Journal of biological engineering · 2026
Early bioprocess development using Komagataella phaffii: application scenarios for the microTOM mini bioreactor system.
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Wollborn David, Hartley Carol J, Schulte Andreas, Correa Juan C P
Аннотация
Developing novel bioprocesses usually starts with an iterative cycle to engineer genetically modified organisms. This leads to large strain libraries that differ in their genetic makeup, showing different growth and production performance. Finding the optimal production strain requires extensive screening and is arguably one of the most important steps for large-scale productivity. For aerobic processes, it is important to ensure the cultivation conditions avoid oxygen limitation. The oxygen transfer rate (OTR) is a parameter to monitor metabolic activity. The micro-scale Transfer rate Online Measurement (microTOM) system allows online monitoring of the respiration activity in 96-individual wells of a microtiter plate. This novel late-stage beta version prototype, provided by Kuhner Shaker, was trialled with the common microbial host Komagataella phaffii. It is demonstrated how the microTOM system can be applied to rapidly determine essential parameters for bioprocess design. Using a 96-well microtiter plate format enabled high-throughput investigation of three strains in parallel. The methanol uptake and growth rate was estimated, which can be used in process models to guide scale-up and decisions regarding feeding rates in fed-batch operation mode. Further, we assessed seven media formulations with two carbon sources, the impact of filling volume on the maximum oxygen transfer capacity, eight different antifoam agents, and growth rates were estimated at five different temperatures. These findings can help select screening conditions and demonstrate how the microTOM system can accelerate bioprocess development. Until now, obtaining high-resolution OTR datasets at high-throughput, suitable for deriving critical process parameters, has not been feasible. Thus, the microTOM supports robust, data-driven bioprocess development.