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Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

A core business in industrial biotechnology using microbial production cell factories is the iterative process of strain engineering and optimization of bioprocess conditions. One important aspect is the improvement of cultivation medium to provide an optimal environment for microbial formation of t...

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Autores principales: Hemmerich, Johannes, Freier, Lars, Wiechert, Wolfgang, von Lieres, Eric, Oldiges, Marco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MyJove Corporation 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755569/
https://www.ncbi.nlm.nih.gov/pubmed/29286407
http://dx.doi.org/10.3791/56234
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author Hemmerich, Johannes
Freier, Lars
Wiechert, Wolfgang
von Lieres, Eric
Oldiges, Marco
author_facet Hemmerich, Johannes
Freier, Lars
Wiechert, Wolfgang
von Lieres, Eric
Oldiges, Marco
author_sort Hemmerich, Johannes
collection PubMed
description A core business in industrial biotechnology using microbial production cell factories is the iterative process of strain engineering and optimization of bioprocess conditions. One important aspect is the improvement of cultivation medium to provide an optimal environment for microbial formation of the product of interest. It is well accepted that the media composition can dramatically influence overall bioprocess performance. Nutrition medium optimization is known to improve recombinant protein production with microbial systems and thus, this is a rewarding step in bioprocess development. However, very often standard media recipes are taken from literature, since tailor-made design of the cultivation medium is a tedious task that demands microbioreactor technology for sufficient cultivation throughput, fast product analytics, as well as support by lab robotics to enable reliability in liquid handling steps. Furthermore, advanced mathematical methods are required for rationally analyzing measurement data and efficiently designing parallel experiments such as to achieve optimal information content. The generic nature of the presented protocol allows for easy adaption to different lab equipment, other expression hosts, and target proteins of interest, as well as further bioprocess parameters. Moreover, other optimization objectives like protein production rate, specific yield, or product quality can be chosen to fit the scope of other optimization studies. The applied Kriging Toolbox (KriKit) is a general tool for Design of Experiments (DOE) that contributes to improved holistic bioprocess optimization. It also supports multi-objective optimization which can be important in optimizing both upstream and downstream processes.
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spelling pubmed-57555692018-01-19 Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology Hemmerich, Johannes Freier, Lars Wiechert, Wolfgang von Lieres, Eric Oldiges, Marco J Vis Exp Bioengineering A core business in industrial biotechnology using microbial production cell factories is the iterative process of strain engineering and optimization of bioprocess conditions. One important aspect is the improvement of cultivation medium to provide an optimal environment for microbial formation of the product of interest. It is well accepted that the media composition can dramatically influence overall bioprocess performance. Nutrition medium optimization is known to improve recombinant protein production with microbial systems and thus, this is a rewarding step in bioprocess development. However, very often standard media recipes are taken from literature, since tailor-made design of the cultivation medium is a tedious task that demands microbioreactor technology for sufficient cultivation throughput, fast product analytics, as well as support by lab robotics to enable reliability in liquid handling steps. Furthermore, advanced mathematical methods are required for rationally analyzing measurement data and efficiently designing parallel experiments such as to achieve optimal information content. The generic nature of the presented protocol allows for easy adaption to different lab equipment, other expression hosts, and target proteins of interest, as well as further bioprocess parameters. Moreover, other optimization objectives like protein production rate, specific yield, or product quality can be chosen to fit the scope of other optimization studies. The applied Kriging Toolbox (KriKit) is a general tool for Design of Experiments (DOE) that contributes to improved holistic bioprocess optimization. It also supports multi-objective optimization which can be important in optimizing both upstream and downstream processes. MyJove Corporation 2017-12-15 /pmc/articles/PMC5755569/ /pubmed/29286407 http://dx.doi.org/10.3791/56234 Text en Copyright © 2017, Journal of Visualized Experiments http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Bioengineering
Hemmerich, Johannes
Freier, Lars
Wiechert, Wolfgang
von Lieres, Eric
Oldiges, Marco
Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
title Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
title_full Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
title_fullStr Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
title_full_unstemmed Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
title_short Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology
title_sort generic protocol for optimization of heterologous protein production using automated microbioreactor technology
topic Bioengineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755569/
https://www.ncbi.nlm.nih.gov/pubmed/29286407
http://dx.doi.org/10.3791/56234
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