Comprehensive Lipidome-Wide Profiling Reveals Dynamic Changes

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Comprehensive lipidome-wide profiling reveals dynamic changes of tea lipids during manufacturing process of black tea Jia Li, Jinjie Hua, Qinghua Zhou, Chunwang Dong, Jinjin Wang, Yuliang Deng, Haibo Yuan, and Yongwen Jiang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b03875 • Publication Date (Web): 23 Oct 2017 Downloaded from http://pubs.acs.org on October 24, 2017

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Journal of Agricultural and Food Chemistry

Comprehensive lipidome-wide profiling reveals dynamic changes of tea lipids during manufacturing process of black tea

Jia Lia, Jinjie Huaa, Qinghua Zhoub, Chunwang Donga, Jinjin Wanga, Yuliang Denga, Haibo Yuana*, Yongwen Jianga*

a

Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture,

Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China b

College of Environment, Zhejiang University of Technology, Hangzhou 310014,

China

* Correspondence should be addressed to: Prof. Yongwen Jiang, Email: [email protected] Prof. Haibo Yuan, Email: [email protected]

1

ACS Paragon Plus Environment


1

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Abstract

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As important biomolecules in Camellia sinensis L., lipids undergo substantial

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changes during black tea manufacture, which is considered to contribute to tea

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sensory quality. However, limited by analytical capacity, detailed lipid composition

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and its dynamic changes during black tea manufacture, remain unclear. Herein, we

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performed tea lipidome profiling using high resolution liquid chromatography

7

coupled to mass spectrometry (LC-MS), which allows simultaneous and robust

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analysis of 192 individual lipid species in black tea, covering 17 (sub)classes.

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Furthermore, dynamic changes of tea lipids during black tea manufacture were

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investigated. Significant alterations of lipid pattern were revealed, involved with

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chlorophylls degradation, metabolic pathways of glycoglycerolipids and other

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extraplastidial membrane lipids. To our knowledge, this report presented most

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comprehensive coverage of lipid species in black tea. This study provides a global and

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in-depth metabolic map of tea lipidome during black tea manufacture.

15 16

Keywords: black tea, manufacturing process, lipid profiling, dynamic changes, LC-

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MS

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Introduction

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Tea is most widely consumed flavored beverage all over the world1, which is

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prepared from fresh leaves of Camellia sinensis L. by complicated plucking and

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manufacturing process. Among all tea types, black tea is most prevalent due to its

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pleasant sensory quality (aroma, taste, color) and beneficial health effect2-3,

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accounting for approximately 78% of global tea consumption4. The post-harvest

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procedure of orthodox black tea manufacture includes delicate steps of withering,

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rolling, fermentation and drying. Massive evidence has shown that substantial

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changes take place during the manufacturing process of black tea in aspect of its non-

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volatile and volatile compounds, which setup important basis for the development of

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unique sensory quality of black tea1, 5. Tea flavanols (catechins) and their oxidation

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products, e.g. theaflavins, thearubigins, as well as flavonol glycosides, amino acids

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and alkaloids have been extensively studied6-8. However, previous studies mainly

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focus on water-soluble components, the knowledge of hydrophobic components in

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black tea is still limited.

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Lipids, broadly defined as hydrophobic biomolecules9, are essential constitutes in

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plants. Increasing studies have revealed versatile roles of lipid in plants including

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membrane structural scaffold, energy storage unit and vital player in various

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biological processes, such as signaling and photosynthesis10-11. Interestingly, lipids are

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as well reported to be implicated in sensory quality of black tea. Hydrophobic

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chlorophylls are major pigments of fresh tea leaves, whose metabolic products

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generated during manufacturing contribute to the unique color of black tea1. Volatiles

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of aliphatic alcohols, aldehydes and lactones responsible for the “fresh” odor of tea

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aroma, are fatty acid derivatives generated from lipid oxidation5,

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degradation also produces fragrant volatiles such as methyl jasmonate, cis-jasmone,

12-13

. Lipid

3



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which contribute to sweet and floral odor of black tea5, 13-14. These odor compounds

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are mainly generated during tea manufacturing process. It is essential, therefore, to

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reveal the detailed lipid composition of black tea and its dynamic alterations and

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transformations during manufacturing process.

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Several studies have been reported of tea lipids in this context. Ravichandran et al.

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and Bhuyan et al. investigated neutral lipids, glycolipids, phospholipids and their fatty

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acid (FA) compositions in different manufacture stages of black tea, by applying

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column fractionation followed by gas chromatography-FID analysis15-16. Considerable

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variation of FA composition was reported during black tea manufacture and

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glycolipids were found to be most pronouncedly degraded15-16. Difference in lipid

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degradation was identified as possible reason of superior aroma of orthodox over CTC

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black tea16. However, limited by sensitivity and specificity of employed methods,

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previous studies were performed on the scale of lipid category and only covered a few

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number of lipid classes, which hampers broader and in-depth insights into tea lipids

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and their metabolic fates during manufacture, and moreover, their role in tea sensory

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characteristics.

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Lipidome profiling or lipidomics, is an emerging analytical strategy that enables

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qualitative and quantitative analysis of a wide range of lipids on the scale of

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individual lipid molecular species, thus providing a global map of “lipidome” and its

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metabolism17-19. The promising perspectives of lipidomics tool in plant field has been

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highlighted in recent years by increasing applications in model plant Arabidopsis and

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crops such as rice and tobacco20-24. However, to our knowledge, by far there is no

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study reported for an improved characterization of tea lipids and its “metabolism”

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during manufacturing process. In this study, we performed comprehensive tea lipid

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profiling by using ultra-performance liquid chromatography coupled to mass 4


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spectrometry (UPLC-MS), which allows simultaneous analysis of 192 individual lipid

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species in black tea. Furthermore, in combination with uni-/multi-multivariate

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statistics, this approach has been applied in investigation of dynamic changes of tea

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lipids and elucidation of altered metabolic pathways during black tea manufacture.

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Materials and Methods

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Chemicals and Regents

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Acetonitrile, isopropanol and methanol of liquid chromatography or mass

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spectrometry grade were purchased from Merck (Darnstadt, Germany). Ammonium

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acetate and methyl tert-butyl ether (MTBE) were purchased from Sigma-Aldrich (St.

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Louis, MO, USA).

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Sample Preparation

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Fresh tea leaves (one bud with one or two leaves) of Chinese tea variety C.

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sinensis cv. Chuyeqi were harvested in August from Gaoqiao tea garden, Tea Research

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Institute of Hunan Province, Changsha, China. Tea leaves were withered for 20 hours

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until the moisture content of tea leaves was decreased to around 62%-64% (wet basis,

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w.b.). Withering temperature, light intensity and relative humidity were set to be

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28°C, 6000 lx and 70%, respectively. Next, tea leaves were subjected to rolling using

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a roller (6CR-25, Shangyang Machinery Co. Ltd., China), followed by fermentation

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for four hours with temperature and relative humidity of 30°C and 95%, respectively.

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Both withering and fermentation steps were carried out using an artificial climate

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chamber (PRX-450D, Saifu Experiment Instrument Co. Ltd., China). Afterwards,

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tea leaves were dried using a hot air drier (JY-6CHZ-7B, Jiayou Machinery Co.

92

Ltd., China) until about 5% of moisture content was reached. The experiment was

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carried out in triplicates (each 6 kg of fresh leaves). Tea samples for analysis were 5



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collected after harvest (fresh leaves), at withering time of 4h, 8h, 12h, 16h, 20h, after

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rolling, at fermentation time of 1h, 2h, 3h, 4h and after drying. In total, 36 tea samples

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were collected. All samples were freeze-dried and stored in -80°C before analysis.

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Tea Lipid Extraction

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Tea lipids were extracted according to the previous report with minor

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modifications25. Briefly, 300 µL methanol, followed by 1 mL MTBE, was added to 20

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mg grounded tea powder. After one-hour vortex, 300 µL ultrapure water was added to

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produce two phases. The upper phase, i.e., MTBE phase, where hydrophobic

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metabolites were retained, was collected after centrifugation and freeze-dried. Each

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tea sample was extracted in two replicates. Tea lipid extracts were stored in -80°C for

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analysis.

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LC-MS Analysis

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LC-MS based tea lipid profiling was performed by an ultra-performance liquid

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chromatography coupled to an electrospray ionization-quadrupole time-of-flight mass

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spectrometer system (UPLC-ESI-q-TOF, Xevo G2-S, Waters), adopted from previous

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method26. Briefly, tea lipid extracts were separated using an ACQUITY UPLC HSS

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T3 column (2.1×100 mm, 1.8 µm, Waters). Gradient elution was started with 32%

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solvent B (isopropanol: acetonitrile = 9:1, 10 mM ammonium acetate) and 68%

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solvent A (acetonitrile: water = 6:4, 10 mM ammonium acetate), which was

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maintained for 2 min, followed by linear increase to 60% B in next 2 min. Solvent B

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was further linearly increased to 97% during next 9 min and maintained for 4 min.

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Subsequently solvent B was decreased to 32% in 0.1 min and equilibrated for 2.9 min

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for next injection. Total run time was 20 min. Data was acquired in ESI positive mode

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with scan mass range of 200-1200. ESI settings of capillary voltage, source

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temperature and desolvation temperature were 3 kV, 120°C and 450°C, respectively. 6


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Cone gas flow and desolvation gas flow were set to be 50 L/min and 800 L/min,

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respectively. Online mass calibration was performed throughout the analysis by

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applying lockspray using reference compound leucine-encephalin with m/z of

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556.2771. High resolution data-dependent MS/MS was performed by HCD with

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collisional energy of 30 ev in ESI(+) using UPLC-quadrupole Orbitrap mass

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spectrometer (Q Exactive, Thermo). Quality control (QC) samples were prepared

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from pooled sample and analyzed every 8 injections during the whole run.

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Data Processing and Statistics

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Acquired LC-MS data was processed using software TransOmics Informatics for

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Metabolomics and Lipidomics (Waters) for feature extraction and time alignment. A

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signal-to-noise ratio of 3 was set as sensitivity level for feature extraction. A peak list

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was generated including retention time (RT), m/z and peak intensity of detected ions.

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Relative intensity was calculated by normalization to total intensity of all ions in each

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sample. It is noteworthy that normalized intensity is relative abundance, not actual

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abundance of lipids. Missing values were removed by applying 80% rule27. Lipid ions

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with relative standard deviation (RSD) less than 30% in all QCs were retained for

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further analysis. Principal component analysis (PCA) and partial least square-

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discriminate analysis (PLS-DA) were performed by SIMCA-P 11.5 (Umetrics AB,

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Umeå, Sweden) with pareto scaling28. Heatmap visualization was conducted by using

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open source tool MultiExperiment Viewer (version 4.9.0)29. Statistical significance

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was determined by one-way ANOVA with adjusted bonferroni correction for false

140

discovery rate (FDR).

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Lipid Nomenclature

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Lipid annotation throughout this manuscript follows the lipid nomenclature

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system proposed by LIPID MAPS9. Sphingolipid species are denoted by long-chain 7



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base and fatty amide. t18:0, hydroxysphinganine (phytosphingosine); t18:1,

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hydroxysphingosine; d18:2, sphingadienine; h in fatty amide indicates hydroxyl.

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Phosphoglycerolipids and acylglycerolipids are denoted by summed carbon number:

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total double bond of all fatty chains. Glycoglycerolipids are denoted by two fatty acyl

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groups (not indicative of stereospecificity).

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Results and Discussion

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Comprehensive profiling of tea lipidome using UPLC-Q-TOF

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The potential complexity and diversity of lipids in fresh tea leaves and in tea

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product after manufacturing process, requires a potent tea lipid profiling method with

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a broad coverage of lipid classes/species, as well as high structural specificity. To this

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end, we developed an UPLC-Q-TOF based approach for wide-scale profiling of tea

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lipids. An efficient chromatographic separation of tea lipids was achieved in 15

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minutes by gradient elution (Figure 1). Polar lyso-phosphoglycerolipids elute earlier

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in about RT of 2.3-4.3 min, whereas neutral lipids including sterol lipids and

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triacylglycerols elute later in around RT of 9.3-13.6 min. Membrane lipids including

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phospho-/glyco-glycerolipids, sphingolipids, and other lipids elute in the RT range of

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5.3-10.8 min. A total of more than 1000 ion features were profiled in non-targeted

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pattern, spanning approximately 5 orders of magnitude in their peak intensities.

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To ensure the reliability and robustness of tea lipid profiling procedure, QC

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samples (n=11) and extraction replicates (n=2) were carefully evaluated (Figure 2).

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Figure 2A shows the distribution of coefficient of variation (CV) of all detected ion

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features in 11 QC samples. Lipid ions with CVs lower than 10% accounted for about

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70% of overall abundance, and this number increased to about 90% for lipid ions with

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CVs lower than 20%. Furthermore, parallel tea lipid extractions also demonstrated 8


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high precision, as reflected by high coefficient of R2=0.99 for two extraction

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replicates (Figure 2B). This result is satisfying for complex plant tissue samples.

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Identification of lipid species in black tea

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To unravel the lipid composition in black tea, pooled tea sample prepared from

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each manufacturing stage was used for lipid identity assignment, aimed to cover not

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only naturally-occurring lipids in fresh tea leaves but also lipid metabolites produced

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during manufacturing process. To constrain false-positive assignments, three aspects

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were concerned to minimize possible error-prone interference from isobaric or

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isoelemental compounds. Firstly, accurate mass measurement (

Comprehensive Lipidome-Wide Profiling Reveals Dynamic Changes

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