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Arne Buchholz

Publications and source records attributed to Arne Buchholz.

3 recordsLinked to original sources

Metabolomics: quantification of intracellular metabolite dynamics.

The rational improvement of microbial strains for the production of primary and secondary metabolites ('metabolic engineering') requires a quantitative understanding of microbial metabolism. A process by which this information can be derived from dynamic fermentation experiments is presented. By applying a substrate pulse to a substrate-limited, steady state culture, cellular metabolism is shifted away from its metabolic steady state. With the aid of a rapid sampling and quenching routine it is possible to take 4-5 samples per second during this process, thus capturing the metabolic response to this stimulus. Over 30 metabolites, nucleotides and cofactors from Escherichia coli metabolism can be extracted and analysed using a range of different techniques, for example enzymatic assays, HPLC and LC-MS methods. Using different substrates as limiting and pulse-substrates (glucose, glycerol), different metabolic pathways and substrate uptake systems are investigated. The resulting plots of intracellular metabolite concentrations against time serve as a data basis for modelling microbial metabolic networks.

Bioreactors↗

Genetic algorithms as a tool for capillary electrophoresis method development.

Capillary electrophoresis is a powerful and versatile analytical tool due to the wide range of separation variables and separation methods possible. CE permits the combination of multiple separation mechanisms (e.g., chiral modifiers, polarity, pH) for the analysis of a large variety of compounds. The main advantage of CE (i.e., the broad range of separation variables) has thus far limited its application. This is due to the nonlinear influence and interactions of different parameters on separation quality, making it difficult to predict trends for the optimization of separation systems and hence hindering CE method development. In this paper, we present a means for rationalizing method development for CE separations using a genetic algorithm. We provide selected examples of separation enhancements achieved in the field of nucleotide and nucleotide sugar separation. An improved method for the enantioselective separation of amino acid derivatives (2-acetylamino-3-phenyl-propionic acid) will also be presented.

Adenine Nucleotides↗

MMT--a pathway modeling tool for data from rapid sampling experiments.

The identification of metabolic regulation is a major concern in metabolic engineering. Metabolic regulation phenomena depend on intracellular compounds such as enzymes, metabolites and cofactors. A complete understanding of metabolic regulation requires quantitative information about these compounds under in vivo conditions. This quantitative knowledge in combination with the known network of metabolic pathways allows the construction of mathematical models that describe the dynamic changes in metabolite concentrations over time. Rapid sampling combined with pulse experiments is a useful tool for the identification of metabolic regulation owing to the transient data they provide. Enzymatic tests in combination with ESI-LC-MS (Electrospray Ionization Liquid Chromatographic Tandem Mass Spectrometry) and HPLC measurements have been used to identify up to 30 metabolites and nucleotides from rapid sampling experiments. A metabolic modeling tool (MMT) that is built on a relational database was developed specifically for analysis of rapid sampling experiments. The tool allows to construct complex pathway models with information stored in the relational database. Parameter fitting and simulation algorithms for the resulting system of Ordinary Differential Equations (ODEs) are part of MMT. Additionally explicit sensitivity functions are calculated. The integration of all necessary algorithms in one tool allows fast model analysis and comparison. Complex models have been developed to describe the central metabolic pathways of Escherichia coli during a glucose pulse experiment.

Algorithms↗