Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Segregation to non-dividing cells in recombinant Escherichia coli fed-batch fermentation processes
KTH, Superseded Departments, Biotechnology.
KTH, Superseded Departments, Biotechnology.
Department of Biology and Chemical Engineering, Mälardalen University.
Department of Biology and Chemical Engineering, Mälardalen University.
Show others and affiliations
2004 (English)In: Biotechnology letters, ISSN 0141-5492, E-ISSN 1573-6776, Vol. 26, no 19, 1533-1539 p.Article in journal (Refereed) Published
Abstract [en]

In Escherichia coli fermentation processes, a drastic drop in viable cell count as measured by the number of colony forming units per ml (c.f.u. ml(-1)) is often observed. This phenomenon was investigated in a process for the production of the recombinant fusion protein, promegapoietin (PMP). After induction, the number of c.f.u. ml(-1) dropped to similar to10% of its maximum though the biomass concentration continued to increase. Flow cytometric analysis of viability and intracellular concentration of PMP showed that almost all cells were alive and contributed to the production. Thus, the drop in the number of c.f.u. ml(-1) probably reflects a loss of cell division capability rather than cell death.

Place, publisher, year, edition, pages
2004. Vol. 26, no 19, 1533-1539 p.
Keyword [en]
Bacterial cell division; Escherichia coli; Fed-batch fermentation; Flow cytometry; Viability; Biochemistry; Biomass; Cells; Cytology; Escherichia coli; Fermentation; Proteins; Cell culture; Bacteria (microorganisms); Escherichia coli; hybrid protein; interleukin 3; interleukin 3 receptor; promegapoietin 1a; promegapoietin-1a; thrombopoietin; apoptosis; article; bacterial count; bioreactor; biosynthesis; cell aggregation; cell survival; comparative study; cytology; Escherichia coli; evaluation; fermentation; flow cytometry; genetics; methodology; microbiology; mitosis; physiology; protein engineering; Apoptosis; Bioreactors; Cell Aggregation; Cell Survival; Colony Count, Microbial; Escherichia coli; Fermentation; Flow Cytometry; Interleukin-3; Mitosis; Protein Engineering; Receptors, Interleukin-3; Recombinant Fusion Proteins; Thrombopoietin
National Category
Other Industrial Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-7620DOI: 10.1023/B:BILE.0000044458.29147.75ISI: 000225490200014Scopus ID: 2-s2.0-21644447627OAI: oai:DiVA.org:kth-7620DiVA: diva2:12704
Note
QC 20100819 QC 20110922Available from: 2007-11-12 Created: 2007-11-12 Last updated: 2017-12-14Bibliographically approved
In thesis
1. Analytical tools for monitoring and control of fermentation processes
Open this publication in new window or tab >>Analytical tools for monitoring and control of fermentation processes
2007 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

The overall objective of this work has been to adopt new developments and techniques in the area of measurement, modelling and control of fermentation processes. Flow cytometry and software sensors are techniques which were considered ready for application and the focus was set on developing tools for research aiming at understanding the relationship between measured variables and process quality parameters. In this study fed-batch cultivations have been performed with two different strains of Escherichia coli (E.coli) K12 W3110 with and without a gene for the recombinant protein promegapoietin.

Inclusion body formation was followed during the process with flow cytometric detection by labelling the inclusion bodies with first an antibody against the protein promegapoietin and then a second fluorescent anti-antibody. The approach to label inclusion bodies directly in disintegrated and diluted cell slurry could be adopted as a method to follow protein production during the process, although the labelling procedure with incubation times and washings was somewhat time-consuming (1.5 h). The labelling of inclusion bodies inside the cells to follow protein production was feasible to perform, although an unexplained decrease in the relative fluorescence intensity occurred late in process. However, it is difficult to translate this qualitative measurement into a quantitative one, since a quantitative protein analysis should give data proportional to the volume, while the labelling of the spheric inclusion bodies gives a signal corresponding to the area of the body, and calibration is not possible. The methods were shown to be useful for monitoring inclusion body formation, but it seems difficult to get quantitative information from the analysis.

Population heterogeneity analysis was performed, by using flow cytometry, on a cell population, which lost 80-90% viability according to viable count analysis. It was possible to show that the apparent cell death was due to cells incapable of dividing on agar plates after induction. These cells continued to produce the induced recombinant protein. It was shown that almost all cells in the population (≈97%) contained PMP, and furthermore total protein analysis of the medium indicated that only about 1% of the population had lysed. This confirms that the "non-viable" cells according to viable count by cfu analysis produced product.

The software sensors XNH3 and µNH3, which utilises base titration data to estimate biomass and specific growth rate was shown to correlate well with the off-line analyses during cultivation of E. coli W3110 using minimal medium. In rich medium the µNH3 sensor was shown to give a signal that may be used as a fingerprint of the process, at least from the time of induction. The software sensor KLaC* was shown to respond to foaming in culture that probably was caused by increased air bubble dispersion. The RO/S coefficient, which describes the oxygen to substrate consumption, was shown to give a distinct response to stress caused by lowered pH and addition of the inducing agent IPTG.

The software sensor for biomass was applied to a highly automated 6-unit multi-bioreactor system intended for fast process development. In this way also specific rates of substrate and oxygen consumption became available without manual sampling.

Place, publisher, year, edition, pages
Stockholm: KTH, 2007. 62 p.
Keyword
Escherichia coli, flow cytometry, software sensors, viability, inclusion bodies, biomass, specific growth rate, stress, population heterogeneity, process analytical technology.
National Category
Other Industrial Biotechnology
Identifiers
urn:nbn:se:kth:diva-4531 (URN)978-91-7178-794-1 (ISBN)
Public defence
2007-11-30, FA32, AlbaNova Universitetscentrum, Roslagstullsbacken 21, Stockholm, 10:00
Opponent
Supervisors
Note
QC 20100819Available from: 2007-11-12 Created: 2007-11-12 Last updated: 2010-08-19Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopusSpringerLink

Search in DiVA

By author/editor
Sundström, HeléneWållberg, FredrikEnfors, Sven-Olof
By organisation
Biotechnology
In the same journal
Biotechnology letters
Other Industrial Biotechnology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 84 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf