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In this report, a fully integrated solution for laboratory digitization is presented. The approach presents a flexible and complete integration method for the digitally assisted workflow. The worker in the laboratory performs procedures in direct interaction with the digitized infrastructure that guides through the process and aids while performing tasks. The digital transformation of the laboratory starts with standardized integration of both new and “smart” lab devices, as well as legacy devices through a hardware gateway module. The open source Standardization in Lab Automation 2 standard is used for device communication. A central lab server channels all device communication and keeps a database record of every measurement, task and result generated or used in the lab. It acts as a central entry point for process management. This backbone enables a process control system to guide the worker through the lab process and provide additional assistance, like results of automated calculations or safety information. The description of the infrastructure and architecture is followed by a practical example on how to implement a digitized workflow. This approach is highly useful for – but not limited to – the biotechnological laboratory and has the potential to increase productivity in both industry and research for example by enabling automated documentation.

Bacillus spp. endospores are important dormant cell forms and are distributed widely in environmental samples. While these endospores can have important industrial value (e.g. use in animal feed as probiotics), they can also be pathogenic for humans and animals, emphasizing the need for effective endospore detection. Standard spore detection by colony forming units (CFU) is time-consuming, elaborate and prone to error. Manual spore detection by spore count in cell counting chambers via phase-contrast microscopy is less timeconsuming. However, it requires a trained person to conduct. Thus, the development of a facilitated spore detection tool is necessary. This work presents two alternative quantification methods: first, a colorimetric assay for detecting the biomarker dipicolinic acid (DPA) adapted to modern needs and applied for Bacillus spp. and second, a model-based automated spore detection algorithm for spore count in phase-contrast microscopic pictures. This automated spore count tool advances manual spore detection in cell counting chambers, and does not require human overview after sample preparation. In conclusion, this developed model detected various Bacillus spp. endospores with a correctness of 85-89%, and allows an automation and time-saving of Bacillus endospore detection. In the laboratory routine, endospore detection and counting was achieved within 5-10 min, compared to up to 48 h with conventional methods. The DPA-assay on the other hand enabled very accurate spore detection by simple colorimetric measurement and can thus be applied as a reference method.

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