4.5 Article

Towards high-throughput optimization of microbial lipid production: from strain development to process monitoring

Journal

SUSTAINABLE ENERGY & FUELS
Volume 4, Issue 12, Pages 5958-5969

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/d0se00540a

Keywords

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Funding

  1. Werner Siemens foundation
  2. Bavarian State Ministry for Environmental and Consumer affairs within the project consortium BayBioTech (TP7) [TLK01U-69045]

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Digitalization drives accelerated process optimization by comprehensive automation. In the advanced biofuels sector this demands automatable high-throughput processes for production strain development and downstream process performance monitoring. In that context, the unit operations of oleaginous yeast-based biodiesel production are amenable to high-throughput process development. Cutaneotrichosporon oleaginosus is a leading production strain for high-energy biofuel options, that is capable of utilizing a broad range of substrates as carbon sources, thereby generating in excess of 60% (w/w) lipids under nutrient limiting conditions. For the first time, we report on the use of fast neutron (FN) irradiation for the rapid, high-throughput genetic enhancement of an oleaginous yeast in conjunction with high-throughput selection of enhanced lipid producing C. oleaginosus mutants by cultivation in the presence of the fatty acid biosynthesis inhibitor cerulenin. Performance monitoring of improved mutants was accomplished by development of a high-throughput lipid qualification methodology based on a miniaturized, low cost Nile red based spectrofluorimetric assay. From the FN mutant library, this high-throughput strain development approach allowed identification of a C. oleaginosus variant (FN M2) displaying a 21.67% (w/v) and 22.58% (w/v) increase in biomass formation and total lipid yield compared to wild-type strain, respectively. Mutant triglyceride characterization revealed a higher content of saturated fatty acids, which is favorable with respect to biofuels production standards, determined here for the first time. This study is an initial step towards an automatable, high-throughput yeast oil optimization process that facilitates accelerated industrial deployment.

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