Sharad Srivastava*a,
Ankita Misraa,
Priyanka Mishrab,
Pushpendra Shuklaa,
Manish Kumara,
Velusamay Sundaresanb,
Kuldeep Singh Negic,
Pawan Kumar Agrawald and
Ajay Kumar Singh Rawata
aPharmacognosy and Ethnopharmacology Division, CSIR-National Botanical Research Institute Lucknow, U.P.226001, India. E-mail: sharad_ks2003@yahoo.com; Fax: +91-522-2205836; Tel: +91-522-2297818
bDepartment of Plant Biology and Systematics, CSIR-Central Institute of Medicinal and Aromatic Plants, Research Centre Bangalore, Karnataka, India
cNBPGR-R/S, Bhowali, Nainital, Uttarakhand, India
dNASF, ICAR, KAB-II, New Delhi-110011, India
First published on 27th January 2017
C. forskohlii (willd.) Briq. is an industrially viable medicinal crop and is widely exploited for the therapeutic potential of its bioactive metabolite, forskolin. The present investigation aimed to explore the chemotypic variability of forskolin content and existing molecular diversity in the wild population of C. forskohlii from the Western Himalayan region of India. Twelve germplasm(s) from different populations were assessed for molecular fingerprinting (ISSR marker) and densitometeric quantification of forskolin. Two elite germplasms viz. NBC-24 (0.728%) and NBC-16 (0.641%) were obtained as the highest accumulator of forskolin with high genetic variability (92%). The UPGMA hierarchical clustering patterns revealed strong genetic grouping between the individuals corresponding to their geographical ranges. Mantel tests showed positive correlation (r = 0.354, p = 0.003) between molecular and chemical fingerprints that reflects the feasibility of the ISSR markers in analyzing genome information related to forskolin biosynthesis from varied phytogeography. Pearson correlation coefficient (0.102) between forskolin content with altitude gradient also denoted a positive correlation. However, the association of both genetic and chemical fingerprinting data with the geographic distance matrix was apparently negative (r = −0.234, p = 0.054; r = −0.067, p = 0.584) which meant that distance might be a predictor of population differentiation. Our study signifies the utility of metabolic and molecular fingerprints for identification of elite accessions and provides a lead to industry for commercial exploitability of Coleus species including its location specific commercial cultivation.
The world market for botanical pharmaceuticals, fragrances, flavors and color ingredients exceed several billion dollars per year and the classic examples include taxol, vincristine, vinblastine, colchicines, artemisinin, podophylotoxin etc. The demand for forskolin has also been increased in recent time due to its high medicinal value and huge demand from pharmaceutical industries. However, a number of threats like habitat loss, climate change, unsustainable use and exhaustive collection of wild sources along with inadequate attempts for its replenishment and/or cultivation have enlisted this species as endangered.1 However, in recent years its cultivation had scaled up due to commercial importance of forskolin. To overcome this, large scale agro-cultivation practices of C. forskohlii have resulted in an annual production of about 100 tons from 700 ha in India.7
Diversity analysis is a prerequisite factor for exploiting the available genetic resources for improvement of plants species producing bioactive secondary metabolites having commercial applications. Molecular markers in association with biochemical traits have demonstrated their potential and wide range of applications in identifying genetic purity of germplasm stocks, understanding genome organization, genetic relationships, chromosome mapping, trait tagging, inheritance pattern and molecular breeding etc.8,9 To assess the genetic diversity in plants, PCR-based markers such as RAPD, ISSR, DAMD, and AFLP are the most common, as their application does not need any prior sequence information.9,10 ISSR is a powerful tool for identifying genetic information and has been widely used in genetic diversity studies with relatively lower analysis cost.11,12 A number(s) of chromatographic methods such as TLC, HPTLC, HPLC, GLC etc. are common methods employed for the quantification of forskolin in C. forskohlii.3 HPTLC has become a simple, rapid, reproducible, efficient and economic technique for forskolin quantification.13,14
Despite being a high value commercial crop, information pertaining to interrelationship between morphology, chemistry and molecular fingerprinting available on C. forskohlii are meagre. Few available reports suggest the variation in forskolin content is due to the climatic and genetic factors.15–17 However majority of these studies are restricted to the southern states of India such as Tamil Nadu and Karnataka where the main focus was given on crop cultivation. Therefore, data on the morphological, chemical and molecular diversity of C. forskohlii is sparsely available. In our recent report, we also demonstrated the phytogeographical variation and chemotaxonomic profile in natural population of C. forskohlii.15 In this present investigation, we aimed towards documenting the level of molecular diversity and variability in the content of potential metabolite forskolin in the wild population of C. forskohlii from the Western Himalayan region of India. We studied the molecular fingerprinting using ISSR marker and chemical profiling of forskolin by HPTLC. This study represents the first exploration of the genetic and chemical diversity of natural populations to identify elite chemotype(s) from Western Himalayas, India.
Stock solution (1 mg ml−1) of standard forskolin and samples (10 mg ml−1) were prepared in methanol and diluted accordingly for further analytical work.
In the chromatographic profile, band (10 μl, methanolic extract) of different genotypes (1 mg ml−1) were applied in triplicate along with the reference standard of forskolin (5 μl). The chromatogram was scanned at 545 nm after development.20 These conditions were kept constant throughout the analysis of samples. Quantification was carried out on the basis of regression equation of area vs. concentration of standard curve.
Genotypes | Collection site | Voucher no. | Collection stage | GPS information | Season of collection | Soil type | ||
---|---|---|---|---|---|---|---|---|
Altitude (m) | Latitude (N) | Longitude (E) | ||||||
NBC-07 | Chamba | 305407 | Flowering | 1480 | 30°20′52.93′′ | 78°23′49.88′′ | August | Loamy |
NBC-08 | Dhanaulti road | 305408 | Flowering | 2089 | 30°25′31.17′′ | 78°14′13.58′′ | August | Sandy–loamy |
NBC-11 | Pauri | 305411 | Flowering | 1693 | 30°08′51.52′′ | 78°46′28.75′′ | October | Stony |
NBC-16 | Dwarikhal | 305416 | Flowering | 448 | 29°54′8.00′′ | 78°40′25.6′′ | January | Stony |
NBC-17 | Bachhetikhal | 305417 | Flowering | 246 | 30°05′42.20′′ | 78°37′54.30′′ | January | Stony |
NBC-18 | Kandikhal | 305418 | Flowering | 436 | 30°20′45.70′′ | 78°37′54.30′′ | January | Stony |
NBC-19 | Budha kedar | 305419 | Flowering | 420 | 30°33′39.50′′ | 78°38′39.00′′ | January | Stony |
NBC-23 | Diwakhal/Pauri | 305423 | Flowering | 457 | 29°48′41.30′′ | 79°02′26.70′′ | January | Stony |
NBC-24 | Pabo | 305424 | Flowering | 336 | 30°06′14.10′′ | 78°52′7.90′′ | January | Stony |
NBC-25 | Bhowali | 305425 | Flowering | 506 | 22°14′17.21′′ | 79°31′12.00′′ | January | Loamy |
NBC-01 | Jammu-01 | 305401 | Flowering | 92 | 32.7°50′01′′ | 75°8′12.00′′ | August | Loamy |
NBC-14 | Jammu-02 | 305414 | Flowering | 94 | 33°30′12′′ | 75°18′30.00′′ | December | Sandy–loamy |
S. No. | Genotypes | Forskolin contenta |
---|---|---|
a Values are mean ± S.D (n = 3). | ||
1 | NBC-07 | 0.116 ± 0.05 |
2 | NBC-08 | 0.189 ± 0.01 |
3 | NBC-11 | 0.563 ± 0.01 |
4 | NBC-16 | 0.641 ± 0.01 |
5 | NBC-17 | 0.098 ± 0.01 |
6 | NBC-18 | 0.159 ± 0.01 |
7 | NBC-19 | 0.061 ± 0.01 |
8 | NBC-23 | 0.235 ± 0.05 |
9 | NBC-24 | 0.728 ± 0.05 |
10 | NBC-25 | 0.474 ± 0.01 |
11 | NBC-01 | 0.013 ± 0.01 |
12 | NBC-14 | 0.039 ± 0.025 |
Marker | Sequence (5′-3′) | Tm °C | TNB | NPB (PPB%) | PIC | EMR | MI | RP |
---|---|---|---|---|---|---|---|---|
a R = (A, G), Y = (C, T), Tm, annealing temperature; TNB, total number of bands; NPB, number of polymorphic bands; PPB%, percentage of polymorphism; PIC, polymorphic information content; EMR, effective multiplex ratio; MI, marker index; RP, resolving power. | ||||||||
UBC 826 | (AC)8 C | 52.5 | 5 | 5 (100.00%) | 0.43 | 5.40 | 2.32 | 3.50 |
UBC 828 | (TG)8 A | 52 | 5 | 3 (60.00%) | 0.26 | 5.52 | 1.44 | 1.99 |
UBC 841 | (GA)8 YC | 52 | 4 | 3 (75.00%) | 0.31 | 5.06 | 1.59 | 2.16 |
UBC 844 | (CT)8 RC | 54 | 7 | 5 (71.42%) | 0.32 | 6.32 | 2.08 | 3.66 |
UBC 845 | (CT)8 RG | 53 | 5 | 4 (80.00%) | 0.36 | 6.24 | 2.09 | 2.50 |
UBC 848 | (CA)8 RG | 52.5 | 6 | 4 (66.66%) | 0.28 | 4.55 | 1.29 | 2.83 |
UBC 855 | (AC)8 YT | 53 | 4 | 3 (75.00%) | 0.31 | 5.25 | 1.64 | 2.00 |
UBC 856 | (AC)8 YA | 53 | 5 | 4 (80.00%) | 0.36 | 6.56 | 2.38 | 2.83 |
UBC 866 | (CTC)6 | 57.2 | 6 | 5 (83.33%) | 0.40 | 5.69 | 2.28 | 4.16 |
UBC 876 | (GATA)2(GACA)2 | 48 | 6 | 3 (50.00%) | 0.21 | 4.08 | 0.86 | 2.16 |
Total | 53 | 39 | ||||||
Average/primer | 5.3 | 3.9 (74.14%) | 0.32 | 5.46 | 1.80 | 2.78 |
For correlation analysis, Mantel test29 was performed using 10000 permutations carried out in XLSTAT©-Pro version 7.5 (2004, Addinsoft Inc., Brooklyn, NY, USA). The significance level was set at α = 0.05 to compute the matrix correlation (r) between the similarity matrices generated from different assays to test the goodness of fit between the molecular and chemical marker system. Finally, isolation by distance based geographic matrix was compared with genetic distance matrix using a Mantel test. Geographic distance matrix was realized based on latitude and longitude coordinates using Geographic Distance Matrix Generator (version 1.2.3).30
Surface imaging of leaves (upper and lower surface) showed the presence of both glandular (peltate and capitates) and non glandular type of trichomes (ESI Fig. 3†). Number of trichomes (per mm2 of leaf) on lower surface varied from 17 to 23 whereas in upper surface trichome frequency was slightly higher (25 to 35) (ESI Table 1†). However, the variation in trichome frequency was statistically insignificant (p > 0.05) among the germplasms.
The chemical profiling of C. forskohlii was carried out by HPTLC to check the existing variability among the metabolites of collected germplasms. This aids in quality check and authentication of standard sample of Coleus in terms of forskolin, the major metabolite of industrial demand. The development of chromatogram was carried out by using different solvents (during method development) and the system consisting of toluene:ethyl acetate:methanol (9:3:0.05) was selected as for optimum separation of bioactive marker forskolin with high resolution and compact spots at Rf 0.56 ± 0.01.
Calibration of the methods used was performed on the basis of peak area versus reference standard concentration, when subjected to regression analysis. Method was calibrated at five different dilutions of standard forskolin (20–100 ng per spot). The linear regression equation was obtained with coefficient greater than 0.9998. Limit of detection (LOD) (3:1) and limit of quantification (LOQ) (10:1) values were within the limit of acceptance and other statistical parameters were in accordance with the International Council for Harmonisation (ICH) guidelines. Stability of method was evaluated by repeated (n = 5) analysis of standard at single level (0.1 mg ml−1), standard deviation (6.083), RSD (0.357%) and variance (37.013) revealed that the method was stable under chromatographic conditions.15
HPTLC chromatogram revealed the variable fingerprint profile of collected germplasm with respect to presence of known (forskolin) and unknown markers. It is noteworthy to mention that, only forskolin was taken into consideration for analysis of chemotypic variability among collected germplasm, firstly due to high relative abundance of forskolin in each germplasm(s) as compared to other unknown chemical marker(s). Secondary, forskolin is potentially bioactive and is majorly responsible for therapeutic activity of the species. In addition to this, the species was also targeted for commercial/industrial exploitation due to its forskolin content only. Overlay spectra of chromatogram (Fig. 1) showed the presence of forskolin in each sample and densitometeric scanning revealed the variation in the content of metabolite (Table 2). The existing variation among the germplasms was found to be significant (p > 0.01). Forskolin content varied from 0.013–0.728% (dry weight of root). The maximum forskolin content was found in NBC-24 (Pebo) and minimum in NBC-01 (Jammu).
Karl Pearson correlation coefficient (0.102) between forskolin content with altitude revealed that there is a positive but week correlation exists among the two parameters. Cluster analysis of C. forskohlii genotypes based on forskolin content bifurcate the genotype group into two major clusters, cluster I and cluster II (Fig. 2a). NBC-25, NBC-11, NBC-16 and NBC-24 were grouped into single node in respect to relative concentration of forskolin (%) with mean value of 0.474, 0.563, 0.641 and 0.728% respectively. The remaining eight germplasms (NBC-01, NBC-17, NBC-07, NBC-19, NBC-14, NBC-23, NBC-08 and NBC-18) were clustered together in other branch. NBC-01 from Jammu and NBC-24 from Himachal Pradesh region showed maximum diversion in terms of forskolin as depicted in the cluster analysis. PCA analysis based on chemical distances has provided a biplot representation of the 12 germplasms accordingly. PCA derived on the basis of mean variables illustrated that the first two components, F1 and F2 were accounted for 55.47 and 44.53% variation respectively. The segregation of the population based on forskolin content with respect to altitude gradient has been shown in Fig. 2b.
C. forskohlii is an important medicinal plant with high commercial value due to its active phytochemical forskolin. In the present investigation, quantification of forskolin by validated HPTLC method was carried out for identification of the elite chemotype(s) to provide basic lead to industry for commercial exploitability including its location specific commercial cultivation. ISSR technique was employed for measuring genetic diversity within the collected genotypes. Besides, correlation between altitude and forskolin content was also established. The HPTLC analysis of twelve collected germplasms showed significant variation in forskolin content. Four elite germplasms viz. NBC-24 (0.728%), NBC-16 (0.641%), NBC-11 (0.563%) and NBC-25 (0.474%) of C. forskohlii were observed from our study were located in Himachal Pradesh. The genotypes from Jammu (NBC-01 and NBC-14) exhibited least amount (0.013 and 0.039%) of forskolin content. Previously, a number of investigators used different chromatographic techniques to determine forskolin content in C. forskohlii genotypes collected from the central and southern parts of India and they also found large variation of forskolin content.31–35 The variation in metabolite content may be due to several eco-geographical factors viz. climate, soil profile and microbial flora.36 Since there is a linear relationship exists between secondary metabolite content and maturity of the plants, all the genotypes were collected at the flowering stage. This was further confirmed by the findings from the anatomical and trichome studies. It is invariably evident in several reports that trichome morphology has significant effect on essential oil and secondary metabolite content of plant species at different stage of growth.37–39 Khatun et al. (2011) reported the pharmacognostic value of trichome morphology in C. forskohlii.40 We therefore investigated trichome characters and morpho-anatomical investigation to justify our study in correlation with existing literature. The presence of glandular trichome is a characteristic feature of the family Lamiaceae, to which the targeted species belongs. The insignificant (p > 0.05) variation in trichome frequency among the germplasms suggest that the collection was done at similar stage of maturity. This was further supported by morpho-anatomical observation, where no distinct variation was found among the samples. The germplasms were collected from the same phyto-geographical zone of Western Himalayas, where altitude and edaphic factors would be the key factors responsible for chemical variation15 and other environmental factors such as precipitation, humidity, temperature and light had no effect.
Molecular fingerprinting using ISSR marker showed high degree of polymorphism in C. forskohlii germplasm(s) from different regions of Western Himalayas. Ten ISSR primers generated a total of 53 products with an average of 5.3 products per primer. Among them, 39 (73.58%) products with an average of 3.9 products per primer were polymorphic and 14 (26.41%) products were monomorphic. The oligonucleotide sequences of these primers and the resultant multiple band patterns are summarized in Table 3. The representative ISSR profile of primer UBC 848 amplification has been shown in Fig. 3 and full-length blots/gels are presented in ESI Fig. 4.† The analysis showed the percentage of polymorphic band (PPB) ranging from 50% (UBC 876) to 100% (UBC 826) with an average value of 74.14% polymorphism per primer at the species level. PIC value was found in the range of 0.21 (UBC 876) to 0.43 (UBC 826) with an average of 0.32 per primer. Other parameters like effective multiplex ratio (EMR), marker index (MI) and resolving power (RP) were also found to be significant with an average value of 5.46, 1.08 and 2.78 per primer respectively. The observed number of alleles (na) ranged from 1.50 to 2.0 with mean value of 1.74 (SD = 0.44), while the effective number of allele (ne) ranged from 1.46 to 1.78 with mean value of 1.59 (SD = 0.41). The Nei's genetic diversity (h) and Shannon index (I) were estimated as 0.32 (SD = 0.20) and 0.46 (SD = 0.29), respectively (Table 4).
Fig. 3 ISSR patterns (cropped) of Coleus forskohlii generated by primer UBC 848. Lane M is double-digested λ DNA (EcoRI and HindIII) DNA ladder and lanes 1–12 represent different Coleus forskohlii genotypes as listed in Table 1 (full-length gel is presented in ESI Fig. 4†). |
S. No. | Diversity indices | Mean value (std. deviation) |
---|---|---|
1 | na (observed number of alleles) | 1.74 (0.44) |
2 | ne (expected number of alleles) | 1.59 (0.41) |
3 | h (Nei's gene diversity) | 0.32 (0.20) |
4 | I (Shannon's information index of genetic diversity) | 0.46 (0.29) |
5 | NPL (no. of polymorphic loci) | 3.9 |
6 | PPL (percentage of polymorphism) | 74.14% |
Cluster analysis revealed that the similarity index ranged from 0.02 (NBC-14 and NBC-11) to 0.92 (NBC-16 and NBC-24) with the mean value of 0.47 suggesting high level of genetic variability within the species. Dendrograms representing most probable genetic relationship between germplasms corresponding to molecular assay were presented in Fig. 4a. The dendrogram obtained from ISSR profiles showed two major clusters placing twelve germplasms into two major groups. It was interesting to observe that both the cluster grouped the genotypes similar to their geographical locations. Cluster I framed all the accessions from different places of Himachal Pradesh region whereas cluster II grouped both of the two genotypes from Jammu region (NBC-01 and NBC-14). Cluster I again sub-clustered into three major clusters with few outliers. Genotypes NBC-24 and NBC-16 from Himachal Pradesh regions shared the closest genetic relationships with 92% genetic similarity index which was also supported by 95% reliability node resulting through the bootstrap analysis. The PCA analysis based on genetic distances provided a spatial representation of the 12 genotypes following ISSR DNA fingerprinting (Fig. 4b). The two-dimensional PCA plot clearly differentiated all genotypes from Himachal Pradesh and Jammu region, thereby illustrating that the first three principal coordinate components accounted for 51.52, 28.76 and 9.06% variation, respectively and accounted for 89.34% of the genetic similarity variance.
A week but positive correlation (r = 0.354, p = 0.003) was achieved from the analysis of genetic and chemical fingerprint similarity matrices. Association of both genetic and chemical fingerprinting data with geographic distance matrix was apparently negative (r = −0.234, p = 0.054; r = −0.067, p = 0.584 respectively).
Genetic differences are considered as a standard and discrete means of identification as they get linked to genotypes for their genetic constitution.11 Molecular markers can more widely sample the genome in comparison to allozymes which reflect only a subset of genes. Highly polymorphic markers are essential to confidently identify genetic diversity. During the present study, a total of ten ISSR primers were screened on twelve C. forskohlii genotypes and the level of polymorphism (71.14%) suggested that these ISSR primers are viable markers to detect the genetic diversity in C. forskohlii at molecular level. The earlier work carried out on similar aspects lend support to our study, which also recorded high polymorphism (RAPD = 61.39%, ISSR = 68.75% and AFLP = 70.81%) in C. forskohlii genotypes collected from different places of central India.41 Recent report by Ahmad et al. (2013) also indicates high genetic diversity in C. forskohlii from central region of India but a lesser chemical diversity among the same samples.42
The result of the present study using ISSR markers revealed high level of genetic diversity with an average Nei's genetic diversity estimated as 0.32 (SD = 0.20). This high genetic diversity of C. forskohlii can be accounted predominantly to the out-crossing trait existing in this perennial herb.23 Along with this, life history traits i.e. seed dispersal mechanism, reproduction and geographical factors have great influence on the levels and distribution of genetic diversity. Geographically widespread species tend to maintain more genetic diversity than species with small geographical ranges.43 C. forskohlii germplasms collected from Western Himalayas, have wide topographical heterogeneity in its habitat which causes substantial changes in the environment, thus resulting in a strong isolation of populations because of drastic differences in phenology due to several factors like elevation gradients and mountain barriers which may have restricted the gene flow between the populations resulting in complex and varied genetic signatures.44
It is well known that the genetic structure and chemical fingerprints of plants are influenced by heredity and environmental factors. A correlation analysis was performed to gain a better understanding of their inter-relationships. Chemical profile and molecular signature were weekly correlated (r = 0.354, p = 0.004) with each other. Earlier work carried out on similar aspects lends support to our study.36 Therefore, the studied markers could play a vital role in dissecting the genome information related to forskolin biosynthesis and its influence by environmental factors. In agreement with previous reports, the present study also revealed negative correlation between genetic and chemical fingerprinting data with geographic distance matrix which implies that distance could be a predictor of population differentiation due to an isolation-by-distance effect, whereby geographically closer populations exchange more genes than more distant populations.36,45,46
The natural distribution of C. forskohlii extends from the sun-exposed arid and semi-arid hill slopes of the Himalayas to the eastward in Sikkim and Bhutan, Deccan Plateau, Eastern Ghats, Eastern Plateau and Western Ghats, India. The commercial cultivation of Coleus is mostly concentrated in Tamil Nadu and Karnataka states of India with some promising high yielding varieties.47 From our results, the positive correlation of forskolin content with altitude gradient was relevant and supported by fact plant species adapted to higher altitude contain increased concentration of active principles.48,49 This will also prompt future efforts towards good agronomic practices for large scale commercial cultivation of this plant adapted to higher elevations.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c6ra26190f |
This journal is © The Royal Society of Chemistry 2017 |