Microbioreactor-assisted cultivation workflows for time-efficient phenotyping of protein producing Aspergillus niger in batch and fed-batch mode.

In recent years, many fungal genomes have become publicly available. In combination with novel gene editing tools, this allows for accelerated strain construction, making filamentous fungi even more interesting for the production of valuable products. However, besides their extraordinary production and secretion capacities, fungi most often exhibit challenging morphologies, which need to be screened for the best operational window. Thereby, combining genetic diversity with various environmental parameters results in a large parameter space, creating a strong demand for time-efficient phenotyping technologies. Microbioreactor systems, which have been well established for bacterial organisms, enable an increased cultivation throughput via parallelization and miniaturization, as well as enhanced process insight via non-invasive online monitoring. Nevertheless, only few reports about microtiter plate cultivation for filamentous fungi in general and even less with online monitoring exist in literature. Moreover, screening under batch conditions in microscale, when a fed-batch process is performed in large-scale might even lead to the wrong identification of optimized parameters. Therefore, in this study a novel workflow for Aspergillus niger was developed, allowing for up to 48 parallel microbioreactor cultivations in batch as well as fed-batch mode. This workflow was validated against lab-scale bioreactor cultivations to proof scalability. With the optimized cultivation protocol, three different micro-scale fed-batch strategies were tested to identify the best protein production conditions for intracellular model product GFP. Subsequently, the best feeding strategy was again validated in a lab-scale bioreactor.