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Profile of secondary metabolites and genetic stability analysis in new lines of Echinacea purpurea (L.) Moench micropropagated via somatic embryogenesis
Industrial Crops & Products 142 (2019) 111851
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Profile of secondary metabolites and genetic stability analysis in new lines of Echinacea purpurea (L.) Moench micropropagated via somatic embryogenesis
T
Justyna Lema-Rumińskaa, Dariusz Kulusa, , Alicja Tymoszuka, Jorge M.T.B. Varejãob, Kiril Bahcevandzievb ⁎
a
UTP University of Science and Technology, Faculty of Agriculture and Biotechnology, Laboratory of Ornamental Plants and Vegetable Crops, 6 Bernardyńska Str., PL-85029, Poland b Polytechnic Institute of Coimbra, Agricultural College, IIA – Institute of Applied Research, CERNAS - Research Centre for Natural Resources, Environment, and Society, 3045-601 Coimbra, Portugal
ARTICLE INFO
ABSTRACT
Keywords: HPLC ISSR Molecular markers Purple coneflower RAPD Selection
Echinacea purpurea (L.) Moench is a plant species important for the phytopharmaceutical industry and in horticulture. Currently, there is lack of standardized plant material with an increased content of secondary metabolites in purple coneflower. The following research meets the expectations of the industry, as new selected lines of purple coneflower were micropropagated by somatic embryogenesis. The plant lines were analyzed both in terms of the content of main secondary metabolites by High Performance Liquid Chromatography (HPLC), as well as the genetic stability within the line and the genetic distance between lines using Random Amplified Polymorphic DNA (RAPD) and Inter-Simple Sequence Repeat (ISSR) genetic markers. Significant differences were found in the relative percentage composition of individual phenolic acids in the tested plant material. Among six selected lines of Echinacea purpurea, three were characterized by a higher content of cichoric acid in relation to the other lines studied. A higher mean polymorphism rate (> 90%) was found with the RAPD technique, with a total of 1427 scorable bands produced (142.7 products per one primer). Unlike the RAPD analysis, ISSRs detected mostly monomorphic loci (63.4%), followed by polymorphic ones (36.6%), while there were no specific loci present. Cluster analysis of both marker systems showed that the tested genotypes were grouped according to their respective lines.
1. Introduction Purple coneflower (Echinacea purpurea (L.) Moench) of the Asteraceae family, is a plant species of high ornamental and medical value, and for these reasons, appreciated all over the world. The ornamental traits of this species are associated with a long flowering period and big inflorescences composed of two flower types: purple ray florets and purple-brown disc florets (Perry et al., 2001). Echinacea purpurea is also an important source of raw material for the phytopharmaceutical industry. Medical use of the plant is associated with immunomodulatory and antitumor effects, since the extract of purple coneflower activates human macrophages, stimulates the production of cytokines and tumor necrosis factor α (TNF-α), which are protecting the host against viruses and cancer (Burger et al., 1997; Goel et al., 2002; Cohrssen, 2006; Tsai et al., 2012; Seckin et al., 2018). An important group of metabolites found in E. purpurea, with comprehensive pharmacological activity, are phenolic acids (Arceusz et al.,
⁎
2013). Especially cichoric acid was reported to have immunostimulatory properties, such as the promotion of phagocyte activity and exertion of antiviral activity, e.g. HIV-1 integrase and viral replication inhibition (Lin et al., 1999; Barrett, 2003). Moreover, polysaccharides derived from Echinacea purpurea suppressed the development of Candida albicans and Listeria monocytogenes in mice (Roesler et al., 1991; Schepetkin and Quinn, 2006). Echinacea products can also provide beneficial physiological effects and protection against chronic disease, and can be used in some popular nutraceuticals, similarly as: ginseng, green tea, omega-3 lipids, and other supplements (Nasri et al., 2014). Purple coneflower can be reproduced both generatively and vegetatively. Unfortunately, propagation of Echinacea purpurea by seeds is low-effective and plants produced by this method often do not flower in the second year of cultivation (Harbage, 2001; Abbasi et al., 2007). For these reasons, vegetative propagation is recommended. However, traditional methods of reproduction by clump division or root cuttings are
Corresponding author. E-mail address: [email protected] (D. Kulus).
https://doi.org/10.1016/j.indcrop.2019.111851 Received 12 July 2019; Received in revised form 6 September 2019; Accepted 7 October 2019 0926-6690/ © 2019 Elsevier B.V. All rights reserved.
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limited by a small number of cuttings produced. Moreover, plant material grown in vivo is exposed to many unfavorable factors throughout the period of cultivation, i.e. pests and diseases, microbial contamination, drought and others. They can deteriorate not only the yield size but also the content of active components and, thus, the value of the medicinal herb material. On the other hand, traditional breeding via field- or greenhouse-performed selection of superior plants that can be later propagated vegetatively by clump division to obtain the clone is time-consuming; lasting for several years. Therefore, the implementation of tissue-culture-based techniques for commercial production and breeding of purple coneflower is justified. In vitro culture systems, cultivated in optimized media and under sterile controlled conditions, are a good alternative to in vivo production of Echinacea (Harbage, 2001). In a laboratory it is possible to obtain, within a short time, millions of progeny plants with the same genotype and phenotype (Singh, 2018). The in vitro produced (micropropagated) plant material is usually uniform, of high quality, and it is free of any microorganisms. Moreover, in vitro production can be set regardless of the weather conditions or growing season, contributing to an increased yield size (Kulus, 2015). Somatic embryogenesis (SE) is considered to be the most efficient micropropagation technique. It is a vegetative propagation method, in which potentially each somatic cell can produce a new plant if proper conditions are provided (Joshi and Kumar, 2013). This technology has a huge potential for plant micropropagation at the industrial level. Moreover, it can be a source of somaclonal variation, i.e. variation induced under in vitro conditions, if a callus phase is involved (Larkin and Scowcroft, 1981), which can be helpful in breeding and producing lines with improved traits. One should keep in mind, though, not all plant material has equal SE potential. Therefore, the selection of lines with the highest SE efficiency is necessary. According to Tahmasebi et al. (2019), better understanding of the phenolics biosynthetic pathway is needed for improvement in metabolic engineering strategies for overproduction of bioactive metabolites in Echinacea. Chen et al. (2016) reported an increase in the biomass and content of valuable substances in clones of colchicine-induced tetraploid purple coneflower plants. Therefore, studies on the selection of lines during in vitro stage for the quantity of secondary metabolites in E. purpurea are justified. The available literature lacks research on the quality improvement of lines or cultivars of E. purpurea as a result of breeding and selection toward increasing the content of desirable secondary metabolites for the phytopharmaceutical industry. Therefore, the strategy proposed here is based on increasing the content of major phenolic acids throughout the selection of purple coneflower lines multiplied via somatic embryogenesis. Explants from identified lines, superior in secondary metabolite production, could be further micropropagated for large-scale production of true-to-type plantlets that will be planted ex vitro or continuously propagated in vitro and harvested for secondary metabolite production. Biochemical and molecular markers are commonly applied in plant studies (Mukherjee et al., 2013; Lema-Rumińska et al., 2018; Tribhuvan et al., 2019). They can be used both to confirm the stability and to detect variation in plants, even in a closely related group (LemaRumińska et al., 2004). Among the most popular genetic markers, one can find: Random Amplified Polymorphic DNA (RAPD), Inter-Simple Sequence Repeat (ISSR), Amplified Fragment Length Polymorphism (AFLP), retrotransposon sequences or RNA sequencing, Single Nucleotide Polymorphism (SNP), and Simple Sequence Repeats (SSR). Over the years, they were applied to characterize interspecific relationships, evaluate germplasm diversity, identify potential sources of unique genetic material, analyze somaclonal variation, and in DNA-fingerprinting of numerous plant species (Hiremath et al., 2012; Bhagyawant, 2016; Kulus, 2018; Vitamvas et al., 2019). They can be also utilized in the studies with Echinacea (Kapteyn et al., 2002; Chuang et al., 2009; Olarte et al., 2013; Tahmasebi et al., 2019).
The aim of this study was to analyze new lines of Echinacea purpurea, micropropagated via indirect somatic embryogenesis, on the biochemical and molecular levels toward the selection of genotypes with a high ability to produce secondary metabolites. The relative percentage composition of main phenolic acids was determined by High Performance Liquid Chromatography (HPLC) technique. Genetic stability (within line) and genetic diversity (between lines) of the produced plants were studied with RAPD and ISSR molecular markers. 2. Material and methods 2.1. Plant material Plant material was obtained by sowing 200 disinfected seeds (TORSEED®, Toruń, Poland) on the basal MS (Murashige and Skoog, 1962) medium without growth regulators. The medium was modified with the increased by half content of calcium and iron (660 mg L−1 CaCl2·2H2O, 41.7 mg L−1 FeSO4·7H2O, and 55.8 mg L−1 −1 Na2EDTA·2H2O), supplemented with 30 g L sucrose, and solidified with 0.8% (w/v) Plant Propagation LAB-AGAR™ (BIOCORP, Warsaw, Poland) having added all the nutrients, prior to autoclaving at 121 °C for 20 min. The medium pH was set at the level of 5.8. Explants derived from seedlings (halves of leaves 0.5 × 1 cm) were cultured on the modified basal MS medium supplemented with cytokinin, 6-benzylaminopurine (BAP), in combination with auxin α-naphtaleneacetic acid (NAA) or 3- indoleacetic acid (IAA) for 14 days in the dark. Six lines were preliminarily selected from 60 seedlings based on the efficiency of indirect SE, i.e. the highest mean number of somatic embryos per one inoculated explant. The plantlets derived from different seedlings were considered as separate lines. To stimulate shoot conversion, the produced somatic embryos were cultured on the MS medium without auxin, but with cytokinin kinetin (KIN) (data not shown; SE method filed as a patent to the Polish Patent Office; no. P.431456). All plant growth regulators were provided by Sigma-Aldrich (St. Louis, MO, US). In the final subculture, the lines: L1, L4, L14, L47, L52, and L54 were propagated on the MS medium with 0.5 mg L-1 KIN by the lateral shoots method to obtain the appropriate amount of material for genetic and chromatographic research. In vitro cultures were maintained in the growth room at the temperature of 24 ± 2 °C, exposed to a 16/8 -h (day/night) photoperiod, using Philips TLD 36 W/54 fluorescent lamps emitting cool daylight, at approximately 35 μmol m-2·s-1 of photosynthetic photon flux density (PPFD). 2.2. HPLC analysis The biochemical analysis of the new selected lines of Echinacea purpurea (L1, L4, L14, L47, L52, L54) was performed using HPLC. Plant material derived from in vitro culture was pre-dried at room temperature, and then desiccated in a laboratory drier to obtain a constant dry matter (at 105 °C for 180 min). Next, the plant material was minced in a mortar. One gram of dried sample (about 15–20 microcuttings) was placed in a glass tube and bath sonicated (Retsch UR1, Germany), in cold water with ice (at 10 °C), with 10 mL of 70% (v/v) methanol water solution for 30 min. Methanol used in the extraction was provided by Lab-Scan (Gliwice, Poland), acetonitrile for HPLC was produced by J.T. Baker (Deventer, Netherland), and phosphoric acid added to the HPLC mobile phase was provided by Merck (Darmstad, Germany). Water was distilled and purified by mixing in a bed exchange resin system. Each sample was placed in nitrogen to avoid oxidation. The samples were frozen at −25 °C to minimalize the degradation of the extracted compounds. Before analysis, the extracts were filtered through a 0.45 μm membrane nanofilter (Millipore, Cork, Ireland) to prevent suspended solids injection. The analysis of phenolic acids was expressed in relative percentage of total phenolic acids. Its identification was made based on the retention time in similar experimental conditions, and the recorded UV spectra were compared with those described in the literature. The 2
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HPLC analysis was run using a Macherey-Nagel (Düren, Germany) column (Nucleosil EC 125/4.6 100-6, C18), Jasco pumps and Jasco UV970 detector. The data was acquired through a Hercule-lite DAQ and analyzed with Jasco-Borwin software. The mobile phases were (A) water with 0.1% (v/v) phosphoric acid and (B) acetonitrile. The linear gradient started with the flow rate of 1.5 mL·min−1 with B concentration of 10%, which was increased to 22% at 11 min. The UV detector monitored the eluent at the wavelength of 330 nm (Pellati et al., 2013). Compounds were identified based on both retention times and UV spectra, and recorded at wavelength range between 200–370 nm. The spectra were compared with those published in the literature (Perry et al., 2001; Nollet and Toldra, 2012; Boulet et al., 2017; Dong et al., 2018). Results were statistically elaborated according to the analysis of variance at significance level P < 0.05 with the F test, in two replicates (Statistica 13.1, StatSoft, Cracow, Poland). For the data expressed as percentage, the Freeman-Tukey transformation was used. Tables with results provide real, untransformed numerical data, with alphabet indicating the homogeneous groups.
20 min, then at 110 V for 90 min (Biometra P25, Jena, Germany), and detected by staining with 20 μl BrEt at a concentration 10 mg mL−1 for 300 mL of gel. Gel images were recorded using a GelDoc XR + Gel Photodocumentation System (Bio-Rad Laboratories, Hercules CA, USA) UV transilluminator with Image Lab 4.1 software. Molecular weights of the fragments were estimated using a 100–5000 bp DNA molecular marker (DNA GeneRuler Express DNA Ladder, Fermentas, MA USA). The bands were then analyzed using the program GelAnalyzer 2010 (Copyright 2010 by Istvan Lazar and Dr. Istvan Lazar). Only the bands which were clear and unambiguous were recorded. The banding patterns were recorded as 0–1 binary matrices, where “1” indicates the presence and “0” – the absence of a given fragment. Five plants randomly selected from each line were used in the statistical analysis. For every primer tested the total number of bands, monomorphic, polymorphic (present in the electrophoretic profile of more than one individual) and specific/unique (present in the electrophoretic profile of a single individual) loci was estimated. Cluster analysis was performed using the Unweighted Pair Group Method (UPGMA) applying Statistica 13.1 software with hierarchical, agglomerative grouping (StatSoft, Cracow, Poland).
2.3. Genetic analysis
3. Results and discussion
The genetic stability of the plantlets was assessed using RAPD and ISSR markers. Twenty specimens obtained from each of the six lines (120 in total) were included. Total genomic DNA was isolated from 100 mg fresh tissues from in vitro cultures using a Genomic Mini AX Plant Kit (A&A Biotechnology, Gdynia, Poland). Isolated DNA was stored in TE buffer (10 mM TRIS, 1 mM EDTA, pH = 8) at 4 °C. The concentration and purity of DNA was monitored with the Quantus™ Fluorometer (Promega, Medison, USA). Fifteen primers (10 for RAPD, 5 for ISSR, Genomed, Warsaw, Poland, Table 1) were used for the PCR reaction. Each 25 μL reaction volume contained 2 mM MgCl2 in Reaction Buffer; 1 mM dNTP Solution Mix; 1 μM single primer; 0.05 U·μL−1 Taq DNA polymerase, 0.8 ng·μL−1 template DNA, and sterile, double-distilled water to volume (2 × PCR Master Mix Plus kit, A&A Biotechnology, Gdynia, Poland). The amplification of DNA was performed in a BioRad C1000 Touch thermal cycler (with heated cover) (Bio-Rad Laboratories, Hercules CA, USA) programmed as follows: 45 cycles of 1 min at 94 °C for denaturation, 1 min at 36/53 °C for annealing (for RAPD/ISSR, respectively), and 2 min at 72 °C for DNA extension. The last cycle was followed by a final extension step of 4 min at 72 °C. The amplified DNA fragments were separated on 1.5% (w/v) agarose gel DN- and RNase-free (Blirt, Gdańsk, Poland), in a TBE buffer (90 mM TRIS, 90 mM boric acid, 2 mM EDTA, pH = 8.0) first at 90 V for
3.1. HPLC analysis One of the strategies to increase the content of antioxidants (e.g. total phenolics) in Echinacea purpurea was the treatment with ornithine decarboxylase inhibitor or polyamine inhibitor and phenol biosynthesis stimulator (carboxymethyl chitin glucan, CCHG), as reported by Hudec et al. (2007). Another effective strategy is the selection of lines characterized by both: high SE potential and high content of valuable phenolic acids in plant tissue, as shown by this research. Significant differences were found in the relative percentage composition of individual phenolic acids among the tested lines in Echinacea purpurea (Table 2; Fig. 1). Echinacoside was present at the highest concentration in line 52 (L52), while line 4 (L4) was characterized by its lowest content. Among the six selected lines of Echinacea purpurea, three yielded significantly higher cichoric acid content. It reached the highest share in lines L54, L52 and L47, while lines L4 and L14 were characterized by its lower content. Caftaric acid was present at a high level in most lines. The exception was line L47, which was characterized by lower content of this compound. A similar tendency was found with the chlorogenic acid content; lines L47 and L52 also had a lower share of this constituent in the dry matter. The strategy of selecting the unique genotypes (from variability pre-existed in seedlings) and their in vitro propagation seems to be promising. Optimization of in vitro conditions for increased secondary metabolite production of desirable phenolic acids in plant tissues may be important for the application of this method on an industrial-scale. In the studies with Echinacea angustifolia DC., Lucchesini et al. (2009) found that the content of valuable substances in in vitro conditions may be higher than in vivo, which may result from adding growth regulators into the medium; in this case cytokinin. Concerning caffeic acid derivatives (CADs), in vitro produced shoots had a higher content of caftaric, chlorogenic and cichoric acids (Lucchesini et al., 2009). Phenolic substances, such as cichoric acid or caftaric acid, belong to the most efficient antioxidants (Oniszczuk et al., 2019). Moreover, as reported by Presser (2000), cichoric acid stimulates viral phagocytosis and bacterial cell destruction. Therefore, Echinacea lines with an increased content of these compounds are desired by the pharmaceutical industry. As for the other unidentified compounds (unc), their level was different in individual lines (Table 2; Fig. 1). The highest level of unc 1 was found in line L4, while the lowest in L54. The majority of lines, except L54, had a high concentration of unc 2. The unc 3 compound occurred at the lowest concentration in line L52, while a significantly higher content of this constituent was found in the L14 line. The
Table 1 Primers used in the molecular (RAPD and ISSR) analysis. No. RAPD 1. 2. 3. 4 5. 6. 7. 8. 9. 10. ISSR 1. 2. 3. 4. 5.
Primer
Sequence 5’→ 3’
Reference
R-A R-B R-C R-D R-E R-F R-G R-H R-I R-J
GGG AAT TCG G GAC CGC TTG T GGA CTG GAG T GCT GCC TCA GG TAC CCA GGA GCG CAA TCG CCG T GGT GAC GCA G CCC AGT CAC T TGG CGT CCT T AGC GTG TCT G
Lema-Rumińska et al. (2004)
I-A I-B I-C I-D I-E
GAG GGT GGA GGA TCT C GAGA GAGA GAGA GAGA GACA GACA GACA GACA GAGAGAGAGAGAGAGAGA T GT GAGA GAGA GAGA GAGA
Palai and Rout (2011)
Shibata et al. (1998) Wolff (1996) Martín and González-Benito (2005) Chattarjee et al. (2006)
Mukherjee et al. (2013) Miao et al. (2007)
RAPD - Random Amplified Polymorphic DNA. ISSR - Inter-Simple Sequence Repeat. 3
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Table 2 Main phenolic acid composition expressed as relative percentage of dry weight of biomass in six lines of Echinacea purpurea multiplied via somatic embryogenesis. Phenolic acid [%] Unc 1 Unc 2 Caftaric acid Chlorogenic acid Cynarin Echinacoside Unc 3 Unc 4 Unc 5 Cichoric acid
Reference
Boulet et al. (2017) Perry et al. (2001) Nollet and Toldra (2012) Dong et al. (2018)
L1
L4
L14
L47
L52
L54
2.17ab ± 1.80 3.24ab ± 1.92 30.20a ± 3.84 8.88a ± 0.97 1.52a ± 0.13 0.24b ± 0.01 0.14b ± 0.02 0.30b ± 0.01 ND 53.31b ± 0.24
4.00a ± 0.09 4.45a ± 0.07 29.35a ± 0.35 8.06b ± 0.15 1.63a ± 0.02 0.03c ± 0.00 0.19b ± 0.01 0.09c ± 0.06 0.41a ± 0.49 51.79c ± 0.03
2.61ab ± 0.44 4.24a ± 0.37 27.80a ± 3.15 11.69a ± 0.92 1.06a ± 0.65 0.32b ± 0.22 0.62a ± 0.15 0.51abc ± 0.19 ND 51.14c ± 3.17
2.72ab ± 0.39 3.18a ± 0.54 27.55b ± 0.37 7.67b ± 0.30 1.70a ± 0.14 0.23b ± 0.18 0.28b ± 0.28 0.14c ± 0.02 0.56a ± 0.06 55.98a ± 1.79
1.83ab ± 1.06 2.01a ± 1.50 30.10a ± 2.84 7.62b ± 0.34 1.86a ± 0.10 0.56a ± 0.06 0.00c ± 0.00 0.44a ± 0.01 0.52a ± 0.01 55.07a ± 0.29
0.47c ± 0.27 0.53b ± 0.02 28.69a ± 2.48 9.74a ± 0.97 1.68a ± 0.37 0.31b ± 0.00 0.22b ± 0.05 0.37a ± 0.03 0.52a ± 0.09 57.46a ± 4.21
Mean ± standard deviation (SD) within the same row having different letters are significantly different (P < 0.05). ND - Not detected. For unidentified compounds (Unc 1- Unc 5), molar extinction coefficient of the closest compound was used.
compound unc 4 was detected at a higher concentration in L52 and L54, while unc 5 occurred at a similar concentration in all four lines, in which it could be found. There was also no significant difference in the content of cynarin in the dry weight of plants in the individual lines tested.
amplicons generated by a single primer (1007 bands in total). Primer I–A generated the greatest number of bands (271), while primer I–E; the lowest (158). Unlike the RAPD analysis, ISSRs detected mostly monomorphic loci (63.4%), followed by polymorphic ones (36.6%), while there were no specific loci present. Cluster analysis of the RAPD marker showed that the tested specimens were grouped according to their respective lines (Fig. 2a). The highest genetic distance was found for individuals belonging to the L1 line; 2 genotypes formed a cluster separate from the other lines (genetic distance: 5.4). The lowest genetic distance was found between genotypes within the lines L47 and L52 (2.7), which together with L4 and L54 formed the largest sub-cluster in relation to line L14. As for the ISSR data, a much simpler dendrogram was obtained (Fig. 2b). According to this analysis, lines L52 and L54 were the most distinctive, but not different from each other (genetic distance: 2.0). Genotypes representing lines L1 and L4 were the least varied (genetic distance 1.0), while lines L14 and L47 showed a medium difference with a maximal genetic distance 1.4. In the present study on the new Echinacea lines, a higher level of polymorphism was detected using the RAPD marker system compared with ISSR. Therefore, RAPD markers turned out to be more useful for molecular analysis in this species. However, in the studies on Larix
3.2. Genetic stability evaluation Diverse results were reported after applying the two marker types: RAPDs and ISSRs. A higher mean polymorphism rate (> 90%) was found with the RAPD technique (Table 3). A total of 1427 scorable bands were detected there (a mean of 142.7 products from one primer). Among the primers used, primers R–H and R–I generated the greatest number of amplicons (over 200 each). On the other hand, primer R–C produced only 69 bands. Monomorphic loci were the least numerous (1.7%), followed by specific (8.3%) and polymorphic ones (90%). Eight primers amplified at least one polymorphic or unique locus (100% polymorphism). The lowest polymorphic rate (90%) was detected with the primer R–B. As for the ISSR analysis, the polymorphism rate reached from 0% (primer I–B) to 66.7% (primer I–D), with a mean of 35.06% (Table 3). The ISSR primers were more productive with a mean of 201.4
Fig. 1. Chromatograms (HPLC) of phenolic acids in extracts obtained from lines L1 (a), L4 (b), L14 (c), L47 (d), L52 (e) and L54 (f) of E. purpurea. The compound identification and order is: unc 1 (2.6 min retention time); unc 2 (3.7 min); caftaric acid (4.8 min); chlorogenic acid (7.0 min); cynarin (7.8 min); echinacoside (9.2 min); unc 3 (10.2 min); unc 4 (11.2 min); unc 5 (12.6 min); cichoric acid (14.0 min). 4
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Table 3 Characteristic of products obtained from the molecular analysis of five selected plantlets (from each of the six lines) after applying RAPD and ISSR markers. Primer
RAPD R-A R-B R-C R-D R-E R-F R-G R-H R-I R-J Total Share [%] ISSR I-A I-B I-C I-D I-E Total Share [%]
No. of products
loci
Polymorphism [%]
monomorphic
polymorphic
specific
total
112 122 69 146 111 179 143 206 216 123 1427 –
0 1 0 0 0 0 0 0 1 0 2 1.7
10 9 6 11 7 16 10 13 14 12 108 90
4 0 1 1 0 0 2 2 0 0 10 8.3
14 10 7 12 7 16 12 15 15 12 120 –
100 90 100 100 100 100 100 100 93.3 100 – –
271 210 185 183 158 1007 –
7 7 5 3 4 26 63.4
3 0 2 6 4 15 36.6
0 0 0 0 0 0 0.0
10 7 7 9 8 41 –
30.0 0.0 28.6 66.7 50.0 – –
RAPD - Random Amplified Polymorphic DNA. ISSR - Inter-Simple Sequence Repeat.
gmelinii (Ruprecht) Kuzeneva, Zhang et al. (2013) reported a slightly higher efficiency of ISSR markers compared with RAPDs. As a result of analyzing 15 genotypes with the RAPD markers, polymorphism was detected at 97.35%, while with the ISSR markers at 98.83%. Research using RAPD and ISSR marker systems was also performed in polymorphism analyzes in Hordeum vulgare L. (Fernández et al., 2002). As for this species, the ISSR markers were more useful, as a higher number of primers gave the possibility of distinguishing all the genotypes tested, whereas with RAPD – only one primer. Also Qian et al. (2001), in the analysis of variability in Oryza granulata Nees et Arn. ex Watt reported a lower share of polymorphisms (30.65%) using RAPD markers and 46.02% with the ISSR marker system. In the present study, such a low level of polymorphisms was obtained for the ISSRs, while the RAPDs detected a polymorphism rate of over 90%. Lema-Rumińska et al. (2004) obtained full identification of radiomutant cultivars in chrysanthemum (Chrysanthemum × grandiflorum /Ramat./Kitam.) by using the RAPD marker system, which indicates a high polymorphism of this marker type. Also Kulus et al. (2019) confirmed a higher effectiveness of RAPDs in detecting variation in chrysanthemum, compared with ISSRs. Therefore, it is possible that for plant species belonging to
the Asteraceae family, which includes coneflower and chrysanthemum, the RAPD markers are characterized by a high level of polymorphisms. The results obtained in this study highlight the utility of somatic embryogenesis, especially in the multiplication of true-to-type clones for the industry. There are several reports on variation in somatic-embryo-derived plants, especially with a prolonged culture proliferation time and callus phase (Dey et al., 2015; Bradaï et al., 2016). The present research, however, demonstrated that indirect SE can be used not only to provide progeny plant material with a high ability to produce important secondary metabolites, as reported previously in Crocus sativus L. (Firoozi et al., 2018), but also maintain its genetic profile, since individuals were grouped according to their respective lines, regardless of the molecular marker used. 4. Conclusions New purple coneflower lines were obtained by a two-aspect selection: 1) choice of lines with the highest SE efficiency, and 2) selection for the high content of valuable phenolic acids in plant tissue. The plant lines were analyzed in terms of the content of main secondary
Fig. 2. Dendrograms based on the estimation of genetic distance coefficient and UPGMA clustering presenting the relationships between genotypes from different lines of E. purpurea, revealed by the RAPD (a) and ISSR (b) analysis. The scale shows a real genetic distance value. 5
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metabolites by HPLC, as well as the genetic stability within the line and the genetic distance between lines using ISSR and RAPD genetic markers. Significant differences were found in the relative percentage composition of individual phenolic acids in the lines tested. Among six selected lines of Echinacea purpurea, three (L47, L52 and L54) yielded significantly higher cichoric acid content. Two of them (L52 and L54) were characterized by higher caftaric acid synthesis ability. Moreover, line L54 produced more chlorogenic acid compared with L47 and L52, while the highest echinacoside content was found in L54. The research has shown that the obtained lines can provide an enhanced production of secondary metabolites in purple coneflower. Those findings are especially important for the pharmaceutical industry. Further application of SE in the multiplication of selected lines of E. purpurea can contribute to an enhancement of antioxidant content, without the need of performing laborious and time-consuming breeding programs. A higher mean polymorphism rate (> 90%) was found with the RAPD technique. Unlike the RAPD analysis, ISSRs detected mostly monomorphic loci (63.4%), followed by polymorphic ones (36.6%). Nonetheless, cluster analysis of both genetic markers showed that the tested genotypes were grouped according to their respective lines. This is beneficial meaning that the plants micropropagated by SE are genetically stable.
Chen, R., Jiang, W., Li, Q., Li, X., Chen, X., Yang, Y., Wu, H., 2016. Comparison of seven colchicine-induced tetraploid clones with their original diploid clones in purple coneflower (Echinacea purpurea L.). Euphytica 207, 387–399. https://doi.org/10. 1007/s10681-015-1556-3. Chuang, S.J., Chen, C.L., Chen, J.J., Chou, W.Y., Sung, J.M., 2009. Detection of somaclonal variation in micro-propagated Echinacea purpurea using AFLP marker. Sci. Hortic. 120 (1), 121–126. https://doi.org/10.1016/j.scienta.2008.09.020. Cohrssen, M.D., 2006. Echinacea’s immune effects - possibilities and pitfalls - two cases. Explore 2 (3), 232–233. https://doi.org/10.1016/j.explore.2006.02.003. Dey, T., Saha, S., Ghosh, P.D., 2015. Somaclonal variation among somatic embryo derived plants - Evaluation of agronomically important somaclones and detection of genetic changes by RAPD in Cymbopogon winterianus. S. Afr. J. Bot. 96, 112–121. https:// doi.org/10.1016/j.sajb.2014.10.010. 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Declaration of Competing Interest The authors declare they have no conflict of interest. Acknowledgments The research has been performed through the Polish-Portugal scientific cooperation between the UTP University of Science and Technology in Bydgoszcz, Poland and the Agricultural College, CERNAS, Polytechnic Institute of Coimbra, Portugal. The authors wish to acknowledge Magdalena Hajzer, Robert Nelke, Tajah Lewter and Dominika Rymarz for their technical assistance in conducting the experiments. The in vitro regeneration protocol via somatic embryogenesis of Echinacea purpurea and the analysis of genetic stability were developed in the Laboratory of Ornamental Plants and Vegetable Crops at UTP in Bydgoszcz, Poland. Biochemical analysis of secondary metabolites in plants regenerated via somatic embryogenesis were done using High Performance Liquid Chromatography at the Agricultural College, Polytechnic Institute of Coimbra, Portugal. References Abbasi, B.H., Saxena, P.K., Murch, S.J., Liu, C.-Z., 2007. Echinacea biotechnology: challenges and opportunities. In Vitro Cell Dev. Biol.—Plant 43, 481–492. https://doi. org/10.1007/s11627-007-9057-2. Arceusz, A., Wesolowski, M., Konieczynski, P., 2013. Methods for extraction and determination of phenolic acids in medicinal plants: a review. Nat. Prod. Commun. 8 (12), 1821–1829. Barrett, B., 2003. Medicinal properties of Echinacea: a critical review. Phytomedicine 10, 66–86. https://doi.org/10.1078/094471103321648692. Bhagyawant, S.S., 2016. RAPD-SCAR markers: an interface tool for authentication of traits. J. Biosci. Med. 4, 1–9. https://doi.org/10.4236/jbm.2016.41001. Boulet, J.C., Ducasse, M.A., Cheynier, V., 2017. Ultraviolet spectroscopy study of phenolic substances and other major compounds in red wines: relationship between astringency and the concentration of phenolic substances: UV spectroscopy of red wine components. Aust. J. Grape Wine Res. 23 (2), 193. https://doi.org/10.1111/ajgw. 12265. Bradaï, F., Pliego-Alfaro, F., Sánchez-Romero, C., 2016. Somaclonal variation in olive (Olea europaea L.) plants regenerated via somatic embryogenesis: influence of genotype and culture age on phenotypic stability. Sci. Hortic. 213, 208–2015. https:// doi.org/10.1016/j.scienta.2016.10.031. Burger, A., Torres, A.R., Warren, R.P., Caldwell, V.D., Hughes, B.G., 1997. Echinaceainduced cytokine production by human macrophages. Int. J. Immunopharmacol. 19 (7), 371–379. Chattarjee, J., Mandal, A.K.A., Ranade, S.A., Teixeira da Silva, J.A., Datta, S.K., 2006. Molecular systematic in Chrysanthemum × grandiflorum (Ramat.) Kitamura. Sci. Hortic. 110, 373–378. https://doi.org/10.1016/j.scienta.2006.06.004.
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Profile of secondary metabolites and genetic stability analysis in new lines of Echinacea purpurea (L.) Moench micropropagated via somatic embryogenesis
T
Justyna Lema-Rumińskaa, Dariusz Kulusa, , Alicja Tymoszuka, Jorge M.T.B. Varejãob, Kiril Bahcevandzievb ⁎
a
UTP University of Science and Technology, Faculty of Agriculture and Biotechnology, Laboratory of Ornamental Plants and Vegetable Crops, 6 Bernardyńska Str., PL-85029, Poland b Polytechnic Institute of Coimbra, Agricultural College, IIA – Institute of Applied Research, CERNAS - Research Centre for Natural Resources, Environment, and Society, 3045-601 Coimbra, Portugal
ARTICLE INFO
ABSTRACT
Keywords: HPLC ISSR Molecular markers Purple coneflower RAPD Selection
Echinacea purpurea (L.) Moench is a plant species important for the phytopharmaceutical industry and in horticulture. Currently, there is lack of standardized plant material with an increased content of secondary metabolites in purple coneflower. The following research meets the expectations of the industry, as new selected lines of purple coneflower were micropropagated by somatic embryogenesis. The plant lines were analyzed both in terms of the content of main secondary metabolites by High Performance Liquid Chromatography (HPLC), as well as the genetic stability within the line and the genetic distance between lines using Random Amplified Polymorphic DNA (RAPD) and Inter-Simple Sequence Repeat (ISSR) genetic markers. Significant differences were found in the relative percentage composition of individual phenolic acids in the tested plant material. Among six selected lines of Echinacea purpurea, three were characterized by a higher content of cichoric acid in relation to the other lines studied. A higher mean polymorphism rate (> 90%) was found with the RAPD technique, with a total of 1427 scorable bands produced (142.7 products per one primer). Unlike the RAPD analysis, ISSRs detected mostly monomorphic loci (63.4%), followed by polymorphic ones (36.6%), while there were no specific loci present. Cluster analysis of both marker systems showed that the tested genotypes were grouped according to their respective lines.
1. Introduction Purple coneflower (Echinacea purpurea (L.) Moench) of the Asteraceae family, is a plant species of high ornamental and medical value, and for these reasons, appreciated all over the world. The ornamental traits of this species are associated with a long flowering period and big inflorescences composed of two flower types: purple ray florets and purple-brown disc florets (Perry et al., 2001). Echinacea purpurea is also an important source of raw material for the phytopharmaceutical industry. Medical use of the plant is associated with immunomodulatory and antitumor effects, since the extract of purple coneflower activates human macrophages, stimulates the production of cytokines and tumor necrosis factor α (TNF-α), which are protecting the host against viruses and cancer (Burger et al., 1997; Goel et al., 2002; Cohrssen, 2006; Tsai et al., 2012; Seckin et al., 2018). An important group of metabolites found in E. purpurea, with comprehensive pharmacological activity, are phenolic acids (Arceusz et al.,
⁎
2013). Especially cichoric acid was reported to have immunostimulatory properties, such as the promotion of phagocyte activity and exertion of antiviral activity, e.g. HIV-1 integrase and viral replication inhibition (Lin et al., 1999; Barrett, 2003). Moreover, polysaccharides derived from Echinacea purpurea suppressed the development of Candida albicans and Listeria monocytogenes in mice (Roesler et al., 1991; Schepetkin and Quinn, 2006). Echinacea products can also provide beneficial physiological effects and protection against chronic disease, and can be used in some popular nutraceuticals, similarly as: ginseng, green tea, omega-3 lipids, and other supplements (Nasri et al., 2014). Purple coneflower can be reproduced both generatively and vegetatively. Unfortunately, propagation of Echinacea purpurea by seeds is low-effective and plants produced by this method often do not flower in the second year of cultivation (Harbage, 2001; Abbasi et al., 2007). For these reasons, vegetative propagation is recommended. However, traditional methods of reproduction by clump division or root cuttings are
Corresponding author. E-mail address: [email protected] (D. Kulus).
https://doi.org/10.1016/j.indcrop.2019.111851 Received 12 July 2019; Received in revised form 6 September 2019; Accepted 7 October 2019 0926-6690/ © 2019 Elsevier B.V. All rights reserved.
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limited by a small number of cuttings produced. Moreover, plant material grown in vivo is exposed to many unfavorable factors throughout the period of cultivation, i.e. pests and diseases, microbial contamination, drought and others. They can deteriorate not only the yield size but also the content of active components and, thus, the value of the medicinal herb material. On the other hand, traditional breeding via field- or greenhouse-performed selection of superior plants that can be later propagated vegetatively by clump division to obtain the clone is time-consuming; lasting for several years. Therefore, the implementation of tissue-culture-based techniques for commercial production and breeding of purple coneflower is justified. In vitro culture systems, cultivated in optimized media and under sterile controlled conditions, are a good alternative to in vivo production of Echinacea (Harbage, 2001). In a laboratory it is possible to obtain, within a short time, millions of progeny plants with the same genotype and phenotype (Singh, 2018). The in vitro produced (micropropagated) plant material is usually uniform, of high quality, and it is free of any microorganisms. Moreover, in vitro production can be set regardless of the weather conditions or growing season, contributing to an increased yield size (Kulus, 2015). Somatic embryogenesis (SE) is considered to be the most efficient micropropagation technique. It is a vegetative propagation method, in which potentially each somatic cell can produce a new plant if proper conditions are provided (Joshi and Kumar, 2013). This technology has a huge potential for plant micropropagation at the industrial level. Moreover, it can be a source of somaclonal variation, i.e. variation induced under in vitro conditions, if a callus phase is involved (Larkin and Scowcroft, 1981), which can be helpful in breeding and producing lines with improved traits. One should keep in mind, though, not all plant material has equal SE potential. Therefore, the selection of lines with the highest SE efficiency is necessary. According to Tahmasebi et al. (2019), better understanding of the phenolics biosynthetic pathway is needed for improvement in metabolic engineering strategies for overproduction of bioactive metabolites in Echinacea. Chen et al. (2016) reported an increase in the biomass and content of valuable substances in clones of colchicine-induced tetraploid purple coneflower plants. Therefore, studies on the selection of lines during in vitro stage for the quantity of secondary metabolites in E. purpurea are justified. The available literature lacks research on the quality improvement of lines or cultivars of E. purpurea as a result of breeding and selection toward increasing the content of desirable secondary metabolites for the phytopharmaceutical industry. Therefore, the strategy proposed here is based on increasing the content of major phenolic acids throughout the selection of purple coneflower lines multiplied via somatic embryogenesis. Explants from identified lines, superior in secondary metabolite production, could be further micropropagated for large-scale production of true-to-type plantlets that will be planted ex vitro or continuously propagated in vitro and harvested for secondary metabolite production. Biochemical and molecular markers are commonly applied in plant studies (Mukherjee et al., 2013; Lema-Rumińska et al., 2018; Tribhuvan et al., 2019). They can be used both to confirm the stability and to detect variation in plants, even in a closely related group (LemaRumińska et al., 2004). Among the most popular genetic markers, one can find: Random Amplified Polymorphic DNA (RAPD), Inter-Simple Sequence Repeat (ISSR), Amplified Fragment Length Polymorphism (AFLP), retrotransposon sequences or RNA sequencing, Single Nucleotide Polymorphism (SNP), and Simple Sequence Repeats (SSR). Over the years, they were applied to characterize interspecific relationships, evaluate germplasm diversity, identify potential sources of unique genetic material, analyze somaclonal variation, and in DNA-fingerprinting of numerous plant species (Hiremath et al., 2012; Bhagyawant, 2016; Kulus, 2018; Vitamvas et al., 2019). They can be also utilized in the studies with Echinacea (Kapteyn et al., 2002; Chuang et al., 2009; Olarte et al., 2013; Tahmasebi et al., 2019).
The aim of this study was to analyze new lines of Echinacea purpurea, micropropagated via indirect somatic embryogenesis, on the biochemical and molecular levels toward the selection of genotypes with a high ability to produce secondary metabolites. The relative percentage composition of main phenolic acids was determined by High Performance Liquid Chromatography (HPLC) technique. Genetic stability (within line) and genetic diversity (between lines) of the produced plants were studied with RAPD and ISSR molecular markers. 2. Material and methods 2.1. Plant material Plant material was obtained by sowing 200 disinfected seeds (TORSEED®, Toruń, Poland) on the basal MS (Murashige and Skoog, 1962) medium without growth regulators. The medium was modified with the increased by half content of calcium and iron (660 mg L−1 CaCl2·2H2O, 41.7 mg L−1 FeSO4·7H2O, and 55.8 mg L−1 −1 Na2EDTA·2H2O), supplemented with 30 g L sucrose, and solidified with 0.8% (w/v) Plant Propagation LAB-AGAR™ (BIOCORP, Warsaw, Poland) having added all the nutrients, prior to autoclaving at 121 °C for 20 min. The medium pH was set at the level of 5.8. Explants derived from seedlings (halves of leaves 0.5 × 1 cm) were cultured on the modified basal MS medium supplemented with cytokinin, 6-benzylaminopurine (BAP), in combination with auxin α-naphtaleneacetic acid (NAA) or 3- indoleacetic acid (IAA) for 14 days in the dark. Six lines were preliminarily selected from 60 seedlings based on the efficiency of indirect SE, i.e. the highest mean number of somatic embryos per one inoculated explant. The plantlets derived from different seedlings were considered as separate lines. To stimulate shoot conversion, the produced somatic embryos were cultured on the MS medium without auxin, but with cytokinin kinetin (KIN) (data not shown; SE method filed as a patent to the Polish Patent Office; no. P.431456). All plant growth regulators were provided by Sigma-Aldrich (St. Louis, MO, US). In the final subculture, the lines: L1, L4, L14, L47, L52, and L54 were propagated on the MS medium with 0.5 mg L-1 KIN by the lateral shoots method to obtain the appropriate amount of material for genetic and chromatographic research. In vitro cultures were maintained in the growth room at the temperature of 24 ± 2 °C, exposed to a 16/8 -h (day/night) photoperiod, using Philips TLD 36 W/54 fluorescent lamps emitting cool daylight, at approximately 35 μmol m-2·s-1 of photosynthetic photon flux density (PPFD). 2.2. HPLC analysis The biochemical analysis of the new selected lines of Echinacea purpurea (L1, L4, L14, L47, L52, L54) was performed using HPLC. Plant material derived from in vitro culture was pre-dried at room temperature, and then desiccated in a laboratory drier to obtain a constant dry matter (at 105 °C for 180 min). Next, the plant material was minced in a mortar. One gram of dried sample (about 15–20 microcuttings) was placed in a glass tube and bath sonicated (Retsch UR1, Germany), in cold water with ice (at 10 °C), with 10 mL of 70% (v/v) methanol water solution for 30 min. Methanol used in the extraction was provided by Lab-Scan (Gliwice, Poland), acetonitrile for HPLC was produced by J.T. Baker (Deventer, Netherland), and phosphoric acid added to the HPLC mobile phase was provided by Merck (Darmstad, Germany). Water was distilled and purified by mixing in a bed exchange resin system. Each sample was placed in nitrogen to avoid oxidation. The samples were frozen at −25 °C to minimalize the degradation of the extracted compounds. Before analysis, the extracts were filtered through a 0.45 μm membrane nanofilter (Millipore, Cork, Ireland) to prevent suspended solids injection. The analysis of phenolic acids was expressed in relative percentage of total phenolic acids. Its identification was made based on the retention time in similar experimental conditions, and the recorded UV spectra were compared with those described in the literature. The 2
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HPLC analysis was run using a Macherey-Nagel (Düren, Germany) column (Nucleosil EC 125/4.6 100-6, C18), Jasco pumps and Jasco UV970 detector. The data was acquired through a Hercule-lite DAQ and analyzed with Jasco-Borwin software. The mobile phases were (A) water with 0.1% (v/v) phosphoric acid and (B) acetonitrile. The linear gradient started with the flow rate of 1.5 mL·min−1 with B concentration of 10%, which was increased to 22% at 11 min. The UV detector monitored the eluent at the wavelength of 330 nm (Pellati et al., 2013). Compounds were identified based on both retention times and UV spectra, and recorded at wavelength range between 200–370 nm. The spectra were compared with those published in the literature (Perry et al., 2001; Nollet and Toldra, 2012; Boulet et al., 2017; Dong et al., 2018). Results were statistically elaborated according to the analysis of variance at significance level P < 0.05 with the F test, in two replicates (Statistica 13.1, StatSoft, Cracow, Poland). For the data expressed as percentage, the Freeman-Tukey transformation was used. Tables with results provide real, untransformed numerical data, with alphabet indicating the homogeneous groups.
20 min, then at 110 V for 90 min (Biometra P25, Jena, Germany), and detected by staining with 20 μl BrEt at a concentration 10 mg mL−1 for 300 mL of gel. Gel images were recorded using a GelDoc XR + Gel Photodocumentation System (Bio-Rad Laboratories, Hercules CA, USA) UV transilluminator with Image Lab 4.1 software. Molecular weights of the fragments were estimated using a 100–5000 bp DNA molecular marker (DNA GeneRuler Express DNA Ladder, Fermentas, MA USA). The bands were then analyzed using the program GelAnalyzer 2010 (Copyright 2010 by Istvan Lazar and Dr. Istvan Lazar). Only the bands which were clear and unambiguous were recorded. The banding patterns were recorded as 0–1 binary matrices, where “1” indicates the presence and “0” – the absence of a given fragment. Five plants randomly selected from each line were used in the statistical analysis. For every primer tested the total number of bands, monomorphic, polymorphic (present in the electrophoretic profile of more than one individual) and specific/unique (present in the electrophoretic profile of a single individual) loci was estimated. Cluster analysis was performed using the Unweighted Pair Group Method (UPGMA) applying Statistica 13.1 software with hierarchical, agglomerative grouping (StatSoft, Cracow, Poland).
2.3. Genetic analysis
3. Results and discussion
The genetic stability of the plantlets was assessed using RAPD and ISSR markers. Twenty specimens obtained from each of the six lines (120 in total) were included. Total genomic DNA was isolated from 100 mg fresh tissues from in vitro cultures using a Genomic Mini AX Plant Kit (A&A Biotechnology, Gdynia, Poland). Isolated DNA was stored in TE buffer (10 mM TRIS, 1 mM EDTA, pH = 8) at 4 °C. The concentration and purity of DNA was monitored with the Quantus™ Fluorometer (Promega, Medison, USA). Fifteen primers (10 for RAPD, 5 for ISSR, Genomed, Warsaw, Poland, Table 1) were used for the PCR reaction. Each 25 μL reaction volume contained 2 mM MgCl2 in Reaction Buffer; 1 mM dNTP Solution Mix; 1 μM single primer; 0.05 U·μL−1 Taq DNA polymerase, 0.8 ng·μL−1 template DNA, and sterile, double-distilled water to volume (2 × PCR Master Mix Plus kit, A&A Biotechnology, Gdynia, Poland). The amplification of DNA was performed in a BioRad C1000 Touch thermal cycler (with heated cover) (Bio-Rad Laboratories, Hercules CA, USA) programmed as follows: 45 cycles of 1 min at 94 °C for denaturation, 1 min at 36/53 °C for annealing (for RAPD/ISSR, respectively), and 2 min at 72 °C for DNA extension. The last cycle was followed by a final extension step of 4 min at 72 °C. The amplified DNA fragments were separated on 1.5% (w/v) agarose gel DN- and RNase-free (Blirt, Gdańsk, Poland), in a TBE buffer (90 mM TRIS, 90 mM boric acid, 2 mM EDTA, pH = 8.0) first at 90 V for
3.1. HPLC analysis One of the strategies to increase the content of antioxidants (e.g. total phenolics) in Echinacea purpurea was the treatment with ornithine decarboxylase inhibitor or polyamine inhibitor and phenol biosynthesis stimulator (carboxymethyl chitin glucan, CCHG), as reported by Hudec et al. (2007). Another effective strategy is the selection of lines characterized by both: high SE potential and high content of valuable phenolic acids in plant tissue, as shown by this research. Significant differences were found in the relative percentage composition of individual phenolic acids among the tested lines in Echinacea purpurea (Table 2; Fig. 1). Echinacoside was present at the highest concentration in line 52 (L52), while line 4 (L4) was characterized by its lowest content. Among the six selected lines of Echinacea purpurea, three yielded significantly higher cichoric acid content. It reached the highest share in lines L54, L52 and L47, while lines L4 and L14 were characterized by its lower content. Caftaric acid was present at a high level in most lines. The exception was line L47, which was characterized by lower content of this compound. A similar tendency was found with the chlorogenic acid content; lines L47 and L52 also had a lower share of this constituent in the dry matter. The strategy of selecting the unique genotypes (from variability pre-existed in seedlings) and their in vitro propagation seems to be promising. Optimization of in vitro conditions for increased secondary metabolite production of desirable phenolic acids in plant tissues may be important for the application of this method on an industrial-scale. In the studies with Echinacea angustifolia DC., Lucchesini et al. (2009) found that the content of valuable substances in in vitro conditions may be higher than in vivo, which may result from adding growth regulators into the medium; in this case cytokinin. Concerning caffeic acid derivatives (CADs), in vitro produced shoots had a higher content of caftaric, chlorogenic and cichoric acids (Lucchesini et al., 2009). Phenolic substances, such as cichoric acid or caftaric acid, belong to the most efficient antioxidants (Oniszczuk et al., 2019). Moreover, as reported by Presser (2000), cichoric acid stimulates viral phagocytosis and bacterial cell destruction. Therefore, Echinacea lines with an increased content of these compounds are desired by the pharmaceutical industry. As for the other unidentified compounds (unc), their level was different in individual lines (Table 2; Fig. 1). The highest level of unc 1 was found in line L4, while the lowest in L54. The majority of lines, except L54, had a high concentration of unc 2. The unc 3 compound occurred at the lowest concentration in line L52, while a significantly higher content of this constituent was found in the L14 line. The
Table 1 Primers used in the molecular (RAPD and ISSR) analysis. No. RAPD 1. 2. 3. 4 5. 6. 7. 8. 9. 10. ISSR 1. 2. 3. 4. 5.
Primer
Sequence 5’→ 3’
Reference
R-A R-B R-C R-D R-E R-F R-G R-H R-I R-J
GGG AAT TCG G GAC CGC TTG T GGA CTG GAG T GCT GCC TCA GG TAC CCA GGA GCG CAA TCG CCG T GGT GAC GCA G CCC AGT CAC T TGG CGT CCT T AGC GTG TCT G
Lema-Rumińska et al. (2004)
I-A I-B I-C I-D I-E
GAG GGT GGA GGA TCT C GAGA GAGA GAGA GAGA GACA GACA GACA GACA GAGAGAGAGAGAGAGAGA T GT GAGA GAGA GAGA GAGA
Palai and Rout (2011)
Shibata et al. (1998) Wolff (1996) Martín and González-Benito (2005) Chattarjee et al. (2006)
Mukherjee et al. (2013) Miao et al. (2007)
RAPD - Random Amplified Polymorphic DNA. ISSR - Inter-Simple Sequence Repeat. 3
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Table 2 Main phenolic acid composition expressed as relative percentage of dry weight of biomass in six lines of Echinacea purpurea multiplied via somatic embryogenesis. Phenolic acid [%] Unc 1 Unc 2 Caftaric acid Chlorogenic acid Cynarin Echinacoside Unc 3 Unc 4 Unc 5 Cichoric acid
Reference
Boulet et al. (2017) Perry et al. (2001) Nollet and Toldra (2012) Dong et al. (2018)
L1
L4
L14
L47
L52
L54
2.17ab ± 1.80 3.24ab ± 1.92 30.20a ± 3.84 8.88a ± 0.97 1.52a ± 0.13 0.24b ± 0.01 0.14b ± 0.02 0.30b ± 0.01 ND 53.31b ± 0.24
4.00a ± 0.09 4.45a ± 0.07 29.35a ± 0.35 8.06b ± 0.15 1.63a ± 0.02 0.03c ± 0.00 0.19b ± 0.01 0.09c ± 0.06 0.41a ± 0.49 51.79c ± 0.03
2.61ab ± 0.44 4.24a ± 0.37 27.80a ± 3.15 11.69a ± 0.92 1.06a ± 0.65 0.32b ± 0.22 0.62a ± 0.15 0.51abc ± 0.19 ND 51.14c ± 3.17
2.72ab ± 0.39 3.18a ± 0.54 27.55b ± 0.37 7.67b ± 0.30 1.70a ± 0.14 0.23b ± 0.18 0.28b ± 0.28 0.14c ± 0.02 0.56a ± 0.06 55.98a ± 1.79
1.83ab ± 1.06 2.01a ± 1.50 30.10a ± 2.84 7.62b ± 0.34 1.86a ± 0.10 0.56a ± 0.06 0.00c ± 0.00 0.44a ± 0.01 0.52a ± 0.01 55.07a ± 0.29
0.47c ± 0.27 0.53b ± 0.02 28.69a ± 2.48 9.74a ± 0.97 1.68a ± 0.37 0.31b ± 0.00 0.22b ± 0.05 0.37a ± 0.03 0.52a ± 0.09 57.46a ± 4.21
Mean ± standard deviation (SD) within the same row having different letters are significantly different (P < 0.05). ND - Not detected. For unidentified compounds (Unc 1- Unc 5), molar extinction coefficient of the closest compound was used.
compound unc 4 was detected at a higher concentration in L52 and L54, while unc 5 occurred at a similar concentration in all four lines, in which it could be found. There was also no significant difference in the content of cynarin in the dry weight of plants in the individual lines tested.
amplicons generated by a single primer (1007 bands in total). Primer I–A generated the greatest number of bands (271), while primer I–E; the lowest (158). Unlike the RAPD analysis, ISSRs detected mostly monomorphic loci (63.4%), followed by polymorphic ones (36.6%), while there were no specific loci present. Cluster analysis of the RAPD marker showed that the tested specimens were grouped according to their respective lines (Fig. 2a). The highest genetic distance was found for individuals belonging to the L1 line; 2 genotypes formed a cluster separate from the other lines (genetic distance: 5.4). The lowest genetic distance was found between genotypes within the lines L47 and L52 (2.7), which together with L4 and L54 formed the largest sub-cluster in relation to line L14. As for the ISSR data, a much simpler dendrogram was obtained (Fig. 2b). According to this analysis, lines L52 and L54 were the most distinctive, but not different from each other (genetic distance: 2.0). Genotypes representing lines L1 and L4 were the least varied (genetic distance 1.0), while lines L14 and L47 showed a medium difference with a maximal genetic distance 1.4. In the present study on the new Echinacea lines, a higher level of polymorphism was detected using the RAPD marker system compared with ISSR. Therefore, RAPD markers turned out to be more useful for molecular analysis in this species. However, in the studies on Larix
3.2. Genetic stability evaluation Diverse results were reported after applying the two marker types: RAPDs and ISSRs. A higher mean polymorphism rate (> 90%) was found with the RAPD technique (Table 3). A total of 1427 scorable bands were detected there (a mean of 142.7 products from one primer). Among the primers used, primers R–H and R–I generated the greatest number of amplicons (over 200 each). On the other hand, primer R–C produced only 69 bands. Monomorphic loci were the least numerous (1.7%), followed by specific (8.3%) and polymorphic ones (90%). Eight primers amplified at least one polymorphic or unique locus (100% polymorphism). The lowest polymorphic rate (90%) was detected with the primer R–B. As for the ISSR analysis, the polymorphism rate reached from 0% (primer I–B) to 66.7% (primer I–D), with a mean of 35.06% (Table 3). The ISSR primers were more productive with a mean of 201.4
Fig. 1. Chromatograms (HPLC) of phenolic acids in extracts obtained from lines L1 (a), L4 (b), L14 (c), L47 (d), L52 (e) and L54 (f) of E. purpurea. The compound identification and order is: unc 1 (2.6 min retention time); unc 2 (3.7 min); caftaric acid (4.8 min); chlorogenic acid (7.0 min); cynarin (7.8 min); echinacoside (9.2 min); unc 3 (10.2 min); unc 4 (11.2 min); unc 5 (12.6 min); cichoric acid (14.0 min). 4
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Table 3 Characteristic of products obtained from the molecular analysis of five selected plantlets (from each of the six lines) after applying RAPD and ISSR markers. Primer
RAPD R-A R-B R-C R-D R-E R-F R-G R-H R-I R-J Total Share [%] ISSR I-A I-B I-C I-D I-E Total Share [%]
No. of products
loci
Polymorphism [%]
monomorphic
polymorphic
specific
total
112 122 69 146 111 179 143 206 216 123 1427 –
0 1 0 0 0 0 0 0 1 0 2 1.7
10 9 6 11 7 16 10 13 14 12 108 90
4 0 1 1 0 0 2 2 0 0 10 8.3
14 10 7 12 7 16 12 15 15 12 120 –
100 90 100 100 100 100 100 100 93.3 100 – –
271 210 185 183 158 1007 –
7 7 5 3 4 26 63.4
3 0 2 6 4 15 36.6
0 0 0 0 0 0 0.0
10 7 7 9 8 41 –
30.0 0.0 28.6 66.7 50.0 – –
RAPD - Random Amplified Polymorphic DNA. ISSR - Inter-Simple Sequence Repeat.
gmelinii (Ruprecht) Kuzeneva, Zhang et al. (2013) reported a slightly higher efficiency of ISSR markers compared with RAPDs. As a result of analyzing 15 genotypes with the RAPD markers, polymorphism was detected at 97.35%, while with the ISSR markers at 98.83%. Research using RAPD and ISSR marker systems was also performed in polymorphism analyzes in Hordeum vulgare L. (Fernández et al., 2002). As for this species, the ISSR markers were more useful, as a higher number of primers gave the possibility of distinguishing all the genotypes tested, whereas with RAPD – only one primer. Also Qian et al. (2001), in the analysis of variability in Oryza granulata Nees et Arn. ex Watt reported a lower share of polymorphisms (30.65%) using RAPD markers and 46.02% with the ISSR marker system. In the present study, such a low level of polymorphisms was obtained for the ISSRs, while the RAPDs detected a polymorphism rate of over 90%. Lema-Rumińska et al. (2004) obtained full identification of radiomutant cultivars in chrysanthemum (Chrysanthemum × grandiflorum /Ramat./Kitam.) by using the RAPD marker system, which indicates a high polymorphism of this marker type. Also Kulus et al. (2019) confirmed a higher effectiveness of RAPDs in detecting variation in chrysanthemum, compared with ISSRs. Therefore, it is possible that for plant species belonging to
the Asteraceae family, which includes coneflower and chrysanthemum, the RAPD markers are characterized by a high level of polymorphisms. The results obtained in this study highlight the utility of somatic embryogenesis, especially in the multiplication of true-to-type clones for the industry. There are several reports on variation in somatic-embryo-derived plants, especially with a prolonged culture proliferation time and callus phase (Dey et al., 2015; Bradaï et al., 2016). The present research, however, demonstrated that indirect SE can be used not only to provide progeny plant material with a high ability to produce important secondary metabolites, as reported previously in Crocus sativus L. (Firoozi et al., 2018), but also maintain its genetic profile, since individuals were grouped according to their respective lines, regardless of the molecular marker used. 4. Conclusions New purple coneflower lines were obtained by a two-aspect selection: 1) choice of lines with the highest SE efficiency, and 2) selection for the high content of valuable phenolic acids in plant tissue. The plant lines were analyzed in terms of the content of main secondary
Fig. 2. Dendrograms based on the estimation of genetic distance coefficient and UPGMA clustering presenting the relationships between genotypes from different lines of E. purpurea, revealed by the RAPD (a) and ISSR (b) analysis. The scale shows a real genetic distance value. 5
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metabolites by HPLC, as well as the genetic stability within the line and the genetic distance between lines using ISSR and RAPD genetic markers. Significant differences were found in the relative percentage composition of individual phenolic acids in the lines tested. Among six selected lines of Echinacea purpurea, three (L47, L52 and L54) yielded significantly higher cichoric acid content. Two of them (L52 and L54) were characterized by higher caftaric acid synthesis ability. Moreover, line L54 produced more chlorogenic acid compared with L47 and L52, while the highest echinacoside content was found in L54. The research has shown that the obtained lines can provide an enhanced production of secondary metabolites in purple coneflower. Those findings are especially important for the pharmaceutical industry. Further application of SE in the multiplication of selected lines of E. purpurea can contribute to an enhancement of antioxidant content, without the need of performing laborious and time-consuming breeding programs. A higher mean polymorphism rate (> 90%) was found with the RAPD technique. Unlike the RAPD analysis, ISSRs detected mostly monomorphic loci (63.4%), followed by polymorphic ones (36.6%). Nonetheless, cluster analysis of both genetic markers showed that the tested genotypes were grouped according to their respective lines. This is beneficial meaning that the plants micropropagated by SE are genetically stable.
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Declaration of Competing Interest The authors declare they have no conflict of interest. Acknowledgments The research has been performed through the Polish-Portugal scientific cooperation between the UTP University of Science and Technology in Bydgoszcz, Poland and the Agricultural College, CERNAS, Polytechnic Institute of Coimbra, Portugal. The authors wish to acknowledge Magdalena Hajzer, Robert Nelke, Tajah Lewter and Dominika Rymarz for their technical assistance in conducting the experiments. The in vitro regeneration protocol via somatic embryogenesis of Echinacea purpurea and the analysis of genetic stability were developed in the Laboratory of Ornamental Plants and Vegetable Crops at UTP in Bydgoszcz, Poland. Biochemical analysis of secondary metabolites in plants regenerated via somatic embryogenesis were done using High Performance Liquid Chromatography at the Agricultural College, Polytechnic Institute of Coimbra, Portugal. References Abbasi, B.H., Saxena, P.K., Murch, S.J., Liu, C.-Z., 2007. Echinacea biotechnology: challenges and opportunities. In Vitro Cell Dev. Biol.—Plant 43, 481–492. https://doi. org/10.1007/s11627-007-9057-2. Arceusz, A., Wesolowski, M., Konieczynski, P., 2013. Methods for extraction and determination of phenolic acids in medicinal plants: a review. Nat. Prod. Commun. 8 (12), 1821–1829. Barrett, B., 2003. Medicinal properties of Echinacea: a critical review. Phytomedicine 10, 66–86. https://doi.org/10.1078/094471103321648692. Bhagyawant, S.S., 2016. RAPD-SCAR markers: an interface tool for authentication of traits. J. Biosci. Med. 4, 1–9. https://doi.org/10.4236/jbm.2016.41001. Boulet, J.C., Ducasse, M.A., Cheynier, V., 2017. Ultraviolet spectroscopy study of phenolic substances and other major compounds in red wines: relationship between astringency and the concentration of phenolic substances: UV spectroscopy of red wine components. Aust. J. Grape Wine Res. 23 (2), 193. https://doi.org/10.1111/ajgw. 12265. Bradaï, F., Pliego-Alfaro, F., Sánchez-Romero, C., 2016. Somaclonal variation in olive (Olea europaea L.) plants regenerated via somatic embryogenesis: influence of genotype and culture age on phenotypic stability. Sci. Hortic. 213, 208–2015. https:// doi.org/10.1016/j.scienta.2016.10.031. Burger, A., Torres, A.R., Warren, R.P., Caldwell, V.D., Hughes, B.G., 1997. Echinaceainduced cytokine production by human macrophages. Int. J. Immunopharmacol. 19 (7), 371–379. Chattarjee, J., Mandal, A.K.A., Ranade, S.A., Teixeira da Silva, J.A., Datta, S.K., 2006. Molecular systematic in Chrysanthemum × grandiflorum (Ramat.) Kitamura. Sci. Hortic. 110, 373–378. https://doi.org/10.1016/j.scienta.2006.06.004.
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