13C-labeled gluconate tracing as a direct and accurate method for determining the pentose phosphate pathway split ratio in Penicillium chrysogenum

In this study we developed a new method for accurately determining the pentose phosphate pathway (PPP) split ratio, an important metabolic parameter in the primary metabolism of a cell. This method is based on simultaneous feeding of unlabeled glucose and trace amounts of [U-13C]gluconate, followed by measurement of the mass isotopomers of the intracellular metabolites surrounding the 6-phosphogluconate node. The gluconate tracer method was used with a penicillin G-producing chemostat culture of the filamentous fungus Penicillium chrysogenum. For comparison, a 13C-labeling-based metabolic flux analysis (MFA) was performed for glycolysis and the PPP of P. chrysogenum. For the first time mass isotopomer measurements of 13C-labeled primary metabolites are reported for P. chrysogenum and used for a 13C-based MFA. Estimation of the PPP split ratio of P. chrysogenum at a growth rate of 0.02 h(-1) yielded comparable values for the gluconate tracer method and the 13C-based MFA method, 51.8% and 51.1%, respectively. A sensitivity analysis of the estimated PPP split ratios showed that the 95% confidence interval was almost threefold smaller for the gluconate tracer method than for the 13C-based MFA method (40.0 to 63.5% and 46.0 to 56.5%, respectively). From these results we concluded that the gluconate tracer method permits accurate determination of the PPP split ratio but provides no information about the remaining cellular metabolism, while the 13C-based MFA method permits estimation of multiple fluxes but provides a less accurate estimate of the PPP split ratio.     

Metabolic flux analysis in Escherichia coli by integrating isotopic dynamic and isotopic stationary 13C labeling data

The novel concept of isotopic dynamic 13C metabolic flux analysis (ID-13C MFA) enables integrated analysis of isotopomer data from isotopic transient and/or isotopic stationary phase of a 13C labeling experiment, short-time experiments, and an extended range of applications of 13C MFA. In the presented work, an experimental and computational framework consisting of short-time 13C labeling, an integrated rapid sampling procedure, a LC-MS analytical method, numerical integration of the system of isotopomer differential equations, and estimation of metabolic fluxes was developed and applied to determine intracellular fluxes in glycolysis, pentose phosphate pathway (PPP), and citric acid cycle (TCA) in Escherichia coli grown in aerobic, glucose-limited chemostat culture at a dilution rate of D = 0.10 h(-1). Intracellular steady state concentrations were quantified for 12 metabolic intermediates. A total of 90 LC-MS mass isotopomers were quantified at sampling times t = 0, 91, 226, 346, 589 s and at isotopic stationary conditions. Isotopic stationarity was reached within 10 min in glycolytic and PPP metabolites. Consistent flux solutions were obtained by ID-13C MFA using isotopic dynamic and isotopic stationary 13C labeling data and by isotopic stationary 13C MFA (IS-13C MFA) using solely isotopic stationary data. It is demonstrated that integration of dynamic 13C labeling data increases the sensitivity of flux estimation, particularly at the glucose-6-phosphate branch point. The identified split ratio between glycolysis and PPP was 55%:44%. These results were confirmed by IS-13C MFA additionally using labeling data in proteinogenic amino acids (GC-MS) obtained after 5 h from sampled biomass.     

Isotopic non-stationary 13C gluconate tracer method for accurate determination of the pentose phosphate pathway split-ratio in Penicillium chrysogenum

Current (13)C labeling experiments for metabolic flux analysis (MFA) are mostly limited by either the requirement of isotopic steady state or the extremely high computational effort due to the size and complexity of large metabolic networks. The presented novel approach circumvents these limitations by applying the isotopic non-stationary approach to a local metabolic network. The procedure is demonstrated in a study of the pentose phosphate pathway (PPP) split-ratio of Penicillium chrysogenum in a penicillin-G producing chemostat-culture grown aerobically at a dilution rate of 0.06h(-1) on glucose, using a tracer amount of uniformly labeled [U-(13)C(6)] gluconate. The rate of labeling inflow can be controlled by using different cell densities and/or different fractions of the labeled tracer in the feed. Due to the simplicity of the local metabolic network structure around the 6-phosphogluconate (6pg) node, only three metabolites need to be measured for the pool size and isotopomer distribution. Furthermore, the mathematical modeling of isotopomer distributions for the flux estimation has been reduced from large scale differential equations to algebraic equations. Under the studied cultivation condition, the estimated split-ratio (41.2+/-0.6%) using the novel approach, shows statistically no difference with the split-ratio obtained from the originally proposed isotopic stationary gluconate tracing method.     

13C metabolic flux analysis for larger scale cultivation using gas chromatography-combustion-isotope ratio mass spectrometry

¹³C-based metabolic flux analysis (¹³CMFA) is limited to smaller scale experiments due to very high costs of labeled substrates. We measured ¹³C enrichment in proteinogenic amino acid hydrolyzates using gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) from a series of parallel batch cultivations of Corynebacterium glutamicum utilizing mixtures of natural glucose and [1-¹³C] glucose, containing 0%, 0.5%, 1%, 2%, and 10% [1-¹³C] glucose. Decreasing the [1-¹³C] glucose content, kinetic isotope effects played an increasing role but could be corrected. From the corrected ¹³C enrichments in vivo fluxes in the central metabolism were determined by numerical optimization. The obtained flux distribution was very similar to those obtained from parallel labeling experiments using conventional high labeling GC-MS method and to published results. The GC-C-IRMS-based method involving low labeling degree of expensive tracer substrate, e.g. 1%, is well suited for larger laboratory and industrial pilot scale fermentations.     

Novel Antifungal and Antifeedant Metabolites from Penicillium chrysogenum Co-Cultured with Nemania primolutea and Aspergillus fumigatus

The endophyte Nemania primolutea, inhibited the growth of Penicillium chrysogenum in the coculture system. Four new compounds, nemmolutines A–B ( 1–2 ), and penigenumin ( 3 ) from N. primolutea, penemin ( 4 ) from P. chrysogenum were isolated from the coculture. On the other hand, P. chrysogenum inhibited the Aspergillus fumigatus in the coculture. Induced metabolites ( 13–16 ) with monasone naphthoquinone scaffolds including a new one from P. chrysogenum were produced by the coculture of P. chrysogenum, and A. fumigatus. Interesting, cryptic metabolites penicichrins A–B isolated from wild P. chrysogenum induced by host Ziziphus jujuba medium were also found in induced P. chrysogenum cultured in PDB ordinary medium. So the induction of penicichrin production by supplementing with host extract occurred in the fungus P. chrysogenum not the host medium. The productions of penicichrins were the spontaneous metabolism, and the metabolites ( 13–16 ) were the culture driven. Compounds 4 , 6 , 8 , 10 , 11 , 14 , and 15 showed significant antifungal activities against the phytopathogen Alternaria alternata with MIC_S of 1–8 μg/mL, and compounds 7 , 9 , and 12 indicated significant antifeedant activities against silkworms with feeding deterrence indexes (FDIs) of 92 %, 66 %, and 64 %. The carboxy group in 4-(2-hydroxybutynoxy)benzoic acid derivatives, and xylabisboeins; the hydroxy group in mellein derivatives; and the quinoid in monasone naphthoquinone increased the antifungal activities.     

A Polymer-Based Magnetic Resonance Tracer for Visualization of Solid Tumors by 13C Spectroscopic Imaging

Morphological imaging precedes lesion-specific visualization in magnetic resonance imaging (MRI) because of the superior ability of this technique to depict tissue morphology with excellent spatial and temporal resolutions. To achieve lesion-specific visualization of tumors by MRI, we investigated the availability of a novel polymer-based tracer. Although the ¹³C nucleus is a candidate for a detection nucleus because of its low background signal in the body, the low magnetic resonance sensitivity of the nucleus needs to be resolved before developing a ¹³C-based tracer. In order to overcome this problem, we enriched polyethylene glycol (PEG), a biocompatible polymer, with ¹³C atoms. ¹³C-PEG40,000 (¹³C-PEG with an average molecular weight of 40 kDa) emitted a single ¹³C signal with a high signal-to-noise ratio due to its ability to maintain signal sharpness, as was confirmed by in vivo investigation, and displayed a chemical shift sufficiently distinct from that of endogenous fat. ¹³C-PEG40,000 intravenously injected into mice showed long retention in circulation, leading to its effective accumulation in tumors reflecting the well-known phenomenon that macromolecules accumulate in tumors because of leaky tumor capillaries. These properties of ¹³C-PEG40,000 allowed visualization of tumors in mice by ¹³C spectroscopic imaging. These findings suggest that a technique based on ¹³C-PEG is a promising strategy for tumor detection.     

Role of the pentose phosphate pathway and the Entner–Doudoroff pathway in glucose metabolism of Gluconobacter oxydans 621H

Glucose catabolism by the obligatory aerobic acetic acid bacterium Gluconobacter oxydans 621H proceeds in two phases comprising rapid periplasmic oxidation of glucose to gluconate (phase I) and oxidation of gluconate to 2-ketogluconate or 5-ketogluconate (phase II). Only a small amount of glucose and part of the gluconate is taken up into the cells. To determine the roles of the pentose phosphate pathway (PPP) and the Entner–Doudoroff pathway (EDP) for intracellular glucose and gluconate catabolism, mutants defective in either the PPP (Δgnd, Δgnd zwf*) or the EDP (Δedd–eda) were characterized under defined conditions of pH 6 and 15 % dissolved oxygen. In the presence of yeast extract, neither of the two pathways was essential for growth with glucose. However, the PPP mutants showed a reduced growth rate in phase I and completely lacked growth in phase II. In contrast, the EDP mutant showed the same growth behavior as the reference strain. These results demonstrate that the PPP is of major importance for cytoplasmic glucose and gluconate catabolism, whereas the EDP is dispensable. Reasons for this difference are discussed.     

Submicronic Fungal Bioaerosols: High-Resolution Microscopic Characterization and Quantification

Submicronic particles released from fungal cultures have been suggested to be additional sources of personal exposure in mold-contaminated buildings. In vitro generation of these particles has been studied with particle counters, eventually supplemented by autofluorescence, that recognize fragments by size and discriminate biotic from abiotic particles. However, the fungal origin of submicronic particles remains unclear. In this study, submicronic fungal particles derived from Aspergillus fumigatus, A. versicolor, and Penicillium chrysogenum cultures grown on agar and gypsum board were aerosolized and enumerated using field emission scanning electron microscopy (FESEM). A novel bioaerosol generator and a fungal spores source strength tester were compared at 12 and 20 liters min⁻¹ airflow. The overall median numbers of aerosolized submicronic particles were 2 × 10⁵ cm⁻², 2.6 × 10³ cm⁻², and 0.9 × 10³ cm⁻² for A. fumigatus, A. versicolor, and P. chrysogenum, respectively. A. fumigatus released significantly (P < 0.001) more particles than A. versicolor and P. chrysogenum. The ratios of submicronic fragments to larger particles, regardless of media type, were 1:3, 5:1, and 1:2 for A. fumigatus, A. versicolor, and P. chrysogenum, respectively. Spore fragments identified by the presence of rodlets amounted to 13%, 2%, and 0% of the submicronic particles released from A. fumigatus, A. versicolor, and P. chrysogenum, respectively. Submicronic particles with and without rodlets were also aerosolized from cultures grown on cellophane-covered media, indirectly confirming their fungal origin. Both hyphae and conidia could fragment into submicronic particles and aerosolize in vitro. These findings further highlight the potential contribution of fungal fragments to personal fungal exposure.     

Key role of LaeA and velvet complex proteins on expression of β-lactam and PR-toxin genes in <Emphasis Type="Italic">Penicillium chrysogenum</Emphasis>: cross-talk regulation of secondary metabolite pathways

Penicillium chrysogenum is an excellent model fungus to study the molecular mechanisms of control of expression of secondary metabolite genes. A key global regulator of the biosynthesis of secondary metabolites is the LaeA protein that interacts with other components of the velvet complex (VelA, VelB, VelC, VosA). These components interact with LaeA and regulate expression of penicillin and PR-toxin biosynthetic genes in P. chrysogenum. Both LaeA and VelA are positive regulators of the penicillin and PR-toxin biosynthesis, whereas VelB acts as antagonist of the effect of LaeA and VelA. Silencing or deletion of the laeA gene has a strong negative effect on penicillin biosynthesis and overexpression of laeA increases penicillin production. Expression of the laeA gene is enhanced by the P. chrysogenum autoinducers 1,3 diaminopropane and spermidine. The PR-toxin gene cluster is very poorly expressed in P. chrysogenum under penicillin-production conditions (i.e. it is a near-silent gene cluster). Interestingly, the downregulation of expression of the PR-toxin gene cluster in the high producing strain P. chrysogenum DS17690 was associated with mutations in both the laeA and velA genes. Analysis of the laeA and velA encoding genes in this high penicillin producing strain revealed that both laeA and velA acquired important mutations during the strain improvement programs thus altering the ratio of different secondary metabolites (e.g. pigments, PR-toxin) synthesized in the high penicillin producing mutants when compared to the parental wild type strain. Cross-talk of different secondary metabolite pathways has also been found in various Penicillium spp.: P. chrysogenum mutants lacking the penicillin gene cluster produce increasing amounts of PR-toxin, and mutants of P. roqueforti silenced in the PR-toxin genes produce large amounts of mycophenolic acid. The LaeA-velvet complex mediated regulation and the pathway cross-talk phenomenon has great relevance for improving the production of novel secondary metabolites, particularly of those secondary metabolites which are produced in trace amounts encoded by silent or near-silent gene clusters.     

Active metabolites produced by Penicillium chrysogenum IFL1 growing on agro-industrial residues

Microbial extracts continue to be a productive source of new molecules with biotechnological importance. Fungi of the genus Penicillium are known to produce biologically active secondary metabolites. The goal of this work is verify the production of antimicrobial metabolites by Penicillium chrysogenum IFL1 using agro-industrial residues. P. chrysogenum IFL1 produced active metabolites growing on the agro-industrial residues, grape waste and cheese whey. The 7-day cultures showed antimicrobial activities against bacteria, fungi and amoebae. The filtrate of the cheese whey culture inhibited the growth of the bacteria Staphylococcus aureus, Bacillus cereus and Pseudomonas aeruginosa, the fungus Fusarium oxysporum and the amoeba Acanthamoeba polyphaga. Due to the greater antimicrobial activity of the cheese whey culture, a footprinting profile was carried out using the ESI-MS and ESI-MS/MS techniques. The presence of penicillin G and other metabolites that have antimicrobial activity such as penicillin V and rugulosin can be suggested. P. chrysogenum IFL1 was able to produce a wide variety of antimicrobial compounds on agro-industrial residues, which makes the process ecologically friendly.     

The thermodynamic meaning of metabolic exchange fluxes

Metabolic flux analysis (MFA) deals with the experimental determination of steady-state fluxes in metabolic networks. An important feature of the ¹³C MFA method is its capability to generate information on both directions of bidirectional reaction steps given by exchange fluxes. The biological interpretation of these exchange fluxes and their relation to thermodynamic properties of the respective reaction steps has never been systematically investigated. As a central result, it is shown here that for a general class of enzyme reaction mechanisms the quotients of net and exchange fluxes measured by ¹³C MFA are coupled to Gibbs energies of the reaction steps. To establish this relation the concept of apparent flux ratios of enzymatic isotope-labeling networks is introduced and some computing rules for these flux ratios are given. Application of these rules reveals a conceptional pitfall of ¹³C MFA, which is the inherent dependency of measured exchange fluxes on the chosen tracer atom. However, it is shown that this effect can be neglected for typical biochemical reaction steps under physiological conditions. In this situation, the central result can be formulated as a two-sided inequality relating fluxes, pool sizes, and standard Gibbs energies. This relation has far-reaching consequences for metabolic flux analysis, quantitative metabolomics, and network thermodynamics.     

A Peptide-Based Method for 13C Metabolic Flux Analysis in Microbial Communities

The study of intracellular metabolic fluxes and inter-species metabolite exchange for microbial communities is of crucial importance to understand and predict their behaviour. The most authoritative method of measuring intracellular fluxes, ¹³C Metabolic Flux Analysis (¹³C MFA), uses the labeling pattern obtained from metabolites (typically amino acids) during ¹³C labeling experiments to derive intracellular fluxes. However, these metabolite labeling patterns cannot easily be obtained for each of the members of the community. Here we propose a new type of ¹³C MFA that infers fluxes based on peptide labeling, instead of amino acid labeling. The advantage of this method resides in the fact that the peptide sequence can be used to identify the microbial species it originates from and, simultaneously, the peptide labeling can be used to infer intracellular metabolic fluxes. Peptide identity and labeling patterns can be obtained in a high-throughput manner from modern proteomics techniques. We show that, using this method, it is theoretically possible to recover intracellular metabolic fluxes in the same way as through the standard amino acid based ¹³C MFA, and quantify the amount of information lost as a consequence of using peptides instead of amino acids. We show that by using a relatively small number of peptides we can counter this information loss. We computationally tested this method with a well-characterized simple microbial community consisting of two species.     

Metabolic network reconstruction,growth characterization and 13C-metabolic flux analysis of the extremophile Thermus thermophilus HB8

Thermus thermophilus is an extremely thermophilic bacterium with significant biotechnological potential. In this work, we have characterized aerobic growth characteristics of T. thermophilus HB8 at temperatures between 50 and 85 °C, constructed a metabolic network model of its central carbon metabolism and validated the model using ¹³C-metabolic flux analysis (¹³C–MFA). First, cells were grown in batch cultures in custom constructed mini-bioreactors at different temperatures to determine optimal growth conditions. The optimal temperature for T. thermophilus grown on defined medium with glucose was 81 °C. The maximum growth rate was 0.25 h⁻¹. Between 50 and 81 °C the growth rate increased by 7-fold and the temperature dependence was described well by an Arrhenius model with an activation energy of 47 kJ/mol. Next, we performed a ¹³C-labeling experiment with [1,2-¹³C] glucose as the tracer and calculated intracellular metabolic fluxes using ¹³C–MFA. The results provided support for the constructed network model and highlighted several interesting characteristics of T. thermophilus metabolism. We found that T. thermophilus largely uses glycolysis and TCA cycle to produce biosynthetic precursors, ATP and reducing equivalents needed for cells growth. Consistent with its proposed metabolic network model, we did not detect any oxidative pentose phosphate pathway flux or Entner-Doudoroff pathway activity. The biomass precursors erythrose-4-phosphate and ribose-5-phosphate were produced via the non-oxidative pentose phosphate pathway, and largely via transketolase, with little contribution from transaldolase. The high biomass yield on glucose that was measured experimentally was also confirmed independently by ¹³C–MFA. The results presented here provide a solid foundation for future studies of T. thermophilus and its metabolic engineering applications.     

Predictions of methane emission levels and categories based on milk fatty acid profiles from dairy cows

Milk fatty acid (MFA) have already been used to model methane (CH₄) emissions from dairy cows. However, the data sets used to develop these models covered limited variation in dietary conditions, reducing the robustness of the predictions. In this study, a data set containing 140 observations from nine experiments (41 Holstein cows) was used to develop models predicting CH₄ expressed as g/day, g/kg dry matter intake (DMI) and g/kg milk. The data set was divided into a training (n=112) and a test data set (n=28) for model development and validation, respectively. A generalized linear mixed model was fitted to the data using the marginal R²_(m) and the Akaike information criterion to evaluate the models. The coefficient of determination of validation (R²_(v)) for different models developed ranged between 0.18 and 0.41. Form the intake-related parameters, only inclusion of total DMI improved the prediction (R²_(v)=0.58). In addition, in an attempt to further explore the relationships between MFA and CH₄ emissions, the data set was split into three categories according to CH₄ emissions: LOW (lowest 25% CH₄ emissions); HIGH (highest 25% CH₄ emissions); and MEDIUM (50% remaining observations). An ANOVA revealed that concentrations of several MFA differed for observations in HIGH compared with observations in LOW. Furthermore, the Gini coefficient was used to describe the MFA distribution for groups of MFA in each CH₄ emission category. The relative distribution of the MFA, particularly of the odd- and branched-chain fatty acids and mono-unsaturated fatty acids of observations in category HIGH differed from those in the other categories. Finally, in an attempt to validate the potential of MFA to identify cases of high or low emissions, the observations were re-classified into HIGH, MEDIUM and LOW according to the proportion of each individual MFA. The proportion of observations correctly classified were recorded. This was done for each individual MFA and for the calculated Gini coefficients, finding that a maximum of 67% of observations were correctly classified as HIGH CH₄ (trans-12 C18:1) and a maximum of 58% of observations correctly classified as LOW CH₄ (cis-9 C17:1). Gini coefficients did not improve this classification. These results suggest that MFA are not yet reliable predictors of specific amounts of CH₄ emitted by a cow, while holding a modest potential to differentiate cases of high or low emissions.     

The oxidative TCA cycle operates during methanotrophic growth of the Type I methanotroph Methylomicrobium buryatense 5GB1

Methanotrophs are a group of bacteria that use methane as sole carbon and energy source. Type I methanotrophs are gamma-proteobacterial methanotrophs using the ribulose monophosphate cycle (RuMP) cycle for methane assimilation. In order to facilitate metabolic engineering in the industrially promising Type I methanotroph Methylomicrobium buryatense 5GB1, flux analysis of cellular metabolism is needed and ¹³C tracer analysis is a foundational tool for such work. This biological system has a single-carbon input and a special network topology that together pose challenges to the current well-established methodology for ¹³C tracer analysis using a multi-carbon input such as glucose, and to date, no ¹³C tracer analysis of flux in a Type I methanotroph has been reported. In this study, we showed that by monitoring labeling patterns of several key intermediate metabolites in core metabolism, it is possible to quantitate the relative flux ratios for important branch points, such as the malate node. In addition, it is possible to assess the operation of the TCA cycle, which has been thought to be incomplete in Type I methanotrophs. Surprisingly, our analysis provides direct evidence of a complete, oxidative TCA cycle operating in M. buryatense 5GB1 using methane as sole carbon and energy substrate, contributing about 45% of the total flux for de novo malate production. Combined with mutant analysis, this method was able to identify fumA (METBUDRAFT_1453/MBURv2__60244) as the primary fumarase involved in the oxidative TCA cycle, among 2 predicted fumarases, supported by ¹³C tracer analysis on both fumA and fumC single knockouts. Interrupting the oxidative TCA cycle leads to a severe growth defect, suggesting that the oxidative TCA cycle functions to not only provide precursors for de novo biomass synthesis, but also to provide reducing power to the system. This information provides new opportunities for metabolic engineering of M. buryatense for the production of industrially relevant products.     

A newly constructed Agrobacterium-mediated transformation system revealed the influence of nitrogen sources on the function of the LaeA regulator in Penicillium chrysogenum

Penicillium chrysogenum is not only an industrially important filamentous fungus for penicillin production, but it also represents as a promising cell factory for production of natural products. Development of efficient transformation systems with suitable selection markers is essential for genetic manipulations in P. chrysogenum. In this study, we have constructed a new and efficient Agrobacterium tumefaciens-mediated transformation (ATMT) system with two different selection markers conferring the resistance to nourseothricin and phleomycin for P. chrysogenum. Under the optimized conditions for co-cultivation at 22 °C for 60 h with acetosyringone concentration of 200 μM, the transformation efficiency of the ATMT system could reach 5009 ± 96 transformants per 10⁶ spores. The obtained transformants could be exploited as the T-DNA insertion mutants for screening genes involved in morphogenesis and secondary metabolism. Especially, the constructed ATMT system was applied successfully to generate a knockout mutant of the laeA regulatory gene and relevant complementation strains in a wild strain of P. chrysogenum. Our results indicated that the LaeA regulator controls growth, sporulation, osmotic stress response and antibiotic production in P. chrysogenum, but its function is reliant on nitrogen sources. Furthermore, we showed that the laeA orthologous genes from the citrus postharvest pathogen P. digitatum and from the industrial fungus Aspergillus niger could recover the phenotypic defects in the P. chrysogenum laeA deletion mutant. Conclusively, this work provides a new ATMT system, which can be employed for T-DNA insertional mutagenesis, heterologous gene expression or for molecular inspections of potential genes related to secondary metabolism in P. chrysogenum.     

Intracellular Carbon Fluxes in Riboflavin-Producing Bacillussubtilis during Growth on Two-Carbon Substrate Mixtures

Metabolic responses to cofeeding of different carbon substrates in carbon-limited chemostat cultures were investigated with riboflavin-producing Bacillus subtilis. Relative to the carbon content (or energy content) of the substrates, the biomass yield was lower in all cofeeding experiments than with glucose alone. The riboflavin yield, in contrast, was significantly increased in the acetoin- and gluconate-cofed cultures. In these two scenarios, unusually high intracellular ATP-to-ADP ratios correlated with improved riboflavin yields. Nuclear magnetic resonance spectra recorded with amino acids obtained from biosynthetically directed fractional ¹³C labeling experiments were used in an isotope isomer balancing framework to estimate intracellular carbon fluxes. The glycolysis-to-pentose phosphate (PP) pathway split ratio was almost invariant at about 80% in all experiments, a result that was particularly surprising for the cosubstrate gluconate, which feeds directly into the PP pathway. The in vivo activities of the tricarboxylic acid cycle, in contrast, varied more than twofold. The malic enzyme was active with acetate, gluconate, or acetoin cofeeding but not with citrate cofeeding or with glucose alone. The in vivo activity of the gluconeogenic phosphoenolpyruvate carboxykinase was found to be relatively high in all experiments, with the sole exception of the gluconate-cofed culture.     

Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver

Computational models based on the metabolism of stable isotope tracers can yield valuable insight into the metabolic basis of disease. The complexity of these models is limited by the number of tracers and the ability to characterize tracer labeling in downstream metabolites. NMR spectroscopy is ideal for multiple tracer experiments since it precisely detects the position of tracer nuclei in molecules, but it lacks sensitivity for detecting low-concentration metabolites. GC-MS detects stable isotope mass enrichment in low-concentration metabolites, but lacks nuclei and positional specificity. We performed liver perfusions and in vivo infusions of ²H and ¹³C tracers, yielding complex glucose isotopomers that were assigned by NMR and fit to a newly developed metabolic model. Fluxes regressed from ²H and ¹³C NMR positional isotopomer enrichments served to validate GC-MS-based flux estimates obtained from the same experimental samples. NMR-derived fluxes were largely recapitulated by modeling the mass isotopomer distributions of six glucose fragment ions measured by GC-MS. Modest differences related to limited fragmentation coverage of glucose C1–C3 were identified, but fluxes such as gluconeogenesis, glycogenolysis, cataplerosis and TCA cycle flux were tightly correlated between the methods. Most importantly, modeling of GC-MS data could assign fluxes in primary mouse hepatocytes, an experiment that is impractical by ²H or ¹³C NMR.     

Enrichment of biologically active 18-β glycyrrhetinic acid in Glycyrrhiza glabra root by solid state fermentation

This paper describes the in situ bioconversion of glycyrrhizin of Glycyrrhiza glabra root to 18-β glycyrrhetinic acid by solid state fermentation. Fermentation was carried out with two different fungal strains, Penicillium chrysogenum and Rhizopus oryzae. The solid state fermentation was carried out under stationary state and under rotating state. Penicillium chrysogenum is a better producer of 18-β glycyrrhetinic acid than Rhizopus oryzae. The induced P. chrysogenum seed culture produces higher 18-β glycyrrhetinic acid with 2.955 mg g^?1 and maximum β-glucuronidase activity of 3,583.8 U ml^?1 under stationary solid state fermentation. The mycelium growth and bioconversion rate is highest at pH of 5.5 and 4.5, respectively. G. glabra root supplemented with a solution of dextrose 9 g l^?1, MnSO₄?·?H₂O 3 g l^?1 and (NH₄)₂SO₄ 0.540 g l^?1 produces 48.580 mg of 18-β glycyrrhetinic acid per gram of G. glabra root, i.e. 86.74 % bioconversion by P. chrysogenum in 96 h under stationary state solid state fermentation.