Accelerated Bioprocess Development of Endopolygalacturonase-Production with Saccharomyces cerevisiae Using Multivariate Prediction in a 48 Mini-Bioreactor Automated Platform

Abstract

Mini-bioreactor systems enabling automatized operation of numerous parallel cultivations are a promising alternative to accelerate and optimize bioprocess development allowing for sophisticated cultivation experiments in high throughput. These include fed-batch and continuous cultivations with multiple options of process control and sample analysis which deliver valuable screening tools for industrial production. However, the model-based methods needed to operate these robotic facilities efficiently considering the complexity of biological processes are missing. We present an automated experiment facility that integrates online data handling, visualization and treatment using multivariate analysis approaches to design and operate dynamical experimental campaigns in up to 48 mini-bioreactors (8–12 mL) in parallel. In this study, the characterization of Saccharomyces cerevisiae AH22 secreting recombinant endopolygalacturonase is performed, running and comparing 16 experimental conditions in triplicate. Data-driven multivariate methods were developed to allow for fast, automated decision making as well as online predictive data analysis regarding endopolygalacturonase production. Using dynamic process information, a cultivation with abnormal behavior could be detected by principal component analysis as well as two clusters of similarly behaving cultivations, later classified according to the feeding rate. By decision tree analysis, cultivation conditions leading to an optimal recombinant product formation could be identified automatically. The developed method is easily adaptable to different strains and cultivation strategies, and suitable for automatized process development reducing the experimental times and costs.

A model‐based framework for parallel scale‐down fed‐batch cultivations in mini‐bioreactors for accelerated phenotyping

“…By this mechanism, the whole bioreactor block was aerated to 10 L air ·min −1 during cultivation. The detailed configuration of hardware‐software protocols, sampling algorithms, pH control routines, pulse feed scheduling and off‐line, at‐line and online analytics on the robot station during parallel cultivations were presented previously (Cruz Bournazou et al, ; Nickel, Cruz‐Bournazou, Wilms, Neubauer, & Knepper, ; Sawatzki et al, ).…”

“…An initial challenge of these systems was the difficulty in implementation of controlled feeding strategies, as in laboratory bioreactors. However, various solutions have been developed recently to enable fed-batch-like conditions, such as the gradual supply of glucose to the culture through enzyme-based glucose release systems (Krause, Neubauer, & Neubauer, 2016), the application of micropumps for continuous feed supply (Gebhardt, Hortsch, Kaufmann, Arnold, & Weuster-Botz, 2011), model-based intermittent feeding (Sawatzki et al, 2018), and membrane-based substrate release systems (Philip et al, 2018). These improvements bring the screening system closer to actual cultivation conditions, such that a better performing strain can be selected for scale-up.…”

Monitoring Parallel Robotic Cultivations with Online Multivariate Analysis

“…Fully automated solutions that include process and feeding control, online and at-line monitoring are very challenging in parallel MBR cultivations [20,21]. The main difficulties are the analysis of multi-dimensional and highly correlated data sets, monitoring and operating a large number of bioreactors and the intrinsic need to solve an optimal experimental design problem considering all MBRs simultaneously [24,27] in a period of time. Additional challenges arise when industrial conditions are investigated at the milliliter scale [22,25].…”

“…Our previous work showed that PCA can be used in parallel MBR experiments to identify and improve feeding strategies with a low number of experiments [27]. In this work we developed a program that enables the monitoring of parallel dynamic cultivations in real-time, supported with visual representations as well as automated event triggers ( Figure 1).…”

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

“…Mini-BioReactors (MBR) integrated in Liquid Handling Stations (LHS) allow a large number of parallel cultivations while maintaining the properties of benchtop bioreactors. With working volumes of 2 -250 mL [17], geometric similarities to large-scale reactors [18], and high frequency measurements and analytics, MBRs have been used for process characterizations [15,[19][20][21] and scale-down studies [11,22] for up to 48 cultivations in parallel [23]. Such robotic facilities with automated cultivation control, sampling and at -line analytic operations [16,24] are very powerful systems that can accelerate bioprocess development, especially in combination with digital solutions for experiment planning [25][26][27][28], data acquisition [4,16]and realtime dynamic analysis [29,30].…”