Issue 9, 2025

Biosynthesis of retinyl esters in Yarrowia lipolytica through metabolic engineering and fermentation condition optimization

Abstract

Retinol, as an essential fat-soluble vitamin, plays an important role in human growth and development. Owing to their excellent stability, retinyl esters, the storage forms of retinol, are widely used in pharmaceuticals and cosmetics. Compared with chemical synthesis, biosynthesis of retinol and its active derivatives is an attractive route for their environmentally friendly and sustainable production. In this study, we first engineered Yarrowia lipolytica to produce retinol; we improved production by screening β-carotene 15,15′-dioxygenase and retinol dehydrogenase orthologs, adjusting the copy numbers of key genes, and strengthening the metabolic flux of the precursor. Combined with cultivation optimization, the engineered strain produced 5.89 g L−1 retinol in fed-batch fermentation. When we changed the cultivation medium from nitrogen-rich to nitrogen-limited medium, the engineered strain switched from producing retinol to producing 8.18 g L−1 retinyl esters. These represent the highest titers of retinol and retinyl esters ever reported for microbial production. Subsequently, specific synthesis of retinyl palmitate production was achieved by adjusting the carbon source and introducing retinol-binding protein expression, which resulted in a 4.53 g L−1 retinyl palmitate titer. In conclusion, we engineered a Yarrowia lipolytica platform for efficient retinyl ester synthesis; these results lay the foundation for the sustainable industrial bioproduction of retinyl esters.

Graphical abstract: Biosynthesis of retinyl esters in Yarrowia lipolytica through metabolic engineering and fermentation condition optimization

Supplementary files

Article information

Article type
Paper
Submitted
06 Nov 2024
Accepted
28 Jan 2025
First published
29 Jan 2025

Green Chem., 2025,27, 2511-2521

Biosynthesis of retinyl esters in Yarrowia lipolytica through metabolic engineering and fermentation condition optimization

J. Zhang, L. Sun, W. Yang, H. Xu, J. Sheng, M. Liu, Q. Qi and J. Hou, Green Chem., 2025, 27, 2511 DOI: 10.1039/D4GC05660D

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