Metabolite Pool Sizes Research Articles

Loss of mitochondrial pyruvate transport initiates cardiac glycogen accumulation and heart failure.

Heart failure involves metabolic alterations including increased glycolysis despite unchanged or decreased glucose oxidation. The mitochondrial pyruvate carrier (MPC) regulates pyruvate entry into the mitochondrial matrix, and cardiac deletion of the MPC in mice causes heart failure. How MPC deletion results in heart failure is unknown. We performed targeted metabolomics and isotope tracing in wildtype (fl/fl) and cardiac-specific Mpc2-/- (CS-Mpc2-/-) hearts after in vivo injection of U-13C-glucose. Cardiac glycogen was assessed biochemically and by transmission electron microscopy. Cardiac uptake of 2-deoxyglucose was measured and western blotting performed to analyze insulin signaling and enzymatic regulators of glycogen synthesis and degradation. Isotope tracing and glycogen analysis was also performed in hearts from mice fed either low-fat diet or a ketogenic diet previously shown to reverse the CS-Mpc2-/- heart failure. Cardiac glycogen was also assessed in mice infused with angiotensin-II that were fed low-fat or ketogenic diet. Failing CS-Mpc2-/- hearts contained normal levels of ATP and phosphocreatine, yet these hearts displayed increased enrichment from U-13C-glucose and increased glycolytic metabolite pool sizes. 13C enrichment and pool size was also increased for the glycogen intermediate UDP-glucose, as well as increased enrichment of the glycogen pool. Glycogen levels were increased ~6-fold in the failing CS-Mpc2-/- hearts, and glycogen granules were easily detected by electron microscopy. This increased glycogen synthesis occurred despite enhanced inhibitory phosphorylation of glycogen synthase and reduced expression of glycogenin-1. In young, non-failing CS-Mpc2-/- hearts, increased glycolytic 13C enrichment occurred, but glycogen levels remained low and unchanged compared to fl/fl hearts. Feeding a ketogenic diet to CS-Mpc2-/- mice reversed the heart failure and normalized the cardiac glycogen and glycolytic metabolite accumulation. Cardiac glycogen levels were also elevated in mice infused with angiotensin-II, and both the cardiac hypertrophy and glycogen levels were improved by ketogenic diet. Our results indicate that loss of MPC in the heart causes glycogen accumulation and heart failure, while a ketogenic diet can reverse both the glycogen accumulation and heart failure. We conclude that maintaining mitochondrial pyruvate import and metabolism is critical for the heart, unless cardiac pyruvate metabolism is reduced by consumption of a ketogenic diet.

A multimodal atlas of tumour metabolism reveals the architecture of gene–metabolite covariation

Tumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and to study gene–metabolite covariation in cancer, we assemble the Cancer Atlas of Metabolic Profiles of metabolomic and transcriptomic data from 988 tumour and control specimens spanning 11 cancer types in published and newly generated datasets. Meta-analysis of the Cancer Atlas of Metabolic Profiles reveals two classes of gene–metabolite covariation that transcend cancer types. The first corresponds to gene–metabolite pairs engaged in direct enzyme–substrate interactions, identifying putative genes controlling metabolite pool sizes. A second class of gene–metabolite covariation represents a small number of hub metabolites, including quinolinate and nicotinamide adenine dinucleotide, which correlate to many genes specifically expressed in immune cell populations. These results provide evidence that gene–metabolite covariation in cellularly heterogeneous tissue arises, in part, from both mechanistic interactions between genes and metabolites, and from remodelling of the bulk metabolome in specific immune microenvironments.

Interactions of molybdenum disulfide nanosheets with wheat plants under changing environments: More than meets the eye?

Molybdenum disulfide (MoS2) nanosheets are being increasingly employed in various applications. It is therefore imperative to assess their potential environmental implications in a changing world, particularly in the context of global warming. Here, we assessed the effects of MoS2 nanosheets on wheat Triticum aestivum L. under today's typical climatic conditions (22 °C) and future climatic conditions (30 °C), respectively. The results showed that MoS2 nanosheets (10 and 100 Mo mg/L) did not significantly affect wheat plant growth, root morphological traits, and chlorophyll fluorescence, regardless of dose and temperature. However, the metabolic processes were significantly altered in T. aestivum upon exposure to individual MoS2 nanosheets and to a combination of MoS2 nanosheets and future global warming. As a non-specific protective strategy, the wheat plants that were under stress conditions maintained the stability of cell membranes and thus relieved cell injury by accumulating more glycerophospholipids. Warming additionally influenced the nitrogen and carbon pool reallocation in wheat root. MoS2 nanosheets mainly depleted a range of antioxidant metabolites involved in phenylpropanoid biosynthesis and taurine and hypotaurine metabolism, while warming activated vitamin B6 cofactors related to vitamin B6 metabolism. Metabolites involved in glutathione metabolism were uniquely upregulated while most metabolites associated with nucleotide metabolisms were uniquely downregulated in combination-treated wheat. Overall, wheat plants regulated a wide range of growth-related processes, including carbohydrate, amino acids, lipid, vitamins, and nucleotide metabolism, to maintain optimal metabolite pool sizes and eventually global metabolic homeostasis upon different stress conditions. Our findings provide novel insights into MoS2 nanosheets-mediated crop responses under global warming.

Re-Programing Glucose Catabolism in the Microalga Chlorella sorokiniana under Light Condition.

The microalga Chlorella sorokiniana has attracted much attention for lipid production and wastewater treatment. It can perform photosynthesis and organic carbon utilization concurrently. To understand its phototrophic metabolism, a biomass compositional analysis, a 13C metabolic flux analysis, and metabolite pool size analyses were performed. Under dark condition, the oxidative pentose phosphate pathway (OPP) was the major route for glucose catabolism (88% carbon flux) and a cyclic OPP–glycolytic route for glucose catabolism was formed. Under light condition, fluxes in the glucose catabolism, tricarboxylic acid (TCA) cycle, and anaplerotic reaction (CO2 fixation via phosphoenolpyruvate carboxylase) were all suppressed. Meanwhile, the RuBisCO reaction became active and the ratio of its carbon fixation to glucose carbon utilization was determined as 7:100. Moreover, light condition significantly reduced the pool sizes of sugar phosphate metabolites (such as E4P, F6P, and S7P) and promoted biomass synthesis (which reached 0.155 h−1). In addition, light condition increased glucose consumption rates, leading to higher ATP and NADPH production and a higher protein content (43% vs. 30%) in the biomass during the exponential growth phase.

Scrutinizing the Impact of Alternating Electromagnetic Fields on Molecular Features of the Model Plant Arabidopsis thaliana.

Natural and anthropogenic electromagnetic fields (EMFs) are ubiquitous in the environment and interfere with all biological organisms including plants. Particularly the quality and quantity of alternating EMFs from anthropogenic sources are increasing due to the implementation of novel technologies. There is a significant interest in exploring the impact of EMFs (similar to those emitted from battery chargers of electric cars) on plants. The model plant Arabidopsis thaliana was exposed to a composite alternating EMF program for 48 h and scrutinized for molecular alterations using photosynthetic performance, metabolite profiling, and RNA sequencing followed by qRT-PCR validation. Clear differences in the photosynthetic parameters between the treated and control plants indicated either lower nonphotochemical quenching or higher reduction of the plastoquinone pool or both. Transcriptome analysis by RNA sequencing revealed alterations in transcript amounts upon EMF exposure; however, the gene ontology groups of, e.g., chloroplast stroma, thylakoids, and envelope were underrepresented. Quantitative real-time PCR validated deregulation of some selected transcripts. More profound were the readjustments in metabolite pool sizes with variations in photosynthetic and central energy metabolism. These findings together with the invariable phenotype indicate efficient adjustment of the physiological state of the EMF-treated plants, suggesting testing for more challenging growth conditions in future experiments.

Isotope-assisted metabolic flux analysis as an equality-constrained nonlinear program for improved scalability and robustness.

Stable isotope-assisted metabolic flux analysis (MFA) is a powerful method to estimate carbon flow and partitioning in metabolic networks. At its core, MFA is a parameter estimation problem wherein the fluxes and metabolite pool sizes are model parameters that are estimated, via optimization, to account for measurements of steady-state or isotopically-nonstationary isotope labeling patterns. As MFA problems advance in scale, they require efficient computational methods for fast and robust convergence. The structure of the MFA problem enables it to be cast as an equality-constrained nonlinear program (NLP), where the equality constraints are constructed from the MFA model equations, and the objective function is defined as the sum of squared residuals (SSR) between the model predictions and a set of labeling measurements. This NLP can be solved by using an algebraic modeling language (AML) that offers state-of-the-art optimization solvers for robust parameter estimation and superior scalability to large networks. When implemented in this manner, the optimization is performed with no distinction between state variables and model parameters. During each iteration of such an optimization, the system state is updated instead of being calculated explicitly from scratch, and this occurs concurrently with improvement in the model parameter estimates. This optimization approach starkly contrasts with traditional “shooting” methods where the state variables and model parameters are kept distinct and the system state is computed afresh during each iteration of a stepwise optimization. Our NLP formulation uses the MFA modeling framework of Wiechert et al. [1], which is amenable to incorporation of the model equations into an NLP. The NLP constraints consist of balances on either elementary metabolite units (EMUs) or cumomers. In this formulation, both the steady-state and isotopically-nonstationary MFA (inst-MFA) problems may be solved as an NLP. For the inst-MFA case, the ordinary differential equation (ODE) system describing the labeling dynamics is transcribed into a system of algebraic constraints for the NLP using collocation. This large-scale NLP may be solved efficiently using an NLP solver implemented on an AML. In our implementation, we used the reduced gradient solver CONOPT, implemented in the General Algebraic Modeling System (GAMS). The NLP framework is particularly advantageous for inst-MFA, scaling well to large networks with many free parameters, and having more robust convergence properties compared to the shooting methods that compute the system state and sensitivities at each iteration. Additionally, this NLP approach supports the use of tandem-MS data for both steady-state and inst-MFA when the cumomer framework is used. We assembled a software, eiFlux, written in Python and GAMS that uses the NLP approach and supports both steady-state and inst-MFA. We demonstrate the effectiveness of the NLP formulation on several examples, including a genome-scale inst-MFA model, to highlight the scalability and robustness of this approach. In addition to typical inst-MFA applications, we expect that this framework and our associated software, eiFlux, will be particularly useful for applying inst-MFA to complex MFA models, such as those developed for eukaryotes (e.g. algae) and co-cultures with multiple cell types.

Impact of Altered Trehalose Metabolism on Physiological Response of Penicillium chrysogenum Chemostat Cultures during Industrially Relevant Rapid Feast/Famine Conditions

Due to insufficient mass transfer and mixing issues, cells in the industrial-scale bioreactor are often forced to experience glucose feast/famine cycles, mostly resulting in reduced commercial metrics (titer, yield and productivity). Trehalose cycling has been confirmed as a double-edged sword in the Penicillium chrysogenum strain, which facilitates the maintenance of a metabolically balanced state, but it consumes extra amounts of the ATP responsible for the repeated breakdown and formation of trehalose molecules in response to extracellular glucose perturbations. This loss of ATP would be in competition with the high ATP-demanding penicillin biosynthesis. In this work, the role of trehalose metabolism was further explored under industrially relevant conditions by cultivating a high-yielding Penicillium chrysogenum strain, and the derived trehalose-null strains in the glucose-limited chemostat system where the glucose feast/famine condition was imposed. This dynamic feast/famine regime with a block-wise feed/no feed regime (36 s on, 324 s off) allows one to generate repetitive cycles of moderate changes in glucose availability. The results obtained using quantitative metabolomics and stoichiometric analysis revealed that the intact trehalose metabolism is vitally important for maintaining penicillin production capacity in the Penicillium chrysogenum strain under both steady state and dynamic conditions. Additionally, cells lacking such a key metabolic regulator would become more sensitive to industrially relevant conditions, and are more able to sustain metabolic rearrangements, which manifests in the shrinkage of the central metabolite pool size and the formation of ATP-consuming futile cycles.

Dynamic Inventory of Intermediate Metabolites of Cyanobacteria in a Diurnal Cycle.

SummaryCyanobacteria are gaining importance both as hosts for photoautotrophic production of chemicals and as model systems for studies of diurnal lifestyle. The proteome and transcriptome of cyanobacteria have been closely examined under diurnal growth, whereas the downstream effects on the intermediary metabolism have not received sufficient attention. The present study focuses on identifying the cellular metabolites whose inventories undergo dramatic changes in a fast-growing cyanobacterium, Synechococcus elongatus PCC 11801. We identified and quantified 67 polar metabolites, whose inventory changes significantly during diurnal growth, with some metabolites changing by 100-fold. The Calvin-Benson-Bassham cycle intermediates peak at midday to support fast growth. The hitherto unexplored γ-glutamyl peptides act as reservoirs of amino acids. Interestingly, several storage molecules or their precursors accumulate during the dark phase, dispelling the notion that all biosynthetic activity takes place in the light phase. Our results will guide metabolic modeling and strain engineering of cyanobacteria.

Evaluation of quenching methods for metabolite recovery in photoautotrophic Synechococcus sp. PCC 7002.

The first step of many metabolomics studies is quenching, a technique vital for rapidly halting metabolism and ensuring that the metabolite profile remains unchanging during sample processing. The most widely used approach is to plunge the sample into prechilled cold methanol; however, this led to significant metabolite loss in Synecheococcus sp. PCC 7002. Here we describe our analysis of the impacts of cold methanol quenching on the model marine cyanobacterium Synechococcus sp. PCC 7002, as well as our brief investigation of alternative quenching methods. We tested several methods including cold methanol, cold saline, and two filtration approaches. Targeted central metabolites were extracted and metabolomic profiles were generated using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results indicate that cold methanol quenching induces dramatic metabolite leakage in Synechococcus, resulting in a majority of central metabolites being lost prior to extraction. Alternatively, usage of a chilled saline quenching solution mitigates metabolite leakage and improves sample recovery without sacrificing rapid quenching of cellular metabolism. Finally, we illustrate that metabolite leakage can be assessed, and subsequently accounted for, in order to determine absolute metabolite pool sizes; however, our results show that metabolite leakage is inconsistent across various metabolite pools and therefore must be determined for each individually measured metabolite.

Discovery for New Herbicide Sites of Action by Quantification of Plant Primary Metabolite and Enzyme Pools

Abstract No herbicide with a new molecular site of action (SOA) has been introduced since the 1980s. Since then, the widespread evolution of resistance of weeds to most commercial herbicides has greatly increased the need for herbicides with new SOAs. Two untried strategies for the discovery on new herbicide SOAs are discussed. Some primary metabolism intermediates are phytotoxic (e.g., protoporphyrin IX and sphingoid bases), and, because of this, the in vivo concentrations of these compounds are maintained at very low levels by plants. The determination of all primary metabolite phytotoxicities and pool sizes will identify targets of interest. Targeting SOAs that result in accumulation of phytotoxic compounds is the first novel approach to herbicide discovery. The second approach is to identify potential SOAs with very low in vivo enzyme levels. We know that higher numbers of enzyme molecules for a SOA requires more herbicide to kill a plant. Modern proteomic methods can identify low enzyme level SOAs for biorational herbicide discovery. These approaches might be useful in discovery of herbicides more closely related to natural compounds and that can be used in lower doses.

Potential of temperature- and salinity-driven shifts in diatom compatible solute concentrations to impact biogeochemical cycling within sea ice

Sea-ice algae are an important source of primary production in polar regions, yet we have limited understanding of their responses to the seasonal cycling of temperature and salinity. Using a targeted liquid chromatography-mass spectrometry-based metabolomics approach, we found that axenic cultures of the Antarctic sea-ice diatom, Nitzschia lecointei, displayed large differences in their metabolomes when grown in a matrix of conditions that included temperatures of –1 and 4°C, and salinities of 32 and 41, despite relatively small changes in growth rate. Temperature exerted a greater effect than salinity on cellular metabolite pool sizes, though the N- or S-containing compatible solutes, 2, 3-dihydroxypropane-1-sulfonate (DHPS), glycine betaine (GBT), dimethylsulfoniopropionate (DMSP), and proline responded strongly to both temperature and salinity, suggesting complexity in their control. We saw the largest (> 4-fold) response to salinity for proline. DHPS, a rarely studied but potential compatible solute, had the highest intracellular concentrations among all compatible solutes of ~85 mM. When comparing the culture findings to natural Arctic sea-ice diatom communities, we found extensive overlap in metabolite profiles, highlighting the relevance of culture-based studies to probe environmental questions. Large changes in sea-ice diatom metabolomes and compatible solutes over a seasonal cycle could be significant components of biogeochemical cycling within sea ice.

Applications of stable isotope-based metabolomics and fluxomics toward synthetic biology of cyanobacteria.

Unique features of cyanobacteria (e.g., photosynthesis and nitrogen fixation) make them potential candidates for production of biofuels and other value-added biochemicals. As prokaryotes, they can be readily engineered using synthetic and systems biology tools. Metabolic engineering of cyanobacteria for the synthesis of desired compounds requires in-depth knowledge of central carbon and nitrogen metabolism, pathway fluxes, and their regulation. Metabolomics and fluxomics offer the comprehensive analysis of metabolism by directly characterizing the biochemical activities of cells. This information is acquired by measuring the abundance of key metabolites and their rates of interconversion, which can be achieved by labeling cells with stable isotopes, quantifying metabolite pool sizes and isotope incorporation by gas chromatography/liquid chromatography-mass spectrometry GC/LC-MS or nuclear magnetic resonance (NMR), and mathematical modeling to estimate in vivo metabolic fluxes. Herein, we review progress that has been made to adapt metabolomics and fluxomics tools to examine model cyanobacterial species. We summarize the application of metabolic flux analysis (MFA) strategies to identify metabolic bottlenecks that can be targeted to boost cell growth, improve stress tolerance, or enhance biochemical production in cyanobacteria. Despite the advances in metabolomics, fluxomics, and other synthetic and systems biology tools during the past years, further efforts are required to increase our understanding of cyanobacterial metabolism in order to create efficient photosynthetic hosts for the production of value-added compounds. This article is categorized under: Laboratory Methods and Technologies > Metabolomics Biological Mechanisms > Metabolism Analytical and Computational Methods > Analytical Methods.

Repression of mitochondrial metabolism for cytosolic pyruvate-derived chemical production in Saccharomyces cerevisiae

BackgroundSaccharomyces cerevisiae is a suitable host for the industrial production of pyruvate-derived chemicals such as ethanol and 2,3-butanediol (23BD). For the improvement of the productivity of these chemicals, it is essential to suppress the unnecessary pyruvate consumption in S. cerevisiae to redirect the metabolic flux toward the target chemical production. In this study, mitochondrial pyruvate transporter gene (MPC1) or the essential gene for mitophagy (ATG32) was knocked-out to repress the mitochondrial metabolism and improve the production of pyruvate-derived chemical in S. cerevisiae.ResultsThe growth rates of both aforementioned strains were 1.6-fold higher than that of the control strain. 13C-metabolic flux analysis revealed that both strains presented similar flux distributions and successfully decreased the tricarboxylic acid cycle fluxes by 50% compared to the control strain. Nevertheless, the intracellular metabolite pool sizes were completely different, suggesting distinct metabolic effects of gene knockouts in both strains. This difference was also observed in the test-tube culture for 23BD production. Knockout of ATG32 revealed a 23.6-fold increase in 23BD titer (557.0 ± 20.6 mg/L) compared to the control strain (23.5 ± 12.8 mg/L), whereas the knockout of MPC1 revealed only 14.3-fold increase (336.4 ± 113.5 mg/L). Further investigation using the anaerobic high-density fermentation test revealed that the MPC1 knockout was more effective for ethanol production than the 23BD production.ConclusionThese results suggest that the engineering of the mitochondrial transporters and membrane dynamics were effective in controlling the mitochondrial metabolism to improve the productivities of chemicals in yeast cytosol.

Inhibition of nucleotide synthesis promotes replicative senescence of human mammary epithelial cells

Cellular senescence is a mechanism by which cells permanently withdraw from the cell cycle in response to stresses including telomere shortening, DNA damage, or oncogenic signaling. Senescent cells contribute to both age-related degeneration and hyperplastic pathologies, including cancer. In culture, normal human epithelial cells enter senescence after a limited number of cell divisions, known as replicative senescence. Here, to investigate how metabolic pathways regulate replicative senescence, we used LC-MS-based metabolomics to analyze senescent primary human mammary epithelial cells (HMECs). We did not observe significant changes in glucose uptake or lactate secretion in senescent HMECs. However, analysis of intracellular metabolite pool sizes indicated that senescent cells exhibit depletion of metabolites from nucleotide synthesis pathways. Furthermore, stable isotope tracing with 13C-labeled glucose or glutamine revealed a dramatic blockage of flux of these two metabolites into nucleotide synthesis pathways in senescent HMECs. To test whether cellular immortalization would reverse these observations, we expressed telomerase in HMECs. In addition to preventing senescence, telomerase expression maintained metabolic flux from glucose into nucleotide synthesis pathways. Finally, we investigated whether inhibition of nucleotide synthesis in proliferating HMECs is sufficient to induce senescence. In proliferating HMECs, both pharmacological and genetic inhibition of ribonucleotide reductase regulatory subunit M2 (RRM2), a rate-limiting enzyme in dNTP synthesis, induced premature senescence with concomitantly decreased metabolic flux from glucose into nucleotide synthesis. Taken together, our results suggest that nucleotide synthesis inhibition plays a causative role in the establishment of replicative senescence in HMECs.

Cyanobacterial carboxysome mutant analysis reveals the influence of enzyme compartmentalization on cellular metabolism and metabolic network rigidity

Cyanobacterial carboxysomes encapsulate carbonic anhydrase and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO). Genetic deletion of the major structural proteins encoded within the ccm operon in Synechococcus sp. PCC 7002 (ΔccmKLMN) disrupts carboxysome formation and significantly affects cellular physiology. Here we employed both metabolite pool size analysis and isotopically nonstationary metabolic flux analysis (INST-MFA) to examine metabolic regulation in cells lacking carboxysomes. Under high CO2 environments (1%), the ΔccmKLMN mutant could recover growth and had a similar central flux distribution as the control strain, with the exceptions of moderately decreased photosynthesis and elevated biomass protein content and photorespiration activity. Metabolite analyses indicated that the ΔccmKLMN strain had significantly larger pool sizes of pyruvate (>18 folds), UDPG (uridine diphosphate glucose), and aspartate as well as higher levels of secreted organic acids (e.g., malate and succinate). These results suggest that the ΔccmKLMN mutant is able to largely maintain a fluxome similar to the control strain by changing in intracellular metabolite concentrations and metabolite overflows under optimal growth conditions. When CO2 was insufficient (0.2%), provision of acetate moderately promoted mutant growth. Interestingly, the removal of microcompartments may loosen the flux network and promote RuBisCO side-reactions, facilitating redirection of central metabolites to competing pathways (i.e., pyruvate to heterologous lactate production). This study provides important insights into metabolic regulation via enzyme compartmentation and cyanobacterial compensatory responses.

Plant hormone effects on isoprene emission from tropical tree in Ficus septica.

Plant hormones and the circadian rhythm have been implicated in coordinated control of isoprene emission in plants. To gain insights into the signalling networks, foliar application of plant hormones was conducted in a native emitter, Ficus septica. Spraying of 50μM jasmonic acid (JA) gradually decreased isoprene emission by 88% compared with initial levels within 5days, and emission increased after relief from JA application. We further explored the molecular regulatory mechanism of isoprene emission by analysing photosynthetic rate, gene expression of 2-C-methyl-D-erythrytol 4-phosphate (MEP) pathway, hormone signalling and circadian rhythm processes, and metabolite pool sizes of MEP pathway. Results show that isoprene emission strongly correlated with isoprene synthase (IspS) gene expression and IspS protein levels over the period of JA treatment, indicating transcriptional and possible translational modulation of IspS by JA. Application of JA coordinately modulated genes in the auxin, cytokinin (CK), and circadian rhythm signal transduction pathways. Among the transcriptional factors analysed, MYC2 (JA) and LHY (circadian clock) negatively correlated with isoprene emission. Putative cis-elements predicted on IspS promoter (G-box for MYC2 and circadian for LHY) supports our proposal that isoprene emission is regulated by coordinated transcriptional modulation of IspS gene by phytohormone and circadian rhythm signalling.

The Role of Pool Size Measurements in Improving Flux Estimations in Non-Stationary Metabolic Flux Analysis

Over the past several decades, Metabolic Flux Analysis (MFA) has gained importance in the biomedical and pharmaceutical sciences. MFA is based on a computational procedure used to determine metabolic reaction rates (fluxes) and in some cases metabolite concentrations (pool sizes) within metabolic pathways where direct observation and measurement of intracellular function is not feasible. Applying 13C MFA to biological data, such as that in liver metabolism, helps to determine, for example, the fate of glucose in regulatory metabolic pathways under physiological and pathophysiological steady state conditions of a cell. However, designing models with reliable flux estimations remains a challenge. A debate that still persists is whether metabolite pool size measurements added as constraints in optimization algorithms improve metabolic flux predictions. We studied the role of pool sizes using simple model networks with total of 8 and 9 metabolites. To investigate the effect of pool size constraints on flux estimations, we set up a series of scenarios varying inputs into the model for several metabolites (such as information on pool size measurements and noise levels in the mass isotopomer distribution (MID) labeling data). Our findings indicate that in models when a full set of MID labeling data (as oppose to just M0 labeling data) is available, pool sizes become dispensable in flux estimations. Moreover, in biological networks where a full set of labeling data for certain metabolites is accessible but the exact model network is unknown, flux estimations are more reliable if pool sizes are not included as model constraints.

Deletion of four genes in Escherichia coli enables preferential consumption of xylose and secretion of glucose

Overcoming carbon catabolite repression presents a significant challenge, largely due to the complex regulatory networks governing substrate catabolism, even in microbial cells. In this work, we have engineered an E. coli strain, which we have named X2G, that not only exhibits a reversed substrate preference for xylose over glucose, but also demonstrates an unusual ability to produce significant amounts of glucose. We obtained this non-intuitive phenotype by deleting four genes in upper central metabolism: ptsI, glk, pfkA, and zwf, which respectively encode Enzyme I of the phosphotransferase system, glucokinase, the dominant isozyme of phosphofructokinase, and glucose-6-phosphate dehydrogenase. The deletion of ptsI and glk blocks glucose uptake in E. coli, while the deletion of pfkA and zwf prevents the reassimilation of carbons through glycolysis and the oxidative pentose phosphate pathway, respectively. Our strain X2G is capable of converting 34% of the carbon it takes up as xylose into exported glucose. This corresponds to a glucose production rate of 1.4 ± 0.3 mmol/gDW/h at a specific growth rate of 0.25 ± 0.03 h−1, or about 1.8 ± 0.1 mM of glucose accumulated for every unit increase in OD600. Despite a 22% decrease in xylose uptake rate, a 33% decrease in biomass yield, and a 52% decrease in acetate production rate relative to the wild-type, the intracellular flux profile and cofactor allocation of X2G remain largely unperturbed, as elucidated through 13C-metabolic flux analysis. Further quantification of the pool sizes of key intracellular metabolites revealed that glucose secretion by X2G is likely driven by the substantial accumulation of intracellular glucose 6-phosphate, fructose 6-phosphate, glucose and fructose at levels greater than 20x of that in wild-type E. coli. Combined, our results shed light on the flexibility of central metabolism, and the opportunities this affords for producing value-added pentose- and hexose-derived products from lignocellulosic feedstocks.

Stage-specific metabolic features of differentiating neurons: Implications for toxicant sensitivity

Developmental neurotoxicity (DNT) may be induced when chemicals disturb a key neurodevelopmental process, and many tests focus on this type of toxicity. Alternatively, DNT may occur when chemicals are cytotoxic only during a specific neurodevelopmental stage. The toxicant sensitivity is affected by the expression of toxicant targets and by resilience factors. Although cellular metabolism plays an important role, little is known how it changes during human neurogenesis, and how potential alterations affect toxicant sensitivity of mature vs. immature neurons. We used immature (d0) and mature (d6) LUHMES cells (dopaminergic human neurons) to provide initial answers to these questions. Transcriptome profiling and characterization of energy metabolism suggested a switch from predominantly glycolytic energy generation to a more pronounced contribution of the tricarboxylic acid cycle (TCA) during neuronal maturation. Therefore, we used pulsed stable isotope-resolved metabolomics (pSIRM) to determine intracellular metabolite pool sizes (concentrations), and isotopically non-stationary 13C-metabolic flux analysis (INST 13C-MFA) to calculate metabolic fluxes. We found that d0 cells mainly use glutamine to fuel the TCA. Furthermore, they rely on extracellular pyruvate to allow continuous growth. This metabolic situation does not allow for mitochondrial or glycolytic spare capacity, i.e. the ability to adapt energy generation to altered needs. Accordingly, neuronal precursor cells displayed a higher sensitivity to several mitochondrial toxicants than mature neurons differentiated from them. In summary, this study shows that precursor cells lose their glutamine dependency during differentiation while they gain flexibility of energy generation and thereby increase their resistance to low concentrations of mitochondrial toxicants.

Deciphering cyanobacterial phenotypes for fast photoautotrophic growth via isotopically nonstationary metabolic flux analysis

BackgroundSynechococcus elongatus UTEX 2973 is the fastest growing cyanobacterium characterized to date. Its genome was found to be 99.8% identical to S. elongatus 7942 yet it grows twice as fast. Current genome-to-phenome mapping is still poorly performed for non-model organisms. Even for species with identical genomes, cell phenotypes can be strikingly different. To understand Synechococcus 2973’s fast-growth phenotype and its metabolic features advantageous to photo-biorefineries, 13C isotopically nonstationary metabolic flux analysis (INST-MFA), biomass compositional analysis, gene knockouts, and metabolite profiling were performed on both strains under various growth conditions.ResultsThe Synechococcus 2973 flux maps show substantial carbon flow through the Calvin cycle, glycolysis, photorespiration and pyruvate kinase, but minimal flux through the malic enzyme and oxidative pentose phosphate pathways under high light/CO2 conditions. During fast growth, its pool sizes of key metabolites in central pathways were lower than suboptimal growth. Synechococcus 2973 demonstrated similar flux ratios to Synechococcus 7942 (under fast growth conditions), but exhibited greater carbon assimilation, higher NADPH concentrations, higher energy charge (relative ATP ratio over ADP and AMP), less accumulation of glycogen, and potentially metabolite channeling. Furthermore, Synechococcus 2973 has very limited flux through the TCA pathway with small pool sizes of acetyl-CoA/TCA intermediates under all growth conditions.ConclusionsThis study employed flux analysis to investigate phenotypic heterogeneity among two cyanobacterial strains with near-identical genome background. The flux/metabolite profiling, biomass composition analysis, and genetic modification results elucidate a highly effective metabolic topology for CO2 assimilatory and biosynthesis in Synechococcus 2973. Comparisons across multiple Synechococcus strains indicate faster metabolism is also driven by proportional increases in both photosynthesis and key central pathway fluxes. Moreover, the flux distribution in Synechococcus 2973 supports the use of its strong sugar phosphate pathways for optimal bio-productions. The integrated methodologies in this study can be applied for characterizing non-model microbial metabolism.