Automated Conditional Screening of Multiple <i>Escherichia coli</i> Strains in Parallel Adaptive Fed-Batch Cultivations

• Main Authors: Sebastian Hans, Benjamin Haby, Niels Krausch, Tilman Barz, Peter Neubauer, Mariano Nicolas Cruz-Bournazou
• Format: Article
• Language: English
• Published: MDPI AG 2020-11-01
• Series: Bioengineering
• Subjects: high-throughput screening; rapid phenotyping; model-based experimental design; <i>Escherichia coli</i>; automated bioprocess development
• Online Access: https://www.mdpi.com/2306-5354/7/4/145

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 in larger reactors, has a major influence on the efficiency of the final process. To overcome this, scale-down approaches during screenings that show the real cell factory performance at industrial-like conditions are essential. 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 <i>Escherichia coli</i> strains in triplicate. The 24 fed-batch cultivations were run under the desired conditions, generating sufficient information to define the fastest-growing strain in an environment with oscillating glucose concentrations similar to industrial-scale bioreactors.