Browsing by Author "Reuss, Matthias"

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    ItemOpen Access
    Identification of factors impeding the production of a single-chain antibody fragment in Escherichia coli by comparing in vivo and in vitro expression
    (2003) Ölschläger, Peter; Lange, Stefan; Schmitt, Jutta; Siemann-Herzberg, Martin; Reuss, Matthias; Schmid, Rolf D.
    In order to produce the atrazine-specific scFv K411B, it was expressed in either the cytoplasm or the periplasm of Escherichia coli BL21(DE3). For periplasmic production, the scFv was N-terminally fused to the pelB leader, whereas the unfused variant resulted in cytoplasmic expression. The extent of protein accumulation differed significantly: The expression level of the scFv with leader was 2.3 times higher than that of the protein without leader. To further investigate this, the respective translation profiles were generated by coupled in vitro transcription/translation assays and gave according results. Periplasmic expression resulted in only 10% correctly folded scFv. The same percentage was obtained when the scFv was expressed in vitro, indicating that the oxidizing environment of the periplasm did not increase proper folding. Thus, the data obtained in vitro confirmed the findings observed in vivo and suggested that the discrepancy in expression levels was due to different translation efficiencies. However, the in vivo production of the scFv with EGFP fused C-terminally (scFv-EGFP) was only successful in the cytoplasm, although in vitro the expression with and without the leader rendered the same production profile. This indicated that neither the translation efficiency nor the solubility but other factors impeded periplasmic expression of the fusion protein.
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    Integrating a dynamic central metabolism model of cancer cells with a hybrid 3D multiscale model for vascular hepatocellular carcinoma growth
    (2022) Lapin, Alexey; Perfahl, Holger; Jain, Harsh Vardhan; Reuss, Matthias
    We develop here a novel modelling approach with the aim of closing the conceptual gap between tumour-level metabolic processes and the metabolic processes occurring in individual cancer cells. In particular, the metabolism in hepatocellular carcinoma derived cell lines (HEPG2 cells) has been well characterized but implementations of multiscale models integrating this known metabolism have not been previously reported. We therefore extend a previously published multiscale model of vascular tumour growth, and integrate it with an experimentally verified network of central metabolism in HEPG2 cells. This resultant combined model links spatially heterogeneous vascular tumour growth with known metabolic networks within tumour cells and accounts for blood flow, angiogenesis, vascular remodelling and nutrient/growth factor transport within a growing tumour, as well as the movement of, and interactions between normal and cancer cells. Model simulations report for the first time, predictions of spatially resolved time courses of core metabolites in HEPG2 cells. These simulations can be performed at a sufficient scale to incorporate clinically relevant features of different tumour systems using reasonable computational resources. Our results predict larger than expected temporal and spatial heterogeneity in the intracellular concentrations of glucose, oxygen, lactate pyruvate, f16bp and Acetyl-CoA. The integrated multiscale model developed here provides an ideal quantitative framework in which to study the relationship between dosage, timing, and scheduling of anti-neoplastic agents and the physiological effects of tumour metabolism at the cellular level. Such models, therefore, have the potential to inform treatment decisions when drug response is dependent on the metabolic state of individual cancer cells.
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    A systems biology approach to dynamic modeling and inter-subject variability of statin pharmacokinetics in human hepatocytes
    (2011) Bucher, Joachim; Riedmaier, Stephan; Schnabel, Anke; Marcus, Katrin; Vacun, Gabriele; Weiss, Thomas S.; Thasler, Wolfgang E.; Nüssler, Andreas K.; Zanger, Ulrich M.; Reuss, Matthias
    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.