Background

In the intervening days, one of the most critical threatens to plant life and biosphere is the emerging surfactant pollutants. Surfactants are chemically synthesized products mostly derived from petroleum compounds [1] and characterized by their active properties in reducing surface tension or interfacial tension between two heterogeneous phases, thus have been used in massive applications of life sectors, ranging from food industries, pharmaceuticals, agrochemicals, and households [2, 3]. More crucially, the production of these surfactants is rapidly growing and is expected to exceed 50 billion dollars within few years due to the high demand of surfactant products like hand sanitizer and disinfectants during COVID-19 pandemic [4]. Surfactants are classified into anionic, cationic, nonionic, and amphoteric composites according to the electrolytic charge of the hydrophilic group [5]. Surfactants contain a polar head group attached with nonpolar hydrocarbon tail and being highly hydrophobic accelerate their pernicious diffuse in marines and surrounding environments [6]. Currently, it was shown that about 60% of surfactant residues contaminate the aquatic sides in significant concentrations [7]. Releasing wastes polluted with large amounts of synthetic surfactants into the water surfaces and nearby agricultural soils jeopardizes the plant community and ecosystem [8].

Sodium dodecyl sulfate (SDS, molecular formula: C12H25SO4Na, and molecular weight: 288.38 g/mol with hydrophobic hydrocarbon chain of 12 carbon atoms); is a type of negative charged anionic surfactant integrated in almost everyday products such as household cleaners, domestic detergents, and cosmetics due to its micellization behavior [8]. It is the most common surfactant extensively utilized in industries for its great emulsifying and fizzing qualities in cost-effective manner. SDS and anionic surfactants can change macromolecules structure and induce disfunction by binding to DNA, enzymes and peptides [9]. Moreover, they bind to plant cell wall molecules such as proteins and phospholipids and consequently alter membrane rigidification and impair its biological function [10]. Recent ecotoxicological studies proved that by continuous evoke of surfactants into the environment in heightened levels, the accumulation of SDS can induce oxidative burst in plants which may devastate cellular redox homeostasis and consequently physiological and biochemical complexes [11]. This eventually exacerbates plant dynamics growth and concomitant humane health through food chain. A crucial question is how plants can deal with all pollution burdens such as surfactants, particularly when combined with other problematic issues restricting plant growth such as soil salinization or alkalinization.

As the exposure of plants to SDS and other pollutants become frequent and a contaminant concern, The World Health Organization (WHO) has set the optimum permissible level of surfactant in water supplies not to exceed 0.2 mg/L [12] however, surfactant was formerly detected to exceed 400 mg/L in wastewater from manufacturing industries [13]. Thus, the current legislations require monitoring the acute toxic effect of the micropollutants to protect the environment and humane safety. It is important to evaluate the effects of pollutant type and concentration on plants performance and treat hazardous pollution on SDS-rich soils where plants grow.

In this regard, innovative strategies have been introduced to manage the severity of pollutant noxiousness including scavenging or removal by using different approaches. Among these methods, H2O2 has gained an increasing attention as a promising cytoprotective motivator toward multi-tolerance adaption mechanisms such as excess temperatures, drought, salinity, heavy metals, light, and UV stresses in numerous plant species [14,15,16]. In conserved plant systems, the accumulation of reactive oxygen species (ROS) is well known to be correlated with various cellular metabolic reactions under stressful conditions. Overproduction of ROS compartments like H2O2 can disrupt the biochemical and physiological pathways in multiple sites within the plant cell, which can lead to permanent cell rupture and programmed cell death [17, 18]. Importantly and in contrary to the classical concepts, plants have progressed several mechanisms to switch ROS signaling components under certain low levels to regulate wide variety of plant pathways, including cell growth and development, and balance adaptive responses to environmental stresses [19, SDS assay

In reference to the methodology of Hayashi [61], SDS analysis was pursued in plant samples and growth media by Methylene Blue Active Substrate (MBAS) protocol. SDS level was assessed by the methylene blue colorimetric assay at wavelength is 655 nm with sensitivity of 0–6 μg of SDS against pure chloroform as a blank sample. The extinction coefficient at 655 nm is of the SDS-methylene blue salt.

Accumulation and translocation of SDS

The bioaccumulation factor (BCF), translocation factors (TCF), and % Removed SDS as described by [23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62] were applied to evaluate the phytoextraction efficiency of plants as follow:

Bioaccumulation factor: SDS concentration in the roots/SDS concentration in medium.

Translocation factor: SDS concentration in the leaves/SDS concentration in the roots.

% Removed SDS: SDS uptake by root/Added medium SDS.

Growth stress indices parameters determination

At the end of the experiment, from the obtained data of lengths, and fresh and dry mass of plantlets, the stress tolerance index was calculated. The plant length stress tolerance index (PHSI), plant dry matter stress tolerance index (PDSI), and fresh matter stress tolerance index (PFSI) were determined according to Nawaz [63] as follow: -.

PHSI (%) = [The length of treated plantlets/the length of control plantlets] × 100.

PDSI (%) = [Dry matter of treated plantlets/dry matter of control plantlets] × 100.

PFSI (%) = [Fresh weight of treated plantlets/fresh weight of control plantlets] × 100.

Determination of pigment contents

The contents of photosynthetic pigments; chlorophyll a (Chl a), chlorophyll b (Chl b), and carotenoids were executed as formerly described by Lichtenthaler [64]. Prior to determination of leaf pigments, fresh leaves were separated from the main culm and sampled. Then, immersed in test tubes containing 5 ml of 95% ethyl alcohol and heated in water bath at 60–70 °C for 30 min. The OD of samples was recorded via spectrophotometer at 663 and 644 nm for Chl a and Chl b, respectively. The carotenoid concentration was also determined by using the same plant extract and measuring the absorbance at 470 nm. The final calculations for chlorophyll and carotenoid content (mg/g FW) were performed using equations based on Lichtenthaler [64].

Transpiration rate

As specified by Bozcuk [65], transpiration rate (TP) was measured. The daily transpiration rate (TP, g day− 1) per container was estimated via using the volumetric method. During the analysis, the transpiration rate (TP) on day i (g), the volume (Vi) of the entire container after loss compensation on day i (g), and the volume (Vi + 1) of the entire container before loss compensation on day i + 1 (g) was registered. Compensation was carried out by substituting the same lost amount of water through transpiration (i.e., TP). TP was assessed using the introduced formula:

$$\textrm{TP}={\textrm{V}}_{\textrm{i}}+{\textrm{V}}_{\textrm{i}+1}$$

Leaf stomatal conductance

Leaf stomatal conductance was estimated adopting equation recommended by Dawood and Abeed [66] in which stomatal conductance is expressed as the reverse of the stomatal resistance. The stomatal resistance measured from the following equation which displayed by Slatyer and Markus [67] and as modified by Abeed et al. [68]

$$T=\frac{Cleaf- Cair}{r\ leaf+ rair}=\frac{0.622p}{p}x\ \frac{eleaf- eair}{rleaf+ rair}$$

where rleaf + rair = r. is the total (stomatal) resistance at the leaf-air interface, then

$$r.\left(\frac{\mathit{\sec}}{cm}\right)=\frac{0.622p}{p}\times \frac{eleaf- eair}{t}$$

Where: T. = transpiration rate (mg H2O/cm2/sec), r. = total stomatal resistance (sec/cm), Cleaf = the level of water vapor in leaf (absolute humidity) (mg/cm3), Cair = the level of water vapor in air (mg/cm3), eleaf = the vapor pressure inside leaf (mm Hg), eair = the vapor pressure of air (mm Hg).

Δe = eleaf - eair is the difference in vapor force between leaf and air bulk outside. The value 0.622 p/p. is a constant conversion factor to modify from Δc (cleaf- cair) to Δe. It has a value of nearly 106, so 1 mm of vapor force is equivalent to about 1 mg of water vapor for each liter of air. In the case of most of stomata are on one leaf side, r. will vary markedly for the upper and lower surfaces [69].

Water use efficiency (WUE)

For water use efficiency estimation, the containers were checked for water loss by measuring the level of the liquid medium in each container prior to every compensation time, and the differences in volumes were converted from ml to kg. The obtained measurements for each container revealed the volume of water applied to the container at that period. The water use efficiency according to Larcher [70] was determined as follows:

WUE (g/kg) = Biomass (mg DW)/ H2O loss.

Net assimilation rate

Net assimilation rate was determined as applied by Dawood et al. [71] according to the following formula:

Net assimilation rate = (ln LDM1 − ln LDM2)/ [(t1 − t2) × LA2] g/cm2/d.

LDM1, 2 and LA2 are the dry weights of leaf and the leaf area recorded before (t2) and after (t1) treatment, respectively.

Electrolyte leakage

Electrolyte leakage (EC %) was assessed following the procedure of Abeed and Dawood [72]. For this, healthy fresh samples of leaves and roots were washed with deionized water and cut into small pieces and, then soaked in 30 ml of deionized distilled water at 10 °C. After 24 h, the elementary electrical conductivity (C1) of the bathing solution was noted at 25 °C. Then, leaf discs were autoclaved for 15 min and left to cool down to 25 °C and the secondary electrical conductivity (C2) was reported.

EC was evaluated in percentage via the following formula:

$$\textrm{EC}=\left({\textrm{C}}_1/{\textrm{C}}_2\right)\times 100$$

Lipid peroxidation

The accumulation of malondialdehyde (MDA), a product of lipid peroxidation, was evaluated by the scheme of thiobarbituric acid (TBA) and the contents of MDA in cell membranes were determined as stated previously by [72]. First, tissue segments were accurately weighed and stabilized in 0.1% trichloroacetic acid (TCA) and then centrifuged for 10 min at 10,000 rpm. Next, 1 ml of the aliquot was mixed with TCA-TBA reagent. Finally, the mixture was heated on water bath at high temperature (95 °C) for 30 min, then cooled quickly in an ice-bath, followed by centrifuging at 10,000 rpm for 15 min and the absorbance was observed at 532 nm. Calculations were adjusted for unspecific turbidity by subtracting the absorbance at 600 nm and the results expressed as μmol/g FW [73].

Hydrogen peroxide (H2O2)

H2O2 levels in Juncus leaves and roots was quantified as reported by Mukherjee and Choudhuri [74]. Briefly, test materials (0.5 g) were completely extracted in 4 ml cold acetone. Three ml of the acetone extract was added to 1 ml of titanium dioxide (0.1%) in 20% H2SO4 and the two mixtures were centrifuged together at 6000 rpm for 15 min. The resultant yellow color of the reaction was read spectrophotometrically at 415 nm.

Total free amino acids

The framework of Moore and Stein [75] was used for the estimation of total free amino acids (TFAA). After accurate extraction of samples and analytical treatment with different chemicals conceded in the protocol, TFAA content was calculated from a calibration curve using glycine as blank and the wavelength was recorded at 570 nm. the data were expressed as mg/g DW.

Proline content measurement

The extraction of proline was performed using the protocol of Bates et al. [76]. In test tubes, fine powdered dry samples were fully macerated in 3% sulfosalicylic acid and a prepared mixture solution containing proline, glacial acetic acid and acidic ninhydrin (1: 1: 1, v/v) and boiled for one hour at 100 °C. The reaction was terminated by placing the tubes in an ice bath. Then the reaction mixture was extracted with toluene (2 ml), mixed via vortex. Using toluene as blank, the optical density of the organic phase was taken at a wavelength of 520 nm.

Total antioxidant

The method of Prieto et al. [77] was applied for the assay of the total antioxidant. Alcoholic extract with reagent mixture of 0.6 M sulfuric acid combined with 28 mM sodium phosphate and 4 mM ammonium molybdate; were well mixed and incubated at 95 °C for one hour and half, and then the mixture was allowed to cool down at room temperature. The absorbance of the mixture was observed at 695 nm and the content of total antioxidants was estimated from its standard curve.

Enzymatic antioxidants

Twenty milligrams of frozen juncus samples were crushed to a fine powder with liquid N2 and then smoothed with 3 ml of 100 mM potassium phosphate buffer at pH 7.8, containing 0.1 mM ethylenediamine tetraacetic acid (EDTA) and 100 mg polyvinylpyrrolidone. The suspension was centrifuged at 18,000 rpm for 10 min at 4 °C and the supernatants collected and used for the assayed superoxide dismutase, catalase, peroxidase, and ascorbate peroxidase. All colorimetric measurements were performed at 20 °C via UV spectrophotometer [17].

Superoxide dismutase (SOD) activity was determined as documented by [17]. The activity of SOD (EC 1.15.1.1) was measured in assay mixture (2 ml), which included 100 μl enzymatic extract treated in 50 mM of sodium carbonate buffer (pH 10.2), 0.1 mM EDTA and 100 μl of 5.5 mg/ml epinephrine (liquified in 10 mM HCl, pH 2). Reads were registered by using UV spectrophotometer at 480 nm for 1 min. The SOD activity was expressed in μmol/mg protein/g FW/min. The assessment of ascorbate peroxidase (APX) activity was conducted spectrophotometrically following the steps in the protocol of Abeed et al. [17]. The activity of (APX; EC 1.11.1.11) was evaluated by the oxidation rate of hydrogen peroxide–dependent of ascorbic acid in a reaction mixture of 50 μl enzyme extract added to potassium phosphate buffer (50 mM, pH 7), Na2-ETDA (0.1 mM), and H2O2 (5 mM). The oxidation rate of ascorbic acid was estimated from the decrease in absorbance at 290 nm for 1 min. For measuring polyphenol oxidase (PPO) activity, mix of phosphate buffer (0.1 M at pH 6.0), catechol (0.1 M) and enzyme extract (0.5 mL) was retained in 25 °C for 5 min, then the reaction was end by adding 1 mL sulfuric acid (2.5 N). The change in absorbance was read at 495 nm and expressed per mg protein per minute [78]. For glutathione-S-transferase (GST), (GST; EC 2.5.1.18, u/mg protein/g FW/min) was quantified by following the methods adopted by AbdElgawad et al. [79].

Statistics

All values given in this trial are average of four samples, presented with standard deviation. The descriptive statistics to determine the significant differences between treatments were investigated by analysis of variance (ANOVA) by SPSS 21.0 software at 5% level of probability. Mean values for the treatments were compared using Duncan’s multiple range test.