Int J Pharm Pharm Sci, Vol 7, Issue 5, 258-265Original Article


IMPACT OF CERTAIN BIOTIC AND ABIOTIC FACTORS ON PHYLLANTHIN AND HYPOPHYLLANTHIN CONTENT OF PHYLLANTHUS AMARUS SCHUM.& THONN. FROM THREE DIFFERENT HABITATS

DHANDAYUTHAPANI KANDAVEL1, SOUNDARAPANDIAN SEKAR2

1Department of Botany, Periyar EVR College (Autonomous), Tiruchirappalli 620023, Tamilnadu, India, 2Department of Industrial Biotechnology, Bharathidasan University, Tiruchirappalli 620024, Tamilnadu, India
Email: kandavel1976@gmail.com

Received: 06 Feb 2015 Revised and Accepted: 05 Mar 2015

ABSTRACT

Objective: Phyllanthus amarus is an important medicinal plant used for its hepatoprotective and other medicinal benefits. The bioactive potential of this plant is due to the presence of two lignans, Phyllanthin and Hypophyllanthin. Overharvest and overexploitation of this plant is reducing its natural population. To develop a proper agrotechnique for cultivation, a wide analysis of habitat ecology and the influence of some factors crucial in the content of these two is essential, which has been attempted. Three different study areas differing in soil profile and color where chosen and used as study areas for comparison.

Methods: Phytosociological associations of plants, morphometric and anatomical studies, soil physico-chemical properties, rhizospheric microbes, endophytic microbes, genetic relatedness through RAPD and HPLC profile of Phyllanthin and Hypophyllanthin content was analyzed between the study areas.

Results: This plant has a natural preference to grow with Cynodondactylon and in wild conditions the content of the two lignans does not fluctuate drastically and are not very significantly correlated to any biotic or abiotic factor in particular to enhance or decrease them.

Conclusion: Agrotechnique for this plant can be developed keeping different geographic locations as cultivation areas since this plant has good adaptive skills and maintains the balanced biochemical potential.

Keywords: Phyllanthus amarus, Phyllanthin, Hypophyllanthin, Hepatoprotective, Agrotechnique, Phytosociology, HPLC, RAPD, Rhizospheric microbes, Endophytes.

INTRODUCTION

Phyllanthus amarusSchum.&Thonn. (Phyllanthaceae) is spread throughout the tropical and subtropical countries and commonly used in the Indian Ayurvedic system in problems of stomach, genitourinary system, liver, kidney and spleen[1]. Phyllanthin (a bitter constituent) and Hypophyllanthin (a non-bitter constituent) [2,3] are the active principles responsible for the hepatoprotective role [4] and are present in combination only in Phyllanthus amarus and not in the other related species [5]. The highest amounts of phyllanthin (0.7% w/w) and hypophyllanthin (0.3% w/w) have been reported in leaves, whereas; in the stem these are in minor quantities [6]. Around 80% of the global trade in medicinal plant species relies on harvest from the wild. Many species are in danger of over-exploitation and even extinction through over-collection and habitat loss. Reasons for the rarity of medicinal plant species include an array of factors such as habitat specificity, narrow range of distribution, introduction of exotic, habitat alterations, climatic changes, heavy livestock grazing, explosion of human population, fragmentation and degradation of population and genetic drift [7].

Cultivation of medicinal plants is a viable alternative. Many manufacturers prefer wild medicinal plants over cultivated ones as there is a general feeling that wild plant species contain better chemical contents [7]. In Botswana, traditional medicinal practitioners avoid cultivated material as they consider them devoid of the power of the material collected from wild [8]. Moreover, information on the propagation of medicinal plants is available for less than 10% and agro technology is available for 1% of the total known plants globally [9,10]. In India, only 82 medicinal plants have recommended agro practices, by National Medicinal Plants Board (NMPB), New Delhi [11]. In this light, it is imperative to check whether habitat ecology has any role in the phytochemical content before arriving at a proper agrotechnique method for cultivation of P. amarus. In this study, three different study areas differing in soil color and profile were chosen and phytosociological analyses, morphometric, anatomical, soil physico-chemical assessment, rhizospheric microbes, endophytes, genetic diversity and phytochemical content were assessed.

Materials and Methods

Materials

Analytical reagent grade chemicals of Sigma–Aldrich for laboratory chemicals and Himedia for microbial media was used for the experiments. The place of work is Tiruchirappalli district and is centrally located in the state of Tamilnadu, India with a total geographic extent of 4404.12 sq. Km. It lies between 78° 10' to 79°5' east longitude and 10°15' and 11 °2' north latitude. It lies at an altitude of 78 m above sea level. The annual mean maximum temperature is 37.7 °C and the annual mean minimum temperature are 18.9 °C. The annual total rainfall is 778 mm. Three Revenue Villages were chosen as study sites representing the major soil types; red (Koppu North), brown (Sathamangalam) and grey (Sikkathambur).

Phytosociological, morphometric and anatomical analyses

Phytosociological studies were carried out following quadrat sampling technique [12]. Since herbaceous species were studied, sampling size of 1 X 1 m2 was followed [13]. For each study area, ten quadrats were laid and the plants present were counted, recorded and identified using standard identification manuals[14-22]. Primary data thus obtained was analyzed for density, frequency, relative density, relative frequency. Further Shannon-Wiener diversity index (H’), Simpson diversity index (λ) and Species Importance Value (SIV) [23-25] was calculated. So renson Index (Cs) was calculated to assess the similarity coefficient of the different study areas [26]. The plants were also tested for any morphometric variation. The following characters were recorded for each plant collected from these quadrats and the mean value was drawn for each quadrat: plant height (cm), number of compound leaves per plant, number of leaflets per compound leaf, length of branchlets (cm), number of fruits per plant, primary root length (cm) and number of secondary roots. Correlation matrix was developed based on this data. Stem and branchlet samples from all the study areas were collected. The plant samples (stem, branchlets and roots) were cross sectioned and compared for any significant changes in the tissue composition, distribution and variation.

So renson index (Cs) = 2j/(a+b)

Where,

j = the number of species found in both sites

a = the number of species found in site A

b = the number of species found in site B

Soil sampling

Rhizosphere soil samples were collected from the study areas following zigzag pattern across the sampling field to ensure homogeneity. All the samples thus collected in a field area are thoroughly mixed,labeled and stored at 4 °C until further analysis.

Soil physico-chemical properties

Soil samples were analyzed for the following parameters: pH and Electrical Conductivity [27]; Available Nitrogen [28]; Organic Carbon [29]; Available Phosphorus [30]; Available Potassium [31]; Micronutrients [32].

Rhizospheric microbes

Rhizosphere soil samples were collected from the plant roots in each study area. 1 gram of soil was taken and mixed with 9 ml of sterile distilled water, vortexed, serially diluted and plated. For bacterial isolation, Nutrient Agar plates were used. The plates were incubated at 37oC for 1-2 day (s) and bacterial, colonies were counted and expressed as CFU/gram dry weight of soil. For fungi, Dichloran Rose Bengal Agar with Chloramphenicol (100 µg/ml) was used.

The plates were incubated at 28 °C for 3-4 day(s) and the number of fungal colonies was counted and expressed as CFU/gram dry weight of soil. For Actinomycetes, Actinomycete Isolation Agar with Nalidixic Acid (25 µg/ml) and Cycloheximide (50 µg/ml) was used. The plates were incubated at 30oC for 7–10 days and the actinomycetes colonies were counted and expressed as CFU/gram dry weight of soil. The dilutions with countable colonies (30 to 300) were looked upon and considered.

Endophytes isolation

The seedlings from the study areas were uprooted, kept in sterile polyethylene bags and brought to the laboratory. Root sections of 2-3 cm were excised using a sterile scalpel from ten plants. Root sections were taken just below the soil line. The samples were surface disinfected with sodium hypochlorite (1.05%) and washed in four changes of 0.02 M phosphate buffer (pH 7.0) solution. Measured quantity of 0.1 ml aliquot from the final buffer wash was removed and transferred in 9.9 ml nutrient agar to serve as sterile check. Samples were discarded, if growth was detected in the sterile check within 48 h [33].

Selected samples were triturated in 9.9 ml of buffer in sterile pestle and mortar. The triturate was serially diluted in potassium phosphate buffer solution and plated on Trypticase Soy Agar (TSA). The medium was supplemented with penicillin G 100 units per ml and streptomycin 100 µg/ml concentrations. The isolates were counted after 48 hrs.

Genetic diversity among P. amarus in the study areas using RAPD analysis

Genomic DNA from the accessions was extracted [34] and twenty different primers used in this study were synthesized by Sigma-Aldrich Chemicals Pvt. Ltd., Bangalore. The primers given in table 1 are designated as MAP01 to MAP20 [35] and the sequences were screened for the accessions. The PCR reaction mix (25 µl)used in the experiment is: DNA template-1.72 µl (25 ng); dNTP mix-0.5 µl (200 µM each); Taq DNA polymerase-0.5 µl (0.2 unit); PCR buffer-2.5 µl; Primer-1 µl (10 pmol); Sterile distilled. H2O-18.78 µl. The amplifications were carried out using a DNA engine thermocycler (Eppendorf Pro-S gradient cyler) and the PCR conditions under which the amplification was carried out is: Initial Denaturation–94oC/5 min; 40 cycles of Denaturation, Annealing and extension at 94oC/1 min,38oC/1 min and 72 °C/2 min respectively; Final Extension–72oC/5 min. The amplified products were separated on 1.8% agarose gel containing 0.5 µg/ml of ethidium bromide and photographed with Alpha InnotechAlphaimager (USA). The profile was analyzed using the Alphaimager systems (version 1.2.0.1). Using the software the molecular weight of each band (by comparing with the marker bands) and their respective Rf values were obtained. Presence and absence of a particular molecular weight band in all the samples for a particular primer were recorded as a binary scoring matrix with 1 in the presence of a band and 0 in the absence of a band. Using RAPDistance Package (Version 1.04) Distance matrix was calculated and dendrogram plotted to assess the genetic relatedness among the accessions.

Table 1: Sequences of primers used in RAPD analysis of P. amarus genome

Oligo name 5'<-----Sequence----->3'
MAP01 AAATCGGAGC
MAP02 GTCCTACTCG
MAP03 GTCCTTAGCG
MAP04 TGCGCGATCG
MAP05 AACGTACGCG
MAP06 GCACGCCGGA
MAP07 CACCCTGCGC
MAP08 CTATCGCCGC
MAP09 CGGGATCCGC
MAP10 GCGAATTCCG
MAP11 CCCTGCAGGC
MAP12 CCAAGCTTGC
MAP13 GTGCAATGAG
MAP14 AGGATACGTG
MAP15 AAGATAGCGG
MAP16 GGATCTGAAC
MAP17 TTGTCTCAGG
MAP18 CATCCCGAAC
MAP19 GGACTCCACG
MAP20 AGCCTGACGC

HPLC quantification of Phyllanthin and Hypophyllanthin from leaf samples of P. amarus in the study areas

Seven grams of fresh leaf material were taken and mixed with 2.1 g of Na2CO3 dissolved in 30 ml of Distilled Water. The material is kept for maceration at room temperature for 18 h. The macerate was then taken in a Soxhlet apparatus (Extractor–100 ml) and boiled with 200 ml of methanol containing 3% potassium hydroxide for 1 h [36]. The refluxed material was filtered and the residue was again refluxed with the same volume of methanol containing 3% potassium hydroxide for 1 h. The filtrate was collected and combined with the earlier filtrate. The combined volume was noted and 10 µl from this sample was injected into Shimadzu High Performance Liquid Chromatographic system equipped with LC10A pump & SPD-M 10Avp Photo diode Array Detector in combination with Class-VP software and LC 2010HT integrated system equipped with Quaternary gradient, auto injector in combination with Lab solution software. 8 mg of Phyllanthin and hypophyllanthin reference standards was weighed in a 50 ml volumetric flask, dissolved in 25 ml of methanol, sonicated for 5 minutes, warmed on a water bath for 5 minutes, cooled and made up to 50 ml with methanol. Further diluted, to get 16 µg and 1.6 µg each. The mobile phase used in this isocratic elution was acetonitrile: phosphate buffer (pH-2.8) run in a C18, 2.5µ, 100 x 3.0 mm Phenomenex column at a flow rate of 0.4 ml/min detected at 230 nm.

Statistical analyses

Wherever required appropriate statistical validations like Correlation matrix and Pearson’s Correlation Coefficient were made with the help of SPSS predictive analysis software, version 18.

Calculation for quantifying phyllanthin (%)

RESULTS AND DISCUSSION

The quadrat analysis revealed the ecological preferences of P. amarus. The enumeration of plants of the quadrats in all the study areas indicated the richness of P. amarus population in places where they grow, whereas, other species of Phyllanthus do not show this population richness. From the recorded plants, fifteen species were found exclusively in Sathamangalam; fourteen species were found exclusively in Sikkathambur and 23 species were found exclusively in Koppu.

Fig. 1: Species Importance value (%) for the study areas (a) Sathamangalam(b) Sikkathambur (c) Koppu

This reveals the inclination of P. amarus to be more associated with C. dactylon in the study areas. Simpson Diversity Index (λ) given in fig. 2 was lowest in Koppu revealing high diversity and the Shannon-Wiener Diversity Index (H1) given in fig. 2 was highest in Koppu justifying its richness.

This indicates the adaptability of the plant and reflects its capability to grow along with diverse plant species in different habitats. The species Importance value presented in fig. 1 in Sathamangalam revealed P. amarus with highest presence of 14.3% (SIV = 28.63) followed byCynodondactylon with 12.29% presence(SIV = 24.58); Sikkathambur revealed the highest presence of 17% for Cynodondactylon(SIV=33.77) and with 14.04% P. amarus (SIV=28. 08) followed and in Koppu the higher of 12.39% presence was by P. amarus (SIV=24.77) followed by Tridaxprocumbens and Euphorbia hirta with 6% presence (SIV = 12.36 and 12.35 respectively).

Fig. 2: Comparative analyses of various phytosociological parameters from the three study areas: (a) Simpson Diversity Index (λ)(b) Shannon-Wiener Diversity (H1)(c) Sorenson Index (Cs)

In Sikkathambur, λ value was highest and a median value was found in Sathamangalam. The H1 value was more or less equal in Sathamangalam and Sikkathambur. As Shannon-Weiner diversity index is not affected by sample size the results can be taken as a generalized pattern followed by P. amarus [37].

Sorenson Index given in fig. 2 implies a similarity in the coefficient between Sathamangalam and Sikkathambur in the diversity whereas Sikkathambur and Koppu have a different diversity pattern.

These analyses disclose certain crucial leads like the distribution pattern, species associations and geospatial variations unique to this species which helped to understand the propagation template it follows in its natural ecosystem, which provides vital clues when agrotechniques were developed.

The correlation matrix of morphometric observations given in table 2 resonates the fact that changes in the values of parameters observed do not significantly affect the overall phenotypic expression in different ecological niches, as, significant positive relationship exists.

Variation in morphometric characters was linked in earlier studies to changes in flavonoids and other production dynamics [38,39] but as the correlation is positive here the variations, if any, in phytochemical constituents between the study areas cannot be attributed to morphometric parameters of this plant in different study areas. Anatomical comparisons of stem, root and branchlets did not show any major variation among the study areas.

Table 2: Correlation matrix for morphometric observations in the study areas

Sathamangalam Koppu Sikkathambur
Sathamangalam 1
Koppu 0.825** 1
Sikkathambur 0.793** 0.899** 1

**. Correlation is significant at the 0.01 level (2-tailed).

Correlation coefficient given in table 3 between Sathamangalam and Koppu (r=0.958, p<0.01), between Sathamangalam and Sikkathambur (r= 0.809, p<0.01) and between Koppu and Sikkathambur (r = 0.732, p<0.01) resonate the fact that changes in the values of parameters observed do not significantly affect the overall soil physico-chemical properties in different ecological niches as significant positive relationship exists.

Table 3: Correlation matrix for soil physicochemical parameters in the study areas

Sathamangalam Koppu Sikkathambur
Sathamangalam 1
Koppu 0.958** 1
Sikkathambur 0.809** 0.732** 1

**. Correlation is significant at the 0.01 level (2-tailed).

Phenolic content was said to be influenced by soil type in some plants [40] and influence of calcareous oil in influencing linalool, linalyl acetate and trans-myrtanol acetate was detected in Myrtuscommunis [41]. As the correlation matrix show positive correlation, any change, in phytochemical profile among the study areas cannot be directly related to soil physico-chemical variables, as the variations are negligible based on statistical analysis of the data. Plant-Soil Feedback studies conducted have suggested that factors like plant abundance, root exudate, etc., can change the soil nature [42] and the positive correlation of the data here may also be due to the influence of P. amarus over the soil in which it grows.

The role of soil parameters in influencing the richness of Rhizospheric microbes and endophytic microbes was assessed by employing Pearson’s Correlation Coefficient. In Sathamangalam, rhizobacteria and rhizospheric actinomycetes were significantly and negatively correlated with phosphorus and copper at 0.05 and 0.01 levels of significance, respectively. Rhizospheric actinomycetes were positively correlated with rhizobacteria at 0.01 significance level as seen from table 4. In Sikkathambur, positive correlation at 0.01 significance exists between endophytic actinomycetes and soil pH and endophytic bacteria and nitrogen.

Similarly, strong negative correlation exists between endophytic actinomycetes and organic carbon percentage at 0.01 significance level and Iron, Manganese and endophytic actinomycetes at 0.05 significance level as seen from table 5. In Koppu, rhizospheric fungi were strongly and positively correlative with endophytic bacteria at 0.01 significance level. Endophytic fungi were strongly and positively correlative with iron at 0.01 significance level and strongly negatively correlative with zinc at 0.01 significance level. Negative correlation also exists between endophytic fungi and nitrogen and potassium at 0.05 level of significance as evident from table 6. Microorganisms in soil were said to be not only inhabitants, but also active participants in the formation and reorganization and hence the stage of soil formation may have an influence over the diversity found [43]. Generally less than 3,000 bp long amplifications result from RAPD PCR [44] but in our case 4000 bp fragments were produced. Of twenty primers used (MAP01 to MAP20) other than MAP07 all other primers responded to all the accessions. The banding patterns revealed polymorphism among different primers and were similar to a large extent among the accessions.

Using RAPDistance Package (Version 1.04) Distance matrix was calculated and dendrogram plotted and given in fig. 6 to assess the genetic relatedness among the accessions.

Table 4: Pearson’s Correlation coefficient between soil physico-chemical parameters and viable microbial population in Sathamangalam

  pH EC(dSm-1) N (Kg/ac) P (Kg/ac) K (Kg/ac) O. C (%) Fe (ppm) Mn (ppm) Zn (ppm) Cu (ppm) R_ Bact EndoBact R_Act EndoAct R_Fungi EndoFungi
pH 1                              
EC (dSm-1) .945 1
N (Kg/ac) .877 .672 1
P (Kg/ac) -.683 -.885 -.249 1
K (Kg/ac) .992 .979 .809 -.771 1
O. C (%) -.987 -.985 -.788 .792 -.999* 1
Fe (ppm) .047 -.283 .521 .697 -.081 .115 1
Mn (ppm) .705 .434 .959 .037 .608 -.581 .742 1
Zn (ppm) -.959 -.814 -.977 .449 -.915 .901 -.327 -.876 1
Cu (ppm) -.655 -.866 -.212 .999* -.746 .768 .724 .075 .415 1
R_ Bact .655 .866 .212 -.999* .746 -.768 -.724 -.075 -.415 -1.000** 1
Endo_Bact -.866 -.982 -.520 .957 -.923 .935 .459 -.255 .690 .945 -.945 1
R_Act .655 .866 .212 -.999* .746 -.768 -.724 -.075 -.415 -1.000** 1.000** -.945 1
Endo_Act -.929 -.756 -.993 .363 -.873 .857 -.414 -.918 .996 .327 -.327 .619 -.327 1
R_Fungi .327 .000 .741 .466 .203 -.171 .959 .901 -.581 .500 -.500 .189 -.500 -.655 1
Endo_Fung -.786 -.945 -.392 .989 -.859 .875 .581 -.115 .579 .982 -.982 .990 -.982 .500 .327 1

* Correlation is significant at the 0.05 level (2-tailed); ** Correlation is significant at the 0.01 level (2-tailed)

EC-Electrical Conductivity; O. C-Organic Carbon; R_Bact-Rhizospheric bacteria; Endo Bact-Endophytic bacteria; R_Act: Rhizospheric Actinomycetes; Endo Act-Endophytic Actinomycetes; R_Fungi-Rhizospheric Fungi; Endo Fungi-Endophytic Fungi.

Table 5: Pearson’s Correlation coefficient between soil physico-chemical parameters and viable microbial population in Sikkathambur

pH EC(dSm-1) N (Kg/ac) P (Kg/ac) K (Kg/ac) O. C (%) Fe (ppm) Mn (ppm) Zn (ppm) Cu (ppm) R_ Bact Endo_Bact R_Act Endo_Act R_Fungi Endo_Fungi
pH 1
EC (dSm-1) .866 1
N (Kg/ac) .866 .500 1
P (Kg/ac) -.971 -.721 -.961 1
K (Kg/ac) .693 .240 .961 -.846 1
O. C (%) -1.000** -.866 -.866 .971 -.693 1
Fe (ppm) -.999* -.888 -.843 .959 -.660 .999* 1
Mn (ppm) -.997* -.825 -.902 .986 -.747 .997* .992 1
Zn (ppm) -.500 -.866 .000 .277 .277 .500 .539 .432 1
Cu (ppm) .693 .240 .961 -.846 1.000** -.693 -.660 -.747 .277 1
R_ Bact -.866 -1.000** -.500 .721 -.240 .866 .888 .825 .866 -.240 1
Endo_Bact .866 .500 1.000** -.961 .961 -.866 -.843 -.902 .000 .961 -.500 1
R_Act -.770 -.986 -.348 .594 -.074 .770 .798 .718 .938 -.074 .986 -.348 1
Endo_Act 1.000** .866 .866 -.971 .693 -1.000** -.999* -.997* -.500 .693 -.866 .866 -.770 1
R_Fungi -.500 .000 -.866 .693 -.971 .500 .460 .565 -.500 -.971 .000 -.866 -.167 -.500 1
Endo_Fungi .000 .500 -.500 .240 -.721 .000 -.045 .077 -.866 -.721 -.500 -.500 -.638 .000 .866 1

* Correlation is significant at the 0.05 level (2-tailed), ** Correlation is significant at the 0.01 level (2-tailed) 

EC-Electrical Conductivity; O. C-Organic Carbon; R_Bact-Rhizospheric bacteria; Endo Bact-Endophytic bacteria; R_Act: Rhizospheric Actinomycetes; Endo Act-Endophytic Actinomycetes; R_Fungi-Rhizospheric Fungi; Endo Fungi-Endophytic Fungi.

Distance matrix ranged from 0.118 to 0.212 and classified the accessions into two clusters. Cluster I included plants from Sathamangalam and Koppu whereas Cluster II comprised of plants from Sikkathambur. Even though the accessions are from geographically distinct study areas, the accessions did not show long genetic distances and a coherent genetic pattern is exhibited among the study areas which is similar to an earlier work [45]. Simultaneous quantification of phyllanthin and hypophyllanthin from the study areas give in fig. 7 revealed the higher percentage of the duo in Sikkathambur followed by Sathamangalam and Koppu respectively.

Table 6: Pearson’s Correlation coefficient between soil physico-chemical parameters and viable microbial population in Koppu

pH EC(dSm-1) N (Kg/ac) P (Kg/ac) K (Kg/ac) O. C(%) Fe (ppm) Mn (ppm) Zn (ppm) Cu (ppm) R_ Bact EndoBact R_Act EndoAct R_Fungi EndoFungi
pH 1
EC(dSm-1) .982 1
N (Kg/ac) .899 .799 1
P (Kg/ac) -.397 -.564 .046 1
K (Kg/ac) .891 .789 1.000* .062 1
O. C (%) .000 .189 -.439 -.918 -.454 1
Fe (ppm) -.866 -.756 -.998* -.115 -.999* .500 1
Mn (ppm) .792 .663 .980 .245 .983 -.610 -.991 1
Zn (ppm) .866 .756 .998* .115 .999* -.500 -1.000** .991 1
Cu (ppm) -.381 -.200 -.748 -.697 -.759 .924 .792 -.866 -.792 1
R_ Bact -.936 -.853 -.995 .049 -.994 .352 .987 -.956 -.987 .682 1
EndoBact .655 .500 .920 .434 .926 -.756 -.945 .980 .945 -.948 -.879 1
R_Act .596 .737 .183 -.974 .167 .803 -.115 -.017 .115 .515 -.276 -.217 1
Endo_Act .982 .929 .965 -.217 .961 -.189 -.945 .893 .945 -.549 -.986 .786 .434 1
R_Fungi .655 .500 .920 .434 .926 -.756 -.945 .980 .945 -.948 -.879 1.000** -.217 .786 1
Endo_Fun -.866 -.756 -.998* -.115 -.999* .500 1.000** -.991 -1.000** .792 .987 -.945 -.115 -.945 -.945 1

*. Correlation is significant at the 0.05 level (2-tailed), **. Correlation is significant at the 0.01 level (2-tailed).

EC-Electrical Conductivity; O. C-Organic Carbon; R_Bact-Rhizospheric bacteria; Endo Bact-Endophytic bacteria; R_Act: Rhizospheric Actinomycetes; Endo Act-Endophytic Actinomycetes; R_Fungi-Rhizospheric Fungi; Endo Fungi-Endophytic Fungi. Molecular marker analyses among accessions from the three study areas given in fig.3, 4, 5 revealed bands ranging from fifty bp to 4000bp in size.

Fig. 3: Submarine Agar gel electrophoresis of RAPD based on PCR products of P. amarus genome from the study areas using MAP01 to MAP08 primers: MAP01, MAP02, MAP03 and MAP04MAP05, MAP06, MAP07 and MAP08; Sa–Sathamangalam; S–Sikkathambur; K–Koppu


Fig. 4: Submarine Agar gel electrophoresis of RAPD based on PCR products of P. amarus genome from the study areas using MAP09 to MAP16 primers: (a) MAP09, MAP10, MAP11 and MAP12 (b) MAP13, MAP14, MAP15 and MAP16; Sa–Sathamangalam S–Sikkathambur K–Koppu


Fig. 5: Submarine Agar gel electrophoresis of RAPD based on PCR products of P. amarus genome from the study areas using MAP17 to MAP20 primers: Sa–Sathamangalam S–Sikkathambur K–Koppu

Recovery of phyllanthin and hypophyllanthin were at 99% for both, revealing the effectiveness of the method, better than, earlier reports of 98.7 and 97.3% recovery for the phyllanthin and hypophyllanthin [46]. The ratios of phyllanthin and hypophyllanthin for Koppu, Sathamangalam and Sikkathambur were, 0.58:0.9, 0.68:1.04 and 1.04:1.36 respectively, indicating higher levels of hypophyllanthin than phyllanthin, compared to higher levels of phyllanthin than hypophyllanthin reported (1.4:0.6) in some studies [36].

Fig. 6: Distance matrix Dendrogram showing diversity of the Phyllanthus amaraus schum.& Thonn. from the study areas


Fig.7: HPLC quantification of Phyllanthin and Hypophyllanthin in Phyllanthus amaraus schum.& Thonn. from the study areas: (a) Mixed standards of Gallic acid, Phyllanthin and Hyphophyllanthin standard (1.6 µg each) (b) Mixed standards of Gallic acid, Phyllanthin and Hyphophyllanthin standard (16 µg each) (c) Phyllanthin and Hyphophyllanthin from P. amarausof Sathamangalam(d) Phyllanthin and Hyphophyllanthin from P. amarausof Sikkathambur(e) Phyllanthin and Hyphophyllanthin from P. amarausof Koppu

CONCLUSION

Phytosociological analysis by quadrats in the three sites revealed the association of P. amarus with other plants. P. amarus was found associated more closely with the grass, Cynodondactylon. Comparison of morphometric, anatomical and soil physico-chemical features in the three areas showed no momentous variations. Microbial diversity in the three study areas showed significant variations. The content of phyllanthin and hypophyllanthin as well as genetic diversity of P. amarus showed slight variations in the study areas. It is thus possible to cultivate P. amarus in different geographical locations without compromising its medicinal value.

ACKNOWLEDGEMENTS

The authors thank University Grants Commission, Govt. of India, New Delhi for the award of Teacher fellowship (FDP) to Kandavel.

CONFLICT OF INTERESTS

We declare that we have no conflict of interest

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