Application of CuNPs and AMF alleviates arsenic stress by encompassing reduced arsenic uptake through metabolomics and ionomics alterations in Elymus sibiricus

Abstract

Recent studies have exhibited a very promising role of copper nanoparticles (CuNPs) in mitigation of abiotic stresses in plants. Arbuscular mycorrhizae fungi (AMF) assisted plants to trigger their defense mechanism against abiotic stresses. Arsenic (As) is a non-essential and injurious heavy-metal contaminant. Current research work was designed to elucidate role of CuNPs (100, 200 and 300 mM) and a commercial inoculum of Glomus species (Clonex^® Root Maximizer) either alone or in combination (CuNPs + Clonex) on physiology, growth, and stress alleviation mechanisms of E. sibiricus growing in As spiked soils (0, 50, and 100 mg Kg^{- 1} soil). Arsenic induced oxidative stress, enhanced biosynthesis of hydrogen peroxide, lipid peroxidation and methylglyoxal (MG) in E. sibiricus. Moreover, As-phytotoxicity reduced photosynthetic activities and growth of plants. Results showed that individual and combined treatments, CuNPs (100 mM) as well as soil inoculation of AMF significantly enhanced root growth and shoot growth by declining As content in root tissues and shoot tissues in As polluted soils. E. sibiricus plants treated with CuNPs (100 mM) and/or AMF alleviated As induced phytotoxicity through upregulating the activity of antioxidative enzymes such as catalase (CAT) and superoxide dismutase (SOD) besides the biosynthesis of non-enzymatic antioxidants including phytochelatin (PC) and glutathione (GSH). In brief, supplementation of CuNPs (100 mM) alone or in combination with AMF reduced As uptake and alleviated the As-phytotoxicity in E. sibiricus by inducing stress tolerance mechanism resulting in the improvement of the plant growth parameters.

Keywords: Arsenic toxicity; Nanoparticles; Oxidative stress; Stress markers; Stress mitigation.

Fig. 1

Flow sheet diagram of synthetic route for preparation of copper nanoparticles by co-precipitation method

Fig. 2

Synthesis of CuO-NPs

Fig. 3

Characterization of copper oxide nanoparticles (CuNPs). (A) Scanning electron micrograph (SEM) for CuNPs, (B) Energy dispersive X-Ray (EDX) graph for CuONPs, (C) Fourier transform infrared (FTIR) spectra for CuNPs

Fig. 4

Effect of CuNPs and mycorrhiza association on (A) total chlorophyll, (B) quantum efficiency of PSII (Φ PSII) and (C) performance index of chlorophylls in Elymus sibiricus under arsenic stress. Graph bars represents mean value of three replicates. Error bars shows standard error and different letters above bars obtained after Tukey’s HSD test, represents mean values are significantly different at p < 0.05

Fig. 5

Effect of CuNPs and mycorrhiza association on (A) malondialdehyde, (B) hydrogen peroxide and (C) superoxide anions in Elymus sibiricus under arsenic stress. Graph bars represents mean value of three replicates. Error bars shows standard error and different letters above bars obtained after Tukey’s HSD test, represents mean values are significantly different at p < 0.05

Fig. 6

Effect of CuNPs and mycorrhiza association on electrolytic leakage of Elymus sibiricus under arsenic stress. Graph bars represents mean value of three replicates. Error bars shows standard error and different letters above bars obtained after Tukey’s HSD test, represents mean values are significantly different at p < 0.05

Fig. 7

Effect of CuNPs and mycorrhiza association on activity of (A) superoxide dismutase, (B) ascorbate peroxidase and (C) catalase in Elymus sibiricus under arsenic stress. Graph bars represents mean value of three replicates. Error bars shows standard error and different letters above bars obtained after Tukey’s HSD test, represents mean values are significantly different at p < 0.05

Fig. 8

Effect of CuNPs and mycorrhiza association on activity of (A) glutathione reductase, (B) glutathione peroxidase and (C) glutathione transferase in Elymus sibiricus under arsenic stress. Graph bars represents mean value of three replicates. Error bars shows standard error and different letters above bars obtained after Tukey’s HSD test, represents mean values are significantly different at p < 0.05

Fig. 9

Effect of CuNPs and mycorrhiza association on non-enzymatic antioxidants (A) ascorbic acid and (B) glutathione content in Elymus sibiricus under arsenic stress. Graph bars represents mean value of three replicates. Error bars shows standard error and different letters above bars obtained after Tukey’s HSD test, represents mean values are significantly different at p < 0.05

Fig. 10

Effect of CuNPs and mycorrhiza association on (A) As uptake in root (B) As uptake in shoot and (C) translocation factor in Elymus sibiricus under arsenic stress. Values presented in the graphs are average of three replicates

Fig. 11

Pearson’s correlation to assess the effect of CuNPs and mycorrhiza association on various attributes of Elymus sibiricus under arsenic stress. Various abbreviations used are; T chl = total chlorophyll, PI = performance index, fv/fm = quantum efficiency of PSII, MDA = malondialdehyde, H₂O₂ = hydrogen peroxide, O₂^•‾ = superoxide anion, EL = electrolytic leakage, SOD = superoxide dismutase, CAT = catalase, APX = ascorbate peroxidase, GST = glutathione transferase, GPX = glutathione peroxidase, GR = glutathione reductase, AsA = ascorbic acid and GSH = glutathione

Fig. 12

Principle component analysis (PCA biplot; dots represents PCA of individual treatment while arrows represents PCA of all parameters) to assess the effect of CuNPs and mycorrhiza association on various attributes of Elymus sibiricus under arsenic stress. (Various abbreviations used are same as in Fig. 11