Automated microfluidics for gene editing is in the works

Published: 19-Feb-2019

Oxford Genetics has announced a partnership to optimise the way laboratories deliver gene editing to cells and interrogate the resultant products

Oxford Genetics, Sphere Fluidics, the University of Edinburgh, and Twist Bioscience have announced a collaboration to expedite the development of automated microfluidic systems for rapid and high-throughput gene editing in mammalian cell lines.

Under the agreement, Sphere Fluidics will act as the lead partner, looking to utilise its knowledge in microfluidic systems to produce new products designed to meet the requirements of multiplexed gene editing workflows.

Frank F Craig, CEO at Sphere Fluidics, explained: “We plan to develop a desktop system that will miniaturise and automate the genome editing of single cells. Such a product is highly innovative and will be disruptive in that sector. This system will enable scientists to easily perform automated genome editing and create new cell lines and valuable biomedical.”

Oxford Genetics and the University of Edinburgh will provide input into industrial and application-specific requirements, both in relation to standard engineering approaches but also for more difficult host systems, including stems cells and primary cell lines, and in discovery contexts. This collaboration forms part of Oxford Genetics push to automate laboratory processes and facilitate intelligent experimental design and data handling.

Twist Bioscience will contribute DNA synthesis capabilities and required reagents for the project.

Commenting on the partnership, Tom Payne, CSO at Oxford Genetics, said: “Gene editing, particularly CRISPR technologies, have revolutionised the way scientists are able to engineer mammalian cells for a wide variety of applications. While these technologies are highly efficient, there is a requirement to further optimise the way laboratories deliver the CRISPR tools to cells and interrogate the resultant products."

Payne added: "By increasing throughput and reducing timelines in this area, this creates new avenues of research and commercial applications, from our ability to address complex genetics in basic biology to utilising big data to facilitate personalised medicine.”

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