Metabolite Profiling of 14 Wuyi Rock Tea Cultivars Using UPLC-QTOF MS and UPLC-QqQ MS Combined with Chemometrics

Chen, Si; Li, Meihong; Zheng, Gongyu; Wang, Tingting; Lin, Jun; Wang, Shanshan; Wang, Xiaoxia; Chao, Qianlin; Cao, Shixian; Yang, Zhenbiao; Yu, Xiaomin

doi:10.3390/molecules23020104

Cited by 86 publications

(87 citation statements)

References 52 publications

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“…In total, nine samples (three biological replicates per treatment group) were analyzed by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS) based metabolomic approach. Tea samples were extracted with 70% (v/v) methanol following our previously published protocol (Chen et al, 2018). One microliter of the metabolite extract was injected into an Acquity UPLC system coupled to a SYNAPT G2-Si HDMS QTOF mass spectrometer (Waters, Milford, MA, USA) and separated with an Acquity UPLC HSS T3 column (2.1×100 mm, 1.8 µm).…”

Section: Uplc-qtof Ms Based Metabolomic Analysismentioning

confidence: 99%

“…One microliter of the metabolite extract was injected into an Acquity UPLC system coupled to a SYNAPT G2-Si HDMS QTOF mass spectrometer (Waters, Milford, MA, USA) and separated with an Acquity UPLC HSS T3 column (2.1×100 mm, 1.8 µm). The instrument setup was the same as previously described (Chen et al, 2018). Progenesis QI software (ver 2.1, Nonlinear Dynamics, Newcastle upon Tyne, UK) with default settings was used for data preprocessing.…”

Section: Uplc-qtof Ms Based Metabolomic Analysismentioning

confidence: 99%

“…To detect amino acids, 25-fold diluted tea extracts was separated on a Merck SeQuant ZIC-HILIC column (2.1 × 100 mm, 5 µm). Chromatographic conditions and the equipment setup were described in our previous study (Chen et al, 2018). Contents of catechins, caffeine and amino acids in tea samples were calculated by comparison of their peak areas with those of standards in the calibration curve.…”

Section: Quantifications Of Catechins Caffeine and Amino Acidsmentioning

confidence: 99%

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Defensive Responses of Tea Plants (Camellia sinensis) Against Tea Green Leafhopper Attack: A Multi-Omics Study

et al. 2020

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Tea green leafhopper [Empoasca (Matsumurasca) onukii Matsuda] is one of the most devastating pests of tea plants (Camellia sinensis), greatly impacting tea yield and quality. A thorough understanding of the interactions between the tea green leafhopper and the tea plant would facilitate a better pest management. To gain more insights into the molecular and biochemical mechanisms behind their interactions, a combined analysis of the global transcriptome and metabolome reconfiguration of the tea plant challenged with tea green leafhoppers was performed for the first time, complemented with phytohormone analysis. Non-targeted metabolomics analysis by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS), together with quantifications by ultra-performance liquid chromatography triple quadrupole mass spectrometry (UPLC-QqQ MS), revealed a marked accumulation of various flavonoid compounds and glycosidically bound volatiles but a great reduction in the level of amino acids and glutathione upon leaf herbivory. RNA-Seq data analysis showed a clear modulation of processes related to plant defense. Genes pertaining to the biosynthesis of phenylpropanoids and flavonoids, plant-pathogen interactions, and the biosynthesis of cuticle wax were significantly up-regulated. In particular, the transcript level for a CER1 homolog involved in cuticular wax alkane formation was most drastically elevated and an increase in C29 alkane levels in tea leaf waxes was observed. The tea green leafhopper attack triggered a significant increase in salicylic acid (SA) and a minor increase in jasmonic acid (JA) in infested tea leaves. Moreover, transcription factors (TFs) constitute a large portion of differentially expressed genes, with several TFs families likely involved in SA and JA signaling being significantly induced by tea green leafhopper feeding. This study presents a valuable resource for uncovering insect-induced genes and metabolites, which can potentially be used to enhance insect resistance in tea plants.

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Section: Uplc-qtof Ms Based Metabolomic Analysismentioning

confidence: 99%

Section: Uplc-qtof Ms Based Metabolomic Analysismentioning

confidence: 99%

Section: Quantifications Of Catechins Caffeine and Amino Acidsmentioning

confidence: 99%

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Defensive Responses of Tea Plants (Camellia sinensis) Against Tea Green Leafhopper Attack: A Multi-Omics Study

et al. 2020

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“…() reported no significant decline of flavonol glycosides in the semi‐fermentation process of oolong tea whereas ~20% of total flavonol glycosides degraded in the subsequent drying process. What is more, flavonol glycosides are considered as a group of promising biomarkers for discriminating the origins or cultivars of teas (Engelhardt et al ., ; Chen et al ., ; Zheng et al ., ), due to their relatively higher stabilities compared to catechins (Zheng et al ., ). These controversial results were attributed to the lack of cultivar control and manufacturing process tracking.…”

Section: Introductionmentioning

confidence: 99%

Dynamic changes in flavonol glycosides during production of green, yellow, white, oolong and black teas from Camellia sinensis L. (cv. Fudingdabaicha)

Fang

Song

et al. 2018

Int J of Food Sci Tech

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Summary Flavonol glycosides with low thresholds are important flavour substances in tea leaves. This study monitored the dynamic changes in flavonol glycosides during the production of different teas. The fresh leaves of cv. Fudingdabaicha with 15.77 mg g−1 of total flavonol glycosides (TFG) were respectively processed into green, yellow, white, oolong and black teas. A reduction of TFG was observed for different teas, amongst which black tea contained the lowest level of TFG (9.83 mg g−1), followed by oolong tea (11.96 mg g−1), while green, yellow and white teas contained similar levels of TFG (~13.70 mg g−1). Fixation was crucial to maintain the stability of flavonol glycosides due to its inactivation effect on enzymes at high temperature. Principal component analysis results indicated that flavonol glycosides were vulnerable to fermentation, and the stabilities of flavonol glycosides were related with aglycone and glycoside moiety.

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“…Nontargeted metabolomics involves the simultaneous detection of a huge range of endogenous metabolites and provides an unbiased and global metabolite profile for living organisms. Recently, nontargeted metabolomics was applied in C. sinensis in both ESI positive and ESI negative ion modes to detect more compounds using GC‐MS or LC‐MS (Chen et al., ; Fraser et al., ; Liu et al., ; Xin et al., ; Yue et al., ). Li et al.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Young Shoots of ‘Anji Baicha’ (Camellia sinensis) at Three Developmental Stages Using Nontargeted LC‐MS‐Based Metabolomics

Zeng

Lin

Liu

et al. 2019

Journal of Food Science

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‘Anji Baicha’ (Camellia sinensis) is a low‐temperature‐sensitive tea variety. During the development of young shoots, the leaves of ‘Anji Baicha’ exhibit periodic albinism. The quality of ‘Anji Baicha’ is closely related to the color of the fresh leaves, with whiter leaves affording a higher amino acid content and superior sensory quality after processing. However, the metabolic mechanism of its quality formation is still unclear. In this study, we analyzed the metabolomic changes of young shoots of ‘Anji Baicha’ and screened for metabolic markers that may be involved in the periodic albinism. Positive‐ and negative‐mode UPLC‐QTOF‐MS was applied to the metabolomic analysis of young leaves of ‘Anji Baicha’ during three developmental stages (i.e., the pre‐albescent, albescent, and regreening stages). The results revealed significant differences in the metabolic profiles of the young leaves at the three stages. The differential metabolites were mainly related to the pathways of flavonoid, phenylpropanoid, and amino acid biosynthesis. The concentrations of several amino acids (primarily l‐theanine, l‐glutamate, N2‐acetyl‐l‐ornithine, l‐aspartic acid, d‐proline, l‐glutamine, l‐leucine, and pyroglutamic acid) and 12‐OPDA were significantly higher in the albescent stage. In contrast, during the albescent stages, the concentrations of several carbohydrates (d‐fructose, β‐d‐galactopyranose, 3‐O‐fucopyranosyl‐2‐acetamido‐2‐deoxyglucopyranose, galactose‐β‐1, 4‐xylose acetyl‐maltose, and 2‐fucosyllactose) were significantly lower. Moreover, catechins (mainly epigallocatechin and catechin derivatives), dimeric catechins (primarily proanthocyanidins), and flavonol and flavonol/flavone glycosides (mainly kaempferol, myricetin, quercetin, cyanidin, and delphinidin glycosides) were detected at the highest levels in the regreening or pre‐albescent stages. The obtained results enhance the current understanding of the metabolic mechanisms of periodic albinism and quality development formation in ‘Anji Baicha’. Practical Application The obtained results not only provide information regarding differential metabolites but also advance the understanding of the mechanism of periodic albinism in ‘Anji Baicha’ at the metabolite level and open up new possibilities for the genetic improvement of tea cultivars.

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Metabolite Profiling of 14 Wuyi Rock Tea Cultivars Using UPLC-QTOF MS and UPLC-QqQ MS Combined with Chemometrics

Cited by 86 publications

References 52 publications

Defensive Responses of Tea Plants (Camellia sinensis) Against Tea Green Leafhopper Attack: A Multi-Omics Study

Defensive Responses of Tea Plants (Camellia sinensis) Against Tea Green Leafhopper Attack: A Multi-Omics Study

Dynamic changes in flavonol glycosides during production of green, yellow, white, oolong and black teas from Camellia sinensis L. (cv. Fudingdabaicha)

Analysis of Young Shoots of ‘Anji Baicha’ (Camellia sinensis) at Three Developmental Stages Using Nontargeted LC‐MS‐Based Metabolomics

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