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A user-friendly, low-cost turbidostat with versatile growth rate estimation based on an extended Kalman filter

Author

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  • Stefan A Hoffmann
  • Christian Wohltat
  • Kristian M Müller
  • Katja M Arndt

Abstract

For various experimental applications, microbial cultures at defined, constant densities are highly advantageous over simple batch cultures. Due to high costs, however, devices for continuous culture at freely defined densities still experience limited use. We have developed a small-scale turbidostat for research purposes, which is manufactured from inexpensive components and 3D printed parts. A high degree of spatial system integration and a graphical user interface provide user-friendly operability. The used optical density feedback control allows for constant continuous culture at a wide range of densities and offers to vary culture volume and dilution rates without additional parametrization. Further, a recursive algorithm for on-line growth rate estimation has been implemented. The employed Kalman filtering approach based on a very general state model retains the flexibility of the used control type and can be easily adapted to other bioreactor designs. Within several minutes it can converge to robust, accurate growth rate estimates. This is particularly useful for directed evolution experiments or studies on metabolic challenges, as it allows direct monitoring of the population fitness.

Suggested Citation

  • Stefan A Hoffmann & Christian Wohltat & Kristian M Müller & Katja M Arndt, 2017. "A user-friendly, low-cost turbidostat with versatile growth rate estimation based on an extended Kalman filter," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-15, July.
    • Handle: RePEc:plo:pone00:0181923
    DOI: 10.1371/journal.pone.0181923
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    References listed on IDEAS

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    1. Kevin M. Esvelt & Jacob C. Carlson & David R. Liu, 2011. "A system for the continuous directed evolution of biomolecules," Nature, Nature, vol. 472(7344), pages 499-503, April.
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    Cited by:

    1. Neythen J Treloar & Alex J H Fedorec & Brian Ingalls & Chris P Barnes, 2020. "Deep reinforcement learning for the control of microbial co-cultures in bioreactors," PLOS Computational Biology, Public Library of Science, vol. 16(4), pages 1-18, April.

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