Computational biofilms: analogue spatial computing with bacterial colonies

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Our aim in this project is to engineer arbitrary analogue computation into bacterial biofilms. To explore this, we will implement a type of artificial neural network (ANN) using engineered bacterial populations arranged spatially and linked by intercellular signals. Previous work on computation in biological systems has mostly tried to emulate the digital logic capabilities of electronic circuits. This is a potentially limiting constraint on the naturally analogue processes that occur in biological systems. In comparison, ANNs are not constrained by these limitations, meaning they could be a useful framework for building artificial biological computers. We will engineer E. coli strains with intercellular signalling (quorum sensing) systems, where spatial separation of communicating colonies form a neural network structure. There are three objectives:1. Develop an in silico design process for computational biofilms 2. Create engineered bacterial neurons 3. Demonstrate computational capabilities of spatial biofilms Our approach will open up new ways to perform biological computation, with applications in synthetic biology, bioengineering and biosensing. Ultimately, these neural-network-inspired bacterial communities will help us explore information processing in natural biological systems.