Dereplication of depsides from the lichen Pseudevernia furfuracea by centrifugal partition chromatography combined to 13C nuclear magnetic resonance pattern recognition

Analytica Chimica Acta 846 (2014) 60–67

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Dereplication of depsides from the lichen Pseudevernia furfuracea by centrifugal partition chromatography combined to 13C nuclear magnetic 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, Austria Institut de Chimie Moléculaire de Reims (UMR CNRS 7312), SFR CAP'sANTE, UFR de Pharmacie, Université de Reims Champagne-Ardenne, BP 1039, 51687 Reims Cedex 2, France b

H I G H L I G H T S


The major depsides of a lichen extract were directly identified within mixtures.
The initial extract was rapidly fractionated by CPC in the pH-zone refining mode.
Hierarchical clustering of 13C NMR signals resulted in the identification of depside molecular skeletons.
13C chemical shift clusters were assigned to structures using a 13C NMR database.
Six depsides were unambiguously identified by this approach.

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

1

Pseudevernia furfuracea

Lichen depsides Fragile metabolites Centrifugal Paron Chromatography (pH-zone refining)

METABOLITE IDENTIFICATION

DEREPLICATION

Simplified mixtures

13C NMR HCA H paern recognion on

2

f1 f2

13C

NMR Database

3

f15

A R T I C L E I N F O

A B S T R A C T

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

Lichens produce a diversity of secondary metabolites, among them depsides comprised of two or more hydroxybenzoic acid units linked by ester, ether, or CC-bonds. During classic solid support-based purification processes, depsides are often hydrolyzed and in many cases time, consuming procedures result only in the isolation of decomposition products. In an attempt to avoid extensive purification steps while maintaining metabolite structure integrity, we propose an alternative method to identify the major depsides 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 by centrifugal partition chromatography in the pH-zone refining mode resulting in twelve simplified mixtures of depsides. After 13C nuclear magnetic resonance analysis of the produced fractions, the major molecular structures were directly identified within the fraction series by using a recently developed pattern recognition method, which combines spectral data alignment and hierarchical clustering analysis. The obtained clusters of 13C chemical shifts were assigned to their corresponding molecular

Keywords: Centrifugal partition chromatography C nuclear magnetic resonance Hierarchical clustering analysis Dereplication Depside Lichen 13

* Corresponding author. Tel.: +33 326918325. E-mail address: [email protected] (J. Hubert). http://dx.doi.org/10.1016/j.aca.2014.07.009 0003-2670/ ã 2014 Elsevier B.V. All rights reserved.

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structures with the help of an in-house 13C NMR chemical shift database, resulting in six unambiguously identified 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). Within these unique associations, especially fungal partners produce a diversity of characteristic secondary lichen metabolites which enhance their growth conditions and protect the symbiosis against hazards like pathogens and predators, intense UV light or oxidative stress. These metabolites can thus be considered as products of adaptability and contribute to the vast distribution of lichens, even in extreme climates and environments hostile to higher plants. Lichens are very sensitive to changes in their habitat serving as useful air pollution indicators [1,2], but simultaneously, hampering the breeding of lichens. In addition to mevalonate-derived terpenoids and shikimate-derived pulvinic acid derivatives, most lichen species are able to synthesize a variety of phenolic compounds like phloroglucinol derivatives, depsides, depsidones, depsones, anthraquinones, xanthones and chromones via the polymalonyl pathway [3]. Depsides consist of two or more hydroxybenzoic acid units linked by ester, ether, or C C-bonds. They can be classified according to the number (di-, tri-, tetradepsides) [4] or to the basic structure and connectivity (orcinol-para-, b-orcinol-para-, meta-depsides) [5] of linked moieties (Fig. 1). Further structural variations result from the substitution patterns of the aromatic ring regarding the length of side chains, oxidation and methylation degrees [5]. Recently, we identified depsides as potent anti-inflammatory natural products with multi-target in vitro effects and promising activities in an in vivo mouse model [6]. Other studies further report on the bioactivities of depsides and depsidones in the field of antioxidant, antimicrobial, and anticancer properties [7,8] and emphasize the phytomedical potential of this compound class. Pseudevernia furfuracea (L.) Zopf (Parmeliaceae) is a wellinvestigated folios lichen, commercially used in the perfume industry as a fragrance or for the preservation of odors [3,9]. It grows on the bark of coniferous trees and can be distinguished in several morphologically identical chemotypes [10,11]. For our

orcinol para-depsides

analysis, we selected P. furfuracea var. ceratea (Ach.) D. Hawksw. which is recognized to contain a range of depsides and depsidones in addition to its major compound, olivetoric acid [12]. The main chromatographic technique described in the literature for the isolation of lichen substances is column chromatography [8,13,14]. Thereby, fragile compounds such as depsides which tend to structural rearrangement often degrade into their monocyclic precursors due to irreversible adsorption [5,13] (Fig. 2). Depsidones which are characterized by an additional ether linkage remain more stable. In this study, we aimed to separate and characterize depsides and depsidones from the crude extract of the lichen P. furfuracea by combining centrifugal partition chromatography (CPC) to a pattern recognition procedure allowing the direct 13C NMR identification of structures present in mixtures of the CPC-generated fractions, without purification of individual components. CPC is a solid support free liquid–liquid separation technique involving the distribution and transfer of solutes between at least two immiscible liquid phases according to their partition coefficient which avoids irreversible adsorption of the analytes due to the absence of solid support, allows a total recovery of injected samples and enables separations of a variety of structures within a large polarity range [15–17]. Considering the possibility to protonate or deprotonate depsides under pH variations, the pH-zone refining mode was selected to develop our CPC method. It consists of (i) adding a base (or an acid) as retaining agent to the stationary phase in order to capture the ionizable target compounds inside the column and (ii) eluting the compounds with an acidic (or basic) displacer in the mobile phase through progressive neutralization according to Ka and KD values of each compound. This novel lichen separation technique is expected to be a promising alternative for the phytochemical screening of lichen substances particularly with respect to metabolite preservation, economy of time and solvents. The metabolites recovered as simplified mixtures in the pHzone refining CPC-generated fractions were directly identified by a dereplication strategy, which consists in 13C NMR analyses of the fraction series, alignment of 13C chemical shifts across spectra and

orcinol meta-depsides

Orcinol Imbricaric acid

β-orcinol para-depsides

β-Orcinol

Atranorin

Sekikaic acid

β-orcinol meta-depsides

Thamnolic acid

Fig. 1. Structural diversity of depsides and depsidones.

orcinol depsidones

Divaronic acid

β-orcinol depsidones

Virensic acid

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Alcoholysis

Atranorin (2) m/z 374

Methyl hematommate m/z 210

Methyl β -orcinolcarboxylate (1) m/z 197

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

hierarchical clustering analysis (HCA) of the resulting twodimensional dataset [18]. The aim of this pattern recognition approach is to highlight the statistical correlations between 13 C NMR signals within the fraction series and directly visualize the individual metabolites as “chemical shift clusters”. These clusters are then assigned to molecular structures by using a locally built 13C NMR database of natural metabolites containing the predicted 13C chemical shifts of a range of depsides and depsidones described in the literature. The results obtained by this strategy were validated by further LC-DAD-ESI/MSn and 2D NMR analyses in order to verify the predictive performance of this novel database and confirm metabolite identification. 2. Materials and methods 2.1. Materials 2.1.1. Solvents and reagents Acetone, ethyl acetate (EtOAc), methyl tert-butyl ether (MtBE), methanol (MeOH), diethyl ether (Et2O), n-hexane, and n-heptane of analytical quality were purchased from VWR (Fontenay-sousBois, France). Sodium hydroxide (NaOH), formic acid (FA) and trifluoroacetic acid (TFA) of analytical quality as well as MeOH and tetrahydrofuran (THF) of gradient grade were purchased from Merck (Darmstadt, Germany). Aqueous solutions were prepared with ultrapure water. Deuterated dimethyl sulfoxide (DMSO-d6) was purchased from Sigma–Aldrich (Saint-Quentin, France).

at pH 5. The first solution was acidified by adding diluted TFA dropwise to decrease the pH stepwise to 1. The second solution was alkalized 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 and lower phases were sampled and promptly analyzed by thin-layer chromatography (TLC) and high performance liquid chromatography (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 apparatus CPC experiments were performed on a FCPC1200 apparatus (Kromaton Technology, Angers, France) equipped with a rotor made of 20 circular partition disks containing 1320 partition cells (0.130 mL per cell, 200 mL total column capacity) and connected to a Gilson pump model 302 (Villiers-Le-Bel, France). The eluent was collected with a SuperFrac fraction collector (Pharmacia, Uppsala, Sweden) in periods of 2 min per fraction.

2.1.2. Plant material Thalli 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 111.120 , altitude 1050 m) in August 2011. The lichen material was unambiguously identified according to the classification key of Wirth [19] by means of microscopic and micro-chemical analyses. A voucher specimen (JR-20110811-A26) was deposited at the Institute of Pharmacy/Pharmacognosy, University of Innsbruck, Austria.

2.4.2. pH-zone refining CPC A 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 as retainer to the aqueous stationary phase, while TFA (8 mM, pH 2) was added as displacer to the organic mobile phase. The CPC column was filled with the alkalized stationary phase at 500 rpm. After accelerating the rotation to 1000 rpm and equilibrating with the non-acidified upper phase, 400 mg of the acetone extract was dissolved in a 20 mL mixture of alkalized aqueous phase and nonacidified organic phase (1:1, v/v), adjusted to pH 9, and injected through a 20 mL sample loop. The acidified mobile phase was pumped at 2 mL min1 in the ascending mode for 240 min until the pH of the eluent decreased to 1, and the displacement was finished. Experimental conditions for the separation procedure are summarized in Table 1.

2.2. Extract preparation

2.5. Characterization of CPC fractions

123 g air-dried thalli of P. furfuracea (var. ceratea) were grinded with a Micro-Dismembrator U-ball mill (Sartorius AG, Göttingen, Germany) and extracted at room temperature with acetone using an ultrasonic bath (1 1230 mL, 5  615 mL, 1 h each). After centrifugation of the suspension, the supernatant was evaporated to dryness and yielded 12.6 g of crude extract. 2.3. Stability test

2.5.1. TLC monitoring The separation process was assessed by TLC. Each collected fraction was spotted on Merck TLC plates coated with silica gel 60 F254 and developed with n-hexane/Et2O/FA (5:3:1; v/v/v). After detection at UV254 and UV366, the plates were sprayed with vanillin–sulfuric acid and heated to 100  C for 5 min. Fractions of similar composition were combined resulting in 12 fractions (F1–F12, Fig. S1).

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

2.5.2. LC-DAD-ESI/MSn analyses Fractions F1–12 were analyzed by HPLC using a 1100 Agilent system (Agilent, Waldbronn, Germany) equipped with a photodiode array detector set at 235 nm. The column (Phenomenex1 Synergi Polar-RP 80A, 4.6  150 mm; 4 mm particle size) was maintained at 35  C. The mobile phases consisted of 0.1% FA in

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

pH-zone refining CPC

Biphasic solvent system Stationary phase (SP) Mobile phase (MP) Applied sample Flow rate Rotation speed Back pressure Stationary phase retention Collection mode Total solvent consumption Recovery rate

MtBE/MeOH/water 10:1:10 (v/v/v; ascending mode) Lower aqueous phase + NaOH (10 mM) Upper organic phase + TFA (8 mM) 400 mg in 10 mL SP + 10 mL non-acidified MP 2 mL min1 1000 rpm 43 bar 65% 4 mL per fraction 480 mL 60%

water (solvent A) and MeOH mixed with 1.5% THF (solvent B). The separation was performed at a flow rate of 1 mL min1 by using the following gradient: 60% solvent B increased to 62% in 5 min, then to 63% in 10 min, maintained for 10 min and increased to 70 % in 3 min, to 72% in 6 min, to 73% in 3 min and finally to 98% in 2 min and maintained for 10 min. The HPLC system was coupled to a Bruker Esquire 3000plus iontrap mass spectrometer (Bruker Daltonics, Bremen, Germany) equipped with an electrospray (ESI) interface and fitted to the following parameters: LC flow split–1:5; spray voltage–4.5 kV, 365  C; dry gas–N2, 9 L min1; nebulizer–He, 40 psi. The precursors and product (MS2, MS3, MS4) ions were detected in the scanning range of m/z 100–1500, both in the positive and negative ionization mode. 2.6.

13

C NMR analyses and data processing

Fractions F1–F12 were dried under vacuum at room temperature and 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 AVIII600 spectrometer (Karlsruhe, Germany) equipped with a cryoprobe optimized for 1H detection and with cooled 1H, 13C and 2D coils and preamplifiers. 13C NMR spectra were acquired at 150.91 MHz. A standard zgpg pulse sequence was used with an acquisition time of 0.909 s and a relaxation delay of 3 s. For each sample, 256 scans were co-added to obtain a satisfactory signal-to-noise ratio. The spectral width was 238.9070 ppm, and the receiver gain was set to the highest possible value. A 1 Hz line broadening filter was applied to each FID prior to Fourier transformation. The spectra were manually phased and baseline corrected using the TOPSPIN 3.2 software (Bruker) and calibrated on the central resonance (d 39.80 ppm) of DMSO-d6. The 13C NMR spectra are provided as supplementary data. A minimum intensity threshold of 0.3% (relative to the most intense signal of each spectrum) was then used to automatically collect all positive 13C NMR signals while avoiding potential noise artifacts. Each peak list was then converted into a text file. Absolute intensities of the collected peaks in the fraction series were aligned by using an in-house algorithm written in the python language. The principle 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 to associate the absolute intensity of each 13C peak to the corresponding bin. The bins for which no signal was detected in any fraction were removed from the bin list. The resulting table was imported into the PermutMatrix version 1.9.3 software (LIRMM, Montpellier, France) for clustering analysis on raw peak intensity values. The classification was performed on the rows only, i.e., on the chemical shift bins. The Euclidean distance was used to measure the proximity between the samples, and the Ward's method was performed to agglomerate the data. The resulting 13C chemical shift clusters were visualized as dendrograms on a two-dimensional map. The higher the intensity of 13C NMR peaks, the brighter the color on the map.

2.7. 13C NMR chemical shift database A literature survey was performed to obtain names and structures for a maximum of metabolites already described in P. furfuracea. In total, 27 P. furfuraceae metabolites, including depsides, depsidones, benzofurans, sugars, amino acids, and fatty acids, were added to the 13C chemical shift database already comprising the chemical shifts of 450 structures of natural products (among them 64 depsides and depsidones from different lichen species). Each metabolite data record was then stored in a 13 C chemical shift database by means of the ACD/NMR Workbook Suite 2012 software (ACD/Labs, Ontario, Canada). The structures were drawn with ChemSketch, and chemical shifts were assigned to the corresponding carbon positions. When 13C chemical shifts were not available in the literature, a predicted spectrum was calculated with the ACD/Labs C NMR Predictor software, and the resulting 13C chemical shifts were supplied to the database. For metabolite identification, each 13C chemical shift cluster obtained from HCA was submitted to the structure search engine of the database management software. A 13C NMR chemical shift tolerance of 2 ppm was used. Additional 2D NMR experiments (HSQC, HMBC, and COSY) of the combined fractions F1–F12 were performed on the same Bruker Avance AVIII-600 spectrometer, by using standard Bruker pulse programs (Bruker, Karlsruhe, Germany) in order to confirm the structures of the identified compounds. Structural data is listed in Table S2 in the supplementary file. 3. Results and discussion The multi-component mixture obtained by extraction of dried thalli of P. furfuracea var. ceratea with acetone was selected as model extract to rapidly characterize the contained depsides and depsidones by applying a recently developed dereplication strategy. This lichen species is easily accessible in subalpine zones of Europe and was described to contain olivetoric acid as main constituent, a diversity of other depsides and eventually depsidones [12,20]. The combination of solid free liquid–liquid chromatography with 13C NMR and HCA-based pattern recognition represents a promising alternative tool for the identification of major compounds, and especially fragile compounds, present in crude extracts. 3.1. Production of simplified mixtures by CPC A pH-zone refining CPC method was developed to separate depsides on the basis of their acidic character due to carboxylic and phenolic moieties. The pH-zone refining mode is indeed dedicated to the separation of compounds whose electric charge depends on the pH value [21–23] and has been widely used in CPC for the separation of alkaloids [15–17], amino acids, peptides [21–23],

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(6) with m/z 248 and a co-eluting minor constituent (1) with m/z 196 were detected. One compound (2) with m/z 374 eluted constantly starting from fraction F3 after 76 min, another one (3) with m/z 408 starting from fraction F4 after 90 min until the end of the process. Between 90 and 180 min, a major compound (5) with m/z 472 was recovered in fractions F5–F8. Another metabolite (4) with m/z 224 was recovered in fractions F8–F11 (180–210 min). A substance (7) detected with m/z 470 in fractions F7 and F8 was collected between 160 and 180 min. In fraction F11 (210–220 min) a substance (8) with m/z 266 was detected. TLC and HPLC analyses clearly showed that eight compounds were enriched within the fraction series (Figs. S1 and S2). The elution profile of these eight characteristic compounds is depicted as a HPLC fractogram in Fig. 3. The content of identified compounds within the fraction series (Table S1) is provided as supplementary data.

dyes [24–27], and to a lesser extend polyphenols [28–31]. In order to ensure the stability of the depsides and depsidones under pH variations, the TLC and HPLC profiles of the crude extract were preliminarily investigated within a pH range of 1–14. In acidic conditions, the substances were stable without any degradation between pH 1 and pH 7. During gradual alkalization of the test solution, the composition of the extract remained stable up to pH 10. At values higher than pH 11, additional signals resulting from degradation products, which had not been present in the original profile, became apparent by TLC and HPLC analysis. The pH-zone refining CPC fractionation of the crude extract was performed by using a biphasic solvent system primarily composing of MtBE and water. Since the acetone crude extract of P. furfuracea contained a diversity of compounds within a large polarity range (fatty acids, polyphenols, sugars, mucilage), MeOH was added as third solvent to reduce the polarity difference between stationary and mobile phase and ensure the solubility of all substances. Based on the preliminary pH stability test, the sample was adjusted to pH 9 before injection to enable the protonation of the contained depsides and depsidones. Thus, NaOH was added to the aqueous stationary phase as retainer in a concentration of 10 mM and TFA was added to the organic mobile phase as displacer in a concentration of 8 mM (Table 1). Fig. 3 shows the HPLC fractogram of the pH-zone refining CPC run, obtained after the injection of 400 mg of the P. furfuracea crude extract dissolved in 20 mL 1:1mixture of alkalized stationary phase and non-acidified mobile phase. Under the optimized conditions of 2 mL min1 flow rate and 1000 rpm, the back pressure was maintained at 43 bar after the release of the mobile phase front (t = 35 min). The initial stationary phase retention was 65%. Gradual neutralization of the basic stationary phase released the protonated compounds from the aqueous to the organic phase with decreasing pKD and pKa. Retention of the stationary phase was of 61% at the end of the process. The pH value remained permanently at pH 6 during the displacement for 170 min. Then, the pH decreased gradually to pH 5. After 240 min in total the pH value quickly dipped to pH 1 and the 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 remaining sample comprising of mainly very polar sugars was fully retrieved. This part was not taken into account for the rest of the study. The fractions yielded between 5.2 mg (F1) and 68.5 mg (F6) (Fig. 3).

3.3.

13

C NMR analyses and hierarchical clustering analysis

NMR is a frequently used profiling tool for the qualitative and quantitative analysis of natural products in complex mixtures. Due to the ubiquitous occurrence of hydrogen atoms in organic compounds, many strategies are currently developed based on 1 H NMR analysis hyphenated to chromatographic techniques. However, in most cases 1H spectra of complex mixtures result in overlapping signals. As an alternative, an original pattern recognition strategy based on 13C NMR has been recently developed for natural metabolite identification [18]. The greatest advantage of using 13C NMR is the single 13C signal correspondence with one specific 13C position of the molecule leading to spectra of higher simplicity. Applying this 13C NMR pattern recognition approach, the fraction series obtained from CPC was analyzed by 13C NMR in order to directly determine the chemical composition of the simplified mixtures. The TLC and HPLC analysis revealed F1 as negligible fraction (devoid of depsides and depsidones), hence it was not included in this study. All other CPC-generated fractions comprised in total eight predominant compounds and were investigated by 13C NMR analysis, which was performed within 18 min (256 scans) for each sample. The 13C signals detected in each fraction were collected by automatic peak picking and aligned into regular bins of Dd = 0.2 ppm [18]. As a result, a two-dimensional table was obtained with 11 columns corresponding to the 11 CPC fractions and 132 rows corresponding to the collected signals. The table was subjected to HCA in order to reveal 13C NMR chemical shift correlations within the rows. Five well-defined clusters were highlighted (Fig. 4). These clusters were assigned to molecular structures with the help of a 13C NMR database comprising metabolites of P. furfuracea already reported in the literature.

3.2. Characterization of CPC fractions For the evaluation of the separation, obtained CPC fractions were 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

AUC

m/z:

100000000 80000000 60000000 40000000 20000000

Cpd 1

196

Cpd 2

374

Cpd 3

408

Cpd 4

224

Cpd 5

472

Cpd 6

248

Cpd 7

470

Cpd 8

266

0 Yields [mg]:

F1 5.2

F2 13.0

F3 18.6

F4 21.8

F5 45.4

F6 68.5

F7 7.8

F8 18.9

F9 15.1

F10 7.7

F11 5.8

F12 6.8

Fraction

Fig. 3. Fractogram of the eight most characteristic compounds from the CPC fractionation of the P. furfuracea crude extract.

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Fig. 4.

13

65

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

3.4. Identification of lichen metabolites After entering the 13C chemical shifts of the main cluster B located in fractions F3–F12 and comprised of 15 signals into the database, one single structure was proposed, the structure of the b-orcinol para-depside atranorin (2) with 15 of 19 signals matching. For the well-defined cluster C ranging from fraction F8 to F10 the database search assigned 12 of 12 correctly matching

13 C signals to the structure of the monomer olivetolcarboxylic acid (4). These results correspond to the LC–MS profiles of compound 2 and 4 with m/z 374 and m/z 224, respectively. Cluster E detected in fractions F2–F6 was comprised of 11 signals, which were assigned to olivetonide (6) by the database. As clusters were classified hierarchically according to the abundance of metabolites, clusters of minor constituents were prone to be split into two or more sub-clusters of 13C signals.

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Accordingly, cluster D consisted of 19 13C signals located in fractions F5–F8. Entering the shift values into the database, the structures of microphyllinic acid, 4-O-demethylmicrophyllinic acid and olivetoric acid were proposed with 16 of 19 signals matching. By comparison of their structural characteristics, it became evident that microphyllinic acid and 4-O-demethylmicrophyllinic acid feature a second carbonyl group at 207 ppm, which is missing in the structure of olivetoric acid. The absence of this significant signal in the raw NMR data indicated olivetoric acid as the right structure for cluster D. Furthermore, a sub-cluster of three signals was detected in the same range of fractions and comparable in intensity as cluster D. In order to verify if this sub-cluster belongs to cluster D, the HCA was repeated removing the major cluster B, C and E first. As a result cluster D and sub-cluster D0 showed up as one unified cluster and the database search unequivocally proposed the orcinol para-depside olivetoric acid (5) as corresponding structure with a correct signal matching of 22 of 26. Considering that olivetoric acid is characterized by a molecular weight of 472.53 g mol1, this finding is in accordance with the LC– MS analysis, which revealed compound 5 as major constituent in F5–F8 with m/z 472. Similarly, cluster A localized between fraction F2 and F4 was divided into two blocks of 9 signals in total. After entering 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 mol1, was proposed. This mass corresponds to the LC–MS profile of the minor constituent 1. No clusters were detected for the two minor compounds 7 and 8, which were observed by LC–MS in fractions F7–F8 and F11, respectively. By applying of the 13C NMR dereplication strategy, five out of the eight compounds fractionated by CPC and detected by TLC and HPLC analyses were successfully identified. Only a few errors occurred in classification due to failures in alignment or binning. If alignment fails, slight chemical shift variations of a single compound across adjacent fractions can for instance result in peak splitting into two consecutive bins and thus to an accessory data point in the 2D matrix. Binning failures can also result from two very close 13C signals merged into one single bin leading to loss of data. Although the bin width has previously been optimized with 0.2 ppm, we observed loss of data points due to very close 13C signals belonging to different carbon skeletons, which join in the same bin. This might be one of the reasons for the failed identification to trace the clusters of the two minor compounds 7 and 8 from the analyzed fractions. Strikingly, the compounds unambiguously identified by the present 13C NMR dereplication method were distributed over three or more successive fractions. By contrast compounds 7 and 8 were detected merely in one or two fractions by LC–MS, and were therefore hardly recognized as clusters. In addition, due to the low concentrations, they were possibly obscured by clusters of more concentrated metabolites. Although the stability of depsides contained in the lichen crude extract was approved between pH 1 and 10, the main compound of P. furfuracea, olivetoric acid (5), might have been partly degraded via ester cleavage to its monomers olivetolcarboxylic acid (4) and olivetonic acid (8, Fig. 5). This hypothesis is in accordance with the LC-ESI/MSn analysis, since both the molecular ion peak of olivetolcarboxylic acid (4) with m/z 225 [M + H]+ in the positive ionization mode (Table S4), and the molecular ion peak of olivetonic acid (8) with m/z 265 [M  H] in the negative ionization mode (Table S3) were detected. Furthermore, the presence of olivetolcarboxylic acid (4) was confirmed by detection of cluster C, while that of olivetonic acid (8) remained undetected in HCA. It can be assumed, that latter was promptly esterified after enolisation of the carbonyl group to form its corresponding lactone (6) and was thus found just in low concentration. Not even a mild procedure like

Olivetoric acid (5) m/z 472

Olivetolcarboxylic acid (4) m/z 224

Olivetonic acid (8) m/z 266

Olivetonide (6) m/z 248 Fig. 5. Degradation of olivetoric acid (5) and arising products.

pH-zone refining CPC, where the pH value remains permanently neutral during the replacement process and no solid support is involved to preserve the fragile lichen compounds completely against degradation. Taking this into account, it is doubtful that an alternative 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 the identified compounds by classical structure elucidation and to validate the performance of this recent 13C NMR chemical shift database. The identities of all five clustered metabolites were successfully validated by LC-DAD-MS and 2D NMR analyses (Table S2). A sixth structure, namely 5-chloroatranorin, was identified by these additional analyses in fractions F3–F12, which corresponds to compound 3 with m/z 408. This implies that compound 2 and 3 are close structural analogues distinguishable only by precise details in the 13C NMR profiles, e.g., dedicate distinction in the chemical shifts of C-5, C-6 and C-9 (Table S2), and thus, cluster B represents not only the structure of compound 2 but also parts of compound 3. By lowering the matching rate of this cluster, the database proposed apart from atranorin (2) its analogue 5-chloroatranorin (3) and confirmed our findings. 4. Conclusion The results of this study emphasize the effectiveness of rapid characterization of pre-fractionated plant extracts by 13C NMR chemical shift pattern recognition. Although depsides and depsidones and their corresponding monomers are often structurally very close, we demonstrated in this study that even natural products of similar structures can be successfully identified by the applied workflow. Accordingly, olivetoric acid (5) and its monoaromatic counterpart olivetolcarboxylic acid (4) which shared three identical 13C NMR signals could be clearly distinguished due to their distribution in different fractions. Even dimeric and monomeric structures of identical carbon skeleton could unambiguously be identified by 13C pattern recognition. In comparison to alternative CPC methods or even solid phase based chromatographic methods, the performed pH-zone refining CPC fractionation was revealed as a gentle, efficient and fast separation technique to be hyphenated to a subsequent 13C NMR pattern recognition procedure. By using these complementary techniques we could successfully identify six out of eight prominent constituents of the Alpine lichen P. furfuracea var.

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ceratea directly from the acetone crude extract without timeconsuming isolation procedures. Conflict of interest The authors declare no conflict of interest. Acknowledgements This research was supported by NatProtec, a Marie Curie Industry-Academia Partnerships and Pathways (IAPP) Fellowship within the 7th European Community Framework Programme (286287) and by the Austrian Science Fund (FWF) Project ‘Drugs from Nature Targeting Inflammation’ (NFN-S10703). Financial supports from the CNRS, Conseil R|%1e[ Accept ]egional de Champagne Ardenne, Conseil General de la Marne, Ministry of Higher Education and Research (MESR) and from the EUprogramme FEDER to the PlAneT CPER project are also gratefully acknowledged. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.aca.2014.07.009. References [1] M.E. Conti, G. Cecchetti, Biological monitoring: lichens as bioindicators of air pollution assessment–a review, Environ. Pollut. 114 (2001) 471–492. [2] S. Sorbo, G. Aprile, S. Strumia, R.C. Cobianchi, A. Leone, A. Basile, Trace element accumulation in Pseudevernia furfuracea (L.) Zopf exposed in Italy's so called Triangle of Death, Sci. Total Environ. 407 (2008) 647–654. [3] S. Huneck, The significance of lichens and their metabolites, Naturwissenschaften 86 (1999) 559–570. [4] S. Huneck, I. Yoshimura, Identification of Liches Substances, Springer-Verlag, Berlin, Heidelberg, 1996. [5] E. Stocker-Wörgötter, Metabolic diversity of lichen-forming ascomycetous fungi: culturing, polyketide and shikimate metabolite production, and PKS genes, Nat. Prod. Rep. 25 (2008) 188–200. [6] S.K. Oettl, J. Gerstmeier, S.Y. Khan, K. Wiechmann, J. Bauer, A.G. Atanasov, C. Malainer, E.M. Awad, P. Uhrin, E.H. Heiss, B. Waltenberger, D. Remias, J.M. Breuss, J. Boustie, V.M. Dirsch, H. Stuppner, O. Werz, J.M. Rollinger, Imbricaric acid and perlatolic acid: multi-targeting anti-inflammatory depsides from cetrelia monachorum, Plos One 8 (2013) e76929. [7] F. Bucar, I. Schneider, H. Ogmundsdottir, K. Ingolfsdottir, Anti-proliferative lichen compounds with inhibitory activity on 12(S)-HETE production in human platelets, Phytomedicine 11 (2004) 602–606. [8] M. Kosanic, N. Manojlovic, S. Jankovic, T. Stanojkovic, B. Rankovic, Evernia prunastri and Pseudoevernia furfuraceae lichens and their major metabolites as antioxidant, antimicrobial and anticancer agents, Food Chem. Toxicol. 53 (2013) 112–118. [9] D. Joulain, R. Tabacchi, Lichen extracts as raw materials in perfumery. Part 2: treemoss, Flavour Frag. J. 24 (2009) 105–116.

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