Caffeine Content and Related Gene Expression: Novel Insight into

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Caffeine content and related gene expression: novel insight into caffeine metabolism in Camellia plants containing low, normal and high caffeine concentrations Biying Zhu, Lin-Bo Chen, Mengqian Lu, Jing Zhang, Jieyun Han, Wei-Wei Deng, and Zheng-Zhu Zhang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.9b00240 • Publication Date (Web): 04 Mar 2019 Downloaded from http://pubs.acs.org on March 5, 2019

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Journal of Agricultural and Food Chemistry

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Caffeine content and related gene expression: novel insight into caffeine

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metabolism in Camellia plants containing low, normal and high caffeine

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concentrations

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Biying Zhu#1, Lin-Bo Chen#2, Mengqian Lu1, Jing Zhang1, Jieyun Han1, Wei-Wei

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Deng1*, Zheng-Zhu Zhang1*

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1State

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Science & Technology, Anhui Agricultural University, Hefei, Anhui 230036, China

Key Laboratory of Tea Plant Biology and Utilization, School of Tea and Food

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2Tea

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Yunnan 666201, China

Research Institute, Yunnan Academy of Agricultural Sciences, Menghai,

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# These

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*Corresponding

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Zhang ([email protected]) ; Tel/fax: +86 551 65785471

authors (Biying Zhu and Lin-Bo Chen) contribute equally. author: Wei-Wei Deng ([email protected]), Zheng-Zhu

16 17 18 19 20 21 22 23

ACS Paragon Plus Environment


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Abstract

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Caffeine is a crucial secondary metabolic product in tea plants. Although the

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presence of caffeine in tea plants has been identified, the molecular mechanisms

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regulating relevant caffeine metabolism remain unclear. To elucidate the caffeine

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biosynthesis and catabolism in Camellia plants, fresh, germinated leaves from four

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Camellia plants with low (2), normal (1) and high (1) caffeine concentrations, namely

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low-caffeine tea 1 (LCT1, Camellia crassicolumna), low-caffeine tea 2 (LCT2, C.

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crassicolumna), Shuchazao (SCZ, C. sinensis) and Yunkang 43 (YK43, C. sinensis)

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were used in this research. Transcriptome and purine alkaloids analyses of these

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Camellia leaves were performed using RNA-Seq and liquid chromatography–mass

34

spectrometry (LC-MS). Moreover,

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the metabolic fate of caffeine in leaves of these plants. Caffeine content was

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correlated with related genes expression levels, and a quantitative real-time (qRT)

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PCR analysis of specific genes showed a consistent tendency with the obtained

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transcriptomic analysis. Based on the results of stable isotope-labelled tracer

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experiments, we discovered a degradation pathway of caffeine to theobromine. These

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findings could assist researchers in understanding the caffeine-related mechanisms in

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Camellia plants containing low, normal, and high caffeine content and be applied to

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caffeine regulation and breeding improvement in future research.

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Keywords: Camellia plants, caffeine metabolism, catechins, differentially expressed

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genes, RNA-Seq, theanine

15N-caffeine

tracing was performed to determine

45


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Introduction

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The tea plant (Camellia sinensis) is one of evergreen perennial plants with a

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lifespan of more than 100 years. Tea, as the second most popular (after water) natural

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nonalcoholic beverage, is processed from the leaves of tea plants.1 Numerous studies

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have suggested that tea can prevent cancer and other neurodegenerative or

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cardiovascular diseases.2-4 However, due to its high caffeine content, high tea intake

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can affect those sensitive to caffeine by increasing their anxiety, blood pressure,

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insomnia, etc.5-6

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Caffeine, 1,3,7-trimethylxanthine, is found in tea, mate, cocoa, coffee and some

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other plant species.7 These purine alkaloids are accumulated in young leaves,

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cotyledons, seeds and fruits. In tea leaves, these alkaloids typically contain 2%–5%

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(w/w) caffeine. The typical biosynthetic pathways of caffeine are: xanthosine (XR) →

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7-methyxanthosine (7mXR) → 7-methylxanthine (7mX) → theobromine (Tb) →

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caffeine (Cf) as the major pathway; 7-methylxanthine (7mX) → paraxanthine (Px)

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→ caffeine (Cf) as a minor route in leaves of tea plants.8 N-methyltransferases (NMTs)

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were reported to catalyze the methylation steps (the 1st, 3rd and 4th steps) in the

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major

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S-adenosyl-L-methionine (SAM).9 Among them, caffeine synthase (CS) has ability to

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catalyze the final two steps (7-methylxanthine → theobromine → caffeine) and shows

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a bifunction of two NMTs.10 The paraxanthine NMT (catalyzing the steps of

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paraxanthine → caffeine) was reported to be existed in tea chloroplasts.

67

activity of caffeine biosynthesis has been investigated in the petals and stamens

caffeine

biosynthetic

pathway

with


the

methyl

donor

11

of

A high


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(before flowering) of tea plants.12 A tea CS gene that encodes CS (TCS1; GenBank

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accession no. AB031280), cloned from young leaves of tea plant (Camellia sinensis),

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was reported by Kato et al.13 An analysis of the expression patterns of TCS1 (encoded

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TCS) in the different organs of tea seedlings revealed that the highest expression was

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found in young leaves. The biosynthesis of caffeine might be closely related with the

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expression levels of TCS1.14 The association analysis on the concentrations of

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caffeine and the expressions of TCS1 was elucidated in tea and other related species.15

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It was reported that there were six types in the alleles of TCS1, TCS1a~f. Among

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them, TCS1a showed as the predominant position of allele; TCS1b-f appeared as the

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rare alleles which only existed in some wild species.16 Hongyacha, as a kind of wild

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tea species, was reported to show a big difference in the characteristics of the

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morphology with a previous reported caffeine-free Cocoa tea (Camellia ptilophylla,

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CCT) in China.17

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In contrast to caffeine biosynthesis, purine alkaloid catabolism and caffeine

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degradation in Camellia plants is relatively unknown. A degradation pathway of

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caffeine has been previously reported in coffee. Caffeine can be subsequently

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catabolized to theophylline, 3-methylxanthine and xanthine. And xanthine enters the

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purine catabolism, and is finally degraded to NH3 and CO2 [xanthine (X) → uric acid

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→

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pathway has been noted in some microorganisms.19-21 And the activity of demethylase

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has been reported in some microorganisms, but not been investigated in plants,

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especially in coffee or tea thus far.

allantoin → allantoic acid → urea → NH3 and CO2].18 The caffeine degradation


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To determine the caffeine metabolism in Camellia plants, four plants LCT1 (C.

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crassicolumna), LCT2 (C. crassicolumna), SCZ (C. sinensis) and YK43 (C. sinensis),

92

with low, normal, and high caffeine content in leaves were performed in this research

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(Figure 1A). RNA-Seq was used to analyze the transcriptomes and identify the related

94

genes in the pathway of caffeine metabolism. To elucidate the caffeine metabolic fate

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in these Camellia plants, a stable isotope tracer experiment involving [15N2]-caffeine

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was conducted. The obtained results can assist researchers in understanding the

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caffeine mechanisms in Camellia plants and be applied to caffeine regulation and

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breeding improvement.

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Materials and methods

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Plant materials

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Fresh young leaves (one apical bud with two terminal leaves) from these Camellia

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plants (LCT1, LCT2, SCZ, and YK43) were picked at the germplasm resource garden

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in the Tea Research Institute of Yunnan Academy of Agricultural Sciences, Menghai,

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Yunnan, China, in June 2017. The freshly plucked leaf samples were stored at −80 °C

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(immediately frozen in liquid nitrogen first) until they were used for further analyses.

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The extraction of RNA, construction of library, and sequencing

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Total RNAs were extracted from the leaf samples by using an RNA-prep Pure Plant

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Kit (TianGen, Beijing, China). Total RNA quantity was evaluated by a bioanalyzer of

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Agilent 2100 (Agilent, Santa Clara, CA, USA). A NanoDropTM ultraviolet



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spectrophotometer (Thermo, Waltham, MA, USA) was used to estimate the RNA

113

integrity. cDNA libraries were established by a kit of NEBNext Ultra RNA Library

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Perp (Gene, Beijing, China) and sequenced by the Illumina HiSeq 4000 platform

115

(Illumina, San Diego, CA) in BGI, Shenzhen, China.

116 117

Data filtering and read mapping

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High-quality clean reads were acquired by removing adaptor sequences, duplicated

119

sequences, ambiguous (with the ratio of “N”>5%) and low quality reads (the reads in

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which quality values of ≤15 comprised more than 20%). All the analyses were

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performed with the clean high quality data.22 The clean reads with high quality from

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samples were mapped to a tea plant genome

123

Spliced Alignment of Transcripts).24

23

by HISAT (Hierarchical Indexing for

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Functional annotation and analysis of differentially expressed genes

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In order to get functional annotations of the proteins, the unigene sequences of

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samples were searched by using BLASTX against nonredundant protein (NR)

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database, nonredundant nucleotide (NT) database, clusters of orthologous groups of

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proteins (COG) database, Kyoto Encyclopedia of Genes and Genomes (KEGG), and

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Swiss-Prot annotated protein sequence database.25 The program of Blast2GO (version

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2.5.0) was employed to receive the gene ontology (GO) annotations based on NR.26

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We used InterProScan (version 5.11-51.0) to annotate the unigenes.27

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After annotations were obtained, expression levels of the unigenes were calculated


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with RSEM software28 and the values of FPKM (fragments per kilobase of transcript

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sequence per millions of base pairs sequenced).29 Transcriptome data were also

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analyzed to identify the DEGs (differentially expressed genes) using DEseq2.30 The

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FDR (false discovery rate), the correction parameter, was used to determine DEGs.31

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Genes with a |log2ratio| of ≥1 and FDR of 0.90 were considered to indicate

184

good correlation and used to construct TF-gene-metabolite network. Moreover, the

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network was displayed using Cytoscape (version 3.6.0).37 The expression of the target

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genes in caffeine metabolic pathway was included for further analysis.

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Stable isotope-labeling tracer experiment for [15N2]-caffeine [15N2]-Caffeine (1, 3-15N2, 99%) was obtained from Cambridge Isotope 15N-tracer

190

Laboratories, MA, USA. The

was conducted according to the publication

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of Ito and Ashihara,38 with a slight modification. The segments of fresh leaves

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(approximately 100 mg) were placed in a flasks with 2 mL of K-Pi buffer (30 mM,

193

pH 5.6, comprising 20 mM sucrose, 1% sodium ascorbate), and 15N2-labelled caffeine

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(10 mM). For comparison, caffeine samples (10 mM [without 15N labeling] and 0 mM)

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were also used as controls. The flasks were treated at 26 °C for 12, 24, and 48 h. After

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incubation, samples were collected and frozen in liquid N2 for further analysis. For

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the analysis of 15N-metabolites, samples were homogenized with 80% aqueous MeOH.

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The fraction of MeOH soluble was concentrated and examined using an LC–MS

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system (Palo Alto, CA, USA). The detection method was the same as the method that



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previously described.

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Determination of other main metabolites

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Catechins were analyzed with the reported method by Jiang39 with minor

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modifications. A 0.06 g freeze-dried sample was ground with 1 mL of 80% methanol

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containing 1% acetic acid, and then added to 2 mL of the extraction solution. After

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the extraction was centrifuged at 16060 g for 10 min at 4 °C, the residue was

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re-extracted as aforementioned. Subsequently, supernatant was set to 4 mL and

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filtered by a membrane of 0.22 μm. Standard compounds and extracted samples were

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determined by a Waters e2695 HPLC system (Milford, MA, USA). A Phenomenex

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C18 column (5 μm, 25 cm × 4.6 mm, Torrance, California, USA), was performed at a

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flow rate of 1.0 mL/min, and at 35 °C. The injection volume of sample was set to 10

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μL. And the mobile phase (100% methanol and 0.2% acetic acid in water) was

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employed with a gradient program of the acetic acid in water, which was increased

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linearly from 95% to 80% in 2 min, to 75% in 12 min, to 58% in 6 min, to 58% in 2

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min, to 0% in 6 min, held at 0% until 31 min, to 95% in 4 min, and then, held at 95%

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until 38 min. Eluate was analyzed by absorbance at 278 nm.

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Free amino acids were extracted from samples according to the published method

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from Wang et al.40 Freeze-dried sample (0.20 g) was powdered and extracted with 2

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mL of 4% sulfonyl salicylic acid by ultrasonic extraction for 30 min. The extraction

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was centrifuged at 13 680 g for 30 min, and the supernatant was metered and filtered

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by a membrane with 0.45 μm. Concentrations of amino acids were determined


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according to the method of Liao 41 by a Hitachi amino acid analyzer (L-8900, Tokyo,

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Japan) with a 4.60 mm × 60 mm column (Hitachi ion exchange resin).

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Statistical analysis

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Three independent biological replicates and technical replicates were used for

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calculating the mean value and the standard deviation (SD) of the metabolite

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concentrations. SPSS 17.0 software was used to determine the significant differences

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by Duncan's multiple-range test at the 5% level. Double coordinate figure was

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produced with Prism 7.0 software. Heat maps were performed with R package. The

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correlations were analyzed via Pearson correlation and the network was displayed

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using Cytoscape (version 3.6.0).

233 234

Results

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RNA sequencing and reference genome alignment

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For RNA-Seq, high-quality total RNAs of samples were reverse transcribed into

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cDNAs, and amplified to construct 12 cDNA libraries. Totally, 80.36 Gb clean reads

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were constructed with an average value of 6.72 Gb each sample. Q20 (base-calling

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error probability of 99%) values were more than 96.48% and the Q30 values were

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more than 89.61% (base-calling error probability of 99.90%; Table 1). The average

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ratio of the sample map to the genome was 76.82%. These results showed the

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obtained high-quality transcriptomic data could be used for the further analysis.

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244

DEGs in these Camellia plants

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The DEGs between the control and comparable sample were defined by the

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fold-change value of the FPKM. As SCZ was the plant material used for genome

247

sequencing23 and SCZ leaves contain normal caffeine concentrations, we chose SCZ

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as the control for this experiment. In our transcriptome data, 14 117 DEGs were

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detected among these four Camellia plants. In SCZ-VS-LCT1, 5701 DEGs were

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detected, of which 2725 were upregulated and 2976 were downregulated. In

251

SCZ-VS-LCT2, 8240 DEGs were identified, of which 3580 were upregulated and

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4660 were downregulated. In SCZ-VS-YK43, 9257 DEGs were noted, of which 3923

253

were upregulated and 5334 were downregulated (Figures 1B and S1).

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Functional enrichment analysis of DEGs using GO and KEGG

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All unigenes of these Camellia plants were annotated using BLASTX. And we

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conducted KEGG and GO enrichment analyses by using the reference genes as the

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background to know the function of DEGs. GO is an international standard system for

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gene functional classification26 that can fully describe the biological category of genes

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and reflect information about genes involved in an organism’s metabolism. GO

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categories include molecular function (MF), cellular component (CC) and biological

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process (BP).42 In the BP category, the metabolic process, the cellular process, and the

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single-organism process were the top three enriched GO terms. In the CC category,

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cell, cell part, and membrane were the top terms. And in the category of MF, catalytic

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activity and binding were the top terms.


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In SCZ-VS-LCT1, 4937, 3153 and 5122 DEGs were enriched to categories of CC,

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MF and BP, respectively. In SCZ-VS-LCT2, 7034, 4626 and 7740 DEGs were

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enriched to categories of CC, MF and BP, respectively. In SCZ-VS-YK43, 7682,

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5276 and 8681 DEGs were enriched to categories of CC, MF and BP, respectively.

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GO classification and the upregulated and downregulated DEGs in the three

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comparisons are shown in Figure S2.

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We also constructed the KEGG analysis with the obtained unigenes against the

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reference canonical pathways. The results revealed 131, 132, and 132 metabolic

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pathways in the SCZ-VS-LCT1, SCZ-VS-LCT2, and SCZ-VS-YK43 samples,

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respectively. These pathways included carbon metabolism, flavone and flavonol

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biosynthesis, purine metabolic pathway, and caffeine metabolic pathway. Among

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them, the target pathways related to the concerned ones were selected (Figure 2). A

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substantial number of DEGs were noted in the metabolic pathways and secondary

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metabolite biosynthesis. Alanine, aspartate, and glutamate metabolism; anthocyanin

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biosynthesis; secondary metabolite biosynthesis; caffeine metabolism; flavonoid

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biosynthesis; flavone and flavonol biosynthesis; phenylalanine metabolism; and

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purine metabolism resulted in different degrees of enrichment in SCZ-VS-LCT1,

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SCZ-VS-LCT2, and SCZ-VS-YK43. Of them, 22 genes were involved in caffeine

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metabolism, of which 4, 8, and 4 DEGs were identified from SCZ-VS-LCT1,

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SCZ-VS-LCT2, and SCZ-VS-YK43, respectively.

286 287

Purine alkaloid content in these Camellia plants



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LC–MS was used to determine purine alkaloids with a high sensitivity and

289

accuracy. The contents of purine alkaloids in these Camellia leaves were shown in

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Table 2. Among these four Camellia plants, YK43 showed the highest total purine

291

alkaloids content (46.68 mg/g), followed by SCZ (35.49 mg/g), LCT1 (15.02 mg/g),

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and LCT2 (8.57 mg/g). Among these purine alkaloids, the caffeine concentrations in

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YK43, SCZ, LCT1, and LCT2 were 42.82, 34.17, 8.33 and 0.59 mg/g DW,

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respectively. Moreover, the caffeine concentrations in LCT1 and LCT2 were

295

considerably lower than that in YK43 and SCZ. However, the concentration of

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another purine alkaloid, theobromine, in LCT1 (5.43 mg/g) and LCT2 (7.70 mg/g)

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was considerably higher than that in YK43 (3.50 mg/g) and SCZ (1.27 mg/g). In

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addition, the concentration of theophylline was substantially higher in the leaf

299

samples of SCZ (4.77 μg/g) and LCT2 (2.46 μg/g) than in those of LCT1 (0.29 μg/g)

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and YK43 (0.53 μg/g). In the leaves of LCT2, 13.02 μg/g of xanthine was detected,

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which was considerably higher than the xanthine concentration in the other three

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Camellia plants.

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Expressions of the genes in the caffeine metabolism

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In addition to the pathway of “caffeine (Cf) → theophylline (Tp) →

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3-methylxanthine (3mX) → xanthine (X) → uric acid → allantoin → allantoic acid

307

→ urea → CO2 + NH3”, 43 we obtained the other five degradation pathways annotated

308

in

309

(https://www.kegg.jp/kegg-bin/highlight_pathway?scale=1.0&map=map00232&keyw

KEGG


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ord=caffeine): “caffeine (Cf) → paraxanthine (Px) → 1,7-dimethyluric acid, ”

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“caffeine (Cf) → paraxanthine (Px) → 7-methylxanthine (7-mX) → 7-methyluric

312

acid, ”

313

1-methyluric acid,” “caffeine (Cf) → theobromine (Tb) → 3,7-dimethyuric acid,”

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and “caffeine (Cf) → 1,3,7-trimethyluric acid → 3,6,8-trimethylallantoin” (Figure 3).

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The identification of these pathways is of considerable importance in research related

316

to the metabolism of caffeine in Camellia plants.

“caffeine (Cf) → paraxanthine (Px) → 1-methylxanthine (1-mX) →

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The expression levels of genes in caffeine’s metabolic pathway were determined to

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ascertain the association between the related gene expression in caffeine metabolism

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and purine alkaloid content in these Camellia plants. Genes involved in caffeine

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metabolism could be grouped into five categories, namely de novo, purine salvage,

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caffeine degradation, caffeine synthesis and methyl donor synthesis44-45. And the

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expression patterns of these unigenes in caffeine metabolism were shown in Figure 4.

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TEA022617.1 (encoded adenylosuccinate synthase, ASS) in the de novo pathway,

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TEA006735.1 (encoded S-adenosylmethionine synthetase, SAMS) in the methyl donor

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synthesis, and TEA019288.1 (encoded adenosine kinase, ADK) were highly expressed

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in these four Camellia plants. In the case of purine alkaloids synthesis pathway, the

327

expression

328

TEA012581.1 (encoded tea caffeine synthase, TCS) were highly expressed in

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Camellia plants with high caffeine concentration. The general expression trends of

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unigenes involved in caffeine degradation pathways were higher in the Camellia

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plants with low caffeine content (Figure 4). From the KEGG enrichment analysis, 4, 8,

patterns

of

TEA015791.1,

TEA028050.1,


TEA028051.1,

and


332

and 4 DEGs were obtained in SCZ-VS-LCT1, SCZ-VS-LCT2, and SCZ-VS-YK43,

333

respectively. These DEGs could be annotated as cytochrome P450 family 1 subfamily

334

A polypeptide 2 (CYP1A2), xanthine oxidase (XO), and urate oxidase (UOX), all of

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which are in the degradation pathway of caffeine (Table S2).

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To further validate the gene expression levels, 20 genes related to purine salvage,

337

caffeine degradation, caffeine synthesis, and the methyl donor synthesis pathways in

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the caffeine metabolism were selected for verification by qRT-PCR. These obtained

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results indicated that the gene expressions showed a consistent tendency with the

340

transcriptome data (Figure 5).

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Metabolic fate of [15N2]-caffeine in the leaves of these Camellia plants

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Stable isotope-labeling tracer experiment was an effective approach for

344

investigating the metabolic pathways that has been comprehensive reported.46-48 To

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investigate the mechanism of caffeine catabolism in these Camellia leaves, a stable

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isotope-labeling tracer was conducted to identify the metabolites involved in caffeine

347

degradation. 15N-labelled metabolites were analyzed by LC–MS, and identified by the

348

standards or the reported tR, ([M+H]+/[M-H]-), major fragment ions, and λmax.49

349

[M+H]+ at m/z 195, and fragment ions at m/z 110 and 138 were determined to be

350

caffeine. According to the second-order MS results, the [M+H]+ of [15N2]-caffeine

351

was at m/z 197, and fragment ions were at m/z 139 and 111. Furthermore, [M+H]+ at

352

m/z 181, and fragment ions at m/z 110 and 138 were considered to be theobromine.

353

Therefore, we deduced that [M+H]+ at 183 and fragment ions at m/z 139, 111 were


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[15N2]-theobromine. In the [15N2]-caffeine stable isotope-labelled tracing experiments,

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[15N2]-theobromine, not theophylline, was detected in the metabolites when

356

[15N2]-caffeine was added (Figure 6).

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TF regulation network in caffeine metabolism

359

Transcriptional control plays an important role in the regulation of secondary

360

metabolites in plants.37 In this study, a correlation analysis between the accumulation

361

of metabolites (caffeine, theobromine, and theophylline) and the expression of related

362

genes and TFs was performed (Figure 7). In total, 53 positively (Figure 7A) and 55

363

negatively (Figure 7B) regulated TF families were associated with unigenes involved

364

in these purine alkaloids metabolites. Most of the TFs can be categorized to bHLH,

365

WRKY, GRAS, MYB/MYB-related, and NAC families. Numerous key genes

366

involved in caffeine metabolism were associated with many TFs, demonstrating that

367

transcriptional regulation of caffeine metabolism was complicated. Pearson

368

correlation coefficients of >0.90 (between metabolites and gene expression, gene

369

expression and TF) were selected to construct a network diagram for positive

370

regulation. A significant positive correlation was revealed in the expression levels of

371

TEA022940.1 (encoded adenine phosphoribosyltransferase, APRT), TEA012581

372

(TCS), TEA028050.1 (TCS), and TEA002100.1 (encoded 5'-nucleotidase, 5'-NT) and

373

caffeine content. Furthermore, theophylline content has a positive correlation with the

374

expression of TEA029871.1 (encoded AMP deaminase, AMPD) and TEA010278.1

375

(AMPD). Theobromine content was shown a positive correlation with the expressions



376

of TEA012514.1 (SAMS) and TEA006735.1 (SAMS), TEA033814.1 (CYP1A2),

377

TEA028881.1 (5'-NT), TEA022785.1 (encoded ribokinase, RK), TEA015523.1

378

(APRT), and BGI_novel_G008251 (encoded allantoinase, ALN).

379 380

Contents of Amino acids and catechins, and gene expression profiles in theanine

381

and catechins metabolisms

382

The concentrations of amino acids in these Camellia leaves are listed in Table 3.

383

Among these plants, the content of total free amino acid of YK43 (19.25 mg/g) was

384

significantly higher than those of the other three Camellia plants, with LCT2 (6.45

385

mg/g) having the lowest content. The concentrations of glutamic acid (Glu),

386

glutamine (GluNH2) and theanine in YK43 and SCZ were higher than those in the

387

other two Camellia plants LCT1 and LCT2. The theanine content in YK43 (10.43

388

mg/g) was considerably higher than that in LCT1 (2.71 mg/g), LCT2 (1.43 mg/g). To

389

better understand theanine accumulation, the expression of key genes encoding

390

alanine aminotransferase (ALT), theanine synthetase (TS), glutamate dehydrogenase

391

(GDH), glutamate synthase (GOGAT), glutamine synthetase (GS) and alanine

392

decarboxylase (ADC) in the theanine biosynthetic pathway was investigated (Figure

393

8). The expression of TS (TEA015198.1) in YK43 was not altered significantly,

394

whereas the expression of GS (TEA015580.1) and ADC (TEA032991.1) was higher;

395

this probably enhanced the theanine biosynthesis process.

396

Catechins can be classified into epicatechin (EC), EC gallate (ECG), catechin (C),

397

gallocatechin (GC), epigalocatechin (EGC), epigallocatechin gallate (EGCG), and


Page 18 of 42

Page 19 of 42


398

gallocatechin gallate (GCG) in fresh tea leaves.50 The concentrations of catechins and

399

gallic acid in the leaves of different Camellia plants are listed in Table 4. Among

400

them, total catechins and gallic acid concentrations in YK43 (189.90 mg/g) and SCZ

401

(176.10 mg/g) were higher, whereas LCT1 (55.29 mg/g) had the lowest catechins and

402

gallic acid concentrations. The concentrations of EGCG, ECG, and EGC were higher

403

in YK43 and SCZ than in the other two Camellia plants. The key genes in catechins

404

biosynthetic pathway were also investigated (Figure 9).

405 406

Discussion

407

Caffeine is an important flavor compound in some soft drinks, particularly in coffee

408

and tea.51 According to the recent studies, caffeine content was less affected by

409

environments, and influenced by genotypic factors;52 caffeine content is different

410

between tea varieties.53 The caffeine distribution was investigated in 23 Camellia

411

species. And caffeine concentrations in young leaves were different.54 The catabolism

412

and biosynthesis of purine alkaloids in Camellia were also reported.55-56 Among these

413

Camellia plants, caffeine biosynthesis and caffeine synthase genes in tea plant and its

414

related species were extensively investigated.15-16 These Camellia resources provide

415

us a novel approach for understanding caffeine metabolism, not only biosynthesis but

416

also catabolism.

417

RNA-Seq is an efficient approach that is widely used for the transcripts

418

quantification and discovery.57-58 From the results of the enriched KEGG pathway,

419

DEGs involved in the caffeine metabolic pathways were found in the comparison



420

groups SCZ-VS-LCT1, SCZ-VS-LCT2, and SCZ-VS-YK43. Concentrations of

421

caffeine and theobromine among these Camellia plants were different. LCT1 and

422

LCT2 had the lower caffeine concentrations and relatively higher theobromine

423

concentrations than the other two plants, while SCZ and YK43 had the higher caffeine

424

concentration with a relatively lower theobromine concentration. The variation of

425

caffeine was closely related to the expression of related genes in metabolic pathways

426

(Table S3). The decreased caffeine content in the low-caffeine plants was probably

427

correlated with the high expressions of related genes in caffeine degradation pathway

428

(Figure 4, Table S4). In addition, many TFs could efficiently regulate the gene

429

expression. And the mechanism through which target genes are regulated by TFs,

430

further affecting the metabolite content, should be verified. The major degradation

431

pathways of caffeine have been clarified. From the results of the stable isotope tracer

432

experiment, a catabolic pathway from caffeine to theobromine in the leaves of

433

Camellia plants was confirmed and detected using LC-MS. It is different from the

434

previous publication that caffeine was first degraded to theophylline by Ashihara’s

435

laboratory using the radioisotope method.59

436

Theanine and catechins were important secondary metabolites in tea, and also

437

greatly contributed to the quality of tea. 60,61 The concentration of theanine was much

438

higher in YK43 than other three Camellia plants. The expression of GS

439

(TEA015580.1) was markedly upregulated in YK43. The sequences of GS and TS are

440

highly homologous,62 and in some plant species, theanine can be synthesized if

441

substrate exists. In addition, the high expression level of ADC in YK43 could enable


Page 20 of 42

Page 21 of 42

442


abundant theanine accumulation.

443

In this study, leaves form Camellia plants with low, normal, and high caffeine

444

concentrations were carried out RNA-Seq, characteristic compound determination,

445

qRT-PCR validation, stable isotope-labelled tracing, and network analysis of

446

TF-gene-metabolite for understanding the caffeine metabolism. Caffeine content

447

variation in these Camellia plants was greatly correlated with the gene expression in

448

caffeine metabolic pathway. For the results of stable isotope-labelled tracer, caffeine

449

was firstly degraded to theobromine, not theophylline, in the leaves of these Camellia

450

plants. The obtained results could provide new insights to understanding caffeine

451

metabolism in Camellia plants, and could also be applied to caffeine regulation and

452

breeding improvement in subsequent research.

453 454

Acknowledgments

455

This work was supported by the National Natural Science Foundation of China

456

(31570692, 31870679), the Changjiang Scholars and Innovative Research Team in

457

University (IRT_15R01), and the Natural Science Foundation of Anhui Province

458

(1608085QC60).

459 460

Authors’ contributions

461

WD and ZZ guided this research. LC prepared the samples. BZ, ML, JZ, and JH

462

analyzed the transcriptomic data and performed all experiments. BZ, WD and ZZ

463

drafted and revised the manuscript. All authors have read and approved the final



464

manuscript.

465 466 467

Ethical standards The authors declare compliance with the ethical standards.

468 469 470

Competing interests The authors declare no competing interests.

471 472 473 474

Data achieving statement The clean data will be available in NCBI SRA under the BioProject (PRJNA522339), if the manuscript is accepted for publication.

475 476

Legends for figures

477

Figure 1 A, Young leaves (one apical bud with two terminal leaves) of these Camellia

478

plants: low-caffeine tea 1 (LCT1), low-caffeine tea 2 (LCT2), Shuchazao (SCZ), and

479

Yunkang 43 (YK43); B, Venn diagram of DEGs in the three comparison groups: total

480

DEGs, upregulated DEGs, and downregulated DEGs

481 482

Figure 2 Enriched KEGG pathways of DEGs. The RichFactor in a pathway is the

483

ratio of the number of DEGs and all annotated genes. The larger enrichment factor is,

484

the higher enrichment degree is; the smaller Q value is, the more significant

485

enrichment is


Page 22 of 42

Page 23 of 42


486 487

Figure 3 Caffeine metabolic pathway. Red represents the pathway of caffeine

488

synthesis, blue represents the main pathway of caffeine degradation reported

489

previously,

490

KEGG. GMPS, GMP synthase; IMPDH, IMP dehydrogenase; GDA, guanine

491

deaminase; URE, urease; 3-NMT, 1-NMT, caffeine synthase (TCS); N-MeNase,

492

N-methyl nucleosidase; ALLC, allantoicase; Anase, adenosine nucleosidase; GK,

493

guanosine

494

phosphoribosyltransferase; NDM, N-demethylase

42

and green represents the pathway of caffeine degradation annotated in

kinase;

Gnase,

guanosine

nucleosidase;

GPRT,

guanine

495 496

Figure 4 Heat maps of key genes expressions in the caffeine metabolic pathway in

497

these Camellia plants. Each column represents the expression in leaves of different

498

Camellia plants and each row represents one gene. FPKM is shown on the logarithmic

499

scale. The red means higher expression and blue denotes lower expression. HPRT,

500

hypoxanthine phosphoribosyltransferase; ADSL, adenylosuccinate lyase

501 502

Figure 5 qRT-PCR validation for the key genes involved in caffeine metabolic

503

pathway. Relative expression levels from qRT-PCR and FPKM from the

504

transcriptome data are shown

505 506

Figure 6 Mass chromatograms of labelled theobromine (Tb) in leaves of Camellia

507

plants LCT1, LCT2, SCZ, and YK43, with [15N2]-caffeine. m/z 138, m/z 110 are



Page 24 of 42

508

characteristic ions of non-labelled Tb in LC-MS analysis; m/z 139, m/z 111 are

509

characteristic ions of labelled Tb. The pattern of non-labelled Tb was used to assign

510

the fragments of labeled Tb

511 512

Figure 7 Transcription factor (TF) regulation network of caffeine’s metabolic pathway.

513

The red nodes represent metabolites, the yellow nodes represent genes, and green

514

nodes represent the enzyme annotated by each gene. TF is represented by pink and

515

blue nodes, and a line between TF and gene indicates the expressions are correlated.

516

A, positive regulation between metabolites and genes; B, negative regulation between

517

metabolites and genes

518 519

Figure 8 Expressions of the key genes in the pathway of theanine biosynthesis. A,

520

theanine biosynthetic pathway; B, heat map of key genes

521 522

Figure 9 Expressions of key genes in pathway of flavonoid biosynthesis. A, flavonoid

523

biosynthetic pathway; B, heat map of key genes. C4H, cinnamate 4-hydroxylase; PAL,

524

phenylalanine ammonia-lyase; 4CL, 4-coumarate-CoA ligase; CHI, chalcone

525

isomerase; ANR, anthocyanidin reductase; DFR, dihydroflavonol 4-reductase; CHS,

526

chalcone synthase; LAR, leucocyanidin reductase; F3H, flavanone 3-hydroxylase;

527

ANS,

528

acyltransferases

leucoanthocyanidin

oxidase;

SCPL,

serine

529 530

Supplementary material


carboxypeptidase-like

Page 25 of 42


531

Figure S1 DEG statistics. The X axis represents the comparison method for each

532

group; the Y axis represents the DEGs number. Red denotes upregulated DEGs and

533

blue represents downregulated DEGs

534

Figure S2 GO classification of DEGs in the three comparison groups: A,

535

SCZ-VS-LCT1; B, SCZ-VS-LCT2; C, SCZ-VS-YK43. The X axis represents the GO

536

terms; the Y axis represents the number of upregulated and downregulated DEGs

537

Table S1 The primers used for qRT-PCR verification

538

Table S2 DEGs in caffeine metabolism in the comparison groups of SCZ-VS-LCT1,

539

SCZ-VS-LCT2 and SCZ-VS-YK43

540

Table S3 The correlation coefficient of caffeine and gene expression levels

541

Table S4 The FPKM value of unigene in the caffeine degradation pathway, and the

542

correlation coefficient of caffeine and gene expression levels

543 544

Reference

545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560

1.

Fang, W. P.; Meinhardt, L. W.; Tan, H. W.; Zhou, L.; Mischke, S.; Zhang, D., Varietal identification

of tea (Camellia sinensis) using nanofluidic array of single nucleotide polymorphism (SNP) markers. Horticulture Research 2014, 1, 14035. 2.

Bordoni, A.; Hrelia, S.; Angeloni, C.; Giordano, E.; Guarnieri, C.; Caldarera, C. M.; Biagi, P. L.,

Green tea protection of hypoxia/reoxygenation injury in cultured cardiac cells. Journal of Nutritional Biochemistry 2002, 13 (2), 103-111. 3.

Nie, G.; Jin, C.; Cao, Y.; Shen, S.; Zhao, B., Distinct effects of tea catechins on

6-hydroxydopamine-induced apoptosis in PC12 cells. Archives of Biochemistry & Biophysics 2002, 397 (1), 84-90. 4.

Lambert, J. D.; Hong, J.; Yang, G. Y.; Liao, J.; Yang, C. S., Inhibition of carcinogenesis by

polyphenols: evidence from laboratory investigations. American Journal of Clinical Nutrition 2005, 81 (1), 284s-291s. 5.

Ogita, S.; Uefuji, H.; Yamaguchi, Y.; Koizumi, N.; Sano, H., Producing decaffeinated coffee plants.

Nature 2003, 423 (6942), 823. 6.

Denis, S.; Augur, C.; Marin, B.; Roussos, S., A new HPLC analytical method to study fungal

caffeine metabolism. Biotechnology Techniques 1998, 12 (5), 359-362.



561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604

7.

Ashihara, H.; Crozier, A., Caffeine: a well known but little mentioned compound in plant science.

Trends in Plant Science 2001, 6 (9), 407-413. 8.

Kato, M.; Kanehara, T.; Shimizu, H.; Suzuki, T.; Gillies, F. M.; Crozier, A.; Ashihara, H., Caffeine

biosynthesis in young leaves of Camellia sinensis: In vitro studies on N-methyltransferase activity involved in the conversion of xanthosine to caffeine. Physiologia Plantarum 1996, 98 (3), 629–636. 9.

Ashihara, H.; Crozier, A., Biosynthesis and metabolism of caffeine and related purine alkaloids in

plants. Advances in Botanical Research 1999, 30 (08), 117-205. 10. Kato, M.; Mizuno, K.; Fujimura, T.; Iwama, M.; Irie, M.; Crozier, A.; Ashihara, H., Purification and characterization of caffeine synthase from tea leaves. Plant Physiology 1999, 120 (2), 579-86. 11. Kato, A.; Crozier, A.; Ashihara, H., Subcellular localization of the N-3 methyltransferase involved in caffeine biosynthes in tea. Phytochemistry 1998, 48 (5), 777-779. 12. Fujimori, N.; Ashihara, H., Adenine metabolism and the synthesis of purine alkaloids in flowers of Camellia. Phytochemistry 1990, 29 (11), 3513-3516. 13. Kato, M.; Mizuno, K.; Crozier, A.; Fujimura, T.; Ashihara, H., Caffeine synthase gene from tea leaves. Nature 2000, 406 (6799), 956-957. 14. Li, Y.; Ogita, S.; Keya, C. A.; Ashihara, H., Expression of caffeine biosynthesis genes in tea (Camellia sinensis). Zeitschrift Für Naturforschung C 2008, 63 (3-4), 267. 15. Jin, J. Q.; Yao, M. Z.; Ma, C. L.; Ma, J. Q.; Chen, L., Association mapping of caffeine content with TCS1 in tea plant and its related species. Plant Physiology & Biochemistry Ppb 2016, 105, 251-259. 16. Jin, J. Q.; Yao, M. Z.; Ma, C. L.; Ma, J. Q.; Chen, L., Natural allelic variations of TCS1 play a crucial role in caffeine biosynthesis of tea plant and its related species. Plant Physiology & Biochemistry 2016, 100, 18-26. 17. Jin, J. Q.; Chai, Y. F.; Liu, Y. F.; Zhang, J.; Yao, M. Z.; Chen, L., Hongyacha, a naturally caffeine-free tea plant from Fujian, China. Journal of Agricultural and Food Chemistry 2018, 66 (43), 11311-11319. 18. Ashihara, H.; Monteiro, A. M.; Moritz, T.; Gillies, F. M.; Crozier, A., Catabolism of caffeine and related purine alkaloids in leaves of Coffea arabica L. Planta 1996, 198 (3), 334-339. 19. Buerstmayr, H.; Lemmens, M., Breeding healthy cereals: genetic improvement of Fusarium resistance and consequences for mycotoxins. World Mycotoxin J 2015, 8 (5), 591-602. 20. Asano, Y.; Komeda, T.; Yamada, H., Microbial production of theobromine from caffeine. Bioscience, Biotechnology, and Biochemistry 2014, 57 (8), 1286-1289. 21. Brand, D.; Pandey, A.; Roussos, S.; Soccol, C. R., Biological detoxification of coffee husk by filamentous fungi using a solid state fermentation system. Enzyme and Microbial Technology 2000, 27 (1), 127-133. 22. Götz, S.; Garcíagómez, J. M.; Terol, J.; Williams, T. D.; Nagaraj, S. H.; Nueda, M. J.; Robles, M.; Talón, M.; Dopazo, J.; Conesa, A., High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Research 2008, 36 (10), 3420-3435. 23. Wei, C.; Yang, H.; Wang, S.; Zhao, J.; Liu, C.; Gao, L.; Xia, E.; Lu, Y.; Tai, Y.; She, G., Draft genome sequence of Camellia sinensis var. sinensis provides insights into the evolution of the tea genome and tea quality. Proceedings of the National Academy of Sciences of the United States of America 2018, 115 (18), 201719622. 24. Kim, D.; Langmead, B.; Salzberg, S. L., HISAT: a fast spliced aligner with low memory requirements. Nature Methods 2015, 12 (4), 357-360. 25. Kanehisa, M.; Goto, S.; Sato, Y.; Furumichi, M.; Tanabe, M., KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Research 2012, 40, 109-114.


Page 26 of 42

Page 27 of 42

605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648


26. Conesa, A.; Gotz, S.; Garciagomez, J. M.; Terol, J.; Talon, M.; Robles, M., Gene ontology database Blast2GO:a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005, 21(18), 3674–3676. 27. Quevillon, E.; Silventoinen, V.; Pillai, S.; Harte, N.; Mulder, N.; Apweiler, R.; Lopez, R., InterProScan: protein domains identifier. Nucleic Acids Research 2005, 33, 116-20. 28. Li, B.; Dewey, C. N., RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 2011, 12 (1), 323-323. 29. Trapnell, C.; Williams, B. A.; Pertea, G.; Mortazavi, A.; Kwan, G.; Van Baren, M. J.; Salzberg, S. L.; Wold, B. J.; Pachter, L., Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature Biotechnology 2010, 28 (5), 511-515. 30. Love, M. I.; Huber, W.; Anders, S., Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 2014, 15 (12), 550. 31. Audic, S.; Claverie, J. M., The significance of digital gene expression profiles. Genome Research 1997, 7 (10), 986-995. 32. Anders, S.; Huber, W., Differential expression analysis for sequence count data. Genome Biology 2010, 11(10), 106 33. Trapnell, C.; Hendrickson, D. G.; Sauvageau, M.; Goff, L.; Rinn, J. L.; Pachter, L., Differential analysis of gene regulation at transcript resolution with RNA-seq. Nature Biotechnology 2013, 31 (1), 46-53. 34. Tai, Y.; Wei, C.; Yang, H.; Zhang, L.; Chen, Q.; Deng, W.; Wei, S.; Zhang, J.; Fang, C.; Ho, C., Transcriptomic and phytochemical analysis of the biosynthesis of characteristic constituents in tea (Camellia sinensis) compared with oil tea (Camellia oleifera). BMC Plant Biology 2015, 15 (1), 190. 35. Wu, Z. J.; Tian, C.; Jiang, Q.; Li, X. H.; Zhuang, J., Selection of suitable reference genes for qRT-PCR normalization during leaf development and hormonal stimuli in tea plant (Camellia sinensis). Scientific Reports 2016, 6, 19748. 36. Zheng, X. Q.; Ashihara, H., Distribution, biosynthesis and function of purine and pyridine alkaloids in Coffea arabica seedlings. Plant Science 2004, 166 (3), 807-813. 37. Vom, E. D.; Kijne, J. W.; Memelink, J., Transcription factors controlling plant secondary metabolism: what regulates the regulators? Phytochemistry 2002, 61 (2), 107-114. 38. Ito, E.; Ashihara, H., Contribution Purine nucleotide biosynthesis de novo to the formation of caffeine in Young Tea (Camellia sinensis ) Leaves. Journal of Plant Physiology 1999, 154 (2), 145-151. 39. Jiang, X.; Liu, Y.; Li, W.; Zhao, L.; Meng, F.; Wang, Y.; Tan, H.; Yang, H.; Wei, C.; Wan, X.; Gao, L.; Xia, T., Tissue-specific, development-dependent phenolic compounds accumulation profile and gene expression pattern in tea plant [Camellia sinensis]. PLoS One 2013, 8 (4), e62315. 40. Wang, H. F.; Tsai, Y. S.; Lin, M. L.; Ou, A., Comparison of bioactive components in GABA tea and green tea produced in Taiwan. Food Chemistry 2006, 96 (4), 648-653. 41. Liao, Y.; Zeng, L.; Li, P.; Sun, T.; Wang, C.; Li, F.; Chen, Y.; Du, B.; Yang, Z., Influence of plant growth retardants on quality of codonopsis radix. Molecules 2017, 22 (10), 1655. 42. Sherlock, G., Gene Ontology: tool for the unification of biology. Canadian Institute of Food Science & Technology Journal 2009, 22 (4), 415. 43. P, M., Catabolism of caffeine in plants and microorganisms. Frontiers in Bioscience A Journal & Virtual Library 2004, 9 (1-3), 1348. 44. Ashihara, H.; Yokota, T.; Crozier, A., Biosynthesis and catabolism of purine alkaloids. Advances in



649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691

Botanical Research 2013, 68 (68), 111-138. 45. Deng, W. W.; Ashihara, H., Profiles of purine metabolism in leaves and roots of Camellia sinensis seedlings. Plant and Cell Physiology 2010, 51 (12), 2105-2118. 46. Boatright, J.; Negre, F.; Chen, X.; Kish, C. M.; Wood, B.; Peel, G.; Orlova, I.; Gang, D.; Dudareva, R. N., Understanding in vivo benzenoid metabolism in petunia petal tissue. Plant Physiology 2004, 135(4), 1993-2011. 47. Eisenreich, W.; Bacher, A.; Arigoni, D.; Rohdich, F., Biosynthesis of isoprenoids via the non-mevalonate pathway. Cellular & Molecular Life Sciences 2004, 61 (12), 1401. 48. Hiroshi, H.; Toshiyuki, O.; Haruka, I.; Kensuke, T.; Miwa, S.; Masakazu, H.; Naoharu, W., Functional characterization of aromatic amino acid aminotransferase involved in 2-phenylethanol biosynthesis in isolated rose petal protoplasts. Journal of Plant Physiology 2012, 169 (5), 444-451. 49. Long-Ze, L.; Pei, C.; Harnly, J. M., New phenolic components and chromatographic profiles of green and fermented teas. Journal of Agricultural & Food Chemistry 2008, 56 (17), 8130. 50. Liang, Y.; Ma, W.; Lu, J.; Ying, W., Comparison of chemical compositions of Ilex latifolia Thumb and Camellia sinensis L. Food Chem. 2001, 75 (3), 339-343. 51. Mohanpuria, P.; Kumar, V.; Yadav, S. K., Tea caffeine: Metabolism, functions, and reduction strategies. Food Science & Biotechnology 2010, 19 (2), 275-287. 52. Wei, K.; Wang, L.-Y.; Zhou, J.; He, W.; Zeng, J.-M.; Jiang, Y.-W.; Cheng, H., Comparison of catechins and purine alkaloids in albino and normal green tea cultivars (Camellia sinensis L.) by HPLC. Food Chem. 2012, 130 (3), 720-724. 53. Wang, L. Y.; Wei, K.; Jiang, Y. W.; Cheng, H.; Zhou, J.; He, W.; Zhang, C. C., Seasonal climate effects on flavanols and purine alkaloids of tea (Camellia sinensis L.). European Food Research & Technology 2011, 233 (6), 1049-1055. 54. Nagata, T. S., S., Difference in caffeine, flavanols and amino acids contents in leaves of cultivated species and hybrids in the genus Camellia. Japan Agricultural Research Quarterly 1986, 19, 276-280. 55. Ashihara, H.; Kubota, H., Biosynthesis of purine alkaloids in Camellia plants. Plant and cell physiology 1987, 28 (3), 535-539. 56. Kato, M.; Ashihara, H., Biosynthesis and catabolism of purine alkaloids in Camellia plants. Natural Product Communications 2008, 3 (9), 1429-1435. 57. Cole, T.; Williams, B. A.; Geo, P.; Ali, M.; Gordon, K.; Baren, M. J., Van; Salzberg, S. L.; Wold, B. J.; Lior, P., Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nature Biotechnology 2010, 28 (5), 511-515. 58. Mortazavi, A.; Williams, B. A.; Mccue, K.; Schaeffer, L.; Wold, B., Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods 2008, 5(7),621-628. 59. Ashihara, H.; Gillies, F. M.; Crozier, A., Metabolism of caffeine and related purine alkaloids in leaves of tea (Camellia sinensis L.). Plant & Cell Physiology 1997, 38 (4), 413-419. 60. Yamaguchi, S.; Ninomiya, K., Umami and food palatability. The Journal of Nutrition 2000, 130(4), 921S-926S. 61. Fei, G.; Guo, Y.; Pu, W.; Yu, W.; Ni, D., Transcriptional profiling of catechins biosynthesis genes during tea plant leaf development. Planta 2017, 246 (1), 1-14.

62. Li, C. F.; Zhu, Y.; Yu, Y.; Zhao, Q. Y.; Wang, S. J.; Wang, X. C.; Yao, M. Z.; Luo, D.; Li, X.; Chen, L., Global transcriptome and gene regulation network for secondary metabolite biosynthesis of tea plant (Camellia sinensis). BMC Genomics 2015, 16 (1), 560.


Page 28 of 42

Page 29 of 42


Table 1. Summary of sequencing reads Sample

Total Raw Reads (Mb)

Total Clean Reads (Mb)

Total Clean Bases (Gb)

Clean Reads Q20 (%)

Clean Reads Q30 (%)

Clean Reads Ratio (%)

LCT1_1 LCT1_2 LCT1_3 LCT2_1 LCT2_2 LCT2_3 SCZ_1 SCZ_2 SCZ_3 YK43_1 YK43_2 YK43_3

60.43 57.16 55.53 60.43 60.43 55.53 60.43 58.80 55.53 57.16 55.53 55.53

44.58 44.65 44.60 44.56 45.04 44.57 45.16 45.11 44.55 44.55 45.13 44.97

6.69 6.70 6.69 6.68 6.76 6.69 6.77 6.77 6.68 6.68 6.77 6.75

97.42 97.81 97.85 96.48 96.77 97.61 96.49 97.47 97.80 97.56 97.81 97.70

92.66 93.66 93.75 89.61 90.91 93.10 90.16 92.70 93.48 92.95 93.53 93.27

73.77 78.10 80.31 73.73 74.53 80.27 74.73 76.72 80.22 77.93 81.27 80.98



Page 30 of 42

Table 2. Determination of purine alkaloids in the leaves of Camellia plants Compounds Purine alkaloids (μg/g) Xanthine (X) 1-Methylxanthine (1-mX) 3-Methylxantine (3- mX) Paraxanthine (Px) Theophylline (Tp) Purine alkaloids (mg/g) 7-Methylxantine (7- mX) Theobromine（Tb） Caffeine (Cf) Total purine alkaloids (mg/g)

C. sinensis Shuchazao (SCZ)

C. crassicolumna low caffeine tea 1 (LCT1)


C. sinensis var. assamica YK43 (YK43)

0.82 ± 0.14 0.33 ± 0.05 n.d. 1.17 ± 0.11 4.77 ± 0.19

1.49 0.04

± ± n.d. 0.72 ± 0.29 ±

0.41** 0.00**

0.33 0.07

0.04** 0.06**

13.02 ± 2.26** 0.12 ± 0.03** tr. 0.73 ± 0.08** 2.46 ± 0.26**

0.05 ± 0.01 1.27 ± 0.21 34.17 ± 3.7

0.14 5.43 8.33

± ± ±

0.00** 0.39** 0.49**

0.26 ± 0.02** 7.7 ± 0.74** 0.59 ± 0.09**

0.22 3.50 42.82

± ± ±

0.04** 0.13** 0.85**

35.49 ± 3.79

15.02

±

2.33**

8.57 ± 0.81**

46.68

±

0.71**

± ± n.d. 1.11 ± 0.53 ±

0.05** 0.01** 0.19 0.10**

Values are expressed as μg/g or mg/g dry weight. n.d., not detected; tr., trace. The significance of the difference of contents between comparison groups (SCZ-VS-LCT1, SCZ-VS-LCT2, and SCZ-VS-YK43) is shown by *P < 0.05, **P < 0.01.


Page 31 of 42


Table 3. Determination of amino acids in the leaves of Camellia plants Compounds

C. sinensis Shuchazao (SCZ)

Main amino acids (μg/g) Asp 606.96 Thr 228 .00 Ser 681.06 Glu 2614.20 GluNH2 1125.21 Theanine 9482.10 Ala 180.14 Leu 5.34 Trp 1363.32 Arg 25.92 Pro 33.45 Total free amino 16.64 acids (mg/g)


± ± ± ± ± ± ± ± ± ± ±

16.32 1.40 8.56 10.38 53.89 256.08 17.61 0.31 14.61 0.85 5.35

577.64 162.40 371.36 1455.40 994.31 2711.90 121.09 221.55 820.74 178.82 49.13

± ± ± ± ± ± ± ± ± ± ±

19.87 7.79* 20.64* 64.86 40.67 156.76** 4.47** 7.21** 23.79** 11.11** 4.48**

±

0.33**

8.61

±

0.33**

C. crassicolumna low caffeine tea 2 (LCT2) 680.96 192.92 282.57 1310.70 697.52 1428.50 127.17 1.39 718.06 5.36 55.15

± ± ± ± ± ± ± ± ± ± ±

13.26 7.33 11.74** 9.49** 29.05** 14.78** 4.01** 0.03 22.26** 0.49* 3.44**

6.45

±

0.08**

C.sinensis var. assamica YK43 (YK43) 864.21 211.76 587.91 2613.90 1841.20 10429.00 183.45 2.47 1059.10 90.21 48.58

± ± ± ± ± ± ± ± ± ± ±

120.15** 25.18 64.38* 192.28** 128.09** 589.95** 15.92 0.28 106.01** 10.21** 2.54**

19.25

±

1.23**

Values are expressed as μg/g or mg/g dry weight. The significance of the difference of contents between comparison groups (SCZ-VS-LCT1, SCZ-VS-LCT2, and SCZ-VS-YK43) is shown by *P < 0.05, **P < 0.01.



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Table 4. Determination of catechins and gallic acid in the leaves of Camellia plants Compounds (A) Catechins (mg/g) Catechin (C) Gallocatechin (GC) Gallocatechin gallate (GCG) Epi-catechin (EC) Epi-gallocatechin (EGC) Epi-catechin-3-gallate (ECG) Epi-gallocatechin-3-gallate (EGCG) (B) Gallic acid (GA) (mg/g) Total catechins and gallic acid (mg/g)

C. sinensis C. crassicolumna C. crassicolumna Shuchazao low caffeine tea 1 low caffeine tea 2 (SCZ) (LCT1) (LCT2) 　　　　　　　　 3.74 ± 0.24 3.22 ± 0.37 4.59 ± 0.70 3.78 ± 0.08 n.d. n.d. 1.99 ± 0.00 2.67 ± 0.18 2.95 ± 0.18 16.99 ± 0.46 9.69 ± 0.81** 8.94 ± 1.49** 34.25 ± 0.70 10.32 ± 0.20** 13.64 ± 1.11** 33.53 ± 2.39 9.62 ± 1.16** 14.28 ± 0.63**

C.sinensis var. assamica YK43 (YK43) 　　 6.54 ± 0.64** 4.14 ± 0.13** 6.14 ± 0.66** 29.5 ± 1.08** 18.35 ± 1.35** 42.31 ± 0.97**

80.91

±

4.29

19.59

±

1.64**

40.21

±

1.80**

82.48

±

3.06

0.34

±

0.03

0.19

±

0.01**

0.21

±

0.02**

0.43

±

0.03**

176.10

±

8.45

55.29

±

2.61**

85.75

±

5.43**

189.90

±

3.25*

Values are expressed as mg/g dry weight. n.d., not detected. The significance of the difference of contents between comparison groups (SCZ-VS-LCT1, SCZ-VS-LCT2, and SCZ-VS-YK43) is shown by *P < 0.05, **P < 0.01.


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Figure 1



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Figure 2


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Figure 3



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Figure 4


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Figure 5



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Figure 6


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Figure 7



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Figure 8


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Figure 9



Graphic abstract (8.44cm wide and 4.73 cm tall)


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Caffeine Content and Related Gene Expression: Novel Insight into

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