Home > Publications database > Microfluidic Reproduction of Dynamic Bioreactor Environment Based on Computational Lifelines > print

001     907221
005     20240506205522.0
024 7 _ |a 10.3389/fceng.2022.826485
|2 doi
024 7 _ |a 2128/31032
|2 Handle
024 7 _ |a altmetric:125696886
|2 altmetric
024 7 _ |a WOS:000994427700001
|2 WOS
037 _ _ |a FZJ-2022-01902
082 _ _ |a 540
100 1 _ |a Ho, Phuong
|0 P:(DE-Juel1)174016
|b 0
|u fzj
245 _ _ |a Microfluidic Reproduction of Dynamic Bioreactor Environment Based on Computational Lifelines
260 _ _ |a Lausanne
|c 2022
|b Frontiers Media
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1714996466_28930
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a The biotechnological production of fine chemicals, proteins and pharmaceuticals is usually hampered by loss of microbial performance during scale-up. This challenge is mainly caused by discrepancies between homogeneous environmental conditions at laboratory scale, where bioprocesses are optimized, and inhomogeneous conditions in large-scale bioreactors, where production takes place. Therefore, to improve strain selection and process development, it is of great interest to characterize these fluctuating conditions at large-scale and to study their effects on microbial cells. In this paper, we demonstrate the potential of computational fluid dynamics (CFD) simulation of large-scale bioreactors combined with dynamic microfluidic single-cell cultivation (dMSCC). Environmental conditions in a 200 L bioreactor were characterized with CFD simulations. Computational lifelines were determined by combining simulated turbulent multiphase flow, mass transport and particle tracing. Glucose availability for Corynebacterium glutamicum cells was determined. The reactor was simulated with average glucose concentrations of 6 g m−3, 10 g m−3 and 16 g m−3. The resulting computational lifelines, discretized into starvation and abundance regimes, were used as feed profiles for the dMSCC to investigate how varying glucose concentration affects cell physiology and growth rate. In this study, each colony in the dMSCC device represents a single cell as it travels through the reactor. Under oscillating conditions reproduced in the dMSCC device, a decrease in growth rate of about 40% was observed compared to continuous supply with the same average glucose availability. The presented approach provides insights into environmental conditions observed by microorganisms in large-scale bioreactors. It also paves the way for an improved understanding of how inhomogeneous environmental conditions influence cellular physiology, growth and production.
536 _ _ |a 2171 - Biological and environmental resources for sustainable use (POF4-217)
|0 G:(DE-HGF)POF4-2171
|c POF4-217
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Täuber, Sarah
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Stute, Birgit
|0 P:(DE-Juel1)128523
|b 2
|u fzj
700 1 _ |a Grünberger, Alexander
|0 P:(DE-Juel1)143612
|b 3
|e Corresponding author
700 1 _ |a von Lieres, Eric
|0 P:(DE-Juel1)129081
|b 4
|e Corresponding author
|u fzj
773 _ _ |a 10.3389/fceng.2022.826485
|g Vol. 4, p. 826485
|0 PERI:(DE-600)3017796-0
|p 826485
|t Frontiers in chemical engineering
|v 4
|y 2022
|x 2673-2718
856 4 _ |u https://juser.fz-juelich.de/record/907221/files/fceng-04-826485.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:907221
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)174016
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)128523
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)129081
913 1 _ |a DE-HGF
|b Forschungsbereich Erde und Umwelt
|l Erde im Wandel – Unsere Zukunft nachhaltig gestalten
|1 G:(DE-HGF)POF4-210
|0 G:(DE-HGF)POF4-217
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-200
|4 G:(DE-HGF)POF
|v Für eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten
|9 G:(DE-HGF)POF4-2171
|x 0
914 1 _ |y 2022
915 p c |a Local Funding
|0 PC:(DE-HGF)0001
|2 APC
915 p c |a DFG OA Publikationskosten
|0 PC:(DE-HGF)0002
|2 APC
915 p c |a DOAJ Journal
|0 PC:(DE-HGF)0003
|2 APC
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-12
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Blind peer review
|d 2021-05-13T10:37:49Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-08-29
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-08-29
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2021-05-13T10:37:49Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2021-05-13T10:37:49Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Anonymous peer review
|d 2021-05-13T10:37:49Z
915 _ _ |a Creative Commons Attribution CC BY (No Version)
|0 LIC:(DE-HGF)CCBYNV
|2 V:(DE-HGF)
|b DOAJ
|d 2021-05-13T10:37:49Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-08-29
915 _ _ |a WoS
|0 StatID:(DE-HGF)0112
|2 StatID
|b Emerging Sources Citation Index
|d 2023-08-29
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-08-29
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-08-29
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-08-29
920 1 _ |0 I:(DE-Juel1)IBG-1-20101118
|k IBG-1
|l Biotechnologie
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)IBG-1-20101118
980 _ _ |a APC
980 _ _ |a UNRESTRICTED
980 1 _ |a APC
980 1 _ |a FullTexts

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21