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Optimizing recombinant mini proinsulin production via response surface method and microbioreactor screening.

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Engineered mini-proinsulin (nMPI) production using a hybrid microscale and statistical modeling approach. Optimized bioprocess achieved high yields, demonstrating a scalable platform for recombinant protein expression in E. coli.

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Area of Science:

  • Biotechnology
  • Bioprocess Engineering
  • Molecular Biology

Background:

  • Recombinant insulin production requires scalable, high-yield, cost-effective bioprocesses.
  • Novel mini-proinsulin (nMPI) engineered for enhanced expression and simplified cleavage.
  • Optimization of nMPI production is crucial for meeting increasing demand.

Purpose of the Study:

  • To develop and optimize a high-yield, scalable bioprocess for novel mini-proinsulin (nMPI) production.
  • To apply a hybrid approach combining microscale cultivation and statistical modeling for process optimization.
  • To validate the predictive accuracy and scalability of the developed optimization system.

Main Methods:

  • Engineered novel mini-proinsulin (nMPI) with modified C-peptide and residue substitutions.
  • Utilized BioLector microbioreactor for microscale high-throughput cultivation.
  • Employed response surface methodology (RSM), including Plackett-Burman Design (PBD) and Central Composite Design (CDD), for medium optimization.
  • Scaled up the optimized process to a 3-L bioreactor.

Main Results:

  • Identified glycerol as the most influential medium component for nMPI yield.
  • Optimized medium formulation (Scenario III) achieved 13.00 g/L productivity in microscale cultivation.
  • Maintained high performance upon scale-up, reaching 11.5 g/L in a 3-L bioreactor.
  • Demonstrated balanced carbon and nitrogen sources enhance cell viability and protein expression.

Conclusions:

  • The hybrid optimization system accurately predicts and scales effectively.
  • A robust and scalable production platform for nMPI in E. coli was established.
  • The presented workflow serves as a model for efficient recombinant protein expression systems.
  • The developed bioprocess is suitable for translation into industrial settings.