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Subject: search.filters.subject.540Subject: search.filters.subject.620Start date: 2020Institute: search.filters.UBSInstitut.Institut für Bioverfahrenstechnik

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Now showing 1 - 5 of 5
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    Streamlining the analysis of dynamic 13C-labeling patterns for the metabolic engineering of corynebacterium glutamicum as L-histidine production host
    (2020) Feith, André; Schwentner, Andreas; Teleki, Attila; Favilli, Lorenzo; Blombach, Bastian; Takors, Ralf
    Today’s possibilities of genome editing easily create plentitudes of strain mutants that need to be experimentally qualified for configuring the next steps of strain engineering. The application of design-build-test-learn cycles requires the identification of distinct metabolic engineering targets as design inputs for subsequent optimization rounds. Here, we present the pool influx kinetics (PIK) approach that identifies promising metabolic engineering targets by pairwise comparison of up- and downstream 13C labeling dynamics with respect to a metabolite of interest. Showcasing the complex l-histidine production with engineered Corynebacterium glutamicum l-histidine-on-glucose yields could be improved to 8.6 ± 0.1 mol% by PIK analysis, starting from a base strain. Amplification of purA, purB, purH, and formyl recycling was identified as key targets only analyzing the signal transduction kinetics mirrored in the PIK values.
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    Predicting by-product gradients of baker’s yeast production at industrial scale : a practical simulation approach
    (2020) Sarkizi Shams Hajian, Christopher; Haringa, Cees; Noorman, Henk; Takors, Ralf
    Scaling up bioprocesses is one of the most crucial steps in the commercialization of bioproducts. While it is known that concentration and shear rate gradients occur at larger scales, it is often too risky, if feasible at all, to conduct validation experiments at such scales. Using computational fluid dynamics equipped with mechanistic biochemical engineering knowledge of the process, it is possible to simulate such gradients. In this work, concentration profiles for the by-products of baker’s yeast production are investigated. By applying a mechanistic black-box model, concentration heterogeneities for oxygen, glucose, ethanol, and carbon dioxide are evaluated. The results suggest that, although at low concentrations, ethanol is consumed in more than 90% of the tank volume, which prevents cell starvation, even when glucose is virtually depleted. Moreover, long exposure to high dissolved carbon dioxide levels is predicted. Two biomass concentrations, i.e., 10 and 25 g/L, are considered where, in the former, ethanol production is solely because of overflow metabolism while, in the latter, 10% of the ethanol formation is due to dissolved oxygen limitation. This method facilitates the prediction of the living conditions of the microorganism and its utilization to address the limitations via change of strain or bioreactor design or operation conditions. The outcome can also be of value to design a representative scale-down reactor to facilitate strain studies.
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    Scale-up of gas fermentations : modelling tools for risk minimisation
    (2020) Siebler, Flora
    The reduction of greenhouse gas emissions is a global endeavour supported by society, politics and industry. In recent years, circular economy, reducing the exploitation of fossil energy sources, have increased the demand for new solutions when producing commodities and fine chemicals. Caboxydotrophic fermentations with acetogenic bacteria are potential processes in order to reach these goals. They convert gaseous substrates such as CO, and CO2/H2 mixtures. However, gases as sole substrate are rather challenging, not only in small lab-scales but especially in large-scale. Transferring an efficient fermentation process from experimental to industrial scales often results in unpredictable performance losses. This study presents an in silico concept minimising possible risks in gas fermentations up-scaling. First, the economical feasibility of various fermentation methods is investigated. Then, two computational tools are presented using Clostridium ljungdahlii as model organism and synthesis gas as substrate in a 125 m3 bubble column reactor. The combination of economical investigation with modelling tools show high potential for successful scale-up of gas fermentations. With this concept feasibility, reactor design, operation mode and general risk minimisation can be analysed and specified.
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    Subcellular fractionation enables assessment of nucleotide sugar donors Inside the Golgi apparatus as a prerequisite for unraveling culture impacts on glycoforms of antibodies
    (2025) Regett, Niklas; Dieterle, Marcel; Peters, Fleur; Deuring, Max; Stegmaier, Kaja; Teleki, Attila; Takors, Ralf
    Glycosylation is a critical quality attribute in biopharmaceuticals that influences crucial properties, such as biological activity and blood clearance. Current methods for modeling glycosylation typically rely on imprecise or limited data on nucleotide sugar donor (NSD) dynamics. These methods use in vitro transporter kinetics or flux balance analysis, which overlook the key aspects of metabolic regulation. We devised an integrative workflow for absolute subcellular NSD quantification in both cytoplasm and secretory organelles. Using subcellular fractionation, exhaustive sample extraction, and liquid chromatography triple‐quadrupole tandem mass spectrometry, we accurately measured NSD concentrations ranging from 1.6 amol/cell to 3 fmol/cell. As expected, NSD concentration profiles aligned closely with the glycan distributions on antibodies, particularly after nutrient pulsing to stimulate NSD production, showcasing method validity. This method enables empirical observation of compartment‐specific NSD dynamics. Thus, this study provides novel insights indicating that N‐glycosylation, which governs NSD supply, is primarily regulated within the Golgi apparatus (GA). This method offers a novel tool to obtain sophisticated data for a more efficient optimization of glycosylation processes in production cell lines.
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    The knowledge driven DBTL cycle provides mechanistic insights while optimising dopamine production in Escherichia coli
    (2025) Hägele, Lorena; Trachtmann, Natalia; Takors, Ralf
    Background. Dopamine is a promising organic compound with several key applications in emergency medicine, diagnosis and treatment of cancer, production of lithium anodes, and wastewater treatment. Since studies on in vivo dopamine production are limited, this study demonstrates the development and optimisation of a dopamine production strain by the help of the knowledge driven design-build-test-learn (DBTL) cycle for rational strain engineering. Results. The knowledge driven DBTL cycle, involving upstream in vitro investigation, is an automated workflow that enables both mechanistic understanding and efficient DBTL cycling. Following the in vitro cell lysate studies, the results were translated to the in vivo environment through high-throughput ribosome binding site (RBS) engineering. As a result, we developed a dopamine production strain capable of producing dopamine at concentrations of 69.03 ± 1.2 mg/L which equals 34.34 ± 0.59 mg/gbiomass. Compared to state-of-the-art in vivo dopamine production, our approach improved performance by 2.6 and 6.6-fold, respectively.Conclusion. In essence, a highly efficient dopamine production strain was developed by implementing the knowledge driven DBTL cycle involving upstream in vitro investigation. The fine-tuning of the dopamine pathway by high-throughput RBS engineering clearly demonstrated the impact of GC content in the Shine-Dalgarno sequence on the RBS strength.