Kinetic and Stoichiometric Modeling-Based Analysis of Docosahexaenoic Acid (DHA) Production Potential by Crypthecodinium cohnii from Glycerol, Glucose and Ethanol
Research output: Journal contributions › Journal articles › Research › peer-review
Authors
Docosahexaenoic acid (DHA) is one of the most important long-chain polyunsaturated fatty acids (LC-PUFAs), with numerous health benefits. Crypthecodinium cohnii, a marine hetero-trophic dinoflagellate, is successfully used for the industrial production of DHA because it can ac-cumulate DHA at high concentrations within the cells. Glycerol is an interesting renewable substrate for DHA production since it is a by-product of biodiesel production and other industries, and is globally generated in large quantities. The DHA production potential from glycerol, ethanol and glucose is compared by combining fermentation experiments with the pathway-scale kinetic modeling and constraint-based stoichiometric modeling of C. cohnii metabolism. Glycerol has the slow-est biomass growth rate among the tested substrates. This is partially compensated by the highest PUFAs fraction, where DHA is dominant. Mathematical modeling reveals that glycerol has the best experimentally observed carbon transformation rate into biomass, reaching the closest values to the theoretical upper limit. In addition to our observations, the published experimental evidence indi-cates that crude glycerol is readily consumed by C. cohnii, making glycerol an attractive substrate for DHA production.
Original language | English |
---|---|
Article number | 115 |
Journal | Marine Drugs |
Volume | 20 |
Issue number | 2 |
Number of pages | 18 |
ISSN | 1660-3397 |
DOIs | |
Publication status | Published - 01.02.2022 |
Bibliographical note
This work was funded by the Latvian ERDF project 1.1.1.1/18/A/022. R.M., M.R.B. and A.P. were supported by University of Latvia under project “Climate change and its impacts on sustainability of natural resources” (Nr. Y5-AZ20-ZF-N-270).
- Central metabolism, Constraint-based model, FTIR spectroscopy, Kinetic model, Krebs cycle
- Biology