Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli

The use of parallel labeling experiments for ¹³C metabolic flux analysis (¹³C-MFA) has emerged in recent years as the new gold standard in fluxomics. The methodology has been termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. In this contribution, we have tested the limits of COMPLETE-MFA by demonstrating integrated analysis of 14 parallel labeling experiments with Escherichia coli. An effort on such a massive scale has never been attempted before. In addition to several widely used isotopic tracers such as [1,2-¹³C]glucose and mixtures of [1-¹³C]glucose and [U-¹³C]glucose, four novel tracers were applied in this study: [2,3-¹³C]glucose, [4,5,6-¹³C]glucose, [2,3,4,5,6-¹³C]glucose and a mixture of [1-¹³C]glucose and [4,5,6-¹³C]glucose. This allowed us for the first time to compare the performance of a large number of isotopic tracers. Overall, there was no single best tracer for the entire E. coli metabolic network model. Tracers that produced well-resolved fluxes in the upper part of metabolism (glycolysis and pentose phosphate pathways) showed poor performance for fluxes in the lower part of metabolism (TCA cycle and anaplerotic reactions), and vice versa. The best tracer for upper metabolism was 80% [1-¹³C]glucose+20% [U-¹³C]glucose, while [4,5,6-¹³C]glucose and [5-¹³C]glucose both produced optimal flux resolution in the lower part of metabolism. COMPLETE-MFA improved both flux precision and flux observability, i.e. more independent fluxes were resolved with smaller confidence intervals, especially exchange fluxes. Overall, this study demonstrates that COMPLETE-MFA is a powerful approach for improving flux measurements and that this methodology should be considered in future studies that require very high flux resolution.     

Parallel labeling experiments validate Clostridium acetobutylicum metabolic network model for 13C metabolic flux analysis

In this work, we provide new insights into the metabolism of Clostridium acetobutylicum ATCC 824 obtained using a systematic approach for quantifying fluxes based on parallel labeling experiments and ¹³C-metabolic flux analysis (¹³C-MFA). Here, cells were grown in parallel cultures with [1-¹³C]glucose and [U-¹³C]glucose as tracers and ¹³C-MFA was used to quantify intracellular metabolic fluxes. Several metabolic network models were compared: an initial model based on current knowledge, and extended network models that included additional reactions that improved the fits of experimental data. While the initial network model did not produce a statistically acceptable fit of ¹³C-labeling data, an extended network model with five additional reactions was able to fit all data with 292 redundant measurements. The model was subsequently trimmed to produce a minimal network model of C. acetobutylicum for ¹³C-MFA, which could still reproduce all of the experimental data. The flux results provided valuable new insights into the metabolism of C. acetobutylicum. First, we found that TCA cycle was effectively incomplete, as there was no measurable flux between α-ketoglutarate and succinyl-CoA, succinate and fumarate, and malate and oxaloacetate. Second, an active pathway was identified from pyruvate to fumarate via aspartate. Third, we found that isoleucine was produced exclusively through the citramalate synthase pathway in C. acetobutylicum and that CAC3174 was likely responsible for citramalate synthase activity. These model predictions were confirmed in several follow-up tracer experiments. The validated metabolic network model established in this study can be used in future investigations for unbiased ¹³C-flux measurements in C. acetobutylicum.     

Mechanical insights of oxythiamine compound as potent inhibitor for human transketolase-like protein 1 (TKTL1 protein)

Transketolase is a connecting link between glycolytic and pentose phosphate pathway, which is considered as the rate-limiting step due to synthesis of large number of ATP molecule and it can be proposed as a plausible target facilitating the growth of cancerous cells suggesting its potential role in cancer. Oxythiamine, an antimetabolite has been proved to be an efficient anticancerous compound in vitro, but its structural elucidation of the inhibitory mechanism has not yet been done against the human transketolase-like 1 protein (TKTL1). The three-dimensional (3D) structure of TKTL1 protein was modeled and subjected for refinement, stability and validation. Based on the reported homologs of transketolase (TKT), the active site residues His46, Ser49, Ser52, Ser53, Ile56, Leu82, Lys84, Leu123, Ser125, Glu128, Asp154, His160, Thr216 and Lys218 were identified and considered for molecular-modeling studies. Docking studies reveal the H-bond interactions with residues Ser49 and Lys218 that could play a major role in the activity of TKTL1. Molecular dynamics (MD) simulation study was performed to reveal the comparative stability of both native and complex forms of TKTL1. MD trajectory at 30?ns, confirm the role of active site residues Ser49, Lys84, Glu128, His160 and Lys218 in suppressing the activity of TKTL1. Glu128 is observed to be the most important residue for deprotonation state of the aminopyrimidine moiety and preferred to be the site of inhibitory action. Thus, the proposed mechanism of inhibition through in silico studies would pave the way for structure-oriented drug designing against cancer.     

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.     

Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system

¹³C-Metabolic flux analysis (¹³C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by ¹³C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for ¹³C-MFA. The best single tracers were doubly ¹³C-labeled glucose tracers, including [1,6-¹³C]glucose, [5,6-¹³C]glucose and [1,2-¹³C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6-¹³C]glucose and [1,2-¹³C]glucose. Combined analysis of [1,6-¹³C]glucose and [1,2-¹³C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1-¹³C]glucose +20% [U-¹³C]glucose.     

13C metabolic flux analysis of microbial and mammalian systems is enhanced with GC-MS measurements of glycogen and RNA labeling

¹³C metabolic flux analysis (¹³C-MFA) is a widely used tool for quantitative analysis of microbial and mammalian metabolism. Until now, ¹³C-MFA was based mainly on measurements of isotopic labeling of amino acids derived from hydrolyzed biomass proteins and isotopic labeling of extracted intracellular metabolites. Here, we demonstrate that isotopic labeling of glycogen and RNA, measured with gas chromatography-mass spectrometry (GC-MS), provides valuable additional information for ¹³C-MFA. Specifically, we demonstrate that isotopic labeling of glucose moiety of glycogen and ribose moiety of RNA greatly enhances resolution of metabolic fluxes in the upper part of metabolism; importantly, these measurements allow precise quantification of net and exchange fluxes in the pentose phosphate pathway. To demonstrate the practical importance of these measurements for ¹³C-MFA, we have used Escherichia coli as a model microbial system and CHO cells as a model mammalian system. Additionally, we have applied this approach to determine metabolic fluxes of glucose and xylose co-utilization in the E. coli ΔptsG mutant. The convenience of measuring glycogen and RNA, which are stable and abundant in microbial and mammalian cells, offers the following key advantages: reduced sample size, no quenching required, no extractions required, and GC-MS can be used instead of more costly LC-MS/MS techniques. Overall, the presented approach for ¹³C-MFA will have widespread applicability in metabolic engineering and biomedical research.     

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.     

Effect of the global redox sensing/regulation networks on Escherichia coli and metabolic flux distribution based on C-13 labeling experiments

Escherichia coli has several elaborate sensing mechanisms for response to the availability of oxygen and the presence of other electron acceptors. Among them, the one component Fnr protein and the two-component Arc system coordinate the adaptive responses to oxygen availability. To systematically investigate the contribution of Arc- and Fnr-dependent regulation in catabolism, glucose-limited chemostat cultures were conducted on wild-type E. coli, an arcA mutant, an fnr mutant, and an arcAfnr double mutant strains under a well-defined semi-aerobic condition. The metabolic flux distributions of the cultures of these strains were estimated based on C-13 labeling experiments. It was shown that the oxidative pentose phosphate (PP) pathway was functioning at low level under semi-aerobic condition. The fluxes through pyruvate dehydrogenase (PDH) and tricarboxylic acid (TCA) cycle were found to be lower in the arcA mutant and the arcAfnr double mutant strains than that in the wild-type strain, although the expression of the genes involved in these pathways have been proved to be derepressed in the mutant strains ([Shalel-Levanon, S., San, K.Y., Bennett, G.N., 2005a. Effect of ArcA and FNR on the expression of genes related to the oxygen regulation and the glycolysis pathway in Escherichia coli under microaerobic growth conditions. Biotechnol. Bioeng. 92, 147-159; Shalel-Levanon, S., San, K.Y., Bennett, G.N., 2005c. Effect of oxygen, and ArcA and FNR regulators on the expression of genes related to the electron transfer chain and the TCA cycle in Escherichia coli. Metab. Eng. 7, 364-374]). The significantly higher lactate production in the arcAfnr double mutant strain was shown to be an indirect effect caused by the reduced pyruvate formate-lyase (PFL) and PDH fluxes as well as the intracellular redox state.     

Metabolic flux analysis for a ppc mutant Escherichia coli based on 13C-labelling experiments together with enzyme activity assays and intracellular metabolite measurements

The physiology and central metabolism of a ppc mutant Escherichia coli were investigated based on the metabolic flux distribution obtained by (13)C-labelling experiments using gas chromatography-mass spectrometry (GC-MS) and 2-dimensional nuclear magnetic resonance (2D NMR) strategies together with enzyme activity assays and intracellular metabolite concentration measurements. Compared to the wild type, its ppc mutant excreted little acetate and produced less carbon dioxide at the expense of a slower growth rate and a lower glucose uptake rate. Consequently, an improvement of the biomass yield on glucose was observed in the ppc mutant. Enzyme activity measurements revealed that isocitrate lyase activity increased by more than 3-fold in the ppc mutant. Some TCA cycle enzymes such as citrate synthase, aconitase and malate dehydrogenase were also upregulated, but enzymes of glycolysis and the pentose phosphate pathway were downregulated. The intracellular intermediates in the glycolysis and the pentose phosphate pathway, therefore, accumulated, while acetyl coenzyme A and oxaloacetate concentrations decreased in the ppc mutant. The intracellular metabolic flux analysis uncovered that deletion of ppc resulted in the appearance of the glyoxylate shunt, with 18.9% of the carbon flux being channeled via the glyoxylate shunt. However, the flux of the pentose phosphate pathway significantly decreased in the ppc mutant.