Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Automated Conditional Screening of Escherichia Coli Knockout Mutants in Parallel Adaptive Fed-Batch Cultivations

Sebastian Hans
* ORCID logo ,
Benjamin Haby
ORCID logo ,
Niels Krausch
ORCID logo ,
Barz Tilman
ORCID logo ,
Peter Neubauer
ORCID logo ,
Mariano Nicolas Cruz-Bournazou
Version 1 : Received: 15 September 2020 / Approved: 17 September 2020 / Online: 17 September 2020 (07:34:19 CEST)

A peer-reviewed article of this Preprint also exists.

Hans, S.; Haby, B.; Krausch, N.; Barz, T.; Neubauer, P.; Cruz-Bournazou, M.N. Automated Conditional Screening of Multiple Escherichia coli Strains in Parallel Adaptive Fed-Batch Cultivations. Bioengineering 2020, 7, 145. Hans, S.; Haby, B.; Krausch, N.; Barz, T.; Neubauer, P.; Cruz-Bournazou, M.N. Automated Conditional Screening of Multiple Escherichia coli Strains in Parallel Adaptive Fed-Batch Cultivations. Bioengineering 2020, 7, 145.

Abstract

In bioprocess development, the host and the genetic construct for a new biomanufacturing process are selected in the early developmental stages. This decision, made at the screening scale with very limited information about the performance of the selected cell factory in larger reactors, has a major influence on the performance of the final process. To overcome this, scaledown approaches are essential to run screenings that show the real cell factory performance at industrial like conditions. We present a fully automated robotic facility with 24 parallel mini-bioreactors that is operated by a model based adaptive input design framework for the characterization of clone libraries under scale-down conditions. The cultivation operation strategies are computed and continuously refined based on a macro-kinetic growth model that is continuously re-fitted to the available experimental data. The added value of the approach is demonstrated with 24 parallel fed-batch cultivations in a mini-bioreactor system with eight different Escherichia coli strains in triplicate. The 24 fed-batches ran under the desired conditions generating sufficient information to define the fastest growing strain in an environment with varying glucose concentrations similar to industrial scale bioreactors.

Keywords

high throughput screening; rapid phenotyping; model-based experimental design; Escherichia coli; automated bioprocess development

Subject

Biology and Life Sciences, Biology and Biotechnology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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