Literature DB >> 32978650

Euler-Lagrangian Simulations: A Proper Tool for Predicting Cellular Performance in Industrial Scale Bioreactors.

Christopher Sarkizi Shams Hajian1, Julia Zieringer1, Ralf Takors2.   

Abstract

Eulerian-Lagrangian approach to investigate cellular responses in a bioreactor has become the center of attention in recent years. It was introduced to biotechnological processes about two decades ago, but within the last few years, it proved itself as a powerful tool to address scale-up and -down topics of bioprocesses. It can capture the history of a cell and reveal invaluable information for, not only, bioprocess control and design but also strain engineering. This way it will be possible to shed light on the actual environment that cell experiences throughout its lifespan. Lifelines of a microorganism in a bioreactor can serve as the missing link that encompasses the biological timescales and the physical timescales. For this purpose digitalization of bioreactors provides us with new insights that are not achievable in industrial reactors easily if at all, namely, substrate and product gradients; high-shear regions are among the most interesting factors that can be reproduced adequately with help of a digital twin. In this chapter basic principles of this method will be introduced, and later on some practical aspects of particle tracking technique will be illustrated. In the final section, some of the advantages and challenges associated with this method will be discussed.

Entities:  

Keywords:  Cell life-lines; Digital twins; Large-scale bioprocesses; Scale-down; Scale-up

Mesh:

Year:  2021        PMID: 32978650     DOI: 10.1007/10_2020_133

Source DB:  PubMed          Journal:  Adv Biochem Eng Biotechnol        ISSN: 0724-6145            Impact factor:   2.635


  27 in total

Review 1.  Living with heterogeneities in bioreactors: understanding the effects of environmental gradients on cells.

Authors:  Alvaro R Lara; Enrique Galindo; Octavio T Ramírez; Laura A Palomares
Journal:  Mol Biotechnol       Date:  2006-11       Impact factor: 2.695

2.  Influence of substrate oscillations on acetate formation and growth yield in Escherichia coli glucose limited fed-batch cultivations.

Authors:  P Neubauer; L Häggström; S O Enfors
Journal:  Biotechnol Bioeng       Date:  1995-07-20       Impact factor: 4.530

3.  Dissolved oxygen concentration profiles in a production-scale bioreactor.

Authors:  N M Oosterhuis; N W Kossen
Journal:  Biotechnol Bioeng       Date:  1984-05       Impact factor: 4.530

4.  Alkaline conditions in hydrophilic interaction liquid chromatography for intracellular metabolite quantification using tandem mass spectrometry.

Authors:  Attila Teleki; Andrés Sánchez-Kopper; Ralf Takors
Journal:  Anal Biochem       Date:  2015-01-16       Impact factor: 3.365

Review 5.  Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses.

Authors:  Guan Wang; Cees Haringa; Wenjun Tang; Henk Noorman; Ju Chu; Yingping Zhuang; Siliang Zhang
Journal:  Biotechnol Bioeng       Date:  2019-12-20       Impact factor: 4.530

6.  CO₂ /HCO₃⁻ perturbations of simulated large scale gradients in a scale-down device cause fast transcriptional responses in Corynebacterium glutamicum.

Authors:  Jens Buchholz; Michaela Graf; Andreas Freund; Tobias Busche; Jörn Kalinowski; Bastian Blombach; Ralf Takors
Journal:  Appl Microbiol Biotechnol       Date:  2014-08-21       Impact factor: 4.813

7.  Engineering E. coli for large-scale production - Strategies considering ATP expenses and transcriptional responses.

Authors:  Michael Löffler; Joana Danica Simen; Günter Jäger; Karin Schäferhoff; Andreas Freund; Ralf Takors
Journal:  Metab Eng       Date:  2016-07-01       Impact factor: 9.783

8.  Euler-Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines.

Authors:  Cees Haringa; Wenjun Tang; Amit T Deshmukh; Jianye Xia; Matthias Reuss; Joseph J Heijnen; Robert F Mudde; Henk J Noorman
Journal:  Eng Life Sci       Date:  2016-09-14       Impact factor: 2.678

9.  Transcriptional response of Escherichia coli to ammonia and glucose fluctuations.

Authors:  Joana Danica Simen; Michael Löffler; Günter Jäger; Karin Schäferhoff; Andreas Freund; Jakob Matthes; Jan Müller; Ralf Takors
Journal:  Microb Biotechnol       Date:  2017-04-26       Impact factor: 5.813

Review 10.  In Silico Prediction of Large-Scale Microbial Production Performance: Constraints for Getting Proper Data-Driven Models.

Authors:  Julia Zieringer; Ralf Takors
Journal:  Comput Struct Biotechnol J       Date:  2018-07-06       Impact factor: 7.271

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