Establishing a Fed-Batch Process for Protease Expression with Bacillus licheniformis in Polymer-Based Controlled-Release Microtiter Plates
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Updated: Jan 20, 2026

A 96 Well Microtiter Plate-based Method for Monitoring Formation and Antifungal Susceptibility Testing of Candida albicans Biofilms
Published on: October 21, 2010
Tobias Habicher1, Edward K A Rauls1, Franziska Egidi1
1AVT-Biochemical Engineering, RWTH Aachen University, Aachen, 52074, Germany.
Abstract:
Introducing fed-batch mode in early stages of development projects is crucial for establishing comparable conditions to industrial fed-batch fermentation processes. Therefore, cost efficient and easy to use small-scale fed-batch systems that can be integrated into existing laboratory equipment and workflows are required. Recently, a novel polymer-based controlled-release fed-batch microtiter plate is described. In this work, the polymer-based controlled-release fed-batch microtiter plate is used to investigate fed-batch cultivations of a protease producing Bacillus licheniformis culture. Therefore, the oxygen transfer rate (OTR) is online-monitored within each well of the polymer-based controlled-release fed-batch microtiter plate using a µRAMOS device. Cultivations in five individual polymer-based controlled-release fed-batch microtiter plates of two production lots show good reproducibility with a mean coefficient of variation of 9.2%. Decreasing initial biomass concentrations prolongs batch phase while simultaneously postponing the fed-batch phase. The initial liquid filling volume affects the volumetric release rate, which is directly translated in different OTR levels of the fed-batch phase. An increasing initial osmotic pressure within the mineral medium decreases both glucose release and protease yield. With the volumetric glucose release rate as scale-up criterion, microtiter plate- and shake flask-based fed-batch cultivations are highly comparable. On basis of the small-scale fed-batch cultivations, a mechanistic model is established and validated. Model-based simulations coincide well with the experimentally acquired data.
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