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Bioreactor Engineering Research and Industrial Applications II

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Attention for Chapter 326: Perturbation Experiments: Approaches for Metabolic Pathway Analysis in Bioreactors
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Chapter title
Perturbation Experiments: Approaches for Metabolic Pathway Analysis in Bioreactors
Chapter number 326
Book title
Bioreactor Engineering Research and Industrial Applications II
Published in
Advances in biochemical engineering biotechnology, January 2015
DOI 10.1007/10_2015_326
Pubmed ID
Book ISBNs
978-3-66-248346-6, 978-3-66-248347-3
Authors

Michael Weiner, Julia Tröndle, Christoph Albermann, Georg A. Sprenger, Dirk Weuster-Botz, Weiner, Michael, Tröndle, Julia, Albermann, Christoph, Sprenger, Georg A., Weuster-Botz, Dirk

Abstract

: In the last decades, targeted metabolic engineering of microbial cells has become one of the major tools in bioprocess design and optimization. For successful application, a detailed knowledge is necessary about the relevant metabolic pathways and their regulation inside the cells. Since in vitro experiments cannot display process conditions and behavior properly, process data about the cells' metabolic state have to be collected in vivo. For this purpose, special techniques and methods are necessary. Therefore, most techniques enabling in vivo characterization of metabolic pathways rely on perturbation experiments, which can be divided into dynamic and steady-state approaches. To avoid any process disturbance, approaches which enable perturbation of cell metabolism in parallel to the continuing production process are reasonable. Furthermore, the fast dynamics of microbial production processes amplifies the need of parallelized data generation. These points motivate the development of a parallelized approach for multiple metabolic perturbation experiments outside the operating production reactor. An appropriate approach for in vivo characterization of metabolic pathways is presented and applied exemplarily to a microbial L-phenylalanine production process on a 15 L-scale.

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Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 4%
Unknown 22 96%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 22%
Other 4 17%
Student > Ph. D. Student 4 17%
Researcher 3 13%
Professor 2 9%
Other 3 13%
Unknown 2 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 30%
Agricultural and Biological Sciences 5 22%
Engineering 3 13%
Environmental Science 3 13%
Chemical Engineering 2 9%
Other 1 4%
Unknown 2 9%