Scientists are building robotic platforms to test thousands of synthetic DNA constructs in living cells at once, replacing slow, manual lab work with automated systems that measure cell health, function, and productivity in parallel. This matters because synthetic biology—engineering cells to produce new drugs, greener chemicals, or detect cancer—is currently slow and expensive. Each new DNA construct must be tested in host cells to see if it works, but doing this one at a time at the bench limits how many designs can be tried. Without faster testing, the field cannot scale up. The researchers are adding high-throughput assay platforms to two existing DNA synthesis centres, the Edinburgh Genome Foundry and Liverpool GeneMill. These platforms will run medium-throughput assays for cell health and function, alongside software that links test results back to the design process. This closes the design-build-test cycle, letting engineers learn from failures quickly and refine their constructs. If successful, this will cut development time and cost for engineered organisms, making synthetic biology accessible to more academic groups and industries. The ultimate impact could be cheaper biofuels, novel pharmaceuticals, and smarter cell-based diagnostics—manufacturing processes that quietly underpin modern life.
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Synthetic biology seeks to model and construct biological components, functions and organisms that do not exist in nature and to redesign existing biological systems to perform new functions. The construction de novo of large and complex genetic circuits or metabolic pathways will enable us to for example, program stem cell differentiation, detect multiple changes in cancer cells, or engineer cell factories to produce completely novel drugs or greener chemicals and biofuels. The conventional approach of engineering cells at the bench is inherently slow and expensive. Automation and industrialization reduce development time and the economies of scale of medium to high throughput processes can reduce the cost of organism development democratising the endeavour and allowing an expansion in the number of academic groups and industries that can undertake such complex organism engineering. To realise our ambitions for synthetic biology we need enabling technologies that can not only provide robust, reliable and cost effective methodologies for the design, construction and incorporation of synthetic DNA we need to understand the interaction of the component or pathway with the host and capture holistic datasets that report back on synthetic part and pathway performance, cell growth and health. The initial BBSRC investment (BBM00029X1 andBBM00094X1) has helped found two DNA synthesis centres, the Edinburgh Genome Foundry (EGF, based in the School of Biological Sciences) and Liverpool GeneMill (LGM, based within the Centre for Genomic Research CGR) offering DNA design, synthesis and validation of large gene constructs (up to 1Mbp). However, we need to further expand our capabilities to include high throughput assay development suited to assessing whether the DNA construct delivers the desired output (i.e. phenotype) in the host cell. Here we request support for capital equipment that will enable us to set up multi parallel medium throughput assays for cell health, function and productivity. Alongside these platforms we build the software tools for automation and analysis, together with software to integrate this data with the design and fabrication pipelines. This will provide the data needed to inform the future design of refined DNA constructs, accelerate the design build test cycle, improve efficiency and reduce the cost of application of synthetic biology applications. Ultimately this will help drive growth of the markets than can benefit from synthetic biology and add value to the initial investment in the DNA synthesis centres.
Anthony Hall (Co-Investigator)Christiane Hertz-Fowler (Co-Investigator)Claire Eyers (Co-Investigator)Neil Hall (Co-Investigator)Olga Mayans (Co-Investigator)Susan Rosser (Principal Investigator)Yizhi Cai (Co-Investigator)
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