基于单细胞拉曼分选的新型酵母突变株筛选方法研究

The capability of yeast to adapt and in situ detoxify lignocellulose derived inhibitors is of great significance to bioethanol industry. However, present approaches for development of highly tolerant mutants are time-consuming and with low efficiency, while in-depth investigation of cellular behavior during the evolution process is still lacking. In our recent work, we have developed a prototypical “Raman-activated Cell Sorter” by integrating single-cell Raman micro-spectroscopy, single cell micromanipulator and microfluidics devices. It is able to perform in vivo and multi-parameter phenotypic analysis of individual living cells, as well as single cell sorting followed by functional genomic analysis. In the present proposal, by using of the wild-type yeast strain Saccharomyces cerevisiae NRRL Y12632 and its tolerant derivatives, a research model for tracking of microbial phenotypes in an isogenous population at single cell level will be established. Dynamics of cellular phenotypes during the microevolution process of yeast cells under inhibitors furfural and hydroxymethylfurfural will be monitored by single-cell Raman micro-spectroscopy. The Raman biomarkers significantly associated with the tolerant genotypes will be identified, and subsequently validated by targeted single cell sorting, and following gene expression analysis on sub-population level or even single cell level. Dynamics of phenotypic heterogeneity among the population during the microevolution process will also be revealed, and the key dynamic features of the cellular microevolution process at both population and single cell level will be identified. By enriching tolerant cells in real time using automatic single cell sorting based on phenotypic biomarkers, the present proposal will eventually develop a high-throughput approach for efficient single-cell resolution screening and identification of new tolerant strains. These efforts may also encourage the development of high-productive strains in other bioprocesses, thus is of general value for a broad range of industrial microorganisms.

构建高耐毒性酵母发酵菌种对于提高木质纤维素转化燃料乙醇的效率具有重大意义，但目前的进化筛选手段具有监测指标粗浅、耗时长、效率低的缺点。本团队的活体单细胞拉曼分选装置平台能够利用拉曼光谱技术进行快速、原位、无损的单细胞表型特征和生理状况的测量，并整合单细胞分选和核酸分析功能。本项目将以野生酵母菌株Y12632及其耐毒突变株为研究模型，在单细胞水平上对酵母细胞在糠醛等抑制物压力下进化的表型变化进行动态监测，结合单细胞分选和基因表达分析深入挖掘酵母细胞耐受和代谢抑制物过程中的细胞表型特征，分析其群体异质性，探索进化过程中细胞获得稳定遗传性状的过程动态特征。最终，建立一种单细胞水平的新型酵母突变株筛选方法，以关键细胞表型特征为指征，在驯化过程中实时高通量检测、分选和富集高耐受潜能细胞，从而合理设计、优化和加速突变株选育过程。本方法的建立也将为其他高产能工业微生物的选育提供共性参考价值。

单个细胞是地球上细胞生命体功能和进化的基本单元。单细胞精度的高通量功能分选是解析生命体系异质性机制、探索自然界微生物暗物质的重要工具。单细胞拉曼光谱（SCRS）能够在无标记、无损的前提下揭示细胞固有的化学组成，因此拉曼激活细胞分选技术（RACS）日益受到广泛关注。本项目以野生酵母菌株Y12632及其耐毒突变株为研究模型，在本团队开发及优化的拉曼光谱单细胞表型检测平台基础上，在单细胞层面分别对野生酵母菌株和耐毒菌株生长代谢和产乙醇过程中的表型变化进行了实时动态监测，并通过对图谱进行数学处理和多变量统计学分析，鉴定出与耐受性相关的细胞表型特征，考察了其作为生物标志物并对细胞行为进行预测的可靠性。建立了耐毒产乙醇的稳定培养系，系统研究了菌群内部细胞的拉曼图谱，考察了细胞适应抑制物的表型特征以及这些特征的群体异质性。同时，在开展单细胞层面表型鉴定和特征筛选工作的过程中，我们重点进行了基于微流控芯片技术的单细胞分选和单细胞基因组分析技术的开发和应用，为单细胞关键表型特征的基因型验证提供了技术支持。