Tom Ellis, September 2013

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Tom Ellis from Imperial College will be visiting on 12 Sep (Thu). If you would like to meet with him, please sign up for a slot below.

Schedule: 12 Sep (Thu)

10:00 am   Richard and Dan S-G, 109 Steele Lab
11:00 am   Continued discussion with Dan S-G [and others?]
11:45 am   Grab lunch (Chandler or Annenberg)
12:15 pm   Lunch seminar: 243 Annenberg
1:15 pm   Zach Sun (meet in 243 ANB)
2:00 pm   John Doyle, 210 ANB
2:45 pm   Open
3:30 pm   Open
4:15 pm   Joe M (Steele 110?)
5:00 pm   Wrap up meeting with Richard
5:30 pm   Done for the day


Characterising, modelling and rewiring the effect synthetic genetic circuits have on the capacity of their host chassis
Tom Ellis, Imperial College, London
12 Sep (Thu), 12-1:15, 243 ANB

Characterisation and understanding of genetic components is a key part of both synthetic biology and systems biology. Quantitative knowledge of how DNA parts encode function allows parts to be predictably constructed into synthetic gene circuits. Less understood is how the expression of a synthetic gene circuit can have a detrimental effect on its host cell (the chassis) and how these effects can feedback to the behaviour of the circuit. We investigate how synthetic circuits use cellular resources (e.g. DNA polymerase, RNA polymerase, ribosomes, tRNA, etc.) to replicate and express and we quantify these effects and model gene expression in a way that accounts for this. This is done by considering this shared 'resource pool' as an interface between the host cell and the synthetic circuit. Through genetic engineering and synthetic biology, we have created a system that monitors the availability of shared resources in E. coli, thus enabling the quantification of the burden a synthetic circuit places on the cell's resources. We then measure the burden of a combinatorial library of different designs to examine how different genetic components influence the magnitude of burden. This is accompanied by a mathematical model. Through this method we work towards a system that will enable the prediction of how to optimise the design of a synthetic circuit with regards to its output and the levels of burden it places on a cell.