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A model-based framework for parallel scale-down fed-batch cultivations in mini-bioreactors for accelerated

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|July 19, 2019
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Summary

This study introduces a novel high-throughput platform for bioprocess development, enabling the study of Escherichia coli strain responses to concentration gradients using mini-bioreactors and mechanistic models for improved scale-up.

Keywords:
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Area of Science:

  • Biotechnology
  • Bioprocess Engineering
  • Metabolic Engineering

Background:

  • Industrial-scale bioreactors face challenges with concentration gradients impacting process efficiency.
  • Scale-up failures can occur due to uncharacterized strain responses to process heterogeneities.
  • Existing scale-down techniques are not readily integrated into early bioprocess development on parallel cultivation devices.

Purpose of the Study:

  • To develop a high-throughput platform for studying strain responses to concentration gradients in bioreactors.
  • To investigate the effects of glucose and dissolved oxygen gradients on Escherichia coli physiology and recombinant protein production.
  • To enable early-stage assessment of strain robustness for bioprocess scale-up.

Main Methods:

  • Integration of mechanistic growth models with a parallel mini-bioreactor system.
  • Application of a model-based glucose pulse feeding scheme, compared to continuous feeding.
  • Cultivation of Escherichia coli to assess cell physiology and noncanonical amino acid incorporation.

Main Results:

  • Significant increase in norvaline incorporation into recombinant proinsulin under oscillating glucose/oxygen conditions.
  • Norvaline incorporation levels were dependent on pulse frequency, unlike continuous feeding.
  • The scale-down approach significantly affected more model parameters than reference cultivations.

Conclusions:

  • The developed platform effectively simulates concentration gradients, revealing strain-specific responses.
  • This approach allows for simultaneous strain screening and scale-down studies.
  • It facilitates the selection of robust strains, reducing risks associated with bioprocess scale-up.