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Adaptive artificial evolution of droplet protocells in a 3D-printed fluidic chemorobotic platform with configurable environments.

Juan Manuel Parrilla-GutierrezSoichiro TsudaJonathan GrizouJames TaylorAlon HensonLeroy Cronin
Published in: Nature communications (2017)
Evolution via natural selection is governed by the persistence and propagation of living things in an environment. The environment is important since it enabled life to emerge, and shapes evolution today. Although evolution has been widely studied in a variety of fields from biology to computer science, still little is known about the impact of environmental changes on an artificial chemical evolving system outside of computer simulations. Here we develop a fully automated 3D-printed chemorobotic fluidic system that is able to generate and select droplet protocells in real time while changing the surroundings where they undergo artificial evolution. The system is produced using rapid prototyping and explicitly introduces programmable environments as an experimental variable. Our results show that the environment not only acts as an active selector over the genotypes, but also enhances the capacity for individual genotypes to undergo adaptation in response to environmental pressures.
Keyphrases
  • high throughput
  • deep learning
  • public health
  • machine learning
  • single cell
  • risk assessment
  • mass spectrometry
  • climate change