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Application of metabolic modeling for targeted optimization of high seeding density processes

Process intensification by application of perfusion mode in pre‐stage bioreactors and subsequent inoculation of cell cultures at high seeding densities (HSD) has the potential to meet the increasing requirements of future manufacturing demands. However, process development is currently restrained by...

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Autores principales: Brunner, Matthias, Kolb, Klara, Keitel, Alena, Stiefel, Fabian, Wucherpfennig, Thomas, Bechmann, Jan, Unsoeld, Andreas, Schaub, Jochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248150/
https://www.ncbi.nlm.nih.gov/pubmed/33491766
http://dx.doi.org/10.1002/bit.27693
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author Brunner, Matthias
Kolb, Klara
Keitel, Alena
Stiefel, Fabian
Wucherpfennig, Thomas
Bechmann, Jan
Unsoeld, Andreas
Schaub, Jochen
author_facet Brunner, Matthias
Kolb, Klara
Keitel, Alena
Stiefel, Fabian
Wucherpfennig, Thomas
Bechmann, Jan
Unsoeld, Andreas
Schaub, Jochen
author_sort Brunner, Matthias
collection PubMed
description Process intensification by application of perfusion mode in pre‐stage bioreactors and subsequent inoculation of cell cultures at high seeding densities (HSD) has the potential to meet the increasing requirements of future manufacturing demands. However, process development is currently restrained by a limited understanding of the cell's requirements under these process conditions. The goal of this study was to use extended metabolite analysis and metabolic modeling for targeted optimization of HSD cultivations. The metabolite analysis of HSD N‐stage cultures revealed accumulation of inhibiting metabolites early in the process and flux balance analysis led to the assumption that reactive oxygen species (ROS) were contributing to the fast decrease in cell viability. Based on the metabolic analysis an optimized feeding strategy with lactate and cysteine supplementation was applied, resulting in an increase in antibody titer of up to 47%. Flux balance analysis was further used to elucidate the surprisingly strong synergistic effect of lactate and cysteine, indicating that increased lactate uptake led to reduced ROS formation under these conditions whilst additional cysteine actively reduced ROS via the glutathione pathway. The presented results finally demonstrate the benefit of modeling approaches for process intensification as well as the potential of HSD cultivations for biopharmaceutical manufacturing.
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spelling pubmed-82481502021-07-02 Application of metabolic modeling for targeted optimization of high seeding density processes Brunner, Matthias Kolb, Klara Keitel, Alena Stiefel, Fabian Wucherpfennig, Thomas Bechmann, Jan Unsoeld, Andreas Schaub, Jochen Biotechnol Bioeng ARTICLES Process intensification by application of perfusion mode in pre‐stage bioreactors and subsequent inoculation of cell cultures at high seeding densities (HSD) has the potential to meet the increasing requirements of future manufacturing demands. However, process development is currently restrained by a limited understanding of the cell's requirements under these process conditions. The goal of this study was to use extended metabolite analysis and metabolic modeling for targeted optimization of HSD cultivations. The metabolite analysis of HSD N‐stage cultures revealed accumulation of inhibiting metabolites early in the process and flux balance analysis led to the assumption that reactive oxygen species (ROS) were contributing to the fast decrease in cell viability. Based on the metabolic analysis an optimized feeding strategy with lactate and cysteine supplementation was applied, resulting in an increase in antibody titer of up to 47%. Flux balance analysis was further used to elucidate the surprisingly strong synergistic effect of lactate and cysteine, indicating that increased lactate uptake led to reduced ROS formation under these conditions whilst additional cysteine actively reduced ROS via the glutathione pathway. The presented results finally demonstrate the benefit of modeling approaches for process intensification as well as the potential of HSD cultivations for biopharmaceutical manufacturing. John Wiley and Sons Inc. 2021-03-01 2021-05 /pmc/articles/PMC8248150/ /pubmed/33491766 http://dx.doi.org/10.1002/bit.27693 Text en © 2021 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals LLC https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle ARTICLES
Brunner, Matthias
Kolb, Klara
Keitel, Alena
Stiefel, Fabian
Wucherpfennig, Thomas
Bechmann, Jan
Unsoeld, Andreas
Schaub, Jochen
Application of metabolic modeling for targeted optimization of high seeding density processes
title Application of metabolic modeling for targeted optimization of high seeding density processes
title_full Application of metabolic modeling for targeted optimization of high seeding density processes
title_fullStr Application of metabolic modeling for targeted optimization of high seeding density processes
title_full_unstemmed Application of metabolic modeling for targeted optimization of high seeding density processes
title_short Application of metabolic modeling for targeted optimization of high seeding density processes
title_sort application of metabolic modeling for targeted optimization of high seeding density processes
topic ARTICLES
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248150/
https://www.ncbi.nlm.nih.gov/pubmed/33491766
http://dx.doi.org/10.1002/bit.27693
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