Identification of Medicinal Plants in the Family Fabaceae Using a Potential DNA Barcode ITS2

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Identification of medicinal plants in the family Fabaceae using a potential DNA barcode ITS2

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Identiﬁcation of medicinal plants in the family Fabaceae using a potential DNA barcode ITS2

Ting Gao a,1, Hui Yao a,1, Jingyuan Song a, Chang Liu a,b, Yingjie Zhu a, Xinye Ma a, Xiaohui Pang a, Hongxi Xu c, Shilin Chen a,∗ a Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, 151 Malianwa North Road, Haidian District, Beijing 100193, PR China b Molecular Chinese Medicine Laboratory, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 10 Sassoon Road, Pokfulam, Hong Kong, PR China c Chinese Medicine Laboratory, Hong Kong Jockey Club Institute of Chinese Medicine, New Territories, Hong Kong, PR China article info abstract

Article history: Aim of the study: To test whether the ITS2 region is an effective marker for use in authenticating of the Received 25 December 2009 family Fabaceae which contains many important medicinal plants. Received in revised form 20 April 2010 Materials and methods: The ITS2 regions of 114 samples in Fabaceae were amplified. Sequence assembly Accepted 21 April 2010 was assembled by CodonCode Aligner V3.0. In combination with sequences from public database, the Available online 7 May 2010 sequences were aligned by Clustal W, and genetic distances were computed using MEGA V4.0. The intra- vs. inter-specific variations were assessed by six metrics, wilcoxon two-sample tests and “barcoding Keywords: gaps”. Species identification was accomplished using TaxonGAP V2.4, BLAST1 and the nearest distance DNA barcoding Fabaceae method. ITS2 (internal transcribed spacer region 2) Results: ITS2 sequences had considerable variation at the genus and species level. The intra-specific diver- Taxonomy gence ranged from 0% to 14.4%, with an average of 1.7%, and the inter-specific divergence ranged from 0% to 63.0%, with an average of 8.6%. Twenty-four species found in the Chinese Pharmacopoeia, along with another 66 species including their adulterants, were successfully identified based on ITS2 sequences. In addition, ITS2 worked well, with over 80.0% of species and 100% of genera being correctly differentiated for the 1507 sequences derived from 1126 species belonging to 196 genera. Conclusions: Our findings support the notion that ITS2 can be used as an efficient and powerful marker and a potential barcode to distinguish various species in Fabaceae. © 2010 Elsevier Ireland Ltd. All rights reserved.

1. Introduction genera of Fabaceae have been reported to be toxic. For example, Fabaceae is the second largest family of medicinal plants, con- Acacia rigidula has been shown to contain appreciable levels of taining over 490 medicinal plant species, most of which have been toxic alkaloids (Clement et al., 1998), and many of species of the used as traditional medicines. There are 31 species of medicinal genus Crotalaria contain pyrrolizidine alkaloids, which are toxic to plants belonging to 20 genera in the family Fabaceae that have been mammals and birds (Williams and Molyneux, 1987). described in the Chinese Pharmacopoeia (Chinese Pharmacopoeia Commonly used medicinal species and their adulterants are Commission, 2005), as well as numerous species that are included frequently found in the market together. For example, Astragalus in the Japanese Pharmacopoeia. These species possess important membranaceus and Astragalus mongolicus are two of the most pop- medicinal properties and have been widely used as components of ular traditional Chinese medicines. However, Hedysarum polybotrys pharmaceutical products. For instance, Glycyrrhiza uralensis, Gly- is often mistaken for Radix Astragali (Ma et al., 2002). Pueraria cyrrhiza inflata, and Glycyrrhiza glabra, which are all generally used tuberosa is often used in traditional medicine in India, but there are in traditional medicines, have inhibitory effects on HIV replication at least three other botanical entities, Ipomoea mauritiana, Adenia in vitro and anti-Fas antibody-induced hepatitis (Okamoto, 2000; hondala and Cycas circinalis that are traded under the same name Watanabe et al., 1996). Trigonella foenum-graecum has been shown (Devaiah and Venkatasubramanian, 2008). to reduce blood glucose levels significantly (Vats et al., 2002). Addi- The identification of different species of Fabaceae is difficult tionally, plant materials from nearly 290 species belonging to 100 when based solely on morphological characteristics (Hou et al., 2008; Newmaster and Ragupathy, 2009); additionally, some limita- tions in traditional taxonomy prevent this technique from meeting

∗ the complicated demands of species recognition (Maddison et al., Corresponding author. Tel.: +86 10 62899700; fax: +86 10 62899776. 2007). As such, a method for the simple and accurate authentication E-mail address: [email protected] (S. Chen). 1 These two authors contribute equally to this work. of Fabaceae is indispensible.

Several DNA barcodes (matK, rbcL, psbA-trnH, ITS, rpoC1, etc.) Table 1 have been developed for the identiﬁcation of species (Kress and The ITS2 sequences of plant materials used in the present study. Erickson, 2007; Kress et al., 2009; Lahaye et al., 2008; Song et al., ITS2 sequences Dataset 1 Dataset 2

2009; Newmaster and Ragupathy, 2009; Pang et al., 2010; Luo et Total no. of sequences 184(92)a 1507(1126) al., 2010), but the barcodes for Fabaceae species are limited to a No. of sequences belonging 119(61) 1393(1028) few genera and cannot been applied across the family (Edwards et to genera having more al., 2008; Hollingsworth et al., 2009; Newmaster and Ragupathy, than one species No. of sequences belonging 136(44) 605(224) 2009). Recently, Plant Working Group has recommended rbcL and to species having more matK as core DNA barcodes (CBOL Plant Working Group, 2009). than one samples However, theoretically, nuclear DNA would provide more infor- a The numbers of species to which these ITS2 sequences belong are shown in mation for barcoding than organellar DNA (Chase and Fay, 2009). bracket. The effectiveness of ITS and ITS1 have been questioned in regard to improving the quality of primers to enhance their universality × (Chase et al., 2007; Kress and Erickson, 2007; Chen et al., 2010). 0.5 TBE buffer and purified with the TIANGel Midi Purification While, being part of ITS, ITS2 is relatively easy to be amplified using Kit (Tiangen Biotech Co., China). The purified PCR products were one pair of universal primers (Chiou et al., 2007; Chen et al., 2010). sequenced on an ABI 3730XL sequencer (Applied Biosystems Inc.) In addition, ITS2 has been found to provide taxonomic signatures using the amplification primers. in systematic evolution (Coleman, 2003, 2007; Schultz et al., 2005). The ITS2 region is also a promising potential molecular marker to 2.3. Sequence alignment and data analysis be used for rapid taxonomic classification (Chiou et al., 2007; Chen et al., 2010). Contig assembly and the generation of consensus sequences In the current study, we utilize ITS2 as a DNA barcode to dif- were performed using CodonCode Aligner V 3.0 (CodonCode Co., ferentiate medicinal plants within the Fabaceae family in order to USA). The ITS2 sequences from GenBank were subjected to Hidden ensure their safe application in traditional uses. Markov Model (HMM) model (Eddy, 1998, 2000) analysis to remove the conserved 5.8S and 26S (or equivalent) rRNA sequences (Keller et al., 2009). And we also used HMM based on well-curated fun- 2. Materials and methods gal sequences to search for downloaded ITS2 sequences to remove the possible contaminated sequences of fungi. The sequences were 2.1. Plant materials then aligned using Clustal W (Thompson et al., 1994) and the genetic distances were computed using MEGA 4.0 according to the In our study, 114 samples, which belonged to 85 species from Kimura 2-Parameter (K2P) model (Tamura et al., 2007). The average 49 genera, were collected from large geographical areas in China intra-specific distance, coalescent depth and Theta were calculated between July 2007 and January 2008 (Online Resource 1). All plant to evaluate the intra-specific variation using the K2P model (Meyer species were identified by Professor Yulin Lin, Institute of Medic- and Paulay, 2005; Chen et al., 2010). The average inter-specific dis- inal Plant Development (IMPLAD), Chinese Academy of Medical tance, the minimum inter-specific distance and Theta prime were Sciences and Professor Quanru Liu, Beijing Normal University. The used to represent inter-specific divergences (Meier et al., 2008; voucher samples were deposited in the herbarium of IMPLAD. Meyer and Paulay, 2005; Chen et al., 2010). The distributions of We have combined the sequences generated in our lab and intra- vs. inter-specific variability were compared using DNA bar- those available from GenBank. The first dataset is comprised of 184 coding gaps (Lahaye et al., 2008; Meyer and Paulay, 2005; Chen et important medicinal species and their adulterants as well as related al., 2010). Wilcoxon two-sample tests were performed as described species in Fabaceae (Online Resource 1, 2). These include 71 sam- previously (Kress and Erickson, 2007; Lahaye et al., 2008; Chen ples belonging to 29 species from 19 genera found in the Chinese et al., 2010). The discriminatory power of ITS2 sequences for sis- Pharmacopoeia (Chinese Pharmacopoeia Commission, 2005). The ter species was calculated by TaxonGAP V2.4 software (Naser et second dataset consists of all data from dataset 1 and all sequences al., 2007; Slabbinck et al., 2008). Two methods of species identi- from GenBank (Online Resource 1–3) belonging to Fabaceae sam- fication, including BLAST1 and the nearest distance method, were ples. This dataset includes 1507 sequences from 1126 species performed as described previously (Ross et al., 2008; Chen et al., representing 196 genera across all three subfamilies of Fabaceae 2010). In the BLAST1 method, correct identification means that and was used as a denser dataset to assess the identification effi- the best BLAST hit of the query sequence is from the expected ciency of ITS2 sequences. Our datasets contain many closely related species; ambiguous identification means that the best BLAST hits species (Table 1). for a query sequence were found to be those of several species including the expected species; incorrect identification means that 2.2. DNA extraction, amplification and sequencing the best BLAST hit of the query sequence is not from the expected species. In the distance method, correct identification means that Genomic DNA was extracted from silica gel-dried leaves or the the hit in our database based on the smallest genetic distances is medicinal materials bought from the markets including Trigonella from the same species as the that of the query; ambiguous iden- foenum-graecum and Glycine max according to the protocol associ- tification means that several hits from our database were found ated with the Plant Genomic DNA Kit (Tiangen Biotech Co., China). to have the same smallest genetic distance to the query sequence; Polymerase chain reaction (PCR) amplification of the ITS2 region incorrect identification means that the hit based on the smallest was carried out in a Peltier Thermal Cycler PTC0200 (BioRad Lab genetic distance is not from the expected species. Inc., USA) using approximately 30 ng of genomic DNA as a tem- plate in a 25-␮l reaction mixture (1× PCR buffer without MgCl2, 3. Results 2.0 mM MgCl2, 0.2 mM of each dNTP, 0.1 ␮M of each primer (Syn- thesized by Sangon Co., China)), and 1.0 U of Taq DNA Polymerase 3.1. Measurement of DNA divergence for ITS2 (Biocolor BioScience & Technology Co., China). We designed universal primers and reaction conditions of the ITS2 region (Online Significant variations in DNA sequences between species and Resource 4). The PCR products were run on a 1.0% agarose gel in smaller variations within species are prerequisites for an ideal 118 T. Gao et al. / Journal of Ethnopharmacology 130 (2010) 116–121

Table 2 Analyses of inter-speciﬁc divergence between congeneric species and intra-speciﬁc variations in ITS2 sequences in Fabaceae.

Measurement Dataset 1 Dataset 2

All inter-specific distance 0.1340 ± 0.1266 0.0860 ± 0.0568 Theta prime 0.1126 ± 0.1028 0.1029 ± 0.0894 The minimum inter-specific distance 0.0444 ± 0.0520 0.0526 ± 0.0783 All intra-specific distance 0.0117 ± 0.0237 0.0170 ± 0.0216 Theta 0.0105 ± 0.0217 0.0148 ± 0.0259 Coalescent depth 0.0154 ± 0.0308 0.0180 ± 0.0304

DNA marker to use in identifying various species. Therefore, we first characterized the intra- and inter-specific variations in ITS2 sequences. The lengths of the ITS2 sequences used for the analyses Fig. 1. Relative distribution of inter-specific divergences between congeneric ranged from 205 to 249 bps and 185 to 301 bps, in dataset 1 and species and intra-specific variations for ITS2 sequences. The colored bars in each dataset 2, respectively. In dataset 1, the inter-specific percentages box represent inter-specific (above) and intra-specific (below) genetic distances; (a) dataset 1, (b) dataset 2. of nucleotide differences ranged from 0% (Caragana rosea vs. Cara- gana sinica, Astragalus membranaceus vs. Astragalus mongholicus) to 42.3% (Phaseolus angularis vs. Phaseolus vulgaris), with an average of 13.4%. The percentage differences between individuals of 3.3. Evaluation of the discriminatory power of ITS2 sequences for the same species among the 184 Fabaceae sequences ranged from sister species 0% (96 sequences) to 10.5% (Pueraria thomsonii), with an average of 1.2%. In dataset 2, the inter-specific percentages of nucleotide The software TaxonGap was used to allow the straightforward differences ranged from 0% (256 sequences) to 63.0% (Sophora evaluation of the discriminatory power of individual genes in alopecuroides var. alopecuroides vs. Sophora secundiflora), with an the identification scheme of dataset 1 (Fig. 2). For the sequences average of 8.6%. The percent differences between individuals of the collected in this study, over 90.0% of the sequences had an inter- same species among the 1507 Fabaceae sequences ranged from 0% specific diversity that was larger than that of the intra-specific (239 sequences) to 14.4% (Trifolium cherler), with an average of 1.7%. diversity, so relatively clear species boundaries were observed for We then used six metrics to characterize inter- vs. intra-specific ITS2 sequences. This data indicates that ITS2 could be used to variations (Meier et al., 2008; Meyer and Paulay, 2005; Chen et identify the medicinal Fabaceae species described in the Chinese al., 2010). As shown in Table 2, dataset 1 showed significant lev- Pharmacopoeia. Yet, there were exceptions: 6.4% of the species (s- els of inter-specific divergence within ITS2 sequences. Relatively separability values = 0, see dark grey bar) had identical sequences lower levels of intra-specific divergence were found with calcula- with their sister-species for Astragalus membranaceus vs. Astragalus tions for all three metrics. An even larger difference was observed in mongholicus, Caragana rosea vs. Caragana sinica and Pueraria lobata dataset 2. vs. Pueraria thomsonii (Fig. 2). The inter-specific percentage differences among the Fabaceae species were greater than the intra-specific variations in dataset 3.4. Testing the efficacy of ITS2 for authentication 1 and dataset 2. Therefore, the ITS2 region of the Fabaceae species, with lower levels of genetic divergence within species than ITS2 sequences generated in this study were used to build ref- between species, may be used as a genomic marker for the identi- erence sequence libraries, and then the sequences obtained from fication of these species. samples with certain identity classifications were used to search the database. Finally, we were able to determine the species iden- 3.2. Assessment of the intra- vs. inter-specific differences of ITS2 tities of the query sequences using BLAST1 and the nearest genetic sequences distance method. ITS2 performed well when using either BLAST1 or distance dis- To perform a preliminary examination of inter- and intra- crimination method. In dataset 1, ITS2 obtained 96.2% and 94.6% specific variation, we investigated the distribution of genetic identification success rates at the species level for BLAST1 and distance in classes of 0.006 distance units. Only a slight overlap in distance discrimination method, respectively, with no ambiguous inter/intra-specific variation of ITS2 was found in our study (Fig. 1). identification at the genus level for ITS2 alone. In dataset 2, the suc- The inter-specific distance equaled to zero for only 1.2% and 0.5% cess rates of ITS2 exceeded 80.0% at the species level and reached of the samples in dataset 1 and dataset 2, respectively. Also, most up to 100% at the genus level, using the BLAST1 and the nearest of the Fabaceae species in our study were found to have a unique genetic distance method (Table 4). sequence in the ITS2. This will provide a useful way to authenticate Table 5 shows that the variations among six large genera different ITS2 species. were discrepant and could only be analyzed individually. ITS2 Wilcoxon two-sample tests also showed that the mean of worked well in Swartzia, in which 77 sequences representing 60 the inter-specific divergences was significantly higher than that Swartzia species were tested, and ITS2 readily identified 97.4% of the of intra-specific variations in both datasets (Table 3, P < 0.001). sequences at the species level. In contrast, only 37.2% of sequences Therefore, ITS2 possessed intra- and inter-specific variation from Caragana that could be successfully identified by ITS2. As for gaps. the other four genera, the rate of successful identification with the

Table 3 Wilcoxon two-sample tests for distribution of intra- vs. inter-speciﬁc divergences.

Data sources No. of inter-speciﬁc distances No. of intra-speciﬁc distances Wilcoxon W P value

Dataset1 171 86 15747.5 2.591 × 10−30 Dataset2 35505 850 2343280.5 0.000 T. Gao et al. / Journal of Ethnopharmacology 130 (2010) 116–121 119

Table 4 Comparison of authentication efﬁciency for ITS2 using different methods.

Data sources Methods of identification No. of samples Correct identification (%) Incorrect identification (%) Ambiguous identification (%)

Dataset 1 BLAST1 184 96.2(100)a 0(0) 3.8(0) Distance 184 94.6(100) 0(0) 5.4(0)

Dataset 2 BLAST1 1507 83.4(100) 0(0) 16.6(0) Distance 1507 80.6(100) 0(0) 19.4(0)

a The percentage of samples correctly identiﬁed at the genus level for ITS2 sequences are shown in brackets.

ITS2 was around 60.0–80.0% at the species level, which is relatively powerful for taxonomic classiﬁcation.

4. Discussion

A rapid and accurate method to authenticate species from the large family Fabaceae is very important to ensure the safe usage of drugs made from these medicinal herbs. To our knowledge, this is the first time that the ITS2 region was used to identify plant materials from Fabaceae with such a large sample size. ITS2 was found to be a sufficiently variable DNA region among Fabaceae species as determination by genetic divergences, and ITS2 also demon- strated a higher capability of successful discrimination. ITS2 can be a powerful marker for taxonomy studies, identifying species and solving taxonomic problems. Moreover, significant success had been achieved using ITS2 to differentiate species from many Fabaceae genera. For example, satisfactory results were obtained when identifying Swartzia species; of the 60 Swartzia species used for this analysis, a successful identification was achieved for all but two species (Swartzia grandifolia and Swartzia longicarpa). A similar success rate was obtained in studies using Astragalus. In particular, the taxonomic status of Astragalus mongholicus and Astragalus membranaceus are not clear, and a consensus has not been reached on whether Astragalus mongholicus (Astragalus membranaceus var. mongholicus) is a variety of Astragalus membranaceus (Dong et al., 2003). The ITS2 sequence of Astragalus membranaceus is 100% identical to that of Astragalus mongholicus, so our results indicate that Astragalus mongholicus is a variety of Astragalus membranaceus (Hsiao, 1964), which is consistent with the results of Dong et al. (2003). Even in the genus Caragana, in which the species were poorly classified, ITS2 was still able to distinguish between some confusing species. Adaptation to arid and cold environments and the possible existence of hybrid species leads to considerable morphological diversity in Caragana species, resulting in the inability to define boundaries between the species using morphological characteristics. There are many controversies regarding the classical taxonomic classifications in Caragana, such as the species Caragana microphylla, Caragana davazamci and Caragana korshinskii (Hou et al., 2008). In the traditional taxonomists’ opinion, Caragana microphylla and Caragana davazamci are closely related genetically, while convergent evolution caused Caragana davazamci and Caragana korshinskii to have similar morphological characteristics; however, this classification has led to considerable taxonomic debate. The ITS2 sequence of Caragana davazamci is 100% identical to that of one sample of Caragana microphylla and is different from that of a Caragana korshinskii sample by only one base. Therefore, the molecular results support the view of the traditional taxonomists and are consistent with a previous study using sequences of trnL-F and ITS (Hou et al., 2006). However, it should be noted that the taxonomic assignment of sequences from GenBank might not be accurate. For example, some morphologic characteristics of Caragana rosea and Caragana Fig. 2. The heterogeneity and separability for individual taxa of ITS2 based on 184 sinica are similar to each other; Caragana rosea has pinnate leaf representatives of the family Fabaceae by TaxonGap (Naser et al., 2007; Slabbinck that is almost the same as that of Caragana sinica, which makes the et al., 2008). classification of these two species controversial. Furthermore, culti- 120 T. Gao et al. / Journal of Ethnopharmacology 130 (2010) 116–121

Table 5 The authentication efﬁciency of ITS2 for six large genera of Fabaceae using different methods.

Genera Method No. of sequences No. of species Success identiﬁcation (%)

Trifolium BLAST1 267 226 62.6 Distance 267 226 59.6

Phaseolus BLAST1 106 64 79.3 Distance 106 64 77.4

Caragana BLAST1 43 28 37.2 Distance 43 28 37.2

Daviesia BLAST1 46 44 82.6 Distance 46 44 78.3

Acacia BLAST1 34 23 82.4 Distance 34 23 67.6

Swartzia BLAST1 77 60 97.4 Distance 77 60 97.4

vars, wild varieties, and horticultural species also cause problems. Acknowledgements Arachis hypogaea has exactly the same sequence as its tetraploid wild congeneric species, Arachis monticola. If we take these factors We would like to thank XC Jia for his valuable comments. into account, the power of ITS2 in species discrimination might be This work is supported by the International Cooperation Program estimated to be lower for some genera (for example, Trifolium and of Science and Technology (No. 2007DFA30990) and the Special Phaseolus). Founding for Ministry of Health (No. 200802043) granted to S.L.C. Still, ITS2 cannot solve all the species determination problems in We also thank the general support by grants from the Hong Kong Fabaceae. For example, in Caragana, Caragana tibetica and Caragana Research Grant Council (HKU 7526/06M) to C.L. ordosica (Ma et al., 2003; Hou et al., 2006, 2008; Wojciechowski et al., 1993; Zhang, 2004) were found to have identical ITS2 sequences, Appendix A. Supplementary data but they were already reported to be two different species based on their ITS sequences (Hou et al., 2008). Thus, other DNA marker(s) Supplementary data associated with this article can be found, in might be valuable when investigating certain genus and broad plant the online version, at doi:10.1016/j.jep.2010.04.026. taxa such that complete species identification could be achieved in Fabaceae. Because there are multiple copies of ITS2 sequences in the plant References genomes, it is questionable whether the sequence obtained through PCR would be stable and representative. However, we think the CBOL Plant Working Group, 2009. A DNA barcode for land plants. 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