Turbid but accurate: automating lysostaphin quantification including uncertainty quantification

Abstract Conventional methods for measuring antibacterial activity, such as disk-diffusion assays, have limitations in quantitative reliability and require long incubation times making them unsuitable for high-throughput applications. To address these limitations, we automated a turbidity-based assay using readily available equipment and Bayesian data analysis, enabling accurate and precise antibacterial quantification from high-throughput experiments. In this study, we demonstrate the method applied to lysostaphin, a potent anti-staphylococcal agent and promising candidate for therapeutic applications. The turbidity assay monitors optical density changes upon lysostaphin-induced lysis of a susceptible Staphylococcus strain. We validated the use of autoclaved Staphylococcus carnosus TM300 as suitable indicator strain and optimized assay conditions for dynamic range of 0.63–10 mg L −1 lysostaphin. Our integrated approach provides a robust, scalable, and reproducible platform for quantifying active lysostaphin, paving the way for its application in high-throughput screening and process development. We believe that the approach is adaptable to other turbidity-based assays, such as those assessing endolysin activity.