An engineering biology approach to automated workflow and biodesign
File(s)
Published version
Author(s)
Casas, Alexis
Bultelle, Matthieu
Kitney, Richard
Type
Journal Article
Abstract
The paper addresses the application of engineering biology strategies and techniques to the automation of laboratory workflow—primarily in the context of biofoundries and biodesign applications based on the Design, Build, Test and Learn paradigm. The trend toward greater automation comes with its own set of challenges. On the one hand, automation is associated with higher throughput and higher replicability. On the other hand, the implementation of an automated workflow requires an instruction set that is far more extensive than that required for a manual workflow. Automated tasks must also be conducted in the order specified in the workflow, with the right logic, utilizing suitable biofoundry resources, and at scale—while simultaneously collecting measurements and associated data. The paper describes an approach to an automated workflow that is being trialed at the London Biofoundry at SynbiCITE. The solution represents workflows with directed graphs, uses orchestrators for their execution, and relies on existing standards. The approach is highly flexible and applies to not only workflow automation in single locations but also distributed workflows (e.g. for biomanufacturing). The final section presents an overview of the implementation—using the simple example of an assay based on a dilution, measurement, and data analysis workflow.
Date Issued
2024-06-15
Date Acceptance
2024-06-11
Citation
Synthetic Biology, 2024, 9 (1)
ISSN
1939-7267
Publisher
Oxford University Press
Journal / Book Title
Synthetic Biology
Volume
9
Issue
1
Copyright Statement
© The Author(s) 2024. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/38939829
PII: ysae009
Subjects
Biochemical Research Methods
Biochemistry & Molecular Biology
biodesign
Biology
Biotechnology & Applied Microbiology
DAGs
DBTL paradigm
laboratory automation
Life Sciences & Biomedicine
Life Sciences & Biomedicine - Other Topics
Science & Technology
STANDARD
SYNTHETIC BIOLOGY
Publication Status
Published
Coverage Spatial
England
Article Number
ysae009
Date Publish Online
2024-06-15