Genetic and chemical profiling of Gymnema sylvestre accessions from central India: Its implication for quality control and therapeutic potential of plant
Ashutosh Kumar Verma1, Sunita Singh Dhawan2, Seema Singh3, Kumar Avinash Bharati4, Jyotsana5
1 Central Botanical Laboratory, Botanical Survey of India, AJC Bose Indian Botanic Garden, Howrah, West Bengal, India
2 Plant Biotechnology Division, CSIR - Central Institute of Medicinal and Aromatic Plants, Lucknow, India
3 Plant Genetics Unit, Department of Botany, University of Lucknow, Lucknow, Uttar Pradesh, India
4 Central National Herbarium, Botanical Survey of India, AJC Bose Indian Botanic Garden, Howrah, West Bengal, India
5 Analytical Chemistry Division, CSIR - Central Institute of Medicinal and Aromatic Plants, Lucknow, Uttar Pradesh, India
|Date of Submission||30-Mar-2016|
|Date of Acceptance||16-Jun-2016|
|Date of Web Publication||30-Sep-2016|
Ashutosh Kumar Verma
Central Botanical Laboratory, Botanical Survey of India, AJC Bose Indian Botanic Garden, Howrah, W.B.
Sunita Singh Dhawan
Plant Biotechnology Division, CSIR-Central Institute of Medicinal and Aromatic Plants, Lucknow, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Gymnema sylvestre, a vulnerable plant species, is mentioned in Indian Pharmacopeia as an antidiabetic drug Objective: Study of genetic and chemical diversity and its implications in accessions of G. sylvestre Materials and Methods: Fourteen accessions of G. sylvestre collected from Central India and assessment of their genetic and chemical diversity were carried out using ISSR (inter simple sequence repeat) and HPLC (high performance liquid chromatography) fingerprinting methods Results: Among the screened 40 ISSR primers, 15 were found polymorphic and collectively produced nine unique accession-specific bands. The maximum and minimum numbers of amplicones were noted for ISSR-15 and ISSR-11, respectively. The ISSR -11 and ISSR-13 revealed 100% polymorphism. HPLC chromatograms showed that accessions possess the secondary metabolites of mid-polarity with considerable variability. Unknown peaks with retention time 2.63, 3.41, 23.83, 24.50, and 44.67 were found universal type. Comparative hierarchical clustering analysis based on foresaid fingerprints indicates that both techniques have equal potential to discriminate accessions according to percentage gymnemic acid in their leaf tissue. Second approach was noted more efficiently for separation of accessions according to their agro-climatic/collection site Conclusion: Highly polymorphic ISSRs could be utilized as molecular probes for further selection of high gymnemic acid yielding accessions. Observed accession specific bands may be used as a descriptor for plant accessions protection and converted into sequence tagged sites markers. Identified five universal type peaks could be helpful in identification of G. sylvestre-based various herbal preparations.
Abbreviations used: HPLC: High Performance Liquid Chromatography, ISSR: Inter Simple Sequence Repeats, CTAB: Cetyl Trimethylammonium Bromide, DNTP: Deoxynucleotide Triphosphates
Keywords: Chemical fingerprinting, genetic fingerprinting, gymnemic acid, HPLC, ISSR, marker peaks
|How to cite this article:|
Verma AK, Dhawan SS, Singh S, Bharati KA, Jyotsana. Genetic and chemical profiling of Gymnema sylvestre accessions from central India: Its implication for quality control and therapeutic potential of plant. Phcog Mag 2016;12, Suppl S4:407-13
|How to cite this URL:|
Verma AK, Dhawan SS, Singh S, Bharati KA, Jyotsana. Genetic and chemical profiling of Gymnema sylvestre accessions from central India: Its implication for quality control and therapeutic potential of plant. Phcog Mag [serial online] 2016 [cited 2021 Jul 24];12, Suppl S4:407-13. Available from: http://www.phcog.com/text.asp?2016/12/47/407/191443
- Nine accession specific unique bands
- Five marker peaks for G. sylvestre.
- Suitability of genetic and chemical fingerprinting
| Introduction|| |
In industrial crops such as Gymnema sylvestre, the content of natural therapeutic molecules are more important than the yield of plant part containing metabolites. The extraction cost of metabolite influences the market value of metabolite-based drugs.  Hence, there is a need for identification and characterization of elite genotypes with quality and yield. In the present scenario, the assessment of genetic and chemical diversity is the most eminent approach for identification and characterization of chemotypes.
G. sylvestre R. Br., a vulnerable plant species (2n = 22, asclepiadaceae), grows wild in the tropical forest of India, Africa, Australia, and China. G. sylvestre R. Br. is mentioned as an official drug for the treatment of diabetes in Indian Pharmacopeia.  Because of the stimulatory effect of its phyto-constituents on pancreatic cells and potential to treat type-I
However, a sustainable cultivation at large scale is yet to be started, about 85% of the demand is primarily met with material collected from natural resources,  and thus enormous pressure mounting on wild stock and plant is now categorized under vulnerable. Therefore, the cultivation of this plant is advocated, for which elite accessions / improved genotypes with higher yield and more adaptive features are required. An effort was made for the assessment of genetic and chemical diversity and also their relative association. Thus, the generated knowledge could be utilized for quality control and therapeutic potential of plant by applying inter simple sequence repeat (ISSR) analysis and chemical profiling by HPLC fingerprinting based methods.
| Materials and Methods|| |
A total of 14 accessions of G. sylvestre were collected from different location of Central India [Table 1] and maintained in glass house condition in CSIR - Central Institute of Medicinal and Aromatic Plants, Lucknow, Uttar Pradesh, India. The accessions were taxonomically identified based on morphological characteristics. The young leaves of all the accessions were collected in triplicate sets for genetic diversity and chemical fingerprinting analysis.
|Table 1: Details of G. sylvestre accessions used in the ISSR and HPLC fingerprinting analysis.|
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Genetic diversity analysis
DNA extraction was performed by the methodology described by Khanuja et al.  Approximately 100 mg of fresh leaves of respective accessions were ground in liquid nitrogen and mixed with 3 mL of freshly prepared preheated extraction buffer containing 100 mM tris, 0.5 M EDTA (ethylene diamine tetra acetic acid), 20% C-TAB (cetyle trimethyl ammonium bromide), 5M NaCl, 1% PVP ( Polyvinyl pyrrolidone-40), and β-merceptoethanols. Equal amount of chlorophorm:isoamyl alcohol (24:1) was added and inverted to mix for few seconds, and then centrifuged at 13 000 rpm for 10 min. The supernatant was transferred to new tubes with 1.5 mL of NaCl with 0.6% of isopropanol, mixed properly and incubated at room temperature for 1 h, and then centrifuged for 10 min at 13 000 rpm. The supernatant was discarded from the tubes, and the pellet was left to dry and 400 μL of trisEDTA was added. The whole mixture was incubated at 42°C for 30 min. An equal amount at chlorophorm:isoamyl alcohol (24:1) was added and centrifuged for 10 min for 13 000 rpm and upper inorganic phase was transferred to new tube and double volume of absolute ethanol were mixed for precipitation, then further washed from 80% ethanol and pellet was dissolved in water.
PCR assay and electrophoresis
A total of 40 ISSR primers were screened and 15 primers (Integrated DNA Technologies, Bangalore , India) that produced clear and reproducible fragments were selected for genetic diversity analysis. DNA amplification was performed in thermal cycler (Veriti 96 Well; Programmable Thermal Controller), programmed for an initial period of 3 min at 94°C, followed by 40 cycles of 1 min at 94°C, 1 min at 45-58°C (for different primers), and 1 min at 72°C and 5 min at 72°C for the final extension and the samples were cooled to 4°C. The PCR amplification reaction was carried out in 25 μL volume. The single reaction contains 25 ng of template DNA, 0.2 unit of Taq DNA polymerase enzyme (Sigma Aldrich, India), 100 μM of each of dNTPs, 1.5 μM MgCl 2 10× buffer, and 8 pmol of respective ISSR primers. The amplified PCR products along with the 1 kb ladder (Merk Millipore, Darmstadt, Germany; λ DNA Eco RI HindIII digest marker) were separated electrophoretically in 2% agarose gels in 0.5 TAE buffer (10 mM Tris-HCl and 1 mM EDTA; pH 8.0) for 2 h (70 mV / 5 cm), and stained with ethidium bromide. DNA fragments were visualized and photographed under UV light and the amplification was performed twice to confirm its reproducibility.
Chemical diversity analysis
Chromatographic condition for chemical fingerprinting
One gram of powdered leaf sample of G. sylvestre accessions were soaked overnight in 10 mL of ethanol for extraction of chemical constituents. The presoaked samples were extracted with ethanol (3 × 10 mL) using ultrasonicator (Microclean-109, Oscar Ultrasonicator, Mumbai, India; 30.0 × 25.0 × 12.50 cm, 34 ± 3 kHz; PZT sand with type-xtransducer, 250 W). Pooled ethanolic extracts were combined, filtered with Whatman filter paper-40, and evaporated under vacuum. The dried product was dissolved in methanol and filtered in similar manner and volume of filtrate is maintained up to 10 mL. Obtained extract were utilized for chemical fingerprinting analysis on Waters equipment (pump 600E, auto-injector-717plus, column oven, detector-996 PDA), Empower software was used for data acquisition and computation and a reverse phase gel (Water Xselect column CHS, 250 × 4.6 μm) was used for analysis. All the samples prepared for HPLC analysis were filtered through a 0.45 μm syringe membrane filter (Type Millipore, Philadelphia, USA) and separation was carried out at 25°C. Solvents were first filtered with 0.45 μm, 50-mm diameter membrane filter (Millipore) and sonicated for 15 min in a Micro clean 109 bath (Oscar, India). Chromatography was carried out using mobile phase of acetonitrile and water, with flow rate of 1 mL/min during the whole analysis. Binary mobile phase consist of solvents acetonitrile and water was used for a gradient elution with an increasing polarity of 0-10 min acetonitrile was 5-15 v/v, at 35 min it is 75 v/v, after 50 min it is 85 v/v, and at 55 min it is 95 v/v, for the optimum separation. Photo diode array detector was set to measure spectra from 200 to 400 nm.
Quantification of gymnemic acid
The quantification of gymnemic acid, a method described previously by Manohar et al. (2009), was followed with minor modifications.  Five hundred milligrams of dried leaf sample was put into a 100-mL round bottom flask and 50 mL of extraction solvent was added (volume ratio of methanol to water is 1:1) with 10 mL of 11% potassium hydroxide solution. The mixture was refluxed for an hour. The 9 mL concentrated HCl was added and refluxed again for 1 h and the mixture was cooled to room temperature. The extract was filtered through 0.45 μm nylon filter (Millipore), the volume was made up to 100 mL with extraction solvent, and the clean supernatant was used for HPLC analysis. The isocratic mobile phase composition (acetonitrile-A and water-B, 80:20 [v/v]) with elution rate of 1 mL/min, data acumination and quantification was done at 210 nm. Gymnemagenin standard was purchased from Sigma Aldrich, USA. The conversion of gymnemagenin to gymnemic acid was done using the equation C = X(809.0 / 506.7), where C is the content of gymnemic acid in the sample, X is the content of gymnemagenin present in the sample, 506.7 is the molecular weight of gymnemagenin, and 809.0 is the molecular weight of gymnemic acid. The chromatogram of gymnemic acid standard shown in [Figure 1], with a retention time of 1.83 min.
All the genotypes were scored for presence and absence of the ISSR bands. The data were entered into binary matrix as discrete variable (1) for the presence of amplification product or band and (0) for the absence of the band and this matrix were subjected to further analysis. Scores of individual bands were used to create data matrix. The similarity indices (SI) were computed as the ratio of number of similar bands to total number of bands in pair wise comparison of all accessions/genotypes. A dendrogram constructed based on Nei and Li's coefficient  with unweighted pair group method and arithmetic average analysis (UPGMA) using Fig Tree Version 1.3.1 software.
Similar methodology was applied for chemical fingerprinting, where presence of peak represented as variable (1) and absence as (0). To measure the informativeness of markers, the polymorphic information content (PIC) for each ISSR marker was calculated according to formula: PIC = 1 − €Pi 2 , where PI is the frequency of the ith allele. Mantel test  was performed using 10 000 permutations carried out in XLSTAT-Pro (Version 7.5, 2004; Addinsoft Inc., Brooklyn, NY, USA) software; the significance level was set at a = 0.05, to compute the matrix correlation (r) between the similarity matrices generated from different assays (genetic and chemical fingerprinting) to test the goodness of fit.
| Results and Discussion|| |
ISSRs involve amplification of DNA segments present at an amplification distance in between two identical microsatellite repeat regions oriented in opposite directions. ISSR uses long poly nucleotide chain (15-30 mers) , which permit the subsequent uses of high annealing temperature, leading to high stringency and reproducibility. It has been used in genetic fingerprinting, phylogenetic studies, gene tagging, and genome mapping in many plant and animal species. , The versatility of this genotyping technique makes ISSR useful for studies in various species.
In this study, 14 genotypes were surveyed with 40 ISSR (microsatellite) markers for their distribution and informativeness and polymorphism for the assessment of genetic diversity among them. Among the 40 primers, 15 were polymorphic and produce scorable, unambiguous bands, of which 12 were anchored-type dinucleotide repeat, one anchored-trinucleotide repeat, and one non-anchored tetra nucleotide repeat. A total of 124 scorable alleles were generated and of which 89 were found to be polymorphic (75.89%). The high level of polymorphism observed with the primers used in this study indicated a high level of genetic variation among the 14 genotypes analyzed in agreement to Rakoczy-Trojanowska and Bolibok (2004), who reported high polymorphic patterns when reaction primers based on microsatellite sequences in plants were used.  The number of alleles were produced by different primers ranged from 1 to 14 with an average of 8.26 alleles per primer [Table 2]. The mean number of allele per locus and allele size generated in this study was in close agreement with earlier studies , on G. sylvestre. The results clearly indicate that the Gymnema accession could be easily distinguished using these ISSR primers. The maximum number of amplicons (14 alleles) were demonstrated in DNA profiles generated by ISSR-15 number primer whereas minimum number of amplicons (5 alleles) were noted for profile of ISSR-11. The banding pattern using ISSR-15 was shown in [Figure 2]. Primers ISSR-11 and ISSR-13 revealed 100% polymorphism, showing their ability for discriminating the accessions of G. sylvestre. The results with these primers were in consonance with earlier studies that marker techniques which amplifies microsatellite regions viz. SSR and ISSR is a potentially highly polymorphictool, which was applied in several DNA marker studies. ,,,,, The highest PIC value recorded for primer ISSR-12 is 0.99 and minimum for primer ISSR-13 is 0.33, with a mean of 0.69. The higher PIC value of any ISSR primer indicates the more informativeness for genotype discrimination and diversity studies  for that particular primer. The 15 ISSR primers collectively yielded nine unique accession-specific bands. Out of nine, four unique bands noted for accessions 3, two for accession 8, one for accession 3, one unique band each for accessions 1 and 14 [Table 3]. These accession-specific bands could be used as a descriptor for plant accessions protection and could also be converted into sequence tagged sites markers of great value to detect between any mixing up of cultivars as an DNA fingerprinting. 
|Figure 2 : ISSR marker profiles of 14 accessions generated by primer ISSR-15 in 2% agarose gel|
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|Table 2: ISSR primers used in this study and different parameters of genetic diversity.|
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The sufficient number of accession-specific bands signifies the power of ISSR markers in fingerprinting and diversity analysis within G. sylvestre. The binary data from the polymorphic primers used for computing Nie and Li's similarity indices. The similarity coefficient based on ISSR markers ranged from 0.70 to 0.94 [Table 5]. Two genotypes (Gym 2 and Gym 3) showed highest similarity index, which indicates that both shares common hypothetical ancestor. Gym 14 showed lowest similarity index. The ISSR marker showed very prominent dissimilarity between the accessions. Higher dissimilarity among the genotypes provide better scope for identifying the accessions with desired characteristics. Cluster analysis based on Nie and Li's similarity using UPGMA grouped 14 accessions into three major clusters. Clusters I, II, and III contains 4, 5, and 5 accessions, respectively. Interestingly, cluster I was characterized by moderate, cluster II by low, and cluster III by high gymnemic acid containing accessions [Figure 3].
|Figure 3 : Dendrogram of 14 accession constructed on the basis of ISSR variation pattern|
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|Table 4: Percentage of gymnemic acid in leaf samples of different accessions of G. sylvestre.|
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|Table 5: Similarity matrix for 14 G. sylvestre accessions based on ISSR finger printing.|
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The HPLC profile of methanolic extract showed that all the accessions possess the secondary metabolites of mid-polarity with considerable variability. The content of gymnemic acid varied from 0.02 to 0.64%, as observed for accession Gym 2 and Gym 10, respectively [Table 4]. The content of gymnemagenine varied from 0.014 to 0.407% and its peak was utilized as standard for chemical fingerprinting [Table 4].
The study of chromatogram indicates that peaks with retention time 2.63, 3.41, 23.83, 24.50, and 44.67 min were of universal type, as observed in all the accessions during analysis [Figure 4] and [Figure 5]. These peaks were selected as marker peaks, which could be utilized in identification and standardization of G. sylvestres germplasm and based herbal preparations/formulations. Hierarchical cluster analysis based on chromatographic fingerprint (38 scorable peaks) grouped all the accessions in three major groups. In cluster I four, in cluster II four, and in cluster III six accessions were grouped, respectively. This analysis also indicated that high-yielding accessions Gym 11, Gym 7, Gym 10, and Gym 11 are closely related with each other as observed in phylogenetic tree [Figure 6]. The similarity coefficient based on HPLC fingerprints ranged from 0.24 to 1.0 [Table 6]. Gym 12 and Gym 13 accessions were almost similar with respect of chemical profiles, therefore both may shares common hypothetical ancestor. It is interesting that, accessions with low gymnemic acid content belongs to cluster I, moderate content in cluster II, and higher belongs to cluster III. HPLC-based chemical fingerprinting was performed in several medicinal plants viz. Vitex rotundifolia,  Berberis vulgaris,  Andrographis paniculata, Pyrola species,  and wild Jujuba leaf tea.  Comparative study of results of genetic and chemical fingerprinting indicates that both techniques have potential to discriminate the G. sylvestre accessions according to gymnemic acid content, an antidiabetic active principle. However, clustering diagram based on both fingerprinting analysis were not perfectly matched with each other. This may be due to fact that ISSR measures genetic variation, mainly noncoding sequences which probably have a minor impact of the phenotypic and physiochemical behavior of plant on the other hand chemical constituents and their availability are affected by environmental conditions and show considerable variation. 
|Figure 4 : A representative HPLC chromatograms of G. sylvestre leaf samples|
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|Figure 6 : Dendrogram of 14 accession constructed on the basis of variation obtained by HPLC chromatography|
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|Table 6: Similarity matrix for 14 G. sylvestre accessions based on HPLC finger printing.|
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Mantel correlation analysis between the similarity matrix based on genetic and chemical fingerprints indicates positive and significant correlation (r = 0.150) between them, which signified the scope of simultaneous study of genetic and chemical finger printing in various medicinal plant species [Figure 7]. Comparative study also indicated that chemical fingerprinting was more suitable than genetic fingerprinting for distinguishing accessions according to their agro-climatic / natural habitat / collection site.
|Figure 7 : Scatter plot represents mental correlation between similarity matrix of genetic and chemical fingerprints|
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Experimental observations of ISSR and HPLC fingerprinting studies concluded that both approaches were suitable for identification of high-yielding accessions and different chemotypes, but their simultaneous application provides more insight to understand evolutionary trends, chemotypic variation, adaptation, and so on. Used ISSR markers were highly polymorphic and could be utilized as molecular probes for further selecting high-yielding accessions / genotypes. Although target metabolite, that is gymnemic acid in G. sylvestre, demonstrates the specific chemotype, but the selection of additional five peaks could also be utilized as standards to define the chemical diversity in the specific accession. Adaptation of both ISSR and HPLC fingerprinting-based methods simultaneously can ensure the consistent quality and therapeutic action of herbal drugs.
Financial support and sponsorships
The corresponding author is highly thankful to DST-SERB, New Delhi, India (File no. SB/YS/LS-115/2013 dated 30 Oct, 2013) for providing financial support in term of SERB- Young Scientist fellowship during this study.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]