Marco Oldiges

Metabolomics: current state and evolving methodologies and tools.

In recent years, metabolomics developed to an accepted and valuable tool in life sciences. Substantial improvements of analytical hardware allow metabolomics to run routinely now. Data are successfully used to investigate genotype–phenotype relations of strains and mutants. Metabolomics facilitates metabolic engineering to optimise mircoorganisms for white biotechnology and spreads to the investigation of biotransformations and cell culture. Metabolomics serves not only as a source of qualitative but also quantitative data of intra-cellular metabolites essential for the model-based description of the metabolic network operating under in vivo conditions. To collect reliable metabolome data sets, culture and sampling conditions, as well as the cells’ metabolic state, are crucial. Hence, application of biochemical engineering principles and method standardisation efforts become important. Together with the other more established omics technologies, metabolomics will strengthen its claim to contribute to the detailed understanding of the in vivo function of gene products, biochemical and regulatory networks and, even more ambitious, the mathematical description and simulation of the whole cell in the systems biology approach. This knowledge will allow the construction of designer organisms for process application using biotransformation and fermentative approaches making effective use of single enzymes, whole microbial and even higher cells.

l-Valine Production with Pyruvate Dehydrogenase Complex-Deficient Corynebacterium glutamicum

ABSTRACT Corynebacterium glutamicum was engineered for the production of l-valine from glucose by deletion of the aceE gene encoding the E1p enzyme of the pyruvate dehydrogenase complex and additional overexpression of the ilvBNCE genes encoding the l-valine biosynthetic enzymes acetohydroxyacid synthase, isomeroreductase, and transaminase B. In the absence of cellular growth, C. glutamicum ΔaceE showed a relatively high intracellular concentration of pyruvate (25.9 mM) and produced significant amounts of pyruvate, l-alanine, and l-valine from glucose as the sole carbon source. Lactate or acetate was not formed. Plasmid-bound overexpression of ilvBNCE in C. glutamicum ΔaceE resulted in an approximately 10-fold-lower intracellular pyruvate concentration (2.3 mM) and a shift of the extracellular product pattern from pyruvate and l-alanine towards l-valine. In fed-batch fermentations at high cell densities and an excess of glucose, C. glutamicum ΔaceE(pJC4ilvBNCE) produced up to 210 mM l-valine with a volumetric productivity of 10.0 mM h−1 (1.17 g l−1 h−1) and a maximum yield of about 0.6 mol per mol (0.4 g per g) of glucose.

Metabolic impact of redox cofactor perturbations in Saccharomyces cerevisiae

Redox cofactors play a pivotal role in coupling catabolism with anabolism and energy generation during metabolism. There exists a delicate balance in the intracellular level of these cofactors to ascertain an optimal metabolic output. Therefore, cofactors are emerging to be attractive targets to induce widespread changes in metabolism. We present a detailed analysis of the impact of perturbations in redox cofactors in the cytosol or mitochondria on glucose and energy metabolism in Saccharomyces cerevisiae to aid metabolic engineering decisions that involve cofactor engineering. We enhanced NADH oxidation by introducing NADH oxidase or alternative oxidase, its ATP-mediated conversion to NADPH using NADH kinase as well as the interconversion of NADH and NADPH independent of ATP by the soluble, non-proton-translocating bacterial transhydrogenase. Decreasing cytosolic NADH level lowered glycerol production, while decreasing mitochondrial NADH lowered ethanol production. However, when these reactions were coupled with NADPH production, the metabolic changes were more moderated. The direct consequence of these perturbations could be seen in the shift of the intracellular concentrations of the cofactors. The changes in product profile and intracellular metabolite levels were closely linked to the ATP requirement for biomass synthesis and the efficiency of oxidative phosphorylation, as estimated from a simple stoichiometric model. The results presented here will provide valuable insights for a quantitative understanding and prediction of cellular response to redox-based perturbations for metabolic engineering applications.

An automated workflow for enhancing microbial bioprocess optimization on a novel microbioreactor platform

BackgroundHigh-throughput methods are widely-used for strain screening effectively resulting in binary information regarding high or low productivity. Nevertheless achieving quantitative and scalable parameters for fast bioprocess development is much more challenging, especially for heterologous protein production. Here, the nature of the foreign protein makes it impossible to predict the, e.g. best expression construct, secretion signal peptide, inductor concentration, induction time, temperature and substrate feed rate in fed-batch operation to name only a few. Therefore, a high number of systematic experiments are necessary to elucidate the best conditions for heterologous expression of each new protein of interest.ResultsTo increase the throughput in bioprocess development, we used a microtiter plate based cultivation system (Biolector) which was fully integrated into a liquid-handling platform enclosed in laminar airflow housing. This automated cultivation platform was used for optimization of the secretory production of a cutinase from Fusarium solani pisi with Corynebacterium glutamicum. The online monitoring of biomass, dissolved oxygen and pH in each of the microtiter plate wells enables to trigger sampling or dosing events with the pipetting robot used for a reliable selection of best performing cutinase producers. In addition to this, further automated methods like media optimization and induction profiling were developed and validated. All biological and bioprocess parameters were exclusively optimized at microtiter plate scale and showed perfect scalable results to 1 L and 20 L stirred tank bioreactor scale.ConclusionsThe optimization of heterologous protein expression in microbial systems currently requires extensive testing of biological and bioprocess engineering parameters. This can be efficiently boosted by using a microtiter plate cultivation setup embedded into a liquid-handling system, providing more throughput by parallelization and automation. Due to improved statistics by replicate cultivations, automated downstream analysis, and scalable process information, this setup has superior performance compared to standard microtiter plate cultivation.

Metabolic and transcriptional response to cofactor perturbations in Escherichia coli.

Metabolic cofactors such as NADH and ATP play important roles in a large number of cellular reactions, and it is of great interest to dissect the role of these cofactors in different aspects of metabolism. Toward this goal, we overexpressed NADH oxidase and the soluble F1-ATPase in Escherichia coli to lower the level of NADH and ATP, respectively. We used a global interaction network, comprising of protein interactions, transcriptional regulation, and metabolic networks, to integrate data from transcription profiles, metabolic fluxes, and the metabolite levels. We identified high-scoring networks for the two strains. The results revealed a smaller, but denser network for perturbations of ATP level, compared with that of NADH level. The action of many global transcription factors such as ArcA, Fnr, CRP, and IHF commonly involved both NADH and ATP, whereas others responded to either ATP or NADH. Overexpressing NADH oxidase invokes response in widespread aspects of metabolism involving the redox cofactors (NADH and NADPH), whereas ATPase has a more focused response to restore ATP level by enhancing proton translocation mechanisms and repressing biosynthesis. Interestingly, NADPH played a key role in restoring redox homeostasis through the concerted activity of isocitrate dehydrogenase and UdhA transhydrogenase. We present a reconciled network of regulation that illustrates the overlapping and distinct aspects of metabolism controlled by NADH and ATP. Our study contributes to the general understanding of redox and energy metabolism and should help in developing metabolic engineering strategies in E. coli.

Stimulation, monitoring, and analysis of pathway dynamics by metabolic profiling in the aromatic amino acid pathway

Using a concerted approach of biochemical standard preparation, analytical access via LC‐MS/MS, glucose pulse, metabolic profiling, and statistical data analysis, the metabolism dynamics in the aromatic amino acid pathway has been stimulated, monitored, and analyzed in different tyrosine‐auxotrophic l‐phenylalanine‐producing Escherichia coli strains. During the observation window from –4 s (before) up to 27 s after the glucose pulse, the dynamics of the first five enzymatic reactions in the aromatic amino acid pathway was observed by measuring intracellular concentrations of 3‐deoxy‐d‐arabino‐heptulosonate 7‐phosphate DAH(P), 3‐dehydroquinate (3‐DHQ), 3‐dehydroshikimate (3‐DHS), shikimate 3‐phosphate (S3P), and shikimate (SHI), together with the pathway precursors phosphoenolpyruvate (PEP) and P5P, the lumped pentose phosphate pool as an alternative to the nondetectable erythrose 4‐phosphate (E4P). Provided that a sufficient fortification of the carbon flux into the pathway of interest is ensured, respective metabolism dynamics can be observed. On the basis of the intracellular pool measurements, the standardized pool velocities were calculated, and a simple, data‐driven criterion‐called “pool efflux capacity” (PEC)‐is derived. Despite its simplifying system description, the criterion managed to identify the well‐known AroB limitation in the E. coli strain A (genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr amp) and it also succeeded to identify AroL and AroA (in strain B, genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr aroB amp) as promising metabolic engineering targets to alleviate respective flux control in subsequent l‐Phe producing strains. Furthermore, using of a simple correlation analysis, the reconstruction of the metabolite sequence of the observed pathway was enabled. The results underline the necessity to extend the focus of glucose pulse experiments by studying not only the central metabolism but also anabolic pathways.

Importance of NADPH supply for improved L-valine formation in Corynebacterium glutamicum

Cofactor recycling is known to be crucial for amino acid synthesis. Hence, cofactor supply was now analyzed for L‐valine to identify new targets for an improvement of production. The central carbon metabolism was analyzed by stoichiometric modeling to estimate the influence of cofactors and to quantify the theoretical yield of L‐valine on glucose. Three different optimal routes for L‐valine biosynthesis were identified by elementary mode (EM) analysis. The modes differed mainly in the manner of NADPH regeneration, substantiating that the cofactor supply may be crucial for efficient L‐valine production. Although the isocitrate dehydrogenase as an NADPH source within the tricarboxylic acid cycle only enables an L‐valine yield of YVal/Glc = 0.5 mol L‐valine/mol glucose (mol Val/mol Glc), the pentose phosphate pathway seems to be the most promising NADPH source. Based on the theoretical calculation of EMs, the gene encoding phosphoglucoisomerase (PGI) was deleted to achieve this EM with a theoretical yield YVal/Glc = 0.86 mol Val/mol Glc during the production phase. The intracellular NADPH concentration was significantly increased in the PGI‐deficient mutant. L‐Valine yield increased from 0.49 ± 0.13 to 0.67 ± 0.03 mol Val/mol Glc, and, concomitantly, the formation of by‐products such as pyruvate was reduced.

Modeling metabolic networks in C. glutamicum : a comparison of rate laws in combination with various parameter optimization strategies

BackgroundTo understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1) experimental measurement of participating molecules, (2) assignment of rate laws to each reaction, and (3) parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem.ResultsWe investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in C. glutamicum. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1) coarse-grained comparison of the algorithms on all models and (2) fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis.ConclusionA mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics model. A Langevin model is advisable to take stochastic effects into account. To estimate the model parameters, three algorithms are particularly useful: For first attempts the settings-free Tribes algorithm yields valuable results. Particle swarm optimization and differential evolution provide significantly better results with appropriate settings.

Comparative 13C Metabolic Flux Analysis of Pyruvate Dehydrogenase Complex-Deficient, l-Valine-Producing Corynebacterium glutamicum

ABSTRACT l-Valine can be formed successfully using C. glutamicum strains missing an active pyruvate dehydrogenase enzyme complex (PDHC). Wild-type C. glutamicum and four PDHC-deficient strains were compared by 13C metabolic flux analysis, especially focusing on the split ratio between glycolysis and the pentose phosphate pathway (PPP). Compared to the wild type, showing a carbon flux of 69% ± 14% through the PPP, a strong increase in the PPP flux was observed in PDHC-deficient strains with a maximum of 113% ± 22%. The shift in the split ratio can be explained by an increased demand of NADPH for l-valine formation. In accordance, the introduction of the Escherichia coli transhydrogenase PntAB, catalyzing the reversible conversion of NADH to NADPH, into an l-valine-producing C. glutamicum strain caused the PPP flux to decrease to 57% ± 6%, which is below the wild-type split ratio. Hence, transhydrogenase activity offers an alternative perspective for sufficient NADPH supply, which is relevant for most amino acid production systems. Moreover, as demonstrated for l-valine, this bypass leads to a significant increase of product yield due to a concurrent reduction in carbon dioxide formation via the PPP.

Monitoring and Modeling of the Reaction Dynamics in the Valine/Leucine Synthesis Pathway in Corynebacterium glutamicum

The intracellular concentrations of the valine and leucine pathway intermediates in a Corynebacterium glutamicum strain were measured during a transient state. The data were obtained by performing a glucose stimulus‐response experiment with the use of a rapid sampling device and advanced mass spectrometry. The glucose stimulus resulted in a 3‐fold increase in the intracellular pyruvate concentration within less than a second, demonstrating the very fast interactions in metabolic networks. The samples were taken at subsecond intervals for a time period of 25 s. The time courses of the metabolite concentrations formed the experimental basis of a mathematical model simulating the fluxes and concentrations in the valine/leucine pathway. The implementation of a model selection criterion based on the second law of thermodynamics is demonstrated to be essential for the identification of realistic and unique models. Large differences between the enzyme properties determined in vitro and those determined in vivo by the model were observed with the in vivo maximal rates being almost an order of magnitude larger than the in vitro maximal rates. The transamination of ketoisovalerate (KIV) to valine is carried out mainly by the transaminase B enzyme, with the transaminase C enzyme playing a minor role. The availability of the cofactors NADP and NADPH only has modest influence on the flux through the valine pathway, while the influence of NAD and NADH on the flux through the leucine pathway is negligible.