Hägele, LorenaPfleger, Brian F.Takors, Ralf2024-10-152024-10-1520242306-53541906279284http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-150563http://elib.uni-stuttgart.de/handle/11682/15056http://dx.doi.org/10.18419/opus-15037In recent years, the design-build-test-learn (DBTL) cycle has become a key concept in strain engineering. Modern biofoundries enable automated DBTL cycling using robotic devices. However, both highly automated facilities and semi-automated facilities encounter bottlenecks in clone selection and screening. While fully automated biofoundries can take advantage of expensive commercially available colony pickers, semi-automated facilities have to fall back on affordable alternatives. Therefore, our clone selection method is particularly well-suited for academic settings, requiring only the basic infrastructure of a biofoundry. The automated liquid clone selection (ALCS) method represents a straightforward approach for clone selection. Similar to sophisticated colony-picking robots, the ALCS approach aims to achieve high selectivity. Investigating the time analogue of five generations, the model-based set-up reached a selectivity of 98 ± 0.2% for correctly transformed cells. Moreover, the method is robust to variations in cell numbers at the start of ALCS. Beside Escherichia coli , promising chassis organisms, such as Pseudomonas putida and Corynebacterium glutamicum , were successfully applied. In all cases, ALCS enables the immediate use of the selected strains in follow-up applications. In essence, our ALCS approach provides a ‘low-tech’ method to be implemented in biofoundry settings without requiring additional devices.eninfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/620660article2024-10-07