Analytica Chimica Acta 846 (2014) 60–67

Dereplication of depsides from the lichen Pseudevernia furfuracea bycentrifugal partition chromatography combined to 13C nuclearmagnetic resonance pattern recognition

Sarah K. Oettl a, Jane Hubert b,*, Jean-Marc Nuzillard b, Hermann Stuppner a,Jean-Hugues Renault b, Judith M. Rollinger a

a Institute of Pharmacy/Pharmacognosy, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innrain 80–82, 6020 Innsbruck, Austriab Institut de Chimie Moléculaire de Reims (UMR CNRS 7312), SFR CAP'sANTE, UFR de Pharmacie, Université de Reims Champagne-Ardenne, BP 1039, 51687Reims Cedex 2, France

H I G H L I G H T S G R A P H I C A L A B S T R A C T

� The major depsides of a lichenextract were directly identified with-in mixtures.

� The initial extract was rapidly frac-tionated by CPC in the pH-zonerefining mode.

� Hierarchical clustering of 13C NMRsignals resulted in the identificationof depside molecular skeletons.

� 13C chemical shift clusters wereassigned to structures using a 13CNMR database.

� Six depsides were unambiguouslyidentified by this approach.

Pseudeve rnia furf uraceaLichen de psides

Fragile metaboli tesCentr ifugal Par� �on

Chromatog raphy(pH-zone refini ng)

Simpli fied mixtures 13C NMRHCA p a�ern recog ni�on

f1f2

f15

DEREPLICATION

on

13C NMR Dat abase

METABOLITEIDENTIFI CATION

1

2 3

H

2

1

A R T I C L E I N F O

Article history:Received 12 March 2014Received in revised form 4 July 2014Accepted 7 July 2014Available online 15 July 2014

Keywords:Centrifugal partition chromatography13C nuclear magnetic resonanceHierarchical clustering analysisDereplicationDepsideLichen

A B S T R A C T

Lichens produce a diversity of secondary metabolites, among them depsides comprised of two or morehydroxybenzoic acid units linked by ester, ether, or C��C-bonds. During classic solid support-basedpurification processes, depsides are often hydrolyzed and in many cases time, consuming proceduresresult only in the isolation of decomposition products. In an attempt to avoid extensive purification stepswhile maintaining metabolite structure integrity, we propose an alternative method to identify the majordepsides of a lichen crude extract (Pseudevernia furfuracea var. ceratea (Ach.) D. Hawksw., Parmeliaceae)directly within mixtures.Exploiting the acidic character of depsides and differences in polarity, the extract was fractionated bycentrifugal partition chromatography in the pH-zone refining mode resulting in twelve simplifiedmixtures of depsides. After 13C nuclear magnetic resonance analysis of the produced fractions, the majormolecular structures were directly identified within the fraction series by using a recently developedpattern recognition method, which combines spectral data alignment and hierarchical clusteringanalysis. The obtained clusters of 13C chemical shifts were assigned to their corresponding molecular

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Analytica Chimica Acta

journal homepa ge: www.elsev ier .com/locate /aca

* Corresponding author. Tel.: +33 326918325.E-mail address: jane.hubert@univ-reims.fr (J. Hubert).

http://dx.doi.org/10.1016/j.aca.2014.07.0090003-2670/ã 2014 Elsevier B.V. All rights reserved.

S.K. Oettl et al. / Analytica Chimica Acta 846 (2014) 60–67 61

structures with the help of an in-house 13C NMR chemical shift database, resulting in six unambiguouslyidentified compounds, namely methyl b-orcinolcarboxylate (1), atranorin (2), 5-chloroatranorin (3),olivetol carboxylic acid (4), olivetoric acid (5), and olivetonide (6).

ã 2014 Elsevier B.V. All rights reserved.

1. Introduction

Lichens are defined as mutualistic symbiosis consisting of fungi(mycobionts) and algae/cyanobacteria (photobionts/cyanobionts).Withinthese uniqueassociations,especially fungal partners producea diversity of characteristic secondary lichen metabolites whichenhance their growth conditions and protect the symbiosis againsthazards like pathogens and predators, intense UV light or oxidativestress. These metabolites can thus be considered as products ofadaptabilityand contribute to the vast distribution of lichens, even inextreme climates and environments hostile to higher plants. Lichensare very sensitive to changes in their habitat serving as useful airpollution indicators [1,2], but simultaneously, hampering thebreeding of lichens. In addition to mevalonate-derived terpenoidsand shikimate-derived pulvinic acid derivatives, most lichen speciesare able to synthesize a variety of phenolic compounds likephloroglucinol derivatives, depsides, depsidones, depsones, anthra-quinones, xanthones and chromones via the polymalonyl pathway[3]. Depsides consist of two or more hydroxybenzoic acid unitslinked byester, ether, orC��C-bonds. Theycanbeclassifiedaccordingto the number (di-, tri-, tetradepsides) [4] or to the basic structureand connectivity (orcinol-para-, b-orcinol-para-, meta-depsides)[5] of linked moieties (Fig. 1). Further structural variations resultfrom the substitution patterns of the aromatic ring regarding thelength of side chains, oxidation and methylation degrees [5].Recently, we identified depsides as potent anti-inflammatorynatural products with multi-target in vitro effects and promisingactivities in an in vivo mouse model [6]. Other studies further reporton the bioactivities of depsides and depsidones in the field ofantioxidant, antimicrobial, and anticancer properties [7,8] andemphasize the phytomedical potential of this compound class.

Pseudevernia furfuracea (L.) Zopf (Parmeliaceae) is a well-investigated folios lichen, commercially used in the perfumeindustry as a fragrance or for the preservation of odors [3,9]. Itgrows on the bark of coniferous trees and can be distinguished inseveral morphologically identical chemotypes [10,11]. For our

β-or cinol para -depsides

Atrano rin

orcinol para -depsides

Imbricaric acid Orcino l

β-Orcino l Fig. 1. Structural diversity of d

analysis, we selected P. furfuracea var. ceratea (Ach.) D. Hawksw.which is recognized to contain a range of depsides and depsidonesin addition to its major compound, olivetoric acid [12].

The main chromatographic technique described in the literaturefor the isolation of lichen substances is column chromatography[8,13,14]. Thereby, fragile compounds such as depsides which tend tostructural rearrangement often degrade into their monocyclicprecursors due to irreversible adsorption [5,13] (Fig. 2). Depsidoneswhich are characterized by an additional ether linkage remain morestable. In this study, we aimed to separate and characterize depsidesand depsidones from the crude extract of the lichen P. furfuracea bycombining centrifugal partition chromatography (CPC) to a patternrecognition procedure allowing the direct 13C NMR identification ofstructures present in mixtures of the CPC-generated fractions,without purification of individual components.

CPC is a solid support free liquid–liquid separation techniqueinvolving the distribution and transfer of solutes between at leasttwo immiscible liquid phases according to their partition coefficientwhich avoids irreversible adsorption of the analytes due to theabsence of solid support, allows a total recovery of injected samplesand enables separations of a variety of structures within a largepolarity range [15–17]. Considering the possibility to protonate ordeprotonate depsides under pH variations, the pH-zone refiningmode was selected to develop our CPC method. It consists of (i)adding a base (oran acid) as retaining agentto the stationaryphase inorder to capture the ionizable target compounds inside the columnand (ii) eluting the compounds with an acidic (or basic) displacer inthe mobile phase through progressive neutralization according to Ka

and KD values of each compound. This novel lichen separationtechnique is expected to be a promising alternative for thephytochemical screening of lichen substances particularly withrespect to metabolite preservation, economy of time and solvents.

The metabolites recovered as simplified mixtures in the pH-zone refining CPC-generated fractions were directly identified by adereplication strategy, which consists in 13C NMR analyses of thefraction series, alignment of 13C chemical shifts across spectra and

β-or cinol meta -depsides

Sekikaic acid

Tha mno lic acid

orcinol meta -depsides orcinol depsidones

Divaron ic acid

β-or cinol depsidones

Viren sic acid

epsides and depsidones.

Atrano rin (2)m/z 37 4

Methyl he matommatem/z 210

Methyl β -orcino lcarbo xylate (1)m/z 19 7

Alcoholysis

Fig. 2. Example for a commonly observed degradation process of depsides.

62 S.K. Oettl et al. / Analytica Chimica Acta 846 (2014) 60–67

hierarchical clustering analysis (HCA) of the resulting two-dimensional dataset [18]. The aim of this pattern recognitionapproach is to highlight the statistical correlations between13C NMR signals within the fraction series and directly visualizethe individual metabolites as “chemical shift clusters”. Theseclusters are then assigned to molecular structures by using a locallybuilt 13C NMR database of natural metabolites containing thepredicted 13C chemical shifts of a range of depsides and depsidonesdescribed in the literature. The results obtained by this strategywere validated by further LC-DAD-ESI/MSn and 2D NMR analyses inorder to verify the predictive performance of this novel databaseand confirm metabolite identification.

2. Materials and methods

2.1. Materials

2.1.1. Solvents and reagentsAcetone, ethyl acetate (EtOAc), methyl tert-butyl ether (MtBE),

methanol (MeOH), diethyl ether (Et2O), n-hexane, and n-heptaneof analytical quality were purchased from VWR (Fontenay-sous-Bois, France). Sodium hydroxide (NaOH), formic acid (FA) andtrifluoroacetic acid (TFA) of analytical quality as well as MeOH andtetrahydrofuran (THF) of gradient grade were purchased fromMerck (Darmstadt, Germany). Aqueous solutions were preparedwith ultrapure water. Deuterated dimethyl sulfoxide (DMSO-d6)was purchased from Sigma–Aldrich (Saint-Quentin, France).

2.1.2. Plant materialThalli of the lichen P. furfuracea var. ceratea (Ach.) D. Hawksw.

were collected from the bark of Arolla pine (Pinus cembra) in Ötztal,Tyrol, Austria (N 46�51.550 E 11�1.120, altitude 1050 m) in August2011. The lichen material was unambiguously identified accordingto the classification key of Wirth [19] by means of microscopic andmicro-chemical analyses. A voucher specimen (JR-20110811-A26)was deposited at the Institute of Pharmacy/Pharmacognosy,University of Innsbruck, Austria.

2.2. Extract preparation

123 g air-dried thalli of P. furfuracea (var. ceratea) were grindedwith a Micro-Dismembrator U-ball mill (Sartorius AG, Göttingen,Germany) and extracted at room temperature with acetone usingan ultrasonic bath (1 �1230 mL, 5 � 615 mL, 1 h each). Aftercentrifugation of the suspension, the supernatant was evaporatedto dryness and yielded 12.6 g of crude extract.

2.3. Stability test

Since pH-zone refining CPC implies acid–base reactions withthe analytes, the stability of the lichen extract under pH variationswas examined from pH 1–14. In two independent test tubes, 30 mgof crude extract were dissolved in a mixture of 10 mL organic phaseand 10 mL aqueous phase of the biphasic solvent system MtBE/MeOH/water (10:1:10; v/v/v). The resulting solutions were initially

at pH 5. The first solution was acidified by adding diluted TFAdropwise to decrease the pH stepwise to 1. The second solution wasalkalized by adding 0.1 M NaOH increasing the pH stepwise to 14.The pH was monitored with indicator strips (Acilit1 and Alkalit1

Merck, Darmstadt, Germany). At every pH value, the upper andlower phases were sampled and promptly analyzed by thin-layerchromatography (TLC) and high performance liquid chromatogra-phy (HPLC; methods described in Sections 2.5.1 and 2.5.2,respectively) for a qualitative assessment of degradation.

2.4. Centrifugal partition chromatography (CPC)

2.4.1. CPC apparatusCPC experiments were performed on a FCPC1200 apparatus

(Kromaton Technology, Angers, France) equipped with a rotormade of 20 circular partition disks containing 1320 partition cells(0.130 mL per cell, 200 mL total column capacity) and connected toa Gilson pump model 302 (Villiers-Le-Bel, France). The eluent wascollected with a SuperFrac fraction collector (Pharmacia, Uppsala,Sweden) in periods of 2 min per fraction.

2.4.2. pH-zone refining CPCA biphasic solvent system was prepared by mixing MtBE, MeOH

and water in the proportion 10:1:10 (v/v/v) in a separation funnel.After phase separation, NaOH (10 mM, pH 12) was added asretainer to the aqueous stationary phase, while TFA (8 mM, pH 2)was added as displacer to the organic mobile phase. The CPCcolumn was filled with the alkalized stationary phase at 500 rpm.After accelerating the rotation to 1000 rpm and equilibrating withthe non-acidified upper phase, 400 mg of the acetone extract wasdissolved in a 20 mL mixture of alkalized aqueous phase and non-acidified organic phase (1:1, v/v), adjusted to pH 9, and injectedthrough a 20 mL sample loop. The acidified mobile phase waspumped at 2 mL min�1 in the ascending mode for 240 min until thepH of the eluent decreased to 1, and the displacement was finished.

Experimental conditions for the separation procedure aresummarized in Table 1.

2.5. Characterization of CPC fractions

2.5.1. TLC monitoringThe separation process was assessed by TLC. Each collected

fraction was spotted on Merck TLC plates coated with silica gel 60F254 and developed with n-hexane/Et2O/FA (5:3:1; v/v/v). Afterdetection at UV254 and UV366, the plates were sprayed withvanillin–sulfuric acid and heated to �100 �C for 5 min. Fractions ofsimilar composition were combined resulting in 12 fractions(F1–F12, Fig. S1).

2.5.2. LC-DAD-ESI/MSn analysesFractions F1–12 were analyzed by HPLC using a 1100 Agilent

system (Agilent, Waldbronn, Germany) equipped with a photodi-ode array detector set at 235 nm. The column (Phenomenex1

Synergi Polar-RP 80A, 4.6 � 150 mm; 4 mm particle size) wasmaintained at 35 �C. The mobile phases consisted of 0.1% FA in

Table 1Experimental conditions for the pH-zone refining CPC experiment.

Conditions pH-zone refining CPC

Biphasic solvent system MtBE/MeOH/water 10:1:10 (v/v/v; ascending mode)Stationary phase (SP) Lower aqueous phase + NaOH (10 mM)Mobile phase (MP) Upper organic phase + TFA (8 mM)Applied sample 400 mg in 10 mL SP + 10 mL non-acidified MPFlow rate 2 mL min�1

Rotation speed 1000 rpmBack pressure 43 barStationary phase retention 65%Collection mode 4 mL per fractionTotal solvent consumption 480 mLRecovery rate 60%

S.K. Oettl et al. / Analytica Chimica Acta 846 (2014) 60–67 63

water (solvent A) and MeOH mixed with 1.5% THF (solvent B). Theseparation was performed at a flow rate of 1 mL min�1 by using thefollowing gradient: 60% solvent B increased to 62% in 5 min, then to63% in 10 min, maintained for 10 min and increased to 70 % in3 min, to 72% in 6 min, to 73% in 3 min and finally to 98% in 2 minand maintained for 10 min. The HPLC system was coupled to aBruker Esquire 3000plus iontrap mass spectrometer (BrukerDaltonics, Bremen, Germany) equipped with an electrospray(ESI) interface and fitted to the following parameters: LC flowsplit–1:5; spray voltage–4.5 kV, 365 �C; dry gas–N2, 9 L min�1;nebulizer–He, 40 psi. The precursors and product (MS2, MS3, MS4)ions were detected in the scanning range of m/z 100–1500, both inthe positive and negative ionization mode.

2.6. 13C NMR analyses and data processing

Fractions F1–F12 were dried under vacuum at room temperatureand a maximum of 20 mg of each was dissolved in 500 mL DMSO-d6.NMR analyses were performed at 298 K on a Bruker Avance AVIII-600 spectrometer (Karlsruhe, Germany) equipped with a cryoprobeoptimized for 1H detection and with cooled 1H, 13C and 2D coils andpreamplifiers. 13C NMR spectra were acquired at 150.91 MHz. Astandard zgpg pulse sequence was used with an acquisition time of0.909 s and a relaxation delay of 3 s. For each sample, 256 scans wereco-added to obtain a satisfactory signal-to-noise ratio. The spectralwidth was 238.9070 ppm, and the receiver gain was set to thehighest possible value. A 1 Hz line broadening filter was applied toeach FID prior to Fourier transformation. The spectrawere manuallyphased and baseline corrected using the TOPSPIN 3.2 software(Bruker) and calibrated on the central resonance (d 39.80 ppm) ofDMSO-d6. The13C NMR spectra are provided as supplementary data.A minimum intensity threshold of 0.3% (relative to the most intensesignal of each spectrum) was then used to automatically collect allpositive 13C NMR signals while avoiding potential noise artifacts.Each peak list was then converted into a text file. Absoluteintensities of the collected peaks in the fraction series were alignedby using an in-house algorithm written in the python language. Theprinciple was to divide the 13C spectral width (from 0 to 200 ppm)into regular bins, i.e., chemical shift intervals (Dd = 0.2 ppm), and toassociate the absolute intensity of each 13C peak to the correspond-ing bin. The bins for which no signal was detected in any fractionwere removed from the bin list. The resulting table was importedinto the PermutMatrix version 1.9.3 software (LIRMM, Montpellier,France) for clustering analysis on raw peak intensity values. Theclassification was performed on the rows only, i.e., on the chemicalshift bins. The Euclidean distance was used to measure theproximity between the samples, and the Ward's method wasperformed to agglomerate the data. The resulting 13C chemical shiftclusters were visualized as dendrograms on a two-dimensionalmap. The higher the intensity of 13C NMR peaks, the brighter thecolor on the map.

2.7. 13C NMR chemical shift database

A literature survey was performed to obtain names andstructures for a maximum of metabolites already described inP. furfuracea. In total, 27 P. furfuraceae metabolites, includingdepsides, depsidones, benzofurans, sugars, amino acids, and fattyacids, were added to the 13C chemical shift database alreadycomprising the chemical shifts of 450 structures of naturalproducts (among them 64 depsides and depsidones from differentlichen species). Each metabolite data record was then stored in a13C chemical shift database by means of the ACD/NMR WorkbookSuite 2012 software (ACD/Labs, Ontario, Canada). The structureswere drawn with ChemSketch, and chemical shifts were assignedto the corresponding carbon positions. When 13C chemical shiftswere not available in the literature, a predicted spectrum wascalculated with the ACD/Labs C NMR Predictor software, and theresulting 13C chemical shifts were supplied to the database. Formetabolite identification, each 13C chemical shift cluster obtainedfrom HCA was submitted to the structure search engine of thedatabase management software. A 13C NMR chemical shifttolerance of �2 ppm was used.

Additional 2D NMR experiments (HSQC, HMBC, and COSY) ofthe combined fractions F1–F12 were performed on the sameBruker Avance AVIII-600 spectrometer, by using standard Brukerpulse programs (Bruker, Karlsruhe, Germany) in order to confirmthe structures of the identified compounds. Structural data is listedin Table S2 in the supplementary file.

3. Results and discussion

The multi-component mixture obtained by extraction of driedthalli of P. furfuracea var. ceratea with acetone was selected asmodel extract to rapidly characterize the contained depsides anddepsidones by applying a recently developed dereplicationstrategy. This lichen species is easily accessible in subalpine zonesof Europe and was described to contain olivetoric acid as mainconstituent, a diversity of other depsides and eventually dep-sidones [12,20]. The combination of solid free liquid–liquidchromatography with 13C NMR and HCA-based pattern recognitionrepresents a promising alternative tool for the identification ofmajor compounds, and especially fragile compounds, present incrude extracts.

3.1. Production of simplified mixtures by CPC

A pH-zone refining CPC method was developed to separatedepsides on the basis of their acidic character due to carboxylic andphenolic moieties. The pH-zone refining mode is indeed dedicatedto the separation of compounds whose electric charge depends onthe pH value [21–23] and has been widely used in CPC for theseparation of alkaloids [15–17], amino acids, peptides [21–23],

64 S.K. Oettl et al. / Analytica Chimica Acta 846 (2014) 60–67

dyes [24–27], and to a lesser extend polyphenols [28–31]. In orderto ensure the stability of the depsides and depsidones under pHvariations, the TLC and HPLC profiles of the crude extract werepreliminarily investigated within a pH range of 1–14. In acidicconditions, the substances were stable without any degradationbetween pH 1 and pH 7. During gradual alkalization of the testsolution, the composition of the extract remained stable up to pH10. At values higher than pH 11, additional signals resulting fromdegradation products, which had not been present in the originalprofile, became apparent by TLC and HPLC analysis.

The pH-zone refining CPC fractionation of the crude extract wasperformed by using a biphasic solvent system primarily composingof MtBE and water. Since the acetone crude extract of P. furfuraceacontained a diversity of compounds within a large polarity range(fatty acids, polyphenols, sugars, mucilage), MeOH was added asthird solvent to reduce the polarity difference between stationaryand mobile phase and ensure the solubility of all substances. Basedon the preliminary pH stability test, the sample was adjusted to pH9 before injection to enable the protonation of the containeddepsides and depsidones. Thus, NaOH was added to the aqueousstationary phase as retainer in a concentration of 10 mM and TFAwas added to the organic mobile phase as displacer in aconcentration of 8 mM (Table 1). Fig. 3 shows the HPLC fractogramof the pH-zone refining CPC run, obtained after the injection of400 mg of the P. furfuracea crude extract dissolved in 20 mL 1:1-mixture of alkalized stationary phase and non-acidified mobilephase. Under the optimized conditions of 2 mL min�1

flow rate and1000 rpm, the back pressure was maintained at 43 bar after therelease of the mobile phase front (t = 35 min). The initial stationaryphase retention was 65%. Gradual neutralization of the basicstationary phase released the protonated compounds from theaqueous to the organic phase with decreasing pKD and pKa.Retention of the stationary phase was of 61% at the end of theprocess. The pH value remained permanently at pH 6 during thedisplacement for 170 min. Then, the pH decreased gradually to pH5. After 240 min in total the pH value quickly dipped to pH 1 andthe CPC fractionation was completed resulting in 12 fractions (F1–F12). The recovery rate accounted 60% of the fractionated sample.By pumping out the aqueous stationary phase the remainingsample comprising of mainly very polar sugars was fully retrieved.This part was not taken into account for the rest of the study. Thefractions yielded between 5.2 mg (F1) and 68.5 mg (F6) (Fig. 3).

3.2. Characterization of CPC fractions

For the evaluation of the separation, obtained CPC fractionswere monitored by both, TLC and HPLC-DAD-ESI/MSn analyses.Fraction F1 did not contain any substance. In fractions F2–F4,eluting during the initial 90 min of the process, a major compound

0

20000000

40000000

60000000

80000000

100000000

F1 F2 F3 F4 F5 F6 F7 5.2 13.0 18.6 21.8 45.4 68.5 7.8 Yie lds [mg]:

AUC

Fig. 3. Fractogram of the eight most characteristic compounds f

(6) with m/z 248 and a co-eluting minor constituent (1) with m/z196 were detected. One compound (2) with m/z 374 elutedconstantly starting from fraction F3 after 76 min, another one (3)with m/z 408 starting from fraction F4 after 90 min until the end ofthe process. Between 90 and 180 min, a major compound (5) withm/z 472 was recovered in fractions F5–F8. Another metabolite (4)with m/z 224 was recovered in fractions F8–F11 (180–210 min). Asubstance (7) detected with m/z 470 in fractions F7 and F8 wascollected between 160 and 180 min. In fraction F11 (210–220 min)a substance (8) with m/z 266 was detected. TLC and HPLC analysesclearly showed that eight compounds were enriched within thefraction series (Figs. S1 and S2). The elution profile of these eightcharacteristic compounds is depicted as a HPLC fractogram inFig. 3. The content of identified compounds within the fractionseries (Table S1) is provided as supplementary data.

3.3. 13C NMR analyses and hierarchical clustering analysis

NMR is a frequently used profiling tool for the qualitative andquantitative analysis of natural products in complex mixtures. Dueto the ubiquitous occurrence of hydrogen atoms in organiccompounds, many strategies are currently developed based on1H NMR analysis hyphenated to chromatographic techniques.However, in most cases 1H spectra of complex mixtures result inoverlapping signals. As an alternative, an original patternrecognition strategy based on 13C NMR has been recentlydeveloped for natural metabolite identification [18]. The greatestadvantage of using 13C NMR is the single 13C signal correspondencewith one specific 13C position of the molecule leading to spectra ofhigher simplicity.

Applying this 13C NMR pattern recognition approach, thefraction series obtained from CPC was analyzed by 13C NMR inorder to directly determine the chemical composition of thesimplified mixtures. The TLC and HPLC analysis revealed F1 asnegligible fraction (devoid of depsides and depsidones), hence itwas not included in this study. All other CPC-generated fractionscomprised in total eight predominant compounds and wereinvestigated by 13C NMR analysis, which was performed within18 min (256 scans) for each sample.

The 13C signals detected in each fraction were collectedby automatic peak picking and aligned into regular bins ofDd = 0.2 ppm [18]. As a result, a two-dimensional table wasobtained with 11 columns corresponding to the 11 CPC fractionsand 132 rows corresponding to the collected signals. The table wassubjected to HCA in order to reveal 13C NMR chemical shiftcorrelations within the rows. Five well-defined clusters werehighlighted (Fig. 4). These clusters were assigned to molecularstructures with the help of a 13C NMR database comprisingmetabolites of P. furfuracea already reported in the literature.

F8 F9 F10 F11 F12

Cpd 1

Cpd 2

Cpd 3

Cpd 4

Cpd 5

Cpd 6

Cpd 7

Cpd 8

m/z:

18.9 15.1 7.7 5.8 6.8

248

196

472

224

470

266

374

408

Fraction

rom the CPC fractionation of the P. furfuracea crude extract.

Fig. 4. 13C NMR chemical shift clusters obtained by applying HCA on CPC fractions of P. furfuracea.

S.K. Oettl et al. / Analytica Chimica Acta 846 (2014) 60–67 65

3.4. Identification of lichen metabolites

After entering the 13C chemical shifts of the main cluster Blocated in fractions F3–F12 and comprised of 15 signals into thedatabase, one single structure was proposed, the structure of theb-orcinol para-depside atranorin (2) with 15 of 19 signalsmatching. For the well-defined cluster C ranging from fractionF8 to F10 the database search assigned 12 of 12 correctly matching

13C signals to the structure of the monomer olivetolcarboxylic acid(4). These results correspond to the LC–MS profiles of compound 2and 4 with m/z 374 and m/z 224, respectively. Cluster E detected infractions F2–F6 was comprised of 11 signals, which were assignedto olivetonide (6) by the database.

As clusters were classified hierarchically according to theabundance of metabolites, clusters of minor constituents wereprone to be split into two or more sub-clusters of 13C signals.

Oli vetoric acid ( 5)m/z 472

Oli vetolcarbo xyli c acid ( 4)m/z 22 4

Oli vetonic acid ( 8)m/z 26 6

Oli vetonide ( 6)m/z 24 8

Fig. 5. Degradation of olivetoric acid (5) and arising products.

66 S.K. Oettl et al. / Analytica Chimica Acta 846 (2014) 60–67

Accordingly, cluster D consisted of 19 13C signals located infractions F5–F8. Entering the shift values into the database, thestructures of microphyllinic acid, 4-O-demethylmicrophyllinic acidand olivetoric acid were proposed with 16 of 19 signals matching.By comparison of their structural characteristics, it became evidentthat microphyllinic acid and 4-O-demethylmicrophyllinic acidfeature a second carbonyl group at 207 ppm, which is missing inthe structure of olivetoric acid. The absence of this significantsignal in the raw NMR data indicated olivetoric acid as the rightstructure for cluster D. Furthermore, a sub-cluster of three signalswas detected in the same range of fractions and comparable inintensity as cluster D. In order to verify if this sub-cluster belongsto cluster D, the HCA was repeated removing the major cluster B, Cand E first. As a result cluster D and sub-cluster D0 showed up asone unified cluster and the database search unequivocallyproposed the orcinol para-depside olivetoric acid (5) as corre-sponding structure with a correct signal matching of 22 of 26.Considering that olivetoric acid is characterized by a molecularweight of 472.53 g mol�1, this finding is in accordance with the LC–MS analysis, which revealed compound 5 as major constituent inF5–F8 with m/z 472. Similarly, cluster A localized between fractionF2 and F4 was divided into two blocks of 9 signals in total. Afterentering the chemical shift values of cluster A into the database,the structure of the monoaromatic methyl b-orcinolcarboxylate,which is characterized by a molecular weight of 196.20 g mol�1,was proposed. This mass corresponds to the LC–MS profile of theminor constituent 1. No clusters were detected for the two minorcompounds 7 and 8, which were observed by LC–MS in fractionsF7–F8 and F11, respectively. By applying of the 13C NMRdereplication strategy, five out of the eight compounds fractionat-ed by CPC and detected by TLC and HPLC analyses weresuccessfully identified.

Only a few errors occurred in classification due to failures inalignment or binning. If alignment fails, slight chemical shiftvariations of a single compound across adjacent fractions can forinstance result in peak splitting into two consecutive bins and thusto an accessory data point in the 2D matrix. Binning failures canalso result from two very close 13C signals merged into one singlebin leading to loss of data. Although the bin width has previouslybeen optimized with 0.2 ppm, we observed loss of data points dueto very close 13C signals belonging to different carbon skeletons,which join in the same bin. This might be one of the reasons for thefailed identification to trace the clusters of the two minorcompounds 7 and 8 from the analyzed fractions. Strikingly, thecompounds unambiguously identified by the present 13C NMRdereplication method were distributed over three or moresuccessive fractions. By contrast compounds 7 and 8 were detectedmerely in one or two fractions by LC–MS, and were thereforehardly recognized as clusters. In addition, due to the lowconcentrations, they were possibly obscured by clusters of moreconcentrated metabolites.

Although the stability of depsides contained in the lichen crudeextract was approved between pH 1 and 10, the main compound ofP. furfuracea, olivetoric acid (5), might have been partly degraded viaester cleavage to its monomers olivetolcarboxylic acid (4) andolivetonic acid (8, Fig. 5). This hypothesis is in accordance with theLC-ESI/MSn analysis, since both the molecular ion peak ofolivetolcarboxylic acid (4) with m/z 225 [M + H]+ in the positiveionization mode (Table S4), and the molecular ion peak of olivetonicacid (8) with m/z 265 [M � H]� in the negative ionization mode(Table S3) were detected. Furthermore, the presence of olivetol-carboxylic acid (4) was confirmed by detection of cluster C, whilethat of olivetonic acid (8) remained undetected in HCA. It canbe assumed, that latter was promptly esterified after enolisation ofthe carbonyl group to form its corresponding lactone (6) and wasthus found just in low concentration. Not even a mild procedure like

pH-zone refining CPC, where the pH value remains permanentlyneutral during the replacement process and no solid support isinvolved to preserve the fragile lichen compounds completelyagainst degradation. Taking this into account, it is doubtful that analternative method would result in a gentler outcome.

The CPC fractions were additionally investigated by 2D COSY,HSQC and HMBC NMR experiments in order to confirm theidentified compounds by classical structure elucidation and tovalidate the performance of this recent 13C NMR chemical shiftdatabase. The identities of all five clustered metabolites weresuccessfully validated by LC-DAD-MS and 2D NMR analyses(Table S2). A sixth structure, namely 5-chloroatranorin, wasidentified by these additional analyses in fractions F3–F12, whichcorresponds to compound 3 with m/z 408. This implies thatcompound 2 and 3 are close structural analogues distinguishableonly by precise details in the 13C NMR profiles, e.g., dedicatedistinction in the chemical shifts of C-5, C-6 and C-9 (Table S2), andthus, cluster B represents not only the structure of compound 2 butalso parts of compound 3. By lowering the matching rate of thiscluster, the database proposed apart from atranorin (2) itsanalogue 5-chloroatranorin (3) and confirmed our findings.

4. Conclusion

The results of this study emphasize the effectiveness of rapidcharacterization of pre-fractionated plant extracts by 13C NMRchemical shift pattern recognition. Although depsides anddepsidones and their corresponding monomers are often struc-turally very close, we demonstrated in this study that even naturalproducts of similar structures can be successfully identified by theapplied workflow. Accordingly, olivetoric acid (5) and its mono-aromatic counterpart olivetolcarboxylic acid (4) which sharedthree identical 13C NMR signals could be clearly distinguished dueto their distribution in different fractions. Even dimeric andmonomeric structures of identical carbon skeleton could unam-biguously be identified by 13C pattern recognition.

In comparison to alternative CPC methods or even solid phasebased chromatographic methods, the performed pH-zone refiningCPC fractionation was revealed as a gentle, efficient and fastseparation technique to be hyphenated to a subsequent 13C NMRpattern recognition procedure. By using these complementarytechniques we could successfully identify six out of eightprominent constituents of the Alpine lichen P. furfuracea var.

S.K. Oettl et al. / Analytica Chimica Acta 846 (2014) 60–67 67

ceratea directly from the acetone crude extract without time-consuming isolation procedures.

Conflict of interest

The authors declare no conflict of interest.

Acknowledgements

This research was supported by NatProtec, a Marie CurieIndustry-Academia Partnerships and Pathways (IAPP) Fellowshipwithin the 7th European Community Framework Programme(286287) and by the Austrian Science Fund (FWF) Project ‘Drugsfrom Nature Targeting Inflammation’ (NFN-S10703). Financialsupports from the CNRS, Conseil R|%1e[ Accept ]egional deChampagne Ardenne, Conseil General de la Marne, Ministry ofHigher Education and Research (MESR) and from the EU-programme FEDER to the PlAneT CPER project are also gratefullyacknowledged.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.aca.2014.07.009.

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