Using metabolic networks as artificial neural network architectures

We have recently demonstrated that it was possible to engineer a perceptron (one-layer neural network) in an E. coli cell extract and to use it for sample classification. Having shown that metabolism can be used to process information in engineered biological systems, we are seeking to which extent this is the case in natural systems, in particular with bacteria where signaling pathways are not as developed as in higher organisms. Answering this question is the main purpose of the internship.