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Phytochemical, phylogenetic, and anti-inflammatory evaluationof 43 Urtica accessions (stinging nettle) based on UPLC–Q-TOF-MSmetabolomic profiles

Mohamed A. Farag a,b, Maximilian Weigend c,⇑,1,2, Federico Luebert c, Grischa Brokamp c,Ludger A. Wessjohann b,⇑,3

a Pharmacognosy Department, College of Pharmacy, Cairo University, Kasr el Aini st., P.B. 11562, Cairo, Egyptb Leibniz Institute of Plant Biochemistry, Dept. Bioorganic Chemistry, Weinberg 3, D-06120 Halle (Saale), Germanyc Institut für Biologie – Systematische Botanik und Pflanzengeographie, Freie Universität Berlin, D-10195 Berlin, Germany

a r t i c l e i n f o

Article history:Received 23 January 2013Received in revised form 11 September 2013Available online 26 October 2013

Keywords:Urtica dioica L.UrticaceaeMetabolic profilingUPLC–MSAnti-inflammatoryPhylogeny

a b s t r a c t

Several species of the genus Urtica (especially Urtica dioica, Urticaceae), are used medicinally to treat avariety of ailments. To better understand the chemical diversity of the genus and to compare differentaccessions and different taxa of Urtica, 63 leaf samples representing a broad geographical, taxonomicaland morphological diversity were evaluated under controlled conditions. A molecular phylogeny for alltaxa investigated was prepared to compare phytochemical similarity with phylogenetic relatedness.Metabolites were analyzed via UPLC–PDA–MS and multivariate data analyses. In total, 43 metaboliteswere identified, with phenolic compounds and hydroxy fatty acids as the dominant substance groups.Principal component analysis (PCA) and hierarchical clustering analysis (HCA) provides a first structuredchemotaxonomy of the genus. The molecular data present a highly resolved phylogeny with well-supported clades and subclades. U. dioica is retrieved as both para- and polyphyletic. European membersof the U. dioica group and the North American subspecies share a rather similar metabolite profile andwere largely retrieved as one, nearly exclusive cluster by metabolite data. This latter cluster also includes– remotely related – Urtica urens, which is pharmaceutically used in the same way as U. dioica. However,most highly supported phylogenetic clades were not retrieved in the metabolite cluster analyses. Overall,metabolite profiles indicate considerable phytochemical diversity in the genus, which largely falls into agroup characterized by high contents of hydroxy fatty acids (e.g., most Andean-American taxa) andanother group characterized by high contents of phenolic acids (especially the U. dioica-clade). Anti-inflammatory in vitro COX1 enzyme inhibition assays suggest that bioactivity may be predicted by grossmetabolic profiling in Urtica.

� 2013 Published by Elsevier Ltd.

1. Introduction

Metabolic fingerprints, profiles and metabolomic studies helpus to gain a broader insight into the biochemical composition ofliving organisms in a certain context. With the recent develop-ments in plant metabolomics techniques (Farag et al., 2012a,2012b; Hall and Hardy, 2012; Sumner et al., 2003), it is now possi-

ble to detect hundreds of metabolites simultaneously and to com-pare samples reliably for differences and similarities in a semi-automated and, essentially, untargeted manner. One particularlyaccepted platform for untargeted metabolite profiling in plantextracts is LC–MS using electrospray ionization (LC–ESI-MS).Compared with conventional LC separation, ultra performanceliquid chromatography (UPLC) can achieve more rapid metaboliteanalyses and provides better peak separation. UPLC–Q-TOF-MS asa relatively new technology is able to provide large amounts ofmetabolite data and can also help to detect chemical compoundswith high sensitivity (Grata et al., 2008; Wolfender et al., 2008).The technology has been used to look at metabolite profiles in clo-sely allied taxa, different cultivars of individual taxa, or plants atdifferent stages of development (Farag et al., 2013; Cao et al.,2011; Farag and Wessjohann, 2012; Hanhineva et al., 2009; Liuet al., 2005; Okada et al., 2009). To date no large screenings of

0031-9422/$ - see front matter � 2013 Published by Elsevier Ltd.http://dx.doi.org/10.1016/j.phytochem.2013.09.016

⇑ Corresponding authors. Tel.: +49 (0) 228 73 2526; fax: +49 (0) 228 73 3120 (M.Weigend). Tel.: +49 (0) 345 5582 1301; fax: +49 (0) 345 5582 1309 (L.A.Wessjohann).

E-mail addresses: [email protected] (M. Weigend), [email protected] (L.A. Wessjohann).

1 Current address: Nees-Institut für Biodiversität der Pflanzen, Rheinische Fried-rich-Wilhelms Universtität Bonn, Meckenheimer Allee 170, 53115 Bonn, Germany.

2 Contact for phylogeny.3 Contact for metabolomics.

Phytochemistry 96 (2013) 170–183

Contents lists available at ScienceDirect

Phytochemistry

journal homepage: www.elsevier .com/locate /phytochem


metabolite profiles across plant genera have been published basedon this new technique. The present study investigates the metab-olite profiles of a range of taxa from the genus Urtica, a plant groupwidely used in pharmaceutical preparations.

Urtica dioica is the only species of Urtica to be cultivated com-mercially for pharmaceutical purposes (El Haouari et al., 2006;Exarchou et al., 2006; Nahata and Dixit, 2012), and the commercialextraction of chlorophyll and stem fibers (Dreyer et al., 1996). Awide range of metabolites has been described from U. dioica,including flavonoids and phenylpropanoids (Fig. 1) (Bucar et al.,2006; Chaurasia and Wichtl, 1987; Pinelli et al., 2008; Roscheket al., 2009). Caffeic acid analogues have also been isolated fromU. dioica and Urtica urens (Budzianowski, 1991). Apart from thesearomatic compounds, pentacyclic triterpenoids and oxygenatedfatty acids have been found in U. dioica roots (Gansser and Spitell-er, 1995; Guil-Guerrero et al., 2003). A number of papers have beenpublished reporting on the lignan content of Urtica laetevirens(Zhou et al., 2009), such as neoolivil, secoisolariciresinol, isolaric-iresinol and pinoresinol (Schottner et al., 1997b), or terpene diolsfrom U. dioica roots (Kraus and Spiteller, 1990). The well reporteduse of nettle extract for rheumatism, eczema, allergic rhinitis andarthritis (Chrubasik et al., 1997; Hirano et al., 1994; Legssyeret al., 2002; Roschek et al., 2009; Takahashi et al., 2008) was foundto be mediated through the inhibition of cyclooxygenases (COX-1,COX-2), and hematopoietic Prostaglandin D2 synthase (HPGDS),central enzymes in pro-inflammatory pathways (Roschek et al.,2009). Both the leaf and the nettle root are used pharmaceutically,with the use for the treatment of benign prostatic hyperplasia lim-ited to the root (Hudec et al., 2007). Anti-prostatic effects are be-lieved to be mediated by many constituents including lignans,

acting via different mechanisms including the inhibition of aroma-tase enzyme (Schottner et al., 1997a).

Most phytochemical studies performed on Urtica focused on U.dioica. However, taxonomists recognize a wide range of infraspe-cific taxa in U. dioica, albeit most studies have been carried outwith plant material not identified to subspecies or variety andlikely represent mostly the ‘‘typical’’ form of the species (U. dioicasubsp. dioica var. dioica). As a consequence, phytochemistry of boththe genus Urtica in general and U. dioica in wider sense is still veryincompletely understood. Urtica is a genus of ca. 50 species (Friis1993) in the family Urticaceae. The genus Urtica as such is verycharacteristic and easily recognized, but species delimitation ishighly problematic, especially for U. dioica L. with more than 20infraspecific taxa currently recognized from Eurasia (Geltman1982; Edmondson 1992; Weigend, 2006) and the Americas(Boufford, 1997; Zuloaga and Morrone, 2008). Recent contributionshave been able to clarify some problems at lower taxonomic levels(Weigend, 2006; Weigend and Luebert 2009). No explicit hypoth-eses have so far been formulated for the relationships of taxa ofthe genus across its range.

This study represents the first attempt to explore variation insecondary metabolites within Urtica based on samples of 63 geno-types belonging to 43 distinct taxa (32 species, 12 subspecies andvarieties of U. dioica) with an aim to: (a) characterize the metabo-lome for a range of taxa and samples of Urtica, (b) investigate thephylogenetic relationships of the taxa, and (c) compare the phylo-genetic and phytochemical relationships in order to provide thebasis for chemotaxonomic and pharmacological studies. This willalso allow the characterization of the pharmaceutical potential ofa range of taxa in the genus and can help clarify to how far the

Quinic acid(QA): R3, R4, R5=H

Acyl=p-Coumaroyl: R1=R2=HCaffeoyl: R1=OH; R2=HFeruloyl: R1=OMe; R2=H

Flavonols and their glycosidesKaempferol: R=R1=R2=H Quercetin: R=R1=H; R2=OH Isorhamnetin: R=R1=H; R2=OCH3

9-Hydroxy-10,12-octadecadienoic acidCH3

O

OH

OH

A

B C

O

ORO

OHR2

R1O

OH

HOOC

OH OR3

OR5

OR4

13

54

QA

O

R2

OH

R1

Fig. 1. Major classes of natural products; phenolic acids (A), flavonoids (B) and fatty acids (C) detected in Urtica with selected compound(s) discussed in text.

M.A. Farag et al. / Phytochemistry 96 (2013) 170–183 171


indiscriminate medicinal use of different subspecies and varietiesof U. dioica and U. urens is justified (i.e., in how far they do showhigh and exclusive phytochemical similarities).

2. Results and discussion

2.1. Extraction development

Several solvents were initially tested including acetone, ethanol,100%, 70%, and 50% methanol/water. Solvent selection for samplepreparation was evaluated with respect to reproducibility, qualityand recovery of the Urtica major secondary metabolites (phenolicacids and flavonoids) as revealed by UPLC–MS (data not shown).Results show that within the solvents tested, 70% (v/v) methanolin HPLC-grade water was the best mixture for the extraction ofthe target analytes from Urtica samples. The choice of extractionsolvent was in agreement with one previously described procedure(Bucar et al., 2006). The 70% methanol extracts from U. dioicaleaves provide approximately 10- and 20-fold higher values forflavonoids and phenolic acids compared to 100% acetone and eth-anol, respectively. This was confirmed by 1H NMR (data notshown). For the identification and relative quantification ofphenolics, an UPLC method was adapted and optimized. AlthoughLC–MS methods have been used to analyze phenolics in Urtica(Bucar et al., 2006; Pinelli et al., 2008; Zhou et al., 2009),UPLC–Q-TOF-MS was selected because of the large sample size(63 Urtica accessions) considering its short run time in addition

to its improved peak separation. In fact, all peaks were quicklyseparated within 10 min at a flow rate of 0.15 ml min�1.

2.2. Characterization of metabolites in Urtica leaves by UV–Vis andmass spectra

Simultaneously acquired UPLC–PDA and full scan MS chromato-grams of U. flabellata are presented in Fig. 2. The chromatogram ob-tained by MS detection in negative ionization mode was quitesimilar to the PDA chromatogram for the first half (150–300 s),with the exception that the peaks for phenolics had a much higherresponse in MS than in UV. In the later elution region (300–600 s),several major peaks were visible in the MS but not in the UV trace,indicative of the absence of strong chromophores, which wereidentified as oxygenated fatty acids. Some hydroxy fatty acids werepreviously identified in U. dioica roots, albeit not in leaves.

The identities, retention times, UV characteristics, and observedmolecular and fragment ions for individual components are pre-sented in Table 2. A total of 43 metabolites were detected, and34 were tentatively identified. Identified metabolites belong tovarious substance classes including caffeic acid derivatives,flavonoid glycosides, terpene glycosides, lignans and fatty acidderivatives, with the latter ones being abundant in most Urtica spe-cies. Metabolite assignments were made by comparing retentiontimes, UV/Vis spectra and MS data (accurate mass, isotopic distri-bution and fragmentation pattern) of the compounds detectedwith Urtica compounds reported in the literature as discussed

rt (sec)

150 200 250 300 350 400 450 500 550 Time [s]0.0

0.2

0.4

0.6

0.8

6x10Intens.

FAM071_U55_1-D,2_01_5133.d: UV Chromatogram, 200-500 nm

150 200 250 300 350 400 450 500 550 Time [s]0.0

0.2

0.4

0.6

0.8

6x10Intens.

FAM071_U55_1-D,2_01_5133.d: BPC 100.0000-800.0000 -All MS

UV

MS

Hydroxy cinnamic acids & flavonoids

Fatty acids

3 2

6+8

9

9 2

11

11

15

15

21

28

26 23

28

26

23

21 43

42

41 40

39

33 34

35

29

30

Fig. 2. Representative UPLC–UV–MS trace of U. flabellata leaf characterized by 2 main regions: a region (150–300 s) with peaks principally due to phenolic acids and flavonoidglycosides, and a region (300–600 s) assigned for mono-, di-, and tri-hydroxy fatty acids. Ranges of retention time and m/z values are 150–600 s and 100–800 amu,respectively. Peak numbers follow those listed in Table 2.

172 M.A. Farag et al. / Phytochemistry 96 (2013) 170–183


below and summarized in Table 2. The basic structures of metabo-lites commonly found in Urtica species and discussed throughoutthe manuscript are shown in Fig. 1.

2.2.1. FlavonolsFlavonoids in Urtica generally occur as sugar conjugates, princi-

pally as O-glycosides (Chaurasia and Wichtl, 1987). In MS analyses,the nature of the sugars could be revealed by elimination of the su-

gar residue, that is, 162 amu (hexose; glucose or galactose) and 146amu (rhamnose). All glycosides identified on the basis of their UV/Vis spectra were flavonol derivatives of quercetin, kaempferol, andisorhamnetin (Fig. 1B) (Chaurasia and Wichtl, 1987).

2.2.2. Hydroxycinnamic acid derivativesConjugates formed from the reaction of hydroxycinnamic acids

with quinic acid, malic acid, glucose, and benzoic acids were

Table 1List of voucher information and sample number of the investigated Urtica samples.

Accession Taxon Country of origin Herbarium voucher Clade

U1 Urtica dioica L. subsp. dioica var. hispida Wedd. Switzerland M. & K. Weigend 8108 I-AU2 Urtica ‘‘incaica’’ spec. nov. ined. Peru Ch. Schwarzer 14-C II-AU3 Urtica ‘‘deltoidea’’ spec. nov. ined. New Zealand M. Weigend 8212 II-BU4 Urtica dioica L. subsp. subinermis (Uechtr.) Weigend Germany M. Weigend 8208-C I-AU5 Urtica magellanica Poir. Argentina M. Weigend et al. 6809-C III-AU6 Urtica longispica Killip Ecuador M. Weigend & G. Brokamp 9106-C III-AU7 Urtica dioica L. subsp. pubescens (Ledeb.) Domin Italy M. Weigend 7099 I-AU8 Urtica dioica L. subsp. holosericea (Nutt.) Thorne USA (California) L. Ahartt 13172-C II-AU9 Urtica longispica Killip Ecuador M. Weigend & G. Brokamp 9113-C III-AU10 Urtica dioica L. subsp. dioica var. angustifolia Wimm. & Grabowsky Czech Republic M. & K. Weigend 5606-C I-AU11 Urtica dioica L. subsp. subinermis (Uechtr.) Weigend Austria M. & K. Weigend 5665-C I-AU12 Urtica pilulifera L. Cyprus M. & K. Weigend 9007-C VU13 Laportea spec. Kamerun Th. Franke & L. Beenken s.n. 26.10.2002 OGU14 Urtica dioica L. subsp. dioica var. hispida Wedd. Switzerland M. & K. Weigend 8179 I-AU15 Urtica cannabina L. Kazakhstan M. Weigend 8695 IV-CU16 Urtica dioica L. subsp. dioica var. dioica Mexico Ch. Schneider et al. 52a I-AU17 Urtica dioica L. subsp. subinermis (Uechtr.) Weigend Germany M. Weigend 8209-C I-AU18 Urtica mairei Levl. Tibet H. Rushforth & H. McAllister 5247 III-BU19 Urtica laetevirens Maxim. Tibet H. Rushforth & H. McAllister 5327 III-BU20 Urtica echinata Benth. cf. trichantha (Wedd.) Acevedo & Navas Peru M. Weigend et al. 8478 III-AU21 Urtica taiwaniana S. S. Ying Taiwan J. N. Chen et al. 00573-C II-AU22 Urtica echinata Benth. Peru M. Weigend et al. 9227-C III-AU23 Urtica andicola Wedd. Peru M. Ackermann & D. Kollehn 276 III-AU24 Urtica dioica L. subsp. holosericea (Nutt.) Thorne USA (California) L. Ahartt 13535-C II-AU25 Urtica stachyoides Webb Spain (Teneriffa) M. & K. Weigend 8230 IV-AU26 Urtica lalibertadensis Weigend Peru M. Weigend et al. 8018-C III-AU27 Urtica atrovirens Loisel. ex Poir. Italy M. Weigend 7798 I-BU28 Urtica kioviensis Rogov. Germany N. Nürk & J. Devers 335 I-AU29 Urtica leptophylla Kunth Peru M. Weigend & M. Ackermann 9271 III-AU30 Urtica urens L. Peru M. Weigend & M. Ackermann 9289 IV-AU31 Urtica flabellata Kunth Peru M. Weigend et al. 8819 III-AU32 Urtica trichantha (Wedd.) Acevedo & L. E. Navas Peru F. Cáceres 3326 III-AU33 Urtica atrovirens Loisel. ex Poir. Italy M. Weigend 7800 I-BU34 Urtica peruviana Geltman Peru M. Weigend et al. 7625-C III-AU35 Urtica morifolia Poir. Spain M. & K. Weigend 9160 III-CU36 Urtica membranacea Poir. ex Savigny Italy N. M. Nürk 340 IV-AU37 Urtica dioica L. subsp. dioica var. elegans Chenev. Switzerland M. Weigend 8115 I-AU38 Urtica pilulifera L. Italy N. M. Nürk 345 VU39 Urtica fissa Pritz. Taiwan M. Weigend 8129 III-DU40 Urtica urentivelutina Weigend Peru M. Weigend & Ch. Schwarzer 7907 III-AU41 Urtica portosanctana Press Spain M. & K. Weigend 8234 IV-AU42 Urtica angustifolia Fisch. ex Hornem. Mongolia H. H. Hilger 1603 II-BU43 Urtica dioica L. subsp. sondenii (Simmons) Hylander Norway T. Alm s.n.-C I-AU44 Laportea peduncularis (Wedd.) Chew South Africa M. Weigend 8713 OGU45 Urtica dioica L. subsp. dioica var. dioica Germany M. Weigend 9388 I-AU46 Urtica dioica L. subsp. dioica var. dioica Germany M. Weigend 9389 I-AU47 Urtica membranacea Poir. ex Savigny Spain M. & K. Weigend 8227 IV-AU48 Urtica bianorii (Knoche) J. Paiva Spain M. & K. Weigend 8155 I-BU49 Urtica aquatica Liebm. Guatemala M. Weigend 7478 II-AU50 Urtica platyphylla Wedd. Japan N. M. Nürk 357 I-AU51 Urtica mollis Steud. Chile M. Weigend 9357 II-AU52 Urtica cannabina L. Mongolia M. Weigend 8678 IV-CU53 Hesperocnide tenella Torr. USA L. Ahartt 12535-C III-AU54 Urtica dioica L. subsp. dioica var. dioica Greece Th. Franke & P. Josifidou 06–64 I-AU55 Urtica dioica L. subsp. gracilis (Ait.) Selander Canada M. Weigend 9332 II-AU56 Urtica dioica L. subsp. dioica var. sarmatica Zapal. Germany M. Weigend 9324 I-AU57 Urtica dioica L. subsp. dioica var. sarmatica Zapal. Germany M. Weigend 9328 I-AU58 Urtica dioica L. subsp. dioica var. sarmatica Zapal. Germany M. Weigend 9327 I-AU59 Urtica dioica L. subsp. dioica var. sarmatica Zapal. Germany M. Weigend 9329 I-AU60 Urtica dioica L. subsp. dioica var. sarmatica Zapal. Germany M. Weigend 9325 I-AU61 Urtica dioica L. subsp. cypria Lindberg f. Cyprus M. Weigend et al. 8229 I-BU62 Urtica ferox Forst. New Zealand M. Weigend 8211–2 IV-BU63 Urtica diocia L. subsp. dioica var. holosericea Fries ex Saelan Germany M. & K. Weigend 8096-C I-A



previously reported for U. dioica (Bucar et al., 2006; Budzianowski,1991; Pinelli et al., 2008). Several of the hydroxycinnamoyl-quinicacid conjugates, such as caffeoyl-, feruloyl-, and p-coumaroyl-qui-nic acids were detected in this study, in addition to novel aminoacid conjugates such as caffeoyl-threonine (peak 5). The predomi-nant fragment of 191 amu for quinic acid (Fig. 1) in the MSn spec-trum and characteristic UVmax values at 298 and 325 nm arediagnostic for hydroxycinnamic acid derivatives (Clifford et al.,2006a,b); a total of 7 peaks show similar spectra. It is worth notingthat the relative amounts of cinnamate isomers attached to quinicacid at 5 position was larger than other isomers in most species.The configuration of the cinnamic acid moiety in hydroxy cinnamicacid peaks is likely to exist in both cis-(Z) and trans-(E) forms as re-vealed from one dimensional 1H NMR analysis of U. ferox extract(Supplementary Fig. S1). Peaks 30 and 32 show UV spectra identi-cal with caffeoylquinic acids and with high resolution masses of515.2502 and 487.0862, respectively (Table 2) identified as posi-tional isomers of di-O-caffeoylquinic acid (peak 30) and caffeoylferulyol tartaric acid (peak 32).

2.2.3. Lignans and terpene glycosidesLignans have been reported in U. dioica root (Schottner et al.,

1997b), but could not be detected by LC–MS (Bucar et al., 2006),probably due to the low sensitivity of LC–MS for some lignans orbecause of very low levels in leaves. Peak 10 has [M�H]� at m/z

537.1962 with MSn ions at m/z 375 (loss of 162 amu). The massspectral data and UV maxima (280 nm) are consistent with a lig-nan glycoside in U. dioica root identified as neo-olivil glycoside.Megastigmane and 2-pinene-9-ol, peaks 14 and 31, respectively,were tentatively identified as minor glycosidic compounds, presentat trace levels in most extracts.

2.2.4. Oxygenated fatty acidsThe negative ion MS spectrum of the unsaturated fatty acid

9,12,15-octadecatrienoic acid (peak 43) was easy to interpret withan exact mass of 277.2188 and a predicted molecular formula ofC18H29O�2 . Negative ionization MS also revealed several unexpectedhydroxy fatty acids as major peaks in most species. Expectedlythese acids show a much lower response in positive ionizationmode (data not shown). Peaks 41 and 42 show a mass of293.2134 and m/z 295.2298 amu, with predicted molecular formu-las of C18H29O�3 and C18H31O�3 , respectively, and a loss of a watermolecule (18 amu), suggestive of an extra hydroxy group. Peak42 was identified as 9-hydroxy-10,12-octadecadienoic acid, an aro-matase inhibitor found in U. dioica roots (Gansser and Spiteller,1995). A mass difference of 2 amu between 41 and 42 is indicativeof an extra double bond and is tentatively identified as 9-hydroxy-octadecatrienoic acid in this fatty acids series (oxylipids). This isthe first report for the presence of similar oxygenated acids in Ur-tica leaves. In this MS study, it was not possible to provide an

Table 2Metabolites identified in leaf extracts of U. dioica, U. platyphylla and U. flabellata using UPLC–UV–MS; n/i = not identifed.

Peak rt (s) UV Formula Identification [M�H]� (m/z) Error (ppm) MSn product ions

1 174 312 C15H15O10 n/i 355.0678 4.4 191(100)2 181 295 shd, 325 C16H17O9 3-O-Caffeoylquinic acid 353.0885 4.5 191(100), 133(19), 93(21)3 186 295 shd, 325 C16H17O9 5-O-Caffeoylquinic acid 353.0878 2.5 191(22), 135(100), 93(23)4 191 295 shd, 312 C15H31O16 n/i 467.1592 3.7 –5 198 295 shd, 325 C13H13O8 O-Caffeoyl-threonine 297.0622 4.8 135(54)6 199 295 shd, 325 C16H17O9 4-O-Caffeoylquinic acid 353.0875 1.7 191(19), 119(47), 97(100)7 203 275, 325 C12H15O9 n/i 303.0725 3.9 –8 205 312 C16H17O8 3-(4-Hydroxycinnamoyl) quinic acid 337.0931 3.3 191(50)9 209 325 C13H11O8 Caffeoyl malic acid 295.0472 6.0 179(24%), 134 (100), 115(34)

10 213 280 C26H33O12 Neoolivil-4-O-glucopyranoside 537.1962 0.8 375(34)11 214 325 C17H19O9 O-Feruloyl quinic acid 367.1039 3.8 191(100%), 173(13%)12 215 280, 348 C28H31O16 Quercetin dihexoside 623.1590 463(80%), 301(100%)13 217 nd C26H43O16 n/i 611.2553 1.8 431(81), 251(100)14 219 nd C19H29O8 Megastigmane hexoside 385.1858 0.6 201(100)15 222 350 C22H21O12 Isorhamnetin hexoside 477.1049 4.2 315(60)16 223 nd C17H29O10 3-Hexenyl-primeveroside 393.1765 2.7 287(100), 219(25)17 228 nd C25H39O12 Hexenyl-primeveroside 531.2427 1.0 387(58), 225(37), 207(100)18 230 nd C22H27O10 n/i 451.1584 3.1 269(100), 209(43)19 231 260, 353 C27H29O16 Rutin 609.1480 5.0 301(100), 271(40)20 232 nd C25H37O12 n/i 529.2235 7.8 387(28), 207(100)21 234 313 C13H11O7 p-Coumaroyl malate 279.0515 4.4 163(17%), 133 (69)22 236 321 C20H33O11 n/i 449.2033 3.9 –23 239 260, 355 C21H19O12 Isoquercetrin 463.0891 3.9 301(100), 271(32), 255(15)24 242 323 C14H13O8 Feruloyl malate 309.0618 3.3 193.0513(50), 134(100)25 243 295 shd, 325 C14H7O2 n/i 207.045 2.6 –26 245 350 C27H29O15 Kaempferol 3-O-rutinoside 593.1514 2.3 285(100), 255(45), 227 (23)27 249 350 C28H31O16 Isorhamnetin 3-O-rutinoside 623.1612 1.0 315(100), 299(52), 271 (25)28 253 260, 340 C21H19O11 Kaempferol 3-O-glucoside 447.0934 2.3 285(100), 255(58), 227(68)29 257 300 C14H23O6 n/i 287.1501 4.0 –30 259 315 C25H39O11 Dicaffeoyl quinic acid 515.2502 3.6 353(78), 209(24), 125(100)31 274 290 C16H25O7 2-Pinene-9-ol-O-glucoside 329.1602 2.2 255(100), 240(50)32 300 nd C30H15O7 Caffeoyl feruloyl tartaric acid 487.0822 1.5 193(100), 133(11)33 324 nd C18H31O5 Pinene-ol-O-glucoside 327.2157 2.2 229(47), 211(100), 171(53)34 339 nd C12H19O4 Dodecenedioic acid 227.1286 3.1 183(52), 143(15)35 342 nd C18H33O5 Hydroxy octadecanedioic acid 329.2330 2.9 229(45), 211(100), 171(35)36 373 nd C18H29O4 Dihydroxy octadecatrienoic acid 309.2068 2.9 211(68), 185(69), 121(100)37 382 312 C18H27O4 n/i 307.1917 4.5 235 (68), 211(67), 185 (90)38 405 312 C18H25O4 Corchorifatty acid D 305.1762 4.9 112(100)39 419 nd C18H29O4 Japonic acid 309.2068 2.9 249(60%), 205 (21),135(100%)40 442 nd C18H31O4 Dihydroxyoctadecadienoic acid 311.2220 1.6 293(38), 211(100), 171(90)41 471 nd C18H29O3 9-Hydroxyoctadecatrienoic acid 293.2104 1.9 275 (29), 195 (60), 183 (100)42 499 nd C18H31O3 9-Hydroxy-10,12-octadecadienoic acid 295.2278 4.1 273(32), 181(100)43 588 nd C18H29O2 Linolenic acid 277.2178 6.2 –



unambiguous structural assignment of the hydroxylated fatty-acidisomers detected with respect to the location of the functionalgroups and the E/Z geometry of the double bonds. The detailedanalysis and full structural elucidation to determine oxygenationposition and stereochemistry of the fatty acid derivatives is underway for the most abundant species. There is an increasing interestin hydroxy fatty acids, reported to perform a variety of biologicalfunctions such as insect attracting, anti-inflammatory, antimicro-bial or cytotoxic activities (Abou-ElWafa et al., 2009; Li et al.,2010; Martin-Arjol et al., 2010). Whether oxygenated fatty acidscontribute to the well documented anti-inflammatory effect foundin Urtica leaves has yet to be investigated.

The overall patterns of chemical composition varied betweendifferent Urtica accessions included in this study. A quantitativeanalysis for different classes of compounds identified in Urtica ispresented (see Supporting Information Table S1), which includesthe relative quantification of each metabolite to the recoveredamount of spiked umbelliferone (IS) to allow for comparison acrosssamples.

2.3. Multivariate data analysis of Urtica phytochemical profiles usingPCA

Differences between samples were apparent by visual examina-tion of the UPLC-QTOFMS chromatograms of different Urtica spe-cies (Supplementary Fig. S2). For instance, U. platyphylla and U.dioica show more intense peaks in the phenolics region comparedto U. mollis and U. flabellata. Due to the large number of samplesstudied, multivariate statistical analysis of the biochemical profilewas adopted for a comparison, in order to test for possible hetero-geneities among different genotypes and for the chemotaxonomyof Urtica in an untargeted approach. Principal component analysis,PCA was applied to the matrix of UPLC–QTOF-MS peak intensitiesand retention times from TIC. The metabolome clusters were lo-cated at different points in the two-dimensional space prescribedby two vectors, principal component 1 (PC1 = 38%) and principalcomponent 2 (PC2 = 21%) (Fig. 3A). Generally, all replicates fromeach sample clustered together and were separated from othergenotypes, confirming the repeatability of the methods used in thisstudy. Only one replica for each accession is displayed for the sakeof clarity. PC1 was mainly related to phenolic acids and fatty acids,based on factor loading values. Chlorogenic acid (5-O-caffeoylqui-nic acid) and caffeic acid malate were important variables to definePC1. Samples placed to the right along PC1 (red dots) were high inphenolic acids and blue dots to the left had high values for fattyacid derivatives (Fig. 3B). These results suggest that metabolitediversity in Urtica species is due not only to phenolic acids content,but also to oxygenated fatty acids. It should be noted that signalsfor flavonoid glycosides (i.e., quercetin and isorhamnetin conju-gates) – major peaks detected by MS (Table 1) – show little effectfor segregation in PCA loading plots along PC1, suggesting thatflavonoids are present at comparably lower levels in Urtica leaves,or at least their extracts. The metabolome cluster of U. dioica, un-ique for its medicinal use, and rich in phenolic acids, was foundat the far left side along PC1 (negative score value), as highlightedby the dash lined circle in (Fig. 3A) for U. diocia subsp. dioicametabolome cluster.

2.4. Multivariate analysis of Urtica phytochemical profiles using HCA

Although the PCA score plot provides some clues for grouping,the available PCs are limited because only two to three PCs canbe graphically shown, and in this case the first two PCs accountfor less than 60% of the variation. Also, the score plot does not pro-vide any information on the closeness between groups. Applyinghierarchical cluster analysis (HCA) can help to obtain further infor-

mation on these aspects. Hierarchical clustering analysis (HCA)was also applied to the TIC data from the UPLC–Q-TOF-MS analysisof each accession to provide the degree of metabolic similarity be-tween the accessions. HCA results derived from all MS signals and/or signals for phenolics did not retrieve a signal that strongly cor-relates to the molecular phylogeny (e.g., Laportea sp. (wood nettle)retrieved within, Supplementary Figs. S3 and S4). Overall, clusteranalysis only reveals a weak relation between phylogeny andchemical similarity.

HCA results derived from all MS signals displaying maximumvariance with a p-value of less than 0.1 (Fig. 4) retrieved a dendo-gram that was closer to the phylogenetic data (Fig. 7) and retrievesall samples corresponding to Clade I-A (‘‘U. dioica’’) in one cluster(Cluster I) and most taxa from Clade III (predominantly Andean-American taxa) in another cluster (Cluster II). Cluster analysis

PC1=38%

PC1

PC2=

21%

1

2

3

4

5

-10000 -5000 0 5000

-500

00

5000

1000

0B

A

0.4

0.2

0.0

-0.2

-0.4

Fig. 3. UPLC–MS (m/z 100–800) principal component analyses of Urtica taxa. (A)Score Plot of PC1 and PC2 scores. Red dots denote accessions enriched in phenolicswith negative score values whereas blue dots denote accessions enriched inoxylipids. (B) Loading plot for PC1 contributing mass peaks and their assignments:1, 5-O-caffeoylquinic acid (chlorogenic acid); 2, caffeoyl malate; 3, dihydroxy-oxo-octadecanoic acid; 4, hydroxy octadecanedioic acid; 5, octadecanetrienoic acid.Group discrimination in samples is related to qualitative and quantitative differ-ences in phenolic acids pattern. Note the lined circle in (A) for U. diocia L. subsp.dioica metabolome cluster.



using the complete data set without maximum variance (Supple-mentary Fig. S3) still retrieved the bulk of Clade I-A in one clusterand many species of Clade III in another, but much less compre-hensively. Using only phenolic components in HCA analysis thephylogenetic signal appears to be largely lost and even taxa ofClade I-A are scattered over the dendogram (SupplementaryFig. S4). An inspection of cluster 1 (Supplementary Fig. S4) formetabolites responsible for the clustering pattern shows that sam-ples from cluster 1 have comparatively higher mass signals forphenolic acids, mainly caffeoyl quinic acid(s), caffeoyl malic acidand to a lesser extent in quercetin conjugates. The phlyogeneticrelationships are thus best reflected in the overall similarity ofsamples using all compounds retrieved under maximum variance(Fig. 4).

2.5. Total phenolics and anti-inflammatory assay

To address the issue of potential variation in bioactivity withinUrtica, and to determine whether bioactivity can be predicted by

multivariate data analysis, we measured the ability of methanolextracts of 9 Urtica species and variants across all accessions to in-hibit cyclooxygenase (COX1) and (COX2) (Roschek et al., 2009): U.dioica L. subsp. cypria, U. dioica L. subsp. dioica var. dioica, U. feroxForst., U. diocia L. subsp. dioica var. holosericea, U. flabellata, U. mol-lis, U. platyphylla, U. dioica L. subsp. gracilis, U. dioica L. subsp. dioicavar. sarmatica, see Table 1 for sample details. All extracts examinedwere much more effective at inhibiting COX1 than at inhibitingCOX2, thus only data for COX1 are shown in Fig. 5. Extracts fromU. platyphylla and U. diocia, U50 & U56, respectively, were amongthe most effective ones, whereas extracts from U. flabellata andU. mollis, U31 & U51, respectively, were among the least effectiveones at a concentration of 100 mg ml�1. A positive relationshipapparently exists between polyphenolics content and anti-inflam-matory activity for most extracts examined. Accessions U50 & 56demonstrated the most potent anti-inflammatory effect and wereenriched in phenolics compared to accessions U31 & 51 with lowphenolic content and weak anti-inflammatory effect (Fig. 5).

To determine whether the bioactivity of Urtica species may bepredicted by either chemometric analysis or gross metabolic profil-ing, PCA analyses conducted for MS peaks for these selected Urticaspecies were compared with a total phenolics (TP) or better ‘‘totalantioxidants’’ assay and the anti-inflammatory assay. PCA loadingand score plots are in general agreement with the TP assay con-cerning differences in phenolics accounting for clustering amongaccessions (Fig. 6A). The loading plots suggest that caffeic acid con-jugates dominantly contribute to the discrimination of Urtica ex-tracts (data not shown). The metabolome cluster of accessionsparticularly enriched in phenolic acids, U. platyphylla and U. diocia,was found at the right side along PC1 (positive side). Clusters of U.flabellata and U. mollis, accessions enriched in hydroxy fatty acids,were also separated at the left side along PC1 with similar negativescores values (Fig. 6A). The PCA model explains 42% of the totalvariance in the first component, PC1, whereas the second principalcomponent, PC2, explains, 19% of the variance. HCA of the samedataset shows two clear clusters, referred to as group 1A and 2A,respectively (Fig. 6B). Inspection of group 1A, for metabolites medi-ating for the clustering pattern shows that individuals from group

Laportea peduncularisLaportea spec.peruvianaplatyphyllamagellanicaaqua caandicolahesperocnideflabellatabianoriiatrovirensmembranaceafissastachyoidesportosanctanatrichanthalongispicamembranaceadeltoideataiwaniana Incaicaleptophyllalongispicauren velu nalaetevirensmorifoliaferoxmolliscf. echinatapiluliferapiluliferaangus foliacannabinacannabinamairei urensdioica ssp. gracilis dioica ssp. dioica var. dioicadioica ssp. dioica var. dioicadioica ssp. dioica var. sarma ca dioica ssp. dioica var. sarma cadioica ssp. dioica var. sarma ca dioica ssp. dioica var. sarma ca dioica ssp. dioica var. elegans dioica ssp. dioica var. dioicadioica ssp. Sondeniidioica ssp. Holosericea dioica ssp. dioica var. dioicadioica ssp. pubescensdioica ssp. dioica var. angus foliadioica ssp. dioica var. hispidadioica ssp. cypriadioica ssp. subinermiskioviensisdioica ssp. dioica var. sarma cadiocia ssp. dioica var. holosericeadioica ssp. dioica var. hispidadioica ssp. subinermisdioica ssp. Subinermis

Clus

ter I

Clus

ter I

I

Fig. 4. Hierarchical cluster analysis of Urtica species and or cultivars based on groupaverage cluster analysis of the MS signals with a S/N ratio above 5 appearing from rt100 till 600 s (see Fig. 2) displaying maximum variance across samples with a pvalue less than 0.1.

0,00

20,00

40,00

60,00

80,00

100,00

120,00

COX1 % inhibi on

Total phenolics (mg/g ext.)

120.0

100.0

80.0

60.0

40.0

20.0

0.0U-31 U-51 U-55 U-46 U-62 U-61 U-63 U-56 U-50

Fig. 5. Anti-inflammatory activity against COX1 and phenolics content of Urtica sp.MeOH extract. Results are expressed for anti-inflammatory activity as % inhibitionto control on the Y1 axis and for polyphenol content as mg g�1 as displayed on theY2 axis, average of 3 replicates ± std. deviation. Accessions compared: U31 = U.flabellata; U46 = U. dioica L. subsp. dioica var. dioica, Germany; U50 = U. platyphylla;U51 = U. mollis Steud., Chile; U55 = U. dioica L. subsp. gracilis; U56 = U. dioica L.subsp. dioica var. sarmatica; U61 = U. dioica L. subsp. cypria; U62 = U. ferox Forst;U63 = U. diocia L. subsp. dioica var. holosericea. For details on sample codes, seeTable 1. Results are average of 3 biological replicates.



1A, are enriched in mass signals for polyphenolic compounds,mainly caffeoyl quinic acid isomers, as evident from the color codein HCA. Phenolic acids were found to exhibit a potent inhibition ofthe inflammation response (Sergent et al., 2010). The data herepresented not only support the use of nettle as an anti-inflamma-tory botanical (Roschek et al., 2009), it also provides a first insighton the nature of compounds accounting for its biological effect.Nevertheless, it should be noted that these findings are just a hint.They will have to be followed by more detailed studies of Urtica ex-tracts in vivo, or ideally by studies on single, isolated compound tobe conclusive.

2.6. Molecular phylogeny

The molecular data based on a four-marker analysis retrieved awell-supported and well-resolved phylogeny of the genus Urticawith considerable geographical sorting (Fig. 7). Morphologicallyaberrant U. pilulifera from the Mediterranean and West Asia repre-sents the basal branch (clade V, 100 Maximum-Likelyhood Boot-strap = ML-BS, 1 Bayesian Posterior Probability = BPP), reflectingits placement in a distinct, monotypic subgenus Sarcourtica(Chrtek, 1979; Geltman, 1988). The remainder of the genus fallsinto two well-supported major clades, one (Clade IV, 99 ML-BS, 1BPP) comprising Asian U. cannabina (IV-C, 99 ML-BS, 1 BPP), NewZealand U. ferox (IV-B, 90 ML-BS, 1 BPP) and all Mediterranean-Macronesian annuals (IV-A, 83 ML-BS, 1 BPP) as consecutive sistergroups. The other clades (I to III) are also resolved into two sister

groups each, one comprising Asian U. fissa (III-D, 91 ML-BS, 1BPP) as sister to an American-Macronesian clade (90 ML-BS, 1BPP), the latter in turn falls into three subclades, one Asian (III-B,100 ML-BS, 1 BPP), one Macronesian (III-C, 100 ML-BS, 1 BPP)and one comprising the species-rich American clade (III-A, 100ML-BS, 1 BPP). The latter clade also includes western North Amer-ican genus Hesperocnide, which has been traditionally consideredas generically distinct, but can here be shown to be nested in Urti-ca. The last major clade (I & II, 100 ML-BS, 1 BPP) is dominated by ahighly paraphyletic U. dioica in the widest sense and falls into twosister clades, one (II, 76 ML-BS, 0.85 BPP) comprising American (II-A, 72 ML-BS, 1 BPP) and East/Australasian (II-B, 0.9 BPP) taxa, theother (I, 82 ML-BS, 1 BPP) dominated by (mainly western) Eurasiantaxa (I-A, 90 ML-BS, 1 BPP) respectively Mediterranean endemics(I-B, 95 ML-BS, 1 BPP). Several morphologically aberrant taxa, suchas U. kioviensis, U. bianorii and U. atrovirens are retrieved in highlysupported clades together with more conventional taxa of the U.dioica group, indicating that (leaf) morphology is of limited valuein determining phylogenetic relatedness. Overall, the resolutionand statistical support for the phylogeny of Urtica is remarkablyhigh and allows a detailed comparison of phytochemical position(Fig. 4) in relation to phylogenetic relatedness (Fig. 7).

3. Conclusions

This work represents the first attempt to explore variation insecondary metabolites from a wide range of Urtica species. We

U. mollisU. feroxU. flabellataU. dioicassp.gracilis U. platyphyllaU. dioicassp.cypria

U. diociassp.dioicavar. holosericeaU. dioicassp. dioicavar. sarmaticaU. dioicassp.dioicavar. dioica

U. dioicassp.subinermis

1B

B

1A

PC1=42%

PC2=

19%

A

Metabolites MS signals

Fig. 6. (A) UPLC–MS (m/z 100–800) principal component analyses of Urtica taxa: U. dioica L. subsp. cypria ( ), U. dioica L. subsp. subinermis (�), U. dioica L. subsp. dioica var.dioica ( ), U. ferox Forst (�), U. diocia L. ssp. dioica var. holosericea ( ), U. flabellata (r), U. mollis ( ), U. platyphylla ( ), U. dioica L. subsp. gracilis (�), U. dioica L. subsp. dioicavar. sarmatica ( ). Note the dashed circle in Fig. 6A for U. dioica subsp. dioica samples clustering together, n = 3. (B) Hierarchical cluster analysis of Urtica species and orcultivars based on its biochemical profile as the analytical data. Note the dashed box in Fig. 6B for MS signals belonging to phenylpropanoids. Increase in metabolites signalintensity is represented by color code change ranging from red to white.



analyzed metabolites using UPLC–Q-TOF-MS, based on an extrac-tion procedure similar to that used in commercial Urtica extracts.Multivariate PCA and HCA were applied to analyze data and iden-tify key metabolites differentially accumulated across Urtica taxa.A range of phenolic compounds and fatty acid derivatives couldbe documented from the leaves of Urtica sp., providing a valuablebasis for the search for bioactive compounds in this plant groupand allowing the specific search for promising species and eco-types for particular compounds or groups of compounds.

A comparison of the metabolite cluster analyses to the phyloge-netic data (Fig. 7) shows that there is little phylogenetic signaloverall in phytochemical similarity (Supplementary Figs. S3 and

S4). The correlation is better when the full metabolite profile isused and when maximum variance is applied (Fig. 4), rather thanapplying a data set reduced to the putatively pharmacologicallyrelevant phenolics. The major clades of the phylogenetic analysisare not retrieved as clusters of phytochemically ‘‘similar’’ acces-sions. However, a single subclade is approximately retrieved inall analyses: Subclade I-A, ‘‘U. dioica’’, is mostly found as a nearlyexclusive group. The morphologically highly variable Andean-American clade is phytochemically heterogeneous and so are theannual species around U. urens. Variations in the biochemical pro-file of the target analytes examined were observed, and thus, it isclear that the differences among Urtica species play an important

Fig. 7. Molecular phylogeny with Laportea as outgroup. Strict consensus tree of a four-marker analysis (ITS, trnL-F, trnS-trnG, psbA). Figures above branches: Maximum-likelihood bootstrap values, figures below branches: Bayesian posterior probability values.



role in determining their potential medicinal value. The applicationof chemometrics for its chemical profile can be a suitable tool tocompare and assess the chemotaxonomy among different geno-types. Individual phenolic acid conjugates are key variables forcapturing most of the biochemical variation among different Urticagenotypes. Consequently, multivariate data analysis could also beused for the prediction of the pharmacological activity of Urtica ex-tracts and or commercial preparations. The data presented hereclearly show that the bulk of the taxa belonging to U. dioica andcorresponding to subclade I-A can be expected to have similaroverall pharmacological properties (Fig. 4), including U. kioviensisfrom E. Europe and U. platyphylla from Japan. The latter may be aparticularly interesting plant from the point of view of itsanti-inflammatory potential (Fig. 5). Phytochemical analysis alsorevealed that among U. dioica subsp. dioica, vars. holosericea,sarmatica & subinermis were particularly enriched in phenolicswhereas vars. elegans & angustifolia are low in these components(Supplementary Table S1). Cluster I also includes the very remotelyrelated U. urens, the second-most commonly used species of Urtica.U. urens has low levels of phenolics and flavonoids, but is close to U.dioica in overall metabolite profile. Across the genus, however,phytochemical similarity has little to do with phylogenetic related-ness and even very closely related taxa, such as U. bianorii andU. atrovirens or U. dioica subsp. gracilis and subsp. holosericea arenot retrieved together in the cluster analysis. The evolution ofthe overall phytochemical profiles in the genus appears to belargely independent of phylogeny.

4. Experimental

4.1. Plant material

We selected 63 well-characterized Urtica accessions in 32 spe-cies and a total of 43 taxa (including subspecies and varieties), rep-resenting broad geographic and taxonomical sampling. Voucherspecimens of the plants used are housed in the herbaria B, BSB(herbarium acronyms following Holmgren and Holmgren, 1998).Detailed voucher information for the chemical analysis data is pro-vided in Table 1, Voucher information and genbank numbers forthe molecular analysis are provided in Table 3. An emphasis wasplaced on (medicinal) U. dioica and its infraspecific taxa: we ana-lyzed a total of 23 samples of U. dioica in a wider sense, corre-sponding to 12 subspecies and varieties. To standardize thesource material and exclude ontogenetic and environmental ef-fects, only air-dried, median stem leaves of flowering shoots wereused. All specimens were identified with recourse to a comprehen-sive literature study and – in problematic cases – the comparisonto type material of the taxa.

4.2. Chemicals and reagents

Acetonitrile and formic acid (UPLC–MS grade) were obtainedfrom J.T. Baker (The Netherlands), milliQ water was used for LCanalysis. Chromoband C18 (500 mg, 3 ml) cartridge was purchasedfrom Macherey & Nagel (Düren, Germany). Rutin, isoquercetrin,isorhamnetin-3-O-rutinoside, isorhamnetin-3-O-glucoside,kaempferol-3-O-rutinoside, and caffeoyl malate were providedfrom Chromadex (Wesel, Germany). All other chemicals and stan-dards were purchased from Sigma Aldrich (St. Louis, MO, USA).

4.3. Extraction procedure and sample preparation for UPLC–MSanalysis

Dried Urtica leaves were ground with a pestle in a mortar usingliquid nitrogen. The powder (30 mg) was then homogenized with

2.5 ml 70% MeOH containing 5 lg/ml umbelliferone (as internalstandard for relative quantification using UPLC–MS) using a Turraxmixer (11,000 RPM) for five 20 s periods. To prevent heating, acooling period of 1 min separated each mixing period. Extractswere then vortexed vigorously and centrifuged at 3000g for30 min to remove plant debris. For UPLC-MS analyses, 500 ll werealiquoted and placed on a (500 mg) C18 cartridge preconditionedwith methanol and water. Samples were then eluted using 3 ml70% MeOH and 3 ml 100% MeOH. The eluent was evaporated undera nitrogen stream and the obtained dry residue was resuspended in500 ll methanol. Three microliter were used for analysis.

4.4. High resolution UPLC–MS analysis

Chromatographic separations were performed on an AcquityUPLC system (Waters) equipped with a HSS T3 column(100 � 1.0 mm, particle size 1.8 lm; Waters) applying the follow-ing binary gradient at a flow rate of 150 ll min–1: 0–1 min,isocratic 95% A (water/formic acid, 99.9/0.1 [v/v]), 5% B(acetonitrile/formic acid, 99.9/0.1 [v/v]); 1–16 min, linear from5% to 95% B; 16–18 min, isocratic 95% B; 18–20 min, isocratic 5%B. The injection volume was 3.1 ll (full loop injection). Eluted com-pounds were detected from m/z 100 to 1000 using a MicrOTOF-Qhybrid quadrupole time-of-flight mass spectrometer (BrukerDaltonics) equipped with an Apollo II electrospray ion source inpositive and negative ion modes using the following instrumentsettings: nebulizer gas, nitrogen, 1.6 bar; dry gas, nitrogen,6 l min–1, 190 �C; capillary, �5500 V (+4000 V); end plate offset,�500 V; funnel 1 RF, 200 Vpp; funnel 2 RF, 200 Vpp; in-sourceCID energy, 0 V; hexapole RF, 100 Vpp; quadrupole ion energy,5 eV; collision gas, argon; collision energy, 10 eV; collision RF200/400 Vpp (timing 50/50); transfer time, 70 ls; prepulse storage,5 ls; pulser frequency, 10 kHz; spectra rate, 3 Hz. Internal masscalibration of each analysis was performed by infusion of 20 ll10 mM lithium formiate in isopropanol/water, 1/1 (v/v), at a gradi-ent time of 18 min using a diverter valve.

4.5. UPLC-CID-MS/MS analysis

MicrOTOF-Q: Precursor ions were selected in Q1 with an isola-tion width of ±2D and fragmented in the collision cell applying col-lision energies in the range of 10 to 30 eV. Argon was used ascollision gas. Product ions were detected using the followingparameter settings: collision RF 150/400 Vpp (timing 50/50);transfer time, 70 ls; prepulse storage, 5 ls; pulser frequency,10 kHz; spectra rate, 1.5 Hz. For CID of in-source fragment ions(pseudo-MS3), in-source CID energy was increased from 0 to100 V.

Ion Trap MS: MSn mass spectra were also obtained from a LCQDeca XP MAX system (ThermoElectron, San Jose, USA) equippedwith a ESI source (electrospray voltage 4.0 kV, sheath gas: nitro-gen; capillary temperature: 275 �C) in negative ionization modes.The ion trap MS system is coupled with a Waters UHPLC setupusing the same elution gradient for high resolution UPLC–MS (Sec-tion 4.4). The MSn spectra were recorded by using the followingconditions: MS/MS analysis with a starting collision-induced disso-ciation energy of 30 eV and an isolation width of ±2D in a datadependent, negative ionization mode.

4.6. Identification and characterization of phenolic compounds inUrtica leaves

Phenolic compounds were characterized by their UV/Vis spectra(220–600 nm), retention times relative to external standards, peakspiking, mass spectra and MSn fragmentation patterns, and spectraof isolated compounds, compared to data from our in-house



Table 3List of vouchers for the molecular phylogeny, including herbarium vouchers and GenBank-accession numbers.

Taxon Country oforigin

Herbarium voucher DNA-Nr

trnL-trnF trnS-trnG psbA-trnH

ITS

Hesperocnide tenella Torr. USA L. Ahartt 12535-C (BSB) 2586 KF559050 KF559111 KF558990 KF558930Hesperocnide tenella Torr. USA L. S. Rose 57086 (B) 2026 KF559027 KF559088 KF558967 KF558907Laportea peduncularis (Wedd.) Chew South Africa M. Weigend 8713 (BSB) 2274 KF559047 KF559108 KF558987 KF558927Laportea spec. Kamerun Th. Franke & L. Beenken s.n. 26.10.2002

(BSB)2006 KF559082 KF558901

U. andicola Wedd. Peru M. Ackermann & D. Kollehn 276 (BSB) 3081 KF559060 KF559121 KF559000 KF558940U. angustifolia Fisch. ex Hornem. Mongolia H. H. Hilger 1603 (BSB) 2007 KF559022 KF559083 KF558962 KF558902U. aquatica Liebm. Guatemala M. Weigend 7478 (BSB) 2892 KF559056 KF559117 KF558996 KF558936U. cf. aquatica Peru Ch. Schwarzer 14-C (BSB) 1728 KF559017 KF559077 KF558957 KF558896U. atrovirens Loisel. ex Poir. Italy

(Sardinia)M. Weigend 7798 (BSB) 1724 KF559016 KF559076 KF558956 KF558895

U. bianorii (Knoche) J.Paiva Spain(Mallorca)

M. & K. Weigend 8155 (BSB) 2224 KF559037 KF559098 KF558977 KF558917

U. cannabina L. Mongolia M. Weigend 8678 (BSB) 2237 KF559043 KF559104 KF558983 KF558923U. dioica L. subsp. dioica var. holosericea Fries Germany M. & K. Weigend 8096-C (BSB) 3083 KF559062 KF559123 KF559002 KF558942U. dioica L. subsp. dioica var. angustifolia

Wimm. & GrabowskyCezchRepublic

M. & K. Weigend 5606-C (BSB) 1081 KF559009 KF559069 KF558949 KF558888

U. dioica L. subsp. dioica var. dioica Mexico Ch. Schneider et al. 52a (BSB) 2906 KF559057 KF559118 KF558997 KF558937

U. dioica L. subsp. dioica var. dioica Germany M. & K. Weigend 7807 (B) 2231 KF559039 KF559100 KF558979 KF558919

U. dioica L. subsp. dioica var. dioica Germany E. Zippel 2002/2b (B) 2232 KF559040 KF559101 KF558980 KF558920

U. dioica L. subsp. dioica var. elegans Chenev. Switzerland M. Weigend 8115 (BSB) 3082 KF559061 KF559122 KF559001 KF558941U. dioica L. subsp. dioica var. hispida Wedd. Switzerland M. & K. Weigend 8112-C (BSB) 2234 KF559042 KF559103 KF558982 KF558922U. dioica L. subsp. dioica var. hispida Wedd. Switzerland M. & K. Weigend 8109-C (BSB) 2233 KF559041 KF559102 KF558981 KF558921U. dioica L. subsp. dioica var. sarmatica Zapal. Germany M. Weigend 9328 (BSB) 3085 KF559063 KF559124 KF559003 KF558943U. dioica L. subsp. dioica var. sarmatica Zapal. Germany M. & K. Weigend 5662 (BSB) 1080 KF559008 KF559068 KF558948 KF558887U. dioica L. subsp. gracilis (Ait.) Selander Canada M. Weigend 9332 (BSB) 2009 KF559023 KF559084 KF558963 KF558903U. dioica L. subsp. sondenii Norway T. Alm s.n.-C (BSB) 1722 KF559015 KF559075 KF558955 KF558894U. dioica L. subsp. subinermis (Uechtr.)

WeigendGermany M. & K. Weigend 5661 (B) 1093 KF559011 KF559071 KF558951 KF558890

U. dioica L. subsp. subinermis (Uechtr.)Weigend

Austria M. & K. Weigend 5665 (B) 1095 KF559012 KF559072 KF558952 KF558891

U. dioica L. subsp. cypria Lind b.f. Cyprus M. Weigend et al. 8229 (BSB) 1992 KF559021 KF559081 KF558961 KF558900U. dioica L. subsp. holosericea (Nutt.) Thorne USA

(California)Ewan 9916 (K) 2288 KF559048 KF559109 KF558988 KF558928

U. dioica L. subsp. holosericea (Nutt.) Thorne USA(California)

L. Ahart 13172 (BSB) 2587 KF559051 KF559112 KF558991 KF558931

U. dioica L. subsp. pubescens (Ledeb.) Domin Italy G. Parolly, Th. Duerbye, H. H. Hilger, A.Mutallimov 13020 (B)

3071 KF559059 KF559120 KF558999 KF558939

U. echinata Benth. Peru M. Weigend et al. 9227-C (BSB) 1078 KF559007 KF559067 KF558947 KF558886U. cf. echinata Benth. Peru M. Weigend et al. 8478 (BSB) 3086 KF559064 KF559125 KF559004 KF558944U. ferox Forst. New

ZealandM. Weigend 8211–2 (BSB) 2010 KF559024 KF559085 KF558964 KF558904

U. fissa Pritz. Taiwan M. Weigend 8129 (BSB) 2011 KF559025 KF559086 KF558965 KF558905U. flabellata Kunth Peru M. Weigend et al. 7728 (BSB) 2040 KF559028 KF559089 KF558968 KF558908U. incisa Poir. New

ZealandAtwood 48288 (NZ Landcare Research) 2265 KF559046 KF559107 KF558986 KF558926

U. cf. incisa NewZealand

M. Weigend 8212 (BSB) 2836 KF559052 KF559113 KF558992 KF558932

U. kioviensis Rogov. Germany N. Nürk & J. Devers 333 (BSB) 2240 KF559044 KF559105 KF558984 KF558924U. laetevirens Maxim. Tibet H. Rushforth & H. McAllister 5327 (B) 2908 KF559058 KF559119 KF558998 KF558938U. lalibertadensis Weigend Peru M. Weigend et al. 8018-C (B) 1683 KF559014 KF559074 KF558954 KF558893U. leptophylla Kunth Peru Weigend et al. 7706 (B) 1552 KF559013 KF559073 KF558953 KF558892U. longispica Killip Ecuador M. Weigend & G. Brokamp 9113-C (BSB) 1889 KF559020 KF559080 KF558960 KF558899U. magellanica Poir. Argentina M. Weigend et al. 6809-C (BSB) 2881 KF559053 KF559114 KF558993 KF558933U. mairei Levl. Tibet H. Rushforth & H. McAllister 5247 (BSB) 2212 KF559032 KF559093 KF558972 KF558912U. membranacea Italy M. Gottschling 1 (BSB) 2229 KF559038 KF559099 KF558978 KF558918U. membranacea Spain

(Mallorca)M. Ackermann & C. Knödler s. n. (BSB) 2219 KF559033 KF559094 KF558973 KF558913

U. mollis Steud. Chile H. Gunckel 29.962 (CONC) 2885 KF559054 KF559115 KF558994 KF558934U. mollis Steud. Chile Kalin Arroyo 81901. (CONC) 2886 KF559055 KF559116 KF558995 KF558935U. mollis Steud. Chile C. Villagrán 53963 (CONC) 2054 KF559029 KF559090 KF558969 KF558909U. morifolia Poir. Spain

(Teneriffa)M. & K. Weigend 8242 (BSB) 2206 KF559030 KF559091 KF558970 KF558910

U. morifolia Poir. Spain(Teneriffa)

M. & K. Weigend 8240 (BSB) 2207 KF559031 KF559092 KF558971 KF558911

U. peruviana Geltman Peru M. Weigend et al. 7625-C (BSB) 1886 KF559018 KF559078 KF558958 KF558897U. pilulifera L. Cyprus M.&. K. Weigend 8153-C (B) 2221 KF559035 KF559096 KF558975 KF558915U. pilulifera L. Italy Hilger s.n. (BSB) 2223 KF559036 KF559097 KF558976 KF558916U. platyphylla Wedd. Japan N. M. Nürk 357 (B) 3088 KF559065 KF559126 KF559005 KF558945U. portosanctana Press Spain

(Teneriffa)M. & K. Weigend 8234 (BSB) 2291 KF559049 KF559110 KF558989 KF558929

U. stachyoides Webb Spain M. & K. Weigend 8230 (BSB) 2017 KF559026 KF559087 KF558966 KF558906



database and reference literature (Bucar et al., 2006; Budzianowski,1991; Chaurasia and Wichtl, 1987; Guil-Guerrero et al., 2003;Kraus and Spiteller, 1990; Zhou et al., 2009).

4.7. MS data processing and multivariate analyses

Relative quantification of metabolite profiles after UPLC-MSwas performed using XCMS data analysis software, which can bedownloaded freely as an R package from the Metlin MetaboliteDatabase (http://137.131.20.83/download/) (Smith et al., 2006).This software approach employs peak alignment, matching andcomparison following the exact procedure described in (Faragand Wessjohann, 2012).

4.8. DNA isolation and amplification

All taxa used in the phytochemical analysis were sequenced,representing a total of 59 ingroup samples, corresponding to 43taxa (32 species, 12 subspecies and varieties). Two species ofLaportea were used as the out group (Hadiah et al., 2008). Themolecular markers used failed to provide resolution between the‘‘varieties’’ of U. dioica subsp. dioica and not all accessions used inthe phytochemical analysis were therefore included in the molec-ular phylogeny. DNA extraction, PCR, purification, and sequencingfollowed standard protocols as described in Gottschling and Hilger(2001). The same primers were used for amplification andsequencing: the trnL-F spacer was amplified with primers C andF of Taberlet et al. (1991), the ITS locus with primers P5 and P4of White et al. (1990), trnS-G with primers trn_S(GCU) andtrn_G(UCC) of Hamilton (1999), psbA—trnH with the primers andthe protocols of (Weigend et al., 2010). Sequences were manuallyaligned in Align Ver.07/04 (Hepperle, 2004).

4.9. Molecular phylogenetic reconstruction

Phylogenetic analyses were conducted for the combined dataset(ITS, trnS-trnG, trnH-psbA and trnL-trnF) with Maximum likelihood(ML) and Bayesian (BA) methods (Felsenstein, 1981). Substitutionmodels were previously tested for each region separately, usingModeltest v.3.7 and the analyses were performed with partitionsunlinked, each with a different substitution model (ITS:GTR + I + G; trnS-G: K81uf + G; psbA: TIM + G; trnL-F; TVM + G).ML analyses were carried out on the RAxML web-server (Stamata-kis et al., 2008), and bootstrap support was calculated from 1000replicates. BA analyses were conducted in MrBayes v. 3.1.2 (Ron-quist and Huelsenbeck, 2003), with four independent runs of2,000,000 generations each, and sampling every 1000 generations.After inspection of convergence in Tracer (available at http://tree.-bio.ed.ac.uk/software/tracer/), the first 1000 trees were discardedas burn-in. Potential incongruence between ITS and the combinedplastid regions was assessed using the Incongruence Length Differ-ence (ILD) test (Farris et al., 1994) as implemented in PAUP v. 4.0(Swofford, 2003), with 1000 replicates and saving a maximum of1000 trees in each replicate. Part of the analyses was conductedat the High Performance Computing of the Freie Universität Berlin.

ILD test indicate that datasets are incongruent (p = 0.001), but sep-arate analysis of the ITS- and the chloroplast markers revealed nowell-supported differences in topology.

4.10. Anti-inflammatory cyclooxygenase-1 (COX) inhibition assay

All reagents and solutions were prepared according to the pro-tocols established by Cayman Chemicals (Ann Arbor, MI, USA) forthe COX-1 inhibition assay. 70% MeOH/water (v/v) extract wasprepared for 9 Urtica accessions (U. dioica subsp. cypria, U. dioicasubsp. dioica var. dioica, U. ferox, U. diocia subsp. dioica var. holoseri-cea, U. flabellata, U. mollis, U. platyphylla, U. dioica subsp. gracilis, U.dioica subsp. dioica var. sarmatica), and the extract lyophilized.Dried extracts were dissolved in neat DMSO and diluted in reactionbuffer to a final DMSO concentration of 1% (v/v). Extracts weretested at concentrations of 100, 150, and 200 mg ml�1. Reactionswere conducted with COX enzyme in the presence of heme as aco-factor. The enzymes were incubated at 37 �C for 15 min with se-rial dilutions of the nettle extracts or reaction buffers to determine100% enzyme activity (positive control), and heat inactivatedenzymes were used to as negative controls (0% enzyme activity).Arachidonic acid (100 lM) was added to each well and the fluores-cence product of the reaction was measured at 670 nm usingmicroplate reader. Percent inhibition of the COX enzymes wasdetermined by comparing the extract loaded wells with thepositive and negative controls. Commercially available COX-1(SC-560) inhibitor was used for comparison. The COX-1 inhibitorhas an IC50 value of 50 nM. The assay was carried out in triplicate.

4.11. Total phenolics quantification

A spectrophotometric method using Folin–Ciocalteu reagent forreducing substances was adapted for the phenolic content assay inUrtica leaves. Extracts were prepared by cold extraction with shak-ing over 3 h using 70% MeOH. Plant debris was removed by centri-fugation and the solvent was removed by evaporation undernitrogen followed by lyophilisation. The residue was dissolved inmethanol to obtain a solution of a concentration of 10 mg ml�1. Fo-lin–Ciocalteu reagent (100 ll) was added to a test tube containing20 ul of the extract solution. Contents were mixed and a saturatedaqueous sodium carbonate solution (200 ll) was added to thetube. The volume was adjusted to 2 ml by the addition of 0.68 mlof milliQ water and the contents were mixed vigorously. Tubeswere allowed to stand at room temperature for 25 min and thencentrifuged for 5 min at 2500g. Absorbance of the supernatantwas read at 760 nm. Blank samples of each extract were used forbackground subtraction. Caffeic acid was used as standard for thecalibration curve at concentrations of 0.01, 0.1, 1, and 5 mg ml�1.The assay was carried out in triplicate.

Acknowledgements

Dr. Mohamed A. Farag acknowledges the financial support ofthe Alexander von Humboldt foundation, Germany. We want toexpress our sincere gratitude to various scientists who provided

Table 3 (continued)

Taxon Country oforigin

Herbarium voucher DNA-Nr

trnL-trnF trnS-trnG psbA-trnH

ITS

(Teneriffa)U. taiwaniana S. S. Ying Taiwan J. N. Chen et al. 00573-C (BSB) 2242 KF559045 KF559106 KF558985 KF558925U. trichantha (Wedd.) Acevedo & L. E. Navas Peru F. Cáceres 3326 (BSB) 3090 KF559066 KF559127 KF559006 KF558946U. urens L. Germany M. Weigend 5667 (BSB) 1082 KF559010 KF559070 KF558950 KF558889U. urens L. Peru M. Weigend et al. 8317 (BSB) 2220 KF559034 KF559095 KF558974 KF558914U. urentivelutina Weigend Peru M. Weigend & Ch. Schwarzer 7907 (BSB) 1887 KF559019 KF559079 KF558959 KF558898



plant material for this study, namely Fatima Cáceres-H. (Arequipa,Peru), Ralf Hand, Nicolai M. Nürk, Tobias Kern, Tilo Henning (Ber-lin), Markus Ackermann (Bonn), Christian Schwarzer (Potsdam),Hugh McAllister (Liverpool, UK), Torbjørn Alm (Tromsø, Norway),Lowell Ahartt (San Francisco, USA). We thank Dr. Andrea Porzel(IPB, Germany) for assistance with NMR analysis.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.phytochem.2013.09.016.

References

Abou-ElWafa, G.S.E., Shaaban, M., Shaaban, K.A., El-Naggar, M.E.E., Laatsch, H., 2009.Three new unsaturated fatty acids from the marine green alga Ulva fasciataDelile. Zeitschrift fur Naturforschung Section B-A Journal of Chemical Sciences64, 1199–1207.

Boufford, D.E., 1997. Urticaceae. In: Flora of North America Editorial Committee(Eds.), Flora of North America (North of Mexico) 3. New York, pp. 400–405.

Bucar, F., Britzmann, B., Streit, B., Weigend, M., 2006. LC-PDA-MS-profiles ofphenolic compounds in extracts of aerial parts of Urtica species. Planta Medica72, 152.

Budzianowski, J., 1991. Caffeic acid-esters from Urtica dioica and U. urens. PlantaMedica 57, 507.

Cao, G., Zhang, Y., Feng, J.A., Cai, H., Zhang, C.R., Ding, M.J., Cong, X.D., Cai, B.C., 2011.A Rapid and sensitive assay for determining the main components in processedFructus corni by UPLC–Q-TOF-MS. Chromatographia 73, 135–141.

Chaurasia, N., Wichtl, M., 1987. Flavonol glycosides from Urtica dioica. PlantaMedica 53, 432–434.

Chrtek, J., 1979. Bestimmungsschlüssel der inder CSR vorkommenden Arten derGattung Urtica L. Zpravy Ceskoslovenske Botanicke Spolecnosti pfiCeskoslovenske Akademii Ved. Prague 14, 1–7.

Chrubasik, S., Enderlein, W., Bauer, R., Grabner, W., 1997. Evidence forantirheumatic effectiveness of herba Urticae dioicae in acute arthritis: a pilotstudy. Phytomedicine 4, 105–108.

Clifford, M.N., Knight, S., Surucu, B., Kuhnert, N., 2006a. Characterization by LC–MSn

of four new classes of chlorogenic acids in green coffee beans:Dimethoxycinnamoylquinic acids, diferuloylquinic acids, caffeoyl-dimethoxycinnamoylquinic acids, and feruloyl-dimethoxycinnamoylquinicacids. Journal of Agricultural and Food Chemistry 54, 1957–1969.

Clifford, M.N., Marks, S., Knight, S., Kuhnert, N., 2006b. Characterization by LC–MSn

of four new classes of p-coumaric acid-containing diacyl chlorogenic acids ingreen coffee beans. Journal of Agricultural and Food Chemistry 54, 4095–4101.

Dreyer, J., Dreyling, G., Feldmann, F., 1996. Cultivation of stinging nettle Urtica dioicaL. with high fibre content as an raw material for the production of fibre andcellulose: qualitative and quantitative differentiation of ancient clones. Journalof Applied Botany-Angewandte Botanik 70, 28–39.

Edmondson, J.R., 1992. Urticaceae. In: Tutin, T.G., Burges, N.A., Chater, A.O.,Edmondson, J.R., Heywood, V.H., Moore, D.M., Valentine, D.H., Walters, S.M.,Webb, D.A. (Eds.), Flora Europaea 1, second edition. Cambridge UniversityPress, Cambridge, pp. 79–81.

El Haouari, M., Bnouham, M., Bendahou, M., Aziz, M., Ziyyat, A., Legssyer, A., Mekhfi,H., 2006. Inhibition of rat platelet aggregation by Urtica dioica leaves extracts.Phytotherapy Research 20, 568–572.

Exarchou, V., Fiamegos, Y.C., van Beek, T.A., Nanos, C., Vervoort, J., 2006. Hyphenatedchromatographic techniques for the rapid screening and identification ofantioxidants in methanolic extracts of pharmaceutically used plants. Journal ofChromatography A 1112, 293–302.

Farag, M.A., EL-Ahmady, S., Elian, F., Wessjohann, L.A., 2013. Metabolomics drivenanalysis of artichoke leaf and its commercial products via UHPLC-q-TOF-MS.Phytochemistry 95, 177–187.

Farag, M.A., Porzel, A., Schmidt, J., Wessjohann, L.A., 2012a. Metabolite profiling andfingerprinting of commercial cultivars of Humulus lupulus L. (hop): acomparison of MS and NMR methods in metabolomics. Metabolomics 8, 492–507.

Farag, M.A., Porzel, A., Wessjohann, L.A., 2012b. Comparative metabolite profilingand fingerprinting of medicinal licorice roots using a multiplex approach of GC–MS, LC–MS and 1D NMR techniques. Phytochemistry 76, 60–72.

Farag, M.A., Wessjohann, L.A., 2012. Metabolome Classification of CommercialHypericum perforatum (St. John’s Wort) Preparations via UPLC–qTOF-MS andChemometrics. Planta Medica 78, 488–496.

Farris, J.S., Kallersjo, M., Kluge, A.G., Bult, C., 1994. Testing significance ofincongruence. Cladistics-the International Journal of the Willi Hennig Society10, 315–319.

Felsenstein, J., 1981. Evolutionary trees from DNA sequences: a maximumlikelihood approach. Journal of Molecular Evolution 17, 368–376.

Friis, I., 1993. Urticaceae. In: Kubitzki, K. (Ed.), The Families and Genera of VascularPlants II. Springer Verlag, Berlin, pp. 612–629.

Gansser, D., Spiteller, G., 1995. Aromatase inhibitors from Urtica dioica roots. PlantaMedica 61, 138–140.

Geltman, D.V., 1982. The genus Urtica (Urticaceae) in the Flora of East Siberia andthe Far East of the USSR. Botanicheskii Zhurnal 67, 194–207.

Geltman, D., 1988. Genus Urtica L. (Urticaceae) in the URSS (in Russian). NovitatesSystematicae Plantarum Vascularum 25, 68–80.

Gottschling, M., Hilger, H.H., 2001. Phylogenetic analysis and character evolution ofEhretia and Bourreria (Ehretiaceae, Boraginales) and their allies based on ITS1sequences. Botanische Jahrbücher für Systematik und Pflanzengeographie 123,249–268.

Grata, E., Boccard, J., Guillarme, D., Glauser, G., Carrupt, P.A., Farmer, E.E., Wolfender,J.L., Rudaz, S., 2008. UPLC–TOF-MS for plant metabolomics: a sequentialapproach for wound marker analysis in Arabidopsis thaliana. Journal ofChromatography B – Analytical Technologies in the Biomedical and LifeSciences 871, 261–270.

Guil-Guerrero, J.L., Rebolloso-Fuentes, M.M., Isasa, M.E.T., 2003. Fatty acids andcarotenoids from Stinging Nettle (Urtica dioica L.). Journal of Food Compositionand Analysis 16, 111–119.

Hall, R.D., Hardy, N.W., 2012. Practical applications of metabolomics in plantbiology. Methods in Molecular Biology (Clifton, NJ) 860, 1–10.

Hadiah, J.T., Conn, B.J., Quinn, C.J., 2008. Infra-familial phylogeny of Urticaceae,using chloroplast sequence data. Australian Systematic Botany 21, 375–385.

Hamilton, M.B., 1999. Four primer pairs for the amplification of chloroplastintergenic regions with intraspecific variation. Molecular Ecolology 8, 521–523.

Hanhineva, K., Kokko, H., Siljanen, H., Rogachev, I., Aharoni, A., Karenlampi, S.O.,2009. Stilbene synthase gene transfer caused alterations in thephenylpropanoid metabolism of transgenic strawberry (Fragaria x ananassa).Journal of Experimental Botany 60, 2093–2106.

Hepperle, D., 2004. Align Ver.07/04�. Multisequence Alignment-Editor andPreparation/Manipulation of Phylogenetic Datasets. Win32-Version 2004.Distributed by the author via : http://www.sequentix.de.

Hirano, T., Homma, M., Oka, A., 1994. Effects of stinging nettle root extracts andtheir steroidal components on the Na+,K+-ATPase of the benign prostatichyperplasia. Planta Medica 60, 30–33.

Holmgren, P.K., Holmgren, N.H., 1998. (continuously updated): Index herbariorum.Published on the Internet http://sciweb.nybg.org/science2/IndexHerbariorum.asp.

Hudec, J., Burdova, M., Kobida, L., Komora, L., Macho, V., Kogan, G., Turianica, I.,Kochanova, R., Lozek, O., Haban, M., Chlebo, P., 2007. Antioxidant capacitychanges and phenolic profile of Echinacea purpurea, nettle (Urtica dioica L.), anddandelion (Taraxacum officinale) after application of polyamine and phenolicbiosynthesis regulators. Journal of Agricultural and Food Chemistry 55, 5689–5696.

Kraus, R., Spiteller, G., 1990. Phenolic-compounds from roots of Urtica dioica.Phytochemistry 29, 1653–1659.

Legssyer, A., Ziyyat, A., Mekhfi, H., Bnouham, M., Tahri, A., Serhrouchni, M., Hoerter,J., Fischmeister, R., 2002. Cardiovascular effects of Urtica dioica L. in isolated ratheart and aorta. Phytotherapy Research 16, 503–507.

Li, S.S., Jiang, Z.M., Thamm, L., Zhou, G.T., 2010. 10-Hydroxy-2-decenoic acid as anantimicrobial agent in draft keg-conditioned wheat beer. Journal of theAmerican Society of Brewing Chemists 68, 114–118.

Liu, F., Pan, C., Drumm, P., Ang, C.Y.W., 2005. Liquid chromatography–massspectrometry studies of St. John’s wort methanol extraction: activeconstituents and their transformation. Journal of Pharmaceutical andBiomedical Analysis 37, 303–312.

Martin-Arjol, I., Bassas-Galia, M., Bermudo, E., Garcia, F., Manresa, A., 2010.Identification of oxylipins with antifungal activity by LC-MS/MS from thesupernatant of Pseudomonas 42A2. Chemistry and Physics of Lipids 163, 341–346.

Nahata, A., Dixit, V., 2012. Ameliorative effects of stinging nettle (Urtica dioica) ontestosterone-induced prostatic hyperplasia in rats. Andrologia 44, 396–409.

Okada, T., Nakamura, Y., Kanaya, S., Takano, A., Malla, K.J., Nakane, T., Kitayama, M.,Sekita, S., 2009. Metabolome analysis of ephedra plants with differentcontents of ephedrine alkaloids by using UPLC–Q-TOF-MS. Planta Medica 75,1356–1362.

Pinelli, P., Ieri, F., Vignolini, P., Bacci, L., Baronti, S., Romani, A., 2008. Extraction andHPLC analysis of phenolic compounds in leaves, stalks, and textile fibers ofUrtica dioica L. Journal of Agricultural and Food Chemistry 56, 9127–9132.

Ronquist, F., Huelsenbeck, J.P., 2003. MrBayes 3: Bayesian phylogenetic inferenceunder mixed models. Bioinformatics 19, 1572–1574.

Roschek, B., Fink, R.C., McMichael, M., Alberte, R.S., 2009. Nettle extract (Urticadioica) affects key receptors and enzymes associated with allergic rhinitis.Phytotherapy Research 23, 920–926.

Schottner, M., Gansser, D., Spiteller, G., 1997a. Lignans from the roots of Urtica dioicaand their metabolites bind to human sex hormone binding globulin (SHBG).Planta Medica 63, 529–532.

Schottner, M., Reiner, J., Tayman, F.S.K., 1997b. (+)-neo-olivil from roots of Urticadioica. Phytochemistry 46, 1107–1109.

Sergent, T., Piront, N., Meurice, J., Toussaint, O., Schneider, Y.J., 2010. Anti-inflammatory effects of dietary phenolic compounds in an in vitro model ofinflamed human intestinal epithelium. Chemico-Biological Interactions 188,659–667.

Smith, C.A., Want, E.J., O’Maille, G., Abagyan, R., Siuzdak, G., 2006. XCMS: Processingmass spectrometry data for metabolite profiling using Nonlinear peakalignment, matching, and identification. Analytical Chemistry 78, 779–787.

Stamatakis, A., Hoover, P., Rougemont, J., 2008. A rapid bootstrap algorithm for theRAxML web servers. Systematic Biology 57, 758–771.



Sumner, L.W., Mendes, P., Dixon, R.A., 2003. Plant metabolomics: large-scalephytochemistry in the functional genomics era. Phytochemistry 62, 817–836.

Swofford, D.L., 2003. PAUP⁄ Phylogenetic analysis using parsimony (⁄and othermethods), v. 4.0 beta 10. Sinauer Associates, Sunderland, Massachusetts.

Taberlet, P., Gielly, L., Pautou, G., Bouvet, J., 1991. Universal primers foramplification of three non-coding regions of chloroplast DNA. Plant MolecularBiology 17, 1105–1110.

Takahashi, H., Kai, K., Shinbo, Y., Tanaka, K., Ohta, D., Oshima, T., Altaf-Ul-Amin, M.,Kurokawa, K., Ogasawara, N., Kanaya, S., 2008. Metabolomics approach fordetermining growth-specific metabolites based on Fourier transform ioncyclotron resonance mass spectrometry. Analytical and BioanalyticalChemistry 391, 2769–2782.

Weigend, M., Luebert, F., 2009. Weeding the Nettles I.: clarifying species limits inperennial Urtica (Urticaceae) from southern and central Chile and Argentina.Phytotaxa 2, 1–12.

Weigend, M., Gottschling, M., Selvi, F., Hilger, H.H., 2010. Fossil and extant WesternHemisphere Boragineae, and the Polyphyly of ‘‘Trigonotideae’’ Riedl(Boraginaceae: Boraginoideae). Systematic Botany 35, 409–419.

Weigend, M., 2006. Urtica dioica subsp. cypria, with a re-evaluation of the U-dioicagroup (Urticaceae) in western Asia. Willdenowia 36, 811–822.

White, T.J., Bruns, T., Lee, S., Taylor, J., 1990. Amplifications and direct sequencing offungal ribosomal RNA genes for phylogenetics. In: Innis, M., Gelfand, D.,Sninsky, J., White, T. (Eds.), PCR Protocols: a Guide to Methods and Applications.Academic Press, San Diego, pp. 315–322.

Wolfender, J.L., Glauser, G., Grata, E., Rudaz, S., 2008. UPLC–TOF-MS for highresolution plant metabolite profiling and metabolomics. Planta Medica 74, 919–920.

Zhou, Y., Wang, W., Tang, L., Yan, X.g., Shi, L.y., Wang, Y.q., Feng, B.m., 2009. Lignanand flavonoid glycosides from Urtica laetevirens Maxim. Journal of NaturalMedicines 63, 100–101.

Zuloaga, F.O., Morrone, O., Belgrano, M.J. (Eds.), 2008. Catálogo de las plantasvasculares del Cono Sur (Argentina, sur de Brasil, Chile, Paraguay y Uruguay).Monographs in Systematic Botany from the Missouri Botanical, Garden 107, vol.3, pp. 3348.


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Author's personal copy - Cairo Universityscholar.cu.edu.eg/sites/default/files/mfarag73/files/farag__urtica... · chemotaxonomy of the genus. The molecular data present a highly resolved