Promoter engineering in oleaginous yeasts for value-added chemical production

Oleaginous yeasts, particularly Yarrowia lipolytica, are increasingly used as microbial platforms for producing lipids and other value-added compounds from renewable feedstocks. Their biotechnological utility derives from active lipid metabolism, broad substrate flexibility, and expanding engineering tools, but efficient production requires transcriptional programs that match changing metabolic states during fermentation. Because carbon flux is redistributed across growth, nutrient limitation, lipid accumulation, and production phases, static constitutive expression is often insufficient for optimal pathway performance. Promoter engineering therefore provides a key strategy to control expression strength, timing, and responsiveness in oleaginous yeasts. This review summarizes the metabolic basis of phase-dependent gene expression demand, examines constitutive, inducible, and dynamic promoter systems, and discusses how machine learning can support promoter prediction and design. Current challenges, including limited host-specific datasets, context dependence, and uncertain robustness to scale-up, are also discussed. These advances provide a basis for more precise and scalable engineering of oleaginous yeast cell factories.