TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. TUHH
  3. Publications
  4. Process-induced cell cycle oscillations in CHO cultures: Online monitoring and model-based investigation
 
Options

Process-induced cell cycle oscillations in CHO cultures: Online monitoring and model-based investigation

Citation Link: https://doi.org/10.15480/882.2439
Publikationstyp
Journal Article
Date Issued
2019
Sprache
English
Author(s)
Möller, Johannes  
Bhat, Krathika  
Riecken, Kristoffer  
Pörtner, Ralf 
Zeng, An-Ping  orcid-logo
Jandt, Uwe  
Institut
Bioprozess- und Biosystemtechnik V-1  
TORE-DOI
10.15480/882.2439
TORE-URI
http://hdl.handle.net/11420/3576
Journal
Biotechnology and bioengineering  
Volume
116
Issue
11
Start Page
2931
End Page
2943
Citation
Biotechnology and Bioengineering 116(11):2931-1943 (2019-01-01)
Publisher DOI
10.1002/bit.27124
Scopus ID
2-s2.0-85070519647
Publisher
Wiley
© 2019 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals, Inc. The influence of process strategies on the dynamics of cell population heterogeneities in mammalian cell culture is still not well understood. We recently found that the progression of cells through the cell cycle causes metabolic regulations with variable productivities in antibody-producing Chimese hamster ovary (CHO) cells. On the other hand, it is so far unknown how bulk cultivation conditions, for example, variable nutrient concentrations depending on process strategies, can influence cell cycle-derived population dynamics. In this study, process-induced cell cycle synchronization was assessed in repeated-batch and fed-batch cultures. An automated flow cytometry set-up was developed to measure the cell cycle distribution online, using antibody-producing CHO DP-12 cells transduced with the cell cycle-specific fluorescent ubiquitination-based cell cycle indicator (FUCCI) system. On the basis of the population-resolved model, feeding-induced partial self-synchronization was predicted and the results were evaluated experimentally. In the repeated-batch culture, stable cell cycle oscillations were confirmed with an oscillating G1 phase distribution between 41% and 72%. Furthermore, oscillations of the cell cycle distribution were simulated and determined in a (bolus) fed-batch process with up to 25 × 106 cells/ml. The cell cycle synchronization arose with pulse feeding only and ceased with continuous feeding. Both simulated and observed oscillations occurred at higher frequencies than those observable based on regular (e.g., daily) sample analysis, thus demonstrating the need for high-frequency online cell cycle analysis. In summary, we showed how experimental methods combined with simulations enable the improved assessment of the effects of process strategies on the dynamics of cell cycle-dependent population heterogeneities. This provides a novel approach to understand cell cycle regulations, control cell population dynamics, avoid inadvertently induced oscillations of cell cycle distributions and thus to improve process stability and efficiency.
Subjects
automated flow cytometry
fed-batch
feeding strategy
FUCCI
repeated-batch
DDC Class
620: Ingenieurwissenschaften
Funding(s)
Projekt DEAL  
Lizenz
https://creativecommons.org/licenses/by/4.0/
Loading...
Thumbnail Image
Name

M-ller_et_al-2019-Biotechnology_and_Bioengineering.pdf

Size

1.76 MB

Format

Adobe PDF

TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback