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Stuttgart Mühlhausen, Germany

Maier K.,University of Stuttgart | Hofmann U.,University of Stuttgart | Reuss M.,University of Stuttgart | Mauch K.,Insilico Biotechnology AG
BMC Systems Biology | Year: 2010

Background: The liver plays a major role in metabolism and performs a number of vital functions in the body. Therefore, the determination of hepatic metabolite dynamics and the analysis of the control of the respective biochemical pathways are of great pharmacological and medical importance. Extra- and intracellular time-series data from stimulus-response experiments are gaining in importance in the identification of in vivo metabolite dynamics, while dynamic network models are excellent tools for analyzing complex metabolic control patterns. This is the first study that has been undertaken on the data-driven identification of a dynamic liver central carbon metabolism model and its application in the analysis of the distribution of metabolic control in hepatoma cells.Results: Dynamic metabolite data were collected from HepG2 cells after they had been deprived of extracellular glucose. The concentration of 25 extra- and intracellular intermediates was quantified using HPLC, LC-MS-MS, and GC-MS. The in silico metabolite dynamics were in accordance with the experimental data. The central carbon metabolism of hepatomas was further analyzed with a particular focus on the control of metabolite concentrations and metabolic fluxes. It was observed that the enzyme glucose-6-phosphate dehydrogenase exerted substantial negative control over the glycolytic flux, whereas oxidative phosphorylation had a significant positive control. The control over the rate of NADPH consumption was found to be shared between the NADPH-demand itself (0.65) and the NADPH supply (0.38).Conclusions: Based on time-series data, a dynamic central carbon metabolism model was developed for the investigation of new and complex metabolic control patterns in hepatoma cells. The control patterns found support the hypotheses that the glucose-6-phosphate dehydrogenase and the Warburg effect are promising targets for tumor treatment. The systems-oriented identification of metabolite dynamics is a first step towards the genome-based assessment of potential risks posed by nutrients and drugs. © 2010 Maier et al; licensee BioMed Central Ltd.

Wahrheit J.,Saarland University | Niklas J.,Saarland University | Niklas J.,Insilico Biotechnology AG | Heinzle E.,Saarland University
Metabolic Engineering | Year: 2014

Metabolism at the cytosol-mitochondria interface and its regulation is of major importance particularly for efficient production of biopharmaceuticals in Chinese hamster ovary (CHO) cells but also in many diseases. We used a novel systems-oriented approach combining dynamic metabolic flux analysis and determination of compartmental enzyme activities to obtain systems level information with functional, spatial and temporal resolution. Integrating these multiple levels of information, we were able to investigate the interaction of glycolysis and TCA cycle and its metabolic control. We characterized metabolic phases in CHO batch cultivation and assessed metabolic efficiency extending the concept of metabolic ratios. Comparing in situ enzyme activities including their compartmental localization with in vivo metabolic fluxes, we were able to identify limiting steps in glycolysis and TCA cycle. Our data point to a significant contribution of substrate channeling to glycolytic regulation. We show how glycolytic channeling heavily affects the availability of pyruvate for the mitochondria. Finally, we show that the activities of transaminases and anaplerotic enzymes are tailored to permit a balanced supply of pyruvate and oxaloacetate to the TCA cycle in the respective metabolic states. We demonstrate that knowledge about metabolic control can be gained by correlating in vivo metabolic flux dynamics with time and space resolved in situ enzyme activities. © 2014 International Metabolic Engineering Society.

Steinkamper A.,Esslingen University of Applied Sciences | Schmid J.,Insilico Biotechnology AG | Schwartz D.,Esslingen University of Applied Sciences | Biener R.,Esslingen University of Applied Sciences
Journal of Biotechnology | Year: 2015

Actinoplanes friuliensis is a rare actinomycete which produces the highly potent lipopeptide antibiotic friulimicin. This lipopeptide antibiotic is active against a broad range of multi-resistant gram-positive bacteria such as methicillin-resistant Enterococcus sp. and Staphylococcus aureus (MRE, MRSA) strains. Antibiotic biosynthesis and regulation in actinomycetes is very complex. In order to study the biosynthesis of these species and to develop efficient production processes, standardized cultivation conditions are a prerequisite. For this reason a chemically defined production medium for A. friuliensis was developed. With this chemically defined medium it was possible to analyze the influence of medium components on growth and antibiotic biosynthesis.These findings were used to develop process strategies for friulimicin production. The focus of the project presented here was to develop cultivation strategies which included fed-batch and continuous cultivation processes. In fed-batch processes, volumetric productivities for friulimicin of 1-2mg/lh were achieved. In a perfusion process, a very simple cell retention system, which works via sedimentation of the mycelial cell pellets, was used. With this system, stable continuous cultivations with cell retention were dependent on the dilution rate. With a dilution rate of 0.05h-1, cell retention worked well and volumetric productivity of friulimicin was enhanced to 3-5mg/lh. With a higher dilution rate of 0.1h-1, friulimicin production ceased because cell retention was not possible any longer with this simple cell retention system. In order to support process development, cultivation data were used to characterize metabolic fluxes in the developed friulimicin production processes. © 2015 Elsevier B.V.

Bucher J.,University of Stuttgart | Bucher J.,Insilico Biotechnology AG | Riedmaier S.,University of Tubingen | Schnabel A.,Ruhr University Bochum | And 8 more authors.
BMC Systems Biology | Year: 2011

Background: The individual character of pharmacokinetics is of great importance in the risk assessment of new drug leads in pharmacological research. Amongst others, it is severely influenced by the properties and inter-individual variability of the enzymes and transporters of the drug detoxification system of the liver. Predicting individual drug biotransformation capacity requires quantitative and detailed models.Results: In this contribution we present the de novo deterministic modeling of atorvastatin biotransformation based on comprehensive published knowledge on involved metabolic and transport pathways as well as physicochemical properties. The model was evaluated on primary human hepatocytes and parameter identifiability analysis was performed under multiple experimental constraints. Dynamic simulations of atorvastatin biotransformation considering the inter-individual variability of the two major involved enzymes CYP3A4 and UGT1A3 based on quantitative protein expression data in a large human liver bank (n = 150) highlighted the variability in the individual biotransformation profiles and therefore also points to the individuality of pharmacokinetics.Conclusions: A dynamic model for the biotransformation of atorvastatin has been developed using quantitative metabolite measurements in primary human hepatocytes. The model comprises kinetics for transport processes and metabolic enzymes as well as population liver expression data allowing us to assess the impact of inter-individual variability of concentrations of key proteins. Application of computational tools for parameter sensitivity analysis enabled us to considerably improve the validity of the model and to create a consistent framework for precise computer-aided simulations in toxicology. © 2011 Bucher et al; licensee BioMed Central Ltd.

Diaz Ochoa J.G.,Insilico Biotechnology AG | Bucher J.,Insilico Biotechnology AG | Pery A.R.R.,INERIS | Zaldivar Comenges J.M.,Insilico Biotechnology AG | And 3 more authors.
Frontiers in Pharmacology | Year: 2014

In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy. © 2013 Diaz Ochoa, Bucher, Péry, Zaldivar Comenges, Niklas and Mauch.

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