# Turbid but accurate: automating lysostaphin quantification including uncertainty quantification

## TL;DR

A new automated method using turbidity measurements and Bayesian analysis enables accurate and fast quantification of lysostaphin, an antibacterial agent, suitable for high-throughput applications.

## Contribution

An automated turbidity-based assay with Bayesian data analysis for precise lysostaphin quantification is introduced, enabling high-throughput antibacterial screening.

## Key findings

- The method uses autoclaved Staphylococcus carnosus TM300 as a suitable indicator strain for lysostaphin activity.
- The optimized assay has a dynamic range of 0.63–10 mg L−1 lysostaphin.
- The approach is robust, scalable, and adaptable to other turbidity-based assays like endolysin activity assessments.

## 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.