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Article
Identification of Medicinal Compounds of Fagopyri Dibotryis
Rhizome from Different Origins and Its Varieties Using
UPLC-MS/MS-Based Metabolomics
Chengcai Zhang 1 , Yang Jiang 2 , Changzheng Liu 1 , Linyuan Shi 1 , Jintong Li 3 , Yan Zeng 3 , Lanping Guo 1, *
and Sheng Wang 1,2, *

1 State Key Laboratory Breeding Base of Dao-Di Herbs, National Resource Center for Chinese Materia Medica,
China Academy of Chinese Medical Sciences, Beijing 100700, China
2 Dexing Research and Training Center of Chinese Medical Sciences, Dexing 334220, China
3 China National Traditional Chinese Medicine, Co., Ltd., Beijing 100191, China
* Correspondence: lpguo@icmm.ac.cn (L.G.); wangsheng@nrc.ac.cn (S.W.)

Abstract: Fagopyrum dibotrys, being native to southwest China, is widely distributed in Yunnan,
Guizhou Provinces and Chongqing City. However, the quality of medicinal materials growing in
different origins varies greatly, and cannot meet the market demand for high-quality F. dibotrys. In
this study, 648 metabolites were identified, and phenolic compounds of F. dibotrys from different
origins were clearly separated by principal component analysis (PCA). Our results suggested that
the medicinal differences of F. dibotrys from different origins can be elucidated via the variations
in the abundance of the phenolic and flavonoid compounds. We found that the epicatechin, total
flavonoids and total tannin content in Yunnan Qujing (YQ) and Yunnan Kunming (YK) were higher
than those in Chongqing Shizhu (CS), Chongqing Fuling (CF) and Guizhou Bijie (GB), suggesting that
Citation: Zhang, C.; Jiang, Y.; Liu, C.;
Yunnan Province can be considered as one of the areas that produce high-quality medicinal materials.
Shi, L.; Li, J.; Zeng, Y.; Guo, L.; Wang,
Additionally, 1,6-di-O-galloyl-β-D-glucose, 2,3-di-O-galloyl-D-glucose and gallic acid could be used
S. Identification of Medicinal
as ideal marker compounds for the quality control of F. dibotrys from different origins caused by
Compounds of Fagopyri Dibotryis
Rhizome from Different Origins and
metabolites, and the F. dibotrys planted in Yunnan Province is well worth exploiting.
Its Varieties Using UPLC-MS/MS-
Based Metabolomics. Metabolites Keywords: Fagopyrum dibotrys; UPLC-MS/MS; phenolic metabolites; PCA; medicinal differences
2022, 12, 790. https://doi.org/
10.3390/metabo12090790

Academic Editor: Hirokazu

1. Introduction
Kawagishi
Fagopyrum dibotrys, also known as golden buckwheat in China, is a perennial herb
Received: 31 July 2022 that belongs the Polygonaceae family of the genus Fagopyrum [1]. As an important tradi-
Accepted: 22 August 2022 tional Chinese medicine (TCM) with high medicinal value, Fagopyri Dibotryis Rhizome
Published: 25 August 2022
(FDR) is often used for treating snakebite, traumatic injuries, lung diseases, inflammation,
Publisher’s Note: MDPI stays neutral dysmenorrhea, lumbago, rheumatism, cancer, etc.; in particular, it has a reputation as
with regard to jurisdictional claims in being effective in treating lung cancer [2,3]. A considerable number of pharmacological
published maps and institutional affil- experiments, both in vivo and in vitro, have validated that FDR possesses anti-diabetic, an-
iations. titumor, anti-inflammatory, antioxidant, hepatoprotective, etc., activities [4]. Wild F. dibotrys
is native to southwest China, and is widely distributed in the following regions: south of
the Yellow River, the middle and lower reaches of the Yangtze River and the Pearl River
Basin (21~32◦ N; 97~121◦ E). F. dibotrys grown in different ecological environments result
Copyright: © 2022 by the authors.
in great changes in rhizome morphology and active-ingredient content. Meanwhile, the
Licensee MDPI, Basel, Switzerland.
differences of origin of FDRs in the market has brought uneven quality, which seriously
This article is an open access article
affects the clinical efficacy. In China, only certain FDRs that grow in specific geographic
distributed under the terms and
regions (Yunnan) can be used in Weimaining Jiao Nang, a Chinese medicine specifically
conditions of the Creative Commons
designed for the treatment of lung cancer. However, the exact compounds underlying this
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
origin variation of FDR are unknown.
4.0/).

Metabolites 2022, 12, 790. https://doi.org/10.3390/metabo12090790 https://www.mdpi.com/journal/metabolites

Metabolites 2022, 12, 790 2 of 14

Several grounds of bioactive chemical constituents, namely flavonoids, phenolics, tan-

nins, cyclitols and triterpenoids, have been isolated from F. dibotrys [5,6]. Among these, phe-
nolic compounds and flavonoids were generally acknowledged to be the main active com-
ponents of FDR, including hyperin, epicatechin, protocatechuic acid, 3-O-methylquercetin,
kaempferol, catechin, luteolin, rutin, procyanidin C1, etc. [7,8]. Flavonoids in FDR exhib-
ited remarkable biological functions in antioxidant, antidiabetic, anti-inflammatory and
antihypertensive aspects [5,6]. The condensed tannins isolated from FDR showed excellent
anti-tumor and antioxidant effects [9,10]. The content of epicatechin, a flavanol, is one of
the key indicators for quality assessment of FDR, in which the Chinese Pharmacopoeia
(2020) stipulates that epicatechin (C15H14O6) in FDR shall not be less than 0.030% [11].
Thus, a study of the detailed profile of metabolites in FDR would be important for compre-
hensively evaluating its medicinal value, explicating compounds underlying this original
variation and understanding its related efficacy. Metabolomics as a technology for the
simultaneous qualitative and quantitative analyses of all the metabolites in living beings
is introduced; this is widely employed in plant [12], medicine [13], food [14], microorgan-
ism [15] and other research fields because of its high efficiency, comprehensiveness and
accuracy. Metabolomics is focused on the quantification and identification of the changes
in metabolites due to environmental, planting or genetic factors. Yajun et al. analyzed the
differences of metabolic components of Lycii fructus in different production areas through
widely targeted metabolomics and found that climate factors have a great impact on the nu-
trition and medicinal quality of fruits of Lycium barbarum from different planting areas [16].
Jing et al. analyzed the differences of flavonoids in buckwheat leaves by metabolomics
and found that there were great differences [17]. To date, a comprehensive and systematic
study on the differences of chemical components of FDR from different habitats has not
been published. In the present research, ultra-performance liquid chromatography mass
spectrometry (UPLC-MS/MS), hierarchical clustering analyses (HCAs), PCA analyses and
orthogonal projections to latent structure discriminant analyses (OPLS-DA) were carried
out to study the differences of metabolites in FDR from different growing areas and find
their common differential metabolites. Our work provides valuable data for assessing the
medicinal value to guide the standardized planting of F. dibotrys.

2. Materials and Methods

2.1. Plant Materials
Fifteen rhizomes of two years Fagopyrum dibotrys were collected in the autumn (11–25
November 2020) from 5 different producing areas: Shizhu in Chongqing (CS), Fuling in
Chongqing (CF), Qujing in Yunnan (YQ), Kunming in Yunnan (YK) and Bijie in Guizhou
(GB). We chose 3 sites as replicates for each producing area, and 10 individuals were
collected in each site as one sample for analysis after being dried at 40 ◦ C and powdered.
Detailed information of samples is displayed in Table S1.

2.2. Quantification of Epicatechin, Total Flavonoids and Total Tannins

The contents of epicatechin in FDRs from five growing areas were determined via high
performance liquid chromatography (HPLC). In detail, sample processing was as follows:
dried sample was ground into powder, then filtered through a sieve with 250 ± 9.9 µm
diameter pore size (a Size No. 4 sieve defined by the Chinese Pharmacopoeia (2020) [11].
Approximately 4.0000 g of precisely measured sample powder was placed into a conical
flask; then, 100 mL of precisely measured 10% (v:v) acetonitrile was carefully mixed with
the sample powder in the flask. The flask was then sealed with the plug and its total weight
was measured as the initial weight. The mixture was then allowed to stand for one hour
and subsequently boiled for one hour before being allowed to stand again until it cooled
down to room temperature. The weight was measured again and 10% (V:V) acetonitrile
was added into the sample mixture to the initial weight. The mixed sample crude extract
was filtered twice with a 0.2 µm PVDF filter to acquire the final sample extract to be
subjected to HPLC analyses. A 4 µL amount of the filtered sample exact was injected into
Metabolites 2022, 12, 790 3 of 14

an HPLC system (Alliance 2695, Waters Corp., Milford, CN, USA) with a Symmetry C18
column (250 mm × 4.6 mm, 5 µm particle size); sample separation was performed with a
gradient elution (V:V) program using acetonitrile (chromatographic purity, Aladdin) and X
M phosphate buffer saline (pH = 3.0) as the mobile phase at a constant column temperature
of 50 ◦ C following the gradient below: 8% acetonitrile for 25 min; 8% to 9% acetonitrile for
20 min; 9% to 10% acetonitrile for 15 min; 10% to 8% acetonitrile for 5 min. Detection of
separated sample was performed with a photo-diode array detector under 280 nm.
As for total flavonoids and total tannins, the content of total flavonoids was indicated
by the absorbance value of the extract solution of FDR at 282 nm. Total tannin content was
determined with insoluble polyvinyl-polypyrrolidone (PVPP), which binds tannins [17].
Briefly, 1 mL of extract (1 mg/mL) was mixed with 100 mg of PVPP, vortexed, kept for
15 min at 4 ◦ C and then centrifuged for 10 min at 3000 rpm.

2.3. Sample Preparation for Metabolomic Analysis

Fifteen FDRs from five different producing areas were handled via vacuum freeze-
drying (Scientz-100F, ANPEL, Shanghai, China). Then, the freeze-dried FDR sample was
ground into fine powder via a mixer mill (MM 400, Retsch), and the setting parameters
of the grinding instrument were: 30 Hz, 1.5 min. Then, 100 mg of lyophilized powder
of FDR was weighed and dissolved with 1.2 mL 70% methanol solution. After that, the
extract solution of FDR was vortexed for 30 s every 30 min, repeatedly 6 times in total,
and then placed at 4 ◦ C inside a refrigerator overnight. After centrifugation at 12,000× g
rpm for 10 min, supernatant was collected as the crude extract. The extract samples were
then filtrated by SCAA-104 with a 0.22 µm pore size (ANPEL, Shanghai, China) before
UPLC-MS/MS analysis. The conditions and methods of UPLC-MS/MS can be found in
Shang, X et al. [18] (details provided in Supplementary Materials Sections S2.3.1 and S2.3.2).

2.4. Multivariate Statistical Analysis

The qualitative and quantitative analysis of 15 FDRs from five different producing
areas was performed according to the method of Zhang, J. et al. [19] and Fraga, C et al. [20]
(details provided in Supplementary Materials Section S2.4.1). Metabolite data of F. dibotrys
from 15 samples were used for unsupervised PCA, HCA and supervised multiple regression
OPLA-DA using the Met ware Cloud. The results of HCA of the metabolites and samples
were presented as heatmaps with dendrograms. The differentially accumulated metabolites
(DAMs) were identified based on the fold-change (Log2FC ≥ 2 or ≤ 0.5) and variable
importance in project scores (VIP ≥ 1), and the VIP values were extracted from OPLS-
DA results. The identified 187 phenolic metabolites were annotated according to the
Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.kegg.jp/kegg/
compound/ (accessed on 24 June 2022)) with a p-value < 0.01, and the pathways with
differentially phenolic metabolites mapped were then fed into metabolite sets enrichment
analysis (MSEA).

3. Results
3.1. Determination of Epicatechin, Total Flavonoids and Total Tannin in FDR from Different
Producing Areas
In this study, FDRs from five different producing areas—Shizhu in Chongqing (CS),
Fuling in Chongqing (CF), Qujing in Yunnan (YQ), Kunming in Yunnan (YK) and Bijie in
Guizhou (GB)—were collected for analysis. Considered active components, the content of
epicatechin, total flavonoids and total tannin from different producing areas were investi-
gated. As shown in Figure 1, contents of epicatechin in YQ and YK were significantly higher
(p < 0.05) than in CF and GB. Among them, contents of epicatechin of YK is the highest
(0.113%); this is considered to be the best quality according to the Chinese Pharmacopoeia;
GB has the lowest epicatechin content of 0.038%. We used Abs at 280 nm to indicate the
relative amount of total flavonoids of FDR samples; the flavonoid content of YK and YQ
are significantly higher (p < 0.05) than that of GB, CS and CF, whereas YK is slightly higher
 highest (0.113%); this is considered to be the best quality according to the Chinese Phar-
macopoeia; GB has the lowest epicatechin content of 0.038%. We used Abs at 280 nm to
indicate the relative amount of total flavonoids of FDR samples; the flavonoid content of
Metabolites 2022, 12, 790 4 of 14
YK and YQ are significantly higher (p < 0.05) than that of GB, CS and CF, whereas YK is
slightly higher than that of YQ, but the difference was not significant. Similarly, the total
tannin content of YQ was significantly higher than that of GB, CS and CF. Nevertheless,
than
therethat
wasof YQ,a but
only the difference
tendency wasthat
higher than not of
significant.
YK, which Similarly, the total
is also slightly tannin
rich content
in content of
of YQ was significantly higher than that of GB, CS and CF. Nevertheless, there
tannins compared to CS, CF and GB. In addition, the cross-sectional colors of YK, CS and was only a
tendency higher than that of YK, which is also slightly rich in content of tannins
GB rhizomes were reddish brown, light red and yellow white, which were consistent with compared
to
theCS, CF and
change GB.ofIntotal
trend addition, the cross-sectional
flavonoid content (Figurecolors of YK, results
S2). These CS andrevealed
GB rhizomes were
a clear as-
reddish brown, light red and yellow white, which were consistent with the change
sociation of chemical composition with distinct FDRs in different producing areas, which trend of
total flavonoid content (Figure S2). These results revealed a clear association
provides representative materials for identification of differentially accumulating metab-of chemical
composition
olites relatedwith distinct FDRs in different producing areas, which provides representative
to origin.
materials for identification of differentially accumulating metabolites related to origin.

Figure 1.
Figure 1. Content
Content of of active
active components
componentsininFagopyri
FagopyriDibotryis
DibotryisRhizome
Rhizome(FDR)
(FDR) from
from different
different produc-
producing
ing areas. (a) Epicatechin content of FDRs. (b) Total flavonoid content of FDRs. (c) Total tannin con-
areas. (a) Epicatechin content of FDRs. (b) Total flavonoid content of FDRs. (c) Total tannin content of
tent of FDRs. The a, b, c above the bar chart indicates the difference significance; and the two com-
FDRs. The a, b, c above the bar chart indicates the difference significance; and the two comparison
parison groups with no significant difference were marked with the same letter; The significance
groups with
value was a >noabsignificant
> b. difference were marked with the same letter; The significance value was a
> ab > b.
3.2. Metabolic Profiling of FDR
3.2. Metabolic Profiling of FDR
Tobetter
To betterunderstand
understand thethe metabolic
metabolic differences
differences from different
from different origins
origins of of FDR,
FDR, the the
metabolic
metabolic profiles of FDRs from five producing areas were constructed
profiles of FDRs from five producing areas were constructed based on UPLC-MS/MS analysis.based on UPLC-
MS/MS
As analysis.
a result, As a result,(Table
648 metabolites 648 metabolites (Table S2)
S2) were detected, were detected,
including including
120 flavonoids, 120 fla-
7 tannins,
9vonoids,
quinones,7 tannins, 9 quinones,
131 phenolic acids, 50131 phenolic
amino acids,
acids (and 50 amino acids
derivatives), (and derivatives),
30 nucleotides (and deriva-30
nucleotides (and derivatives), 21 lignans and coumarins, 49 alkaloids, 20 terpenoids,
tives), 21 lignans and coumarins, 49 alkaloids, 20 terpenoids, 48 organic acids, 94 lipids and 48
organic
69 acids,compounds
additional 94 lipids and 69did
that additional compounds
not fit into these 11 mainthat classes
did not(Figure
fit into2a).
these
The11results
main
classes (Figure 2a). The results show that secondary metabolites accounted
show that secondary metabolites accounted for a relatively high proportion in metabolic for a relatively
high proportion
profiles for FDRsinofmetabolic profiles for
different origins. TheFDRs of heatmap
cluster different of
origins. The clustereffectively
the metabolites heatmap
of the metabolites
demonstrated effectively
similarity among demonstrated
the compounds similarity amongrepeats,
of biological the compounds of biological
and differences in the
repeats, and differences
components among the FDRin thesamples
components
from among
differentthe FDR samples
origins from different origins
(Figure 2b).
(Figure 2b).
3.3. Differential Analysis of Phenolic Compounds Based on PCA
Natural phenolic compounds have an outstanding role in preventing and treating
cancer. Thus, five phenolic compounds (flavonoid, phenolic acid, quinones, tannins, and
lignans and coumarins) likely contributing to the medicinal quality were subjected to
PCA. The PCA results showed that the first two principal components of FDRs of different
origins could explain 54.9% of variance contribution value; PC1 and PC2 were 43.1% and
11.8%, respectively (Figure 3). In the PCA score plot, CS, CF, GB and YK, YQ and quality
control (QC) were clearly separated, and the biological repeats of QC were closely clustered,
showing the repeatability of the experiments and reliability of our data. The results of PCA
suggested that five separated clusters were associated with different metabolite profiles of
FDR from different producing areas, and CS, CF and GB belong to the non-Yunnan (NYN)
group and YK and YQ belong to the Yunnan (YN) group.
Metabolites2022,
Metabolites 12,x790
2022,12, FOR PEER REVIEW 5 5ofof15
14

Figure 2. (a) Statistics of metabolites in all samples of FDR. (b) Heat map showing the relative variatons
Figure 2. (a) Statistics of metabolites in all samples of FDR. (b) Heat map showing the relative
in the metabolic profiles of different origins of FDRs. (a) Pie chart visualization. The lipids, organic
variatons in the metabolic profiles of different origins of FDRs. (a) Pie chart visualization. The
acids, amino acids and derivatives, and nucleotides and derivatives of the exploded pie diagram are
lipids, organic
primary acids,(b)
metabolites. amino
Eachacids andfrom
sample derivatives,
differentand nucleotides
origins and with
is visualized derivatives of the and
one column, exploded
each
metabolite of FDRs of different origins is represented by a raw element. Color gradient indicateswith
pie diagram are primary metabolites. (b) Each sample from different origins is visualized the
one column, level
accumulation and ofeach metabolite
metabolite of FDRs
content of different
(red: high origins
abundance; blue:islow
represented by a raw element.
abundance).
Metabolites 2022, 12, x FOR PEER REVIEW
Color gradient indicates the accumulation level of metabolite content (red: high abundance; blue:
3.3.
lowDifferential
abundance).Analysis of Phenolic Compounds Based on PCA
Natural phenolic compounds have an outstanding role in preventing and treating
cancer. Thus, five phenolic compounds (flavonoid, phenolic acid, quinones, tannins, and
lignans and coumarins) likely contributing to the medicinal quality were subjected to
PCA. The PCA results showed that the first two principal components of FDRs of different
origins could explain 54.9% of variance contribution value; PC1 and PC2 were 43.1% and
11.8%, respectively (Figure 3). In the PCA score plot, CS, CF, GB and YK, YQ and quality
control (QC) were clearly separated, and the biological repeats of QC were closely clus-
tered, showing the repeatability of the experiments and reliability of our data. The results
of PCA suggested that five separated clusters were associated with different metabolite
profiles of FDR from different producing areas, and CS, CF and GB belong to the non-
Yunnan (NYN) group and YK and YQ belong to the Yunnan (YN) group.

Figure 3. PCA ofFigure 3. PCA

the relative of the relative
differences differences
in phenolic in phenolic
compounds compounds
of FDRs of FDRsproducing
from different from different pro
areas.(QC)
areas. Quality control Quality control
samples (QC)by
mixed samples mixed byofequal
equal volumes volumes
all FDR of all FDR rhizomes.
rhizomes.

3.4. Differential 3.4.

Analysis of Phenolic
Differential Compounds
Analysis Based
of Phenolic on OPLS-DA
Compounds Based on OPLS-DA
To further illustrate
To further illustrate the differences of 187 phenolicOPLS-DA
the differences of 187 phenolic compounds, compounds,wasOPLS-DA
per- wa
formed in the comparison group of FDRs from different origins. The OPLS-DA analysis
formed in the comparison group of FDRs from different origins. The OPLS-DA is an
a multivariate statistical analysisstatistical
is a multivariate method with supervised
analysis methodpattern recognition,
with supervised whichrecognition,
pattern can
can effectively eliminate the effects unrelated to the study. Subsequently, high pre
bility (Q2) of the OPLS-DA models was observed in the 10 comparison groups. The r
of Figure 4 showed that the OPLS-DA models of all comparison groups were reliab
stable (R2X > 0.8, Q2 > 0.9), which could be used to screen for even more differentia
 Figure 3. PCA of the relative differences in phenolic compounds of FDRs from different producing
areas. Quality control (QC) samples mixed by equal volumes of all FDR rhizomes.

3.4. Differential Analysis of Phenolic Compounds Based on OPLS-DA

Metabolites 2022, 12, 790 To further illustrate the differences of 187 phenolic compounds, OPLS-DA was6per- of 14
formed in the comparison group of FDRs from different origins. The OPLS-DA analysis
is a multivariate statistical analysis method with supervised pattern recognition, which
can effectively eliminate the effects unrelated to the study. Subsequently, high predicta-
effectively eliminate the effects unrelated to the study. Subsequently, high predictability
bility (Q2) of the OPLS-DA models was observed in the 10 comparison groups. The results
(Q2 ) of the OPLS-DA models was observed in the 10 comparison groups. The results of
of Figure 4 showed that the OPLS-DA models of all comparison groups were reliable and
Figure 4 showed that the OPLS-DA models of all comparison groups were reliable and
stable (R2X > 0.8, Q2 > 0.9), which could be used to screen for even more differential phe-
stable (R2 X > 0.8, Q2 > 0.9), which could be used to screen for even more differential
nolic metabolites (DPMs).
phenolic metabolites (DPMs).

Figure 4. OPLS-DA score map of phenolic compounds of FDRs from different producing areas. (a–j)
Figure 4. OPLS-DA score map of phenolic compounds of FDRs from different producing areas.
OPLS-DA model plots for the comparison group CS vs. CF, CS vs. GB, CS vs. YK, CS vs. YQ, CF vs.
(a–j)
GB, CFOPLS-DA model
vs. YK, CF plotsGB
vs. YQ, forvs.
theYK,
comparison group
GB vs. YQ CS vs.
and YK vs. CF,
YQ,CS vs. GB, CS vs. YK, CS vs. YQ, CF
respectively.
vs. GB, CF vs. YK, CF vs. YQ, GB vs. YK, GB vs. YQ and YK vs. YQ, respectively.

3.5. Differential Phenolic Analysis

We further performed DPM screening among all 187 phenolic compounds based on
the fold-change (Log2 FC ≥ 2 or ≤ 0.5) and variable importance in project (VIP ≥ 1) scores.
The DPM results are shown as upset plots in detail (Figure 5 and Table S3). Among these,
there were five DPMs (four down-regulated and one up-regulated) in YQ compared to
YK, six between CS and CF (four down-regulated in CF), seven between CF and GB (five
down-regulated in GB), 15 between CS and GB (12 down-regulated in GB), 20 between
CS and YK (eight down-regulated in CS), 36 between CS and YQ (19 down-regulated in
CS), 24 between CF and YK (14 down-regulated in CF), 40 between CF and YQ (27 down-
regulated in CF), 26 between GB and YK (14 down-regulated in GB) and 50 between GB
and YQ (36 down-regulated in GB). The number of DPMs was the highest between the
samples collected in GB and YQ (50 DPMs in total); relatively high numbers of DPMs were
also identified between CF and YQ (40 DPMs), and CS and YQ (36 DPMs). In addition,
compared with the YN group (YQ, YK), most of the identified DPMs of the NYN group
(GB, CF) were down-regulated, whereas CS vs. YK was not. These results showed evident
differences in phenolic metabolites between samples collected in the YN and NYN groups.
In contrast, only five DPMs were identified between the samples from YK and YQ, reflecting
comparatively slight difference in phenolic metabolites among the samples from habitats
within Yunnan Province.
The DPMs were classified among different comparison groups in an upset plot (Figure 5).
Three common DSMs were shown amongst comparison groups CS vs. YQ, CF vs. YQ, GB
vs. YQ, CS vs. YK, CF vs. YK and GB vs. YK, of which 1,6-di-O-galloyl-β-D-glucose, 2,3-di-
O-galloyl-D-glucose and gallic acid were classified as phenolic acid. When comparing the
metabolite ion intensity between FDRs from the YN group (YQ, YK) and the NYN group
(GB, CF, and CS), we observed a significant increase in the content of 2,3-di-O-galloyl-D-
glucose, 1,6-di-O-galloyl-β-D-glucose and gallic acid in FDRs from the YN group (YQ, YK)
compared to those from the NYN group (GB, CF and CS) (Figure 6). The results showed
Metabolites 2022, 12, 790 7 of 14

Metabolites 2022, 12, x FOR PEER REVIEW 8 of 15

Metabolites 2022, 12, x FOR PEER REVIEW 8 of 15
that the three DPMs could be used as ideal chemical markers for the quality control of F.
dibotrys from different origins.

Figure
Figure 5. 5. Upset
Upset plot
plot ofof differentially
differentially accumulated
accumulated phenolic
phenolic metabolites
metabolites of FDRs from different ori-
Figure 5. Upset plot of differentially accumulated phenolic metabolites of of FDRs
FDRs from
from different
different ori-
origins.
gins. Venn
gins. Venn diagram
diagram and
and upset upset plot show
plot sets
showand sets and intersections
setsintersections
and intersections of different
of different comparison
comparison groups ofof
Venn diagram
FDRs. Refer and
to upset
Tong, B. plot
et show
al. [21] for legend description. of different comparison groupsgroups
of FDRs.
FDRs.to
Refer Refer
Tong, toB.
Tong,
et al.B.[21]
et al.
for[21] for legend
legend description.
description.

Figure
Figure
Figure 6.6.
6. TheThe
The total
total
total ionion
ion intensity
intensity ofof
of three
three
three classesofof
classes
classes ofphenolic
phenolic
phenolic metabolitesinin
metabolites
metabolites FDRs
in
FDRs FDRs from
from fromdifferent
different
different
producing
producing areas.
areas. (a)(a)
2, 2, 3-di-O-galloyl-D-glucose,
3-di-O-galloyl-D-glucose, (b) (b) 1,6-di-O-galloyl-β-D-glucose,
1,6-di-O-galloyl-β-D-glucose,
producing areas. (a) 2, 3-di-O-galloyl-D-glucose, (b) 1,6-di-O-galloyl-β-D-glucose, (c) gallic acid. (c) (c)
gallicgallic
acid.acid.
Bars
Bars represent
represent the sumtheofsum
ion of ion intensity
intensity of all of all metabolites
metabolites belonging
belonging to to
each each
class. class.
The
Bars represent the sum of ion intensity of all metabolites belonging to each class. The a, b, c above The
a, b, a,
c b, c
aboveabove
the
the
the bar
bar chart
chart indicates
indicates the difference significance; and the two comparison groups with no signifi-
bar chart indicates the the difference
difference significance;
significance; andandthethe
twotwo comparison
comparison groups
groups withwithnono signifi-
significant
cant
cant difference
difference were marked with the same letter; The significance value was a > b > c.
difference werewere
marked marked
with with the
the same same
letter;letter; The significance
The significance valuevalue
was awas
> b a> >c.b > c.

AApathway
pathwayenrichment
enrichmentanalysis
analysisofofKEGG
KEGGofof187
187phenolic
phenoliccompounds
compounds(Table
(TableS4)
S4)be-be-
tweenthe
tween theNYN
NYNand andYNYNgroups
groupswas
wasalso
alsoperformed.
performed.The Theenrichment
enrichmentanalysis
analysisresults
resultsofof
DPMs in NYN vs. YN were mainly enriched in ‘phenylpropanoid biosynthesis’
DPMs in NYN vs. YN were mainly enriched in ‘phenylpropanoid biosynthesis’ (8), (8),‘the
‘the
pathway of flavone and flavonol biosynthesis’ (11), ‘flavonol biosynthesis’ (17), ‘metabolic
pathway of flavone and flavonol biosynthesis’ (11), ‘flavonol biosynthesis’ (17), ‘metabolic
Metabolites 2022, 12, 790 8 of 14

In addition, nine DPMs (isorhamnetin-3-O-glucoside, isorhamnetin-7-O-glucoside (bras-

sicin), nepetin-7-O-glucoside, phloretin, apigenin-3-O-glucoside, luteolin-8-C-glucoside (ori-
entin), limocitrin-7-O-glucoside, fraxetin-7,8-di-O-glucoside and piperitol) can be observed
only among comparison groups of CS vs. YQ, CF vs. YQ and GB vs. YQ, and one DPM
(2-methoxybenzaldehyde) was observed only among comparison groups CS vs. YK, CF vs.
YK and GB vs. YK.
A pathway enrichment analysis of KEGG of 187 phenolic compounds (Table S4)
Metabolites 2022, 12, x FOR PEER REVIEW 9 of 15
between the NYN and YN groups was also performed. The enrichment analysis results of
DPMs in NYN vs. YN were mainly enriched in ‘phenylpropanoid biosynthesis’ (8), ‘the
pathway of flavone and flavonol biosynthesis’ (11), ‘flavonol biosynthesis’ (17), ‘metabolic
pathways’
pathways’(25)(25)and
and‘biosynthesis
‘biosynthesisofofsecondary
secondarymetabolites’
metabolites’(24)
(24)(Figure
(Figure7 7and
andTable
TableS5).
S5).
These
Theseresults
resultsshow
showthat
thatenvironmental
environmentaland andclimate
climatefactors
factorshave
haveaastrong
strongimpact
impacton onthe
the
biosynthesis
biosynthesisof ofthe
thesecondary
secondarymetabolites
metabolitesofofFDRs.
FDRs.The
Theflavonoid
flavonoidprofiles
profilesofofthe
theF.F.dibotrys
dibotrys
samples
samplesfrom
fromthe
thehabitats
habitatseither
eitherinside
insideor
oroutside
outsideYunnan
Yunnanprovince
provinceeach
eachhad
hadsignificance
significance
and distinct variance.
and distinct variance.

Figure
Figure7.7.Metabolic
Metabolicpathway
pathway enrichment analysis for
enrichment analysis for the
theNYN
NYNand
andYN
YNgroups
groupsdifferentially
differentially accu-
accumu-
mulated metabolites.
lated metabolites.

3.6.Metabolite
3.6. MetaboliteDifferences
Differencesamong
amongNYNNYNGroupGroupand
andYNYNGroup
Group
Wefocused
We focusedononclasses
classesof ofmetabolites
metaboliteslikely
likelyto
tobebemajor
majorcontributors
contributorsto tothe
themedicinal
medicinal
andnutritional
and nutritionalqualities
qualitiesamong
amongFDRsFDRsof ofthe
theNYN
NYNand andYNYNgroups.
groups.Based
BasedononLog2FC
Log2FC(fold
(fold
change)and
change) andVIP
VIPvalues,
values,we wescreened
screenedout out4444up-regulated
up-regulatedsubstances
substancesininthetheYNYNgroup
group
comparedto
compared tothe
theNYN
NYNgroup group(Figure
(Figure88and andTable
Table S6).
S6). In
Indetail,
detail,4141 phenolic
phenolicmetabolites
metabolites
presented comprise 12 phenolic acids, 24 flavonoids, two quinones
presented comprise 12 phenolic acids, 24 flavonoids, two quinones and three lignans and three lignansandand
coumarins. Of these, the majority of flavonoid phenolic acids were significantly
coumarins. Of these, the majority of flavonoid phenolic acids were significantly greater in greater in
the YN group than in the NYN group (Log 2 FC ≥ 2), whereas the
the YN group than in the NYN group (Log 2 FC ≥ 2), whereas the majority of quinones majority of quinones
andlignans
and lignansand
andcoumarins
coumarins exhibited
exhibited differences
differences (1(1 ≤ Log22FC
≤ Log FC ≤≤2),2),suggesting
suggestingthat
thatthese
these
phenolic metabolites are involved in the medicinal differences between
phenolic metabolites are involved in the medicinal differences between the YN group and the YN group
andNYN
the the NYN
group.group. Furthermore,
Furthermore, three primary
three primary differential
differential metabolitesmetabolites
comprising comprising
L-cyclo-
L-cyclopentylglycine, N-methyl-trans-4-hydroxy-L-proline
pentylglycine, N-methyl-trans-4-hydroxy-L-proline and L-asparagine were also and L-asparagine were also
identi-
identified; these are involved in the nutritional differences between the
fied; these are involved in the nutritional differences between the YN group and the NYN YN group and the
NYN group. These results showed that among the DAMs between
group. These results showed that among the DAMs between the F. dibotrys from Yunnan the F. dibotrys from Yun-
nannon-Yunnan
and and non-Yunnan habitats,
habitats, the majority
the majority werewere up-regulated
up-regulated in secondary
in the the secondary metabolites
metabolites of
of FDRs.
FDRs. Therefore,
Therefore, it could
it could be speculated
be speculated that that compared
compared withwith
primaryprimary metabolites,
metabolites, the
the bio-
synthesis of the secondary metabolites was more responsive to environmental factors.
This might be one of the reasons why herbs from different habitats would exert distinct
therapeutical effects; meanwhile, it places further importance on the geo-authenticity of
traditional Chinese medicinal plants.
Metabolites 2022, 12, 790 9 of 14

biosynthesis of the secondary metabolites was more responsive to environmental factors.

This might be one of the reasons why herbs from different habitats would exert distinct
Metabolites 2022, 12, x FOR PEER REVIEW 10 ofof15
therapeutical effects; meanwhile, it places further importance on the geo-authenticity
traditional Chinese medicinal plants.

Figure 8. Heatmap of differential metabolites from FDR samples of NYN group and YN group. Red
Figure 8. Heatmap of differential metabolites from FDR samples of NYN group and YN group. Red
colors show high abundance, whereas low abundance is presented by blue.
colors show high abundance, whereas low abundance is presented by blue.

4.4.Discussion
Discussion
SouthwestChina
Southwest Chinaisisananinternationally
internationallyrecognized
recognizedcenter
centerofofbuckwheat
buckwheatorigin,
origin,among
among
which the wild F. dibotrys resources in Yunnan, Guizhou and Chongqing are
which the wild F. dibotrys resources in Yunnan, Guizhou and Chongqing are the most con- the most con-
centrated [22–25]. F. dibotrys rhizomes have been used to develop different health
centrated [22–25]. F. dibotrys rhizomes have been used to develop different health products products
duetototheir
due theirabundant
abundantbioactive
bioactivephenolic
phenoliccompounds.
compounds.However,
However,most mostFDRs
FDRscirculating
circulatinginin
themarket
the marketofofmedicinal
medicinalmaterials
materialshave
havedifferent
differentorigins,
origins,and
andtheir
theirquality
qualityisisuneven.
uneven.TheThe
qualitydifference
quality differenceofofFDRs
FDRsgrown
growninindifferent
differenthabitats
habitatswill
willeventually
eventuallybebereflected
reflectedininthethe
terminalmetabolites
terminal metabolitesofofthe
themetabolic
metabolicpathway.
pathway.Thus,
Thus,this
thisstudy
studyaimed
aimedtotoprovide
provideevidence
evidence
ofofmetabolomics-based
metabolomics-basedmedicinal
medicinalcompound
compoundidentification
identificationof ofFDR
FDR from
from different
different origins.

4.1.
4.1.Metabolic
MetabolicProfiling
ProfilingofofFDR
FDRfromfromDifferent
Different Origins
Origins
ToTocomprehensively
comprehensivelyanalyze analyzethe themedicinal
medicinalvalues
valuesofofFDRs differentF.F.dibotrys-
FDRsinindifferent dibotrys-
producing
producing areas, the results of metabolome analysis showed that 648 metaboliteswere
areas, the results of metabolome analysis showed that 648 metabolites were
identified,
identified,including 120120
including flavonoids,
flavonoids,7 tannins, 9 quinones
7 tannins, and 131
9 quinones andphenolic acids, 50acids,
131 phenolic amino50
acids
aminoand derivatives,
acids 30 nucleotides
and derivatives, and derivatives,
30 nucleotides 21 lignans
and derivatives, and coumarins,
21 lignans 49 al-49
and coumarins,
kaloids, 20 terpenoids,
alkaloids, 20 terpenoids, 48 48
organic acids
organic acidsand 94 94
and lipids. Phenolic
lipids. Phenolic compounds,
compounds,flavonoids
flavonoids
(catechin
(catechinand andepicatechin), γ-aminobutyricacid
epicatechin),γ-aminobutyric acidandandterpenoids
terpenoidshavehavebeen
beenreported
reportedinin
FDRs
FDRs[26].
[26].InInour
ourstudy,
study,we wefound
foundthat
thatalkaloids,
alkaloids,organic
organicacids
acidsand
andlipids
lipidswere
werealso
alsoranked
ranked
ininFDRs; of F. dibotrys
FDRs; the metabolic profilings of F. dibotrys were further extended. In sofar
the metabolic profilings were further extended. In so farasaswe
we
know, our current study is the first metabolome report to differentiate varieties of F.
dibotrys from different origins. The establishment of the metabolite profiles of F. dibotrys
from different habitats is important for elucidating the differential therapeutical effects
and clinical values of FDR. Meanwhile, it is also important for further understanding the
Metabolites 2022, 12, 790 10 of 14

know, our current study is the first metabolome report to differentiate varieties of F. di-
botrys from different origins. The establishment of the metabolite profiles of F. dibotrys
from different habitats is important for elucidating the differential therapeutical effects
and clinical values of FDR. Meanwhile, it is also important for further understanding the
complex effect and underlying mechanisms of traditional Chinese herbs. The results of
this study are particularly meaningful for evaluating the quality of F. dibotrys resources,
developing standardized F. dibotrys farming systems and establishing a quality control
system for geo-authentic F. dibotrys products. These results show that the synthesis of
metabolites of F. dibotrys is induced by the environment under different growth areas,
which is consistent with the detection results of different metabolic substances in different
ecotypes for Cistanche deserticola, indicating that the production environment is the main
factor affecting the accumulation of metabolites of medicinal plants [27–29].

4.2. Differential Phenolic Metabolite Analysis of FDR from Different Origins

Fifteen FDR samples obtained from five F. dibotrys-producing areas were collected
to identify the differences in metabolite extracts. PCA results show that the metabolites
of FDRs from different origins are obviously different, and could be divided into two
major subgroups. The rhizomes of YK and YQ show higher total flavonoids, particularly
epicatechin, being a major bioactive element in Chinese pharmacopoeia. In addition, the
total tannin content of FDRs in YQ was the highest, followed by YK, CS, CF and GB. These
findings revealed five distinct groups associated with distinct metabolite profiles of FDR
from different producing areas, and CS, CF and GB belong to the non-Yunnan (NYN) group
and YK and YQ belong to the Yunnan (YN) group. The number of DPMs was the highest
between the samples collected in GB and YQ (50 DPMs in total); relatively high numbers
of DPMs were also identified between CF and YQ (40 DPMs), and CS and YQ (36 DPMs).
Moreover, the YN group (YQ, YK) had more DPMs than the NYN group (CS, CF and GB),
the up-regulated metabolites of which account for the majority of all DPMs (Figure 5).
In contrast, only five DPMs (four down-regulated in YQ and one up-regulated) were
identified between the samples from YK and YQ, reflecting comparatively slight difference
in phenolic metabolites among the samples from habitats within Yunnan Province. These
results showed evident differences in phenolic metabolites between samples collected in
the YN and NYN groups.
A number of phenolic compounds, namely phenolic acids, tannins, flavonoids, quinones,
coumarins, lignans and so on, were extracted from multiple medicinal herbs or dietary
plants, and these compounds were proven to have important roles in preventing and treat-
ing lung cancers [30]. Among the above phenolic compounds, flavonoids were acknowledged
as the most functionally valuable components; they were reported to be beneficial to health,
for example, because they enhance vascular toughness, are good for treating gastrointesti-
nal dysfunction, reduce blood sugar and blood fat and are good for treating inflammation;
also, they can improve immunity and promote tumor inhibition [31,32]. The present results
suggested that the level of flavonoid compounds increased in YN group compared with
NYN group. In addition, our results show that there is a higher content of some flavonoids
and phenolic acids in the YN group, such as isorhamnetin 3-O-glucoside, isorhamnetin-7-O-
glucoside (brassicin), apigenin-3-O-glucoside, nepetin-7-O-glucoside, phloretin, piperitol,
fraxetin-7,8-di-O-glucoside, syringetin-7-O-glucoside, syringetin, limocitrin-3-O-glucoside
and 2-methoxybenzaldehyde (Figure 8), which possess anti-inflammatory, anti-cancer,
anti-oxidant, anti-bacterial and anti-diabetic activities, suggesting that FDRs from Yunnan
province have a better medicinal value and are worth exploiting. Our findings confirmed
that the metabolites with the greatest variation in the FDRs of five producing places were
phenolic and flavonoids. Based on these results, the phenolic and flavonoid compounds
could be selected to assess the quality of FDRs from different origins. The enrichment
analysis results indicate that the DPMs were significantly enriched in metabolic pathways,
biosynthesis of secondary metabolites and flavone and flavonol biosynthesis. That is the
Metabolites 2022, 12, 790 11 of 14

reason why we think that YQ and YK were divided into the high medicinal value (YN)
group, and CS, CF and GB were classed as the low medicinal value (NYN) group.

4.3. The Common DPMs of FDR from Different Origins

Gallic acid, a predominant polyphenol, has the simplest molecular structure among
all the natural polyphenols. In recent years, remarkable anti-tumor effects of gallic acid on
cancers, including pancreatic cancer, lung cancer, prostatic cancer and skin cancer, have been
confirmed through in vitro and in vivo approaches [33–35]. Gallic acid was reported to have
significant anti-tumor effects: gallic acid and its derivatives can inhibit the proliferation of
tumor cells, induce the apoptosis of tumor cells and suppress tumor metastasis; meanwhile,
gallic acid can exert these anti-tumor functions with high selectivity, specificity and low
damage concerning the healthy cells. The major traditional Chinese medicinal plants that
are rich in gallic acid include Galla chinensis [36], Cornus officinalis [37], Pomegranate [38],
Rheum palmatum L. [39] and Moutan cortex [40]. 1,6-di-O-galloyl-β-D-glucose and 2,3-
di-O-galloyl-D-glucose have been isolated from the leaves of Castanopsis fordii Hance
and the rhizomes of rhubarb, which had a strong effect reducing blood pressure [41–43].
Shao et al., studying the phenolic acid derivatives from the rhizome of Fagopyrum cymosum,
showed the pharmacological material basis of FDRs [44]. At present, approximately 20
phenolic derivatives in F. dibotrys have been detected, including gallic acid, syringic acid,
3,4-dihydroxy benzoic acid, succinic acid, etc. [45]. The results of common DPM analysis of
CS vs. YQ, CF vs. YQ, GB vs. YQ, CS vs. YK, CF vs. YK and GB vs. YK suggested that
2,3-di-O-galloyl-D-glucose, 1,6-di-O-galloyl-β-D-glucose and gallic acid could be used as
ideal chemical markers for the quality control of FDR from different origins. Moreover, the
three common DPMs were higher in the YN group (YQ, YK) than the NYN group (GB, CF
and CS).
In addition to the medicinal values, three primary differential metabolites contributing
to its nutritional value were also identified. In detail, the contents of L-cyclopentylglycine,
N-methyl-trans-4-hydroxy-l-proline and L-asparagine were significant higher in the YN
group than in the NYN group. Previous studies reported that F. dibotrys contained 18 amino
acids, multiple vitamins and essential inorganic substances, which proved its important
nutritional value as a silage additive and health food [7,46]. Hence, F. dibotrys is a herb that
is further worth exploiting.

4.4. The ‘Good Traits’ of the High-Quality Fagopyri Dibotryis

The ‘good traits’ of traditional Chinese medicine (TCM) could be used as one of the
identification criteria of the high-quality herbs, such as ‘Yunjin huawen’ of Heshouwu (in
Chinese), which is a pattern formed by anomalous vascular bundles and can be observed
on the cross-section of the root tuber of Fallopia multiflora (Thunb.) Harald [47]. Hence, the
cross-sectional colors of YK, CS and GB rhizomes were reddish-brown, light red and yellow
white, which was consistent with the change trend of total flavonoids and total tannin
content. This illustrates that the reddish-brown section of FDRs may contribute to its high
quality as a ‘good trait’. In addition, the results showed that absorbance values and total
tannin content of FDRs were also positively correlated with its section color. Anthocyanins
belong to the flavonoid family that widely exists among the leaves, roots and flowers
of most fruits and some medicinal plants [48,49]. Zhang et al. found that delphinidin
3-O-glucoside, malvidin 3-O-glucoside and delphinidin may be the key anthocyanins
conferring the red pigmentation of jujube peel over the fruit ripening periods [50]. The three
anthocyanins, therefore, could be regarded as a red coloration of plant organs. In our current
findings, we found that procyanidin B3, procyanidin B1, procyanidin B2 and procyanidin
B4 of FDRs from different origins were identified; their relative contents were significantly
different. Considering the possible coloring mechanism, these four metabolites may lead to
the changes from reddish-brown to yellow white in FDRs of YK, CS and GB.
Metabolites 2022, 12, 790 12 of 14

5. Conclusions
Identification of medicinal compounds and metabolite profiling analyses of Fagopyrum
dibotrys rhizomes (FDR) indicated that the medicinal differences of FDR from different ori-
gins can be elucidated via the variations in the abundance of phenolic and flavonoids. The
metabolic profiles of F. dibotrys from different origins were significantly enriched. We found
that the epicatechin, total flavonoids and total tannin content in Qujing in Yunnan (YQ)
and Kunming in Yunnan (YK) were higher than those in Shizhu in Chongqing (CS), Fuling
in Chongqing (CF) and Bijie in Guizhou (GB), consistent with the traditional view that
Yunnan Province can be considered as one of the producing areas of high-quality medicinal
materials. After that, a medicinal-difference analysis of F. dibotrys from different origins
was successfully performed. In detail, phenolic acids and flavonoids, such as isorhamnetin-
7-O-glucoside (brassicin), isorhamnetin 3-O-glucoside, apigenin-3-O-glucoside, nepetin-
7-O-glucoside, phloretin, piperitol, fraxetin-7,8-di-O-glucoside, syringetin, 7-O-glucoside,
syringetin, limocitrin-3-O-glucoside and 2-methoxybenzaldehyde were significantly higher
in the YN group. Moreover, phenolic and flavonoids exhibited the greatest variation among
the metabolic profiles of FDRs from different origins, which could be used to assess the
quality of raw medicine. Additionally, 2,3-di-O-galloyl-D-glucose, gallic acid and 1,6-di-O-
galloyl-β-D-glucose could be used as ideal marker compounds for the quality control of
F. dibotrys from different origins.

Supplementary Materials: The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/metabo12090790/s1, Table S1. Sample number information of
Fagopyri Dibotryis rhizome from different origins. Table S2. Widely targeted UPLC-MS/MS based
metabolite profiling of Fagopyri Dibotryis rhizome from different origins. Table S3. The screening
results of differential phenolic metabolites. Table S4. Statistics of 187 phenolic metabolites in the
Rhizome between YN group and NYN group. Table S5. Metabolic pathways enrichment analysis for
the NYN and YN group differentially accumulated metabolites. Table S6. Statistics of up-regulated
metabolites in the Rhizome between YN group and NYN group. Figure S1. The stacking diagram
of total ions current (TIC) maps from quality control samples (QC) mass spectrometry. Figure S2.
Cross-section of FDR from different producing areas. (A) YK (Reddish-brown); (B) CS (Light red); (C)
GB (Yellow white).
Author Contributions: Conceive and design, S.W. and L.G.; sample collection, Y.J., C.Z., J.L., Y.Z.;
sample preparation and measurement, Y.J., L.S., C.L.; data analysis, C.Z. and S.W.; methodology,
C.Z.; data curation, C.Z. and S.W.; writing-review and editing, C.Z. and S.W.; writing-original
draft preparation, C.Z.; funding acquisition, S.W. and L.G. All authors have read and agreed to the
published version of the manuscript.
Funding: This research was financially funded by the National Key Research and Development
Program of China (2017YFC1701405), China Agriculture Research System of MOF and MARA (CARS-
21), Innovation Team and Talents Cultivation Program of National Administration of Traditional
Chinese Medicine (ZYYCXTD-D-202005), Scientific and technological innovation project of China
Academy of Chinese Medical Sciences (CI2021A03903).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments: Thanks to Yuefeng Wang and Hongyang Wang for their support in data analysis
of this study.
Conflicts of Interest: The authors declare no conflict of interest.
Metabolites 2022, 12, 790 13 of 14

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