A review of yeast: High cell-density culture, molecular mechanisms of stress response and tolerance during fermentation

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation. Raman tweezers was used to acquire the Raman spectra of individual yeast cells. Multivariate curve resolution-alternating least squares (MCR-ALS) and principal component analysis were employed to analyze the Raman spectra dataset. MCR-ALS extracted the spectra of proteins, phospholipids, and triacylglycerols and their relative contents in individual cells. Changes in intracellular biomolecules showed that yeast cells undergo three distinct physiological stages during fermentation. In addition, heterogeneity among yeast cells significantly increased in the late fermentation period, and different yeast cells may respond to ethanol stress via different mechanisms. Our findings suggest that the combination of Raman tweezers and chemometrics approaches allows for characterizing the dynamics of molecular components within individual cells. This approach can serve as a valuable tool in investigating the resistance mechanism and metabolic heterogeneity of yeast cells during ethanol fermentation.

Fed-batch fermentation of Mucor circinelloides reveals significant improvement in biomass and lipid accumulation through performance evaluation, chemical analysis, and expression profiling

This study aimed to improve the lipid and biomass yields of Mucor circinelloides WJ11 by implementing four different fed-batch fermentation strategies, varied in time and glucose concentration (S1-S4). The S1 fermentation strategy yielded the highest biomass, lipid, and fatty acid content (22 ± 0.7 g/L, 53 ± 1.2 %, and 28 ± 1.6 %) after 120 and 144 h, respectively. The γ-linolenic acid titer of 0.75 ± 0.0 g/L was greatest in S3 after 48 h. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to analyze the transcription of key genes involved in lipid accumulation. The glucose-6-phosphate dehydrogenase, 6-phosphogluconate dehydrogenase, and ATP-citrate lyase genes showed increased expression levels. Fourier-transform infrared (FTIR) spectroscopy was used to analyze the biochemical profile during fermentation strategies. Optimal abiotic factors for production efficiency included pH 6.5, 25-26 °C, 15 % (v/v) inoculum, 500 rpm, 20 %-30 % dissolved oxygen, and 120 h fermentation. Glucose co-feeding offers valuable insights to develop effective fermentation strategies for lipid production.