Tom EllisView all speakers
Tom Ellis is a lecturer (Assistant Professor) in the Department of Bioengineering at Imperial College London and leads the Ellis Lab at the Centre for Synthetic Biology and Innovation (CSynBI). His research focuses on developing the tools and methods to rewire gene expression and to enable the future design and assembly of synthetic microbial genomes. This research is being utilised in CSynBI on projects on intrinsic containment and for biofuel and antibiotic biosynthesis.
Ellis was an undergraduate at Oxford University and received his PhD from the University of Cambridge. Following two years in commercial drug discovery, he was a postdoctoral fellow with James J Collins at Boston University. At Imperial College, he leads the UK contribution to the Sc2.0 Synthetic Yeast genome project and co-organises undergraduate synthetic biology teaching.
As we construct the first synthetic eukaryotic genome with the Sc2.0 consortium, how do we plan to add new functions to the minimal genomes that are created? While much larger, our own genome contains less than 23,000 genes, yet it encodes for many of the most complex systems we know. The key to this immense complexity is gene regulation, and recent work has estimated that the human genome contains nearly 4 million switches that control where and when the genes are turned on and off in a myriad of ways. Engineering composable switches is the key to bringing designed complexity to synthetic biology. To do this we are taking a bottom-up approach; using bioinformatics tools to first identify minimal promoter sequences and then using these as the framework to rationally engineer dozens of new synthetic switches. Starting in S. cerevisiae, we have developed a workflow to rapidly generate promoter libraries during the process of DNA assembly. Mutation then guides where we target these promoters with a combinatorial TAL-Effector library that offers 1-to-1 repression of the intended gene. Wiring these synthetic switches together in increasingly large constructs enables us to understand the current limiting factors for engineering complexity – orthogonality, noise, burden and genetic instability – and guides us to generate new designs that account for these factors.