Transcriptomic profiling of five industrial wine yeast strains at three time points during alcoholic fermentation

Our study involves a transcriptomic approach to the analysis of industrial yeast metabolism. Historically, among the hundreds of yeast species, Saccharomyces cerevisiae has played an important role in scientific investigations and industrial applications, and it is universally acknowledged as one of the model systems for eukaryotic organisms. Yeast is also an important component of the wine fermentation process and determines various attributes of the final product.Our research takes a holistic approach to the improvement of industrial yeast strains by integrating large data sets from various yeast strains during fermentation. This means that analysis can be done in such a way as to co-evaluate several parameters simultaneously to identify points of interest and target genes for metabolic engineering.Eventually we hope to construct an accurate information matrix and a more complete cellular map for the fermenting yeast. This will enable accurate model-building for industrial yeast and facilitated the design of intelligent yeast improvement strategies which can be applied via traditional avenues of molecular biology.

本研究采用转录组学方法分析工业酵母的代谢过程。长期以来，在数百种酵母菌中，酿酒酵母（Saccharomyces cerevisiae）在科学研究与工业应用中均发挥了关键作用，被公认为真核生物的经典模式系统之一。同时，酿酒酵母也是葡萄酒发酵过程的核心功能组分，可直接决定最终成品的多项品质属性。本研究采用整体性研究策略，通过整合不同酵母菌株在发酵过程中产生的多源大数据，开展工业酵母菌株的改良研究。该研究模式可实现多参数同步协同评估，从而精准锁定代谢工程研究中的关键靶点与目标基因。本研究最终目标是构建发酵过程中酿酒酵母的精准信息矩阵与更为完整的细胞图谱，这将为工业酵母构建精准预测模型提供坚实支撑，并助力设计智能酵母改良方案，后续可通过传统分子生物学技术路径实现落地应用。