13C Metabolic Flux Analysis Research Articles

GC/MS-based 13C metabolic flux analysis resolves the parallel and cyclic photomixotrophic metabolism of Synechocystis sp. PCC 6803 and selected deletion mutants including the Entner-Doudoroff and phosphoketolase pathways

BackgroundCyanobacteria receive huge interest as green catalysts. While exploiting energy from sunlight, they co-utilize sugar and CO2. This photomixotrophic mode enables fast growth and high cell densities, opening perspectives for sustainable biomanufacturing. The model cyanobacterium Synechocystis sp. PCC 6803 possesses a complex architecture of glycolytic routes for glucose breakdown that are intertwined with the CO2-fixing Calvin-Benson-Bassham (CBB) cycle. To date, the contribution of these pathways to photomixotrophic metabolism has remained unclear.ResultsHere, we developed a comprehensive approach for 13C metabolic flux analysis of Synechocystis sp. PCC 6803 during steady state photomixotrophic growth. Under these conditions, the Entner-Doudoroff (ED) and phosphoketolase (PK) pathways were found inactive but the microbe used the phosphoglucoisomerase (PGI) (63.1%) and the oxidative pentose phosphate pathway (OPP) shunts (9.3%) to fuel the CBB cycle. Mutants that lacked the ED pathway, the PK pathway, or phosphofructokinases were not affected in growth under metabolic steady-state. An ED pathway-deficient mutant (Δeda) exhibited an enhanced CBB cycle flux and increased glycogen formation, while the OPP shunt was almost inactive (1.3%). Under fluctuating light, ∆eda showed a growth defect, different to wild type and the other deletion strains.ConclusionsThe developed approach, based on parallel 13C tracer studies with GC–MS analysis of amino acids, sugars, and sugar derivatives, optionally adding NMR data from amino acids, is valuable to study fluxes in photomixotrophic microbes to detail. In photomixotrophic cells, PGI and OPP form glycolytic shunts that merge at switch points and result in synergistic fueling of the CBB cycle for maximized CO2 fixation. However, redirected fluxes in an ED shunt-deficient mutant and the impossibility to delete this shunt in a GAPDH2 knockout mutant, indicate that either minor fluxes (below the resolution limit of 13C flux analysis) might exist that could provide catalytic amounts of regulatory intermediates or alternatively, that EDA possesses additional so far unknown functions. These ideas require further experiments.

Validation-based model selection for 13C metabolic flux analysis with uncertain measurement errors.

Accurate measurements of metabolic fluxes in living cells are central to metabolism research and metabolic engineering. The gold standard method is model-based metabolic flux analysis (MFA), where fluxes are estimated indirectly from mass isotopomer data with the use of a mathematical model of the metabolic network. A critical step in MFA is model selection: choosing what compartments, metabolites, and reactions to include in the metabolic network model. Model selection is often done informally during the modelling process, based on the same data that is used for model fitting (estimation data). This can lead to either overly complex models (overfitting) or too simple ones (underfitting), in both cases resulting in poor flux estimates. Here, we propose a method for model selection based on independent validation data. We demonstrate in simulation studies that this method consistently chooses the correct model in a way that is independent on errors in measurement uncertainty. This independence is beneficial, since estimating the true magnitude of these errors can be difficult. In contrast, commonly used model selection methods based on the χ2-test choose different model structures depending on the believed measurement uncertainty; this can lead to errors in flux estimates, especially when the magnitude of the error is substantially off. We present a new approach for quantification of prediction uncertainty of mass isotopomer distributions in other labelling experiments, to check for problems with too much or too little novelty in the validation data. Finally, in an isotope tracing study on human mammary epithelial cells, the validation-based model selection method identified pyruvate carboxylase as a key model component. Our results argue that validation-based model selection should be an integral part of MFA model development.

On maintenance and metabolisms in soil microbial communities

Biochemistry is an essential yet undervalued aspect of soil ecology, especially when analyzing soil C cycling. We assume, based on tradition, intuition or hope, that the complexity of biochemistry is confined to the microscopic world, and can be ignored when dealing with whole soil systems. This opinion paper draws attention to patterns caused by basic biochemical processes that permeate the world of ecosystem processes. From these patterns, we can estimate activities of the biochemical reactions of the central C metabolic network and gain insights into the ecophysiology of microbial biosynthesis, growth, and maintenance energy requirements: important components of Carbon Use Efficiency (CUE). We show that glucose is processed via the Embden-Meyerhof-Parnas glycolysis in one soil, but via Pentose Phosphate or Entner-Doudoroff pathways in two other soils. However, notwithstanding this metabolic diversity, glucose use efficiency is high and thus substrate use for maintenance energy and overflow respiration is low in these soils. These results contradict current dogma, based on four decades of debate in soil ecology, that the maintenance energy demand in soil communities is a quantitative important, although variable, component of soil community energy metabolism. We identify three main shortcomings in our current understanding of substrate use efficiency: 1) in numeric and conceptual models, we lack appreciation of the strategies that microbes employ to quickly reduce energy needs in response to starvation; 2) in order to understand variation in CUE, we need to improve our understanding of the processes of exudation (including all changes in allocation of C from the cell soluble to insoluble fraction and extracellular environment) and microbial turnover; and 3) whether tracer experiments can be used to measure the long-term substrate use efficiency of soil microbial communities depends critically on the ability and speed with which non-growing cells take up tracer substrates and metabolism activates and subsequently de-activates in response to starvation, as well as on how cellular activities scale to the community level. To move the field of soil ecology forward, future research must consider the details of microbial ecophysiology and develop new tools that enable direct measurement of microbial functioning in intact soils. We submit that 13C metabolic flux analysis is one of those new tools.

Mutants lacking global regulators, fis and arcA, in Escherichia coli enhanced growth fitness under acetate metabolism by pathway reprogramming.

Global regulatory transcription factors play a significant role in controlling microbial metabolism under genetic and environmental perturbations. A system-level effect of carbon sources such as acetate on microbial metabolism under disrupted global regulators has not been well established. Acetate is one of the major substrates available in various nutrient niches such as the mammalian gut and a keto diet. A substantial amount of acetate gets secreted in aerobic metabolism. Therefore, investigating the study on acetate metabolism is highly significant. It is known that the global regulatorsfisandarcAregulate acetate uptake genes inE. coliunder glucose conditions. This study deciphered the growth and flux distribution ofE. colitranscription regulatory knockouts Δfis,ΔarcAand double deletion mutant, ΔarcAΔfisunder acetate using 13C-metabolic flux analysis (MFA), which has not been investigated before. We observed that the mutants exhibited an expeditious growth rate (~ 1.2-1.6-fold) with a proportionate increase in acetate uptake rates compared to the wild type. 13C-MFA displayed the distinct metabolic reprogramming of intracellular fluxes via the TCA cycle, anaplerotic pathway and gluconeogenesis, which conferred an advantage of a faster growth rate with better carbon usage in all the mutants. This resulted in higher metabolic fluxes through the TCA cycle (~ 18-90%), lower gluconeogenesis (~ 15-35%) and higher CO2 and ATP production with the proportional increase in growth rate. The study reveals a novel insight by stating the sub-optimality of the wild-type strain grown under acetate substrate aerobically. These mutant strains efficiently oxidize acetate, thus acting as potential candidates for the biosynthesis of isoprenoids, biofuels, vitamins and various pharmaceutical products.Key Points• Mutants exhibited a better balance between energy and precursor synthesis than WT.• Leveraged in the unravelling of regulatory control under various nutrient shifts.• Metabolic readjustment resulted in optimal biomass requirement and faster growth.

Quantitative metabolic fluxes regulated by trans-omic networks

Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.

13C-metabolic flux analysis of Clostridium ljungdahlii illuminates its core metabolism under mixotrophic culture conditions

Carbon dioxide-fixing acetogenic bacteria (acetogens) utilizing the Wood-Ljungdahl Pathway (WLP) play an important role in CO2 fixation in the biosphere and in the development of biological processes – alone or in cocultures, under both autotrophic and mixotrophic conditions – for production of chemicals and fuels. To date, limited work has been reported in experimentally validating and quantifying reaction fluxes of their core metabolic pathways. Here, the core metabolic model of the acetogen Clostridium ljungdahlii was interrogated using 13C-metabolic flux analysis (13C-MFA), which required the development of a new defined culture medium. Autotrophic, heterotrophic, and mixotrophic growth in defined medium was possible by adding 1 mM methionine to replace yeast extract. Our 13C-MFA found an incomplete TCA cycle and inactive core pathways/reactions, notably those of the oxidative pentose phosphate pathway, Entner-Doudoroff pathway, and malate dehydrogenase. 13C-MFA during mixotrophic growth using the parallel tracers [1–13C]fructose, [1,2–13C]fructose, [1,2,3–13C]fructose, and [U–13C]asparagine found that externally supplied CO2 contributed the majority of carbon consumed. All internally-produced CO2 from the catabolism of asparagine and fructose was consumed by the WLP. While glycolysis of fructose was active, it was not a major contributor to overall production of ATP, NADH, and acetyl-CoA. Gluconeogenic reactions were active despite the availability of organic carbon. Asparagine was catabolized equally via conversion to threonine and subsequent cleavage to produce acetaldehyde and glycine, and via deamination to fumarate and then the anaplerotic conversion of malate to pyruvate. Both pathways for asparagine catabolism produced acetyl-CoA, either directly via pyruvate or indirectly via the WLP. Cofactor stoichiometry based on our data predicted an essentially zero flux through the ferredoxin-dependent transhydrogenase (Nfn) reaction. Instead, nearly all of NADPH generated from the hydrogenase reaction was consumed by the WLP. Reduced ferredoxin produced by the hydrogenase reaction and glycolysis was mostly used for ATP generation via the RNF/ATPase system, with the remainder consumed by the WLP. NADH produced by RNF/ATPase was entirely consumed via the WLP.

MetAMDB: Metabolic Atom Mapping Database.

MetAMDB is an open-source metabolic atom mapping database, providing atom mappings for around 43,000 metabolic reactions. Each atom mapping can be inspected and downloaded either as an RXN file or as a graphic in SVG format. In addition, MetAMDB offers the possibility of automatically creating atom mapping models based on user-specified metabolic networks. These models can be of any size (small to genome-scale) and can subsequently be used in standard C metabolic flux analysis software.

Assessing the impact of substrate-level enzyme regulations limiting ethanol titer in Clostridium thermocellum using a core kinetic model

Clostridium thermocellum is a promising candidate for consolidated bioprocessing because it can directly ferment cellulose to ethanol. Despite significant efforts, achieved yields and titers fall below industrially relevant targets. This implies that there still exist unknown enzymatic, regulatory, and/or possibly thermodynamic bottlenecks that can throttle back metabolic flow. By (i) elucidating internal metabolic fluxes in wild-type C. thermocellum grown on cellobiose via 13C-metabolic flux analysis (13C-MFA), (ii) parameterizing a core kinetic model, and (iii) subsequently deploying an ensemble-docking workflow for discovering substrate-level regulations, this paper aims to reveal some of these factors and expand our knowledgebase governing C. thermocellum metabolism. Generated 13C labeling data were used with 13C-MFA to generate a wild-type flux distribution for the metabolic network. Notably, flux elucidation through MFA alluded to serine generation via the mercaptopyruvate pathway. Using the elucidated flux distributions in conjunction with batch fermentation process yield data for various mutant strains, we constructed a kinetic model of C. thermocellum core metabolism (i.e. k-ctherm138). Subsequently, we used the parameterized kinetic model to explore the effect of removing substrate-level regulations on ethanol yield and titer. Upon exploring all possible simultaneous (up to four) regulation removals we identified combinations that lead to many-fold model predicted improvement in ethanol titer. In addition, by coupling a systematic method for identifying putative competitive inhibitory mechanisms using K-FIT kinetic parameterization with the ensemble-docking workflow, we flagged 67 putative substrate-level inhibition mechanisms across central carbon metabolism supported by both kinetic formalism and docking analysis.

Isotopically nonstationary 13C metabolic flux analysis in resting and activated human platelets

Platelet metabolism is linked to platelet hyper- and hypoactivity in numerous human diseases. Developing a detailed understanding of the link between metabolic shifts and platelet activation state is integral to improving human health. Here, we show the first application of isotopically nonstationary 13C metabolic flux analysis to quantitatively measure carbon fluxes in both resting and thrombin activated platelets. Metabolic flux analysis results show that resting platelets primarily metabolize glucose to lactate via glycolysis, while acetate is oxidized to fuel the tricarboxylic acid cycle. Upon activation with thrombin, a potent platelet agonist, platelets increase their uptake of glucose 3-fold. This results in an absolute increase in flux throughout central metabolism, but when compared to resting platelets they redistribute carbon dramatically. Activated platelets decrease relative flux to the oxidative pentose phosphate pathway and TCA cycle from glucose and increase relative flux to lactate. These results provide the first report of reaction-level carbon fluxes in platelets and allow us to distinguish metabolic fluxes with much higher resolution than previous studies.

Coordinated reprogramming of metabolism and cell function in adipocytes from proliferation to differentiation

Adipose tissue plays a major role in regulating lipid and energy homeostasis by storing excess nutrients, releasing energetic substrates through lipolysis, and regulating metabolism of other tissues and organs through endocrine and paracrine signaling. Adipocytes within fat tissues store excess nutrients through increased cell number (hyperplasia), increased cell size (hypertrophy), or both. The differentiation of pre-adipocytes into mature lipid-accumulating adipocytes requires a complex interaction of metabolic pathways that is still incompletely understood. Here, we applied parallel labeling experiments and 13C-metabolic flux analysis to quantify precise metabolic fluxes in proliferating and differentiated 3T3-L1 cells, a widely used model to study adipogenesis. We found that morphological and biomass composition changes in adipocytes were accompanied by significant shifts in metabolic fluxes, encompassing all major metabolic pathways. In contrast to proliferating cells, differentiated adipocytes 1) increased glucose uptake and redirected glucose utilization from lactate production to lipogenesis and energy generation; 2) increased pathway fluxes through glycolysis, oxidative pentose phosphate pathway and citric acid cycle; 3) reduced lactate secretion, resulting in increased ATP generation via oxidative phosphorylation; 4) rewired glutamine metabolism, from glutaminolysis to de novo glutamine synthesis; 5) increased cytosolic NADPH production, driven mostly by increased cytosolic malic enzyme flux; 6) increased production of monounsaturated C16:1; and 7) activated a mitochondrial pyruvate cycle through simultaneous activity of pyruvate carboxylase, malate dehydrogenase and malic enzyme. Taken together, these results quantitatively highlight the complex interplay between pathway fluxes and cell function in adipocytes, and suggest a functional role for metabolic reprogramming in adipose differentiation and lipogenesis.

Computational Framework for Machine-Learning-Enabled 13C Fluxomics.

13C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

Establishment of a GC-MS-based 13 C-positional isotopomer approach suitable for investigating metabolic fluxes in plant primary metabolism.

13 C-Metabolic flux analysis (13 C-MFA) has greatly contributed to our understanding of plant metabolic regulation. However, the generation of detailed in vivo flux maps remains a major challenge. Flux investigations based on nuclear magnetic resonance have resolved small networks with high accuracy. Mass spectrometry (MS) approaches have broader potential, but have hitherto been limited in their power to deduce flux information due to lack of atomic level position information. Herein we established a gas chromatography (GC) coupled to MS-based approach that provides 13 C-positional labelling information in glucose, malate and glutamate (Glu). A map of electron impact (EI)-mediated MS fragmentation was created and validated by 13 C-positionally labelled references via GC-EI-MS and GC-atmospheric pressure chemical ionization-MS technologies. The power of the approach was revealed by analysing previous 13 C-MFA data from leaves and guard cells, and 13 C-HCO3 labelling of guard cells harvested in the dark and after the dark-to-light transition. We demonstrated that the approach is applicable to established GC-EI-MS-based 13 C-MFA without the need for experimental adjustment, but will benefit in the future from paired analyses by the two GC-MS platforms. We identified specific glucose carbon atoms that are preferentially labelled by photosynthesis and gluconeogenesis, and provide an approach to investigate the phosphoenolpyruvate carboxylase (PEPc)-derived 13 C-incorporation into malate and Glu. Our results suggest that gluconeogenesis and the PEPc-mediated CO2 assimilation into malate are activated in a light-independent manner in guard cells. We further highlight that the fluxes from glycolysis and PEPc toward Glu are restricted by the mitochondrial thioredoxin system in illuminated leaves.

Robustifying Experimental Tracer Design for13C-Metabolic Flux Analysis.

13C metabolic flux analysis (MFA) has become an indispensable tool to measure metabolic reaction rates (fluxes) in living organisms, having an increasingly diverse range of applications. Here, the choice of the13C labeled tracer composition makes the difference between an information-rich experiment and an experiment with only limited insights. To improve the chances for an informative labeling experiment, optimal experimental design approaches have been devised for13C-MFA, all relying on some a priori knowledge about the actual fluxes. If such prior knowledge is unavailable, e.g., for research organisms and producer strains, existing methods are left with a chicken-and-egg problem. In this work, we present a general computational method, termed robustified experimental design (R-ED), to guide the decision making about suitable tracer choices when prior knowledge about the fluxes is lacking. Instead of focusing on one mixture, optimal for specific flux values, we pursue a sampling based approach and introduce a new design criterion, which characterizes the extent to which mixtures are informative in view of all possible flux values. The R-ED workflow enables the exploration of suitable tracer mixtures and provides full flexibility to trade off information and cost metrics. The potential of the R-ED workflow is showcased by applying the approach to the industrially relevant antibiotic producer Streptomyces clavuligerus, where we suggest informative, yet economic labeling strategies.

Thirty years development of ¹³C metabolic flux analysis: a review

¹³C metabolic flux analysis (¹³C-MFA) enables the precise quantification of intracellular metabolic reaction rates by analyzing the distribution of mass isotopomers of proteinogenic amino acids or intracellular metabolites through ¹³C labeling experiments. ¹³C-MFA has received much attention as it can help systematically understand cellular metabolic characteristics, guide metabolic engineering design and gain mechanistic insights into pathophysiology. This article reviews the advances of ¹³C-MFA in the past 30 years and discusses its potential and future perspective, with a focus on its application in industrial biotechnology and biomedicine.

Comparative 13 C-metabolic flux analysis indicates elevation of ATP regeneration, carbon dioxide, and heat production in industrial Saccharomyces cerevisiae strains.

Various industrial Saccharomyces cerevisiae strains are used for specific processes, such as sake, wine brewing and bread making. Understanding mechanisms underlying the fermentation performance of these strains would be useful for further engineering of the S. cerevisiae metabolism. However, the relationship between the fermentation performance, intra-cellular metabolic states, and other phenotypic characteristics of industrial yeasts is still unclear. In this study, 13 C-metabolic flux analysis of four diploid yeast strains-laboratory, sake, bread, and wine yeasts-was conducted. While the Crabtree effect was observed for all strains, the metabolic flux level of glycolysis was elevated in bread and sake yeast. Furthermore, increased flux levels of the TCA cycle were commonly observed in the three industrial strains. The specific rates of CO2 production, net ATP regeneration, and metabolic heat generation estimated from the metabolic flux distribution were two to three times greater than those of the laboratory strain. The elevation in metabolic heat generation was correlated with the tolerance to low-temperature stress. These results indicate that the metabolic flux distribution of sake and bread yeast strains contributes to faster production of ethanol and CO2 . It is also suggested that the generation of metabolic heat is preferable under the actual industrial fermentation conditions.

13C Metabolic Flux Analysis Indicates Endothelial Cells Attenuate Metabolic Perturbations by Modulating TCA Activity.

Disrupted endothelial metabolism is linked to endothelial dysfunction and cardiovascular disease. Targeted metabolic inhibitors are potential therapeutics; however, their systemic impact on endothelial metabolism remains unknown. In this study, we combined stable isotope labeling with 13C metabolic flux analysis (13C MFA) to determine how targeted inhibition of the polyol (fidarestat), pentose phosphate (DHEA), and hexosamine biosynthetic (azaserine) pathways alters endothelial metabolism. Glucose, glutamine, and a four-carbon input to the malate shuttle were important carbon sources in the baseline human umbilical vein endothelial cell (HUVEC) 13C MFA model. We observed two to three times higher glutamine uptake in fidarestat and azaserine-treated cells. Fidarestat and DHEA-treated HUVEC showed decreased 13C enrichment of glycolytic and TCA metabolites and amino acids. Azaserine-treated HUVEC primarily showed 13C enrichment differences in UDP-GlcNAc. 13C MFA estimated decreased pentose phosphate pathway flux and increased TCA activity with reversed malate shuttle direction in fidarestat and DHEA-treated HUVEC. In contrast, 13C MFA estimated increases in both pentose phosphate pathway and TCA activity in azaserine-treated cells. These data show the potential importance of endothelial malate shuttle activity and suggest that inhibiting glycolytic side branch pathways can change the metabolic network, highlighting the need to study systemic metabolic therapeutic effects.

Auxiliary Module Promotes the Synthesis of Carboxysomes in E. coli to Achieve High-Efficiency CO2 Assimilation.

Carboxysomes (CBs) are protein organelles in cyanobacteria, and they play a central role in assimilation of CO2. Heterologous synthesis of CBs in E. coli provides an opportunity for CO2-organic compound conversion under controlled conditions but remains challenging; specifically, the CO2 assimilation efficiency is insufficient. In this study, an auxiliary module was designed to assist self-assembly of CBs derived from a model species cyanobacteria Prochlorococcus marinus (P. marinus) MED4 for synthesizing in E. coli. The results indicated that the structural integrity of synthetic CBs is improved through the transmission electron microscope images and that the CBs have highly efficient CO2-concentrating ability as revealed by enzyme kinetic analysis. Furthermore, the bacterial growth curve and 13C-metabolic flux analysis not only consolidated the fact of CO2 assimilation by synthetic CBs in E. coli but also proved that the engineered strain could efficiently convert external CO2 to some metabolic intermediates (acetyl-CoA, malate, fumarate, tyrosine, etc.) of the central metabolic pathway. The synthesis of CBs of P. marinus MED4 in E. coli provides prospects for understanding their CO2 assimilation mechanism and realizing their modular application in synthetic biology.

An energetic profile of Corynebacterium glutamicum underpinned by measured biomass yield on ATP

The supply and usage of energetic cofactors in metabolism is a central concern for systems metabolic engineering, particularly in case of energy intensive products. One of the most important parameters for systems wide balancing of energetic cofactors is the ATP requirement for biomass formation YATP/Biomass. Despite its fundamental importance, YATP/Biomass values for non-fermentative organisms are still rough estimates deduced from theoretical considerations. For the first time, we present an approach for the experimental determination of YATP/Biomass using comparative 13C metabolic flux analysis (13C MFA) of a wild type strain and an ATP synthase knockout mutant. We show that the energetic profile of a cell can then be deduced from a genome wide stoichiometric model and experimental maintenance data. Particularly, the contributions of substrate level phosphorylation (SLP) and electron transport phosphorylation (ETP) to ATP generation become available which enables the overall energetic efficiency of a cell to be characterized. As a model organism, the industrial platform organism Corynebacterium glutamicum is used. C. glutamicum uses a respiratory type of energy metabolism, implying that ATP can be synthesized either by SLP or by ETP with the membrane-bound F1FO-ATP synthase using the proton motive force (pmf) as driving force. The presence of two terminal oxidases, which differ in their proton translocation efficiency by a factor of three, further complicates energy balancing for this organism. By integration of experimental data and network models, we show that in the wild type SLP and ETP contribute equally to ATP generation. Thus, the role of ETP in respiring bacteria may have been overrated in the past. Remarkably, in the genome wide setting 65% of the pmf is actually not used for ATP synthesis. However, it turns out that, compared to other organisms C. glutamicum still uses its energy budget rather efficiently.

13C metabolic flux analysis (MFA) to find out the metabolic fluxes of biomass production and lipid accumulation in Neochloris oleoabundans UTEX 1185

Neochloris oleoabundans UTEX 1185 is a green microalga that is considered as a promising feedstock for microalgal biodiesel production as it contains high amount of lipids. Our preliminary work has shown that a faster growth, more biomass, and higher lipid content could be achieved in mixotrophic mode of growth of the strain in medium with reduced nitrate concentration. In order to estimate the central carbon flux distribution of N. oleoabundans UTEX 1185 under these conditions that improve lipid productivity, we conducted a stationary 13C-metabolic flux analysis (MFA). Our study shows that in addition to Calvin-Benson-Bassham (CBB) and tricarboxylic acid (TCA) cycles, the glyoxylate shunt is active, and a positive flux for the synthesis of storage carbohydrates was also observed in the mixotrophic growth condition. Consistent with the increased lipid content of the organism, about 33% of carbon taken up goes to the acetyl-CoA sink. A comparison of the flux distributions in the metabolic networks with and without the Entner-Doudoroff (ED) pathway showed that the network with ED pathway gave a more plausible flux distribution and suggested that ED pathway is active under the conditions tested. Therefore, this work provides quantitative assessment of the activity of the major pathways associated with growth and lipid production of N. oleoabundans under mixotrophy in reduced N condition.

Exploring the metabolic fate of propanol in industrial erythromycin-producing strain via 13C labeling experiments and enhancement of erythromycin production by rational metabolic engineering of Saccharopolyspora erythraea

Propanol had been widely used as a precursor for erythromycin synthesis in industrial production. However, the knowledge on the exact metabolic fate of propanol was still unclear. In the present study, the metabolic fate of propanol in industrial erythromycin-producing strain Saccharopolyspora erythraea E3 was explored via 13C labeling experiments. An unexpected pathway in which propanol was channeled into tricarboxylic acid cycle was uncovered, resulting in uneconomic catabolism of propanol. By deleting the sucC gene, which encodes succinyl-CoA synthetase that catalyse a reaction in the unexpected propanol utilization pathway, a novel strain E3-ΔsucC was constructed. The strain E3-ΔsucC showed a significant enhancement in erythromycin production in the chemically defined medium compared to E3 (786.61 vs 392.94 mg/L). Isotopically nonstationary 13C metabolic flux analysis were employed to characterize the metabolic differences between Saccharopolyspora erythraea E3 and E3-ΔsucC. The results showed that compared with the starting strain E3, the fluxes of pentose phosphate pathway in E3-△sucC increased by almost 200%. The flux of the metabolic reaction catalyzed by succinyl-CoA synthetase in E3-ΔsucC was almost zero, while the glyoxylate bypass flux significantly increased. These new insights into the precursor utilization of antibiotic biosynthesis by rational metabolic engineering in Saccharopolyspora erythraea provided the new vision in increasing industrial production of secondary metabolites.