The therapeutics of tomorrow will be individualized, specific, and self-regulated. This could be achieved by synthetic organisms, once we know how to engineer them. The simplest and safest is the bacteriophage (phage). We aim to experimentally construct a new phage (de novo) that could be useful against antibiotic-resistant bacteria.

Another aim is to experimentally create artificial intelligence in living cells. For this, we propose a new way to engineer general-purpose gene circuits without a predefined final behaviour. The circuit dynamics will adapt through reinforcement learning to acquire the desired phenotype only once the cell activates it. We have demonstrated this with E. coli, where we have empowered the cells with the ability to learn board games such as tic-tac-toe. This adaptation is inherited to the offspring but it is not genetic. 

We will pursue those aims by developing general methodologies to design new biological molecules, viruses and cells with completely new functions. These methodologies rely on automated computational and/or experimental procedures. We have developed computational methodologies to design de novo: RNA, proteins and whole-cell transcriptional circuits. We have also developed automated methodologies to design biomolecules based on experimental procedures. They rely on the combination of phage transduction, evolution and continuous culture bioreactors to implement an accelerated evolution in living cells, which mimics our computational optimisation algorithms. We work at the interface of experimental molecular biology, combinatorial optimisation, microfluidics and directed evolution.

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Instituto de Biología Integrativa de Sistemas (I2SysBio)
Parc Científic Universitat de València
C/ Catedrático Agustín Escardino, 9
46980 Paterna (Valencia). Spain

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