Login / Signup

Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback.

Joaquín Gutiérrez MenaSant KumarMustafa Khammash
Published in: Nature communications (2022)
Communities of microbes play important roles in natural environments and hold great potential for deploying division-of-labor strategies in synthetic biology and bioproduction. However, the difficulty of controlling the composition of microbial consortia over time hinders their optimal use in many applications. Here, we present a fully automated, high-throughput platform that combines real-time measurements and computer-controlled optogenetic modulation of bacterial growth to implement precise and robust compositional control of a two-strain E. coli community. In addition, we develop a general framework for dynamic modeling of synthetic genetic circuits in the physiological context of E. coli and use a host-aware model to determine the optimal control parameters of our closed-loop compositional control system. Our platform succeeds in stabilizing the strain ratio of multiple parallel co-cultures at arbitrary levels and in changing these targets over time, opening the door for the implementation of dynamic compositional programs in synthetic bacterial communities.
Keyphrases
  • high throughput
  • healthcare
  • escherichia coli
  • deep learning
  • public health
  • machine learning
  • single cell
  • gene expression
  • genome wide
  • microbial community
  • quality improvement
  • risk assessment
  • climate change