The production of bulk enzymes used in food industry or organic chemistry constitutes an important part of industrial biotechnology. The development of production processes for novel proteins comprises a variety of biological engineering and bioprocess reaction engineering factors. The combinatorial explosion of these factors can be effectively countered by combining high‐throughput experimentation with advanced algorithms for data analysis and experimental design. We present an experimental optimization strategy that merges three different techniques: (1) advanced microbioreactor systems, (2) lab automation, and (3) Kriging‐based experimental analysis and design. This strategy is demonstrated by maximizing product titer of secreted green fluorescent protein (GFP), synthesized by Corynebacterium glutamicum, through systematic variation of CgXII minimal medium composition. First, relevant design parameters are identified in an initial fractional factorial screening experiment. Then, the functional relationship between selected media components and protein titer is investigated more detailed in an iterative procedure. In each iteration, Kriging interpolations are used for formulating hypotheses and planning the next round of experiments. For the optimized medium composition, GFP product titer was more than doubled. Hence, Kriging‐based experimental analysis and design has been proven to be a powerful tool for efficient process optimization.

Development times for efficient large‐scale production, utilizing fungal species, are still very long. This is mainly due to the poor knowledge of many important variables related to fungal growth and morphogenesis. We specifically addressed this knowledge gap by combining a microfluidic cultivation device with time‐lapse live cell imaging. This combination facilitates (i) studying population heterogeneity at single‐cell resolution, (ii) monitoring of fungal morphogenesis in a high spatiotemporal manner under defined environmental conditions, and (iii) parallelization of experiments for statistical data analysis. Our analysis of Penicillium chrysogenum, the workhorse for antibiotic production worldwide, revealed significant heterogeneity in size, vitality and differentiation times between spore, mycelium and pellets when cultivated under industrially relevant conditions. For example, the swelling rate of single spores in complex medium (μ=0.077±0.036h−1) and the formation rate of higher branched mycelia in defined glucose medium (μ=0.046±0.031h−1) were estimated from broad time‐dependent cell size distributions, which in turn were derived from computational image analysis of 257 and 49 time‐lapse series, respectively. In order to speed up the development of new fungal production processes, a deeper understanding of these heterogeneities is required and the presented microfluidic single‐cell approach provides a solid technical foundation for such quantitative studies.

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