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Related Experiment Video

Updated: May 20, 2025

Assembly and Quantification of Co-Cultures Combining Heterotrophic Yeast with Phototrophic Sugar-Secreting Cyanobacteria
05:44

Assembly and Quantification of Co-Cultures Combining Heterotrophic Yeast with Phototrophic Sugar-Secreting Cyanobacteria

Published on: December 27, 2024

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Directing microbial co-culture composition using cybernetic control.

Ting An Lee1, Jan Morlock2, John Allan1

  • 1Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK.

Cell Reports Methods
|March 25, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a cybernetic method to control microbial co-cultures without genetic engineering. The approach uses bioreactor data and temperature adjustments to precisely manage bacterial populations, offering broad applicability for synthetic biology.

Keywords:
CP: biotechnologyCP: microbiologyPI controlbiofilmbioreactorco-culturecontrolcybergeneticcyberneticsystems biology

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Area of Science:

  • Synthetic Biology
  • Biotechnology
  • Control Engineering

Background:

  • Microbial co-cultures are essential in biotechnology but challenging to control.
  • Existing methods often rely on genetic engineering, limiting broad applicability.
  • Precise, non-invasive control strategies are needed for stable co-culture management.

Purpose of the Study:

  • To develop and demonstrate a cybernetic framework for controlling the composition of a bacterial co-culture (Pseudomonas putida and Escherichia coli).
  • To achieve this control without employing genetic engineering for cell-computer interfacing.
  • To establish a broadly applicable method for robustly managing diverse microbial consortia.

Main Methods:

  • Utilized bioreactor measurements to extract real-time composition information.
  • Integrated measurements with a system model using an extended Kalman filter for accurate state estimation.
  • Employed temperature as a control input, leveraging differential species' optimal growth temperatures.
  • Implemented a proportional-integral (PI) control algorithm for dynamic reference tracking and noise rejection.

Main Results:

  • Successfully estimated co-culture composition from noisy bioreactor data.
  • Demonstrated temperature-driven control of microbial composition.
  • Achieved stable co-culture maintenance for 7 days (approximately 250 generations) using PI control.
  • Showcased independence from initial inoculation ratios and effective real-time noise rejection.

Conclusions:

  • The developed cybernetic framework enables precise, non-genetic control of microbial co-cultures.
  • This approach offers a robust and broadly applicable strategy for managing microbial consortia in synthetic biology and biotechnology.
  • The method successfully stabilized a P. putida and E. coli co-culture, demonstrating its practical viability.