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Evaluation of Chemical and Physical Triggers for Enhanced Photosynthetic Glycerol Production in Different Dunaliella Isolates.

Linda KeilFarah Mitry QouraJonas Martin BreitsameterBernhard RiegerDaniel GarbeThomas Bartholomäus Brück
Published in: Microorganisms (2024)
The salt-tolerant marine microalgae Dunaliella tertiolecta is reported to generate significant amounts of intracellular glycerol as an osmoprotectant under high salt conditions. This study highlights the phylogenetic distribution and comparative glycerol biosynthesis of seven new Dunaliella isolates compared to a D. tertiolecta reference strain. Phylogenetic analysis indicates that all Dunaliella isolates are newly discovered and do not relate to the D. tertiolecta reference. Several studies have identified light color and intensity and salt concentration alone as the most inducing factors impacting glycerol productivity. This study aims to optimize glycerol production by investigating these described factors singularly and in combination to improve the glycerol product titer. Glycerol production data indicate that cultivation with white light of an intensity between 500 and 2000 μmol m -2 s -1 as opposed to 100 μmol m -2 s -1 achieves higher biomass and thereby higher glycerol titers for all our tested Dunaliella strains. Moreover, applying higher light intensity in a cultivation of 1.5 M NaCl and an increase to 3 M NaCl resulted in hyperosmotic stress conditions, providing the highest glycerol titer. Under these optimal light intensity and salt conditions, the glycerol titer of D. tertiolecta could be doubled to 0.79 mg mL -1 in comparison to 100 μmol m -2 s -1 and salt stress to 2 M NaCl, and was higher compared to singularly optimized conditions. Furthermore, under the same conditions, glycerol extracts from new Dunaliella isolates did provide up to 0.94 mg mL -1 . This highly pure algae-glycerol obtained under optimal production conditions can find widespread applications, e.g., in the pharmaceutical industry or the production of sustainable carbon fibers.
Keyphrases
  • high intensity
  • escherichia coli
  • machine learning
  • genetic diversity
  • mental health
  • electronic health record
  • artificial intelligence