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Zhu et al. BMC Plant Biology (2025) 25:663
https://doi.org/10.1186/s12870-025-06691-8
Introduction
Tea, derived from the young leaves and shoots of the
evergreen perennial tea plant (Camellia sinensis), is the
world’s most popular beverage and enjoys global con-
sumption. Its health-promoting properties have been
widely explored. Its health-promoting properties have
been widely explored [1]. e health benefits of tea are
attributed to its phytochemical content, which includes
approximately 4,000 bioactive compounds [2]. e sec-
ondary metabolites such as purine alkaloids (caffeine)
and flavonoids (catechins) are particularly abundant
[3]. ese major secondary metabolites in tea not only
enhance human health but also influence tea quality.
eacrine significantly contributes to the bitterness of
tea and has a mild stimulatory effect on the nervous sys-
tem [4]. It has various physiological functions, including
BMC Plant Biology
*Correspondence:
Wentao Yu
wtyu@foxmail.com; yuwentao@customs.gov.cn
Naixing Ye
ynxtea@126.com; 000q020063@fafu.edu.cn
1College of Horticulture-Key Laboratory of Tea Science at Universities in
Fujian, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian,
China
2Fujian Key Laboratory for Technology Research of Inspection and
Quarantine, Technology Center of Fuzhou Customs District PR China,
Fuzhou 350001, Fujian, China
3Fujian Yongganhua Tea Industry Co., Ltd, Fuzhou 350011, Fujian, China
4Fujian Guoxin Green Valley Agricultural Development Co., Ltd,
Anxi 362400, Fujian, China
5Anxi Tea Industry Development Center, Anxi 362400, Fujian, China
Abstract
Theacrine and epigallocatechin-3-O-(3-O-methyl) gallate (EGCG3"Me) are notable secondary metabolites in tea
(Camellia sinensis), celebrated for their unique avors and signicant health eects. Theacrine has a mild eect
on nerve stimulation, while EGCG3"Me exhibits better stability, higher oral bioavailability and stronger biological
activity. However, tea plant varieties naturally rich in both theacrine and EGCG3"Me are rare. This study unveils
a unique tea variety ‘Anxi kucha’, which is abundant in both theacrine and EGCG3"Me. Through integrated
transcriptome-proteome-metabolome analysis, SAMS3, APRT1, IMPDH, and TCS1 were identied as critical
enzymes for theacrine synthesis; while CHI1, CHI2, FLS2 and LAR1 were key for EGCG3"Me synthesis. Additionally,
transcription factor analysis revealed that MYB4 and bHLH74 were positively correlated with the contents of
theacrine and EGCG3"Me. This study provides valuable materials for further exploring theacrine and EGCG3"Me in
tea plants, and establishes a theoretical basis for their biosynthesis.
Keywords Camellia sinensis, Theacrine, epigallocatechin-3-O-(3-O-methyl) gallate, Anxi Kucha, Metabolic pathways,
Proteomics; transcriptomics
Multi-omics analysis of the mechanisms
of abundant theacrine and EGCG3"Me in tea
(Camellia sinensis)
YanyuZhu1, MengyaGu1, WentaoYu2*, LonghuaLiao3, ShuilianGao1, ShuyanWang1, HongzhengLin1, WenjingGui1,
YouliangZhou4, ZhimingChen5, JingdeZeng5 and NaixingYe1*
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 2 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
locomotor activation, improving sleep, inhibiting breast
cancer cell metastasis, etc [5]. In certain tea plants, caf-
feine can be converted into non-irritating theacrine.
Studies have shown that caffeine is oxidized at C8 to pro-
duce the intermediate 1,3,7-trimethyluric acid, which is
then methylated to N9 to synthesize theacrine [6]. Caf-
feine is a central nervous system stimulant and its con-
sumption may cause occasional adverse reactions [7].
Naturally reducing caffeine intake has significant eco-
nomic and health implications. Tea plant resources
containing theacrine have been found in many places
in Fujian Province. e earliest discovery was in Anxi
County, and its main biochemical components have been
studied [8, 9].
Methylated (-)-Epigallocatechin gallate (EGCG), a
polyphenolic compound and derivative of EGCG, is bio-
synthesized through the phenylpropanoid and flavonoid
biosynthetic pathways. Japanese scholars first discovered
EGCG3"Me in the ‘Benifuuki’ cultivar and observed that
it has superior stability, fat solubility, higher oral bioavail-
ability and stronger biological activity compared with
EGCG [10]. It also possesses antiallergic, antioxidant and
cytoprotective properties [11]. In addition, the methyla-
tion of phenolic hydroxyl groups enhances the bioavail-
ability of polyphenols, which has garnered significant
scholarly attention [12]. However, the tea plant resources
containing EGCG3"Me that have been screened are very
scarce, with only a few germplasms containing natural
EGCG3"Me (> 10mg/g) [13]. e tea plants abundant in
EGCG3"Me are mainly found in Fujian, Guangdong and
Yunnan provinces, in China [13, 14].
Related research has found that tea plants with high
theacrine content are suitable for processing black
tea, which has a mellow and fresh taste [4]. eacrine
impacts the astringency of EGCG by promoting the
binding of salivary proteins to EGCG, thus enhancing its
astringency [15]. EGCG and EGCG3"Me are positively
correlated with bitterness [16]. Transcriptome technol-
ogy has been used to compare the differences in gene
expression among tea cultivars with varying theacrine
levels [17]. It was found that CsWRKY31 and CsWRKY48
might negatively participate in EGCG3"Me biosynthe-
sis by downregulating the expression of CsLAR, CsDFR
and CCoAOMT [18]. Our research group has extensively
studied tea plant resources containing theacrine and
EGCG3"Me across various regions in Fujian. Based on
the transcriptome analysis, we explored the genes related
to theacrine synthesis in the leaves and flowers of ‘Jiao-
cheng kucha’ [8, 14, 19, 20].
‘Anxi kucha’ (AXKC) is a tea variety resource discov-
ered by our research group in Wulang Mountain, Anxi.
rough targeted metabolomics, we found that the
concentrations of theacrine and EGCG3"Me in three
varieties showed interesting changes. With the help
of transcriptomics, proteomics and metabolomics, we
revealed the reasons why AXKC is rich in theacrine and
EGCG3"Me from multiple perspectives, providing data
background for subsequent in-depth research such as
genetic engineering and enzyme engineering. e aim is
to provide a new tea plant experimental material for the
study of theacrine and EGCG3"Me, and to provide a ref-
erence for the development and utilization of AXKC.
Materials and methods
Tea samples
In early April 2024, ‘Anxi kucha’ (AXKC) (also known as
the Camellia sinensis ‘Anxi Langshan Tea’) and ‘Tieguan-
yin’ (TGY) were picked at the Wulang Mountain in Anxi
County, Fujian Province. e control cultivar ‘Fudingda-
baicha’ (FDDB) was picked in the tea plant cultivar
resource garden of Fujian Agriculture and Forestry Uni-
versity. Previous studies indicated that theacrine content
and EGCG3"Me increased initially and then decreased
with leaves maturation [20, 21]. Consequently, the third
leaf of the tender shoot with relatively consistent growth
was selected as the experimental material. ree biologi-
cal replicates were prepared for each sample and each
omics experiment. e third leaf was promptly frozen in
liquid nitrogen and stored at -80 ℃ refrigerator for sub-
sequent experiments.
Targeted metabolite assays
Chemicals
e following 9 catechin standards were used: epigallo-
catechin-3-O-(3-O-methyl) gallate (EGCG3"Me), cat-
echin (C), epicatechin (EC), epigallocatechin gallate
(EGCG), epigallocatechin (EGC), gallocatechin (GC),
epicatechin gallate (ECG), gallocatechin gallate (GCG),
catechin gallate (CG). Purine alkaloid standards: thea-
crine (TC), caffeine (CAF), theobromine (TB), and
theophylline (TP) were purchased from Yuanye Bio-tech-
nology Co., Ltd. (Shanghai, China). Methanol (chromato-
graphic grade) and acetonitrile (chromatographic grade)
were purchased from Shanghai Merck Chemical Tech-
nology Co., Ltd. Formic acid (chromatographic grade)
was purchased from China National Pharmaceutical
Group Chemical Reagent Co., Ltd., and ultrapure water
was used.
Instruments and equipment
UltiMate 3000 high performance liquid chromatograph
(ermo Fisher Scientific, USA), diode array detector
(DAD), C18 reversed-phase chromatographic columns
(5 μm, 4.6 × 250 mm, 2.6 μm, 2.1 × 100 mm) (Phenom,
Guangzhou, China), Nexera X2 LC-30A HPLC system
(Shimadzu, Kyoto, Japan), tandem Sciex 4500 Q-Trap
mass spectrometer (Sciex, Massachusetts, USA); AB204-
N analytical balance (Mettler, USA); ultrapure water
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 3 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
system (Medium Touch, Shanghai Hetai Instrument
Co., Ltd., China). KQ-800E ultrasonic cleaner (Kunshan
Ultrasonic Instrument Co., Ltd., China); MS3 basic vor-
tex shaker (Aika (Guangzhou) Instrument Co., Ltd.,
China).
Determination of catechins and purine alkaloid
components
Catechins sample preparation
e catechin components were carried out using high-
performance liquid chromatography (HPLC). e spe-
cific method was referred to this study [22]. A 200mg
portion of crushed freeze-dried sample was treated with
30 mL of methanol and vortexed. Ultrasonic extraction
was performed at room temperature for 30min, followed
by refrigerated centrifugation at 4℃ and 10,000 r/min
for 5min. en the supernatant was filtered through the
0.22μm organic phase microporous membrane.
On-machine data collection and analysis
Catechins chromatographic conditions were as follows:
C18 reverse phase column (5 μm, 4.6 × 250 mm) was
used, with mobile phase A being 0.2% formic acid-water
solution (v: v), and mobile phase B being methanol. e
flow rate was set to: 1.00 mL/min, the column tempera-
ture to: 40 ℃, and the injection volume: to 10.0 µL. Gra-
dient elution conditions were: 0–2min, 88% A; 2–10min,
88%-75% A; 10–15 min, 75%-73% A; 15–25 min, 73%-
68% A; 25–30min, 68% A; 30–32min, 68-88% A. e
detector wavelength was set at: 280nm.
Preparation of purine alkaloid samples and on-machine data
collection and analysis
e steps for obtaining the supernatant were the same as
for catechins. e supernatant was diluted 10-fold and
1000-fold, respectively. e dilution was passed through
a 0.22 μm organic phase microporous membrane for
UPLC-MS/MS analysis. is was performed using a Nex-
era X2 LC-30A HPLC system and a tandem Sciex 4500
Q-Trap mass spectrometer at a column temperature of
40 ℃, a wavelength of 231nm, an injection volume of 5
µL, and a flow rate of 0.3 mL/min. A C18 column (2.6μm,
2.1 × 100mm) was used with solvent A (0.1% formic acid)
and solvent B (acetonitrile) as the mobile phase. Gradi-
ent elution conditions: 0–0.2min, 10% B; 0.2–2.5min,
10-90% B; 2.5–4.0 min, 90% B; 4.0–4.2 min, 90%-10%
B; 4.2–6.0 min, 10% B. Mass spectrometry conditions:
the electrospray ionization source (ESI) was operated in
positive ion mode with the following parameters: curtain
gas (N2) pressure at 30 psi, electrospray voltage at 4500V,
auxiliary gas (N2) temperature at 550 °C, nebulizer gas
(N2) pressure at 55 psi, and heater gas (N2) pressure at 55
psi [19]. All samples underwent three replicates.
RNA isolation and RNA-seq analysis
RNA extraction and sequencing
Total RNA was extracted from the test materials using
the Omega Plant RNA kit (Omega Bio-Tek, Inc, Cat. No.
R6827, USA) following the manufacturer’s protocol. RNA
sequencing was performed by Genedenovo Biotechnol-
ogy Co., Ltd. (Guangzhou, China), for detailed methods,
please refer to the study by Huang et al. [23]. Nine librar-
ies (3 samples, 3 biological replicates) were sequenced on
Hiseq™ 4000 platform.
Data quality control
Fastp was used to perform quality control on the raw
data, filter low-quality data to obtain high-quality
clean read length data. HISAT 2 was used to align the
sequences obtained from the paired-end sequencing to
reference tea genome of Tieguanyin, with the parameters
set to default [24]. Based on the alignment results, tran-
scripts were reconstructed using Stringtie, and the gene
expression levels in each sample were calculated using
RSEM software.
Identication and quantication of proteins
Proteome extraction and sequencing
To extract proteins from the samples, the DIA experi-
mental method was employed. In brief, it involved pro-
tein denaturation, reduction, alkylation, enzymatic
digestion and peptide purification [25]. ese procedures
were conducted by Genedenovo Biotechnology Co., Ltd.
(Guangzhou, China). After preparing the protein sam-
ples, DIA protein detection was performed.
Protein qualitative and quantitative analysis
e UltiMate 3000 (ermo Fisher Scientific, MA, USA)
liquid chromatography system was connected to the
tims TOF Pro2 Mass spectrometer (Bruker Daltonics),
an ion-mobility spectrometry quadrupole time of flight
mass spectrometer (Bruker Daltonics). DIA data were
acquired in the diaPASEF mode. Raw DIA data were pro-
cessed and analyzed using Spectronaut 18 (Biognosys
AG, Switzerland) with default settings. To ensure the reli-
ability of results, checked whether the qualitative analy-
sis results of the protein meet the following identification
criteria: precursor thresholds of 1.0% FDR and protein
thresholds of 1.0% FDR at the peptide and protein levels,
respectively. Normalization strategy was set to local nor-
malization. Peptides which passed the 1% Qvalue cutoff
were used to calculate the major group quantities with
MaxLFQ method. After counting the reads for each pro-
tein, the set of genes expressed in each time period was
counted for each variety, and differences between variet-
ies were analyzed by Venn diagrams.
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 4 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
Quantitative real-time PCR (qRT-PCR) analysis
cDNA synthesis, qRT-PCR, and specific primer design
were based on previously reported methods [26]. Primers
were designed using an online website ( h t t p s : / / w w w . p r i m
e r 3 p l u s . c o m / i n d e x . h t m l. September 10, 2024) (Table S2).
e tea plant GAPDH (registration number GE651107)
was selected as the internal reference gene [27]. qRT-
PCR analysis was performed using a CFX96 Touch™ Real-
Time PCR detection system (Bio-Rad, Hercules, CA,
USA), according to the instructions of the Hieff® qPCR
SYBR Green Master Mix (No Rox) Mixing kit (Yisheng
Biotechnology (Shanghai) Co., Ltd., Shanghai, China). All
samples were analyzed in three biological replicates. Rel-
ative expression levels were calculated using the 2−△△Ct
method [28]. e correlation coefficients of the RNA-seq
data and qRT-PCR was performed in Omicshare Tools ( h
t t p s : / / w w w . o m i c s h a r e . c o m / t o o l s).
Data analysis
Each experiment was repeated at least three times, and
data presented as mean ± standard deviation. Differ-
ences between groups were assessed using one-way
ANOVA followed by Duncan’s test. Principal Component
Analysis (PCA) was performed using R studio (4.0.5)
[29]. Cluster analysis and correlation analysis were per-
formed with the Mfuzz R package. e chemical struc-
tures were created using ChemDraw 22.0.0. e network
diagram of transcription factors and genes was drawn
using Cytoscape−v3.10.2 software. Differentially abun-
dant proteins (DAPs) were analyzed using Student’s t
test, with selection criteria of a fold change > 1.2, P < 0.05
[30]. e edge R package was applied to identify differ-
entially expressed genes (DEGs) across samples with a
criterion of fold change > 2, FDR < 0.05 [31]. e gene
functions of DEGs and the enriched metabolic pathways
were annotated based on Gene Ontology (GO, h t t p : / / w
w w . g e n e o n t o l o g y . o r g / ) and Kyoto Encyclopedia of Genes
and Genomes (KEGG, https://www.genome.jp/kegg/),
respectively. Transcriptome data have been uploaded to
the National Center for Biotechnology Information h t t p s
: / / s u b m i t . n c b i . n l m . n i h . g o v / s u b s / s r a / via the SRA partner
repository under the data set identifier PRJNA1179900.
e mass spectrometry proteomics data have been
deposited to the ProteomeXchange Consortium via the
PRIDE partner repository with the dataset identifier
PXD062468.
Results
Analysis of purine alkaloids and catechins content in ‘Anxi
Kucha’
We measured the purine alkaloid and catechin contents
of the leaves of FDDB, TGY and AXKC. Among them,
the contents of theacrine and EGCG3"Me were sig-
nificantly different among the three varieties. e total
purine alkaloid content of AXKC was significantly higher
than that of the other two tested samples. e difference
in the total content of purine alkaloids among the three
tested samples was mainly reflected in the theacrine
content. e theacrine content of AXKC was as high as
17.44 ± 0.40 mg/g, which was significantly higher than
that of TGY and FDDB (not detected) (Fig.1A).
e EGCG3"Me content of AXKC was
11.25 ± 0.17mg/g. For TGY, the EGCG3"Me content was
5.32 ± 0.30mg/g. FDDB had an EGCG3"Me content of
0.93 ± 0.01 mg/g (Table 1). Analysis of significant differ-
ences indicated that the differences in the EGCG3"Me
content of AXKC, TGY and FDDB varied significantly
(p < 0.05), and the contents showed a low, medium and
high distribution in order (Fig.1B).
In general, the contents of theacrine and EGCG3"Me
were significantly different among the three tea varieties,
with AXKC leaves exhibiting substantially higher levels
of both metabolites compared to the other two varieties.
Multivariate proteomics and transcriptomics analysis of
‘Anxi Kucha’
e content of theacrine and EGCG3"Me in AXKC
was higher, and the content was significantly differ-
ent from the other two varieties. To further explore the
synthesis pathways and enzymes/genes of theacrine and
EGCG3"Me, proteomic and transcriptomic studies were
continued. A total of 10,035 proteins were identified
from the proteomics dataset, and the samples were clus-
tered into three groups in the PCA plot based on their
protein abundance values. e proteome profiles of dif-
ferent samples were well differentiated (Fig.2A). Further
research is warranted. RNA sequencing identified 53,422
transcripts, with 7,521 were novel genes. Pearson analy-
sis of TPMs (Transcripts Per Millions) distribution across
samples (Fig. 2B) and the heatmap depicted dynamic
trends of transcripts. Strong correlations between differ-
ent biological replicates were observed, confirming anal-
ysis’s reliability.
Using DIA and RNA-seq analysis to explore the
enzymes and genes that synthesize theacrine and
EGCG3"Me. Proteomic analysis identified 6049 DAPs
(Fig. 2C), while transcriptome data revealed, 16,102
DEGs (Fig.2D). In the FDDB vs TGY comparison, there
were 1419 up-regulated and 1537 down-regulated DAPs.
ere were 4239 up-regulated and 5763 down-regulated
DEGs. In the FDDB vs AXKC comparison, there were
2254 up-regulated and 2067 down-regulated DAPs. ere
were 4831 up-regulated and 5646 down-regulated DEGs.
In the TGY vs AXKC comparison, there were 1894 up-
regulated and 1689 down-regulated DAPs. ere were
4413 up-regulated and 3713 down-regulated DEGs.
In organisms, different proteins coordinate to perform
various functions. Pathway analysis aids in understanding
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Page 5 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
these biological functions of proteins. Pathway enrich-
ment analysis identified pathways related to theacrine
and EGCG3"Me synthesis. Key pathways, including
purine metabolism and flavonoid biosynthesis, were
highlighted in the KEGG enrichment results of the pro-
teome (Fig.2E). e abundance levels of DAPs enzymes
in these two pathways were analyzed (Fig. 2F). High
enzyme abundance levels of SAMS3, TCS1, TCS2,
APRT3, IMPDH and ADK2 were found in the purine
metabolism pathway, while CHI1, CHI2, FLS2 and ANR4
were prominent in the flavonoid biosynthesis pathway.
ese enzymes played a role in the synthesis of theacrine
and EGCG3"Me, respectively. In the transcriptome data,
the KEGG enrichment results of DEGs also enriched
the purine metabolism and flavonoid biosynthesis path-
ways (Fig.2G). e transcriptome data were verified by
qRT-PCR. e strong correlation coefficient between
qRT-PCR analysis and RNA-seq data indicated that the
transcriptome data in this study accurately reflected tran-
script abundance (Fig.2H).
e results of proteomic and transcriptomic analysis
showed that the three tea varieties could be well distin-
guished from each other. e key pathways regulating
theacrine and EGCG3"Me synthesis were successfully
enriched.
Integrated transcriptome-proteome-metabolome analysis
Protein and mRNA in organisms represent gene expres-
sion at the protein level and transcription level. Protein-
transcriptome association analysis can focus on enzymes
expressed in both omics simultaneously. Venn diagram
analysis screened the three comparison groups for DAPs
and DEGs expressed in both omics, resulting in 808,
1167, and 759, respectively. e specific distribution and
up-regulation and down-regulation of the commonly
expressed enzymes in each comparison group were
shown in Fig.3A and B.
Fig. 1 Theacrine and EGCG3"Me content of FDDB, TGY and AXKC varieties. (A/C) The chemical structure and content of theacrine. (B/D) The chemical
structure and content of EGCG3"Me. The signicance of dierential compounds between the two control groups is indicated as **P < 0.05, ***P < 0.01.
FDDB: ‘Fudingdabaicha’, TGY: ‘Tieguanyin’, AXKC: ‘Anxi kucha’. N.D. means not detected
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 6 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
Nine quadrant graphs were drawn based on the log2
values of fold differences between the two omics (Fig.3C,
D, and E). In the purine metabolism pathway, common
mRNAs and corresponding proteins were mostly con-
centrated in quadrant 6. Related proteins and mRNAs in
the flavonoid biosynthesis pathway were relatively more
common in quadrants 3, 6, and 7. Various enzymes in
the proteome directly participate in metabolic processes
and regulate metabolic reactions. erefore, we focused
on the DAPs in quadrants 6, 8, and 9. KEGG enrichment
analysis (Fig. 3F) revealed that purine metabolism and
flavonoid biosynthesis pathways related to theacrine and
EGCG3"Me synthesis were enriched.
We further focused on the two enriched pathways
and performed correlation analysis between their DAPs
(quadrant 3) that were upregulated in both proteomic
and transcriptomic data and the targeted metabolites,
displayed as a correlation heat map (Fig.3G). ere was
a highly significant correlation between the abundance
of IMPDH, TCS1, SAMS3, APRT1 enzymes and thea-
crine content. is was partially consistent with the
analysis results in Fig.2F, indicating that SAMS3, APRT1,
IMPDH and TCS1 enzymes abundance levels regulated
theacrine synthesis. ere was a highly significant cor-
relation between EGCG3"Me content and the abundance
of LAR1, CHI1 and FLS2 enzymes, as well as a significant
correlation with CHI2. ere was a significant correlation
between LAR1, FLS2 and CHI1 enzymes abundance and
EGCG content. is further illustrating that CHI1, CHI2,
and FLS2 enzymes regulated EGCG3"Me synthesis.
e results of transcriptome-proteome-metabolome
analysis showed that IMPDH, TCS1, SAMS3, and APRT1
enzymes were closely related to theacrine synthesis,
and LAR1, CHI1, CHI2 and FLS2 enzymes were closely
related to EGCG3"Me synthesis. Further analysis of
these related enzymes in the regulation of theacrine and
EGCG3"Me synthesis pathways was needed.
Analysis of DAPs and DEGs involved in purine metabolism
and avonoid biosynthesis pathways in ‘Anxi kucha’
Purine metabolism pathway
At the protein level, SAMS3, ADK1, ADK2, APRT1,
APRT2, APRT3, AMPD, and IMPDH (Fig. 4A) were
expressed at higher levels in AXKC leaves, and all
were upregulated. ese enzymes are crucial in xan-
thine nucleoside synthesis. High-level expression pro-
moted the accumulation of more xanthine nucleosides
in AXKC leaves, providing more abundant initial sub-
strates for purine alkaloids synthesis. Conversely, these
enzymes were generally down-regulated in FDDB and
TGY leaves. TCS1 and TCS2 enzymes were upregu-
lated in AXKC, providing more precursors for the sub-
sequent theacrine synthesis. N-methyltransferase plays a
vital role in theacrine synthesis, with higher expression
of the NMT2 enzyme in AXKC leaves. Previous studies
have shown that most genes involved in caffeine metab-
olism are upregulated. URE is part of the caffeine meta-
bolic pathway [32]. In this study, the expression level of
URE1 enzyme was consistent with the changes in caffeine
content in FDDB and AXKC leaves. URE1 enzyme was
highly expressed in samples with low caffeine content,
which is consistent with the results of previous studies
[33]. Caffeine seems to be a precursor for theacrine syn-
thesis, and the catalytic effect of URE1 enzyme on caf-
feine may affect the synthesis of theacrine by AXKC.
Gene expression changes related to theacrine synthesis
regulation in the purine metabolism pathway were also
analyzed. e SAMSs genes were mainly up-regulated
in FDDB leaves, with SAMS3 up-regulated in AXKC
leaves. ADK1 and ADK3 genes were highly expressed
and upregulated in TGY and AXKC leaves. APRT genes
were all up-regulated in FDDB leaves, with APRT1
solely up-regulated in AXKC leaves. e IMPDH gene
was up-regulated in AXKC leaves. e expression levels
of these genes in FDDB, TGY and AXKC leaves varied
between up-regulated and down-regulated, facilitating
xanthosine accumulation and laying the foundation for
caffeine synthesis. TCS1, TCS2, TCS3 and TCS4 genes
were all up-regulated in AXKC leaves. e NMT1 gene
was upregulated in AXKC and FDDB leaves, while URE2
and URE3 genes had higher expression in FDDB leaves.
Transcriptomic data were slightly less consistent with the
theacrine concentrations changes across the three vari-
eties, aligning with the nine-quadrant diagram analysis,
where genes and corresponding enzymes related to the
purine metabolic pathway were mainly concentrated in
quadrant 6, with higher protein expression abundance
Table 1 Relative quantitative analysis of alkaloid and Catechin in
the third leaf of dierent tea varieties
Cultivar AXKC TGY FDDB
CAF 32.29 ± 0.48a33.27 ± 1.10a30.37 ± 0.30b
TC 17.44 ± 0.40aND ND
TB 1.39 ± 0.01a0.65 ± 0.01b0.48 ± 0.01c
TP ND ND ND
Total alkaloids 51.11 ± 0.75a33.92 ± 1.10b30.85 ± 0.30c
GC 1.99 ± 0.07c3.61 ± 0.11a2.46 ± 0.030b
EGC 16.83 ± 0.09c27.69 ± 0.08b48.01 ± 0.07a
C0.37 ± 0.05b0.55 ± 0.05a0.17 ± 0.03c
EGCG 97.33 ± 0.12a75.13 ± 0.32b67.98 ± 0.26c
EC 3.02 ± 0.15c7.19 ± 0.13a6.26 ± 0.02b
EGCG3"Me 11.25 ± 0.17a5.32 ± 0.30b0.93 ± 0.01c
ECG 24.56 ± 0.04a19.61 ± 0.17b13.98 ± 0.03c
CG 0.29 ± 0.04a0.16 ± 0.05b0.28 ± 0.01a
Total catechins 155.64 ± 0.17a139.26 ± 0.44c140.08 ± 0.20b
All data are presented as mean ± standard statistical (SD) of three replicates.
Values are exp ressed as mg/g. The let ters (a, b, c) indicate stati stical signican ce
(P < 0.05). ND means not detected. FDDB: ‘Fudingdabaicha’, TGY: ‘Tieguanyin’,
AXKC: ‘Anxi kucha’. The con tents of TC.
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Zhu et al. BMC Plant Biology (2025) 25:663
Fig. 2 (See legend on next page.)
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Page 8 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
than mRNA. Enzymes directly catalyze chemical reac-
tions in organisms and promote metabolites synthesis.
eir abundance levels directly affect the accumulation
of metabolites in the leaves of the three varieties.
At the protein and transcription levels, the changing
trends of SAMS3, ADK1, APRT1, IMPDH and TCS1 in
FDDB, TGY and AXKC leaves were consistent with thea-
crine content, with relatively high expression levels were
relatively high in AXKC leaves. In the association analy-
sis of targeted metabolites with proteome and transcrip-
tome (Fig.3G), the abundance levels of SAMS3, APRT1,
IMPDH and TCS1 were significantly correlated with
theacrine synthesis. is further illustrates the positive
effects of genes and corresponding enzymes on theacrine
synthesis in AXKC leaves.
Flavonoid biosynthesis pathway
Based on the enrichment of multiple analysis results
in flavonoid biosynthesis pathways, we examined the
DAPs and DEGs in these biosynthesis pathways in
detail (Fig.5). In the protein group, we found five PALs
enzymes, with higher enzyme expression levels in FDDB
leaves and the lowest enzyme expression levels in TGY
leaves. A 4CL enzyme, the enzyme expression level was
higher in FDDB and AXKC leaves. CHS1 was expressed
at a higher level in AXKC leaves, while the enzymes
CHI1, CHI2, CHI3, F3H1, FLS1 and FLS2 were expressed
at high levels in both AXKC and TGY leaves. e CHI
enzymes were responsible for synthesizing correspond-
ing flavanols, which were then converted into flavonoids
like epigallocatechin-3-glucose (EGCG precursor) by the
FLS enzymes. e high expression of these enzymes facil-
itates the formation of more EGCG, providing the basic
molecules needed for the accumulation of EGCG3"Me.
In the results of target metabolites, EGCG content in
AXKC and TGY leaves was higher, indicating that these
enzymes positively regulate the synthesis of EGCG3"Me
precursor, EGCG. e transcriptome data showed that
the expression trends of the identified CHIs genes were
consistent with those of the corresponding enzymes,
demonstrating a positive regulatory effect. e expres-
sion level of F3’H1 enzyme was higher in FDDB and TGY
leaves, while the F3’5’H2 enzyme expression level was
higher in TGY and AXKC leaves. DFR1 was expressed at
a higher level in FDDB leaves, and DFR2 showed higher
abundance in TGY and AXKC leaves. ANR1 and ANR2
expression abundance was higher in FDDB and TGY
leaves, whereas ANR3 and ANR4 enzymes had higher
expression levels in AXKC leaves. e abundance levels
of LAR1, LAR2, CCoAOMT1 and CCoAOMT2 were
relatively high in AXKC leaves. ese two enzymes have
both indirect and direct effects on EGCG3"Me synthesis,
and their high-level expression promotes the production
of higher content of EGCG and EGCG3"Me, consistent
with the results of targeted metabolites.
DEGs involved in the flavonoid biosynthesis pathway
in the transcriptome data were identified, and the fol-
lowing genes were included. e PALs and 4CL2 genes
were expressed at higher levels in FDDB leaves. e C4H,
CHS2, CHS3, CHI1, CHI2, and CHI4 were expressed
at higher levels in TGY and AXKC leaves, especially in
AXKC leaves. Most of the F3’H and F3’5’H genes were
highly expressed in TGY and AXKC. FLS1, FLS2, and
FLS3 were up-regulated in TGY and AXKC leaves, and
FLS4 was up-regulated in FDDB. DFR1, DFR3, and DFR4
were highly expressed in FDDB leaves, with only DFR3
was up-regulated in AXKC leaves. ANS was up-regu-
lated in FDDB leaves. ANR3 was up-regulated in FDDB
and AXKC leaves. ANR1 and ANR2 were up-regulated
in TGY leaves. LAR1 was expressed at a higher level
in AXKC leaves, consistent with the enzyme expres-
sion abundance trend. Previous studies have found that
CCoAOMT enzymes are involved in many plant sec-
ondary metabolic processes and affect the biosynthesis
of lignin [34, 35]. In this study, CCoAOMT3 was highly
expressed in FDDB leaves.
CHI1, CHI2, FLS1, FLS2 and LAR1, genes and their
corresponding enzymes were consistent with the chang-
ing trend of EGCG3"Me content in FDDB, TGY and
AXKC leaves. In the association analysis of targeted
metabolites with proteome and transcriptome (Fig.4H),
the abundance levels of CHI1, CHI2, FLS2 and LAR1
enzymes were significantly correlated with EGCG3"Me
synthesis. is further illustrates the positive effects of
(See gure on previous page.)
Fig. 2 Overview of proteomic and transcriptomic analysis of tea varieties. Sample relationship between the tested samples. (A) Proteomics data set. (B)
Transcriptome sequencing data. Multiple group dierence scatter plots: These plots list the number of up-regulated and down-regulated DAPs and DEGs
based on pairwise comparisons. (C) Log2-transformed fold changes in DAPs abundance among dierent germplasms. (D) Log2-transformed fold chang-
es in DEGs expression among dierent germplasms. Enrichment Analysis: (E) Enrichment analysis of proteomic DAPs. The top 20 enriched pathways are
listed. KEGG terms related to theacrine and EGCG3"Me metabolism are highlighted in bold and red. (F) Circular dendrogram showing the abundance
levels of DAPs in the purine metabolism and avonoid biosynthesis pathways. The size of the circle indicates the abundance level of the enzyme. (G)
DEGs are listed in a circle diagram with the top 50 KEGG enriched pathways. The rst circle represents the Pathway ID, with dierent colors distinguish-
ing KEGG_A_class. The second circle indicates the number of genes enriched in the Pathway ID in the background gene set. The third circle shows the
number of genes in the target gene set enriched in the Pathway, and dierent colors distinguish up- and down-regulation. The fourth circle represents
Gene Ratio, calculated as the number of genes in the target gene set enriched in the pathway divided by the number of genes in the background gene
set enriched in the pathway. The Pathway ID of purine metabolism and avonoid biosynthesis pathways were marked in red and bold. (H) Correlation
analysis of 7 selected DEGs. The correlation coecients of the RNA-seq data and qRT-PCR analyses for each gene are represented by the values between
two heatmaps. FDDB: ‘Fudingdabaicha’, TGY: ‘ Tieguanyin’, AXKC: ‘Anxi kucha’
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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Zhu et al. BMC Plant Biology (2025) 25:663
these genes and corresponding enzymes on EGCG3"Me
synthesis in AXKC leaves.
Transcription factor regulations in theacrine and
EGCG3"Me metabolism
Transcription factors (TFs) can specifically bind to the
cis-acting elements in the promoter region of struc-
tural genes, regulating their transcriptional expression
by either activating or inhibiting the promoter activity
of target genes. It has been found that related enzymes/
genes have a regulatory effect on the synthesis of thea-
crine and EGCG3"Me. To explore the upstream changes
in the expression of these enzymes and genes, TFs
were analyzed. TF annotation was performed using the
PlantTFDB website h t t p s : / / p l a n t t f d b . g a o - l a b . o r g /. e
proteomic data from this experiment were statistically
analyzed, resulting in the annotation of a total of 46 TFs
families. To further clarify the regulatory effects of TFs
on the purine metabolic and the flavonoid metabolic
pathways, the following analysis was performed. Firstly,
previous studies have shown that bHLH, MYB, WRKY,
and ERF can regulate these two pathways [18, 36]. e
motif information of these TF bindings was obtained
from the JASPAR database, and the transcriptional target
genes were predicted using the MEME FIMO software.
TFs and target genes with correlation (pearson > 0.8)
were selected, and the TFs that played an up-regulated
role were used to draw the network diagram.
In the purine metabolism pathway (Fig. 6B), one
bHLH, two MYB, and two ERF transcription factor fam-
ily members were identified to play an up-regulatory role.
BHLH74 and MYB4 targeted and regulated TCS2, while
CSTF50 (ERF) targeted and regulated ADK3 and IMPDH,
MYB4 and ERF4 also targeted and regulated IMPDH, and
SRM1 (MYB) targeted and regulated SAMS1, SAMS2,
SAMS4, and SAMS5. e expression levels of IMPDH
and TCS2 were consistent with the expression trends of
CSTF50(ERF), ERF4, MYB4 and BHLH74 (Fig.6A and
C), which further demonstrating, the up-regulation of
TCS2 and IMPDH by these four TFs.
In the flavonoid biosynthesis pathway (Fig. 6E), two
bHLH, two MYB, and one WRKY transcription factor
family members were identified. BHLH74 and MYB4
targeted and regulated FLS2, MYC2 (bHLH) targeted
and regulated CHS2, WRKY46 targeted and regulated
CHI1, and SRM1 (MYB) targeted and regulated FLS1,
CHI1, CHI4, F3’5’H5 and FLS2. e expression levels of
FLS2, CHI1, CHI4, and F3’5’H5 were consistent with the
expression trend of SRM1(MYB) (Fig.6D and F), indicat-
ing the up-regulation of FLS2, CHI1, CHI4, and F3’5’H5
by SRM1(MYB).
Discussion
Most alkaloids are known for their bitterness. Stud-
ies had shown that the bitterness of theacrine surpasses
that of caffeine, suggesting that theacrine was a key com-
pound responsible for the bitterness of Yunnan kucha
and crude Pu-erh tea (Pt) [37]. In this study, AXKC tea
leaves exhibited higher theacrine content, while TGY and
FDDB showed barely detectable levels, consistent with
previous findings [21]. Additionally, AXKC leaves had
elevated levels of EGCG and EGCG3"Me, particularly
EGCG, which was significantly higher than in the other
two cultivars. is indicates a higher bitter compound
accumulated in AXKC leaves. ese bitter tastes can
stimulate the body’s oral secretions, promote digestion,
and increase appetite [5]. AXKC is rich in theacrine and
EGCG3"Me, suggesting it may have potential superior
health benefits compared to other tea varieties. ese
compounds are also key contributors to the flavor of tea,
warranting further study.
Relationship between theacrine content and gene/enzyme
expression
SAMS is one of the key enzymes in the purine alkaloid
metabolic pathway and acts as a methyl- donor in the
synthesis of theacrine and other purine alkaloids biosyn-
thesis [17]. e expression levels of SAMS3 and the cor-
responding enzymes were upregulated in ‘Anxi kucha’
leaves, and the expression trend was consistent with the
theacrine content. is was consistent with the result
that the theacrine content was significantly positively
correlated, further indicating that it had an important
contribution to the synthesis of theacrine. Related studies
have shown that blocking of IMPDH activity with riba-
virin inhibited caffeine biosynthesis [38]. e expression
abundance level of IMPDH enzyme was consistent with
the purine alkaloid content of the three tea varieties, and
the IMPDH enzyme had a very significant correlation
with the theacrine content. TCS is a class of N-methyl-
transferase that catalyzes the methylation of N-1 and N-3
in tea plant. Previous studies have pointed out that TCS1
plays a crucial role in the methylation of xanthosine at
the 1-N position in caffeine biosynthesis [39]. At both the
protein and transcriptional levels, TCS1 was upregulated
in AXKC leaves, which may explain its moderate caffeine
content. Recently, researchers identified three N-meth-
yltransferases (NMTs), including a N-methyltransferase,
CkTcS, as a key N9-methyltransferase that acted only
on 1,3,7-trimethyluric acid but not on caffeine, and was
involved in the biosynthesis of theacrine [6]. In ‘Anxi
kucha’ leaves, the expression level of NMT2 enzyme was
higher and it played a role in up-regulating expression.
At the protein and mRNA levels, the expression trends
of SAMS3, APRT1, IMPDH, and TCS1 were consistent
with the theacrine content in AXKC, TGY, and FDDB
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Zhu et al. BMC Plant Biology (2025) 25:663
Fig. 3 (See legend on next page.)
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Page 11 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
leaves, and their expression levels were higher in AXKC
leaves. e results of the transcriptome-proteome-
metabolome joint analysis showed (Fig. 3G) that there
was a significant correlation between these enzymes and
theacrine content. is may be the reason why more
theacrine accumulates in AXKC leaves.
Relationship between EGCG3"Me content and gene/
enzyme expression
e accumulation and composition of catechins were
highly correlated with the expression levels of bio-
synthetic genes [40]. Research has shown that CsCHI,
CsF3H, CsDFR, CsANS, and CsANR are key regulatory
genes for catechin content [41]. F3’H and F3’5’H are key
enzymes involved in forming dihydroxylated and trihy-
droxylated catechins [40]. e protein abundance of FLS
is positively correlated with the total concentration of fla-
vonol derivatives [42]. Catechin epimerization is mainly
catalyzed by the enzymes LAR, ANS, and ANR [43]. e
accumulation of EGCG3"Me is positively correlated with
the expression levels of CsDFR, CsLAR and CsCCoAOMT
[18].
At the protein and mRNA levels, CHI1 and CHI2 were
highly expressed in AXKC and TGY leaves. Meanwhile,
there was a significant positive correlation between the
abundance levels of CHI1 and CHI2 enzymes and EGCG
and EGCG3"Me contents. is indicates that the active
regulation of CHI1 and CHI2 enzymes promotes the syn-
thesis of EGCG and EGCG3"Me in targeted metabolites.
e regulation of CHI enzyme provides intermediates for
the subsequent synthesis of various catechins [41]. From
these intermediates, several side branches are formed,
each producing different categories of flavonoids. F3’5’H
catalyzes dihydrokaempferol. ere are two other
branches: one is the F3’H catalysis-mediated branch for
biosynthesis of C (catechin), EC (epicatechin), querce-
tin and its glycosyl derivatives. e other is the FLS-
mediated branch for the biosynthesis of kaempferol and
its glycosyl derivatives. In Fig. 5, the protein and tran-
scriptional expression levels of F3’H were much lower
than those of F3’5’H and FLS, suggesting that the F3’H-
mediated branch is not the dominating branched path-
way for flavonoid biosynthesis in tea leaves [44]. Among
the targeted metabolites, the contents of C and EC were
relatively small compared with other catechins (such as
EGCG and ECG). FLS, with high levels of mRNA and
protein, boosted the biosynthesis of flavonol glycosides.
ere is a significant positive correlation between FLS2,
which has a higher enzyme abundance level, and EGCG
and EGCG3"Me content.
Parallel to the biosynthesis of catechin compounds
in tea leaves, at the protein and mRNA levels, LAR and
CCoAOMT were highly expressed in AXKC leaves.
In the correlation analysis with targeted metabolites
(Fig. 4H), there was a highly significant positive cor-
relation between LAR1 and the contents of EGCG and
EGCG3"Me. In the real-time fluorescence quantitative
PCR results, the correlation coefficients of LAR1 and
CCoAOMT3 genes were both above 0.9, indicating high
reliability of the results.
In general, CHI1, CHI2, FLS2, and LAR1, which were
highly expressed at both protein and mRNA levels, play
crucial roles in the flavonoid biosynthesis pathway. ese
genes and corresponding enzymes are the primary con-
tributors to catechin biosynthesis.
Theacrine and EGCG3"Me transcription factor regulation in
‘Anxi Kucha’
TFs regulate gene expression by specifically binding to
promoters in downstream genes, modulating the bio-
synthesis of metabolites [18]. Many TFs are known to be
involved in purine metabolism and flavonoid biosynthe-
sis across different plants [18]. is study focused on TFs
related to purine metabolism and flavonoid biosynthesis
pathways. bHLH, MYB and ERF are related to the bio-
synthesis of purine alkaloids [36]. e expression trends
of TCS2 targeted by MYB4 and bHLH74 in the protein
group were consistent, with both upregulated. MYB4,
CSTF50 (ERF), and ERF4 upregulate the expression of
IMPDH enzymes. In the correlation analysis of targeted
metabolites, IMPDH and TCS2 enzymes were extremely
significantly related to theacrine content.
ree R2R3-MYB proteins, including MYB11, MYB12,
and MYB111, regulate flavonol biosynthesis by activating
upstream genes such as CHI and FLS, while the MYB-
bHLH-WD40 (MBW) complex activates the downstream
genes in flavonoid pathway, regulating the biosynthesis of
procyanidin and anthocyanins [45]. SRM1 (MYB) posi-
tively regulated CHI1 and FLS2, and MYB4 and BHLH74
jointly positively regulated FLS2. eir expression lev-
els at the protein and transcriptional were consistent
with the trend of EGCG3"Me in the three tea varieties,
(See gure on previous page.)
Fig. 3 Joint analysis of proteome, transcriptome, and metabolome. (A) DAPs shared by the three varieties in the Venn diagram analysis. (B) DEGs shared
by the three germplasms in the Venn diagram analysis. Transcriptome-Proteome nine-quadrant diagram. (C) FDDB vs. TGY, (D) FDDB vs. AXKC, (E) TGY vs.
AXKC. The numbers in the nine-quadrant diagram are common mRNA and protein numbers, where red represents protein. (F) Enrichment analysis of the
top 30 KEGG in the 6th, 8th, and 9th quadrants of the transcriptome-protein nine-quadrant diagram, the purine metabolism and avonoid biosynthesis
pathways are highlighted in bold and red. Heat map of the correlation between enzymes upregulated in both the transcriptional and protein levels and
targeted metabolites. (G) In the purine metabolism pathways. (H) In the avonoid biosynthesis pathways. Statistical signicance: P > = 0.05 no mark , “*”
indicates the signicant dierence between the data (0.01 < P < 0.05), “**” indicates the signicant dierence between the data (0.001 < P < 0.01), “***”
indicates the signicant dierence between the data Signicance (P < = 0.001). FDDB: ‘Fudingdabaicha’, TGY: ‘Tieguanyin’, AXKC: ‘Anxi kucha’
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
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Zhu et al. BMC Plant Biology (2025) 25:663
Fig. 4 (See legend on next page.)
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Page 13 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
and their expression levels were relatively high. In the
correlation analysis of targeted metabolites, CHI1 and
FLS2 enzymes were highly significantly correlated with
EGCG3"Me content. ey significantly contributed to
the accumulation of EGCG3"Me in AXKC.
Compared with the same types of TFs transcripts
reported in tea plants, we identified fewer bHLH, MYB,
WRKY, and ERF isoforms, which may be due to the limi-
tations of current protein identification technology [45].
MYB4, bHLH74, ERF4 and CSTF50 (ERF) positively
regulated IMPDH and TCS2, which positively affected
theacrine synthesis in AXKC SRM1 (MYB) positively
regulated CHI1 and FLS2, and MYB4 and BHLH74
jointly positively regulated FLS2 to promote the accu-
mulation of EGCG3"Me in AXKC. TFs played a key role
in tea plant metabolism, affecting multiple biosynthetic
pathways by regulating gene expression.
(See gure on previous page.)
Fig. 4 Purine metabolic pathway. The pathway consists of three main parts: the xanthosine synthesis pathway, the caeine synthesis pathway and the
theacrine synthesis pathway. Enzyme abbreviations are as follows: SAMS (S-adenosylmethionine synthetase); ADK (adenosine Kinase); APRT (adenine
phosphoribosyltransferase); AMPD (adenosine monophosphate deaminase); IMPDH (inosine monophosphate dehydrogenase); 5’-NT (5’-nucleotidase);
TCS (3-NMT and 1-NMT, tea caeine synthase); CYP1A2 (cytochrome P450 family 1 subfamily apolypeptide 2); 9-NMT (9-methyltransferase); ALN (allanto-
inase); URE (urease). FDDB: ‘Fudingdabaicha’, TGY: ‘ Tieguanyin’, AXKC: ‘Anxi kucha’
Fig. 5 Flavonoid biosynthesis pathway. Abbreviations of enzymes are as follows: PAL, phenylalanine ammonia-lyase; C4H, cinnamic acid 4-hydroxylase;
4CL, 4-coumarate-CoA ligase; CHS, chalcone synthase; CHI, chalcone isomerase; F3H, avanone 3-hydroxylase; F3’5’H, avonoid 3’,5’-hydroxylase; F3’H,
avonoid 3’-hydroxylase; FLS, avonol synthase; DFR, dihydroavanol 4-reductase; ANS, anthocyanidin synthase; ANR, anthocyanidin reductase; LAR, leu-
cocyanidin reductase; FGS, avan-3-ol gallate synthase; CCoAOMT, caeoyl-CoA 3-O-methyltransferase. FDDB: ‘Fudingdabaicha’, TGY: ‘Tieguanyin’, AXKC:
‘Anxi kucha’
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Zhu et al. BMC Plant Biology (2025) 25:663
In conclusion, the integrated transcriptome-proteome-
metabolome analysis showed that SAMS3, APRT1,
IMPDH and TCS1 were the key rate-limiting enzymes
promoting theacrine synthesis. Meanwhile, CHI1, CHI2,
FLS2 and LAR1 were the key rate-limiting enzymes pro-
moting EGCG3"Me synthesis. e analysis of transcrip-
tion factors revealed that MYB4 and bHLH74 positively
regulated the synthesis of theacrine and EGCG3"Me.
AXKC is a brand-new and unique tea variety, provid-
ing valuable experimental materials for the subsequent
cultivation of varieties rich in functional ingredients
and the improvement of tea quality. Multi-omics analy-
sis methods help us combine information from mul-
tiple species to explore plant metabolic pathways and
their dynamic development. We found that the mutual
regulation between transcription factors and enzymes
plays an important role in the synthesis of theacrine and
EGCG3"Me, which provides a comprehensive explana-
tion for the complex network of metabolite biosynthesis
and provides a rich data basis for molecular breeding,
Fig. 6 Transcription factor analysis. Expression levels of targeted genes in the purine metabolism pathway in the proteome and transcriptome. (A)
Gene expression heatmap. (C) Protein heat map expression. Expression levels of targeted genes in the avonoid biosynthesis pathway in the proteome
and transcriptome. (D) Transcriptomic expression. (F) Protein expression. (B) Transcription factors that upregulate the purine metabolism pathway. (E)
Transcription factors that upregulate the avonoid biosynthesis pathway. Orange icons represent transcription factors, and purple icons represent target
genes. In the expression heat map, rectangles represent transcript levels (DEGs), and the circles represented protein levels (DAPs). FDDB: ‘Fudingdabaicha’,
TGY: ‘Tieguanyin’, AXKC: ‘Anxi kucha’
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Page 15 of 16
Zhu et al. BMC Plant Biology (2025) 25:663
which is of great significance for the cultivation of high-
quality tea germplasm. At the same time, the exploration
of this tea varieties also provides us with more excel-
lent genetic resources for synthesizing theacrine and
EGCG3"Me, which will lay a research foundation for the
subsequent enzyme engineering synthesis of theacrine
and EGCG3"Me.
Supplementary Information
The online version contains supplementary material available at h t t p s : / / d o i . o r
g / 1 0 . 1 1 8 6 / s 1 2 8 7 0 - 0 2 5 - 0 6 6 9 1 - 8.
Supplementary Material 1
Author contributions
Y.Z., M.G., W.Y., and N.Y. designed the research. L.L., S.G., Y.Z., Z.C., and J.Z.
collected experimental samples. Y.Z. performed experiments and wrote the
manuscript. S.W., W.G. analyzed the data. M.G., W.Y., S.W., and N.Y. provided
valuable suggestions. W.Y., H.L., and N.Y. provided project funding. W.Y., N.Y.
supervised and revised the manuscript. All authors reviewed and approved
the manuscript.
Funding
This work was supported by the Open Fund of Collaborative Innovation
Center of Chinese Oolong Tea Industry (2024W01), Major Special Project of
Scientic and Technological Innovation on Anxi Tea (AX2021001), Special
Fund for Science and Technology Innovation of Fujian Zhang Tianfu Tea
Development Foundation (FJZTF01), and the Agricultural Guidance Project of
Fujian Provincial Science and Technology Department (2021N0024).
Data availability
Transcriptome data have been uploaded to the National Center for
Biotechnology Information h t t p s : / / s u b m i t . n c b i . n l m . n i h . g o v / s u b s / s r a / via the
SRA partner repository under the data set identier PRJNA1179900.The mass
spectrometry proteomics data have been deposited to the ProteomeXchange
Consortium via the PRIDE partner repository with the dataset identier
PXD062468 ( h t t p s : / / w w w . e b i . a c . u k / p r i d e / a r c h i v e / p r o j e c t s / P X D 0 6 2 4 6 8 / p r i v a
t e).
Declarations
Ethics approval and consent to participate
All authors conrm that all the methods and experiments in this study,
including the collection of plant material, complied with the institutional,
national, and international guidelines and legislation.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Clinical trial number
Not applicable.
Received: 10 December 2024 / Accepted: 7 May 2025
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