Next Article in Journal
Ceramics and Nanostructures for Energy Harvesting and Storage
Next Article in Special Issue
Nano-Pesticides and Fertilizers: Solutions for Global Food Security
Previous Article in Journal
X-ray Investigation of CsPbI3:EuCl3 Infiltrated into Gig-Lox TiO2 Spongy Layers for Perovskite Solar Cells Applications
Previous Article in Special Issue
Toxic Effects of Copper Fungicides on the Development and Behavior of Zebrafish in Early-Life Stages
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Metabolomics Response of Solanum melongena L. Leaves to Various Forms of Pb

1
Key Laboratory of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
4
National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management, Institute of Eco-Environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Nanomaterials 2023, 13(22), 2911; https://doi.org/10.3390/nano13222911
Submission received: 8 September 2023 / Revised: 30 September 2023 / Accepted: 2 October 2023 / Published: 8 November 2023
(This article belongs to the Special Issue Environmental Analysis and Environmental Processes of Nanomaterials)

Abstract

:
Due to activities like mining and smelting, lead (Pb) enters the atmosphere in various forms in coarse and fine particles. It enters plants mainly through leaves, and goes up the food chain. In this study, PbXn (nano-PbS, mic-PbO and PbCl2) was applied to eggplant (Solanum melongena L.) leaves, and 379 differential metabolites were identified and analyzed in eggplant leaves using liquid chromatography–mass spectrometry. Multivariate statistical analysis revealed that all three Pb treatments significantly altered the metabolite profile. Compared with nano-PbS, mic-PbO and PbCl2 induced more identical metabolite changes. However, the alterations in metabolites related to the TCA cycle and pyrimidine metabolism, such as succinic acid, citric acid and cytidine, were specific to PbCl2. The number of differential metabolites induced by mic-PbO and PbCl2 was three times that of nano-PbS, even though the amount of nano-PbS absorbed by leaves was ten times that of PbO and seven times that of PbCl2. This suggests that the metabolic response of eggplant leaves to Pb is influenced by both concentration and form. This study enhances the current understanding of plants’ metabolic response to Pb, and demonstrates that the metabolomics map provides a more comprehensive view of a plant’s response to specific metals.

1. Introduction

In recent years, with extensive attention directed towards atmospheric particulate matter, heavy metals (lead, Pb) present in particles have also gained increased scholarly scrutiny [1,2,3]. Pb is a prevalent heavy metal contaminant, which has garnered attention due to their its non-degradability, bioaccumulation, and high toxicity. Studies have shown that various forms of Pb exist in atmospheric particles. Common Pb forms in inhalable and fine particle aerosols include lead oxide (PbO), chloride (PbCl2) and sulfate (PbSO4), most of which originate from coal burning [2]. Pb forms in the total suspended particulates of road dust encompass lead sulfide (PbS), PbSO4, and PbCl2 [1]. These Pb particles can directly endanger human health and life through inhalation [4]. They can also enter plants through leaves and roots in the form of dry and wet deposition. This not only affects the growth and development of plants but also indirectly harms human health by entering the food chain and reaching the human body [5,6,7]. Therefore, it is necessary to study the effects of atmospheric Pb particles on plants.
At present, studies have shown that lead can inhibit the growth of plant roots, cause leaf yellowing and wilting, and dwarf plant growth [8]. By exploring its mechanism through metabolism, it was found that lead ion (Pb2+) affected the energy metabolism process of plants [8]. Low-molecular-weight metabolites are the end products of gene expression. Thus, alterations in cell metabolite profiles can be used as an effective strategy for evaluating biological activity [9]. Metabolomics, defined as techniques aiming to offer an unbiased, comprehensive qualitative and quantitative overview of metabolites in living organisms [10], has demonstrated its effectiveness as a tool for comprehending how plants respond to and alleviate various stresses at the molecular level [11,12,13]. Pidatala et al. showed that Pb2+ had a significant inducing effect on key metabolic pathways, such as glucose metabolism and amino acid metabolism, in vetiver leaves and roots [14]. Li et al. found that glycolysis, purine, pyrimidine, and phospholipid metabolism were the primary metabolic pathways involved in the response of maize roots to Pb2+ stress [15]. These studies provide a basis for understanding the molecular mechanism of terrestrial plants’ response to Pb.
However, these articles have studied the exposure of plant roots to Pb ions, and the metabolic response to Pb after leaf exposure has not been reported. Numerous studies have shown that leaf tissue plays a more significant role in absorbing Pb from atmospheric particulate matter than roots [16,17,18]. Taking radish (Raphanus sativus) and parsley (Petroselinum crispum) as examples, foliar uptake of Pb was 1.6 times higher than root uptake [19]. Near a secondary lead smelter, foliar uptake of Pb by lettuce and ryegrass was 5~8 times higher than root uptake [20]. Previous studies comparing Fe and Fe3O4, Cu(OH)2 and CuSO4, and Ag nanoparticles (NPs) and Ag+ have demonstrated that different metal forms have distinct effects on plant metabolism [12,21,22]. Notably, Ag NPs induce disruptions in amino acid metabolism, the TCA cycle, and oxidative stress, which are unique to Ag NPs [21]. However, the study of the effects of different forms of Pb on plant metabolism has not received much attention. Therefore, gaining an in-depth understanding of the metabolic response mechanism of crop leaves to various forms of Pb absorption is of great significance for comprehending Pb exposure and assessing Pb risk.
The purpose of this study was to understand how PbXn (nano-PbS, mic-PbO and PbCl2) exposure affects metabolites and metabolic pathways in eggplant leaves, and to identify the metabolic differences and causes of the leaves induced by the three types of Pb. The obtained data not only offer a comprehensive understanding of the mechanism of stress response in eggplant leaves, but will also provide essential baseline knowledge for controlling Pb pollution in agriculture.

2. Materials and Methods

2.1. Materials

Bulk PbO and PbCl2 of analytical reagent grade were obtained from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China). Lead acetate of analytical reagent grade was obtained from Fu Chen (Tianjin) Chemical Reagent Co., Ltd. (Tianjin, China). Thioacetamide (≥98.0%), cetyltrimethylammonium bromine (99%) and EDTA-2Na (≥99.9%) were sourced from Shanghai Aladdin Biochemical Technology Co., Ltd. (Shanghai, China). Nitric acid (HNO3, 69~70%, trace metal < 1 ppb) of guaranteed reagent grade was obtained from ANPEL Laboratory Technologies (Shanghai) Inc. (Shanghai, China). Perchloric acid (HClO4, 70~72%) and hydrogen peroxide (H2O2, ≥30%) of guaranteed reagent grade was sourced from Tianjin Kemiou Chemical Reagent Co., Ltd. (Tianjin, China). Ethanol (99.7%) was acquired from Chengdu Kelong Chemical Co., Ltd. (Chengdu, China). Standard substance citrus (GBW10020) and celery (GBW10048) leaves were purchased from the National Sharing Platform for Reference Materials. Ultrapure water (resistivity ≥ 18.2 MΩ*cm) was prepared using a Milli-Q Direct 8 system (Merck Millipore, Darmstadt, Germany). Eggplant (Solanum melongena L.) seeds were purchased from Shenyang Kexing Seeds Co., Ltd. (Shenyang, China).

2.2. Preparation of PbXn Stock Solution

Details of the synthesis of nanoscale PbS (nano-PbS) can be found in Supplementary Materials Text S1. A 1000 mg Pb/L nano-PbS suspension was prepared and uniformly dispersed via ultrasonic treatment using a water bath ultrasonic generator (KQ-300B, Kunshan, China) at 800 W for 3 h. Bulk PbO was ground into large sheets to facilitate dispersion, and then sonicated at 720 W with an immersing probe in an ultrasonic cell disrupter (1800-99, Biosafer, Shanghai, China) for 3 h to achieve a dispersion of 2000 mg Pb/L and to obtain micron-sized PbO (mic-PbO).
Dissolvable Pb salts (PbCl2) were used for comparison with the particles. PbCl2 was dissolved in distilled water directly with the assistance of ultrasonication to obtain a solution with 100 mg Pb/L concentration. Stock Pb suspensions/solutions were sealed and stored at 4 °C. Plant experiments should be carried out as soon as possible.

2.3. PbXn Characterization

PbXn stock suspensions were sonicated at 800 W for 1 h in a water bath ultrasonicator to achieve better dispersion. Then, the stock suspensions were diluted to an experimental concentration of 10 mg Pb/L. For the determination of particle hydrodynamic size and zeta potential (Nano-ZS, Malvern, UK) in nanopure water, solutions of 10 mg Pb/L nano-PbS and mic-PbO were prepared and subjected to bath sonication (KQ-300B, Kunshan, China) at 50 kHz for 30 min before measurements. The following steps were repeated daily during the 5-day PbXn suspension application stage of the plant experiment. PbXn suspensions were filtered through 0.1 µm mixed cellulose ester membranes to remove particles, and were acidified with 5% HNO3 before analysis via inductively coupled plasma–mass spectrometry (ICP-MS, NexION 300X, Perkin Elmer, Waltham, MA, USA) to determine the amounts of ionic Pb. The analytical conditions and quality control of ICP-MS are described in Supplementary Materials Text S2. Freeze-dried nano-PbS and mic-PbO samples were imaged using a scanning electron microscope (SEM, Gemini 300, Zeiss, Jena, Germany) to characterize their diameter and surface morphology.

2.4. Plant Growth and Experimental Design

Eggplant (Solanum melongena L.) seeds were cultivated in plastic pots (diameter: 10 cm; height: 9 cm) filled with nutrient substrates (pH: 6.5~6.8; N, P, K ≥ 12 g/kg; organic matter contents ≥ 40%; Si ≥ 0.3 g/kg). Deionized water was sprayed to moisten the nutrient matrix, a preservative film was attached to maintain the temperature and humidity required for seed germination, and the film was punctured to ensure an adequate oxygen supply. Initially, three seeds were planted in each pot, and the healthiest plant was retained after germination. All plants were placed in growth chambers (day/night period: 16 h/8 h; temperature: 25 °C/22 °C; humidity: 45%/65%), and the photosynthetic luminous power density during the daytime period was 14.5 W/m2. Plants were watered with tap water (Pb < 0.1 μg/L) every 2 days to maintain the humidity of the nutrient substrates at 40%. After reaching the 7~8 leaf stage (height: ~25 cm), the plants were foliarly exposed to different forms of Pb, respectively. The experiment was conducted over a 5-day application stage. During the exposure state, 3.4 mL Pb suspensions containing 34 μg Pb were evenly added dropwise to the adaxial surfaces of all leaves of each whole plant using a pipettor each day (Figure S1). Prior to amendment, the Pb suspensions were sonicated for 30 min to achieve a stable dispersion. Over the 5-day application stage, the plants were exposed to a total of 170 μg Pb. We stopped applying and harvesting the plants on the sixth day. Deionized water without any forms of Pb was used as the control in the same manner. Each treatment consisted of 12 replicates.

2.5. ICP-MS Analysis for Pb Content in Plants

The roots, stems, and leaves of the five eggplants were separated after harvest. The roots and leaves were immersed in a 20 mM EDTA-2Na solution for 10 min to remove the surface metals. The stems were washed with deionized water three times. Plant tissues were dried to a constant weight at 75 °C in an oven (101-3AB, Taisite, Tianjin, China). After grinding the dried tissues, 0.2 g of the tissues sample was digested using 3 mL HNO3-HClO4 (4:1, v/v) solutions and 0.5 mL 30% H2O2 in a dispelling furnace (DB-3AB, Lichen, Jinjiang, China). Subsequently, the digested sample was diluted with 5% HNO3 solution to a final volume of 10 mL before analysis. The concentrations of Pb in various tissue samples were determined using ICP-MS. The recovery was determined to be 94% ± 9% [mean ± standard deviation, n = 5].

2.6. Liquid Chromatography–Mass Spectrometry (LC-MS)-Based Leaf Metabolomics

At harvest, a portion of fresh tissues were quickly frozen in liquid N2 and stored at −80 °C for metabolite analysis by LC-MS [23]. We accurately weighed 200 mg (±1%) of sample in a 2 mL EP tube, added 0.6 mL of 2-chlorophenylalanine solution (4 mg/L) methanol (−20 °C), then vortexed for 30 s. The treated sample was added to 100 mg glass beads, placed into the tissue grinder, and ground for 90 s at 55 Hz. A room-temperature ultrasound was performed for 15 min. The sample was centrifuged at 12,000 rpm for 10 min, and 200 μL of the supernatant was taken and filtered through a 0.22 μm membrane and then added to the detection bottle. Each treatment consisted of six replicates. A quality control (QC) sample was prepared by mixing aliquots of all treatment samples, assuming that the QC sample contained a mean concentration of all components present in the samples under investigation. We used these samples for LC-MS detection. The analytical conditions of LC-MS are described in Supplementary Materials Text S3.

2.7. Statistical Analysis

The relative abundances of the metabolites were analyzed using a supervised partial least-squares discriminant analysis (PLS-DA) and a multivariate analysis, both conducted using MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/, accessed on 16 September 2022). These analyses aimed to normalize the data via log transformation (normalized by sum), enabling better comparability of individual features [24]. Variable importance in projection (VIP) represents the weighted sum of squares in the PLS-DA analysis, signifying the variable’s significance within the entire model [25]. A variable with a VIP > 1 is considered significant [26]. Additionally, univariate statistical analyses (one-way ANOVA) were performed using online resources (http://www.metaboanalyst.ca/, accessed on 20 June 2023) with a threshold value of 0.05. A biological pathway analysis was conducted based on all identified metabolite data using MetaboAnalyst 4.0 [26]. The threshold value for pathway identification was set at 0.1 [26]. Significant differences in Pb content within plant tissues were assessed using a one-way ANOVA followed by a Duncan test, performed with SPSS 24.0 software (SPSS, Chicago, IL, USA). Differences were deemed statistically significant at p < 0.05.

3. Results and Discussion

3.1. Characterization of PbXn

SEM results showed that the average diameter of nano-PbS and mic-PbO is 82 ± 18 and 720 ± 257 nm, respectively (Figure S2). Some 10 mg Pb/L PbXn suspensions were characterized in terms of the average hydrodynamic size, zeta potential (ZP), and dissolution. The average hydrodynamic sizes for nano-PbS and mic-PbO were 316 ± 6 and 1144 ± 70 nm, respectively, with corresponding zeta potentials of −23 ± 1 and 20 ± 1 mV, respectively (Table S1). The nano-PbS- and mic-PbO-released Pb ions reached equilibrium (4.5 ± 0.1 mg/L for nano-PbS, 4.2 ± 0.2 mg/L for mic-PbO) on the fourth day. The release of Pb ions reached a maximum value of 10.2 ± 0.8 mg/L for PbCl2 within one day, and remained largely unchanged over 5 days (Figure S3). Therefore, the two Pb particle suspensions not only contain the original Pb particle type, but also contain 45% lead ions in the nano-PbS suspension, and 42% in the mic-PbO suspension.

3.2. Pb Absorption in Eggplant

The absorption and position of Pb in leaves were analyzed via ICP-MS. Exposure to PbXn significantly increased the Pb content of eggplant leaves (p < 0.05), with the order nano-PbS > PbCl2 > mic-PbO (Figure 1). The Pb content upon exposure to nano-PbS (104.5 ± 4.5 μg), mic-PbO (10.4 ± 1.4 μg), and PbCl2 (14.7 ± 0.3 μg) was nearly 235-fold, 23-fold, and 33-fold higher than in the control, respectively. The detected Pb in eggplant leaves may be particles or Pb irons released from particles. Herein, we determined the dissolution dynamics of PbXn in particle aqueous solution for up to 5 days. The dissolution rate of nano-PbS and mic-PbO was 44% and 42%, respectively (Figure S3). The dissolution rate of PbCl2 was 97~102%, indicating a complete dissolution. Therefore, most of the Pb in nano-PbS treated leaves may be nano-PbS, while most of the Pb in PbCl2 treated leaves may be Pb ions. Additionally, eggplant leaves absorbed more nano-PbS than mic-PbO. This could be attributed to the relatively smaller size of nano-PbS (82 ± 18 nm) compared to mic-PbO (720 ± 257 nm), facilitating its easier transport into guard cells or cuticles and movement between mesophyll cells [27]. Compared with the control group (CK), the content of Pb in the stem was essentially the same as that of CK (0.13 ± 0.03 μg) after nano-PbS (0.14 ± 0.04 μg), mic-PbO (0.11 ± 0.08 μg), and PbCl2 (0.14 ± 0.07 μg) treatments (Figure 1). After nano-PbS (0.26 ± 0.06 μg), mic-PbO (0.35 ± 0.13 μg), and PbCl2 (0.40 ± 0.06 μg) treatments, there was no significant difference in the Pb content in roots compared to CK (0.25 ± 0.05 μg) (Figure 1). Therefore, the results showed that Pb was not transferred from leaves to stems and roots. It is possible that PbXn in leaves did not reach the vascular bundle and thus could not be transported to the roots [27].

3.3. Metabolic Response of Eggplant Leaves to PbXn

Metabolite profiles of unexposed eggplant leaves were obtained through LC-MS-based metabolomics. A total of 2484 metabolites were detected, and based on retention indices and mass spectra, 472 metabolites were identified using the Metlin identifier. To compare the metabolite profiles of the three Pb species, an unsupervised multivariate method using a principal component analysis (PCA) was performed on the eggplant leaf datasets. The model was not provided with any prior information regarding the sample identities [28]. The grouping of samples in a PCA scores plot is determined by the similarities in their metabolic profiles.
The PCA scores plot (Figure 2a) shows that the metabolite profiles of unexposed and exposed eggplant leaves were separated along the first principal component (PC1), which explained 15.5% of the total variance. This indicates that the metabolite patterns were different for unexposed and exposed eggplant leaves. All samples were within a 95% confidence interval, and the difference was statistically acceptable without outliers. To visualize general grouping information based on treatment, PLS-DA analysis was performed. The score plot (Figure 2b) demonstrates that all PbXn groups were distinctly separated from the controls, explaining 15.5% of the data variation. These results indicate that PbXn altered the metabolic profile of the eggplant leaves. Additionally, we observe that the metabolic changes are PbXn-dependent, with PbCl2 inducing the most noticeable metabolic changes, followed by mic-PbO, and then nano-PbS.
The responsive metabolites were subsequently isolated based on VIP score > 1. The Venn diagram of 379 metabolites that resulted in the separation of the control and all PbXn treatment groups was shown in Figure 3. Differential metabolites include sugars and sugar alcohols, amino acids and polyamines, nucleotides, lipids, organic acids, fatty acids, and other metabolites such as phenolic acids and alkaloids. Compared with CK, the number of differential metabolites induced by nano-PbS, mic-PbO and PbCl2 was 81, 256 and 267, respectively. Among them, organic acids were the main metabolites, accounting for 20%, 21% and 20%, respectively. Organic acids are strong cation chelators, which play an important role in facilitating mineral element uptake and sequestering or excluding toxic metals [29,30,31,32]. Among 38 identical metabolites induced by nano-PbS, mic-PbO and PbCl2, sugars and sugar alcohols accounted for 21% (Figure S4). The results showed that all three lead treatments interfered with the carbon metabolism of eggplant leaves. Among the differential metabolites interfered with by mic-PbO and PbCl2 treatments, the same differential metabolites accounted for 44%, while among the differential metabolites interfered with by nano-PbS and mic-PbO, nano-PbS and PbCl2 treatments, the same differential metabolites accounted for 20% and 16%, respectively. This indicates that the metabolic response mechanisms of eggplant leaves induced by mic-PbO and PbCl2 treatments were more similar.

3.4. Metabolic Differences Induced by PbXn

3.4.1. Amino Acid Metabolism

Exposure to PbXn in eggplant leaves resulted in significant changes in amino acid metabolism (Figure 4 and Figure 5). Amino acids are important primary metabolites, structural units of proteins and peptides, and precursors for the synthesis of other metabolites. Amino acids have multiple functions in plant growth and other biological processes [33,34]. The relative abundance of some amino acids (glutamic acid, tyrosine, kynurenine, proline, sarcosine, tryptophan, phenylalanine, valine, threonine, glutamine, histidine and γ-aminobutyric acid) was significantly reduced under all three Pb treatments (p < 0.05) (Figure 4), indicating that these amino acids were either reduced in synthesis or increased in utilization in response to Pb treatment.
Nano-PbS, mic-PbO and PbCl2 induced significant down-regulation of glutamate and tyrosine (p < 0.05) (Figure 4). Glutamate is known to be a signaling molecule that plays a role in the antioxidant defenses of plants [35]. The down-regulation of glutamate indicates that the three lead treatments interfered with the signal transduction of leaves. Mic-PbO and PbCl2 down-regulated phenylalanine (p < 0.05). Phenylalanine and tyrosine, two aromatic amino acids, are central molecules of plant metabolism. They are not only the essential components of protein synthesis, but also important precursors of the shikimate pathway and phenylpropanoid pathway, which produce a large number of secondary metabolites, including phenolic compounds, flavonoids, alkaloids and indoleacetic acid. These secondary metabolites play an crucial role in plant defense and detoxification [36]. The down-regulation of phenylalanine and tyrosine suggests that the shikimic acid and phenylpropionic acid pathways in leaves may have been disturbed. As a product of glutamic acid, the levels of proline in leaves were significant decreased after exposure to nano-PbS and PbCl2 (Figure 4). Proline is well known to function as an osmolyte, radical scavenger, macromolecule stabilizer, and metal chelator under heavy metal stress [35,37]. The decrease in proline may be the result of its use as a free radical scavenger or metal-chelating agent. As a branched-chain amino acid, valine is the main constituent of the transmembrane region of membrane proteins [38]. The treatment of mic-PbO and PbCl2 significantly down-regulated valine, leading us to speculate that the physiological function of the leaf cell membrane may have been disturbed.
PbCl2 treatment also significantly interfered with glutamine, histidine, and γ-aminobutyric acid (GABA), which were not disturbed by nano-PbS and mic-PbO treatments (Figure 4). Glutamine is a nitrogen-rich amino acid involved in nitrate and ammonia assimilation in plants [39,40]. The decrease in glutamine indicates that the ability of plants to obtain nitrogen compounds is reduced. Positively charged histidine was also significantly reduced (p < 0.05). Histidine is an essential amino acid for plant cell growth and development, so its reduction reveals the effect of Pb treatment on eggplant growth. In addition, histidine is involved in deamination, suggesting changes in this process as well [34,41]. GABA is a non-protein amino acid that plays an important role in signal transduction, pH regulation, nitrogen storage, plant development and stress defense [42]. The specific down-regulation of GABA by PbCl2 indicates that PbCl2 induced more severe oxidative stress on the leaves. In general, amino acid levels exhibited a downward trend with all three Pb treatments, indicating that nitrogen metabolism was disrupted.

3.4.2. Fatty Acids Metabolism

Nano-PbS, mic-PbO and PbCl2 induced significant down-regulation (p < 0.05) of palmitic acid (Figure 5 and Figure S5). Stearic acid was significantly down-regulated by mic-PbO and PbCl2, while oleic acid was significantly up-regulated by nano-PbS and significantly down-regulated by mic-PbO (p < 0.05) (Figure S5). Bovinic acid and linoleic acid were specifically up-regulated by mic-PbO, linolenic acid was specifically down-regulated, and arachidonic acid was specifically up-regulated by PbCl2. Fatty acids are the main component of the plasma membrane. The down-regulation of saturated fatty acids (palmitic acid, stearic acid and caprylic acid) and the up-regulation of unsaturated fatty acids (oleic acid, bovinic acid, linoleic acid and arachidonic acid) caused by PbXn treatment resulted in high levels of unsaturated lipid membrane. The plant plasma membrane may be regarded as the first “living” structure that is the target of metal toxicity [43]. Excessive metal can cause plasma membrane dysfunction, including increased cell leakage [43]. Changes in fatty acid levels may lead to changes in membrane fluidity and permeability, and can be used as a mechanism for stress adaptation. Up-regulation or down-regulation of fatty acids may change plasma membrane composition, thereby changing metal homeostasis [43].

3.4.3. Sugars Metabolism

We found that all three Pb-treatments significantly down-regulated (p < 0.05) the levels of cellobiose and raffinose. PbCl2 significantly down-regulated xylose (Figure 5 and Figure S6). Since cellobiose, raffinose and xylose are polysaccharides located on the cell wall, the decrease in cellobiose and raffinose indicates that plant cell walls are broken down to produce small sugar molecules, such as osmolytes, to protect cell membranes and plant proteins [44]. D-ribose is the main component of RNA and the raw material for maintaining the energy (ATP and NADH) required for the normal physiological activities of cells. PbCl2 induced its significant up-regulation to maintain the energy metabolism of cells. After Pb treatment, the levels of erythritol, ribitol, and arabitol changed (Figure S6). These metabolites are sugar polyols in reduced forms of aldoses and ketoses. Sugar polyols have been reported to act as osmoprotective agents. The accumulation of sugar polyols may help maintain cell hydration levels and cell function [44]. Therefore, changes in the compositions of sugar and sugar polyols may be a protective mechanism for eggplant leaves in response to PbXn.

3.4.4. Nucleotide Metabolism

Exposure to PbXn changed nucleotide metabolism in eggplant leaves (Figure 5 and Figure S7). The metabolism of both purine and pyrimidine derivatives was affected. For example, a significant increase in cytidine monophospate (CMP) was accompanied by a decrease in cytosine, indicating that pyrimidine metabolism was disturbed [45,46]. Similarly, guanine was reduced in all three Pb-treatments, indicating that purine metabolism also changed [45,46]. This decrease in nucleobases may be related to the accumulation of nucleotides caused by Pb-treatments. The abundance of other nucleoside, such as guanosine, thymidine and uridine, increased significantly under PbCl2 treatment. Compared with nano-PbS and mic-PbO treatments, PbCl2 treatment had a more serious effect on nucleic acid metabolism in eggplant leaves.

3.4.5. Organic Acids and Antioxidants

The three Pb-treatments up-regulated the content of several organic acids, such as citric acid, cis aconitic acid and succinic acid, and down-regulated malic acid (Figure S8). These organic acids are key metabolic components in the tricarboxylic acid cycle (TCA cycle) [47]. They are usually related to heavy metal stress and are considered to be reliable indicators of metal accumulation [48]. The accumulation of organic acids can participate in the detoxification process of leaves by chelating metal ions. The up-regulation of TCA cycle intermediates may indicate the activation of TCA pathway. The TCA cycle is the core of the cellular respiration mechanism. Plants with up-regulated respiratory regulation may be to produce the energy required for defense compounds to cope with oxidative stress [49,50]. Another explanation for the up-regulation of citric acid is that plants try to chelate excess metal ions with citric acid [51], which may also be the reason why citric acid is only significantly up-regulated by PbCl2 (p < 0.05). Nicotinic acid is a key component of the plant pathways involved in redox homeostasis and stress signaling [52]. Nano-PbS, mic-PbO and PbCl2 treatments significantly down-regulated the level of nicotinic acid, indicating that Pb induced oxidative stress in eggplant leaves. Ascorbate, salicylic acid and 2-hydroxycinnamic acid, as non-enzymatic antioxidants, were up-regulated by nano-PbS, mic-PbO and PbCl2 [53], while 4-hydroxybenzoic acid, 4-hydroxycinnamic acid and shikimic acid were down-regulated (Figure S8). It is speculated that the changes in these secondary metabolites may be related to the non-enzymatic antioxidant defense system.

3.5. Biological Pathways Analysis

A more detailed analysis of the relevant pathways and networks altered by nano-PbS, mic-PbO and PbCl2 was performed. Pathway enrichment analysis showed that nano-PbS, mic-PbO and PbCl2 disturbed 67, 83, and 83 biological pathways in eggplant leaves, of which 9, 7, and 10 pathways were significantly disturbed (p < 0.05), respectively (Figure 6 and Tables S2–S4). Among them, galactose metabolism; phenylalanine, tyrosine and tryptophan biosynthesis; and ABC transporters were significant affected by all the Pb treatments, and are related to carbohydrate metabolism, amino acid metabolism and membrane transport, respectively. Two pathways were perturbed by both nano-PbS and mic-PbO: phenylpropanoid biosynthesis and tyrosine metabolism. Phenylalanine metabolism was perturbed by nano-PbS and PbCl2. Although all three Pb-treatments perturbed galactose metabolism, nano-PbS treatment only perturbed 11% of metabolites in the pathway, while mic-PbO and PbCl2 induced 24% of metabolites, and the metabolites induced by the two treatments were exactly the same. Similarly, although the nano-PbS treatment had the same interference pathways as the other two treatments, the number of metabolites disturbed by nano-PbS was significantly less than that of mic-PbO and PbCl2. The results showed that the mic-PbO and PbCl2 treatments had a greater impact on related metabolic pathways than the nano-PbS treatment.
Under the stress of nano-PbS, glycine, serine and threonine metabolism, the pentose phosphate pathway and glutathione metabolism were perturbed specifically. Among these pathways, pyruvic acid, betaine, and ascorbate were significantly effected (p < 0.05) (Figures S8 and S9). Pyruvate is a precursor of branched-chain amino acids, the up-regulation of pyruvate indicates that branched-chain amino acid-related metabolism is activated. Branched-chain amino acids have been shown to be an energy source for oxidative phosphorylation during under adverse conditions in plant [54]. Betaine acts as an osmoprotectant in abiotic stress, maintains plant turgor, stabilizes and protects cell membranes, and also acts as an active oxygen scavenger [55,56]. Ascorbate, as the main metabolite in the glutathione metabolic pathway, acts as a reactive oxygen species scavenger to protect plants from oxidative damage. As an unsaturated fatty acid on the plasma membrane, mic-PbO exposure specifically up-regulated the concentration of linoleic acid, bovinic acid, and 8,10,14-eicosatrienoic acid (Figures S5 and S9). This increase in unsaturated membrane lipids plays a essential role in maintaining the necessity of fluidity for membrane function. Aminoadipic acid is an intermediate in the lysine degradation pathway. Lysine degradation in plants is an over-regulated metabolic pathway that effectively converts lysine into glutamate and other metabolites to cope with stress and certain developmental processes [57].
PbCl2 specifically perturbed two amino acid metabolic pathways (alanine, aspartate and glutamate metabolism; tryptophan metabolism), two carbohydrate metabolic pathways (butanoate metabolism; TCA cycle), one nucleotide metabolic pathway (pyrimidine metabolism), and a pathway of translation in genetic information processing (aminoacyl-tRNA biosynthesis). PbCl2 specifically induced the down-regulation of glutamine, histidine and GABA (Figure 4). Their specific down-regulation indicated that PbCl2 had more serious interference on amino acid metabolism in eggplant leaves than nano-PbS and mic-PbO. Glutamine and histidine are also important intermediates in the biosynthesis of amino acid-tRNA. The interference of PbCl2 in the translation pathway indicates that the process of tRNA recognizing codons and transporting amino acids is disturbed. Succinic acid and citric acid were specifically up-regulated by PbCl2, and fumaric acid was down-regulated. They are important metabolites in butyric acid metabolism and TCA cycling (Figure S8). Cytidine, thymidine, and guanosine were specifically up-regulated by PbCl2 (Figure S7). Up-regulation of pyrimidine metabolism may be a strategy for plants to redistribute energy and resources to other stress-related processes [58].

3.6. Effects of PbXn Properties on Metabolomics

Our metabolomic analysis showed that PbCl2 and mic-PbO induced the amount, degree and metabolic pathway of differential metabolites far more severely than nano-PbS. The differential metabolites induced by mic-PbO and PbCl2 were three times that of nano-PbS. However, the absorption of PbCl2 and mic-PbO in eggplant leaves was much less than that of nano-PbS, and the absorption of nano-PbS in leaves was ten and seven times that of mic-PbO and PbCl2, respectively (Figure 1). Huang et al. studied the antioxidant-related metabolites of cucumber using nano-Cu pesticides, and found that the concentration of antioxidants changed with the dose [59]. Compared with a low concentration (400 mg/L) of lead nitrate, a high concentration (1200 mg/L) of lead nitrate induced more significant up-regulation and down-regulation of metabolites in Chrysopogon zizanioides L. Nash [14]. Zhang et al. found that in addition to inducing the same metabolites as Ag+, Ag NPs also specifically induced carbazole, raffinose, lactulose, citraconic acid, aspartic acid and other metabolites related to antioxidant defense in cucumber leaves [60]. Liu et al. also found that no specific metabolites in freshwater algae Poterioochromonas malhamensis were only affected by Ag NPs. However, compared with Ag+, some metabolites related to amino acid and pyrimidine metabolism were more accumulated or consumed after exposure to Ag NPs [21].
In our results, the differential metabolites induced by mic-PbO and PbCl2 were more similar compared to nano-PbS. This may be due to the superposition of ion effects and nano effects. The applied mic-PbO partially entered the leaves in the form of Pb ions (4.2 ± 0.2 mg/L Pb ions), resulting in a 44% overlap in the same metabolites induced by mic-PbO and PbCl2. Mic-PbO (1144 ± 70 nm) with a larger particle size can induce the metabolic response of leaves through stomatal entry [61]. This is also the reason that although mic-PbO and PbCl2 induced 44% of the same metabolites, they did not induce the same metabolic pathways (except for the metabolic pathway induced by the three kinds of Pb). The uptake of nano-PbS in leaves was ten times that of mic-PbO, but the number of induced metabolites was only one third of that in mic-PbO. Since the concentration of lead ions released from nano-PbS and mic-PbO is similar, we suspect that this may be related to the unique size of nanoparticles. It has been confirmed that metal nanoparticles can penetrate cell membranes [62]. After nano-PbS enters cells, it accumulates in vacuoles to avoid damaging cells due to the cell’s detoxification mechanism [29]. Sulfur ions released by PbS are involved in the detoxification process of cells. Some sulfur-containing substances in plants, such as glutathione, cysteine, and plant-chelating peptides, play an important role in the process of plant resistance to heavy metal stress [63]. It has been documented that under Cu stress, supplying sufficient sulfate or elemental sulfur increases the content of glutathione and phytochelatins in high castors, thereby alleviating stress [64].

4. Conclusions

In-depth understanding of the interaction between heavy metal particles and plants is the basis for the prevention and control of heavy metal pollution in agriculture. Three kinds of lead (nano-PbS, mic-PbO and PbCl2) were applied to eggplant leaves for 5 days to study their effects on plant metabolomics. The results provide a comprehensive perspective on the molecular changes caused by Pb exposure in leaves. Importantly, although the absorption of nano-PbS by leaves was the largest, the observed metabolic changes were the least, which highlighted the importance of applying heavy metal forms. In eggplant leaves, nano-PbS, mic-PbO, and PbCl2 all induced reprogramming of carbon and nitrogen metabolism (including sugars, organic acids, amino acids and nitrogen-containing compounds). PbCl2 specifically induced more amino acid metabolic pathways and nucleotide metabolic pathways. This may be due to the high concentrations of Pb ions. Notably, this response might have adverse effects on crop yield and quality during prolonged exposure to Pb-containing particles due to the continuous release of lead ions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nano13222911/s1, Figure S1: Plant experiment; Figure S2: SEM images and size distributions of PbXn; Figure S3: Concentrations of Pb ions in 10 mg Pb/L PbXn suspensions and salt solutions; Figure S4: VIP scores from PLS-DA analysis of eggplant leaves showing the discriminating metabolites between unexposed control, nano-PbS, mic-PbO and PbCl2; Figure S5: Box plots of relative intensity of fatty acids in eggplant leaves after PbXn treatments; Figure S6: Box plots of relative intensity of sugars in eggplant leaves after PbXn treatments; Figure S7: Box plots of relative intensity of nucleotide/side metabolites in eggplant leaves after PbXn treatments; Figure S8: Box plots of relative intensity of organic acids and antioxidants in eggplant leaves after PbXn treatments; Figure S9: Box plots of relative intensity of metabolites in eggplant leaves after PbXn treatments; Table S1: Characterizations of PbXn (10 mg Pb/L) in pure water; Table S2: Perturbed biological pathways in eggplant leaves exposed to nano-PbS; Table S3: Perturbed biological pathways in eggplant leaves exposed to mic-PbO; Table S4: Perturbed biological pathways in eggplant leaves exposed to PbCl2.

Author Contributions

Conceptualization, S.Z. and Q.Z.; methodology, B.Z.; software, B.Z.; validation, X.Z., S.Z. and F.W.; formal analysis, B.Z.; investigation, F.W.; resources, S.Z.; data curation, Q.Z.; writing—original draft preparation, B.Z.; writing—review and editing, Q.Z.; visualization, S.Z.; supervision, F.W.; project administration, Q.Z.; funding acquisition, S.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by the National Natural Science Foundation of China (42022056, 42192574, 21976186, 22176196, 42077394, 42277423), the GDAS’ Project of Science and Technology Development (2022GDASZH-2022010105, 2022GDASZH-2022020402, 2020GDASYL-20200101002, 2021GDASYL-20210302003), and the Guangdong Foundation for Program of Science and Technology Research (Grant Nos. 2020B1212060048, 2019B121201004). The authors also acknowledge the Youth Innovation Promotion Association CAS awarded to S.Z. (2017–2020), the CAS Pioneer Hundred Talents Program awarded to X.Z. (2016–2021), the Liaoning Province Natural Science Foundation (2020-YQ-10), the Revitalize Liaoning Talents Program (XLYC2007124, XLYC1907136, XLYC1907118), and the Shenyang Pioneer Scientific and Technological Innovation Talents Team (RC190362).

Data Availability Statement

The data can be shared upon contact with the corresponding author (zhaoqing@iae.ac.cn).

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Funasaka, K.; Tojo, T.; Katahira, K.; Shinya, M.; Miyazaki, T.; Kamiura, T.; Yamamoto, O.; Moriwaki, H.; Tanida, H.; Takaoka, M. Detection of Pb-Liii Edge Xanes Spectra of Urban Atmospheric Particles Combined with Simple Acid Extraction. Sci. Total Environ. 2008, 403, 230–234. [Google Scholar] [CrossRef] [PubMed]
  2. Gao, P.-P.; Xue, P.-Y.; Dong, J.-W.; Zhang, X.-M.; Sun, H.-X.; Geng, L.-P.; Luo, S.-X.; Zhao, J.-J.; Liu, W.-J. Contribution of Pm2.5-Pb in Atmospheric Fallout to Pb Accumulation in Chinese Cabbage Leaves Via Stomata. J. Hazard. Mater. 2021, 407, 124356. [Google Scholar] [PubMed]
  3. Guo, G.; Zhang, D.; Wang, Y. Characteristics of Heavy Metals in Size-Fractionated Atmospheric Particulate Matters and Associated Health Risk Assessment Based on the Respiratory Deposition. Environ. Geochem. Hlth. 2021, 43, 285–299. [Google Scholar]
  4. Rai, P.K.; Lee, S.S.; Zhang, M.; Tsang, Y.F.; Kim, K.-H. Heavy Metals in Food Crops: Health Risks, Fate, Mechanisms, and Management. Environ. Int. 2019, 125, 365–385. [Google Scholar]
  5. Li, L.; Zhang, Y.; Ippolito, J.A.; Xing, W.; Qiu, K.; Yang, H. Lead Smelting Effects Heavy Metal Concentrations in Soils, Wheat, and Potentially Humans. Environ. Pollut. 2020, 257, 113641. [Google Scholar]
  6. Liao, J.; Cai, X.; Yang, Y.; Chen, Q.; Gao, S.; Liu, G.; Sun, L.; Luo, Z.; Lei, T.; Jiang, M. Dynamic Study of the Lead (Pb) Tolerance and Accumulation Characteristics of New Dwarf Bamboo in Pb-Contaminated Soil. Chemosphere 2021, 282, 131089. [Google Scholar]
  7. Ye, J.; Liao, W.; Zhang, P.; Li, J.; Nabi, M.; Wang, S.; Cai, Y.; Li, F. Fe1-Xs/Biochar Combined with Thiobacillus Enhancing Lead Phytoavailability in Contaminated Soil: Preparation of Biochar, Enrichment of Thiobacillus and Their Function on Soil Lead. Environ. Pollut. 2020, 267, 115447. [Google Scholar]
  8. Zhang, X.; Yang, H.; Schaufelberger, M.; Li, X.; Cao, Q.; Xiao, H.; Ren, Z. Role of Flavonol Synthesized by Nucleus Fls1 in Arabidopsis Resistance to Pb Stress. J. Agric. Food Chem. 2020, 68, 9646–9653. [Google Scholar] [CrossRef]
  9. Hong, J.; Yang, L.; Zhang, D.; Shi, J. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science. Int. J. Mol. Sci. 2016, 17, 767. [Google Scholar] [CrossRef]
  10. Hall, R.D. Plant Metabolomics: From Holistic Hope, to Hype, to Hot Topic. New Phytol. 2006, 169, 453–468. [Google Scholar] [CrossRef]
  11. Zhao, L.; Huang, Y.; Hu, J.; Zhou, H.; Adeleye, A.S.; Keller, A.A. 1h Nmr and Gc-Ms Based Metabolomics Reveal Defense and Detoxification Mechanism of Cucumber Plant under Nano-Cu Stress. Environ. Sci. Technol. 2016, 50, 2000–2010. [Google Scholar] [CrossRef] [PubMed]
  12. Zhao, L.; Ortiz, C.; Adeleye, A.S.; Hu, Q.; Zhou, H.; Huang, Y.; Keller, A.A. Metabolomics to Detect Response of Lettuce (Lactuca sativa) to Cu(Oh)2 Nanopesticides: Oxidative Stress Response and Detoxification Mechanisms. Environ. Sci. Technol. 2016, 50, 9697–9707. [Google Scholar] [CrossRef] [PubMed]
  13. Zhao, L.; Huang, Y.; Adeleye, A.S.; Keller, A.A. Metabolomics Reveals Cu(Oh)2 Nanopesticide-Activated Anti-Oxidative Pathways and Decreased Beneficial Antioxidants in Spinach Leaves. Environ. Sci. Technol. 2017, 51, 10184–10194. [Google Scholar] [PubMed]
  14. Pidatala, V.R.; Li, K.; Sarkar, D.; Ramakrishna, W.; Datta, R. Identification of Biochemical Pathways Associated with Lead Tolerance and Detoxification in Chrysopogon zizanioides L. Nash (Vetiver) by Metabolic Profiling. Environ. Sci. Technol. 2016, 50, 2530–2537. [Google Scholar] [CrossRef] [PubMed]
  15. Li, K.; Wang, X.; Pidatala, V.R.; Chang, C.P.; Cao, X. Novel Quantitative Metabolomic Approach for the Study of Stress Responses of Plant Root Metabolism. J. Proteome Res. 2014, 13, 5879–5887. [Google Scholar] [CrossRef] [PubMed]
  16. Ma, C.; Liu, F.-Y.; Hu, B.; Wei, M.-B.; Zhao, J.-H.; Zhang, K.; Zhang, H.-Z. Direct Evidence of Lead Contamination in Wheat Tissues from Atmospheric Deposition Based on Atmospheric Deposition Exposure Contrast Tests. Ecotox. Environ. Safe. 2019, 185, 109688. [Google Scholar]
  17. Tan, M.; Zhang, G.; Li, X.; Zhang, Y.; Yue, W.; Chen, J.; Wang, Y.; Li, A.; Li, Y.; Zhang, Y. Comprehensive Study of Lead Pollution in Shanghai by Multiple Techniques. Anal. Chem. 2006, 78, 8044–8050. [Google Scholar] [CrossRef]
  18. Grantz, D.; Garner, J.; Johnson, D. Ecological Effects of Particulate Matter. Environ. Int. 2003, 29, 213–239. [Google Scholar]
  19. Xiong, T.; Leveque, T.; Shahid, M.; Foucault, Y.; Mombo, S.; Dumat, C. Lead and Cadmium Phytoavailability and Human Bioaccessibility for Vegetables Exposed to Soil or Atmospheric Pollution by Process Ultrafine Particles. J. Environ. Qual. 2014, 43, 1593–1600. [Google Scholar]
  20. Schreck, E.; Dappe, V.; Sarret, G.; Sobanska, S.; Nowak, D.; Nowak, J.; Stefaniak, E.A.; Magnin, V.; Ranieri, V.; Dumat, C. Foliar or Root Exposures to Smelter Particles: Consequences for Lead Compartmentalization and Speciation in Plant Leaves. Sci. Total Environ. 2014, 476, 667–676. [Google Scholar]
  21. Liu, W.; Majumdar, S.; Li, W.; Keller, A.A.; Slaveykova, V.I. Metabolomics for Early Detection of Stress in Freshwater Alga Poterioochromonas Malhamensis Exposed to Silver Nanoparticles. Sci. Rep.-UK 2020, 10, 20563. [Google Scholar]
  22. Li, P.; Wang, A.; Du, W.; Mao, L.; Zhao, L. Insight into the Interaction between Fe-Based Nanomaterials and Maize (Zea mays) Plants at Metabolic Level. Sci. Total Environ. 2020, 738, 139795. [Google Scholar] [CrossRef]
  23. Dunn, W.B.; Broadhurst, D.; Begley, P.; Zelena, E.; Francis-McIntyre, S.; Anderson, N.; Brown, M.; Knowles, J.D.; Halsall, A.; Haselden, J.N. Procedures for Large-Scale Metabolic Profiling of Serum and Plasma Using Gas Chromatography and Liquid Chromatography Coupled to Mass Spectrometry. Nat. Protoc. 2011, 6, 1060–1083. [Google Scholar]
  24. Dieterle, F.; Ross, A.; Schlotterbeck, G.; Senn, H. Probabilistic Quotient Normalization as Robust Method to Account for Dilution of Complex Biological Mixtures. Application in 1h Nmr Metabonomics. Anal. Chem. 2006, 78, 4281–4290. [Google Scholar] [CrossRef] [PubMed]
  25. Jung, Y.; Ahn, Y.G.; Kim, H.K.; Moon, B.C.; Lee, A.Y.; Hwang, G.-S. Characterization of Dandelion Species Using 1h Nmr-and Gc-Ms-Based Metabolite Profiling. Analyst 2011, 136, 4222–4231. [Google Scholar] [CrossRef] [PubMed]
  26. Xia, J.; Wishart, D.S. Msea: A Web-Based Tool to Identify Biologically Meaningful Patterns in Quantitative Metabolomic Data. Nucleic Acids Res. 2010, 38 (Suppl. 2), W71–W77. [Google Scholar] [CrossRef] [PubMed]
  27. Lowry, G.V.; Avellan, A.; Gilbertson, L.M. Opportunities and Challenges for Nanotechnology in the Agri-Tech Revolution. Nat. Nanotechnol. 2019, 14, 517–522. [Google Scholar] [CrossRef]
  28. Holmes, E.; Antti, H. Chemometric Contributions to the Evolution of Metabonomics: Mathematical Solutions to Characterising and Interpreting Complex Biological Nmr Spectra. Analyst 2002, 127, 1549–1557. [Google Scholar] [CrossRef]
  29. Ma, J.F. Role of Organic Acids in Detoxification of Aluminum in Higher Plants. Plant Cell Physiol. 2000, 41, 383–390. [Google Scholar] [CrossRef]
  30. Meier, S.; Alvear, M.; Borie, F.; Aguilera, P.; Ginocchio, R.; Cornejo, P. Influence of Copper on Root Exudate Patterns in Some Metallophytes and Agricultural Plants. Ecotox. Environ. Safe. 2012, 75, 8–15. [Google Scholar]
  31. Nigam, R.; Srivastava, S.; Prakash, S.; Srivastava, M. Cadmium Mobilisation and Plant Availability–the Impact of Organic Acids Commonly Exuded from Roots. Plant Soil 2001, 230, 107–113. [Google Scholar] [CrossRef]
  32. Duressa, D.; Soliman, K.; Taylor, R.; Senwo, Z. Proteomic Analysis of Soybean Roots under Aluminum Stress. Int. J. Plant Genom. 2011, 2011, 1–12. [Google Scholar] [CrossRef] [PubMed]
  33. Bromke, M. Amino Acid Biosynthesis Pathways in Diatoms. Metabolites 2013, 3, 294–311. [Google Scholar] [CrossRef] [PubMed]
  34. Miyashita, Y.; Good, A.G. Glutamate Deamination by Glutamate Dehydrogenase Plays a Central Role in Amino Acid Catabolism in Plants. Plant Signal. Behav. 2008, 3, 842–843. [Google Scholar] [CrossRef] [PubMed]
  35. Sharma, S.S.; Dietz, K.-J. The Significance of Amino Acids and Amino Acid-Derived Molecules in Plant Responses and Adaptation to Heavy Metal Stress. J. Exp. Bot. 2006, 57, 711–726. [Google Scholar]
  36. Tzin, V.; Galili, G. The Biosynthetic Pathways for Shikimate and Aromatic Amino Acids in Arabidopsis Thaliana. In Arabidopsis Book; American Society of Plant Biologists: Rockville, MD, USA, 2010; Volume 8. [Google Scholar]
  37. Saradhi, P.P. Proline Accumulation under Heavy Metal Stress. J. Plant Physiol. 1991, 138, 554–558. [Google Scholar]
  38. Binder, S.; Knill, T.; Schuster, J. Branched-Chain Amino Acid Metabolism in Higher Plants. J. Plant Physiol. 2007, 129, 68–78. [Google Scholar] [CrossRef]
  39. Joy, K. Ammonia, Glutamine, and Asparagine: A Carbon–Nitrogen Interface. Can. J. Bot. 1988, 66, 2103–2109. [Google Scholar] [CrossRef]
  40. Forde, B.G.; Lea, P.J. Glutamate in Plants: Metabolism, Regulation, and Signalling. J. Exp. Bot. 2007, 58, 2339–2358. [Google Scholar] [CrossRef]
  41. Lieberman, M.A.; Ricer, R. Brs Biochemistry, Molecular Biology, and Genetics; Lippincott Williams & Wilkins: Philadelphia, PA, USA, 2019. [Google Scholar]
  42. Shelp, B.J.; Bown, A.W.; McLean, M.D. Metabolism and Functions of Gamma-Aminobutyric Acid. Trends Plant Sci. 1999, 4, 446–452. [Google Scholar] [CrossRef]
  43. Hall, J.á. Cellular Mechanisms for Heavy Metal Detoxification and Tolerance. J. Exp. Bot. 2002, 53, 1–11. [Google Scholar] [CrossRef] [PubMed]
  44. Zhao, Y.; Zhao, J.; Zhao, C.; Zhou, H.; Li, Y.; Zhang, J.; Li, L.; Hu, C.; Li, W.; Peng, X. A Metabolomics Study Delineating Geographical Location-Associated Primary Metabolic Changes in the Leaves of Growing Tobacco Plants by Gc-Ms and Ce-Ms. Sci. Rep.-UK 2015, 5, 16346. [Google Scholar] [CrossRef]
  45. Stasolla, C.; Katahira, R.; Thorpe, T.A.; Ashihara, H. Purine and Pyrimidine Nucleotide Metabolism in Higher Plants. J. Plant Physiol. 2003, 160, 1271–1295. [Google Scholar] [PubMed]
  46. Moffatt, B.A.; Ashihara, H. Purine and Pyrimidine Nucleotide Synthesis and Metabolism. In Arabidopsis Book; American Society of Plant Biologists: Rockville, MD, USA, 2002; Volume 1. [Google Scholar]
  47. Zhao, L.; Hu, Q.; Huang, Y.; Fulton, A.N.; Hannah-Bick, C.; Adeleye, A.S.; Keller, A.A. Activation of Antioxidant and Detoxification Gene Expression in Cucumber Plants Exposed to a Cu(Oh)2 Nanopesticide. Environ. Sci.-Nano 2017, 4, 1750–1760. [Google Scholar]
  48. Xie, Y.; Hu, L.; Du, Z.; Sun, X.; Amombo, E.; Fan, J.; Fu, J. Effects of Cadmium Exposure on Growth and Metabolic Profile of Bermudagrass [Cynodon dactylon (L.) Pers]. PLoS ONE 2014, 9, e115279. [Google Scholar]
  49. Akram, M. Citric Acid Cycle and Role of Its Intermediates in Metabolism. Cell Biochem. Biophys. 2014, 68, 475–478. [Google Scholar] [CrossRef]
  50. Anderson, N.M.; Mucka, P.; Kern, J.G.; Feng, H. The Emerging Role and Targetability of the Tca Cycle in Cancer Metabolism. Protein Cell 2018, 9, 216–237. [Google Scholar]
  51. Zhao, L.; Huang, Y.; Keller, A.A. Comparative Metabolic Response between Cucumber (Cucumis sativus) and Corn (Zea mays) to a Cu(Oh)2 Nanopesticide. J. Agric. Food Chem. 2017, 66, 6628–6636. [Google Scholar] [CrossRef]
  52. Berglund, T.; Lindström, A.; Aghelpasand, H.; Stattin, E.; Ohlsson, A.B. Protection of Spruce Seedlings against Pine Weevil Attacks by Treatment of Seeds or Seedlings with Nicotinamide, Nicotinic Acid and Jasmonic Acid. Forestry 2016, 89, 127–135. [Google Scholar] [CrossRef]
  53. Zhao, L.; Hu, Q.; Huang, Y.; Keller, A.A. Response at Genetic, Metabolic, and Physiological Levels of Maize (Zea mays) Exposed to a Cu(Oh)2 Nanopesticide. ACS Sustain. Chem. Eng. 2017, 5, 8294–8301. [Google Scholar] [CrossRef]
  54. Taylor, N.L.; Heazlewood, J.L.; Day, D.A.; Millar, A.H. Lipoic Acid-Dependent Oxidative Catabolism of A-Keto Acids in Mitochondria Provides Evidence for Branched-Chain Amino Acid Catabolism in Arabidopsis. Plant Physiol. 2004, 134, 838–848. [Google Scholar] [CrossRef] [PubMed]
  55. Muller, B.; Pantin, F.; Génard, M.; Turc, O.; Freixes, S.; Piques, M.; Gibon, Y. Water Deficits Uncouple Growth from Photosynthesis, Increase C Content, and Modify the Relationships between C and Growth in Sink Organs. J. Exp. Bot. 2011, 62, 1715–1729. [Google Scholar] [PubMed]
  56. Van den Ende, W.; Valluru, R. Sucrose, Sucrosyl Oligosaccharides, and Oxidative Stress: Scavenging and Salvaging? J. Exp. Bot. 2009, 60, 9–18. [Google Scholar] [CrossRef]
  57. Galili, G.; Tang, G.; Zhu, X.; Gakiere, B. Lysine Catabolism: A Stress and Development Super-Regulated Metabolic Pathway. Curr. Opin. Plant Biol. 2001, 4, 261–266. [Google Scholar] [PubMed]
  58. Zhao, L.; Zhang, H.; White, J.C.; Chen, X.; Li, H.; Qu, X.; Ji, R. Metabolomics Reveals That Engineered Nanomaterial Exposure in Soil Alters Both Soil Rhizosphere Metabolite Profiles and Maize Metabolic Pathways. Environ. Sci.-Nano 2019, 6, 1716–1727. [Google Scholar]
  59. Huang, Y.; Adeleye, A.S.; Zhao, L.; Minakova, A.S.; Anumol, T.; Keller, A.A. Antioxidant Response of Cucumber (Cucumis sativus) Exposed to Nano Copper Pesticide: Quantitative Determination Via Lc-Ms/Ms. Food Chem. 2019, 270, 47–52. [Google Scholar] [CrossRef]
  60. Zhang, H.; Du, W.; Peralta-Videa, J.R.; Gardea-Torresdey, J.L.; White, J.C.; Keller, A.; Guo, H.; Ji, R.; Zhao, L. Metabolomics Reveals How Cucumber (Cucumis sativus) Reprograms Metabolites to Cope with Silver Ions and Silver Nanoparticle-Induced Oxidative Stress. Environ. Sci. Technol. 2018, 52, 8016–8026. [Google Scholar] [CrossRef]
  61. Schreck, E.; Foucault, Y.; Sarret, G.; Sobanska, S.; Cecillon, L.; Castrec-Rouelle, M.; Uzu, G.; Dumat, C. Metal and Metalloid Foliar Uptake by Various Plant Species Exposed to Atmospheric Industrial Fallout: Mechanisms Involved for Lead. Sci. Total Environ. 2012, 427–428, 253–262. [Google Scholar]
  62. Liu, Y.; Peng, B.; Sohrabi, S.; Liu, Y. The Configuration of Copolymer Ligands on Nanoparticles Affects Adhesion and Uptake. Langmuir 2016, 32, 10136–10143. [Google Scholar] [CrossRef]
  63. Astolfi, S.; Zuchi, S.; Passera, C. Effect of Cadmium on H+ Atpase Activity of Plasma Membrane Vesicles Isolated from Roots of Different S-Supplied Maize (Zea mays L.) Plants. Plant Sci. 2005, 169, 361–368. [Google Scholar] [CrossRef]
  64. Ren, G.; Hu, H. Effects of Sulfur on Toxicity and Bioavailability of Cu for Castor (Ricinus communis L.) in Cu-Contaminated Soil. Environ. Sci. Pollut. R. 2017, 24, 27476–27483. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Mass of Pb in the leaves, stems and roots of eggplant plants exposed to PbXn (MPb = 170 μg) for 5 days. The lowercase letters on top of columns indicate significant differences between different Pb species (p < 0.05). Data are reported as the mean and standard deviation (n = 5). PbS: nano-PbS; PbO: mic-PbO; CK: control.
Figure 1. Mass of Pb in the leaves, stems and roots of eggplant plants exposed to PbXn (MPb = 170 μg) for 5 days. The lowercase letters on top of columns indicate significant differences between different Pb species (p < 0.05). Data are reported as the mean and standard deviation (n = 5). PbS: nano-PbS; PbO: mic-PbO; CK: control.
Nanomaterials 13 02911 g001
Figure 2. Multivariate analysis of LC-MS metabolite data of eggplant leaves. (a) Score plot of the principle component analysis (PCA); (b) score plot of the partial least-squares discriminant analysis (PLS-DA). Each treatment had six replicates.
Figure 2. Multivariate analysis of LC-MS metabolite data of eggplant leaves. (a) Score plot of the principle component analysis (PCA); (b) score plot of the partial least-squares discriminant analysis (PLS-DA). Each treatment had six replicates.
Nanomaterials 13 02911 g002
Figure 3. Venn diagrams showing the overlapping and interconnection of metabolites with a VIP score > 1 in eggplant leaves with different PbXn exposures compared with the control. Numbers represent the number of differential metabolites.
Figure 3. Venn diagrams showing the overlapping and interconnection of metabolites with a VIP score > 1 in eggplant leaves with different PbXn exposures compared with the control. Numbers represent the number of differential metabolites.
Nanomaterials 13 02911 g003
Figure 4. Box plots of the relative intensity of amino acids in eggplant leaves after 5 days of PbXn-treatments. PbS: nano-PbS; PbO: mic-PbO; CK: control. * represents a significant difference at the p < 0.05 level.
Figure 4. Box plots of the relative intensity of amino acids in eggplant leaves after 5 days of PbXn-treatments. PbS: nano-PbS; PbO: mic-PbO; CK: control. * represents a significant difference at the p < 0.05 level.
Nanomaterials 13 02911 g004
Figure 5. Schematic diagram of the proposed metabolic pathways in eggplant leaves exposed to PbXn. Red and green represent the up- and down-regulated metabolites, respectively.
Figure 5. Schematic diagram of the proposed metabolic pathways in eggplant leaves exposed to PbXn. Red and green represent the up- and down-regulated metabolites, respectively.
Nanomaterials 13 02911 g005
Figure 6. Summary of pathway analysis with MetaboAnalyst 4.0. All identified metabolites were considered in the pathway analysis. The numbers (1–10) represent the metabolic pathways that interferes.
Figure 6. Summary of pathway analysis with MetaboAnalyst 4.0. All identified metabolites were considered in the pathway analysis. The numbers (1–10) represent the metabolic pathways that interferes.
Nanomaterials 13 02911 g006
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, S.; Zhao, B.; Zhang, X.; Wu, F.; Zhao, Q. The Metabolomics Response of Solanum melongena L. Leaves to Various Forms of Pb. Nanomaterials 2023, 13, 2911. https://doi.org/10.3390/nano13222911

AMA Style

Zhang S, Zhao B, Zhang X, Wu F, Zhao Q. The Metabolomics Response of Solanum melongena L. Leaves to Various Forms of Pb. Nanomaterials. 2023; 13(22):2911. https://doi.org/10.3390/nano13222911

Chicago/Turabian Style

Zhang, Siyu, Bing Zhao, Xuejiao Zhang, Fengchang Wu, and Qing Zhao. 2023. "The Metabolomics Response of Solanum melongena L. Leaves to Various Forms of Pb" Nanomaterials 13, no. 22: 2911. https://doi.org/10.3390/nano13222911

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop