基于气相色谱-质谱联用与液相色谱-质谱联用的非靶向代谢组学用于3类茶叶中化学成分分析

doi:10.3724/SP.J.1123.2014.04029

色谱 ›› 2014, Vol. 32 ›› Issue (8): 804-816.DOI: 10.3724/SP.J.1123.2014.04029

基于气相色谱-质谱联用与液相色谱-质谱联用的非靶向代谢组学用于3类茶叶中化学成分分析

张磊, 曾仲大, 叶国注, 赵春霞, 路鑫, 许国旺

分离分析化学重点实验室, 中国科学院大连化学物理研究所, 辽宁大连 116023

收稿日期:2014-04-18 修回日期:2014-05-20 出版日期:2014-08-08 发布日期:2014-08-01
通讯作者: 许国旺，E-mail：xugw@dicp.ac.cn
基金资助:
This work was supported by the project (No. 201210075) from the General Administration of Quality Supervision, Inspection and Quarantine of China, the project (No. 2012CB720801) from the Ministry of Science and Technology of China, the foundation (No. 21175132) and the creative search group project (No. 21321064) from the National Natural Science Foundation of China.

Non-targeted metabolomics study for the analysis of chemical compositions in three types of tea by using gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry

ZHANG Lei, ZENG Zhongda, YE Guozhu, ZHAO Chunxia, LU Xin, XU Guowang

Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China

Received:2014-04-18 Revised:2014-05-20 Online:2014-08-08 Published:2014-08-01

摘要/Abstract

摘要：

茶叶中的化学成分是构成其风味特征的物质基础。本研究建立了基于气相色谱-质谱联用和液相色谱-质谱联用的非靶向代谢组学方法。完成预处理及分析条件优化后，使用标准样品考察方法的线性、回收率及重复性，结果表明方法整体稳定且结果可靠。将该方法用于绿茶、乌龙茶和红茶中化学成分的分析。通过超声辅助溶剂提取及气相色谱-质谱联用分析共获得1812个特征峰，而使用加热溶剂提取及液相色谱-质谱联用分析可获得2608个特征峰。结合保留规律及质谱数据库，共定性173种化合物（109 种随后经标准样品验证），其中只有9种化合物在上述两类分析中被同时检出，表明方法互补性良好。3类茶叶数据的偏最小二乘判别分析结果表明，三者间存在显著差异。结合模型的变量重要因子（VIP）与非参数检验共筛选出90种化合物，其中包含儿茶素、氨基酸、糖、有机酸和黄酮苷类等众多与茶叶滋味密切相关的化学成分。

关键词: 茶, 代谢组学, 气相色谱-质谱, 液相色谱-质谱

Abstract:

Tea is one of the most widely consumed beverages in the world for its benefits to daily life and health. To discover the difference and correlation of chemical compositions in the three typical types of tea, a non-targeted metabolomics method was developed. After the optimization of extraction methods, gas chromatography-time-of-flight mass spectrometry and liquid chromatography-quadrupole time-of-flight mass spectrometry were applied for metabolomics analysis, 1812 and 2608 features were obtained, respectively. By comparing with the known compounds in public and/or commercial databases, 173 compounds were tentatively identified, and 109 of them were experimentally confirmed by standards. Totally, 33 tea samples including 12, 12 and 9 samples of green, oolong and black tea, respectively, were analyzed by using the above two methods. Multivariate analysis, Mann-Whitney U test and hierarchical cluster analysis were used to find and visualize the differential components in the three types of tea. Finally, 90 compounds, which contain catechins, amino acids, organic acids, flavonol glycosides, alkaloids, carbohydrates, lipids, etc, were found with a significant difference among them. This study demonstrates the potentials and power of metabolomics methods to understand the chemical secrets of tea. This should help a lot to optimize the processes of agriculture, storage, preparation and consumption.

Key words: gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), metabolomics, tea

中图分类号:

O658

张磊, 曾仲大, 叶国注, 赵春霞, 路鑫, 许国旺. 基于气相色谱-质谱联用与液相色谱-质谱联用的非靶向代谢组学用于3类茶叶中化学成分分析[J]. 色谱, 2014, 32(8): 804-816.

ZHANG Lei, ZENG Zhongda, YE Guozhu, ZHAO Chunxia, LU Xin, XU Guowang. Non-targeted metabolomics study for the analysis of chemical compositions in three types of tea by using gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry[J]. Chinese Journal of Chromatography, 2014, 32(8): 804-816.

参考文献

[1] Higdon J V, Frei B. Crit Rev Food Sci Nutr, 2003, 43(1): 89
[2] Tu Y F, Yang X F, Zhang S K, et al. Chinese Journal of Chromatography, 2012, 30(2): 184
[3] Khan N, Mukhtar H. Life Sci, 2007, 81(7): 519
[4] Fraser K, Harrison S J, Lane G A, et al. Food Chem, 2012, 134(3): 1616
[5] Pierce A R, Graham H N, Glassner S, et al. Anal Chem, 1969, 41(2): 298
[6] Bedner M, Duewer D L. Anal Chem, 2011, 83(16): 6169
[7] Zeeb D J, Nelson B C, Albert K, et al. Anal Chem, 2000, 72(20): 5020
[8] Zhao Y, Chen P, Lin L, et al. Food Chem, 2011, 126(3): 1269
[9] Lee M J, Prabhu S, Meng X, et al. Anal Biochem, 2000, 279(2): 164
[10] Fiehn O. Plant Mol Biol, 2002, 48(1/2): 155
[11] Capanoglu E, Beekwilder J, Boyacioglu D, et al. J Agric Food Chem, 2008, 56(3): 964
[12] Griffiths W J, Koal T, Wang Y, et al. Angew Chem Int Ed, 2010, 49(32): 5426
[13] Goodacre R, Vaidyanathan S, Dunn W B, et al. Trends Biotechnol, 2004, 22(5): 245
[14] Ramautar R, Somsen G W, de Jong G J. Electrophoresis, 2013, 34(1): 86
[15] Zhou J, Wang S Y, Chang Y W, et al. Chinese Journal of Chromatography, 2012, 30(10): 1037
[16] Zhou H, Liang J, Lv D, et al. Food Chem, 2013, 138(4): 2390
[17] Sreekumar A, Poisson L M, Rajendiran T M, et al. Nature, 2009, 457(7): 910
[18] Le Gall G, Colquhoun I J, Defernez M. J Agric Food Chem, 2004, 52(4): 692
[19] Pongsuwan W, Fukusaki E, Bamba T, et al. J Agric Food Chem, 2007, 55(2): 231
[20] Xie G, Ye M, Wang Y, et al. J Agric Food Chem, 2009, 57(8): 3046
[21] Ku K M, Choi J N, Kim J, et al. J Agric Food Chem, 2009, 58(1): 418
[22] Lee J E, Lee B J, Chung J O, et al. J Agric Food Chem, 2010, 58(19): 10582
[23] Zhang L, Zeng Z, Zhao C, et al. J Chromatogr A, 2013, 1313: 245
[24] Smith C A, Want E J, OMaille G, et al. Anal Chem, 2006, 78(3): 779
[25] Arbona V, Iglesias D J, Talón M, et al. J Agric Food Chem, 2009, 57(16): 7338
[26] Fraga C G, Clowers B H, Moore R J, et al. Anal Chem, 2010, 82(10): 4165
[27] Wang L, Weller C L. Trends Food Sci Tech, 2006, 17(6): 300
[28] Ali S L. Chromatographia, 1975, 8(1): 33
[29] Weldegergis B T, Crouch A M, Górecki T, et al. Anal Chim Acta, 2011, 701(1): 98
[30] Zhu Z J, Schultz A W, Wang J, et al. Nat Protoc, 2013, 8(3): 451
[31] Price K R, Rhodes M J C, Barnes K A. J Agric Food Chem, 1998, 46(7): 2517
[32] Nishimura M, Ishiyama K, Watanabe A, et al. J Agric Food Chem, 2007, 55(18): 7252
[33] Chang Y, Zhao C, Wu Z, et al. Electrophoresis, 2012, 33(15): 2399
[34] Chen J, Wang W, Lv S, et al. Anal Chim Acta, 2009, 650(1): 3
[35] Scharbert S, Hofmann T. J Agric Food Chem, 2005, 53(13): 5377
[36] Wang K, Liu F, Liu Z, et al. Int J Food Sci Tech, 2011, 46(7): 1406
[37] Alcázar A, Ballesteros O, Jurado J M, et al. J Agric Food Chem, 2007, 55(15): 5960
[38] Zuo Y, Chen H, Deng Y. Talanta, 2002, 57(2): 307
[39] Lin J K, Lin C L, Liang Y C, et al. J Agric Food Chem, 1998, 46(9): 3635

基于气相色谱-质谱联用与液相色谱-质谱联用的非靶向代谢组学用于3类茶叶中化学成分分析

Non-targeted metabolomics study for the analysis of chemical compositions in three types of tea by using gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry

PDF

可视化

摘要/Abstract

引用本文

使用本文

扫码分享

参考文献

相关文章 15

编辑推荐

Metrics

[1]	赵原庆, 胡锴, 杨成, 韩鹏昭, 李立新, 刘晓冰, 张振强, 张书胜. 基于Ti₃C₂T_x/聚酰亚胺复合材料的分散固相萃取-液相色谱法测定尿液中儿茶酚胺类神经递质[J]. 色谱, 2023, 41(7): 572-581.
[2]	王亚婷, 杨阳, 孙秀兰, 纪剑. 基于气相色谱-质谱法的广泛靶向代谢组学方法开发[J]. 色谱, 2023, 41(6): 520-526.
[3]	吴瑛瑕, 牟燕, 刘佩珊, 张易天, 曾颖炫, 周枝凤. 气相色谱-质谱法测定大鼠肝脏中的39种脂肪酸[J]. 色谱, 2023, 41(5): 443-449.
[4]	陈佳, 刘玉龙, 徐斌, 刘勤, 谢剑炜. 顶空固相微萃取-气相色谱-质谱法快速筛查油性基质中化学武器公约相关化合物[J]. 色谱, 2023, 41(4): 348-358.
[5]	吴丽娟, 杨丽莉, 胡恩宇, 王美飞, 杨超, 尹明明. 气相色谱-质谱法测定土壤中14种苯胺类和联苯胺类化合物[J]. 色谱, 2023, 41(12): 1127-1134.
[6]	曲涛, 陈阳, 杨长军, 刘其耸, 陈惠, 何志勇, 王召君, 陈洁, 曾茂茂. 松花粉干预卵巢早衰大鼠肝脏的广泛靶向代谢组学分析[J]. 色谱, 2023, 41(1): 47-57.
[7]	谷艳, 臧鹏, 李进霞, 闫燕艳, 王佳. 基于超高效液相色谱-静电场轨道阱高分辨质谱的深静脉血栓模型大鼠血浆代谢组学分析[J]. 色谱, 2022, 40(8): 736-745.
[8]	张莹, 杨静, 马跃新, 曹玲, 黄青. 基于超高效液相色谱-质谱法的肽段分析中非特异性吸附评估及通用型最小化策略[J]. 色谱, 2022, 40(7): 616-624.
[9]	胡国绅, 王红, 余可垚, 沈伟健, 侯燕, 季美泉, 朱一鸣, 田雯, 李锡东. 气相色谱-负化学源质谱法测定船舶压载水中4种三卤甲烷[J]. 色谱, 2022, 40(6): 584-589.
[10]	马占君, 李振国, 王欢, 王仁军, 韩晓菲. 基于液相色谱-串联质谱的结肠癌血清氧固醇标志物筛选[J]. 色谱, 2022, 40(6): 541-546.
[11]	穆应花, 邢家溧, 沈坚, 应璐, 毛玲燕, 徐晓蓉, 娄永江, 吴希. QuEChERS-气相色谱-质谱法检测鱼肉中19种氯酚类化合物[J]. 色谱, 2022, 40(5): 477-487.
[12]	许芮菡, 谢倩文, 李旭军, 赵红丽, 刘学彬, 魏远隆, 邱爱东. 基于多壁碳纳米管改进QuEChERS法结合气相色谱-串联质谱检测茶叶中10种拟除虫菊酯类农药残留[J]. 色谱, 2022, 40(5): 469-476.
[13]	黄斯晨, 赵宏朋, 胡永丹, 任达兵, 易伦朝. 超高效液相色谱-高分辨质谱联用结合整合过滤策略全面分析茶树花中化学成分[J]. 色谱, 2022, 40(3): 242-252.
[14]	何嘉雯, 温家欣, 刘亚雄, 胡佳哲, 曹雅静, 赖宇红. 超高效液相色谱-静电场轨道阱高分辨质谱快速筛查和确证凉茶中167种非法添加药物[J]. 色谱, 2022, 40(3): 253-265.
[15]	王雪婷, 李静静, 姜珊, 沈伟健, 王毅谦, 顾强. 酸性酯交换-气相色谱-质谱法同时测定植物油中氯丙二醇酯和缩水甘油酯[J]. 色谱, 2022, 40(2): 198-205.