An energetic profile of Corynebacterium glutamicum underpinned by measured biomass yield on ATP.

The supply and usage of energetic cofactors in metabolism is a central concern for systems metabolic engineering, particularly in case of energy intensive products. One of the most important parameters for systems wide balancing of energetic cofactors is the ATP requirement for biomass formation YATP/Biomass. Despite its fundamental importance, YATP/Biomass values for non-fermentative organisms are still rough estimates deduced from theoretical considerations. For the first time, we present an approach for the experimental determination of YATP/Biomass using comparative 13C metabolic flux analysis (13C MFA) of a wild type strain and an ATP synthase knockout mutant. We show that the energetic profile of a cell can then be deduced from a genome wide stoichiometric model and experimental maintenance data. Particularly, the contributions of substrate level phosphorylation (SLP) and electron transport phosphorylation (ETP) to ATP generation become available which enables the overall energetic efficiency of a cell to be characterized. As a model organism, the industrial platform organism Corynebacterium glutamicum is used. C. glutamicum uses a respiratory type of energy metabolism, implying that ATP can be synthesized either by SLP or by ETP with the membrane-bound F1FO-ATP synthase using the proton motive force (pmf) as driving force. The presence of two terminal oxidases, which differ in their proton translocation efficiency by a factor of three, further complicates energy balancing for this organism. By integration of experimental data and network models, we show that in the wild type SLP and ETP contribute equally to ATP generation. Thus, the role of ETP in respiring bacteria may have been overrated in the past. Remarkably, in the genome wide setting 65% of the pmf is actually not used for ATP synthesis. However, it turns out that, compared to other organisms C. glutamicum still uses its energy budget rather efficiently.

Unravelling the regulatory structure of biochemical networks using stimulus response experiments and large-scale model selection.

To unravel the complex in vivo regulatory interdependences of biochemical networks, experiments with the living organism are absolutely necessary. Stimulus response experiments (SREs) have become increasingly popular in recent years. The response of metabolite concentrations from all major parts of the central metabolism is monitored over time by modem analytical methods, producing several thousand data points. SREs are applied to determine enzyme kinetic parameters and to find unknown enzyme regulatory mechanisms. Owing to the complex regulatory structure of metabolic networks and the amount of measured data, the evaluation of an SRE has to be extensively supported by modelling. If the enzyme regulatory mechanisms are part of the investigation, a large number of models with different enzyme kinetics have to be tested for their ability to reproduce the observed behaviour. In this contribution, a systematic model-building process for data-driven exploratory modelling is introduced with the aim of discovering essential features of the biological system. The process is based on data pre-processing, correlation-based hypothesis generation, automatic model family generation, large-scale model selection and statistical analysis of the best-fitting models followed by an extraction of common features. It is illustrated by the example of the aromatic amino acid synthesis pathway in Escherichia coli.

Applying metabolic profiling techniques for stimulus-response experiments: chances and pitfalls.

So far it is mainly transcriptome and proteome analysis that has been applied to elucidate the correlation between genotype and phenotype although thorough metabolome studies can provide substantial information on the control of the metabolism at the biochemical level. Stimulus-response experiments, i.e. the investigation of metabolism dynamics after a glucose pulse (pulse experiment), can be used to study the in vivo enzyme kinetics offering insight into underlying reaction mechanisms. Usually, this requires rapid cell quenching combined with cell inactivation to'freeze' the microbial metabolism response at a definite time-lag after pulse stimulation. To access the 'frozen' metabolic reply, adequate analytical methods are needed to measure intracellular metabolite concentrations in the cell extract. As shown in the introductory review part, stimulus-response experiments were usually applied to study central metabolism dynamics in wildtype strains. Our own results, presented in the second part of the contribution, indicate that stimulus-response experiments should also be applied to analyse pathway dynamics in anabolic routes. Using the example of the aromatic amino acid pathway, an LC-MS/MS technique is presented that allows the quantification of intracellular pools of central metabolism as well as of the aromatic amino acid pathway. Based on the analytical approach metabolic profiling is performed to monitor the metabolism dynamics after a glucose pulse experiment allowing the conclusion that pulse stimulation is transmitted to the anabolic pathway of interest.

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 delta(pheA tyrA aroF)/pJF119EH aroF(fbr) pheA(fbr) amp) and it also succeeded to identify AroL and AroA (in strain B, genotype delta(pheA tyrA aroF)/pJF119EH aroF(fbr) pheA(fbr) 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.