ArticleBioprocess and biosystems engineering2022
Control of parallelized bioreactors II: probabilistic quantification of carboxylic acid reductase activity for bioprocess optimization.
Article in Bioprocess and biosystems engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 11 citations in OpenAlex.
- A Guide to Bayesian Optimization in Bioprocess Engineering.Biotechnology and bioengineering · 2026Review
- Scale-down bioreactors-comparative analysis of configurations.Bioprocess and biosystems engineering · 2025Review
- Automation of RNA-Seq Sample Preparation and Miniaturized Parallel Bioreactors Enable High-Throughput Differential Gene Expression Studies.Microorganisms · 2025Article
- Accelerated Adaptive Laboratory Evolution by Automated Repeated Batch Processes in Parallelized Bioreactors.Microorganisms · 2023Article
- Quantification of nisin concentration from fluorescence-based antimicrobial activity assay using Bayesian calibration.Biotechnology progressArticle
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7 authors at 2 institutions in 1 country.
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Abstract
Autonomously operated parallelized mL-scale bioreactors are considered the key to reduce bioprocess development cost and time. However, their application is often limited to products with very simple analytics. In this study, we investigated enhanced protein expression conditions of a carboxyl reductase from Nocardia otitidiscaviarum in E. coli. Cells were produced with exponential feeding in a L-scale bioreactor. After the desired cell density for protein expression was reached, the cells were automatically transferred to 48 mL-scale bioreactors operated by a liquid handling station where protein expression studies were conducted. During protein expression, the feed rate and the inducer concentration was varied. At the end of the protein expression phase, the enzymatic activity was estimated by performing automated whole-cell biotransformations in a deep-well-plate. The results were analyzed with hierarchical Bayesian modelling methods to account for the biomass growth during the biotransformation, biomass interference on the subsequent product assay, and to predict absolute and specific enzyme activities at optimal expression conditions. Lower feed rates seemed to be beneficial for high specific and absolute activities. At the optimal investigated expression conditions an activity of [Formula: see text] was estimated with a [Formula: see text] credible interval of [Formula: see text]. This is about 40-fold higher than the highest published data for the enzyme under investigation. With the proposed setup, 192 protein expression conditions were studied during four experimental runs with minimal manual workload, showing the reliability and potential of automated and digitalized bioreactor systems.
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