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Article

Suaeda glauca and Suaeda salsa Employ Different Adaptive Strategies to Cope with Saline–Alkali Environments

by
Xiaoqian Song
1,2,
Nan Yang
1,2,
Yuhang Su
1,2,
Xueyan Lu
3,
Jia Liu
4,
Yang Liu
5,
Zhonghua Zhang
1,2,* and
Zhonghua Tang
1,2,*
1
College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University, Harbin 150040, China
2
Key Laboratory of Forest Plant Ecology, Ministry of Education, Northeast Forestry University, Harbin 150040, China
3
Center for Ecological Research, Northeast Forestry University, Harbin 150040, China
4
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin 150040, China
5
School of Life Sciences, Heilongjiang University, Harbin 150040, China
*
Authors to whom correspondence should be addressed.
Agronomy 2022, 12(10), 2496; https://doi.org/10.3390/agronomy12102496
Submission received: 31 August 2022 / Revised: 3 October 2022 / Accepted: 10 October 2022 / Published: 13 October 2022
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Abstract

:
(1) Background: soil salinization has become a global problem that restricts agricultural production; thus, there is a need to explore the special survival strategies of halophytes in saline–alkali environments. (2) Methods: this study conducted a comparative analysis of the differences in metabolites and mineral elements between two indicator plants (Suaeda glauca and Suaeda salsa) in the study area. (3) Results: S. salsa leaves accumulated more total nitrogen (TN), total organic carbon (TOC), calcium (Ca), sodium (Na) and manganese (Mn). The Na/K analysis showed that S. salsa was more tolerant of saline–alkali environments than S. glauca. Metabolite analysis revealed a significant increase in added sugars in S. salsa compared with S. glauca and a significant accumulation of most organic acids associated with the TCA cycle, which suggests an enhancement in the flow of carbon from glycolysis to the TCA cycle. In addition, the content of phenolic substances, such as phenylpropane compounds and flavonols, also changed in saline–alkali environments, which may have promoted the metabolism of organic acids. (4) Conclusions: during the process of plant adaptation to salinity, the central metabolism of S. glauca was nitrogen metabolism, while that of S. salsa was organic acid metabolism.

1. Introduction

Soil salinization is a worldwide problem for resources and the environment. According to statistics, 7% of the world’s land area and 70% of agricultural land is affected by salinization [1], and most of these areas are in arid regions scattered across continents. Researchers have predicted that by 2050, 50% of the world’s land area will be threatened by salinization due to global vegetation destruction and uneven rainfall [2]. The area of salinized land in China is approximately 100 million hm2, accounting for approximately 10.3% of the country’s land area. In recent years, the Hulunbuir grassland has been seriously degraded, with a large area of desertification. The area of salinized soil has reached 460,000 hectares, accounting for more than 62.68% of the grassland area [3]. Salinity stress has negative effects on plant growth and development and has gradually reduced crop productivity. Excessive soil salinity can cause ion toxicity [4,5] and nutrient deficiencies [6,7], and it induces many metabolic changes that affect the overall growth of salt-sensitive plants and even some halophytes. Therefore, a better understanding of the unique survival strategies of halophytes adapted to specific environments is of crucial importance for the improvement of saline–alkali land, grassland restoration and crop salt tolerance.
In recent years, research on halophytes has gradually become a popular topic, with studies mainly focusing on indoor simulations and short-term treatment [8,9,10], as well as the mechanism of salt tolerance in plants and developing crop substitutes [11]. While plant breeders have successfully improved salt tolerance in some plants in recent decades, selection may be more convenient and practical if unique indicators of salt tolerance at the whole plant, tissue or cellular level are identified. Thus, there is a need to understand the underlying metabolomic and ionomic prospects of salinity tolerance to provide plant breeders with appropriate indicators. Metabolomics can be used to reveal the mechanism of the plant stress response, with the main target being metabolites with molecular weights of less than one thousand kilodaltons [12]. The ultrahigh sensitivity of gas chromatography–mass spectrometry (GC–MS) enables more low-level metabolites to be detected, such as amino acids, carbohydrates, sugar alcohols, lipids, organic acids and hormones, which are involved in the primary metabolism of the central pathways in plants [13,14]. Phenolics are produced by many plant species for protection against biotic or abiotic stress during growth, and their accumulation correlates with the antioxidant capacity of plants across several species [15]. The content of phenolics is also altered under increased salinity [5]. The production of antioxidative polyphenol compounds in response to salinity in halophytes was also observed [16]. However, in most cases, the effects of salinity on the induction of plant secondary metabolism have been assessed by studying changes in plant carbon and oxidative metabolism, as well as nutrient and ion accumulation and impairment of the physiological processes associated with the production of plant secondary metabolites [17]. Plant metabolites have different metabolically stable states under different environmental conditions, and therefore, metabolites can serve as a key basis for plants to respond to the environment [14,18]. For example, in a metabolomics study of the halophyte Cansjera rheedei under long-term salt stress, it was found that salt induced significant differences in the expression of related compounds in central metabolic pathways, including carbon metabolism, amino acid metabolism and the tricarboxylic acid cycle [8]. In the latest study, the elemental composition of eight different salt-tolerant types of Chenopodiaceae plants in the Hulunbuir saline–alkali grassland showed that elements including K, Ca and Mg had a higher level of accumulation in recretohalophyte leaves. In salt-dilution halophytes, Na had a higher level of accumulation in the leaves [19]. With the development of omics technology, it has become possible to conduct research using multi-omics integration, which can help us further study the adaptation strategies and mechanisms of saline–alkali plants from the perspective of systems biology [20,21]. Although comprehensive omics and metabolomics analyses have been performed [22], there are few studies focused on the natural saline–alkali environment.
Currently, research on the mechanism of plant salt and alkali tolerance mainly focuses on model halophytes and nonhalophyte plants. Many wild plants have outstanding salt and alkali tolerance, which makes them not only important genetic resources for improving plant salt and alkali tolerance, but also excellent materials for mining key genes involved in salt and alkali tolerance. In our previous study, preliminary investigations showed that in the saline–alkali grassland of Hulunbuir New Barag Left Banner, Inner Mongolia, the long-adapted Suaeda glauca community [23] and Suaeda salsa community [24] are widely distributed as dominant communities. Among them, S. glauca and S. salsa are two very important salinity-tolerant species. S. glauca is considered a pioneer plant in saline–alkali land and exhibits high salt tolerance during germination, growth and reproduction [25]. S. salsa is considered an indicator plant for saline–alkali land and is the best plant for improving that land. Studies have shown that S. salsa has a stable ability to transfer salt under artificial planting conditions, and continuous planting of S. salsa can effectively improve severely saline soil in arid areas [26]. S. glauca and S. salsa are both annual salt-dilution halophytes of the genus Suaeda from the family Chenopodiaceae, and field investigations have shown that the two plants generally grow together and are morphologically similar. However, the leaf shape of S. glauca is that of fleshy filamentous strips, and the leaf color is green, while the leaf shape of S. salsa is fleshy cylindrical, the leaf color is yellow–green, and the front edge of the leaf is purple–red. Although some studies have also been carried out on these two plants, the energy distribution between the central and specific metabolism of these plants under the same saline–alkali environment remains unclear. In this study, two typical plants, S. glauca and S. salsa, were collected from the Hulunbuir saline–alkali grassland, and the effects of growth in saline–alkali habitats on the central metabolism (nitrogen metabolism), defensive metabolism (phenolic compounds) and ion accumulation of these two species were compared. The insights from this study provide an in-depth understanding of the adaptation strategies of plants in saline–alkali grasslands. In addition, we attempted to clarify the internal mechanism of the dominant species in the Hulunbuir area that have adapted to the saline–alkali environment, explore the functional metabolites related to saline–alkali tolerance and provide theoretical support for the protection, utilization and domestication of grassland germplasm resources, thereby increasing the production of grain, feed and bioenergy species in grassland saline–alkali land.

2. Materials and Methods

2.1. Sample Collection

The samples were collected from the New Barag Left Banner of Hulun Buir, Inner Mongolia Autonomous Region, China (N 48°20′53″–48°20′36″, E 118°6′1″–117°58′21″). The region has a mid-temperate continental monsoon climate, with long and severe winters and a snow cover period of approximately 140 days. The annual average temperature is 0.2 °C, the annual precipitation is approximately 280 mm and the annual evaporation is 950 to 1900 mm. According to early statistics, the Hulunbuir region contains the largest saline–alkali land area. In this study, 2 species of Chenopodiaceae (S. glauca and S. salsa) were collected from 3 saline–alkali grasslands in the New Barag Left Banner (Figure 1), and the soil type of the sampling plot was calcic chernozem. The sampling time coincided with the period of vigorous plant growth (July 28–August 2). Approximately 30–50 plant individuals with good growth and of a similar size were used as standard sample plants. Correspondingly, the rhizosphere soil (0–20 cm) surrounding each plant was obtained, and soil samples were collected from depths of 0–20 cm (i.e., the root layer) using a 100 cm3 cutting ring. The plants and soil collected from each plot were mixed together to obtain 3 independent plant and soil samples. Whole plants were sampled in the field, stored in a cryostat and then shipped back to the laboratory for cleaning and separation. The 3 plot samples collected were divided into 2 groups. One set was immediately frozen in liquid nitrogen and stored at −80 °C for primary metabolite analysis [8]. The other was oven-dried at 120 °C for 20 min. Then, the oven temperature was lowered to 60 °C, and the samples were dried to a constant weight, crushed (Nail AQ-180E) and passed through a 1 mm sieve for elemental and secondary metabolite analysis. Soil samples were processed to remove impurities, placed in a ventilated location to dry in the shade and ground and sieved (1 mm) for physicochemical analysis.

2.2. Determination of Soil Properties and Ion Contents

Electrical conductivity (EC) was chosen as the soil salinity index. Leaching solution with a 1:5 soil–water ratio was prepared according to the method described by the American Saline Soil Laboratory [27]. The soil pH was used to judge the acidity and alkalinity of the soil, and the ratio of soil to water was 1:5. The pH of the extract was determined using a PHS-3F pH meter (Shanghai Lei Magnetic Science Instrument Factory) [28]. Cl− and SO42− contents were determined with silver nitrate titration and EDTA complexometric titration, respectively. CO32− and HCO3− contents were determined via dual indicator titration. Ca2+ and Mg2+ contents were determined with EDTA complexing titration. K+ and Na+ contents were determined by flame atomic absorption spectrometry [29].

2.3. Elemental Analysis

Total organic carbon (TOC) concentrations in the plants were measured with the Walkley–Black method. Total nitrogen (TN) concentrations in the plants and soil were measured with the semi-micro-Kjeldahl method. Molybdenum antimony colorimetry was used to measure the total phosphorus (TP) concentrations in the plants. The elements present in the plants were determined by an inductively coupled plasma optical emission spectrometer (ICP–OES Optima 8000, Perkin Elmer), and the content was calculated according to the standard curve of each element [19].

2.4. Primary Metabolite Analysis

The extraction and detection of samples followed the detection method of Liu et al. [30] with slight modifications. A 90 mg plant sample was weighed, and 540 μL of cold methanol and 60 μL of the internal standard (L-2-chloro-phenylalanine, 0.3 mg mL−1 in methanol) were added and homogenized in a TissueLyser II (QIAGEN GmbH, Hilden, Germany). After removing the samples, ultrasonic extraction was performed for 30 min; then, 300 μL of chloroform and 600 μL of water were added. The sample was vortexed (20 Hz, 2 min), ultrasonically extracted for 30 min and subjected to cryogenic centrifugation for 10 min (14,000 rpm, 4 °C). Next, 700 μL of the supernatant was transferred to a glass vial and dried in vacuo. Finally, GC–MS analysis was performed.
This experiment used GC–MS (Agilent 7890A-5975C, Agilent Technologies, Inc., Santa Clara, CA, USA) for primary metabolite analysis. The detection samples were separated by a nonpolar DB-5MS capillary column (30 m × 250 μm I.D., J&W Scientific, Folsom, CA, USA) and then subjected to mass spectrometry detection. The sample was injected in split mode with a split ratio of 1:1, the temperature of the injection port and the transfer line was 260 °C and a constant flow rate of 1.0 mL/min was used. The GC temperature program was as follows: initially set to 50 °C, then an increase of 8 °C min−1 to an oven temperature of 125 °C, increase of 15 °C min−1 to 170 °C, increase of 4 °C min−1 to 210 °C, increase of 10 °C min −1 to 270 °C and increase of 5 °C min−1 to 305 °C, followed by a 5 min hold. Mass spectral signals were recorded while scanning from the 50–600 m/z interval, with a delay of 5 min at the start of the acquisition at a speed of 20 spectra/sec.

2.5. Determination of Phenol Metabolites

Phenolic metabolites were extracted and detected according to the method of Liu et al. [30]. First, 0.5 g of dry plant samples was weighed; then, 10 mL of 70% methanol (including methanol and water with a volume ratio of 7:3) was added. Ultrasonic-assisted extraction was performed for 45 min at room temperature, and the supernatant was collected after centrifugation at 8000 r/min for 10 min, followed by an addition of 10 mL of methanol. The solvent was subjected to a second ultrasonic extraction, and after centrifugation, the two supernatants were combined. The supernatants were filtered, concentrated to dryness under vacuum, reconstituted by adding 1 mL of 70% methanol to all samples and subsequently filtered through a 0.22 μm nylon membrane. Finally, the LC–MS analysis was performed.
The collected solution was analyzed by UPLC/Q-TOF-MS (Waters ® Xevo G2 QTOF, MA, USA). The mass spectrometer was run in positive-ion mode with a capillary voltage of 3.0 kV, cone voltage of 45 V, source temperature of 400 °C, desolvation temperature of 500 °C, cone gas flow of 50 L/h and desolvation gas flow of 800 L/h. The scan range was set to 50–1000 m/z, and the ion acquisition rate was 0.2 per second. Separations were performed using an ACQUITY UPLC BEH C18 Column (1.7 μm, 2.1 mm × 50 mm) with an in-line filter and maintained at 25 °C. The injection volume was 5 μL. The solutions, (A) 0.05% formic acid–water and (B) 0.05% formic acid–acetonitrile, were subjected to gradient elution at a flow rate of 0.5 mL/min for 0–20 min at 5% B and 95% B, 20–22.1 min at 95% B and 5% B and 22.1–28 min at 5% B and 5% B.

2.6. Statistical Analysis

Analysis of variance was performed on all data using SPSS 19.0 (SPSS Inc., Chicago, IL USA). Data are presented as the mean ± standard error (SE), and raw data from GC–MS were analyzed by data analysis software (Agilent GC–MS 5975) and converted into a NetCDF file. Each compound is shown as the peak area normalized to the internal standard. Compounds are identified by structural comparison, i.e., comparing retention times and mass spectra with known compounds in the National Institute of Standards and Technology (NIST) library. LC–MS data were analyzed and normalized by the mass spectrometry software MassLynxTM (Waters Corporation, Milford, MA, USA). The information on detected peaks includes detected and matched peaks along with retention time and m/z pairs and their corresponding intensities. Metabolite data were subjected to statistical (PLS-DA analysis and T test) and pathway enrichment analysis by MetaboAnalyst 5.0 after normalization by mean centering and unit-variance scaling. Correlations were based on the Pearson correlation analysis of SPSS 19.0 (p < 0.05), and the column chart was further completed by Origin 2017. The obtained S. glauca- and S. salsa-related networks were visualized by Cytoscape version 3.7.1.

3. Results

3.1. Differential Distribution of Mineral Elements in Leaves of S. glauca and S. salsa

The properties and ion contents in the soil surrounding S. glauca and S. salsa were detected first. Since the habitat conditions of the two plants were basically the same, higher levels of HCO3− were revealed in the soil surrounding S. salsa than in that surrounding S. glauca (Table 1).
No significant difference in the element content was observed between S. glauca and S. salsa apart from TN, TOC, Ca, Na, Mn and Na/K (Table 2). In S. salsa, both macroelements and microelements, including TN, TOC, Na and Mn, had higher levels of accumulation in the leaves. Compared to S. glauca, TN, TOC, Ca, Na and Mn were increased by approximately 50%, 20%, 60%, 30% and 25%, respectively, in S. salsa. In addition, the Na/K ratio can indirectly reflect the tolerance of plants to salt stress. The Na/K ratio was the highest in the leaves of S. salsa.

3.2. Primary Metabolite Profiles of Leaves in S. glauca and S. salsa

A total of 87 metabolites, including sugars, organic acids, amino acids, alcohols, amines and other compounds, were identified from the metabolite profiles of S. glauca and S. salsa. To reveal the differences between species, PLS-DA analysis of metabolites in the leaves of S. glauca and S. salsa was performed. From the PLS-DA score plot (Figure 2a), it can be seen that there is a clear distinction between the two plants, which are distinguished by the first principal component (PC 1), explaining 58.9% of the total variation, and the second principal component (PC 2), explaining 11.1% of the total variation. Moreover, the PLS-DA loading plots of the first two PCs are also presented. According to the PLS-DA loading plot (Figure 2b), the variation in leaves is mainly attributed to sucrose, malic acid, L-threonine, propanoic acid, leucine, D-xylose, D-fructose, D-galactose, carbamic acid and galactopyranose.
Moreover, a total of 33 metabolites with VIP > 1 were identified as having significant variations in the leaves of S. glauca and S. salsa (Figure 3). The changed metabolites were mainly amino acids, organic acids, sugars, alcohols and amines. Compared with S. glauca, 20 metabolites—namely carbamic acid, propanoic acid, ethanolamine, niacin, dodecane, trisiloxane, arabinofuranose, malic acid, arabinose, sucrose, putrescine, n-butylamine, citric acid, sulfurous acid, D-xylose, succinic acid, D-glucose, propylene glycol, pentasiloxane and D-fructose—increased in concentration, while 13 metabolites decreased in concentration in S. salsa (Figure 3).
To assess the induction of metabolic pathways under salinity, a KEGG pathway enrichment test was carried out. Pathway enrichment was used to identify the metabolic pathways containing significantly changed metabolites from our metabolite data. An interactive visualization of the pathway enrichment analysis results at the metabolome level is presented in Figure 4, and a detailed explanation of the pathway enrichment analysis is provided in Table A1. Moreover, pathway enrichment analysis was also carried out to study the relevant pathways involved in saline–alkali tolerance using the A. thaliana KEGG pathway library (Figure 4). There were seven biological pathways involved (−log p > 0.2, impact > 0.05) (Figure 4). Nevertheless, the citric acid cycle (TCA cycle) had the highest enrichment value (−log p > 2) with the highest impact (p > 0.15).

3.3. Secondary Metabolite Profiles of Leaves between S. glauca and S. salsa

In the analysis of nontargeted metabolomics by GC–MS, compared with S. glauca, the tolerance and adaptability of S. salsa to saline–alkali stress were mainly manifested in the accumulation of higher contents of metabolites. To further explore the reasons for the differences in tolerance, LC–MS was performed to examine phenolic metabolism in response to saline–alkali stress. A total of 31 phenolic compounds, including 5 phenylpropanoids, 6 phenolic acids, 16 flavonoids and 3 other compounds, were detected by LC–MS and were significant based on VIP > 1 and an independent samples T test (p < 0.05). In total, 13 different phenolic compounds were obtained; these compounds differed widely in abundance in S. glauca and S. salsa. Seven compounds, isoliquiritigenin, gallic acid, chlorogenic acid, luteolin, vanillic acid and genistein, showed extremely significant accumulation in S. glauca, while kaempferol, ferulic acid, protocatechuic acids, p-hydroxybenzoic acid, L-phenylalanine, rutin and naringenin showed extremely significant accumulation in S. salsa (Table 3).
To obtain differential metabolites related to salt tolerance, metabolite pathway enrichment analysis was performed on phenolic compounds in S. glauca and S. salsa (Figure 5). As shown, differences in the properties of phenolic metabolites can be clearly observed. These phenolic metabolites are involved in flavone and flavonol biosynthesis, flavonoid biosynthesis, the biosynthesis of phenylpropanopanoids, ubiquinone and other terpenoid–quinone biosynthesis and aminobenzoate degradation. Compared with S. glauca, the flavonoid kaempferol, the phenolic acid protocatechuic acid and the phenylpropanoids L-phenylalanine were significantly accumulated in S. salsa.

3.4. Correlation-Based Network Analysis for Uncovering Metabolite Variation in S. glauca and S. salsa under Saline–Alkali Stress

To more intuitively understand the similarities or differences in primary metabolites and phenolic compounds between S. glauca and S. salsa, metabolic pathway maps were obtained by integrating the measured primary metabolites and phenolic compounds. Figure 6 shows that in S. glauca leaves, carbohydrates are the primary metabolites. For example, D-glucose, D-fructose and galactopyranose accumulated significantly. Valine accumulated significantly in S. glauca leaves. In addition, the organic acid and fumaric acid also accumulated significantly in S. glauca leaves. Compared with S. glauca, the sugar compounds sucrose and arabinofuranose, the TCA cycle compounds succinic acid and malic acid and various organic acid compounds—including galactaric acid, carbamic acid and sulfurous acid—accumulated significantly in S. salsa leaves. Furthermore, several secondary compounds, precursors and final phenolic metabolites, such as L-phenylalanine, p-coumaric acid, caffeic acid, ferulic acid, naringenin, kaempferol, quercetin and quercetin-3-O-rhamnoside, accumulated in S. salsa leaves. Other phenolic metabolites, including isoliquiritigenin, cinnamic acid, salicylic acid, vanillic acid, syringic acid, genistein, luteolin, gallic acid and chlorogenic acid, were mainly distributed in S. glauca leaves. From the metabolic pathway, it is obvious that S. glauca mainly accumulates compounds through the flavonoid synthesis pathway, while S. salsa mainly accumulates compounds through the flavonol synthesis pathway, indicating the difference between S. glauca and S. salsa in response to saline–alkali stress.

4. Discussion

Long-term exposure to a saline–alkali environment enables plants to evolve a complex adaptive system, allowing them to effectively adapt to harsh environments and avoid extinction [31]. Therefore, to survive under high-salt conditions, plants must maintain a proper ion balance. Halophytes alter mineral ion uptake through the selective accumulation or exclusion of ions under high-salinity conditions [32] to reduce the toxicity caused by high-salt concentrations [33]. At higher Na+ concentrations, deficiency of K+ in the cytosol is a result of the poor retention of K+ caused by Na+-induced membrane depolarization, which results in K+ efflux through depolarization-activated KOR channels [34,35]. Moreover, to maintain ion balance, highly selective absorption of K+ and Ca2+ is an important adaptive mechanism of Leymus chinensis under saline–alkali stress [36]. In our study, a significant increase in Ca was observed in S. salsa leaves compared with S. glauca leaves. This increase has also been reported previously in other halophytes under salt stress, namely Sesuvium portulacastrum [37], Kochia sieversiana [38] and Suaeda glauca [39]. Therefore, the accumulation of calcium in plants may be beneficial to maintain ionic balance and promote the healthy growth of saline–alkali grassland plants.
Additionally, halophytes adopt various mechanisms to prevent the accumulation of Na+ in the cytoplasm, including Na+ extrusion and/or intracellular compartmentalization of Na+ and the recirculation of Na+ out of the shoot [40]. In the present study, S. glauca and S. salsa, as salt-dilution halophytes, accumulated Na+ in the vacuoles of succulent leaves and green tissues and in succulent columns. However, both halophytes showed selective absorption of elements. Elements such as TN, TOC, Ca, Na and Mn accumulated more in the leaves of S. glauca, while other elements accumulated more in the leaves of S. salsa. This difference can be explained by their different adaptive strategy mechanisms in salt environments.
Under salinity stress, the accumulation of compatible solutes is most effective in reducing osmotic stress, leading to severe osmotic imbalance and causing detrimental changes at the physiological and molecular levels in cellular components [41]. To combat such conditions, plants respond with up- and downregulation of a wide range of metabolites, which provides protection against the detrimental effects of salinity. A wide range of metabolites have been identified. The compatible solutes comprise sugars, sugar alcohols, nitrogen-containing compounds and organic acids [42]. These solutes also function to protect cellular structures by scavenging reactive oxygen species (ROS) [43]. Amino acids play a major role in osmoregulation during salt stress [44]. In addition, they protect macromolecular subcellular structures and mitigate oxidative damage caused by free radicals produced in response to salt stress [43], and they also play important roles in plant stress tolerance. It has been reported that the oxidation of some amino acids, such as valine, leucine, isoleucine and lysine, directly feeds electrons into the mitochondrial electron transport chain. Therefore, these amino acids contribute to mitochondrial metabolism and ATP production [45]. It has been previously reported that amino acids such as proline, serine, threonine, glycine and phenylalanine are increased in Lotus to prevent high salinity [46]. Our results showed high levels of amino acids (L-threonine, leucine) in S. glauca leaves compared to S. salsa leaves, which suggests the role of these amino acids in maintaining the mitochondrial electron transport chain in S. glauca. This result suggests that amino acids function as osmolytes to relieve osmotic stress caused by saline–alkali conditions in S. glauca. The accumulation of organic acids has long been reported as a central adaptive mechanism in maintaining intracellular ionic balance, redox balance and pH homeostasis under salt–alkaline stress [47]. Organic acids are the main anions that are usually compartmentalized in vacuoles to neutralize cations [39]. Most organic acids, including malic acid, succinic acid and citric acid from the TCA cycle and niacin from nicotinate and nicotinamide metabolism, accumulate more in S. salsa leaves than in S. glauca leaves. Niacin contributes to over 500 reactions in the metabolism of carbohydrates, fatty acids and amino acids and can be synthesized from tryptophan [48]. Tryptophan is an important metabolite that can lead to the biosynthesis of serotonin and melatonin [49], both of which serve as lines of defense against abiotic and biotic stress in plants [50,51]. While niacin levels increased in both species, the accumulation was significant in S. glauca. A high niacin level could possibly impart enhanced salinity tolerance to S. glauca. Moreover, the TCA cycle is a crucial component of energy metabolism. Our results demonstrate that metabolites related to the TCA cycle, such as malic acid, citric acid and succinic acid, were substantially accumulated in S. salsa. Pathway analysis also indicated that the TCA cycle was significantly affected by salt stress. The contents of the three intermediates significantly accumulated in the TCA cycle, indicating enhanced metabolism in S. salsa. Comparatively higher levels of organic acids in S. salsa as a result of higher TCA cycle activity suggest an optimum flow of carbon from glycolysis and an optimal supply of reducing compounds and ATP [52]. The optimal energy supply for viable growth through higher TCA cycle activity suggests that upregulation of the TCA cycle and higher levels of reducing equivalents are adaptive strategies developed by S. salsa in response to a salt environment.
The accumulation of sugar is a common response of various plants to salt, but the changes in specific carbohydrates in plants under stress conditions are still divergent, which means that there is a phenomenon of differential metabolic rearrangement between species [10]. The accumulation of sugars under salt stress has been mostly associated with the maintenance of cellular osmolarity, energy metabolism and ROS scavenging [31,53]. In support of our results, salt-induced carbohydrate accumulation was also reported in halophytes, such as sucrose, d-xylose, fructose and glucose accumulation in T. halophila [33], Juncus acutus and Juncus maritimus [54] due to high salinity, whereas d-galactose decreased, suggesting a vital role of these metabolites in the regulation of stress-induced oxidative imbalance [8]. In contrast to sucrose, a higher accumulation of glucose suggests the downregulation of glycolysis and/or upregulation of gluconeogenesis, which provides metabolic flux for the production of downstream metabolites involved in salt tolerance [10]. Our results showed that sugars (sucrose, d-xylose, fructose and glucose) significantly accumulated in the leaves of S. salsa compared with those of S. glauca. This suggests that S. salsa utilizes various sugars as osmotic agents to alleviate osmotic stress caused by prolonged exposure to salt environments. In addition, sugars have been shown to be primary photosynthetic products, providing carbon and energy for ordinary cellular metabolism [55]. Galactaric acid is derived from galacturonic acid and produced by galacturonic acid oxidase. Galacturonic acid stimulates the oxidation of IAA by peroxidase and acts as a substrate for galacturonic acid reductase, leading to the synthesis of ascorbic acid [56]. Galactaric acid was found to decrease under salinity stress in Arabidopsis [33]. Consistent with our findings, the galacturonic acid content was reduced in S. salsa compared with S. glauca. This may be due to the stress response of S. salsa in the salt environment.
In summary, the high levels of organic acids and reducing sugars in S. salsa possibly suggest an enhancement in carbon flow from glycolysis to the TCA cycle. This not only leads to the increased production of ATP and reductants but also helps maintain ionic balance and pH homeostasis [47]. Furthermore, it can be inferred that S. salsa has a significant accumulation of sugars (sucrose, glucose, d-fructose, d-xylose and arabinose) and organic acids (citric acid, succinic acid and malic acid) compared with S. glauca. In contrast, metabolites that are high in S. glauca include nitrogen-metabolizing compounds such as amino acids (e.g., leucine and L-threonine). This indicates that the central metabolism shifted from nitrogen metabolism to organic acid metabolism during plant adaptation and sequentially from S. glauca to S. salsa.
Phenolic compounds are a class of compounds synthesized from phenylalanine, mainly through the shikimic acid pathway. As a natural antioxidant, these compounds play a crucial role in salt stress [57]. Studies have noted that under adverse conditions (e.g., high salt, drought, high light), plants preferentially accumulate flavonols to scavenge ROS free radicals and reduce damage [58]. Changes in cellular redox homeostasis have also been found to activate flavonoid biosynthesis, especially flavonol metabolism [59]. Severe stress conditions resulted in the inactivation of antioxidant enzymes, and an upregulation of flavonol biosynthesis was also found [60]. In the present study, it was found that metabolites involved in the synthetic pathways of flavonols, such as kaempferol, naringin and quercetin, were significantly accumulated in S. salsa leaves compared with S. glauca leaves, implying that S. salsa mainly responded to salinity by upregulating the synthetic pathways of flavonols. In addition, the preferential accumulation of flavonols in S. salsa in a saline–alkali environment may be related to the imbalance of cellular redox homeostasis and the inactivation of enzymatic activities. In contrast, S. glauca mainly enhanced the synthetic pathway of flavonoids, including isoliquiritigenin and genistein. L-phenylalanine can alleviate salt stress by enhancing the glycolytic pathway. As a precursor to the synthesis of phenolic compounds, L-phenylalanine is essential to maintaining normal phenolic metabolism [61]. Gallic acid is a polyphenol with strong antioxidant and antiradical effects. As the main component of cell-wall structural phenols, ferulic acid can regulate cell-wall ductility [62]. Previous studies have shown that the increase in cell-wall-bound ferulic acid and other phenolic substances is related to the hardening of the cell wall in S. chinensis leaves under salt stress [63]. Studies have demonstrated that increased cell-wall stiffness due to salt stress helps maintain swelling pressure and reduces water permeability through the plasma membrane, which is an adaptive mechanism for plants in saline–alkali soils [64]. In the present study, L-phenylalanine, gallic acid and ferulic acid significantly accumulated in S. salsa, and S. salsa relieved salt stress by ingesting phenylpropanoid compounds. Taken together, the accumulation of phenolic compounds is multifunctional, and S. glauca and S. salsa activate different pathways in response to the saline–alkali environment. In addition, Ca not only maintains ion balance but also participates in the construction of cell walls. The regulation of calcium in the production of secondary metabolites under salt stress [65] may imply that the two are synergistically involved in the adaptation to saline–alkali environments.

5. Conclusions

The contents of primary metabolites, secondary metabolites and mineral elements in the indicator plants S. glauca and S. salsa growing in the Hulunbuir saline–alkali grassland were comparatively studied by ionomic and metabolomic techniques. The ionomics results showed that the contents of TN, TOC, Ca, Na and Mn in the leaves of S. glauca and S. salsa were significantly different; specifically, these elements accumulated more in the leaves of S. salsa, while other elements were more abundant in the leaves of S. glauca. The high levels of accumulation in S. salsa leaves can be explained by their adaptive strategy to salt environments. The metabolomics results showed that sugars (sucrose, d-xylose, fructose and glucose) were significantly accumulated in S. salsa compared with S. glauca, suggesting that S. salsa utilizes various sugars as osmotic agents to relieve osmotic stress caused by prolonged exposure to salt environments. At the same time, malic acid, citric acid and succinic acid, which are related to the TCA cycle, were significantly accumulated in S. salsa. Taken together, the high levels of organic acids and reducing sugars in S. salsa may indicate enhanced carbon flow from glycolysis to the TCA cycle. High levels of amino acids (L-threonine and leucine) were found in leaves of S. glauca. This suggests that amino acids act as osmotic agents to alleviate osmotic stress in S. glauca caused by saline–alkali conditions. In addition, S. salsa can alleviate salt stress mainly by upregulating the flavonol synthesis pathway and by ingesting phenylpropanoid compounds. However, S. glauca mainly enhances the synthetic pathway of flavonoids to alleviate salt stress. The metabolic pathway analysis revealed that the central metabolism of S. glauca was nitrogen metabolism, while that of S. salsa was organic acid metabolism during the process of plant adaptation to salinity. Taken together, S. glauca and S. salsa adopt different adaptive strategies in response to saline–alkali environments.

Author Contributions

Z.T., Z.Z. and X.S. conceived and designed the analysis and wrote and reviewed the paper; X.S., N.Y. and Y.S. collected the data and performed the experiment; X.S. and N.Y. carried out the analysis of the data; and X.L., J.L. and Y.L. revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Fundamental Research Funds for the Central Universities (2572022AW24).

Data Availability Statement

The data used to support the findings of this study area are available from the corresponding author upon request via email.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. KEGG pathway enrichment analysis of altered metabolites in the leaves of S. glauca and S. salsa in response to salinity.
Table A1. KEGG pathway enrichment analysis of altered metabolites in the leaves of S. glauca and S. salsa in response to salinity.
Total CompoundsExpectedHitsRaw pLog (p)Holm AdjustFDRImpact
a Sulfur metabolism150.2629820.0269841.5689110.32044
Propanoate metabolism200.3506420.0462821.3346110
a Citrate cycle (TCA cycle)200.3506420.0462821.3346110.15581
Valine, leucine and isoleucine biosynthesis220.385720.055081.259110
Galactose metabolism270.4733620.0793571.1004110.04252
Glyoxylate and dicarboxylate metabolism290.5084320.0898651.0464110.00702
Aminoacyl-tRNA biosynthesis460.8064720.191660.71748110
a Nitrogen metabolism120.2103810.191880.71696110.05882
Nicotinate and nicotinamide metabolism130.2279210.206170.68578110.0202
Amino sugar and nucleotide sugar metabolism500.876620.217620.6623110
Pentose and glucuronate interconversions160.2805110.247580.60629110
Butanoate metabolism170.2980410.260910.58351110
a Ascorbate and ldarate metabolism180.3155810.274020.56222110.1791
Alanine, aspartate and glutamate metabolism220.385710.324250.48912110
a Starch and sucrose metabolism220.385710.324250.48912110.0889
Glutathione metabolism260.4558310.371130.43047110
Glycolysis/Gluconeogenesis260.4558310.371130.43047110.00038
a Glycine, serine and threonine metabolism330.5785610.445750.35091110.1204
a Arginine and proline metabolism340.5960910.455690.34133110.07496
Valine, leucine and isoleucine degradation370.6486910.484480.31472110
Glycerophospholipid metabolism370.6486910.484480.31472110.00947
Glucosinolate biosynthesis651.139610.691330.16032110
a The metabolic pathway having significant impact in salinity tolerance of S. glauca and S. salsa.

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Agronomy 12 02496 g001 550
Figure 1. The habitats of S. glauca and S. salsa. (a): S. glauca; (b): S. salsa; (c–e): The habitats of S. glauca and S. salsa.
Figure 1. The habitats of S. glauca and S. salsa. (a): S. glauca; (b): S. salsa; (c–e): The habitats of S. glauca and S. salsa.
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Agronomy 12 02496 g002 550
Figure 2. Multivariate analysis of metabolites between S. glauca and S. salsa leaves. (a): PLS-DA score plot for leaves; (b): PLS-DA loading plot for leaves. Sg: S. glauca; Ss: S. salsa.
Figure 2. Multivariate analysis of metabolites between S. glauca and S. salsa leaves. (a): PLS-DA score plot for leaves; (b): PLS-DA loading plot for leaves. Sg: S. glauca; Ss: S. salsa.
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Figure 3. VIP score plots of discriminatory metabolites (VIP > 1) in the leaves of S. glauca and S. salsa. Red and blue-colored boxes on the right indicate up- and downregulation of metabolites in each plant. Sg: S. glauca; Ss: S. salsa.
Figure 3. VIP score plots of discriminatory metabolites (VIP > 1) in the leaves of S. glauca and S. salsa. Red and blue-colored boxes on the right indicate up- and downregulation of metabolites in each plant. Sg: S. glauca; Ss: S. salsa.
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Figure 4. Enriched metabolic pathways containing the discriminatory metabolites in leaves between S. glauca and S. salsa. Red represents more significant changes in metabolites in the corresponding pathway, and yellow represents the opposite. Circle size indicates the pathway impact value.
Figure 4. Enriched metabolic pathways containing the discriminatory metabolites in leaves between S. glauca and S. salsa. Red represents more significant changes in metabolites in the corresponding pathway, and yellow represents the opposite. Circle size indicates the pathway impact value.
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Figure 5. Distribution of the accumulation of phenolic compounds in S. glauca and S. salsa. Metabolites are represented by circles, and related pathways are represented by diamonds. Correlation networks are composed of 15 phenolic compounds. Metabolites from the merged dataset were mapped to the KEGG and MBRole reference pathways, and interaction networks were generated in Cytoscape (p < 0.05). For metabolites, colored points represent the ratio of S. glauca to S. salsa, and the number of metabolites is represented by the size of the points.
Figure 5. Distribution of the accumulation of phenolic compounds in S. glauca and S. salsa. Metabolites are represented by circles, and related pathways are represented by diamonds. Correlation networks are composed of 15 phenolic compounds. Metabolites from the merged dataset were mapped to the KEGG and MBRole reference pathways, and interaction networks were generated in Cytoscape (p < 0.05). For metabolites, colored points represent the ratio of S. glauca to S. salsa, and the number of metabolites is represented by the size of the points.
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Figure 6. Visualization of primary metabolites and phenolic metabolite dynamics in S. glauca and S. salsa metabolic pathway maps. Primary metabolic pathways are shown in purple boxes, while phenolic biosynthetic pathways are shown in blue boxes. Significantly up- and downregulated metabolites are indicated by red and green boxes, respectively. Sg and Ss on the X-axis represent S. glauca and S. salsa in red and green, respectively. The relative abundance of metabolites on the Y-axis is shown as normalized values transformed by MetaboAnalyst software. After normalization, the levels of primary metabolites and phenolic metabolites were averaged across three biological replicates.
Figure 6. Visualization of primary metabolites and phenolic metabolite dynamics in S. glauca and S. salsa metabolic pathway maps. Primary metabolic pathways are shown in purple boxes, while phenolic biosynthetic pathways are shown in blue boxes. Significantly up- and downregulated metabolites are indicated by red and green boxes, respectively. Sg and Ss on the X-axis represent S. glauca and S. salsa in red and green, respectively. The relative abundance of metabolites on the Y-axis is shown as normalized values transformed by MetaboAnalyst software. After normalization, the levels of primary metabolites and phenolic metabolites were averaged across three biological replicates.
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Table
Table 1. The properties and ion contents in the soil surrounding S. glauca and S. salsa in natural habitats. Asterisks indicate significantly different means between communities according to the T test (p < 0.05).
Table 1. The properties and ion contents in the soil surrounding S. glauca and S. salsa in natural habitats. Asterisks indicate significantly different means between communities according to the T test (p < 0.05).
Specie Soil PropertiesIon Content (cmol·kg−1)
pHEC mS/cmK+Na+Ca2+Mg2+Cl−CO32−HCO3−SO42−
S. glaucaAV9.751.000.101.491.170.840.370.020.040.12
SE0.570.010.030.190.540.260.020.010.010.02
S. salsaAV9.761.300.132.342.031.350.780.030.09 *0.15
SE0.670.330.050.450.090.390.290.0200.01
Note: The asterisks represent significant differences between species according to the T test (p < 0.05). AV: Average; SE: standard error.
Table
Table 2. Distribution of the contents of 11 elements in S. glauca and S. salsa.
Table 2. Distribution of the contents of 11 elements in S. glauca and S. salsa.
Specie Essential Microelement (mg·g−1)Essential Microelement (mg·g−1)
TPTNTOCKCaMgNaFeCuZnMnNa/K
S. glaucaAV0.7313.07 *320.62 *10.802.11 *6.8190.28 *0.550.020.020.08 *4.47 *
SE0.11.295.571.360.151.056.50.100.0100.84
S. salsaAV1.0519.7938512.923.418.85119.210.390.020.010.108.37
SE0.210.695.291.280.350.365.930.080000.42
Note: The asterisks represent significant differences between species according to the T test (p < 0.05). AV: Average; SE: standard error; TP: total phosphorus; TN: total nitrogen; and TOC: total organic carbon. p values are in bold when p < 0.05.
Table
Table 3. Significantly different phenolic compounds between S. glauca and S. salsa.
Table 3. Significantly different phenolic compounds between S. glauca and S. salsa.
VIPChangep-Value
Isoliquiritigenin1.13271Sg > Ss**
Kaempferol1.1305Ss > Sg**
Ferulic acid1.1293Ss > Sg**
Gallic acid1.12871Sg > Ss**
Chlorogenic acid1.12648Sg > Ss**
protocatechuic acids1.11508Ss > Sg**
vanillic acid1.10797Sg > Ss**
p-Hydroxybenzoic acid1.10255Ss > Sg**
Luteolin1.10158Sg > Ss**
L-Phenylalanine1.09893Ss > Sg**
rutin1.0904Ss > Sg**
Genistein1.07673Sg > Ss**
Naringenin1.06547Ss > Sg**
VIP: variable importance in the projection; Sg: S. glauca; Ss: S. salsa; “**”: indicates a significant difference (p < 0.01).
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Song, X.; Yang, N.; Su, Y.; Lu, X.; Liu, J.; Liu, Y.; Zhang, Z.; Tang, Z. Suaeda glauca and Suaeda salsa Employ Different Adaptive Strategies to Cope with Saline–Alkali Environments. Agronomy 2022, 12, 2496. https://doi.org/10.3390/agronomy12102496

AMA Style

Song X, Yang N, Su Y, Lu X, Liu J, Liu Y, Zhang Z, Tang Z. Suaeda glauca and Suaeda salsa Employ Different Adaptive Strategies to Cope with Saline–Alkali Environments. Agronomy. 2022; 12(10):2496. https://doi.org/10.3390/agronomy12102496

Chicago/Turabian Style

Song, Xiaoqian, Nan Yang, Yuhang Su, Xueyan Lu, Jia Liu, Yang Liu, Zhonghua Zhang, and Zhonghua Tang. 2022. "Suaeda glauca and Suaeda salsa Employ Different Adaptive Strategies to Cope with Saline–Alkali Environments" Agronomy 12, no. 10: 2496. https://doi.org/10.3390/agronomy12102496

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