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Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools

BACKGROUND: Single cell analysis for bioprocess monitoring is an important tool to gain deeper insights into particular cell behavior and population dynamics of production processes and can be very useful for discrimination of the real bottleneck between product biosynthesis and secretion, respectiv...

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Detalles Bibliográficos
Autores principales: David, Florian, Berger, Antje, Hänsch, Robert, Rohde, Manfred, Franco-Lara, Ezequiel
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3101136/
https://www.ncbi.nlm.nih.gov/pubmed/21496219
http://dx.doi.org/10.1186/1475-2859-10-23
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author David, Florian
Berger, Antje
Hänsch, Robert
Rohde, Manfred
Franco-Lara, Ezequiel
author_facet David, Florian
Berger, Antje
Hänsch, Robert
Rohde, Manfred
Franco-Lara, Ezequiel
author_sort David, Florian
collection PubMed
description BACKGROUND: Single cell analysis for bioprocess monitoring is an important tool to gain deeper insights into particular cell behavior and population dynamics of production processes and can be very useful for discrimination of the real bottleneck between product biosynthesis and secretion, respectively. RESULTS: Here different dyes for viability estimation considering membrane potential (DiOC(2)(3), DiBAC(4)(3), DiOC(6)(3)) and cell integrity (DiBAC(4)(3)/PI, Syto9/PI) were successfully evaluated for Bacillus megaterium cell characterization. It was possible to establish an appropriate assay to measure the production intensities of single cells revealing certain product secretion dynamics. Methods were tested regarding their sensitivity by evaluating fluorescence surface density and fluorescent specific concentration in relation to the electronic cell volume. The assays established were applied at different stages of a bioprocess where the antibody fragment D1.3 scFv production and secretion by B. megaterium was studied. CONCLUSIONS: It was possible to distinguish between live, metabolic active, depolarized, dormant, and dead cells and to discriminate between high and low productive cells. The methods were shown to be suitable tools for process monitoring at single cell level allowing a better process understanding, increasing robustness and forming a firm basis for physiology-based analysis and optimization with the general application for bioprocess development.
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spelling pubmed-31011362011-05-25 Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools David, Florian Berger, Antje Hänsch, Robert Rohde, Manfred Franco-Lara, Ezequiel Microb Cell Fact Research BACKGROUND: Single cell analysis for bioprocess monitoring is an important tool to gain deeper insights into particular cell behavior and population dynamics of production processes and can be very useful for discrimination of the real bottleneck between product biosynthesis and secretion, respectively. RESULTS: Here different dyes for viability estimation considering membrane potential (DiOC(2)(3), DiBAC(4)(3), DiOC(6)(3)) and cell integrity (DiBAC(4)(3)/PI, Syto9/PI) were successfully evaluated for Bacillus megaterium cell characterization. It was possible to establish an appropriate assay to measure the production intensities of single cells revealing certain product secretion dynamics. Methods were tested regarding their sensitivity by evaluating fluorescence surface density and fluorescent specific concentration in relation to the electronic cell volume. The assays established were applied at different stages of a bioprocess where the antibody fragment D1.3 scFv production and secretion by B. megaterium was studied. CONCLUSIONS: It was possible to distinguish between live, metabolic active, depolarized, dormant, and dead cells and to discriminate between high and low productive cells. The methods were shown to be suitable tools for process monitoring at single cell level allowing a better process understanding, increasing robustness and forming a firm basis for physiology-based analysis and optimization with the general application for bioprocess development. BioMed Central 2011-04-15 /pmc/articles/PMC3101136/ /pubmed/21496219 http://dx.doi.org/10.1186/1475-2859-10-23 Text en Copyright ©2011 David et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
David, Florian
Berger, Antje
Hänsch, Robert
Rohde, Manfred
Franco-Lara, Ezequiel
Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools
title Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools
title_full Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools
title_fullStr Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools
title_full_unstemmed Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools
title_short Single cell analysis applied to antibody fragment production with Bacillus megaterium: development of advanced physiology and bioprocess state estimation tools
title_sort single cell analysis applied to antibody fragment production with bacillus megaterium: development of advanced physiology and bioprocess state estimation tools
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3101136/
https://www.ncbi.nlm.nih.gov/pubmed/21496219
http://dx.doi.org/10.1186/1475-2859-10-23
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