中国农业科学 ›› 2020, Vol. 53 ›› Issue (18): 3833-3845.doi: 10.3864/j.issn.0578-1752.2020.18.017

• 畜牧·兽医·资源昆虫 • 上一篇    下一篇

基于高分辨质谱和代谢组学技术评估和优化蜂王浆代谢物提取方法

张丽翠(),马川,冯毛,李建科()   

  1. 中国农业科学院蜜蜂研究所,北京 100093
  • 收稿日期:2020-01-18 接受日期:2020-02-25 出版日期:2020-09-16 发布日期:2020-09-25
  • 通讯作者: 李建科
  • 作者简介:张丽翠,E-mail: 604011320@qq.com
  • 基金资助:
    国家现代农业产业技术体系(蜜蜂CARS-44);中国农业科学院科技创新工程(CAAS-ASTIP-2015-IAR)

Evaluation and Optimization of Metabolite Extraction Protocols for Royal Jelly by High Resolution Mass Spectrometry and Metabolomics

ZHANG LiCui(),MA Chuan,FENG Mao,LI JianKe()   

  1. Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093
  • Received:2020-01-18 Accepted:2020-02-25 Online:2020-09-16 Published:2020-09-25
  • Contact: JianKe LI

摘要:

【目的】蜂王浆是具有医疗保健功效的天然产品,含有丰富的小分子活性成分,目前蜂王浆代谢物的提取尚缺乏系统研究。通过蜂王浆代谢轮廓分析,比较不同溶剂对蜂王浆小分子化合物的提取效果,优化蜂王浆代谢物提取方法,鉴定蜂王浆中的代谢物。【方法】分别使用6种溶剂(50%和80%的甲醇、乙醇和乙腈)提取蜂王浆代谢物,运用反相液相色谱(reverse phase liquid chromatography,RPLC)和亲水相互作用色谱(hydrophilic interaction liquid chromatography,HILIC)分别联合四级杆-静电场轨道阱高分辨质谱技术(Q-exactive orbitrap HRMS)进行检测。比较不同溶剂组的代谢特征离子数量和相对标准偏差(relative standard deviation,RSD),并进行主成分分析(principal component analysis,PCA)。利用质谱数据库定性代谢物,并经标准品验证,比较其RSD差异,进行聚类热图(clustering heatmap)分析。通过正交偏最小二乘判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA)、单变量统计分析(student’s t-test)和倍数变化(fold change,FC)筛选溶剂组间具有显著差异的代谢物。【结果】强极性化合物,包括葡萄糖与果糖等同分异构体,在HILIC条件下分离良好,而脂类等中低极性化合物在RPLC条件下得到较好的分离。两种色谱分离方法的应用实现了对不同极性代谢物的检测,在蜂王浆中共鉴定到70种高丰度化合物,涵盖了糖、氨基酸、脂类、维生素等,其丰度差异高达8 340倍,其中有17种化合物为本研究首次报道。乙腈溶剂得到的代谢特征离子数量最少,80%乙腈比50%乙腈的提取效果更差;对甲醇和乙醇而言,高浓度时的代谢特征离子数量更多。所有溶剂组得到的RSD值集中分布在20%范围内,但80%乙腈组在10%内的占比最低,已鉴定的70种代谢物的RSD值进一步证明80%乙腈的重复性较差。PCA结果表明,来自同一提取溶剂的蜂王浆代谢谱高度相似,不同溶剂提取的样品间存在差异,其中,80%乙腈组与其他5组差异最大。聚类热图等分析结果表明,中低极性物质在50%溶剂组丰度较低,强极性物质特别是果糖、葡萄糖、蔗糖、赖氨酸、腺苷、胆碱、磷酸胆碱和葡萄糖酸在80%乙腈组丰度最低。【结论】RPLC和HILIC分别联合高分辨质谱技术能够较全面准确地检测蜂王浆中的小分子化合物,80%甲醇或80%乙醇是提取蜂王浆代谢物的最佳溶剂。

关键词: 蜂王浆, 代谢组学, 样品提取, 高分辨质谱

Abstract:

【Objective】Royal jelly, a natural product with health-promoting effect, is rich in small-molecule bioactive compounds. The systematic analysis of the metabolite extraction from royal jelly is still lacking. This study performed metabolic profiling of royal jelly with an aim to compare the metabolite extraction efficiency using different solvents, optimize the metabolite extraction protocol, and globally identify the small-molecule compounds in royal jelly. 【Method】Metabolites in royal jelly were extracted separately using six different solvents including 50% and 80% methanol, ethanol, and acetonitrile. They were analyzed by reverse phase liquid chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) each combined with Quadrupole-Exactive Orbitrap high resolution mass spectrometry (HRMS). The amount and relative standard deviation (RSD) values of metabolite features among the solvent groups were compared. Principal component analysis (PCA) was conducted on the basis of these metabolite features. The compound identification was based on mass spectrometry databases and was validated with standards. Both the RSD value comparison and clustering heatmap analysis were performed for the identified compounds. Significantly differential metabolites among the solvent groups were screened out by orthogonal partial least squares-discriminant analysis (OPLS-DA), univariate analysis (Student’s t-test) and fold change (FC). 【Result】Highly polar metabolites, including two isomeric sugars (glucose and fructose), and medium and weakly polar metabolites such as lipids were sufficiently separated using the HILIC and PRLC approach, respectively. The combination of the two separation methods enabled comprehensive detection of metabolites with different polarity in royal jelly. A total of 70 high-abundance compounds were identified, including carbohydrates, amino acids, lipids, and vitamins, with the highest difference of 8 340 times in abundance. Among them, 17 compounds were reported for the first time. The lowest number of metabolite features was obtained with acetonitrile, and a worse coverage was obtained with 80% than 50% acetonitrile. For methanol and ethanol, the number of metabolite features was higher at higher solvent concentrations. The RSD values of most metabolite features were lower than 20% in all solvent groups, and the 80% acetonitrile group had the lowest proportion within 10% RSD values compared with other solvents. The RSD values of the 70 identified compounds provided further evidence for the poor repeatability of 80% acetonitrile. The PCA score plots indicated a similar metabolic profiling from the same solvent. Differences in metabolic profiling were observed among the solvents, and the largest difference existed between 80% acetonitrile and the five other solvents. The clustering heatmap showed a lower abundance of medium and weakly polar metabolites obtained from 50% solvents and a lower abundance of highly polar metabolites including, in particular, fructose, glucose, sucrose, lysine, adenosine, choline, phosphorylcholine, and gluconic acid from 80% acetonitrile. 【Conclusion】The combination of RPLC-HRMS and HILIC-HRMS enables comprehensive and accurate detection of small-molecule compounds in royal jelly. 80% methanol or 80% ethanol is an optimal solvent for metabolite extraction from royal jelly.

Key words: royal jelly, metabolomics, sample extraction, high resolution mass spectrometry (HRMS)