Getting the Right Clones in an Automated Manner: An Alternative to Sophisticated Colony-Picking Robotics
In 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 scre...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-09-01
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| Series: | Bioengineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2306-5354/11/9/892 |
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| Summary: | In 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 <i>Escherichia coli</i>, promising chassis organisms, such as <i>Pseudomonas putida</i> and <i>Corynebacterium glutamicum</i>, 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. |
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| ISSN: | 2306-5354 |