Extensive Proﬁling of Polyphenols from Two Trollius
Species Using a Combination of Untargeted and
He Tian 1,†, Zhiyang Zhou 2,†, Guanghou Shui 1,* and Sin Man Lam 1,2,*
1 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China;
2 Lipidall Technologies Company Limited, Changzhou 213022, China; email@example.com
* Correspondence: firstname.lastname@example.org (G.S.); email@example.com (S.M.L.);
Tel.: +86-106-480-8831 (G.S.); +86-106-480-6670 (S.M.L.)
† These authors contributed equally.
Received: 13 February 2020; Accepted: 20 March 2020; Published: 23 March 2020
Abstract: Various species of globeﬂowers, belonging to the genus Trollius, have been extensively used
in traditional Chinese medicine due to their anti-inﬂammatory, antimicrobial, and antiviral properties,
which are mainly attributed to their high polyphenol content. Diﬀerences in polyphenol composition,
and abundances, will lead to varying treatment eﬃcacies of globeﬂowers. Herein, we employ a
combination of targeted and untargeted mass spectrometry (MS) approaches to characterize and
quantify a comprehensive array of polyphenols, mainly including ﬂavonoids and phenolic acids in two
globeﬂower species commonly used in Chinese medicine, Trollius chinensis Bunge and Trollius ledebouri
Reichb. In addition, free radical scavenging activity was investigated to evaluate the association
between polyphenol composition and antioxidation capacity. Liquid chromatography (LC)-based
separation and multiple-reaction-monitoring (MRM) transitions were optimized using a library of
78 polyphenol reference compounds to achieve absolute quantiﬁcation on triple quadrupoles MS
(QqQ). The analytical method was further expanded via high-resolution MS to provide relative
quantitation of an additional 104 endogenous polyphenols in globeﬂowers not included in our
reference library. Our results revealed stark diﬀerences in polyphenol content between T. chinensis and
T. ledebouri, emphasizing the need for systematic characterization of polyphenol composition to ensure
treatment eﬃcacy and consistency in standardizing the use of globeﬂowers in Chinese medicine.
Keywords: polyphenols; globeﬂowers; ﬂavonoids; mass spectrometry
The genus Trollius comprises 31 species inhabiting the northern hemisphere areas, which have
been used in folk medicine in Europe, western Siberia, and China . Trollius chinensis Bunge and
Trollius ledebouri Reichb, mainly produced in northern China , are commonly used in Chinese
traditional medicine to treat upper respiratory infections, pharyngitis, tonsillitis, esoenteritis, canker,
Polyphenols, which mainly include ﬂavonoids and phenolic acids , are present, in high
abundance, amongst the genus Trollius (including T. chinensis and T. ledebouri), and are responsible for
the antiviral, antimicrobial, antioxidant activities associated with these plant species [4,5]. Previous
research had demonstrated that speciﬁc polyphenols impede cancer cell proliferation . A recent
study showed that orientin and vitexin exhibited appreciable inhibitory eﬀects on the proliferation
of the esophageal cancer (EC)-109 cells . Moreover, orientin displayed higher antitumor eﬀects
than vitexin. In another study, the extract from T. chinensis displayed a strong inhibitory eﬀect on
Metabolites 2020, 10, 119; doi:10.3390/metabo10030119 www.mdpi.com/journal/metabolites
Metabolites 2020, 10, 119 2 of 12
proliferation of human gastric carcinoma cells, human melanoma cells, and two diﬀerent cell lines of
human breast adenocarcinoma [8,9].
Preceding studies on the pharmacological activity globeﬂowers, however, were mostly conﬁned
to only one species of Trollius, without comparing the diﬀerences among frequently used globeﬂowers,
such as T. chinensis and T. ledebouri [10–12]. In most cases, Chinese medicine practitioners do not
diﬀerentiate between T. chinensis and T. ledebouri and consider them as one . As a result, endogenous
diﬀerences in the compositions of polyphenols between T. chinensis and T. ledebouri can lead to
varying treatment eﬃcacies when they are combined in diﬀering proportions . Thus, a systematic
comparison of bioactive components (in particular polyphenols) in T. chinensis and T. ledebouri,
is essential to standardize the use of globeﬂowers in Chinese medicine to ensure consistency in terms
of treatment eﬀects.
Currently, LC-MS is the most widely adopted technique used to characterize and quantify phenolic
compounds in various food, plants, and herbs [14–16]. With rapid development in tandem mass
spectrometry and chromatographic separation techniques, numerous phenolic compounds have
been characterized and identiﬁed as the primary antioxidants and functional components in various
fruits, vegetables, agricultural products, herbs, and plants [14,17,18]. Tandem triple quadrupole
(QqQ)-MS is regarded as the gold standard in quantiﬁcation due to its superior sensitivity and wide
dynamic ranges over high-resolution MS (HR-MS) . Nonetheless, QqQ has constraint in terms of
compound identiﬁcation, owing to its limitation in acquiring accurate mass to charge ratio (m/z) of
molecules, making QqQ-MS heavily reliant on the need of reference standards/compounds to achieve
unambiguous identiﬁcation . Considering the plethora of metabolites and bioactive compounds in
plants and other biological samples, it is often economically impractical and technically infeasible to
obtain all of reference standards to achieve compound identiﬁcation solely via QqQ-MS. In comparison,
HR-MS is powerful in identifying unknown compounds and providing semi-quantitative results.
Information dependent acquisition (IDA) using HR-MS can provide annotated identiﬁcation
results even in the absence of reference standard compounds . A shortcoming of IDA, however,
lies in its limited acquisition of product ion spectra, as the secondary mass spectra of only the top ten
to twenty precursor ions can be recorded in a single scan cycle, while parent ions of lower intensities
are not triggered for MS/MS. In comparison, data independent acquisition (DIA) simultaneously
performs fragmentation of all precursors, albeit resulting in a higher complexity in identiﬁcation due
to composite product ion spectra from co-eluting substances .
In this study, we ﬁrst constructed and optimized a high-performance liquid chromatography
(HPLC)-multiple-reaction-monitoring (MRM) method based on QqQ-MS using a library of 78 reference
polyphenol standards, which was used to provide absolute quantiﬁcation of these polyphenols in
T. chinensis and T. ledebouri. Next, we employed HR-MS in both IDA and DIA modes to expand our
existing library to include an additional 104 endogenous polyphenols in T. chinensis and T. ledebouri,
of which 81 had product ion spectra that matched with known metabolites in commercial databases
(Figure 1). In all, we report the absolute/relative quantitative results of 131 identiﬁed and 23 unidentiﬁed
polyphenols in the two species of globeﬂowers under investigation.
Metabolites 2020, 10, 119 3 of 12
Metabolites 2020, 10, x FOR PEER REVIEW 3 of 14
Globeflower polyphenol extracts
Fragment parent ions Low collision energy High collision energy
with highest intensities (CE) transmission (CE) transmission
Full scan Full scan
No fragmentation Fragmentation
78 polyphenol reference compounds Parent ions Product ions
QqQ‐MS Polyphenol Identification
Retention time, Peak Width, Tailing Factor, m/z
for 78 known deviation, characteristic fragments
Compare with metabolite databases
Globeflower polyphenol extracts
Absolute quantitation of Unidentified polyphenols (23) Identified polyphenols (111)
50 detected polyphenols
Semi‐quantitation of Overlap with reference
104 polyphenols compounds library (30)
Globeflower endogenous polyphenols
of known identities (131)
Polyphenol reference 30 23 Polyphenol HR‐MS
compound library on 28 library (134)
FigFuigreur1e. 1S.c Shcehmemataitcicd diaiaggrarammi lillulussttrraattiinngg ccoommbbiinnaattiioonn ooff ((AA) )uusisningg HHPPLCLC‐Q-QqQq Q(M(MRMRM) a)nadn (dB() Bu)siunsgi ng
UPULPCL-CQ‐TQOTFOF( ID(IDAAa nanddD DIAIA)) aapppprrooaacchheess ffoorr iiddeennttiifﬁiccaattiioonn aanndd qquuaanntitfiiﬁcactaiotino nofo pf oployplyhpehneonlso lisn in
glogbloebﬂeofwloewrse.rsH. PHLPCL,Ch, ighhig-hp‐epreforfromrmanacneceli qliuqiudidc hcrhormomataotgorgarpaphhyy; ;Q QqQqQ, t, atnadnedmemt ritprilpeleq uqaudardurpuoploel;eM; S,
maMssS,s pmeacstrso smpeetcrtyro; mHeRtr,yh; igHhR,r ehsioglhu tiroenso;lUutPioLnC; ,UuPltLrCa-, puelrtfroar‐pmearfnocremlaiqnuceid licqhuriodm cahtroogmraatpohgyra;pQhTyO; F,
tanQdTeOmFq, tuaanddreump oqlueatdimruepoofleﬂ tiigmhet .of flight.
2. 2R. eRseuslutslts
2.12..1C. oCluomlunmnS eSlecletciotinonfo frorP PoloylypphheennoollS Seeppaarraattiioon
WaWteartserHs iHgihghS tSretrnegntghthS iSliilciaca( H(HSSSS)) TT33 ccoolluummnn ((22..11 mmmm ×× 11000 0mmmm, 1, .18. 8μmµm) a) nadn dPhPehneonmoemneexn ex
KinKeinteexteCx 1C818(2 (.12.1m mmm× ×1 10000m mmm,, 11..88 µμmm)) wweerree sseelleecctteedd ttoo ccoommppaarere ththeieri rsespeapraartaiotino nbebheahvaiovriso rfosrf or
poplyoplyhpehneonlso.lsD. iﬀDeifrfeenrtencto mcopmospiotisointioonf mofo bmileobpihlea spehsawseesr ewalesroe inalvseos tiingvateesdti,giantecldu, diinncglupduirneg aqpuuereo us
phaaqseue(oi.ue.s, pwhaatseer (cio.en.,t awinatienrg c0o.n1t%ainfoinrgm 0ic.1a%c ifdo;rmFAic) aacnidd; pFuAr)e aonrdg apnuircep ohragsaen,ici. ep.h, aascee,t oi.ne.i,t raicleeto(AniCtrNile) or
me(tAhCanNo) lo(rM meeOthHa)n, oals (wMeelOl aHs),a aqsu weoeulls -aosr agqauneicoums‐ioxrtugarensici nmcilxutduirnegs iwncaltuedr/iAngC wNaoterrM/AECONH orc oMnEtaOinHi ng
0.1cc%oomnFtpaAirniasininngdg 02w.01a%mte rFM Aco anamtnadmin o2in0ng imu 0mM.1% aa cmFeAtma,t oean,niduet mcp. uarOcee utAartCreNe, se uatclrt.e s Otshuhero iwrdeeesaudll ttmsh oasbht iomlew opebdhi alteshepa tch oammsoebbsiinlceao tmipohnpa rsfioessrin g
wabtoetrhc ocnoltuaminninsg, c0o.1n%sidFeAri,nagn tdhep upreeakA CshNapaerse othf ealild e7a8 l pmoolybpilheenpohla sreefceoremncbein caotmiopnofuonrdbso t(hdactoal unmotn s,
conshsoidwenri)n. gThthe etoptaela kelushtiaopne tsimoef aolfl H78SSp oTl3y fpohr ethneo ltersetfeedre rnecfeerceonmcep cooumnpdosu(nddast awnaos tshshoortwern a)n. dT hpeeatok tal
elusthioapnetsi mweeroef mHoSrSe iTd3eafol rthtahne ttheastt eodf Kreinfeerteenx cCe1c8o (mFipguoruen Sd1s);w thausss, hHoSrSte Tr3a cnodlupmena kwsahs acphoessewn edrueem too re
idesahlotrhtearn atnhaaltytoicfaKl idnuertaetxioCn1 a8n(dF ibgeuttreer Sc1h)r;otmhuatso, gHraSpShTic3 bceohluamvionrws. as chosen due to shorter analytical
duration and better chromatographic behaviors.
Metabolites 2020, 10, 119 4 of 12
2.2. Identiﬁcation and Quantiﬁcation of Polyphenols
An HPLC-MRM method was constructed on QqQ-MS using 78 reference polyphenol standards
(Table S1), MRM transitions of individual polyphenols were presented in Table S2. Of these polyphenols,
50 were detected in the extracts of T. chinensis and T. ledebouri, and standard addition was used to provide
absolute quantitation of these 50 polyphenols in globeﬂowers (Table S3). Furthermore, an additional
104 polyphenols were putatively identiﬁed via HR-MS on ultra-performance liquid chromatography
coupled to tandem quadrupole time of ﬂight (UPLC-QTOF) and were relatively quantiﬁed.
In the IDA method, 20 most intense parent ions in one scan cycle were selected for further
fragmentation, and the resultant product spectra were compared with metabolite databases for
identiﬁcation. For the DIA method, parent-product ion pairs, separately generated from experiment
1 (scans for parent ions) and 2 (scans for product ions of all parent ions), were ﬁrst output into two
dimensional matrix, including mass-to-charge ratios (m/z), retention time (rt), start and end time,
and tailing factors of all ion peaks. In the second step, precursor and daughter ions were processed
to match with each other according to the following criteria: (i) rt (min) should be equal between
ion pairs (accurate to two decimal places), (ii) span of start and end time of product ions should be
within that of their corresponding parent ions, (iii) tailing factors of product ions should be equal to
or less than that of their corresponding parent ions. If an ion pair satisﬁed all of the above criteria,
then evaluation of characteristic fragmentation will be conducted further both for DIA and IDA results
to judge whether these ion pairs belong to polyphenols.
For identiﬁcation of a parent ion as ﬂavonoid or phenolic acid, it requires matching of three or more
product ions that are characteristic fragments of ﬂavonoids and phenolic acids with the parent ion under
evaluation (Table 1). For identiﬁcation of ﬂavonoid glycosides, on top of satisfying the identiﬁcation
criteria for ﬂavonoids or phenolic acids as aforementioned, a parent ion needs to have at least one neutral
loss matching with the characteristic neutral loss for ﬂavonoid glycosides (Table 2). Using HR-MS
approaches, a total of 134 candidate polyphenols matched the identiﬁcation criteria mentioned above.
Amongst these compounds, 111 polyphenols exhibited product ion spectra that matched with known
polyphenols in metabolite database, of which 30 coincided with polyphenols included in our own
reference library constructed on QqQ-MS (Figure 1), and 23 polyphenols remained unidentiﬁed.
Therefore, the current work had (putatively) identiﬁed and absolutely/relatively quantiﬁed a total of
131 polyphenols endogenous to globeﬂower extracts.
Table 1. Characteristic fragments of ﬂavonoids and phenolic acids.
No. Characteristic Fragments Theoretical m/z [M − H] No Characteristic Fragments Theoretical m/z [M − H]
1 C15H10O7 301.0354 18 C7H4O3 135.0088
2 C15H9O7 300.0276 19 C9H10O 133.0659
3 C15H12O6 287.0561 20 C5H8O4 131.0350
4 C15H10O6 285.0405 21 C6H6O3 125.0244
5 C14H8O6 271.0248 22 C6H4O3 123.0088
6 C15H10O5 269.0455 23 C7H6O2 121.0295
7 C14H8O5 255.0299 24 C5H6O3 113.0244
8 C13H12O5 247.0612 25 C6H4O2 107.0139
9 C13H14O 185.0972 26 C5H6O2 97.0295
10 C8H6O5 178.9986 27 C5H4O2 95.0139
11 C12H12O 171.0815 28 C6H4O 91.0190
12 C8H4O4 163.0037 29 89.0397
13 C6H9O10 161.0456 30 C7H6 83.0139
14 C7H4O4 151.0037 31 C4H4O2 59.0139
15 C8H6O3 149.0244 32 C2H4O2 55.0190
16 C6H9O4 144.0428 33 C3H4O 53.0033
17 C7H6O3 137.0244 C3H2O
[M − H] refers to deprotonated molecular ion.
Metabolites 2020, 10, 119 5 of 12
Table 2. Characteristic neutral loss of ﬂavonoid glycosides.
No. Formula Molecular Weight Molecular Assignment
1 C7H12O7 208.0589 Glucose + CO
2 C7H12O6 192.0640 Glucose + C
3 C6H12O6 180.0628
4 C6H10O7 194.0432 Glucose
5 C6H8O6 176.0326 Glucuronic acid
6 C4H8O4 120.04281 Glucuronic acid − H2O
7 C6H10O5 162.0523 Glucose − C2H4O2
8 C6H11O5. 163.0612 Glucose − H2O
9 C6H12O5 164.0679 Glucose − HO.
10 C6H10O4 146.0574
11 C5H10O5 150.0523 Rhamnose
12 C5H8O4 132.0417 Rhamnose − H2O
Arabinose − H2O or Xylose
To demonstrate the advantages of combining the use of IDA and DIA in HR-MS, we use the
example of putatively identiﬁed kaempferide 7-hexoside, an endogenously low polyphenol (m/z 461.109)
in globeﬂowers. In the IDA list of this study (Figure 2A), there were two ions at m/z 461.1079–461.1081
from index order 3316 to 3327 (circled red), and their corresponding rt were also displayed. Product
ion spectra of every parent ions in the IDA list were acquired in the IDA scan. However, DIA results
generated an additional ion (m/z 461.109, rt 6.29), corresponding to kaempferide 7-glucoside, which was
not included in IDA list due to its comparatively low intensity. Figure 2B (panels A, B) illustrate the
extracted ion chromatograms (XICs) of ions at rt 6.29 min, of which m/z 461.109 was not observed.
This ion can be seen when the spectrum was enlarged (Figure 2B, panel C). Since its intensity was
lower than other signals eluting within the same retention time window, IDA scan failed fragment
this ion, leading to the missing information. By comparison, DIA can fragment all of parent ions,
independent of ion intensities. Figure 2C displays the XICs of product ions from the parent ion at m/z
461.109, rt 6.29 min, which coincided with the characteristic fragmentations of ﬂavonoids (Tables 1
and 2). In the product ion spectra of m/z 461.109, 161.0462 (Table 1, No13), 113.0244 (Table 1, No 24)
59.0139 (Table 1, No 31) corresponded to fragments of ﬂavonoid aglucones, while ion at m/z 298.0482
represented the fragment after neutral loss of 163.0612 C6H11O5- (Table 2, No 8).
2.3. Method Validation
Optimized MRM transitions in QqQ-MS were listed in Table S2. The HPLC-MRM method was
validated in terms of dynamic linearity range (DLR), limit of detection (LOD), limit of quantiﬁcation
(LOQ), recovery, as well as relative standard deviation (RSD) across three consecutive days (Table S3).
Diﬀerent concentrations of all 78 standard references solutions were spiked into matrix-matched
globeﬂower extracts for the determination of DLR, LOD, and LOQ of QqQ-MS. Precision is
satisfactory, with RSD below 14% across consecutive three days in all three spiked concentrations,
except for procyanidin B2 (23.89% at lowest spiked concentration of 625 µg·L−1) and resveratrol
(16.89% at lowest spiked concentration of 625 µg·L−1), LOD and LOQ ranged from 0.12 µg·L−1
and %0.40 µg·L−1, respectively, for formononetin, to 33.33µg·L−1 and 111.11 µg·L−1, respectively,
for 4-Hydroxy-3,5-dimethoxybenzoic acid). Recovery was within 70–120% for all spiked polyphenol
standard references, except for 4-Hydroycoumarin.
Metabolites 2020, 10, 119 6 of 12
Metabolites 2020, 10, x FOR PEER REVIEW 6 of 14
A. IDA list
B. DIA spectra in experiment 1
a. XIC of m/z 461.109
b. MS spectrum at rt 6.29
Unknown flavonoid c. Enlarged MS spectrum
at rt 6.29
C. DIA spectra in experiment 2
a. XIC of m/z 298.0482
b. XIC of m/z 161.0462
c. XIC of m/z 113.0244
d. XIC of m/z 59.0139
FiFgiugruere2 . 2E. xEamxapmlepliell uisllturasttrinatginhgo whoDwI ADsIeAr vseesrtvoesc htaor acchtaerraizceteernizdeo genendoougeslnyoluoswly ploolwyp phoenlyoplhs emnioslsse d
bymIiDssAeds cbayn .ID(AA) IsDcaAn.l i(sAt )s hIDowAi nligstt hsheoawcqinugir tehder aecsquultisreodf iroenssulatrso oufn idonms/ za4ro6u1.n1d0 9ma/nz d46R1T.160.92 9anmdi nRuTt es.
(B6).2T9h me XinIuCteosf. m(B/z) T46h1e .1X0IC9 aonf dmi/tzs 4c6o1r.1re0s9p aonndd iitnsg cosrpreecstprounmdianng RspTe6ct.2ru9mm ainnu RteTs 6i.n29D mIAineuxtepse irnim DeInAt 1.
(mCe4ti)inx6mXup1e.Iet1Ce.r 0si9moi fneapntD rtR oI1ATd. u(6eCc.x2t)p9 iXeo mrIniCsmi n(oeumfn t/petzsr22 o.i9dnX8u .ID0cC8tI ,4Aioe2 xn,etmsxr pa(/zmectr1/eiz6md 12e.i90on84nt.6 022c8.,h4 m2Xro,I /zmCm1,/a z1et 3ox1.gt60r1r2aa.4c0mt44e,6;dm2R ,i/ Tzom,n5/r z9ec .t1h0e11rn3o3t.m9i0o)2ano4t4ofti,gm mmr/aze/mz.4 5;6 91R..01T10, 39r9ea)t teoRnf tTmio6/nz.2 9
Metabolites 2020, 10, 119 7 of 12
2.4. Polyphenol Proﬁles of T. chinensis and T. ledebouri
In all, 154 polyphenols were quantiﬁed (50 absolute quantitation, 104 relative quantitation),
including 16 ﬂavonoid aglycones, 80 ﬂavonoid glycosides, 58 phenolic acids (Tables S4 and S5).
Among these polyphenols, 135 components were signiﬁcantly diﬀerent between T. chinensis and T.
ledebouri (p < 0.05), indicating polyphenol biosynthesis are diﬀerentially regulated in these two Trollius
species. The contents of total ﬂavonoid aglycones in T. chinensis was 1.63-fold that of T. ledebouri, and
total phenolic acids in T. chinensis was 1.55-fold of T. ledebouri. Total ﬂavonoid glycoside in T. chinensis
was almost equal to those in T. ledebouri, but stark diﬀerences in ﬂavonoid glycoside composition
was observed (Figure 3). Therefore, in general, T. chinensis contains signiﬁcantly higher levels of
polyphenols compared to T. ledebouri. In particular, T. ledebouri exhibited enhanced biosynthesis of
ﬂavone and ﬂavonol, with stark elevations in the corresponding pathway bio-constituents compared
to T. chinensis (Figure 4). In addition, contents of speciﬁc phenolic acids, which had been reported to be
key bioactive constituents acting against inﬂuenza and other viruses [22,23], were found in appreciably
higher levels in T. chinensis than T. ledebouri. For example, isochlorogenic acid C, which exhibits a
broad-spectrum antiviral potency against coxsackievirus  and human immunodeﬁciency virus ,
was more than 2000-fold higher in T. chinensis than in T. ledebouri (Figure 3). These ﬁndings aligned
with our hypothesis that diﬀerent Trollius species may have diﬀerent therapeutic potential resulting
from Mtheteabiorlidtesi s20p2a0,r 1a0t, ex FcOoRm PEpEoRs RitEiVoInEWo f bioactive constituents [2,8,26]. 8 of 14
FigurFeig3u.re 3H. eHaetamtmaappss iilllluussttrraatet ethteh deiffdeirﬀenecreesn icne slevienls loefv fellasvoonfoiﬂda gvlyocnoosiiddesg, lpyhceonsoildice asc, idpsh, eanndo lic acids,
and ﬂflaavvoonoiidd aagglylyccoonnese sbebtewtewene eTn. Tch.icnheninsiesn asnisd aTn. dleTde.bloeudreib eoxutrriaectxst. rTahcets s.yTmhbeols y“+m” binodl i“c+at”esi npd <i c0a.0t5e,s p < 0.05,
and *afnodr *a fbosr oalbusotelulyteqlyu qaunatniﬁtifeidedp poollyypphheennoolsl.s .
Metabolites 2020, 10, 119 8 of 12
Metabolites 2020, 10, x FOR PEER REVIEW 9 of 14
Quercitrin Apigenin Luteolin
Quercetin 3-O-rhamnoside 7-O-glucoside
FigFuigruer4e. 4P. aPtahthwwaayy ooff ﬂflaavvoonnee aanndd flﬂavaovnoonlo bliobsiyonsythnetshise asidsaapdteadp ftreodmf rthoem KtEhGeGK pEaGthGwpaya.t hBwluea yli.nBe lue line
andanrde dreldin leinien idnidcaictaetet htehee xextrtaracctteedd iioonn cchhrroommaattooggrraammss fofor rththe eininddiviivdiudaul afllaﬂvaovnoonidosi dins Tin. lTed. elebdouebrio uri and
T. cahnidn eTn. scihsi,nreensspise, crteisvpeelcyt.ivKelEyG. KGE,GKGy,o KtoyoEton cEyncclyocploepdeidaioa foGf Geneneessa anndd GGeennoommeess
3. D3. iDscisucsussisoinon
OuOrupr rpesreesnetnst tsutdudyyd desecscrirbibeess tthhee ccoommbbiinneedd uussee ooff QQqqQQ‐M-MSS aanndd HHRR‐M-MS Scocmopmrpisrinisgi nbgotbho ItDhAID A and
DIAganlomdb eeDftlhoIAow demsrste o(tTha.o ccdhhsii netevone siahsc iahgnihedv -Tceo. lvheiedgerhbao‐gcueorviq)e ucroaamgnetm iﬁqocunaalytni touifnsiecodaft iiopnn oC lyhopifn hepesoenl yomplsehdeinincoitnlwse o[i1ns] p. tWewcioite hss tpohefec giuelssoa bgoeefﬂ owers
(T.ocfh aincceunrsaistea mnd/z T(.aclecduerbaoteu rtoi) fcooumr mor omnolyreu dseecdiminal Cphlaicneess) eanmde rdeilcaitnivee [a1b]u. nWdainthcetsh oef upsaaregnet oafndac curate
m/zp(raocdcuuctr aitoensto, HfoRu‐Mr oSr ims oporewderefcuilm ina lipdelanctiefsy)inagn dcormelpaotuivnedsa bbuyn mdaantccheinsgo fthpeamre nwtitahn advpairlaobdlue ct ions,
HRd-aMtaSbaissepso, wanedr ffuulrtihneird ceonntfiifryminagtiocno mcapno buen adcshbieyvemda btcyh cionmg pthaerimngw aidtdhitaivonaailla pbaleradmaetatebras,s esus,cahn ads further
conrﬁetremntaiotino ntimcaen wbeitahc hstiaenvdeadrdb yrecfoemrepncaersin [g19a]d. dCiotimonparlepda rwamithe tQerqsQ, s‐MucSh; ahsorweetevnerti, oHnRti‐mMeS wisi tlhessst andard
refseureitnedce fsor[ 1q9u]a.nCtifoicmatpioanre dduew tiot hitsQ lqimQit-eMd Ss;enhsoitwiveitvye ar,nHd Rre-lMatiSveilsy lneassrrsouwi tdeydnfaomricq uraanngteisﬁ, cwathiiocnh due to
its cliommipterodmsiesne stihtiev irteypaenatdabrieliltayt ivoef lyqunaanrtritoawtivde ydnaatma idcerraivnegde sf,rowmh icHhRc‐MomS p[r1o9m]. iWsehtihlee QreqpQe‐aMtaSb ility of
quaonpteirtaattiinvge idn atthae dMeRriMve md ofrdoem is HreRg-aMrdSed[1 a9s] .thWe hgoilled QstqanQd-aMrdS ionp qeuraantitnifgicaintiothn,e iMt mRaMinlmy osedreveiss troe garded
as tqhueangtoiflyd kstnaonwdna rmdeitnabqouliatnest,i ﬁacnadt iiosn r,eiltiamnta oinnl ythsee ravveasilatobiqlituya noft irfeyfekrneonwcen stmanedtaabrdo lciotems,paonudndiss rteol iant on
thedioaenvrsiav fieol aro bqpiutliiamtlyifaiolc fatrtriaeonfnes irateinondnc qepusaatrnaatnmifdiecataertrdiso,n cio,n amcsl upwdoeiunllng a dsi sornetot esnodtueirorcinev teipmoarepa.t mIinme mtaelrosts,rt a ccnoalssleiitssii,oo tnnh epesneae rrraegmqyu,e irpteermrosde,uninctstc luding
ionlismoiut rrecseeparacrhaemrse ttoe qrsu,acnotilflyis oionnly eknneorwgny, cpormopdouucntdiso nwsitfho rreqfeureanlicﬁec sattainodnaradnsd inq huaanndtsiﬁ. cation, as well as
retentioInn tbiimome.edInicmal‐oosrtiecnatseeds ,sttuhdeisees,r ereqsueiarrecmheerns tosftleimn ihtorpees etoa rocbhtearins tqouqanutaifnictiaftyioonn rleysuklntso, wnont coonmlyp ounds
witfhorr teafregreetnecde msetatanbdoalirtdess, ibnuth aalnsod sfo. r other endogenous metabolites that are structurally similar (i.e.,
belIonnbgiongm tehdei cahle-moricieanl tgerdousptus doire csl,arsessees)a, rbcehcearusseo fttheenseh mopeetatbooloitbetsa ainreq euxapnectitﬁedc attoi oenlicriet ssuimltsil,anr ot only
forbtioalroggeitceadl fumncettiaobnos loitre ms,edbiucatl aplrsoopefortrieos t[h27e]r. Aenpdarot gfreonmo uspsemcifeicta mbeotlaitbeoslitteh caltasasrees, sturcuhc atus rliaplildys,s imilar
(i.e., belonging the chemical groups or classes), because these metabolites are expected to elicit similar
biological functions or medical properties . Apart from speciﬁc metabolite classes, such as lipids,
that possess characteristic head groups/fragments that facilitate biochemical classiﬁcation [28–30], such
Metabolites 2020, 10, 119 9 of 12
identiﬁcation and quantiﬁcation of closely related metabolites without prior known reference standards
in hands are extremely challenging for QqQ-MS, which does not come with high mass resolution.
Henceforth, we have combined the use of QqQ-MS with HR-MS in the current work to generate more
comprehensive polyphenol annotations, and our combined approaches had realized a high-coverage
quantiﬁcation for both identiﬁed and unidentiﬁed polyphenols in globeﬂowers. The expansion in
metabolite coverage in our work is considerable, even for ﬂavonoid glycosides alone, we have reported
a total of 75 species (Table S5) in comparison to a previous work based upon LC/HR-MS on ﬁve Trollius
species that covered only 34 ﬂavonoid glycosides .
Many of the individual polyphenols, previously reported to be bioactive constituents with notable
antiviral potency, are found in signiﬁcantly diﬀerent levels between these two species of globeﬂowers
being investigated, suggestive of diﬀering medical eﬃcacy. Further pharmacological experiments are
needed to systematically evaluate the bioactivity of antibiosis, antiviral potency, and anti-inﬂammation
capacity among the diﬀerent Trollius species to assure consistency in the medical eﬃcacy of globeﬂowers.
4. Materials and Methods
All polyphenol references were obtained from J&K Scientiﬁc, Beijing, China. Detailed information
of these reference compounds were described in Table S1. Formic acid (FA), was of HPLC grade and
purchased from Sigma-Aldrich (Steinheim, Germany). Ultra-pure water (resistivity, 18.2 MΩ) was
puriﬁed on a Milli-Q Plus apparatus (Millipore, Brussels, Belgium). Acetonitrile (ACN) and methanol
(MeOH) of LC-MS grade were purchased from Merck (Darmstadt, Germany). Trollius chinensis
Bunge and Trollius ledebouri Reichb were obtained from Farmer professional cooperative of Corylus
heterophylla, JiaGeDaQi district, DaXingAnLing, northwestward of HeiLongJiang Province, China.
4.2. Polyphenols Extraction and Preparation
Polyphenols were extracted from Chinese globeﬂowers, according to previous publications with
modiﬁcations . Brieﬂy, 20 mg of dried ﬂowers was ground into powder in liquid nitrogen. Next,
0.8 mL of 90% methanol containing 0.5% acetic acid and 0.05% butylated hydroxytoluene was added.
Samples were sonicated for 30 min and then centrifuged at 12,000× g for 5 min at 4 ◦C. Clean supernatant
was transferred to new tube, and dried using miVac concentrator (Genevac Ltd., Ipswich, UK). Dried
extracts were resuspended in 0.5 mL water, containing 0.1% FA, 2% ACN, 0.5 µg of internal standards
((-)-Epigallocatechin, kaempferol-3-O-rutinosid, and resveratrol) for LC-MS analysis.
ACQUITY UPLC HSS T3 column (2.1 mm × 100 mm × 1.8 µm) and a guard column, both
from Waters (Dublin, Ireland), were used. The column oven temperature was maintained at 40 ◦C,
and autosampler was set at 10 ◦C. The injector volume was 5 µL. Flow rate was 0.40 mL/min. Mobile
phase A was water containing 0.1% FA (v/v), and mobile phase B was ACN. The following linear
gradient was used: 0–1.0 min with 2% B, 1.0–6.0 min with 2%—42% B, 6.0-8.0 min with 42%–65% B,
8.0–10.0 min with 65%–76% B, 10.0-11.0 min with 76%–100% B, 11.0–14.0 min with 100%–100% B.
For the identiﬁcation of polyphenols, Agilent 1290 II UPLC coupled to AB Sciex QTOF 5600 Plus
was used. The electrospray ionization (ESI) source was set up in positive and negative ion modes,
respectively. The MS parameters for detection were: ESI source voltage 5.5 kV or −4.5 kV; vaporizer
temperature, 550 ◦C; drying gas (N2) pressure, 60 psi; nebulizer gas (N2) pressure, 60 psi; curtain gas
(N2) pressure, 35 psi; and declustering potential, 80 V. The scan range was m/z 100–1000. Data acquisition
and processing were performed using Analyst® TF 1.7.1 Software (AB Sciex company, Concord, ON,
IDA method, Information-dependent acquisition mode was used for MS/MS analyses of the
polyphenols. The collision energy was set at 35 ± 15 eV.
Metabolites 2020, 10, 119 10 of 12
DIA method, data independent acquisition is composed of two full scan experiment. In ﬁrst
experiment, transmission energy was set at 10 eV or −10 eV to generate precursor ions, and in second
experiment, this value was increased to 30 eV or −30 eV to produce product ions. Both experiments
ran in full scan modes.
High-resolution MS, isotope abundance ratios, MS/MS, the Human Metabolome database (https:
//hmdb.ca/), the METLIN database (https://metlin.scripps.edu/), PubChem database (https://pubchem.
ncbi.nlm.nih.gov/), a literature search, and standard references were applied to identify ion structures.
For the quantiﬁcation of polyphenols, Japser HPLC system coupled to 4500 MD (AB Sciex company,
Concord, ON, Canada) was used. Related MS parameters are listed in Table S2. Due to lack of stable
isotope-labeled standards of polyphenols, the method of standard addition was employed to quantify
endogenous polyphenols in Trollius plants. A series of diluted standard references of polyphenols
in diﬀerent concentrations were added into Trollius extract matrix to construct eight-point standard
calibration curves. For calibration samples, endogenous polyphenol were deducted from Trollius
extract matrix without the addition of standard references.
Parent and product ions, generated from IDA and DIA method experiments, were extracted using
MarkerView 1.3 and MultiQuant 3.0.2 (AB Sciex company, Concord, ON, Canada).
Self-compiled R language program was used to process IDA and DIA data. R 3.6.2, used in this
work, was downloaded from open source (https://www.R-project.org/), . For IDA data, the program
can determine if the ion pairs belong to polyphenols according to characteristic fragmentations (Tables 1
and 2). For DIA data, the program ﬁrst attributes all product ions to their corresponding parent ions
with the parameters (rt, peak width, tailing factors), then determines whether they are polyphenols
based on characteristic fragmentations.
Standard references, (-)-Epigallocatechin, kaempferol-3-O-rutinosid, and resveratrol, not detected
in globeﬂowers, were used as internal standards to calibrate MS data for quantiﬁcation. The ﬁrst
standard is aglycones, used for calibration of all ﬂavonoids without glycoside, the second is applied
for calibrating all ﬂavonoids with glycoside, and the third is phenolic acid for calibrating all phenolic
acid components. In addition, individual contents of those semi-quantiﬁed 104 polyphenols were
referenced to their corresponding ﬂavonoid aglycones, ﬂavonoid glycosides, or phenolic acids from
these three internal standards.
Precision studies were performed according to international guidelines (International Conferenceon
Harmonisation, Harmonised Tripartite Guideline, and Validation of Analytical Procedures: Text and
Methodology Q2(R1). 1994). Globeﬂower extracts were spiked with known concentrations (low,
middle, and high) of each polyphenol (Table S3). Reproducibility was assessed by inter- and intra-assay
coeﬃcient of variation (CV). The inter-assay CV was established by performing 5 assay replicates by
three consecutive days. The intra-assay CV was established by 5 replicates. Recovery was calculated on
low, medium, and high concentrations of standard references with ﬁve parallel replicates. The recovery
of the spiked standards was determined by assaying two sets of samples: peak areas of endogenous
metabolites were subtracted from those of matrix samples (set 1), and subtracted from those of matrix
samples added with standards after preparation (set 2). The recoveries of spiked standards were
calculated as the percent ratio of set 1 peak areas to set 2 peak areas.
Our current study reports the systematic characterization and quantiﬁcation of polyphenols
endogenous to two Trollius species, namely Trollius chinensis Bunge and Trollius ledebouri Reichb. In all,
154 polyphenols (131 identiﬁed, 23 unidentiﬁed) were proﬁled and quantiﬁed using a combination of
HPLC-QqQ-MS and UPLC-HR-MS operating in both IDA and DIA modes. Our ﬁndings showed that
T. chinensis and T. ledebouri are remarkably diﬀerent in terms of polyphenol content and composition,
and contributed new information in terms of standardizing the use of globeﬂowers in Chinese
Metabolites 2020, 10, 119 11 of 12
medicine. Future studies to further evaluate potential diﬀerences in other pharmalogical aspects of
the Trollius species, such as antiviral potency and anti-inﬂammation capacity, are needed to ensure
better consistency in the therapeutic eﬃcacy of globeﬂowers. Although Trollius extracts have been
widely and traditionally used in Chinese medicine, large-scale clinical trials to evaluate the therapeutic
eﬀects of globeﬂowers in human cohorts are by far lacking, and formal assessment via randomized,
placebo-controlled clinical trials should be conducted in future.
Supplementary Materials: The following are available online at http://www.mdpi.com/2218-1989/10/3/119/s1,
Figure S1. XICs of polyphenol reference compounds using diﬀerent columns, Table S1. Standard references used
for quantiﬁcation, Table S2. MRM parameters used for method validation, Table S3. Summary of the method
validation performance characteristics as determined in extracts from Chinese globeﬂower. Samples (n = 5),
Table S4. Absolute quantiﬁcation results of T. chinensis and T. ledebouri by QqQ-MS. Samples (n = 5), Table S5.
Quantitative results of 154 polyphenols in T. chinensis and T. ledebouri extracts.
Author Contributions: Conceptualization, S.M.L., G.S., and H.T.; methodology, H.T., Z.Z.; validation, H.T., Z.Z.;
formal analysis, H.T., Z.Z.; investigation, H.T., Z.Z.; writing—original draft preparation, H.T.; writing—review
and editing, S.M.L., G.S.; supervision, S.M.L., G.S.; funding acquisition, G.S. All authors have read and agreed to
the published version of the manuscript.
Funding: This research was funded by National Key R&D Program of China (2018YFA0800901, 2018YFA0506902),
The Strategic Priority Research Program of the Chinese Academy of Sciences (XDA12030211), Ningxia Hui
Autonomous Region (NTKJ2018-06), National Natural Science Foundation of China (31671226, 31871194).
Conﬂicts of Interest: The authors declare no conﬂict of interest.
1. Witkowska, B.E. Flavonoids from Trollius europaeus ﬂowers and evaluation of their biological activity.
J. Pharm. Pharmacol. 2018, 70, 550–558. [CrossRef] [PubMed]
2. Wu, X.A.; Zhao, Y.M.; Yu, N.J. Flavone c-glycosides from Trollius ledebouri reichb. J. Asian Nat. Prod. Res.
2006, 8, 541–544.
3. Yuan, M.; Wang, R.F.; Liu, L.J.; Yang, X.; Peng, Y.S.; Sun, Z.X. Contribution evaluation of the ﬂoral parts to
orientin and vitexin concentrations in the ﬂowers of Trollius chinensis. Chin. J. Nat. Med. 2013, 11, 699–704.
4. Shi, D.; Chen, M.; Liu, L.; Wang, Q.; Liu, S.; Wang, L.; Wang, R. Anti-inﬂuenza A virus mechanism of three
representative compounds from Flos Trollii via TLRs signaling pathways. J. Ethnopharmacol. 2020, 28, 112634.
5. Liu, Y.; Tong, J.; Tong, Y.; Li, P.; Cui, X.; Cao, H. In vitro anti-inﬂuenza virus eﬀect of total ﬂavonoid from
Trollius ledebouri Reichb. J. Int. Med. Res. 2018, 46, 1380–1390.
6. Davatgaran-Taghipour, Y.; Masoomzadeh, S.; Farzaei, M.H.; Bahramsoltani, R.; Karimi-Soureh, Z.; Rahimi, R.;
Abdollahi, M. Polyphenol nanoformulations for cancer therapy: Experimental evidence and clinical
perspective. Int. J. Nanomedicine. 2017, 12, 2689–2702. [CrossRef]
7. An, F.; Yang, G.; Tian, J.; Wang, S. Antioxidant eﬀects of the orientin and vitexin in Trollius chinensis Bunge
in D-galactose-aged mice. Neural. Regen. Res. 2012, 7, 2565–2675.
8. Witkowska, B.E. The genus Trollius-review of pharmacological and chemical research. Phytother. Res. 2015,
29, 475–500. [CrossRef]
9. Sioud, F.; Amor, S.; Toumia, I.B.; Lahmar, A.; Aires, V.; Chekir-Ghedira, L.; Delmas, D. A new highlight of
ephedra alata decne properties as potential adjuvant in combination with cisplatin to induce cell death of
4T1 breast cancer cells in vitro and in vivo. Cells 2020, 9, 362. [CrossRef]
10. Li, D.Y.; Wei, J.X.; Hua, H.M.; Li, Z.L. Antimicrobial constituents from the ﬂowers of Trollius chinensis.
J. Asian Nat. Prod. Res. 2014, 16, 1018–1023.
11. Li, D.; Wang, Q.; Xu, L.; Li, M.; Jing, X.; Zhang, L. Pharmacokinetic study of three active ﬂavonoid glycosides
in rat after intravenous administration of Trollius ledebourii extract by liquid chromatography. Biomed.
Chromatogr. 2008, 22, 1130–1136.
12. Guo, L.; Qiao, S.; Hu, J.; Li, D.; Zheng, S.; Shi, D.; Liu, J.; Wang, R. Investigation of the eﬀective components
of the ﬂowers of Trollius chinensis from the perspectives of intestinal bacterial transformation and intestinal
absorption. Pharm. Biol. 2017, 55, 1747–1758.
13. Giampieri, F.; Afrin, S.; Stewart, D.; McDougall, G.J.; Brennan, R.; Blyth, L.; Gasparrini, M.; Mazzoni, L.;
Capocasa, F.; Alvarez-Suarez, J.M.; et al. Phytochemical Composition and Cytotoxic Eﬀects on Liver
Metabolites 2020, 10, 119 12 of 12
Hepatocellular Carcinoma Cells of Diﬀerent Berries Following a Simulated In Vitro Gastrointestinal Digestion.
Molecules 2018, 23, 1918. [CrossRef] [PubMed]
14. Shui, G.; Leong, L.P. Screening and identiﬁcation of antioxidants in biological samples using high-performance
liquid chromatography-mass spectrometry and its application on Salacca edulis Reinw. J. Agric. Food Chem.
2005, 53, 880–886.
15. Peters, K.; Treutler, H.; Döll, S.; Kindt, A.S.D.; Hankemeier, T.; Neumann, S. Chemical Diversity and Classification
of Secondary Metabolites in Nine Bryophyte Species. Metabolites 2019, 9, 222. [CrossRef] [PubMed]
16. La Barbera, G.; Capriotti, A.L.; Cavaliere, C.; Montone, C.M.; Piovesana, S.; Samperi, R.; Zenezini Chiozzi, R.;
Laganà, A. Liquid chromatography-high resolution mass spectrometry for the analysis of phytochemicals in
vegetal-derived food and beverages. Food Res. Int. 2017, 100, 28–52. [CrossRef]
17. Gangopadhyay, N.; Rai, D.K.; Brunton, N.P.; Gallagher, E.; Hossain, M.B. Antioxidant-guided isolation and
mass spectrometric identiﬁcation of the major polyphenols in barley (Hordeum vulgare) grain. Food Chem.
2016, 210, 212–220. [CrossRef]
18. Wu, T.; Lv, H.; Wang, F.; Wang, Y. Characterization of Polyphenols from Lycium ruthenicum Fruit by
UPLC-Q-TOF/MS(E) and Their Antioxidant Activity in Caco-2 Cells. J. Agric. Food Chem. 2016, 64, 2280–2288.
19. Haag, A.M. Mass Analyzers and Mass Spectrometers. Adv. Exp. Med. Biol. 2016, 919, 157–169.
20. Tsugawa, H.; Satoh, A.; Uchino, H.; Cajka, T.; Arita, M.; Arita, M. Mass Spectrometry Data Repository Enhances
Novel Metabolite Discoveries with Advances in Computational Metabolomics. Metabolites 2019, 9, 119. [CrossRef]
21. Alcoriza-Balaguer, M.I.; García-Cañaveras, J.C.; López, A.; Conde, I.; Juan, O.; Carretero, J.; Lahoz, A.
LipidMS: An R Package for Lipid Annotation in Untargeted Liquid Chromatography-Data Independent
Acquisition-Mass Spectrometry Lipidomics. Anal. Chem. 2019, 91, 836–845. [CrossRef] [PubMed]
22. Zhou, W.; Shan, J.; Tan, X.; Zou, J.; Yin, A.; Cai, B.; Di, L. Eﬀect of chito-oligosaccharide on the oral absorptions
of phenolic acids of Flos Lonicerae extract. Phytomedicine 2014, 21, 184–194.
23. Wu, Y.H.; Zhang, B.Y.; Qiu, L.P.; Guan, R.F.; Ye, Z.H.; Yu, X.P. Structure Properties and Mechanisms of Action
of Naturally Originated Phenolic Acids and Their Derivatives against Human Viral Infections. Curr. Med.
Chem. 2017, 24, 4279–4302.
24. Zhou, X.; Chen, X.; Wu, X.; Cao, G.; Zhang, J. Characterization of the chemical composition of white
chrysanthemum ﬂowers of Hangzhou by using high-performance ion trap mass spectrometry. J. Sep. Sci.
2016, 39, 1218–1222.
25. Heyman, H.M.; Senejoux, F.; Seibert, I.; Klimkait, T.; Maharaj, V.J.; Meyer, J.J. Identiﬁcation of anti-HIV
active dicaﬀeoylquinic and tricaﬀeoylquinic acids in helichrysum populifolium by NMR-based metabolomic
guided fractionation. Fitoterapia 2015, 103, 155–164. [CrossRef] [PubMed]
26. Liao, M.; Cheng, X.; Zhang, X.; Diao, X.; Liang, C.; Zhang, L. Qualitative and Quantitative Analyses of Active
Constituents in Trollius ledebourii. J. Chromatogr. Sci. 2018, 56, 619–635.
27. Forouzesh, A.; Samadi Foroushani, S.; Forouzesh, F.; Zand, E. Reliable Target Prediction of Bioactive
Molecules Based on Chemical Similarity Without Employing Statistical Methods. Front. Pharmacol. 2019, 10,
28. Lam, S.M.; Shui, G. Lipidomics as a principal tool for advancing biomedical research. J. Genet. Genomics.
2013, 40, 375–390. [CrossRef]
29. Wang, R.X.; Li, B.W.; Lam, S.M.; Shui, G. Integration of lipidomics and metabolomics for in-depth
understanding of cellular mechanism and disease progression Journal of Genetics and Genomics. J. Genet.
Genom. 2019, in press. [CrossRef]
30. Tian, H.; Lam, S.M.; Shui, G. Metabolomics, a Powerful Tool for Agricultural Research. Int. J. Mol. Sci. 2016,
31. Wu, L.Z.; Zhang, X.P.; Xu, X.D.; Zheng, Q.X.; Yang, J.S.; Ding, W.L. Characterization of aromatic glycosides in
the extracts of Trollius species by ultra high-performance liquid chromatography coupled with electrospray
ionization quadrupole time-of-ﬂight tandem mass spectrometry. J. Pharm. Biomed. Anal. 2013, 75, 55–63.
32. The R Project for Statistical Computing. Available online: https://www.r-project.org/ (accessed on 12 February
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).