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Synthetic associative learning in engineered multicellular consortia.

Javier Macia1,2, Blai Vidiella1,2, Ricard V Solé3,2,4

  • 1ICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr Aiguader 88, 08003 Barcelona, Spain.

Journal of the Royal Society, Interface
|April 14, 2017
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Summary
This summary is machine-generated.

This study introduces novel two-cell microbial consortia for associative learning (AL). These synthetic biology circuits offer adaptable memory functions, overcoming single-cell design challenges.

Keywords:
adaptationassociative learningcellular circuitsneural systemssynthetic biology

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Area of Science:

  • Synthetic biology
  • Neuroscience
  • Microbiology

Background:

  • Associative learning (AL) is crucial for organism adaptation.
  • Previous synthetic biology approaches for AL faced implementation challenges in single cells.
  • Simpler organisms also exhibit associative learning.

Purpose of the Study:

  • To design and present alternative circuit designs for associative learning using two-cell microbial consortia.
  • To overcome the complexity of single-cell molecular wiring for AL.
  • To engineer biological circuits with memory and adaptation capabilities.

Main Methods:

  • Development of three distinct two-cell microbial consortium designs.
  • Implementation of circuits capable of responding to two classes of stimuli.
  • Demonstration of both long-term and short-term memory functionalities.

Main Results:

  • Successfully demonstrated associative learning responses in microbial consortia.
  • Circuits exhibited both short-term and long-term memory capabilities.
  • Overcame the limitations of single-cell designs for complex biological circuits.

Conclusions:

  • Two-cell microbial consortia offer a viable alternative for engineering associative learning.
  • These designs can be applied to engineer the human gut microbiome and synthetic organoids.
  • Presents a new class of decision-making biological circuits with adaptive memory.