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Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

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An automated microscale platform for evaluation and optimization of oxidative bioconversion processes.

Jasmin Z Baboo¹, James L Galman, Gary J Lye

¹Dept. of Biochemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.

Biotechnology Progress

|January 7, 2012

Summary

This summary is machine-generated.

A fully automated robotic platform enables rapid microscale bioprocess optimization using E. coli TOP10 expressing cyclohexanone monooxygenase (CHMO). This high-throughput method accelerates kinetic data collection for improved bioprocess development and scale-up.

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Area of Science:

Biotechnology
Bioprocess Engineering
Synthetic Biology

Background:

Microscale bioprocessing offers advantages for rapid screening and optimization.
Automated platforms are crucial for high-throughput experimentation in bioprocess development.

Purpose of the Study:

To develop and validate a fully automated microscale process for fermentation and bioconversion.
To accelerate the collection of kinetic data for optimizing bioprocesses.
To investigate substrate specificity and product selectivity of cyclohexanone monooxygenase (CHMO) in E. coli.

Main Methods:

Utilized an integrated robotic platform for automated microscale process sequence development.
Employed 96-Deep Square Well (96-DSW) microtiter plates for microbial culture and enzyme-catalyzed conversion.
Applied a matched oxygen transfer coefficient (k(L)a) approach for scale-up validation.

Main Results:

Successfully automated fermentation and bioconversion using E. coli TOP10 [pQR210] expressing CHMO.
Identified nutritional and oxygen limitations through high-throughput investigation of media formulation and well fill volumes.
Demonstrated substrate specificity and product selectivity for six novel CHMO substrates, including norcamphor and cycloheptanone.

Conclusions:

Automated microscale processing significantly accelerates the collection of kinetic data for bioprocess development.
The developed automated process sequence is robust and reproducible at larger scales (75 L).
This approach has clear implications for accelerating bioprocess optimization and scale-up in biotechnology.