Frontiers in Bioengineering and Biotechnology (May 2022)

Optimization and Kinetic Modeling of a Fed-Batch Fermentation for Mannosylerythritol Lipids (MEL) Production With Moesziomyces aphidis

  • Alexander Beck,
  • Alexander Beck,
  • Franziska Vogt,
  • Lorena Hägele,
  • Steffen Rupp,
  • Steffen Rupp,
  • Susanne Zibek,
  • Susanne Zibek

DOI
https://doi.org/10.3389/fbioe.2022.913362
Journal volume & issue
Vol. 10

Abstract

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Mannosylerythritol lipids are glycolipid biosurfactants with many interesting properties. Despite the general interest in those molecules and the need for a robust process, studies on their production in bioreactors are still scarce. In the current study, the fermentative production of MEL in a bioreactor with Moesziomyces aphidis was performed using a defined mineral salt medium. Several kinetic process parameters like substrate consumption rates and product formation rates were evaluated and subsequently enhanced by increasing the biomass concentration through an exponential fed-batch strategy. The fed-batch approaches resulted in two to three fold increased dry biomass concentrations of 10.9–15.5 g/L at the end of the growth phase, compared with 4.2 g/L in the batch process. Consequently, MEL formation rates were increased from 0.1 g/Lh up to around 0.4 g/Lh during the MEL production phase. Thus, a maximum concentration of up to 50.5 g/L MEL was obtained when oil was added in excess, but high concentrations of residual fatty acids were also present in the broth. By adjusting the oil feeding to biomass-specific hydrolysis and MEL production rates, a slightly lower MEL concentration of 34.3 g/L was obtained after 170 h, but at the same time a very pure crude lipid extract with more than 90% MEL and a much lower concentration of remaining fatty acids. With rapeseed oil as substrate, the ideal oil-to-biomass ratio for full substrate conversion was found to be around 10 goil/gbiomass. In addition, off-gas analysis and pH trends could be used to assess biomass growth and MEL production. Finally, kinetic models were developed and compared to the experimental data, allowing for a detailed prediction of the process behavior in future experiments.

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