Dataset on the generation and inhibitor-based selection of Candida utilis mutants for enhanced protein production

This data article presents a dataset on the generation and inhibitor-based selection of Candida utilis mutants for enhanced protein production. The experimental approach combines random mutagenesis using ethyl methanesulfonate with screening in media supplemented with amino acid biosynthesis inhibitors. These inhibitors impose selective pressure on metabolic pathways related to amino acid synthesis. The dataset includes experimental data from medium screening, mutagenesis, inhibitor-based mutant selection, and cultivation medium optimization using Response Surface Methodology. The applied screening concept uses inhibitory compounds to identify mutant cells that can grow under conditions where the wild-type strain is suppressed. Measured parameters include biomass concentration, protein content, protein yield, optical density, survival rates, and amino acid composition. The dataset also provides replicate measurements, mean values, and standard deviations. The dataset documents the complete workflow from medium screening to mutant selection and process optimization, including validation under shake-flask and bioreactor conditions. It identifies an optimized workflow for C. utilis strain improvement for single-cell protein production. Among the generated mutants, GA0.4/39-2 showed the best overall performance and was successfully validated in 5 L bioreactor cultivation, reaching a maximum biomass concentration of 23.87 ± 0.75 g/L and a maximum protein yield of 11.49 g/L. The dataset provides a reusable framework for microbial strain improvement, single-cell protein production, and bioprocess optimization that may also support the development of similar workflows for other microorganisms.