试图用拉曼光谱法同时定量单个隐环菌细胞中的多糖、总脂质、蛋白质和色素。

Xiufen Wang, Yuehui He, Yuanyuan Zhou, Baohua Zhu, Jian Xu, Kehou Pan, Yun Li
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摘要

背景:目前,常规的微藻光合产物测定方法通常是基于大量的细胞质量来达到测量基线,结果只能揭示群体水平上的平均状态,这对于从大量潜在的微藻突变体中大规模、快速筛选特定表型是不可行的。近年来,单细胞拉曼光谱(SCRS)被证明能够快速、同步地定量微藻的生化成分。然而,用该方法分析隐环菌(Cyclotella cryptica)的生化成分尚未见报道。因此,SCRS首次尝试测定该硅藻中的这四种生化成分。结果:建立了基于SCRS的同时定量隐藻多糖、总脂、蛋白质和Chl-a含量的方法,发现13条拉曼谱带是硅藻成分的主要标记谱带。基于全谱的偏最小二乘回归(PLSR)模型能够较好地预测这4种元胞成分,Pearson相关系数分别达到0.949、0.904、0.801和0.917。最后,以一个等基因样品的SCRS数据为基础,利用IRCA (Intra-ramanome correlation Analysis)分析了这些组分的两两相关关系和动态转化过程,结果表明,硅饥饿可促进隐藻细胞中的碳从蛋白质和色素代谢流向多糖和脂质代谢。结论:首先,建立了同时定量单个隐隐隐苔细胞中多糖、总脂质、蛋白质和色素的方法。其次,通过IRCA构建胞内组分的即时互转换,该方法基于一个等基因群体的数据集,具有更高的准确性和及时性;综上所述,缺硅可促进隐藻细胞碳从蛋白质和色素代谢向多糖和脂质代谢转移。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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An attempt to simultaneously quantify the polysaccharide, total lipid, protein and pigment in single Cyclotella cryptica cell by Raman spectroscopy.

Background: At present, the conventional methods for determining photosynthetic products of microalgae are usually based on a large number of cell mass to reach the measurement baseline, and the result can only reveal the average state at the population level, which is not feasible for large-scale and rapid screening of specific phenotypes from a large number of potential microalgae mutants. In recent years, single-cell Raman spectra (SCRS) has been proved to be able to rapidly and simultaneously quantify the biochemical components of microalgae. However, this method has not been reported to analyze the biochemical components of Cyclotella cryptica (C. cryptica). Thus, SCRS was first attempt to determine these four biochemical components in this diatom.

Results: The method based on SCRS was established to simultaneously quantify the contents of polysaccharide, total lipids, protein and Chl-a in C. cryptica, with thirteen Raman bands were found to be the main marker bands for the diatom components. Moreover, Partial Least Square Regression (PLSR) models based on full spectrum can reliably predict these four cellular components, with Pearson correlation coefficient for these components reached 0.949, 0.904, 0.801 and 0.917, respectively. Finally, based on SCRS data of one isogenic sample, the pairwise correlation and dynamic transformation process of these components can be analyzed by Intra-ramanome Correlation Analysis (IRCA), and the results showed silicon starvation could promote the carbon in C. cryptica cells to flow from protein and pigment metabolism to polysaccharide and lipid metabolism.

Conclusions: First, method for the simultaneous quantification of the polysaccharide, total lipid, protein and pigment in single C. cryptica cell are established. Second, the instant interconversion of intracellular components was constructed through IRCA, which is based on data set of one isogenic population and more precision and timeliness. Finally, total results indicated that silicon deficiency could promote the carbon in C. cryptica cells to flow from protein and pigment metabolism to polysaccharide and lipid metabolism.

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