ECCO · Evolutionary Cellular Computing for Environmental Synthetic Biology

This project will build living evolutionary cellular computers, and showcase them as intelligent bioremediation agents. Current synthetic genetic networks that perform human-defined computations must remain unchanged—as initially designed—in order to perform well. This is a problem, since biological substrate adapts and evolves, compromising durability, robustness, and computing power. We will exploit the intrinsic dynamic features of living systems. ECCO’s biocomputers will be able self-adapt and reconfigure at run-time. They will show unprecedented levels of robustness and efficiency—far beyond current technological limits. To this end, we will tackle intra-cellular evolvability and multi-cellular reconfigurability. At the intra-cellular level, we will upgrade current genetic circuitry with pre-defined mutation, evaluation and selection dynamics. Circuits will optimise themselves. At the multi-cellular level, we will design cellular consortia able to reconfigure its structure—therefore changing its functionality—according to environmental needs, thus adaptive. The ECCO project will integrate theoretical developments with in-vivo experimentation. The soil bacteria Pseudomonas putida will be used as a host to illustrate the capabilities of evolutionary genetic circuits. To demonstrate long-run efficiency, bacteria will be used to colonize the root of the plant Arabidopsis thaliana—a much more complex environment than the pristine laboratory conditions where circuits are often characterized. Reconfigurability will be achieved by building a multicellular computer able to switch between metal and aromatic removal circuits—two important pollutants. Evolution, adaptation and reconfigurability are elusive to conventional computers; conveniently, these are intrinsic properties of living organisms. The ECCO will benefit from this in order to engineer living computers that unlock applications in novel domains—from synthetic agriculture to precision bioremediation.