基于亲水相互作用液相色谱-三重四极杆质谱法研究白茶萎凋过程中代谢物的变化

doi:10.13305/j.cnki.jts.2020.02.010

摘要/Abstract

摘要： 采用亲水相互作用液相色谱-三重四极杆质谱法,对白茶鲜叶(F)和室内萎凋处理29 h(W)、53 h(P)的2个萎凋样进行了代谢物靶向检测,Quality control(QC)样本中共检测到111个代谢物,主要包括47种氨基酸及其衍生物、29种核酸类代谢物、12种维生素和辅酶、17种糖代谢物和6种甘油磷脂代谢物。与鲜叶F相比,萎凋叶W和P中显著增加的代谢物分别有39种和41种,其中共有代谢物35种;显著降低的代谢物分别有9种和11种,其中共有代谢物8种。显著变化代谢物分析结果表明,萎凋叶的细胞膜受损、DNA和RNA降解、氨基酸衍生物显著增加、糖代谢异常。根据代谢物含量的变化幅度和组成特异性,筛选了表征萎凋叶细胞膜生理状态和核酸、糖代谢的标志代谢物。此外,针对代谢物中氨基酸和核苷酸的组成特点,提出了研究氨基酸衍生物滋味特性的必要性和应用代谢谱分析建立萎凋工艺适度标准的可能性。

关键词: 白茶, 萎凋, 靶向代谢谱

Abstract: In this study, the metabolic profiles of fresh leaves (F), two indoor withered samples for 29 h (W) and 53 h (P) respectively were investigated by HILIC-QqQ MS based targeted metabolomics. Totally 111 metabolites were detected in the QC sample, including 47 amino acids and their derivatives, 29 nucleic acid metabolites, 12 vitamins and coenzymes, 17 sugar metabolites and 6 glycerophospholipid metabolites. Compared with the fresh leaves (F), 39 and 41 metabolites were significantly increased in withered samples W and P, with 35 overlapped metabolites. On the other hand, 9 and 11 metabolites were dramatically reduced, with 8 overlapped metabolites. The metabolite changes suggested that the cell membranes were damaged, DNA and RNA were degraded, amino acids derivatives were significantly increased and glucose metabolism was abnormal. Furthermore, according to the variations of metabolite contents and compositions, the marker metabolites of the withered leaves were identified which could reflect the physiological states of cell membrane, nucleic acid and glucose metabolism. Eventually, based on the characteristic changes in amino acids and nucleotides, the necessities of characterizing the flavor properties of amino acids and their derivatives as well as exploring the possibility of using metabolic profiling as white tea withering standards were proposed.

Key words: white tea, withering, targeted metabolic profiling

中图分类号:

陈翔, 田月月, 张丽霞. 基于亲水相互作用液相色谱-三重四极杆质谱法研究白茶萎凋过程中代谢物的变化[J]. 茶叶科学, 2020, 40(2): 238-249. doi: 10.13305/j.cnki.jts.2020.02.010.

CHEN Xiang, TIAN Yueyue, ZHANG Lixia. The Changes of Metabolites during the Withering Process of White Tea Based on HILIC LC-QqQ MS Method[J]. Journal of Tea Science, 2020, 40(2): 238-249. doi: 10.13305/j.cnki.jts.2020.02.010.

参考文献

[1] 施兆鹏, 黄建安. 茶叶审评与检验[M]. 4版. 北京: 中国农业出版社, 2010.
Shi Z P, Huang J A.Tea evaluation and inspection [M]. 4th ed, Beijing: China Agricultural Press, 2010.
[2] 顾谦, 陆锦时, 叶宝存. 茶叶化学[M]. 北京: 中国科学技术出版社, 2002.
Gu Q, Lu J S, Ye B C.Tea chemistry [M]. Beijing: Science and Technology of China Press, 2002.
[3] 杨伟丽, 肖文军, 邓克尼. 加工工艺对不同茶类主要生化成分的影响[J]. 湖南农业大学学报(自然科学版), 2001, 27(5): 384-386.
Yang W L, Xiao W J, Deng N K.Effects of processing technology of different teas on the main biochemistry components[J]. Journal of Hunan Agricultural University, 2001, 27(5): 384-386.
[4] Fiehn O, Kopka J, Trethewey R N, et al.Identification of uncommon plant metabolites based on calculation of elemental compositions using gas chromatography and quadrupole mass spectrometry[J]. Analytical Chemistry, 2000, 72(15): 3573-3580.
[5] 王凯. 基于稳定性同位素¹⁵N示踪和代谢谱分析技术的茶叶氮代谢研究[D]. 合肥: 安徽农业大学, 2012.
Wang K.¹⁵N stable isotope tracer-based spectral analysis techniques and metabolism of nitrogen metabolism of tea plant [D]. Hefei: Anhui Agricultural University, 2012.
[6] 张磊, 曾仲大, 叶国注, 等. 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 L,Zeng Z D, Ye G Z, et al.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.
[7] Zhang L, Ning L, Yan Y C, et al.Development of the fingerprints of crude Pu-erh tea and ripened Pu-erh tea by high performance liquid chromatography[J]. Journal of Chinese Pharmaceutical Sciences, 2011(20): 352-359.
[8] 李万春. 气质联用在不同茶叶品质鉴定中的应用[D]. 南京: 南京理工大学, 2012.
Li W C.Application of GC-MS in different tea quality identification [D]. Nanjing: Nanjing University of Science and Technology, 2012.
[9] Van d H J J J, Akermi M, Ünlü F Y, et al. Structural annotation and elucidation of conjugated phenolic compounds in black, green, and white tea extracts[J]. Journal of Agricultural and Food Chemistry, 2012, 60(36): 8841-8850.
[10] 王秀梅. 祁门红茶加工过程中代谢谱分析及其品质形成机理研究[D]. 合肥: 安徽农业大学, 2012.
Wang X M.Analysis of metabolism profile and its quality formation mechanism in the process of keemun black tea [D]. Hefei: Anhui Agricultural University, 2012.
[11] Lee J E, Lee B J, Chung J O, et al.¹H NMR-based metabolomic characterization during green tea(Camellia sinensis) fermentation[J]. Food Research International, 2011(44): 597-604.
[12] Tan J, Dai W, Lu M, et al.Study of the dynamic changes in the non-volatile chemical constituents of black tea during fermentation processing by a non-targeted metabolomics approach[J]. Food Research International, 2016, 79: 106-113.
[13] Dai W, Qi D, Yang T, et al.Non-targeted analysis using ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry uncovers the effects of harvest season on the metabolites and taste quality in tea (Camellia sinensis L.)[J]. Journal of Agricultural & Food Chemistry, 2015, 63(44): 9869-9878.
[14] 汤莎莎, 芦晨阳, 周君, 等. 基于电子鼻和HS-SPME-GC-MS技术解析乌牛早茶的挥发性风味物质[J]. 食品工业科技, 2018, 39(14): 223-230.
Tang S S, Lu C Y, Zhou J, et al.Volatile flavor compounds of different Wu Niuzao leaves and different heating temperatures based on electronic nose and GC-MS[J]. Science and Technology of Food Industry. 2018, 39(14): 223-230.
[15] Pongsuwan W, Bamba T, Yonetani T, et al.Quality prediction of Japanese green tea using pyrolyzer coupled GC/MS based metabolic fingerprinting[J]. J Agric Food Chem, 2008, 56(3): 744-750.
[16] 戴宇樵, 吕才有. 代谢组学技术在茶学中的应用研究进展[J]. 江苏农业科学, 2019, 47(2): 24-28.
Dai Y Q, Lv C Y.Research progress of application of metabolomics technology in tea science[J]. Jiangsu Agricultural Sciences, 2019, 47(2): 24-28.
[17] Dai W D, Xie D C, Lu M L, et al.Characterization of white tea metabolome: Comparison against green and black tea by a nontargeted metabolomics approach[J]. Food Research International, 2017, 96: 40-45.
[18] Cai Y P, Weng K, Guo Y, et al.An integrated targeted metabolomic platform for high-throughput metabolite profiling and automated data processing[J]. Metabolomics, 2015, 11(6): 1575-1586.
[19] 崔桂友. 呈味核苷酸及其在食品调味中的应用[J]. 中国调味品, 2001, 16(10): 25-29.
Cui G Y.Favor nucleotides and its application in food seasoning[J]. Chinese Condiment, 2001, 16(10): 25-29.
[20] 沈浥. 调味品中呈味核苷酸的研究进展和我国标准化现状[J]. 中国调味品, 2017, 42(1): 177-180.
Shen Y.Research progress of the flavor nucleotides in condiments and standardization status in China[J]. China Condiment, 2017, 42(1): 177-180.