Quantitative assessment of cellular oxidative stress requires parallel matched profiling of intracellular redox state and extracellular respiratory activity, yet paired sensing approaches remain limited. Here, we present a dual-fluorescent sensing platform combining a genetically encoded redox biosensor (roGFP2-Tsa2ΔC_R) with an optical oxygen sensor embedded in microwell plates for parallel, non-invasive quantification of intracellular hydrogen peroxide, a major reactive oxygen species (ROS), and oxygen consumption rates (OCR) in industrial yeast systems. The roGFP2-based sensor was stably expressed in Saccharomyces cerevisiae (S. cerevisiae) and Yarrowia lipolytica (Y. lipolytica), enabling dynamic monitoring of oxidative stress at population, single-cell, and subcellular levels, while oxygen-sensitive films provided real-time respiration measurements. Using this platform, we identified distinct redox-respiration phenotypes between the two yeasts. Crabtree-positive S. cerevisiae exhibited low OCR and mitochondrial ROS during glucose cultivation, whereas growth on ethanol-glycerol increased OCR and mitochondrial ROS by ∼2.5-fold and 12%, respectively. In contrast, the obligate respiratory yeast Y. lipolytica displayed 3-fold higher OCR and 16% lower mitochondrial ROS than respiring S. cerevisiae, indicating differences in respiratory oxidative burden. Antimycin A treatment (1.25 μM) reduced OCR by 85% in respiring S. cerevisiae while increasing mitochondrial ROS by 27% when compared to corresponding basal levels, whereas Y. lipolytica showed greater resistance to respiratory and oxidative perturbations. By combining intracellular redox sensing with extracellular oxygen measurements, this platform enables paired quantitative profiling of redox state and respiration in living cells. The approach provides a scalable framework for evaluating cellular fitness, stress tolerance, and metabolic state, with broad applications in biomanufacturing and development of yeast-based disease models.

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Journal Article

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Parvin S, Ploessl D, Zhang Z, Shao Z, Lu M

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