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Related Experiment Videos

Dual-substrate utilization by Bordetella pertussis.

R Neeleman1, M Joerink, C Beuvery

  • 1National Institute of Public Health and the Environment, Laboratory for Product and Process Development, Bilthoven, The Netherlands. Ronald.Neeleman@rivm.nl

Applied Microbiology and Biotechnology
|January 5, 2002
PubMed
Summary

A new model improves Bordetella pertussis cultivation by quantitatively describing substrate utilization. This essential kinetics model enhances monitoring and control strategies for the bacterium.

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Area of Science:

  • Microbiology
  • Biotechnology
  • Bioprocess Engineering

Background:

  • Bordetella pertussis cultivation requires improved methods for enhanced monitoring and control.
  • Current modeling approaches are insufficient for accurately describing Bordetella pertussis growth kinetics.
  • Understanding substrate utilization is crucial for optimizing bacterial growth.

Purpose of the Study:

  • To develop a quantitative model for Bordetella pertussis substrate utilization.
  • To improve the efficiency and accuracy of Bordetella pertussis cultivation.
  • To provide a foundation for advanced monitoring and control techniques.

Main Methods:

  • Development of a novel model combining essential and enhanced kinetics.
  • Utilizing experimental observations for model parameterization.

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  • Implementing a step-wise procedure for model parameter fitting.
  • Validation through two experimental cultivations.

    • Main Results:

    • A quantitative model accurately describing Bordetella pertussis growth was successfully developed.
    • The model integrates essential and enhanced kinetic parameters.
    • Step-wise parameter fitting proved effective for model calibration.
    • Experimental cultivations confirmed the model's predictive accuracy.

    Conclusions:

    • The developed model offers a significant improvement for Bordetella pertussis cultivation.
    • This quantitative description facilitates enhanced monitoring and control strategies.
    • The model provides a robust framework for bioprocess optimization.