Enhancement of secondary metabolites in Bacopa monnieri (L.) Pennell plants treated with copper‐based nanoparticles in vivo

Abstract

The study aims to document the effect of starch‐stabilised copper‐based nanoparticles (CuNPs) on the biosynthesis of pharmaceutically valuable secondary metabolites, especially saponins, of the reputed nootropic herb Bacopa monnieri (L.) Pennell. CuNPs were synthesised chemically by the reduction of cupric sulphate pentahydrate with ascorbic acid using starch as the capping agent. They were characterised by UV–visible spectrophotometry, Fourier‐transform infra‐red spectroscopy, X‐ray diffraction, high‐resolution transmission electron microscopy and zeta potential. The nanoparticles consisted of cuprous oxide and metallic copper, were approximately spherical, polydispersed with diameter <20 nm. Hydroponically grown B. monnieri plants were treated in vivo with the CuNPs between the concentrations of 0–100 mg l⁻¹. Spectrophotometric estimation of the total contents of saponins, alkaloids, phenolics, flavonoids and DPPH radical scavenging capacity from the methanolic extracts of the whole plants showed a hormetic increase in the content of secondary metabolites in a concentration‐dependent manner from 5 mg l⁻¹ until it declined at toxic metabolic concentration. This was accompanied by an increase in ROS markers hydrogen peroxide and malondialdehyde as well as a hormetic effect on activities of phenylalanine ammonia lyase and antioxidant enzymes catalase, ascorbate peroxidase and superoxide dismutase. CuNPs at sub‐toxic concentrations were found to enhance secondary metabolism and antioxidant capacity in Bacopa monnieri through ROS‐mediated defence response.

1 Introduction

Bacopa monnieri (L.) Pennell (BM) (also known as Bacopa monniera, Herpestes monniera, Brahmi and water hyssop) (Family Plantaginaceae) is a reputed nootropic herb which has been traditionally used in Indian folklore and Ayurvedic medicine as a brain tonic and memory and intellect enhancer. The entire plant is medicinally useful. Its clinical effects include anti‐depressant and anti‐anxiety, sedative and anti‐epileptic, anti‐inflammatory, immunostimulatory and antimicrobial, adaptogenic, anti‐oxidant, analgesic, hepatoprotective, antipyretic, anti‐ulcerogenic and anti‐neoplastic properties. It is also known to attenuate age‐related dementia [1, 2]. The pharmacological effects of BM are attributed to the presence of a number of compounds including saponins, alkaloids and sterols. The major chemical entities responsible for the nootropic effects of BM are the family of 12 dammarane‐type triterpenoid saponins known as bacosides with jujubogenin or pseudojujubogenin as aglycone moieties [3, 4]. The most important therapeutic constituents are the steroidal bacosides A, B, and C. Novel saponins called bacopasides I‐XII have also been identified. The significant role of saponins in neuroprotection is attributed to the modulation of antioxidant enzymes (namely superoxide dismutase and catalase) in stressed neuronal cells [5]. The alkaloids brahmine, nicotine and herpestine have also been reported along with D‐mannitol, apigenin, hersaponin, monnierasides I‐III, cucurbitacin and plantainoside B. The drug is generally characterised on the basis of its total bacoside content [2, 6].

BM is a native of India and Australia and grows widely in East Asia and the USA. It is a perennial creeping herb which grows in warm wetlands and rice fields. The annual demand for this plant in India is estimated to be about 1000 metric tonnes which is increasing at a rapid pace. The demand is largely met from wild populations leading to its depletion due to over‐exploitation. Thus, it has been listed as an threatened species by the International Union for the Conservation of Natural and National Resources and prioritised in a list of 32 medicinal plants for cultivation and conservation by the National Medicinal Plants Board of India (2004) [7]. The amount of active principle, mainly bacoside A, shows considerable variation in wild populations which may be due to genotypic variations [8] as well as season of harvest [9]. So both the amount of total harvestable biomass and the level of bacosides are important for the available active principle. Thus, it can be extremely useful to enhance the levels of active principles per unit biomass of BM. It is known that the active principles are a product of secondary metabolism which respond positively to abiotic stress [10].

Plants are in constant interaction with air, soil and water all of which may contain nanoparticles, due to their widespread use in household and commercial products in recent years. Copper nanoparticles have widespread application in nanopesticides, antimicrobial agents, catalysts, gas sensors, electronics, batteries, heat transfer fluids and so on [11]. There are several reports of enhancement of secondary metabolites by nanoparticles both in vitro in cultures of various plants [12] as well as in vivo [13]. Plantlets of Citrus reticulata, when germinated in vitro in media supplemented separately with CuO NPs (15–32 nm) at concentrations of 30 μg/ml, showed significant enhancement of total phenolic and flavonoid contents as well as antioxidant capacity [14]. Foliar treatment of Mentha piperata L.(peppermint) plants with CuNPs (1.0 g l⁻¹) was reported to increase essential oil percentage by 20% [15]. CuO NPs were found to significantly enhance polyphenol, flavonoid and tannin content along with antioxidant capacity in roots of the Indian medicinal plant Withania somnifera L. Dunal (Ashwagandha) [16]. In view of such reports, the present study was undertaken with the view to enhance the amount of the valuable secondary metabolites per unit biomass of Bacopa monnieri in vivo by inducing abiotic stress using copper‐based nanoparticles (CuNPs).

2 Materials and methods

2.1 Synthesis of copper nanoparticles

Starch‐stabilised copper nanoparticles were synthesised by the chemical method of Dinda et al. [17] with slight modifications. 1.25 g starch was dissolved in 15 ml double distilled water by heating and mixed with 10 ml of 0.04 (M) solution of cupric sulphate pentahydrate. To that 1 g of ascorbic acid was added as the reducing agent and mixed well under constant magnetic stirring. The final concentration was CuSO₄. 5H₂ O 16 mM, ascorbic acid 227 mM and starch 5% (w/v). The solution was kept at 60°C for 3 h. It was then centrifuged at 5000 r.p.m. for 15 min, the nanoparticles were washed, freeze‐dried and stored in a vacuum desiccator [17].

2.2 Characterisation of CuNPs

The UV–visible absorbance spectra of the CuNPs was recorded after 3 h in double distilled water at a concentration of 10 mg ml⁻¹ in the range of 200–800 nm in a Mecasys Optizen – POP UV–visible spectrophotometer using a quartz cell of 1 cm path length.

High‐resolution transmission electron microscopy (HRTEM) was carried out on a 200 kV JEOL‐JEM 2100HR microscope with EELS (JEOL, Tokyo, Japan). For HRTEM the CuNPs were dispersed in distilled water by sonication and a 5 μl droplet was placed on a carbon‐coated copper grid of mesh size 300 lines/inch. The grid was allowed to dry completely in a vacuum desiccator before observation and photomicrography.

The Fourier transform infra‐red (FTIR) spectroscopy study was carried out on a Perkin Elmer spectrum two FTIR spectrometer (Perkin Elmer, U.S.A.) in the range of 4000–450 cm⁻¹ wave number and analysed by Perkin Elmer software (version 10.5.2).

The X‐ray diffraction (XRD) pattern of the powdered sample was obtained with a Seifert P3000 diffractometer operated at 40 kV and 30 mA using Cu Kα (λ  = 0.15406 nm) radiation as a source. The scanning range of 2Ɵ was from 20° to 80°. For sample preparation, the nanoparticle powder was placed on an aluminium slide and spread out to cover up a specified area.

The mean size of nanocrystals was measured from the broadening of the diffraction peaks corresponding to the most intensive reflections according to the JCPDS (Joint Committee on Powder Diffraction Standards) database. Scherrer equation was used to determine the crystallite size from XRD pattern measured for nanoparticles

$$d=K\lambda /B\cos \ominus$$

where K is the Scherrer constant (shape factor, its value is 0.9), λ is the X‐ray wavelength (λ  = 0.154 nm), B is the line broadening at half the maximum intensity (FWHM) in radians, Ɵ is the Bragg angle, (the position of the diffraction peak maximum) and d is the mean dimension of crystallites in nanometres.

The zeta potential was determined by dispersing 10 mg of the nanoparticles in 1 ml of double distilled water and Hoagland's nutrient solution [18], respectively, and measuring at room temperature (∼25°C) using a Zetasizer Nano ZS (Malvern Instruments, UK).

2.3 Hydroponic culture of Bacopa monnieri plants and nanoparticle treatment

Bacopa monnieri plants were collected from the field and taxonomically identified. 3‐inch tips of plants were taken and sand‐cultured for 2 months with 10% (v/v) Hoagland's nutrient solution [18] under natural light condition till the plants developed roots and appeared healthy. For preparing the sand bed, fine‐grain sand (0.45–1 mm diameter) was soaked in 2N HCl for 24 h, washed several times with tap water until the water showed neutral pH, and finally washed with distilled water before being spread out on a tray and air‐dried. The acclimatised plants were transferred to Erlenmeyer flasks containing 100 ml of 10% (w/v) Hoagland's nutrient solution containing CuNPs dispersed at concentrations of 5, 10, 20, 30, 40, 50, 75 and 100 mg l⁻¹. The control set contained no nanoparticles. Each experimental set was made in triplicate. The experimental plants were kept for 10 days under natural light (13 h L: 11 h D), at a maximum temperature of 37 ± 3°C, minimum temperature 27 ± 3°C and relative humidity of 70 ± 10%, replenishing the medium after 5 days. After treatment, the plants were washed with distilled water and dried at room temperature in a dust‐free enclosure for the extraction of secondary metabolites.

2.4 Extraction of secondary metabolites

For spectrophotometric estimation, methanolic extraction of secondary metabolites was carried out. 1 gm of dry, powdered BM whole plant was mixed with 30 ml of 70% (v/v) methanol in a 100 ml flask and refluxed for 30 min at 95°C. The extract was filtered and the extraction was repeated twice with 30 ml of 70% (v/v) methanol (2 × 30 ml). All the extracts were combined, filtered with Whatman filter paper No. 41 and the volume made up to 100 ml [19]. The recovery rate of extraction (mass of extract/mass of dry matter × 100%) was calculated by evaporation of the extract in a rotary evaporator and was found to be ∼50–60%.

2.5 Estimation of total saponin content (TSC)

TSC was estimated spectrophotometrically by the vanillin‐sulphuric acid method of Ebrahimzadeh and Niknam [20] as modified by Bhardwaj et al. [21]. For this 0.125 ml of the methanolic extract was mixed with 0.125 ml of 8% (w/v) vanillin solution in ethanol and 1.25 ml 72% (v/v) sulphuric acid. The test tube was incubated in a water bath at 60°C for 10 min and cooled in a crushed ice bath. The absorbance was determined at 544 nm against a reagent blank using a Mecasys Optizen POP UV–visible spectrophotometer. The standard curve was prepared using saponin and results were expressed as milligram of saponins per gram (mg gm⁻¹) of the dry weight of the plant. The range of detection of this method is 0–400 μg of saponin.

2.6 Estimation of total alkaloid content (TAC)

Estimation of TAC was carried out spectrophotometrically using Dragendorff's reagent. A 5 ml amount of the methanolic extract was taken and the pH was maintained at 2–2.5 with dilute HCl. A 2 ml amount of Dragendorff's reagent was added to it and the precipitate formed was centrifuged. The centrifugate was checked for complete precipitation. After centrifugation, the supernatant was decanted completely and meticulously. The precipitate was further washed with ethanol. The supernatant was discarded and the precipitate was treated with 2 ml of 1% (w/v) disodium sulphide solution. The brownish‐black precipitate was then centrifuged. Completion of precipitation was checked by adding two drops of disodium sulphide. The residue was dissolved in 2 ml of concentrated nitric acid, with warming, if necessary. This solution was diluted to 10 ml in a standard flask with distilled water, 1 ml was then pipetted out and 5 ml of 3% (w/v) thiourea solution was added to it. The absorbance was measured spectrophotometrically at 435 nm using a reagent blank. The standard curve was prepared using a stock solution of bismuth nitrate pentahydrate and results were expressed as mg of Bi(NO₃)₃. 5H₂ O equivalent per gm (mg gm⁻¹) of the dry weight of the plant [22].

2.7 Estimation of total phenolic content (TPC)

Estimation of TPC was carried out spectrophotometrically by Folin‐Ciocalteu reagent method of Ainsworth and Gillespie [23] as modified by Bhardwaj et al. [21]. For this 25 μl of the methanolic extract was mixed with 1.25 ml 0.2N folin‐ciocalteau reagent and 1 ml of 7.5%(w/v) of sodium carbonate. The solution was incubated for 3 h at room temperature in the dark and the absorbance was measured at 765 nm against a reagent blank. The calibration curve was prepared using gallic acid and the results were expressed as mg gallic acid equivalent per gm (mg gm⁻¹) of the dry weight of the plant.

2.8 Estimation of total flavonoid content (TFC)

Estimation of TFC was carried out spectrophotometrically by the aluminium chloride method. 0.5 ml of the methanolic extract was mixed successively with 1.5 ml of methanol, 0.1 ml of 10% (w/v) aluminium chloride, 0.1 ml of 1(M) potassium acetate and 2.8 ml of distilled water. After mixing, the solution was incubated for 30 min at room temperature. The absorbance was measured at 415 nm against a reagent blank. The standard curve was prepared using quercetin and the results were expressed as μg quercetin equivalent per gm (μg gm⁻¹) of the dry weight of the plant [24].

2.9 Estimation of DPPH radical scavenging capacity (DRSC)

DRSC of the methanolic extract was estimated using 1,1‐diphenyl 2‐picrylhydrazyl (DPPH). DRSC is an assay of the antioxidant capacity of the plant extract. For the assay, 950μl of 100 μM methanolic solution of DPPH was incubated with 50 μl of methanolic extract at 37°C for 30 min. The absorbance was measured spectrophotometrically at 517 nm. The percent radical scavenging activity was determined by comparison with a methanol‐treated control using the following formula:

$$\mathrm{DRSC}\left(\text{\%}\right)=\left(A_{\mathrm{c}}-A_{\mathrm{s}}\right)/A_{\mathrm{c}}\times 100,$$

where A _c denotes the absorbance of the control and A _s denotes the absorbance of the sample or standard. Ascorbic acid was used as a standard. Results were expressed as milligram of ascorbic acid equivalent per gram (mg gm⁻¹) of the dry weight of the plant [21, 25].

2.10 Determination of hydrogen peroxide and malondialdehyde (MDA) contents

Contents of oxidative stress markers H₂ O₂ and MDA were estimated spectrophotometrically from fresh shoot tissues of control and BM plants treated with CuNPs at concentrations of 40 and 100 mg l⁻¹ for 10 days. All experiments were performed in triplicate.

H₂ O₂ contents of shoots were determined spectrophotometrically according to Loreto and Velikova [26]. 100 mg of tissues were homogenised in an ice bath with 5 ml of 0.1% (w/v) trichloroacetic acid (TCA) and the homogenate was centrifuged at 12,000 g for 15 min. The reaction mixture consisted of 0.5 ml of the supernatant in 0.5 ml of 10 mm potassium phosphate buffer (pH 7.0) and 1 ml of 1M KI. The absorbance was measured at 390 nm. The content of H₂ O₂ was calculated by comparison with a standard calibration curve previously made by using different concentrations of H₂ O₂ and was expressed as μM g⁻¹ fresh weight.

MDA as an end product of lipid peroxidation was estimated by the thiobarbituric acid (TBA) test [27]. 100 mg of tissue was homogenised in 5 ml of 0.1% (w/v) TCA solution and the homogenate was centrifuged at 12,000 g for 15 min. 0.5 ml of the supernatant was added to 1 ml of 0.5% (w/v) TBA in 20% TCA. The mixture was incubated in boiling water for 30 min, and the reaction was stopped by placing the reaction tubes in an ice bath. Then the samples were centrifuged at 10,000 g for 5 min, and the absorbance of the supernatant was measured at 532 nm, subtracting the value for non‐specific absorption at 600 nm. The amount of MDA‐TBA complex (red pigment) was calculated from the extinction coefficient Ɛ  = 155 mM⁻¹ cm⁻¹. Results were expressed as μM g⁻¹ fresh weight.

2.11 Assay of phenylalanine ammonia lyase (PAL) and antioxidant enzymes

Activities of PAL and anti‐oxidant enzymes catalase (CAT), ascorbate peroxidase (APX) and superoxide dismutase (SOD) were estimated from fresh leaves and stems of control and BM plants treated with CuNPs at concentrations of 40 and 100 mg l⁻¹ for 10 days. For PAL assay, 1 gm of fresh tissue was homogenised at 4°C with 5 ml 0.05 M Tris–HCl buffer, pH 8.0 containing 0.8 mM β‐mercaptoethanol and 1% (w/v) polyvinyl‐pyrrolidone (PVP). The homogenate was centrifuged at 18,000 × g for 15 min at 4°C and the supernatant was used to measure PAL activity [28]. For CAT, APX and SOD assays, 1 gm of fresh plant material was homogenised in 3 ml ice‐cold extraction buffer consisting of 50 mM Na₂ PO₄, 1 mM EDTA and 0.1% PVP, pH 7.0 at 4°C. The extract was centrifuged at 10,000 rpm at 4°C for 10 min and the supernatant was stored at −20°C till further use. The enzyme concentrations were expressed in terms of total protein concentration. Quantification of total protein was done by the method of Bradford [29]. To 50 μl of the extract diluted to 1 ml with extraction buffer, 5 ml of Coomassie brilliant blue G‐250 was added and mixed thoroughly. The absorbance was read spectrophotometrically at 595 nm against a reagent blank. The standard curve was prepared with bovine serum albumin in the concentration range of 10–100 μg/ml.

PAL activity was measured by the trans‐cinnamic acid method [28]. The enzyme reaction mixture consisted of 1 ml 0.05 M Tris–HCl buffer, pH 8.0, 0.1 ml enzyme extract, 0.5 ml of 10 mM L‐phenylalanine and distilled water to a total volume of 3 ml. After 1 h incubation at 37°C, the reaction was stopped by the addition of 0.1 ml 1N HCl and the absorbance was read spectrophotometrically at 290 nm. The standard curve was made using trans‐cinnamic acid. The enzyme activity was expressed in U mg⁻¹ protein (U  = amount of enzyme required for the formation of 1 μM of trans‐cinnamic acid per min).

For the assay of CAT, the reaction mixture consisted of 2.5 ml 100 mM phosphate buffer, pH 7.0, 0.1 ml of 10 mM H₂ O₂ and 0.2 ml of enzyme extract. Catalase activity was estimated spectrophotometrically as decrease in absorbance at 240 nm due to decomposition of H₂ O₂ by catalase. The results were expressed as U mg⁻¹ of protein (U  = decomposition 1 mM of H₂ O₂ min⁻¹) [30].

APX activity was determined in a reaction mixture containing 50 mM phosphate buffer (pH 7.0), 0.6 mM ascorbic acid and enzyme extract. The reaction was started by adding 10 μl of 10% H₂ O₂. The decrease in absorbance due to the reaction was recorded spectrophotometrically at 290 nm for 3 min. Enzyme activity was expressed as U mg⁻¹ protein (U  = change in 0.1 absorbance min⁻¹) [31].

SOD activity was assayed by the NBT method [32]. 20 μl of the enzyme extract was added to 3 ml of 50 mM sodium phosphate buffer, pH 6.8 and mixed with 2.7 ml 13 mM methionine, 100 μl 75 μM nitroblue tetrazolium and 100 μl 0.1 μM EDTA. The reaction was started by the addition of 100 μl riboflavin to the mixture under 4000 Lx candescent lamp and the rate of increase in absorbance at 560 nm was measured spectrophotometrically for 15 min. Enzyme activity was expressed as U mg⁻¹ protein (U  = SOD enzyme that inhibited 50% of NBT reduction). All experiments were performed in triplicate.

2.12 Estimation of CuNP‐cupric ion concentrations

The concentration of Cu²⁺ ions in the medium and the accumulation of CuNPs in the plant samples after 10 days was determined from plants treated with CuNPs at concentrations of 40 and 100 mg l⁻¹. The plant samples were washed thoroughly with distilled water to remove all residual medium and oven dried at 70°C for 24 h. 50 mg of the plant matter was digested with 4 ml plasma pure HNO₃ (65%) and H₂ O₂ (30%) (1:4) by heating in a water bath at 100°C till all organic matter was completely digested. The final volume was adjusted to 10 ml with double distilled water. The concentrations of Cu²⁺ ions in the medium as well as in the plant samples were determined using inductively coupled plasma‐atomic emission spectroscopy (ICP‐AES, Perkin‐Elmer 1100B, USA) [33].

Nanoparticle concentrations in plant tissue were determined based on a relationship between the CuNP suspension and Cu²⁺ ions. CuNPs were dissolved in 65% HNO₃ at concentrations of 5, 10 and 20 mg l⁻¹ and the concentrations of Cu²⁺ ion extracted were determined by ICP‐AES. A linear graph was constructed and the CuNP concentrations were calculated based on the relationship between the concentrations of CuNPs and Cu²⁺ ions [34]. All experiments were performed in triplicate.

2.13 Statistical analysis

All experiments were conducted in triplicate. Data are expressed as mean ± standard error of mean (S.E.M.). Differences between groups were analysed by one‐way analysis of variance followed by post‐hoc Student's t ‐test to compare significant groups, using MS‐Excel. The differences between groups were considered statistically significant at a probability of p  ≤ 0.05.

3 Results and discussion

3.1 Synthesis of CuNPs

CuNPs were prepared by a chemical method using easily available, inexpensive and biocompatible chemicals: ascorbic acid as a reductant for cupric sulphate pentahydrate as well as an antioxidant, and starch as the capping agent. The characteristic copper‐pink colour of the solution indicated the formation of metallic copper nanoparticles. Starch was chosen as a non‐toxic capping agent so that the effect on the plants is solely due to the copper or copper oxide present in the nanoparticles.

3.2 Characteristics of CuNPs

The UV–visible absorbance spectrum of CuNPs in distilled water after 3 h is shown in Fig. 1. No absorbance in the visible range is observed while distinct bands are observed at ∼205, 215, 230, 250, 275 and 285 nm according to Mie's theory (dipole oscillation) [35]. The exact position of the plasmon absorption band is a function of stability (pH, solvent type and stabilising agent) and particle size [36]. In this case, CuNPs demonstrated no surface plasmon resonance. This could be attributed to a combination of small particle size preventing aggregation or a thin copper oxide layer around the copper nanoparticles [37]. Usually, for CuNPs ranging between 10 and 40 nm in diameter, the plasmon resonance appears around 560 nm. However, the absorption spectra of small metal particles (diameter <20 nm) depend only on the dipole oscillation and do not evidence surface plasmon resonance [36].

Fig. 1.

The ultraviolet‐visible spectrum of starch‐stabilized copper nanoparticles after 3 hours

The HRTEM micrographs of the CuNPs are shown in Fig. 2. As per HRTEM micrographs the CuNPs were approximately spherical in shape, polydispersed with a diameter between 2 and 20 nm.

Fig. 2.

HRTEM image of CuNPs. Particles were approximately spherical, polydispersed with a diameter in the range of 2–20 nm

The FTIR spectrum of the CuNPs is shown in Fig. 3 and the band assignments are mentioned in Table 1. The deep trough around 3412 cm⁻¹ was assigned to the OH stretching vibrations from starch. The bands at 668, 611, 576, 527 and 472 cm⁻¹ are assigned to the vibration of Cu in the Cu(II)–O form and the band at 1383 cm⁻¹ to Cu²⁺ O² [38]. The band at 1338 cm⁻¹ could be due to O–C–O⁻ and also due to S = O sulfone from residual CuSO₄. The bands at 935, 860, 795, 764, 710, 668 and 576 cm⁻¹ are assigned to the out of plane CH vibrations of the anhydroglucose ring of starch [39]. It appears that desiccation and exposure to air cause oxidation of the Cu in the nanoparticles to cuprous/cupric oxide.

Fig. 3.

FTIR spectrum of starch‐stabilised CuNPs

Table 1.

Assignments of the characteristic peaks of starch‐stabilised CuNPs

Wave number, cm−1	%T	Assignment
3414–3409	21.7	OH stretch
2925	33.23	CH2
1638	33.26	C = C stretch
1426	33.89	O‐C‐O− stretch
1383	34.10	Cu2+ O2− stretch
1373	34.07	CH2 and CH3
1338	34.97	S = O sulfone/O–C–O− stretch
1281	36.75	C–O stretch
1242	36.24	C–O stretch
1156	26.40	C–O stretch
1079	23.46	C–O stretch
1024	21.31	C–O stretch
935	37.24	C–H out of plane
860	40.08	C–H out of plane
795	40.16	C–H out of plane
764	38.41	C–H out of plane
710	38.51	C–H out of plane
668	39.30	#C–H bend/Cu(II)–O
611	38.02	#C–H bend/Cu(II)–O
576	37.26	#C–H bend/Cu(II)–O
527	38.87	Cu(II)–O
472	40.11	Cu(II)–O

The XRD pattern of the nanoparticles is shown in Fig. 4.

Fig. 4.

XRD pattern of the Cu and Cu₂ O nanoparticles

Peaks observed at 2ɵ values of 43.25°, 50.44° and 74.19° correspond to (111), (200) and (220) planes of metallic Cu. These three peaks were close to those of the standard JCPDS Card No. 04‐0836 for the standard spectrum of the pure fcc (face‐centred cubic) metallic Cu. Besides the metallic Cu peaks, several other diffraction peaks appeared at 29.63°, 36.38°, 42.32°, 61.37° and 73.57° corresponding to (110), (111), (200), (220) and (311) planes of cuprite, respectively, indicating the formation of cubic copper (I) oxide nanocrystals [40, 41]. XRD peaks observed for cuprite were consistent with the standard powder diffraction card of bcc (body‐centred cubic) cuprite (JCPDS No. 05‐667) [42]. The XRD diffraction pattern showed the coexistence of two crystalline phases, i.e. metallic Cu and copper (I) oxide (Cu₂ O). This indicates that the zero‐valent metallic CuNPs formed by chemical reduction are readily oxidised due to the low stability of metallic Cu [43] resulting in the formation of Cu₂ O [44]. All the nanocubes were of Cu and Cu₂ O; no other phase of copper oxide (i.e. CuO) was detected. The peak broadening in the XRD pattern indicates the presence of small nanocrystals [45]. The mean crystallite size as calculated from Scherrer's equation was found to be 14.09 nm.

The mean zeta potential of the CuNPs in distilled water was found to be −7.57 ± 8.64 mV and in Hoagland's nutrient medium was found to be −5.03 ± 13.5 mV. The low negative zeta potential may be due to the substantial starch capping on the CuNPs. The concept of zeta potential is useful to understand and predict the interaction between particles in suspension and has been used to study cell adhesion which is related to surface charge properties [46]. It is known that particles in suspension that have a large negative or positive zeta potential (beyond ± 30 mV) tend to repel each other and there is no tendency to flocculate. However, in case of low zeta potential, as is seen here, there is no force to prevent the particles from coming together and flocculating. However, particles with negative zeta potential are considered to be stable. It is expected that stability of colloidal CuNPs of zeta potential less than −20 mV will result from steric stabilisation of the particles by the macromolecular compounds, which, in this case, is starch [47].

3.3 Effect of CuNPs on secondary metabolism of B. monnieri

Treatment of B. monnieri with CuNPs was found to result in a significant increase in the content of secondary metabolites in a concentration‐dependent manner till toxic concentration was reached when the secondary metabolism gradually declined. Such a pattern is called hormetic effect. However, the NPs did not cause the death of the plants till a concentration of 100 mg l⁻¹ after 10 days. It must be mentioned that treatment of B. monnieri plants with cupric sulphate pentahydrate showed a much higher degree of toxicity and caused the death of the plants at a dose of 5 mg l⁻¹ within 24 h.

The effect of CuNPs on TSC is shown in Fig. 5. The increase in TSC was significant at a concentration of 5 mg l⁻¹, reached a maximum of about 89% at 30 mg l⁻¹ and remained significantly high till 100 mg l⁻¹, declining to about 39%.

Fig. 5.

Effect of CuNPs on TSC of Bacopa monnieri whole plants. Data represent mean ± S.E.M. (n = 3). Differences were considered statistically significant at p ≤ 0.05

The effect on TAC is shown in Fig. 6. The increase in TAC was significant at a concentration of 5 mg l⁻¹, reached a maximum of about 204% at 40 mg l⁻¹ and remained significantly high till 75 mg l⁻¹, declining below control at 100 mg l⁻¹.

Fig. 6.

Effect of CuNPs on TAC of Bacopa monnieri whole plants. Data represent mean ± S.E.M. (n = 3). Differences were considered statistically significant at p ≤ 0.05

The effect on TPC is shown in Fig. 7. The increase in TPC was significant at a concentration of 5 mg l⁻¹, reached a maximum of about 116% at 20 mg l⁻¹ and remained significantly high till 75 mg l⁻¹, declining to about 12% at 100 mg l⁻¹. It appears that the phenolic biosynthetic pathway in BM is more sensitive to the toxic effect of the CuNPs than the others.

Fig. 7.

Effect of CuNPs on TPC of Bacopa monnieri whole plants. Data represent mean ± S.E.M. (n = 3). Differences were considered statistically significant at p ≤ 0.05

The effect on TFC is shown in Fig. 8. The increase in TFC was significant at a concentration of 5 mg l⁻¹, reached a maximum of about 140% at 40 mg l⁻¹ and remained significantly high till 75 mg l⁻¹, declining to below control at 100 mg l⁻¹.

Fig. 8.

Effect of CuNPs on TFC of Bacopa monnieri whole plants. Data represent mean ± S.E.M. (n = 3). Differences were considered statistically significant at p ≤ 0.05

The effect on DRSC is shown in Fig. 9. The increase in DRSC was significant at a concentration of 5 mg l⁻¹, reached a maximum of about 70% at 40 mg l⁻¹ and remained significantly high till 75 mg l⁻¹, declining to about 1% at 100 mg l⁻¹.

Fig. 9.

Effect of CuNPs on DRSC of Bacopa monnieri whole plants. Data represent mean ± S.E.M. (n = 3). Differences were considered statistically significant at p ≤ 0.05

3.4 Effect of CuNPs on hydrogen peroxide and MDA contents of B. monnieri

The effect of CuNPs on the content of oxidative stress markers H₂ O₂ and MDA in shoots of B. monnieri plants are shown in Fig. 10. The contents of H₂ O₂ and MDA were found to show significant increase over control levels in a concentration‐dependent manner, indicating that the CuNPs in B. monnieri act by generating ROS and the amount of ROS generated increased consistently with increasing concentration.

Fig. 10.

Effect of copper‐based nanoparticles on

(a) Hydrogen peroxide, (b) Malondialdehyde contents of Bacopa monnieri shoots. Data represent mean ± S.E.M. (n  = 3). Differences were considered statistically significant p  ≤ 0.05

H₂ O₂ is a key ROS molecule having a central role in signal transduction in a plant system due to a relatively long half‐life (1 ms) and its small size which allows traversing through cellular membranes and migration in different compartments. It plays a key role in biotic and abiotic stress response through antioxidant defence systems [48]. MDA is an indicator of lipid peroxidation, which in turn is indicative of the extent of oxidative damage.

Copper is an essential micronutrient, which is incorporated in many proteins and enzymes, thereby playing an important role in plant health and nutrition. However, as demonstrated in Nicotiana tabacum L. cv. BY‐2 cells, presence of excess Cu in the form of CuO NPs caused enhanced generation of ROS such as H₂ O₂ and OH ^. through the disruption of the electron transport chain, finally resulting in membrane damage through lipid peroxidation, as indicated by increased MDA and lactate dehydrogenase contents [49]. CuNPs have been shown to cause ROS generation leading to membrane lipid peroxidation in several other plant species including Brassica napus [50], Brassica juncea [51], Cucumis sativus [52], Oryza sativa [53] and Coriandrum sativum [54]. Similar results were observed in B. monnieri.

3.5 Effect of CuNPs on PAL and anti‐oxidant enzymes of B. monnieri

The effects of CuNPs on PAL and antioxidant enzymes CAT, APX and SOD are mentioned in Table 2. The effect of CuNPs on PAL and antioxidant enzymes reveals a similar trend to that of secondary metabolism with an increase of PAL, CAT, APX and SOD levels by ∼91, 90, 147 and 117% in leaves and by ∼88, 95, 122 and 95% in stems, respectively, at CuNP concentrations of 40 mg l⁻¹, decreasing to near control levels at 100 mg l⁻¹. While the others are antioxidant enzymes, PAL is the first enzyme of the general phenylpropanoid pathway that catalyses the deamination of phenylalanine to cinnamic acid and plays a key role in diverting aromatic amino acids from primary metabolism to the phenylpropanoid pathway of secondary metabolism [55]. This indicated that CuNPs in B. monnieri functioned as in other plant systems by generating ROS which activated secondary metabolism as well as the anti‐oxidant defence enzymes.

Table 2.

Effect of CuNPs on PAL and anti‐oxidant enzymes of B. monnieri

CuNP conc.,	Phenylalanine ammonia lyase		Catalase		Ascorbate peroxidase		Superoxide dismutase
mg l−1	(U mg−1) TP		(U mg−1) TP		(U mg−1) TP		(U mg−1) TP
	Leaves	Stems	Leaves	Stems	Leaves	Stems	Leaves	Stems
0	1.56 ± 0.22	0.67 ± 0.12	82.2 ± 7.6	47.5± 5.1	1.7 ± 0.21	2.2 ± 0.32	3.5 ± 0.51	2.1 ± 0.25
40	2.98 ± 0.41*	1.26 ± 0.18*	155.6 ± 9.2*	92.7 ± 8.7*	4.2 ± 0.35*	4.9 ± 0.46*	7.6 ± 0.54*	4.1 ± 0.31*
100	1.77 ± 0.34	0.74 ± 0.23	85.7 ± 5.3	50.4 ± 6.1	2.2 ± 0.4	2.5 ± 0.52	4.2 ± 0.53	2.4 ± 0.21

Data represent mean ± S.E.M. (n  = 3). Differences were considered statistically significant at p  ≤ 0.05.

It has been shown in different species that increased CuNP‐mediated increase in ROS levels lead to the activation of enzymatic and non‐enzymatic antioxidant defence mechanisms.

Antioxidant enzymes such as CAT, APX, SOD and glutathione reductase are activated by CuNPs as reported in many plant species such as Brassica napus [50], Brassica juncea [51], Cucumis sativus [52], Oryza sativa [53] and Saccharum officinarum [56]. Zhao et al. [57] reported that in Zea mays, expression of genes for antioxidant enzymes, POD 1 and GST 1 increased significantly at a Cu(OH)₂ nanopesticide dose of 10 mg but declined at 100 mg. CATs dismutase H₂ O₂ to H₂ O and O₂ while the SODs catalyse the conversion of superoxides to H₂ O₂. APX is an important enzyme of the ascorbate‐reduced glutathione cycle and plays a key role in catalysing the conversion of H₂ O₂ into H₂ O, using ascorbate as a specific electron donor [58]. Decline in enzyme content at toxic concentrations is regarded as a general stress response and is supposedly due to inhibition of enzyme synthesis or dysfunction in the assembly of enzyme subunits [59].

3.6 Bioaccumulation of Cu in B. monnieri plants

A direct linear relationship was found between the concentration of CuNPs in suspension and that of Cu²⁺ ions extracted from them as determined by ICP‐AES, where CuNP = 0.066 Cu²⁺ ions (R ²  = 0.98). The concentration of Cu²⁺ ions in Hoagland's medium treated with CuNPs at concentrations of 40 and 100 mg l⁻¹ for 10 days was found to be 58.78 ± 2.32 and 228.82 ± 3.28 mg l⁻¹ which translates to a CuNP breakdown concentration of 3.87 ± 0.153 mg l⁻¹ (9.69%) and 15.10 ± 0.216 mg l⁻¹ (15.1%), respectively. This indicates that the CuNPs are quite stable in Hoagland's medium, presumably due to the substantial starch capping, and the effect on the plants is largely due to the uptake of CuNPs rather than copper ions.

The concentration of Cu²⁺ ions in B. monnieri plants treated with CuNPs was found to be 224.62 ± 3.45 and 1120.45 ± 5.32 mg kg⁻¹ for concentrations of 40 and 100 mg l⁻¹, respectively. The bioavailability of the CuNPs to the plants was estimated by calculating the bioaccumulation factor defined as the CuNP concentration in the plants (mg kg⁻¹ dry weight) divided by the CuNP concentration in the medium (mg l⁻¹) and was found to be 5.61 and 11.2 lkg⁻¹ when they were exposed to CuNP concentrations of 40 and 100 mg l⁻¹, respectively. Bioavailability is a function of several factors including nanoparticle size, concentration and surface area of exposure. In the present study, the size of the CuNPs was very small (<20 nm) but the surface area of exposure was moderate as B. monnieri plants do not develop profuse roots, resulting in moderate bioaccumulation levels [34].

As mentioned earlier, CuNPs were found to exert their effects in B. monnieri, as in most plants, by the generation of ROS, which activates the enzymatic and non‐enzymatic antioxidant defence mechanism including secondary metabolic pathways [13]. This was indicated by the rise in H₂ O₂ and MDA levels as well as hormetic enhancement of the activities of the secondary metabolism regulating enzyme PAL and anti‐oxidant enzymes CAT, APX and SOD. Metallic CuNPs, except in inert atmosphere, tend to become readily oxidised to Cu₂ O or CuO NPs which are assumed to have a greater toxicological effect on plants. It has been reported in Arabidopsis thaliana that the acute toxicity effects are due to dissolved Cu²⁺ ions while the chronic effects are due to intracellular nanoparticles [60]. Upregulation of 47 oxidative stress genes due to CuO NP (10 and 20 mg/l) stress was reported in Arabidopsis thaliana [61].

Depending on the delicate balance between ROS generation and scavenging, ROS may cause oxidative damage or act as cellular signalling molecules in plants. The ROS signal can first activate phospholipase C (PLC), which hydrolyses phosphatidylinositol 4, 5 biphosphate (PIP₂) to generate inositol triphosphate (IP₃) and diacylglycerol (DAG). IP₃ diffuses into the cytosol and subsequently releases Ca²⁺ ions from intracellular Ca²⁺ stores, resulting in a spike of Ca²⁺ ions in the cytosol. The increased Ca²⁺ concentration is sensed by calcium‐binding proteins (CaBP, calcium sensor) or directly by calcium‐dependent protein kinases (CDPK). These sensors decode and relay the information downstream to initiate a phosphorylation cascade including the mitogen‐activated protein kinase (MAPK). MAPK phosphorylation and activation of downstream transcription factors like WRKY by alteration of phosphorylation status generally lead to the transcriptional upregulation of secondary metabolism genes in plants [13, 62, 63, 64]. ROS are thought to modulate secondary metabolism either directly or by acting as signals for other inducers like jasmonic acid (JA), salicylic acid, ethylene, nitric oxide and brassinosteroids. The biosynthesis of many of the secondary metabolites is mediated through (methyl) jasmonate [(Me)Ja)], a plant hormone produced in response to stress [65]. CuO NPs were reported to affect the JA and glucosinolates pathways in Arabidopsis [66]. The different secondary metabolites are structurally and functionally different and follow different biosynthetic pathways. This may explain the slightly different concentration‐dependent effects of the CuNPs on the biosynthesis of the different secondary metabolites. Saponin and flavonoid concentrations along with DRSC are measures of the antioxidant capacity of the plant.

4 Conclusions

The present study shows that chemically synthesised starch‐stabilised CuNPs of diameter <20 nm, on hydroponic treatment for 10 days, caused a significant increase in the total content of secondary metabolites viz. saponins, alkaloids, phenolics, flavonoids and DRSC of B. monnieri whole plants from a concentration of 5 mg l⁻¹ up to about 40 mg l⁻¹. After this the secondary metabolism declined, presumably due to metabolic toxicity. In the case of phenolics the total content was found to decline after a CuNP concentration of 20 mg l⁻¹. However, the content of saponins remained significantly high up to a CuNP concentration of 100 mg l⁻¹, while all the other secondary metabolites remained significantly high up to 75 mg l⁻¹. The results could be correlated with the increase in ROS species like H₂ O₂ and MDA and hormetic effect on secondary metabolism regulating enzyme PAL and antioxidant enzymes CAT, APX and SOD.

The study shows that at sub‐toxic concentrations, CuNPs of <20 nm diameter, presumably due to their high degree of cell penetrability, can act as an efficient abiotic stress agent to induce a defence response in B. monnieri plants which translates into enhanced biosynthesis of medicinally valuable secondary metabolites. This also enhances the free‐radical scavenging capacity, i.e. antioxidant activity of the plant. These findings may have commercial application in the pharmaceutical industry.