Metabolic control analysis of L-tryptophan producing Escherichia coli applying targeted perturbation with shikimate

L-tryptophan production from glycerol with Escherichia coli was analysed by perturbation studies and metabolic control analysis. The insertion of a non-natural shikimate transporter into the genome of an Escherichia coli L-tryptophan production strain enabled targeted perturbation within the product pathway with shikimate during parallelised short-term perturbation experiments with cells withdrawn from a 15 L fed-batch production process. Expression of the shikimate/H+-symporter gene (shiA) from Corynebacterium glutamicum did not alter process performance within the estimation error. Metabolic analyses and subsequent extensive data evaluation were performed based on the data of the parallel analysis reactors and the production process. Extracellular rates and intracellular metabolite concentrations displayed evident deflections in cell metabolism and particularly in chorismate biosynthesis due to the perturbations with shikimate. Intracellular flux distributions were estimated using a thermodynamics-based flux analysis method, which integrates thermodynamic constraints and intracellular metabolite concentrations to restrain the solution space. Feasible flux distributions, Gibbs reaction energies and concentration ranges were computed simultaneously for the genome-wide metabolic model, with minimum bias in relation to the direction of metabolic reactions. Metabolic control analysis was applied to estimate elasticities and flux control coefficients, predicting controlling sites for L-tryptophan biosynthesis. The addition of shikimate led to enhanced deviations in chorismate biosynthesis, revealing a so far not observed control of 3-dehydroquinate synthase on L-tryptophan formation. The relative expression of the identified target genes was analysed with RT-qPCR. Transcriptome analysis revealed disparities in gene expression and the localisation of target genes to further improve the microbial L-tryptophan producer by metabolic engineering.

Integrating systemic and molecular levels to infer key drivers sustaining metabolic adaptations

Metabolic adaptations to complex perturbations, like the response to pharmacological treatments in multifactorial diseases such as cancer, can be described through measurements of part of the fluxes and concentrations at the systemic level and individual transporter and enzyme activities at the molecular level. In the framework of Metabolic Control Analysis (MCA), ensembles of linear constraints can be built integrating these measurements at both systemic and molecular levels, which are expressed as relative differences or changes produced in the metabolic adaptation. Here, combining MCA with Linear Programming, an efficient computational strategy is developed to infer additional non-measured changes at the molecular level that are required to satisfy these constraints. An application of this strategy is illustrated by using a set of fluxes, concentrations, and differentially expressed genes that characterize the response to cyclin-dependent kinases 4 and 6 inhibition in colon cancer cells. Decreases and increases in transporter and enzyme individual activities required to reprogram the measured changes in fluxes and concentrations are compared with down-regulated and up-regulated metabolic genes to unveil those that are key molecular drivers of the metabolic response.

Improved Synthesis of Flavonoids by Simulation of Nargenine Chalcone Biosynthetic Reaction

Metabolic Control Analysis provides a quantitative description of concentration dynamics with the change in system parameters. A metabolic Control Analysis aids determination of the threshold value of metabolites involved in a reaction and also helps to understand the role of various parameters in a reaction. In this work, a metabolic model of a Naringenine chalcone biosynthetic reaction is defined and a time series simulation was carried out based on the law of Mass action. Initial concentration of p-Coumaroyl-CoA and Malonyl-CoA were taken 5.0*10-2 mM 2.2*10-3 mM respectively. This concentration was then simulated over time for 10 seconds to find the steady state. Final concentration of Naringenine chalcone,CO2, and CoA becomes 8.593946e-004 mM after 5.00 second of simulation at reaction constant 6.587753e-005 mM*ml/s. Steady state solution shows that Initial concentration of Naringenine chalcone was 2.199777e-003 mM which is eventually converted into 2.785128e+013 seconds half-life concentration of product at 7.898e-017 mM/s rate and 0.000000e+000 mM*ml/s rate constant. Phenylpropanoid pathway was analysed to predict all the enzymes that can maximise and minimise the concentration of Malonyl-CoA and P-Coumaroyl-CoA which leads to flavonoid biosynthesis. In the Phenylpropanoid pathway four enzymes Phenylalanine/tyrosine ammonia lyase, trans-cinnamate 4-monooxygenase, Phenylalanine ammonia lyase, maximise the flavonoid biosynthesis. This analysis shows that other enzymes minimise the concentrations of Malonyl-CoA and P-coumaroyl-CoA, these are Cinnamoyl Co A reductase, shikimate O hydroxyl transferase HCT), Oxidoreductase. Furthermore, Protein domain analysis of chalcone synthase mutants ( 1jwx Medicago sativa and 4yjy from Oryza sativa) was done to predict structural features to understand reaction mechanism and structure-based engineering to maximise flavonoid biosynthesis. Natural sequence variation CHS G256A, G256V, G256L, and G256F mutants of residue 256 reduce the size of the active site cavity but quick diversification of product specificity occurs. The threshold concentration of Malonyl-CoA and P-coumaroyl-CoA were predicted, maximisation of this concentration leads to enhanced flavonoid biosynthesis. Inhibition of few enzymes may also maximise the flavonoid biosynthesis if appropriate inhibitors are used and a constant supply of Malonyl-CoA and P-Coumaroyl-CoA is maintained using activator molecules. Chalcone synthase Mutants diversify product specificity that occurs without loss of catalytic activity and any conformational changes.

Constraint-based metabolic control analysis for rational strain engineering

The advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering interventions on flows in metabolic networks and metabolic concentrations, it fails to account for the physiological limitations of the cellular environment and metabolic engineering design constraints. We report here a constraint-based framework based on MCA, Network Response Analysis (NRA), for the rational genetic strain design that incorporates biologically relevant constraints, as well as genome editing restrictions. The NRA core constraints being similar to the ones of Flux Balance Analysis, allow it to be used for a wide range of optimization criteria and with various physiological constraints. We show how the parametrization and introduction of biological constraints enhance the NRA formulation compared to the classical MCA approach, and we demonstrate its features and its ability to generate multiple alternative optimal strategies given several user-defined boundaries and objectives. In summary, NRA is a sophisticated alternative to classical MCA for rational metabolic engineering that accommodates the incorporation of physiological data at metabolic flux, metabolite concentration, and enzyme expression levels.

Organization and control of the ascorbate biosynthesis pathway in plants

ABSTRACTThe enzymatic steps involved in l-ascorbate biosynthesis in photosynthetic organisms (the Smirnoff-Wheeler, SW pathway) has been well established and here we comprehensively analyze the subcellular localization, potential physical interactions of SW pathway enzymes and assess their role in control of ascorbate synthesis. Transient expression of GFP-fusions in Nicotiana benthamiana and Arabidopsis (Arabidopsis thaliana) mutants complemented with genomic constructs showed that while GME is cytosolic, VTC1, VTC2, VTC4, and l-GalDH have cytosolic and nuclear localization. While transgenic lines GME-GFP, VTC4-GFP and l-GalDH-GFP driven by their endogenous promoters accumulated the fusion proteins, the functional VTC2-GFP protein is detected at low level using immunoblot in a complemented vtc2 null mutant. This low amount of VTC2 protein and the extensive analyses using multiple combinations of SW enzymes in N. benthamiana supported the role of VTC2 as the main control point of the pathway on ascorbate biosynthesis. Interaction analysis of SW enzymes using yeast two hybrid did not detect the formation of heterodimers, although VTC1, GME and VTC4 formed homodimers. Further coimmunoprecipitation (CoIP) analysis indicted that consecutive SW enzymes, as well as the first and last enzymes (VTC1 and l-GalDH), associate thereby adding a new layer of complexity to ascorbate biosynthesis. Finally, metabolic control analysis incorporating known kinetic characteristics, showed that previously reported feedback repression at the VTC2 step confers a high flux control coefficient and rationalizes why manipulation of other enzymes has little effect on ascorbate concentration.One sentence summaryMetabolic engineering, genetic analysis and functional mutant complementation identify GDP-l-galactose phosphorylase as the main control point in ascorbate biosynthesis in green tissues.

Metabolic control analysis of hepatic glycogen synthesis in vivo

Multiple insulin-regulated enzymes participate in hepatic glycogen synthesis, and the rate-controlling step responsible for insulin stimulation of glycogen synthesis is unknown. We demonstrate that glucokinase (GCK)-mediated glucose phosphorylation is the rate-controlling step in insulin-stimulated hepatic glycogen synthesis in vivo, by use of the somatostatin pancreatic clamp technique using [13C6]glucose with metabolic control analysis (MCA) in three rat models: 1) regular chow (RC)-fed male rats (control), 2) high fat diet (HFD)-fed rats, and 3) RC-fed rats with portal vein glucose delivery at a glucose infusion rate matched to the control. During hyperinsulinemia, hyperglycemia dose-dependently increased hepatic glycogen synthesis. At similar levels of hyperinsulinemia and hyperglycemia, HFD-fed rats exhibited a decrease and portal delivery rats exhibited an increase in hepatic glycogen synthesis via the direct pathway compared with controls. However, the strong correlation between liver glucose-6-phosphate concentration and net hepatic glycogen synthetic rate was nearly identical in these three groups, suggesting that the main difference between models is the activation of GCK. MCA yielded a high control coefficient for GCK in all three groups. We confirmed these findings in studies of hepatic GCK knockdown using an antisense oligonucleotide. Reduced liver glycogen synthesis in lipid-induced hepatic insulin resistance and increased glycogen synthesis during portal glucose infusion were explained by concordant changes in translocation of GCK. Taken together, these data indicate that the rate of insulin-stimulated hepatic glycogen synthesis is controlled chiefly through GCK translocation.