimidine and pyridylsulfonamide as final products and could not be used as nitrogen source and mycelium didn’t increase in GSM medium. Metabolomics results further showed that nicosulfuron degradation was not detected in intracellular. Therefore, oxalate secretion in GSM medium by strain YC-WM1 led to nicosulfuron acidolysis.

A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). The Pearson correlation coefficient between experimental data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47 (k-ecoli457 is available for download at http://www.maranasgroup.com).

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.

Growth retardation of Escherichia coli by artificial increase of intracellular ATP

Overexpression of phosphoenolpyruvate carboxykinase (PCK) was reported to cause the harboring of higher intracellular ATP concentration in Escherichia coli, accompanied with a slower growth rate. For systematic determination of the relationship between the artificial increase of ATP and growth retardation, PCKWT enzyme was directly evolved in vitro and further overexpressed. The evolved PCK67 showed a 60% greater catalytic efficiency than that of PCKWT. Consequently, the PCK67-overexpressing E. coli showed the highest ATP concentration at the log phase of 1.45 μmol/gcell, with the slowest growth rate of 0.66 h(-1), while the PCKWT-overexpressing cells displayed 1.00 μmol/gcell ATP concentration with the growth rate of 0.84 h(-1) and the control had 0.28 μmol/gcell with 1.03 h(-1). To find a plausible reason, PCK-overexpressing cells in a steady state during chemostat growth were applied to monitor intracellular reactive oxygen species (ROS). Higher amount of intracellular ROS were observed as the ATP levels increased. To confirm the hypothesis of slower growth rate without perturbation of the carbon flux by PCK-overexpression, phototrophic Gloeobacter rhodopsin (GR) was expressed. The GR-expressing strain under illumination harbored 81% more ATP concentration along with 82% higher ROS, with a 54% slower maximum growth rate than the control, while both the GR-expressing strain under dark and dicarboxylate transporter (a control membrane protein)-expressing strain showed a lower ATP and increased ROS, and slower growth rate. Regardless of carbon flux changes, the artificial ATP increase was related to the ROS increase and it was reciprocally correlated to the maximum growth rate. To verify that the accumulated intracellular ROS were responsible for the growth retardation, glutathione was added to the medium to reduce the ROS. As a result, the growth retardation was restored by the addition of 0.1 mM glutathione. Anaerobic culture even enabled the artificial ATP-increased E. coli to grow faster than control. Collectively, it was concluded that artificial ATP increases inhibit the growth of E. coli due to the overproduction of ROS.

Fluxome study of Pseudomonas fluorescens reveals major reorganisation of carbon flux through central metabolic pathways in response to inactivation of the anti-sigma factor MucA

Background

The bacterium Pseudomonas fluorescens switches to an alginate-producing phenotype when the pleiotropic anti-sigma factor MucA is inactivated. The inactivation is accompanied by an increased biomass yield on carbon sources when grown under nitrogen-limited chemostat conditions. A previous metabolome study showed significant changes in the intracellular metabolite concentrations, especially of the nucleotides, in mucA deletion mutants compared to the wild-type. In this study, the P. fluorescens SBW25 wild-type and an alginate non-producing mucA- ΔalgC double-knockout mutant are investigated through model-based ¹³C-metabolic flux analysis (¹³C-MFA) to explore the physiological consequences of MucA inactivation at the metabolic flux level. Intracellular metabolite extracts from three carbon labelling experiments using fructose as the sole carbon source are analysed for ¹³C-label incorporation in primary metabolites by gas and liquid chromatography tandem mass spectrometry.

Results

From mass isotopomer distribution datasets, absolute intracellular metabolic reaction rates for the wild type and the mutant are determined, revealing extensive reorganisation of carbon flux through central metabolic pathways in response to MucA inactivation. The carbon flux through the Entner-Doudoroff pathway was reduced in the mucA- ΔalgC mutant, while flux through the pentose phosphate pathway was increased. Our findings also indicated flexibility of the anaplerotic reactions through down-regulation of the pyruvate shunt in the mucA- ΔalgC mutant and up-regulation of the glyoxylate shunt.

Conclusions

Absolute metabolic fluxes and metabolite levels give detailed, integrated insight into the physiology of this industrially, medically and agriculturally important bacterial species and suggest that the most efficient way of using a mucA- mutant as a cell factory for alginate production would be to use non-growing conditions and nitrogen deprivation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0148-0) contains supplementary material, which is available to authorized users.

The Energy Metabolism in Caenorhabditis elegans under The Extremely Low-Frequency Electromagnetic Field Exposure

A literal mountain of documentation generated in the past five decades showing unmistakable health hazards associated with extremely low-frequency electromagnetic fields (ELF-EMFs) exposure. However, the relation between energy mechanism and ELF-EMF exposure is poorly understood. In this study, Caenorhabditis elegans was exposed to 50 Hz ELF-EMF at intensities of 0.5, 1, 2, and 3 mT, respectively. Their metabolite variations were analyzed by GC-TOF/MS-based metabolomics. Although minimal metabolic variations and no regular pattern were observed, the contents of energy metabolism-related metabolites such as pyruvic acid, fumaric acid, and L-malic acid were elevated in all the treatments. The expressions of nineteen related genes that encode glycolytic enzymes were analyzed by using quantitative real-time PCR. Only genes encoding GAPDH were significantly upregulated (P < 0.01), and this result was further confirmed by western blot analysis. The enzyme activity of GAPDH was increased (P < 0.01), whereas the total intracellular ATP level was decreased. While no significant difference in lifespan, hatching rate and reproduction, worms exposed to ELF-EMF exhibited less food consumption compared with that of the control (P < 0.01). In conclusion, C. elegans exposed to ELF-EMF have enhanced energy metabolism and restricted dietary, which might contribute to the resistance against exogenous ELF-EMF stress.

Metabolic Regulation and Coordination of the Metabolism in Bacteria in Response to a Variety of Growth Conditions

Living organisms have sophisticated but well-organized regulation system. It is important to understand the metabolic regulation mechanisms in relation to growth environment for the efficient design of cell factories for biofuels and biochemicals production. Here, an overview is given for carbon catabolite regulation, nitrogen regulation, ion, sulfur, and phosphate regulations, stringent response under nutrient starvation as well as oxidative stress regulation, redox state regulation, acid-shock, heat- and cold-shock regulations, solvent stress regulation, osmoregulation, and biofilm formation, and quorum sensing focusing on Escherichia coli metabolism and others. The coordinated regulation mechanisms are of particular interest in getting insight into the principle which governs the cell metabolism. The metabolism is controlled by both enzyme-level regulation and transcriptional regulation via transcription factors such as cAMP-Crp, Cra, Csr, Fis, P(II)(GlnB), NtrBC, CysB, PhoR/B, SoxR/S, Fur, MarR, ArcA/B, Fnr, NarX/L, RpoS, and (p)ppGpp for stringent response, where the timescales for enzyme-level and gene-level regulations are different. Moreover, multiple regulations are coordinated by the intracellular metabolites, where fructose 1,6-bisphosphate (FBP), phosphoenolpyruvate (PEP), and acetyl-CoA (AcCoA) play important roles for enzyme-level regulation as well as transcriptional control, while α-ketoacids such as α-ketoglutaric acid (αKG), pyruvate (PYR), and oxaloacetate (OAA) play important roles for the coordinated regulation between carbon source uptake rate and other nutrient uptake rate such as nitrogen or sulfur uptake rate by modulation of cAMP via Cya.

Mass-spectrometry-based microbial metabolomics: recent developments and applications

Metabolomics is an omics technique aiming at qualitatively and quantitatively describing a metabolome by various analytical platforms. It is an indispensable component of modern systems biology. Microbial metabolomics can be roughly classified as metabolic footprint analysis and metabolic fingerprint analysis depending on the analyte origins. Both of them have been beneficial to microbiological research for different reasons. Mass spectrometry and nuclear magnetic resonance spectroscopy techniques are popular analytical strategies prevailing in the metabolomics field. In this review, chromatography-mass-spectrometry-based microbial metabolomic analysis steps are summarized, including sample collection, metabolite extraction, instrument analysis, and data analysis. Moreover, their applications in some representative fields are discussed as examples. The aim of this review is to present briefly recent technical advances in mass-spectrometry-based analysis, and to highlight the value of modern applications of microbial metabolomics.

Metabolic flux analysis of Escherichia coli knockouts: lessons from the Keio collection and future outlook

Cellular metabolic and regulatory systems are of fundamental interest to biologists and engineers. Incomplete understanding of these complex systems remains an obstacle to progress in biotechnology and metabolic engineering. An established method for obtaining new information on network structure, regulation and dynamics is to study the cellular system following a perturbation such as a genetic knockout. The Keio collection of all viable Escherichia coli single-gene knockouts is facilitating a systematic investigation of the regulation and metabolism of E. coli. Of all omics measurements available, the metabolic flux profile (the fluxome) provides the most direct and relevant representation of the cellular phenotype. Recent advances in (13)C-metabolic flux analysis are now permitting highly precise and accurate flux measurements for investigating cellular systems and guiding metabolic engineering efforts.

Metabolic flux responses to genetic modification for shikimic acid production by Bacillus subtilis strains

BACKGROUND

Shikimic acid (SA) is a key chiral starting molecule for the synthesis of the neuramidase inhibitor GS4104 against viral influenza. Microbial production of SA has been extensively investigated in Escherichia coli, and to a less extent in Bacillus subtilis. However, metabolic flux of the high SA-producing strains has not been explored. In this study, we constructed with genetic manipulation and further determined metabolic flux with 13C-labeling test of high SA-producing B. subtilis strains.

RESULTS

B. subtilis 1A474 had a mutation in SA kinase gene (aroI) and accumulated 1.5 g/L of SA. Overexpression of plasmid-encoded aroA, aroB, aroC or aroD in B. subtilis revealed that aroD had the most significantly positive effects on SA production. Simultaneous overexpression of genes for 3-deoxy-D-arabinoheptulosonate-7-phosphate synthase (aroA) and SA dehydrogenase (aroD) in B. subtilis BSSA/pSAAroA/pDGSAAroD resulted in SA production of 3.2 g/L. 13C-Metabolic flux assay (MFA) on the two strains BSSA/pHCMC04/pDG148-stu and BSSA/pSAAroA/pDGSAAroD indicated the carbon flux from glucose to SA increased to 4.6% in BSSA/pSAAroA/pDGSAAroD from 1.9% in strain BSSA/pHCMC04/pDG148-stu. The carbon flux through tricarboxylic acid cycle significantly reduced, while responses of the pentose phosphate pathway and the glycolysis to high SA production were rather weak, in the strain BSSA/pSAAroA/pDGSAAroD. Based on the results from MFA, two potential targets for further optimization of SA production were identified. Experiments on genetic deletion of phosphoenoylpyruvate kinase gene confirmed its positive influence on SA production, while the overexpression of the transketolase gene did not lead to increase in SA production.

CONCLUSION

Of the genes involved in shikimate pathway in B. subtilis, aroD exerted most significant influence on SA accumulation. Overexpression of plasmid-encoded aroA and aroD doubled SA production than its parent strain. MFA revealed metabolic flux redistribution among phosphate pentose pathway, glycolysis, TCA cycle in the low and high SA-producing B. subtilis strains. The high SA producing strain BSSA/pSAAroA/pDGSAAroD had increased carbon flux into shikimate pathway and reduced flux into TCA cycle.

Physiological and transcriptional characterization of Escherichia coli strains lacking interconversion of phosphoenolpyruvate and pyruvate when glucose and acetate are coutilized

Phosphoenolpyruvate (PEP) is a precursor involved in the biosynthesis of aromatics and other valuable compounds in Escherichia coli. The PEP:carbohydrate phosphotransferase system (PTS) is the major glucose transport system and the largest PEP consumer. To increase intracellular PEP availability for aromatics production purposes, mutant strains of E. coli JM101 devoid of the ptsHIcrr operon (PB11 strain) have been previously generated. In this derivative, transport and growth rate on glucose decreased significantly. A laboratory evolved strain derived from PB11 that partially recovered its growth capacity on glucose was named PB12. In the present study, we blocked carbon skeletons interchange between PEP and pyruvate (PYR) in these ptsHIcrr⁻ strains by deleting the pykA, pykF, and ppsA genes. The PB11 pykAF⁻ppsA⁻ strain exhibited no growth on glucose or acetate alone, but it was viable when both substrates were consumed simultaneously. In contrast, the PB12 pykAF⁻ppsA⁻ strain displayed a low growth rate on glucose or acetate alone, but in the mixture, growth was significantly improved. RT-qPCR expression analysis of PB11 pykAF⁻ppsA⁻ growing with both carbon sources showed a downregulation of all central metabolic pathways compared with its parental PB11 strain. Under the same conditions, transcription of most of the genes in PB12 pykAF⁻ppsA⁻ did not change, and few like aceBAK, sfcA, and poxB were overexpressed compared with PB12. We explored the aromatics production capabilities of both ptsHIcrr⁻pykAF⁻ppsA⁻ strains and the engineered PB12 pykAF⁻ppsA⁻tyrR⁻pheA^ev2+/pJLBaroG^fbrtktA enhanced the yield of aromatic compounds when coutilizing glucose and acetate compared with the control strain PB12 tyrR⁻pheA^ev2+/pJLBaroG^fbrtktA. Biotechnol. Bioeng. 2014;111: 1150–1160. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

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.

Structural control of metabolic flux

Organisms have to continuously adapt to changing environmental conditions or undergo developmental transitions. To meet the accompanying change in metabolic demands, the molecular mechanisms of adaptation involve concerted interactions which ultimately induce a modification of the metabolic state, which is characterized by reaction fluxes and metabolite concentrations. These state transitions are the effect of simultaneously manipulating fluxes through several reactions. While metabolic control analysis has provided a powerful framework for elucidating the principles governing this orchestrated action to understand metabolic control, its applications are restricted by the limited availability of kinetic information. Here, we introduce structural metabolic control as a framework to examine individual reactions' potential to control metabolic functions, such as biomass production, based on structural modeling. The capability to carry out a metabolic function is determined using flux balance analysis (FBA). We examine structural metabolic control on the example of the central carbon metabolism of Escherichia coli by the recently introduced framework of functional centrality (FC). This framework is based on the Shapley value from cooperative game theory and FBA, and we demonstrate its superior ability to assign “share of control” to individual reactions with respect to metabolic functions and environmental conditions. A comparative analysis of various scenarios illustrates the usefulness of FC and its relations to other structural approaches pertaining to metabolic control. We propose a Monte Carlo algorithm to estimate FCs for large networks, based on the enumeration of elementary flux modes. We further give detailed biological interpretation of FCs for production of lactate and ATP under various respiratory conditions.

Insight into the functioning of metabolic control to meet changing demands is a first step in rational engineering of biological systems towards a desired behavior. Metabolic control analysis provides the means to examine the impact of change of reaction fluxes on a specific target flux based on kinetic modeling, but suffers from limitations of the kinetic approach. Here, we introduce and analyze structural metabolic control as a framework to overcome these limitations. We utilize functional centrality, a framework based on the Shapley value from cooperative game theory and flux balance analysis, to determine the contribution of individual reactions to the functions accomplished by a metabolic network. These contributions, in turn, depend on the control exerted on the remaining network. Functional centrality provides the mathematical means to gain further understanding of metabolic control. The potential applications range from facilitating strategies of rational strain design to drug target identification.

Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations.

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.

Genetic analysis of D-xylose metabolism pathways in Gluconobacter oxydans 621H

D-xylose is one of the most abundant carbohydrates in nature. This work focuses on xylose metabolism of Gluconobacter oxydans as revealed by a few studies conducted to understand xylose utilization by this strain. Interestingly, the G. oxydans 621H Δmgdh strain (deficient in membrane-bound glucose dehydrogenase) was greatly inhibited when grown on xylose and no xylonate accumulation was observed in the medium. These experimental observations suggested that the mgdh gene was responsible for the conversion of xylose to xylonate in G. oxydans, which was also verified by whole-cell biotransformation. Since 621H Δmgdh could still grow on xylose in a very small way, two seemingly important genes in the oxo-reductive pathway for xylose metabolism, a xylitol dehydrogenase-encoding gox0865 (xdh) gene and a putative xylulose kinase-encoding gox2214 (xk) gene, were knocked out to investigate the effects of both genes on xylose metabolism. The results showed that the gox2214 gene was not involved in xylose metabolism, and there might be other genes encoding xylulose kinase. Though the gox0865 gene played a less important role in xylose metabolism compared to the mgdh gene, it was significant in xylitol utilization in G. oxydans, which meant that gox0865 was a necessary gene for the oxo-reductive pathway of xylose in vivo. To sum up, when xylose was used as the carbon source, the majority of xylose was directly oxidized to xylonate for further metabolism in G. oxydans, whereas only a minor part of xylose was metabolized by the oxo-reductive pathway.

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 flux ratio analysis and multi-objective optimization revealed a globally conserved and coordinated metabolic response of E. coli to paraquat-induced oxidative stress

The ability of a microorganism to adapt to changes in the environment, such as in nutrient or oxygen availability, is essential for its competitive fitness and survival. The cellular objective and the strategy of the metabolic response to an extreme environment are therefore of tremendous interest and, thus, have been increasingly explored. However, the cellular objective of the complex regulatory structure of the metabolic changes has not yet been fully elucidated and more details regarding the quantitative behaviour of the metabolic flux redistribution are required to understand the systems-wide biological significance of this response. In this study, the intracellular metabolic flux ratios involved in the central carbon metabolism were determined by fractional (13)C-labeling and metabolic flux ratio analysis (MetaFoR) of the wild-type E. coli strain JM101 at an oxidative environment in a chemostat. We observed a significant increase in the flux through phosphoenolpyruvate carboxykinase (PEPCK), phosphoenolpyruvate carboxylase (PEPC), malic enzyme (MEZ) and serine hydroxymethyltransferase (SHMT). We applied an ε-constraint based multi-objective optimization to investigate the trade-off relationships between the biomass yield and the generation of reductive power using the in silico iJR904 genome-scale model of E. coli K-12. The theoretical metabolic redistribution supports that the trans-hydrogenase pathway should not play a direct role in the defence mounted by E. coli against oxidative stress. The agreement between the measured ratio and the theoretical redistribution established the significance of NADPH synthesis as the goal of the metabolic reprogramming that occurs in response to oxidative stress. Our work presents a framework that combines metabolic flux ratio analysis and multi-objective optimization to investigate the metabolic trade-offs that occur under varied environmental conditions. Our results led to the proposal that the metabolic response of E. coli to paraquat-induced oxidative stress is globally conserved and coordinated.

Modification and evolution of Gluconobacter oxydans for enhanced growth and biotransformation capabilities at low glucose concentration

Gluconobacter oxydans is widely used in several biotechnological applications, where sorbitol or mannitol is commonly used as carbon source at high concentration. In this study, a membrane-bound glucose dehydrogenase-deficient strain (GDHK) was constructed to eliminate growth problems on glucose caused by direct oxidation of glucose in the medium. To achieve improved growth properties for the GDHK strain on glucose, a laboratory adaptive evolution experiment was performed with glucose as the sole carbon source. Results indicated evident, albeit modest, improvements in cell growth after a 50-day (about 430 generations) experimental evolution on glucose. The maximum specific growth rate and biomass yield of the resulting GDHE50 strain were increased around 1.35- to 1.4-fold compared with those of the GDHK strain. Meanwhile, two types of biotransformation reactions using resting cells of G. oxydans were investigated. Significant elevations in biotransformation performance of the GHDE50 strain were observed in comparison with that of the wild-type strain. In addition, resting cells of the GDHE50 strain grown on a relatively low concentration of glucose (10 g/l) could catalyze the biotransformation of glycerol to dihydroxyacetone and ethylene glycol to glycolic acid as efficient as the wild-type G. oxydans cultured on higher concentration of sorbitol or other carbon sources. These results suggest very favorable prospects of using glucose to lower production cost in many important industrial biocatalysis and biotransformation processes.

Catabolic regulation analysis of Escherichia coli and its crp, mlc, mgsA, pgi and ptsG mutants

BACKGROUND

Most bacteria can use various compounds as carbon sources. These carbon sources can be either co-metabolized or sequentially metabolized, where the latter phenomenon typically occurs as catabolite repression. From the practical application point of view of utilizing lignocellulose for the production of biofuels etc., it is strongly desirable to ferment all sugars obtained by hydrolysis from lignocellulosic materials, where simultaneous consumption of sugars would benefit the formation of bioproducts. However, most organisms consume glucose prior to consumption of other carbon sources, and exhibit diauxic growth. It has been shown by fermentation experiments that simultaneous consumption of sugars can be attained by ptsG, mgsA mutants etc., but its mechanism has not been well understood. It is strongly desirable to understand the mechanism of metabolic regulation for catabolite regulation to improve the performance of fermentation.

RESULTS

In order to make clear the catabolic regulation mechanism, several continuous cultures were conducted at different dilution rates of 0.2, 0.4, 0.6 and 0.7 h⁻¹ using wild type Escherichia coli. The result indicates that the transcript levels of global regulators such as crp, cra, mlc and rpoS decreased, while those of fadR, iclR, soxR/S increased as the dilution rate increased. These affected the metabolic pathway genes, which in turn affected fermentation result where the specific glucose uptake rate, the specific acetate formation rate, and the specific CO₂ evolution rate (CER) were increased as the dilution rate was increased. This was confirmed by the ¹³C-flux analysis. In order to make clear the catabolite regulation, the effect of crp gene knockout (Δcrp) and crp enhancement (crp⁺) as well as mlc, mgsA, pgi and ptsG gene knockout on the metabolism was then investigated by the continuous culture at the dilution rate of 0.2 h⁻¹ and by some batch cultures. In the case of Δcrp (and also Δmlc) mutant, TCA cycle and glyoxylate were repressed, which caused acetate accumulation. In the case of crp⁺ mutant, glycolysis, TCA cycle, and gluconeogenesis were activated, and simultaneous consumption of multiple carbon sources can be attained, but the glucose consumption rate became less due to repression of ptsG and ptsH by the activation of Mlc. Simultaneous consumption of multiple carbon sources could be attained by mgsA, pgi, and ptsG mutants due to increase in crp as well as cyaA, while glucose consumption rate became lower.

CONCLUSIONS

The transcriptional catabolite regulation mechanism was made clear for the wild type E. coli, and its crp, mlc, ptsG, pgi, and mgsA gene knockout mutants. The results indicate that catabolite repression can be relaxed and crp as well as cyaA can be increased by crp⁺, mgsA, pgi, and ptsG mutants, and thus simultaneous consumption of multiple carbon sources including glucose can be made, whereas the glucose uptake rate became lower as compared to wild type due to inactivation of ptsG in all the mutants considered.

13C-metabolic flux analysis for batch culture of Escherichia coli and its Pyk and Pgi gene knockout mutants based on mass isotopomer distribution of intracellular metabolites

Since most bio-production processes are conducted in a batch or fed-batch manner, the evaluation of metabolism with respect to time is highly desirable. Toward this aim, we applied (13)C-metabolic flux analysis to nonstationary conditions by measuring the mass isotopomer distribution of intracellular metabolites. We performed our analysis on batch cultures of wild-type Escherichia coli, as well as on Pyk and Pgi mutants, obtained the fluxes and metabolite concentrations as a function of time. Our results for the wild-type indicated that the TCA cycle flux tended to increase during growth on glucose. Following glucose exhaustion, cells controlled the branch ratio between the glyoxylate pathway and the TCA cycle, depending on the availability of acetate. In the Pyk mutant, the concentrations of glycolytic intermediates changed drastically over time due to the dumping and feedback inhibition caused by PEP accumulation. Nevertheless, the flux distribution and free amino acid concentrations changed little. The growth rate and the fluxes remained constant in the Pgi mutant and the glucose-6-phosphate dehydrogenase reaction was the rate-limiting step. The measured fluxes were compared with those predicted by flux balance analysis using maximization of biomass yield or ATP production. Our findings indicate that the objective function of biosynthesis became less important as time proceeds on glucose in the wild-type, while it remained highly important in the Pyk mutant. Furthermore, ATP production was the primary objective function in the Pgi mutant. This study demonstrates how cells adjust their metabolism in response to environmental changes and/or genetic perturbations in the batch cultivation.

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.

13C-tracer and gas chromatography-mass spectrometry analyses reveal metabolic flux distribution in the oleaginous microalga Chlorella protothecoides

The green alga Chlorella protothecoides has received considerable attention because it accumulates neutral triacylglycerols, commonly regarded as an ideal feedstock for biodiesel production. In order to gain a better understanding of its metabolism, tracer experiments with [U-(13)C]/[1-(13)C]glucose were performed with heterotrophic growth of C. protothecoides for identifying the metabolic network topology and estimating intracellular fluxes. Gas chromatography-mass spectrometry analysis tracked the labeling patterns of protein-bound amino acids, revealing a metabolic network consisting of the glycolysis, the pentose phosphate pathway, and the tricarboxylic acid cycle with inactive glyoxylate shunt. Evidence of phosphoenolpyruvate carboxylase, phosphoenolpyruvate carboxykinase, and malic enzyme activity was also obtained. It was demonstrated that the relative activity of the pentose phosphate pathway to glycolysis under nitrogen-limited environment increased, reflecting excess NADPH requirements for lipid biosynthesis. Although the growth rate and cellular oil content were significantly altered in response to nitrogen limitation, global flux distribution of C. protothecoides remained stable, exhibiting the rigidity of central carbon metabolism. In conclusion, quantitative knowledge on the metabolic flux distribution of oleaginous alga obtained in this study may be of value in designing strategies for metabolic engineering of desirable bioproducts.