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
Monitoring and quantification of inclusion body formation in Escherichia coli by multi-parameter flow cytometry
KTH, School of Biotechnology (BIO).
KTH, School of Biotechnology (BIO).
Department of Biology and Chemical Engineering, Mälardalen University.
Centre for Formulation Engineering, School of Engineering (Chemical Engineering), University of Birmingham.
Show others and affiliations
2005 (English)In: Biotechnology letters, ISSN 0141-5492, E-ISSN 1573-6776, Vol. 27, no 13, 919-926 p.Article in journal (Refereed) Published
Abstract [en]

Multi-parameter flow cytometry was used to monitor the formation of promegapoietin (PMP) inclusion bodies during a high cell density Escherichia coli fed-batch fermentation process. Inclusion bodies were labelled with a primary antibody and then with a secondary fluorescent antibody. Using this method it was possible to detect PMP inclusion body formation with a high specificity and it was possible to monitor the increased accumulation of the protein with process time (6-48 mg PMP/g CDW) whilst highlighting population heterogeneity.

Place, publisher, year, edition, pages
2005. Vol. 27, no 13, 919-926 p.
Keyword [en]
Alexa fluor 488; Escherichia coli; Fed-batch fermentation; Flow cytometry; Inclusion bodies; Escherichia coli; Fermentation; Fluorescence; Cell density; Cytometry; Fluorescent antibodies; Inclusion bodies; Proteins; fluorescent dye; hybrid protein; interleukin 3; interleukin 3 receptor; promegapoietin 1a; promegapoietin-1a; recombinant protein; thrombopoietin; article; bioreactor; cell inclusion; chemistry; Escherichia coli; fermentation; flow cytometry; fluorescence microscopy; genetics; growth, development and aging; high performance liquid chromatography; human; metabolism; methodology; microbiology; Bioreactors; Chromatography, High Pressure Liquid; Escherichia coli; Fermentation; Flow Cytometry; Fluorescent Dyes; Humans; Inclusion Bodies; Interleukin-3; Microscopy, Fluorescence; Receptors, Interleukin-3; Recombinant Fusion Proteins; Recombinant Proteins; Thrombopoietin
National Category
Other Industrial Biotechnology
Identifiers
URN: urn:nbn:se:kth:diva-7621DOI: 10.1007/s10529-005-7184-6ISI: 000231164000007PubMedID: 16091887Scopus ID: 2-s2.0-23844548756OAI: oai:DiVA.org:kth-7621DiVA: diva2:12705
Note
QC 20100819Available from: 2007-11-12 Created: 2007-11-12 Last updated: 2010-08-19Bibliographically 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 textPubMedScopusSpringerLink

Search in DiVA

By author/editor
Wållberg, FredrikSundström, HeléneEnfors, Sven-Olof
By organisation
School of Biotechnology (BIO)
In the same journal
Biotechnology letters
Other Industrial Biotechnology

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 116 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