A programmable rhizosphere: Highly-integrated genetic programs for spatio-temporal control

by Anil Wipat

16:00 (40 min) in CT 7.01

The study of patterns in gene regulation in space and time is central to several questions in modern biology. A significant portion of the nascent field of synthetic biology has revolved around developing synthetic gene networks to recapitulate regulatory mechanisms found in nature. The ability to implement highly integrated genetic programs encoding spatial and temporal control over biological functions with the requisite precision in living systems is the ‘holy grail’ for the synthetic biology community. Artificial gene networks have not approached the sophistication of their natural counterparts in either design or performance, and technical and scientific challenges currently limit the engineering of large-scale integrated genetic networks.

We therefore set out to develop a framework for automating the process of gene network design that leverages our cumulative experience in:

  1. abstracting functional regulatory modules from nature,
  2. reorganizing these modules into synthetic gene networks,
  3. characterizing these modules to define their operational features and
  4. applying the engineering sciences of optimization, dynamical control systems and reliability theory to model their behavior computationally.

We aimed to demonstrate value of this integrated, systems-approach through the design of the ‘Programmable Rhizosphere’, an engineered mutualism between a plant (Arabidopsis thaliana) and soil microbe (Bacillus subtilis).

In this talk I will give an overview of this recent blue-skies collaborative project between partners in the US and the UK. I will particularly focus on the Newcastle computational and biological outputs of the project but will also highlight key outputs from the other partners.