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Multi-omics analyses reveal the mechanisms underlying the responses of Casuarina equisetifolia ssp. incana to seawater atomization and encroachment stress

Abstract

Casuarina equisetifolia trees are used as windbreaks in subtropical and tropical coastal zones, while C. equisetifolia windbreak forests can be degraded by seawater atomization (SA) and seawater encroachment (SE). To investigate the mechanisms underlying the response of C. equisetifolia to SA and SE stress, the transcriptome and metabolome of C. equisetifolia seedlings treated with control, SA, and SE treatments were analyzed. We identified 737, 3232, 3138, and 3899 differentially expressed genes (SA and SE for 2 and 24 h), and 46, 66, 62, and 65 differentially accumulated metabolites (SA and SE for 12 and 24 h). The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that SA and SE stress significantly altered the expression of genes related to plant hormone signal transduction, plant–pathogen interaction, and starch and sucrose metabolism pathways. The accumulation of metabolites associated with the biosynthetic pathways of phenylpropanoid and amino acids, as well as starch and sucrose metabolism, and glycolysis/gluconeogenesis were significantly altered in C. equisetifolia subjected to SA and SE stress. In conclusion, C. equisetifolia responds to SA and SE stress by regulating plant hormone signal transduction, plant–pathogen interaction, biosynthesis of phenylpropanoid and amino acids, starch and sucrose metabolism, and glycolysis/gluconeogenesis pathways. Compared with SA stress, C. equisetifolia had a stronger perception and response to SE stress, which required more genes and metabolites to be regulated. This study enhances our understandings of how C. equisetifolia responds to two types of seawater stresses at transcriptional and metabolic levels. It also offers a theoretical framework for effective coastal vegetation management in tropical and subtropical regions.

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Introduction

Plants, as sessile organisms, are often subjected to environmental stress such as drought, cold, heat, and salinity [1]. Salinity stress diminishes soil fertility and precipitates soil degradation, adversely impacting plant growth by hindering water and nutrient uptake [2]. Notably, the worldwide terrestrial zone characterized by elevated salinity surpasses 900 million hectares and continues to expand as a result of climate change and anthropogenic influences [3, 4]. Unraveling the mechanisms underlying plant responses to saline stress can enhance the efficiency of utilizing highly saline soils [4].

The ability to withstand high salinity is crucial for flora in coastal ecosystems. The current study focuses on the impact of salt stress on Casuarina equisetifolia, a species indigenous to Australia and the Pacific Islands. C. equisetifolia is characterized by rapid growth and the capacity to endure extreme drought, intense light, and elevated salinity, making it vital for windbreaks and sand stabilization in the southeastern coastal regions of Asia and tropical zones of the Americas [5]. Despite its remarkable resilience to saline conditions, including resistance to seawater atomization (SA) and seawater encroachment (SE) caused by typhoons [6,7,8], the underlying molecular mechanisms about this tolerance remain unclear.

Omics provides a comprehensive approach to elucidating the molecular mechanisms underlying plant responses to saline stress at the genomic, proteomic, and metabolomic levels [9]. Salt stress influences the expression of particular genes, as well as the accumulation of proteins and metabolites within both primary and secondary metabolic pathways in plants [1, 10,11,12]. Under salt stress, plants regulate osmotic pressure through the accumulation of amino acids and the expression of related genes[2, 4]. Transcriptomic analysis of Chinese cabbage (Brassica rapa) under salt stress indicated that differentially expressed genes (DEGs) were predominantly associated with amino acid biosynthesis and carbon metabolism [4]. Additionally, comparative metabolomic profiling of Salvadora persica revealed that heightened salinity levels led to an increased accumulation of glutamate, glycine, and cysteine [2]. Besides amino acids, starch and soluble sugars play a significant role in enhancing plant salt tolerance [13]. Transcriptomic and proteomic analyses of Thellungiella halophila identified that the proteins and genes related to starch and sucrose metabolism are essential for sustaining salt tolerance [14]. Furthermore, studies have demonstrated that plants have developed mechanisms to synthesize secondary metabolites, such as phenylpropanoids and flavonoids, as a response to salt stress [1]. Within the phenylpropanoid biosynthesis pathway, numerous substrates are involved in the production of flavonoids, phenols, and lignin, which are crucial for plant adaptation to environmental stress [12, 15]. As scavengers of reactive oxygen species (ROS), phenols mitigate the impact of oxidative stress, while lignin helps preserve the structural integrity of the xylem during salt exposure [4, 12]. Moreover, comparative analyses of transcriptomes, proteomes, and metabolomes in Chinese cabbage and cotton subjected to salt stress showed that genes encoding enzymes in the phenylpropanoid biosynthesis pathway were upregulated, leading to enhanced accumulation of phenols, flavonoids, and lignin [4, 12, 16].

Plants modulate the expression of genes associated with salt stress through a multitude of signaling pathways, notably incorporating hormone signal transduction pathways, the ROS signaling pathway, and the mitogen-activated protein kinase (MAPK) cascade [17, 18]. Additionally, plant hormone signaling pathways play a pivotal role in enhancing salt tolerance, with the abscisic acid (ABA) signaling pathway serving as the central mechanism [19, 20]. Transcriptomic and proteomic analyses of Chinese cabbage and foxtail millet (Setaria italica) showed that the ABA signaling pathway transmitted the signal of salt stress downstream to regulate gene expression [4, 21]. Importantly, salt stress prompts plants to generate ROS, which function as an indirect signal that activates various signaling pathways, including the MAPK cascade [22]. The activated pathways mitigate ROS toxicity by regulating Na+ and K+ transport to improve salt tolerance [23].

Researchers have evaluated the alterations in transcription factors (TFs), genes, osmotic substances (such as proline), and ions (specifically Na+ and K+) that contribute to the salt stress tolerance of C. equisetifolia to salt stress, but previous studies have predominantly concentrated on physiological and transcriptional adaptations to NaCl treatment [5, 24,25,26,27,28]. Furthermore, the impacts of two types of salt stress (SA and SE) that contribute to the degradation of C. equisetifolia windbreak forests have not been examined. In this study, we performed simulations of SA by atomizing a NaCl solution and SE by flooding with a NaCl solution to elucidate the underlying mechanisms of C. equisetifolia responses to salt stress. We expected that the results would increase our understanding of the response mechanisms of C. equisetifolia to SA and SE stress, while also providing a theoretical foundation for efficient coastal vegetation management.

Materials and methods

Plant materials and salt treatments

The C. equisetifolia ssp. incana seedlings used in this study were germinated from seeds, and they were 20 cm tall when transplanted into pots. Each pot had an internal diameter and height of 17.5 cm, accommodating three seedlings per pot. The growth medium consisted of a substrate blend of sand and coconut coir (3:1, v/v). To eliminate potential effects of mycorrhizae or nodules, the substrate components were sterilized using gamma radiation. The pots containing the seedlings were randomly arranged within the greenhouse of the South China Botanical Garden, Chinese Academy of Sciences (Guangzhou, Guangdong Province, China). The arrangement of pots was systematically altered to guarantee that the seedlings experienced minimal interference from light and moisture. The experimental design incorporated three treatments, namely, a control treatment (CT), SA, and SE. Each pot in both the CT and SA groups received 50 mL of water daily. For the SA group, the seedlings were positioned within a nearly sealed chamber constructed of a metallic framework and transparent plastic film (Fig. S1a), equipped with a humidifier. The humidifier atomized a 33‰ NaCl solution, mimicking the salinity levels of the surface seawater in the South China Sea [29]. The seedlings within the SE group were fully submerged in the same NaCl solution (Fig. S1b). The young branchlets from the seedlings across the SA, SE, and CT groups were harvested at 0, 2, 12, and 24 h post-treatment for transcriptomic analysis (at 0, 2, and 24 h) and metabolomic studies (at 0, 12, and 24 h). For each treatment, ten seeding pots (thirty seedlings) with similar seedling growth status were selected to collect sample. The young branches from ten seedlings were harvested to serve as a biological replicate, with three such biological replicates conducted. All seedlings were treated and harvested at the same time of day to exclude the effects of rhythm on gene expression and metabolite synthesis. Upon collection, the plant samples were wrapped in aluminum foil, frozen in liquid nitrogen, and stored at − 80 °C for subsequent analysis.

RNA extraction, transcriptome sequencing, and analysis

The total RNA from each branchlet sample was extracted using Trizol reagent (Invitrogen, Waltham, USA). The determination of the integrity and the purification of RNA, library construction, and sequencing were conducted by Shanghai Majorbio Bio-pharm Biotechnology Co., Ltd. (Majorbio, Shanghai, China) using the Illumina NovaSeq 6000 sequencer (Illumina, California, USA). Subsequently, the clean reads were aligned to the C. equisetifolia genome [30] using HISAT2 [31]. The expression level of each gene was calculated according to transcripts per million fragments (FPKM) by RSEM [32]. Genes with | log2 (fold change) | ≥ 2.0 and P-adjusted < 0.05 by DESeq2 were considered to be DEGs [33]. Additionally, KEGG (Kyoto Encyclopedia of Genes and Genomes, www.genome.jp/kegg) enrichment analysis was used to determine the metabolic pathways in which DEGs were significantly enriched at the P-adjusted < 0.05 level using KOBAS (http://kobas.cbi.pku.edu.cn/home.do) [34]. The sequenced raw reads generated in this study have been submitted to NCBI with BioProject ID: PRJNA983994 (https://dataview.ncbi.nlm.nih.gov/object/PRJNA983994?reviewer=9l7862c0ce35e9ad0jrtt8t87b).

Widely targeted metabolomics analysis

The extraction and analysis of the metabolome were performed by Metware Biotechnology Co., Ltd. (Metware, Wuhan, China). After the lyophilized sample was ground in a MM 400 mixer (Retsch, Düsseldorf, Germany), 100 mg of powder was added to 0.6 ml of 70% methanol. The sample was then placed at 4 °C overnight and was centrifuged at 10,000 × g for 10 min before the supernatant was passed through a microporous filter membrane (0.22-µm pore size). The filtrate was analyzed using a UPLC-MS/MS system composed of UPLC (Shim-pack UFLC SHIMADZU CBM30A, Shimadzu, Japan) and MS / MS (4500 QTRAP, Applied Biosystems, USA). The working conditions of UPLC and MS were set as detailed prior [35]. The qualitative analysis of metabolites was performed utilizing the Metware database (MWDB) of Metware Biotechnology Co., Ltd. Metabolites were considered to be differentially accumulated metabolites (DAMs) when the variable importance in projection (VIP) was ≥ 1 and the absolute log2 (fold change) was ≥ 1.

Quantitative real-time polymerase chain reaction

The cDNAs from each group of samples (CT, SA_2h, SA_24h, SE_2h, and SE_24h) were used for quantitative real-time polymerase chain reaction (qRT-PCR). The cDNAs were synthesized from RNA according to the instructions of a GoScript™ Reverse Transcription System (Promega, USA). The qRT-PCR was carried out in a LightCycler® 480 II real-time PCR system (Roche, Switzerland) utilizing Unique Aptamer™ qPCR SYBR® Green Master Mix (Novogene, China). The PCR cycling parameters were 95 °C for 120 s, 40 cycles of 95 °C for 15 s, 60 °C for 60 s, 95 °C for 15 s, 60 °C for 60 s, 95 °C for 15 s, and 60 °C for 15 s [36]. The elongation factor 1-alpha (EF1α) and ubiquitin (UBI) were used as reference genes [25, 37]. The expression level of a target gene was calculated based on the 2−ΔΔCT method [38]. The expression levels of genes in all of the samples (CT, SA_2h, SA_24h, SE_2h, and SE_24h) were set to 1 in CT, and there were three biological and technical replicates. The primers for qRT-PCR were designed by Integrated DNA Technologies (http://www.idtdna.com/Primerquest/Home); these are listed in Table S1.

Results

Genes in response to SA and SE stress

To assess the transcriptional response of C. equisetifolia to SA and SE, we conducted Illumina high-throughput sequencing on branchlets subjected to CT, SA, or SE treatments. A total of 250,684,171 clean reads were obtained from the five groups of samples (CT, SA_2h, SA_24h, SE_2h, and SE_24h), with the Q30% ranging from 95.05 to 95.32%, and the GC content ranging from 47.54 to 47.92%. According to the reference database, the total mapping percentage was greater than 92.38%, and over 86.83% of the clean reads could be uniquely mapped in every group of samples (Table S2).

We found that a total of 11,006 DEGs were involved in the responses to SA and SE stress. Compared with the CT group, we identified 737 DEGs (492 up and 245 downregulated), 3232 DEGs (2077 up and 1155 downregulated), 3138 DEGs (1482 up and 1656 downregulated), and 3899 DEGs (1901 up and 1998 downregulated) in group comparisons SA_2h/CT, SA_24h/CT, SE_2h/CT, and SE_24h/CT, respectively (Fig. 1a). A Venn diagram demonstrated that 218 DEGs were shared across the four sample groups, indicating their involvement in the response to both SA and SE treatments (Fig. 1b). Hierarchical cluster analysis conducted on common DEGs identified six clusters (Fig. 1c) and elucidated four different expression patterns within these clusters. Following treatments with SA and SE, the expression levels of genes in clusters 3, 2, and 4 exhibited upregulation, whereas cluster 1 demonstrated a downregulation in gene expression. Notably, gene expression levels in cluster 5 were elevated under SA treatment but showed a downregulation under SE treatment, with the expression pattern in cluster 6 displaying an inverse trend compared to that of cluster 5 (Fig. S2).

Fig. 1
figure 1

DEGs in four contrasts. (a) Summary of the numbers of DEGs in four contrasts. (b) Venn diagram representation of the numbers of DEGs between two contrasts. (c) Cluster analysis of common DEGs in four contrasts. (d) KEGG pathway analysis of DEGs in the top three clusters. DEGs: Differentially expressed genes; KEGG: Kyoto Encyclopedia of Genes and Genomes

The KEGG pathway enrichment analysis was used to elucidate the biological functions of the common DEGs. The results indicated that the genes within clusters 1, 2, and 3 exhibited significant enrichment in pathways including phenylpropanoid biosynthesis pathway, thiamine metabolism, flavonoid biosynthesis, plant–pathogen interaction, amino sugar and nucleotide sugar metabolism, and the glycolysis/gluconeogenesis pathways (Fig. 1d). All DEGs from SA_2h/CT, SA_24h/CT, SE_2h/CT, and SE_24h/CT were subjected to KEGG pathway enrichment analysis. Notably, among the top five pathways with the highest DEG counts for both SA_2h/CT and SA_24h/CT, four were consistent, namely phenylpropanoid biosynthesis, plant–pathogen interaction, flavonoid biosynthesis, and the MAPK signaling pathway (Fig. S3). In SE_2h/CT and SE_24h/CT, the top five pathways with the most DEGs were shared, which included plant hormone signal transduction, phenylpropanoid biosynthesis, starch and sucrose metabolism, plant–pathogen interaction, and the MAPK signaling pathway (Fig. S4). Furthermore, an increase in the duration of SA or SE treatments correlated with a rise in the number of DEGs within the same pathways (Table S3).

To verify the accuracy of transcriptome data with SA and SE treatments, four DEGs from the phenylpropanoid biosynthesis and plant–pathogen interaction pathways were selected for qRT-PCR. The results showed that two DEGs were upregulated and two DEGs were downregulated, which were consistent with the transcriptome data (Fig. S5).

Metabolites in response to SA and SE stress

In the analysis of the metabolome, a total of 239 DAMs were identified across four groups of samples (SA_12h/CT, SA_24h/CT, SE_12h/CT, and SE_24h/CT). Among all of the DAMs, 46 (12 up and 34 downregulated DAMs) were from SA_12h/CT; 66 (15 up and 51 downregulated DAMs) were from SA_24h/CT; 62 (44 up and 18 downregulated DAMs) were from SE_12h/CT; and 65 (20 up and 45 downregulated DAMs) were from SE_24h/CT (Figs. S6 & S7). The KEGG pathway enrichment analysis indicated that there were significant alterations in two, three, three, and five pathways (P < 0.05) in SA_12h/CT, SA_24h/CT, SE_12h/CT, and SE_24h/CT, respectively. Furthermore, samples collected at the same time points for SA and SE treatments exhibited two overlapping pathways (Table S4). The primary pathways that demonstrated significant changes following SA and SE treatments included purine metabolism, photosynthesis, ABC transporters, arginine biosynthesis, fructose and mannose metabolism, C5-branched dibasic acid metabolism, glucosinolate biosynthesis, valine, leucine, and isoleucine degradation, as well as cyanoamino acid metabolism (Figs. S8 & S9).

DEGs and DAMs in response to SA and SE stress

The results of KEGG pathway enrichment analysis of DEGs showed that plant hormone signal transduction was important in the responses of C. equisetifolia to SA and SE stress. Within the auxin signaling pathway, two genes from the small auxin up RNA (SAUR) family were found to be downregulated, while one gene from the Gretchen Hagen 3 (GH3) family exhibited upregulation in SA_24h/CT, SE_2h/CT, and SE_24h/CT. Additionally, a gene encoding a member of the type-A Arabidopsis response regulator (A-ARR) family, integral to the cytokinin signaling pathway, was downregulated in the groups of SA_24h/CT, SE_2h/CT, and SE_24h/CT. In the ABA signaling pathway, one gene encoding protein phosphatase 2 C (PP2C), one gene encoding sucrose non-fermenting-1-related protein kinase 2 (SnRK2), and another gene encoding ABA-responsive element binding factor (ABF) were upregulated in SA_24h/CT, SE_2h/CT, and SE_24h/CT. Furthermore, there were three upregulated PP2C genes in samples with SE treatment. Conversely, genes encoding F-box protein coronatine insensitive 1 (COI1) and myelocytomatosis proteins 2 (MYC2) were downregulated in SE_2h/CT and SE_24h/CT. Notably, one gene encoding the jasmonate ZIM-domain (JAZ) protein showed upregulation across all samples (Fig. 2). Within the plant–pathogen interaction pathway, three genes encoding primary calcium (Ca2+) sensor calmodulin/calmodulin-like (CAM/CML) proteins and two genes encoding pathogenesis related protein 1 (PR1) were upregulated in SA_24h/CT, SE_2h/CT, and SE_24h/CT. Additionally, genes encoding Ca-dependent protein kinases (CDPKs) and TF WRKY33 were upregulated across all samples. Moreover, three genes in the CAM/CML family and two genes in the WRKY 22/29 family were upregulated in SA_24h/CT and SE_24h/CT (Fig. 3).

Fig. 2
figure 2

Genes involved in plant hormone signal transduction in C. equisetifolia after exposure to SA and SE stress for 2 and 24 h. The original figure of plant hormone signal transduction pathway was cited from the Kanehisa laboratories [95]. Blue asterisks indicated genes with significantly down-regulated expression and red asterisks indicated genes with significantly up-regulated expression. SA: Seawater atomization; SE: Seawater encroachment; AUX1: Auxin resistant 1; AUX/IAA: Auxin/indole-3-acetic acid; ARF: Auxin response factor; GH3: Gretchen Hagen 3; SAUR: Small auxin-up RNA; CRE1: Cytokinin response 1; AHP: Arabidopsis histidine phosphotransfer proteins; A-ARR: Type-A Arabidopsis response regulator; PYL: Pyrabactin resistance 1-like; PP2C: Protein phosphatase 2 C; Sucrose non-fermenting-1-related protein kinase 2; ABF: ABA-responsive element binding factor; COI1: Coronatine insensitive 1; JAZ: Jasmonate ZIM-domain; MYC2: Myelocytomatosis proteins 2

Fig. 3
figure 3

Genes involved in the plant–pathogen interaction pathway in C. equisetifolia after exposure to SA and SE stress for 2 and 24 h. The original figure of plant–pathogen interaction pathway was cited from the Kanehisa laboratories [96, 97]. Red asterisks indicated genes with significantly up-regulated expression. SA: Seawater atomization; SE: Seawater encroachment; CDPK: Calcium-dependent protein kinase; Rboh: Respiratory burst oxidase homolog; CAM/CML: Calmodulin/calmodulin-like proteins; NOS: Nitric oxide synthase; MPK4: Mitogen-activated protein kinase 4; MPK3: Mitogen-activated protein kinase 3; PR1: Pathogenesis related protein-1

In the integrated KEGG pathway enrichment analyses of DEGs and DAMs across all samples, key regulatory pathways significantly modified by SA and SE treatments included phenylpropanoid biosynthesis, starch and sucrose metabolism, glycolysis/gluconeogenesis, and amino acid biosynthesis. The phenylpropanoid biosynthesis pathway includes three genes encoding cinnamate 4-hydroxylase (CYP73A) and three genes encoding hydroxycinnamoyl transferase (HCT) that were upregulated by the SA treatment. The expression levels of two genes encoding cinnamyl alcohol dehydrogenase (CAD) were elevated, while the expression level of one gene encoding caffeic acid O-methyltransferase (COMT) was downregulated with the SE treatment. Additionally, two genes encoding phenylalanine ammonia lyase (PALs) were upregulated, and one gene encoding hydroxycinnamoyl transferase (HCT) was downregulated under both SA and SE treatments. Phenylalanine, caffeoyl aldehyde, and sinapyl alcohol concentrations increased in SE_24h/CT, whereas only caffeoyl aldehyde concentration rose in SA_12h/CT. Conversely, caffeoylquinic acid levels decreased in both SA_24h/CT and SE_24h/CT (Fig. 4). In starch and sucrose metabolism, two sucrose synthases (SUSs), two invertases (INVs), and two terpene synthases (TPSs) were found to be upregulated following SE treatment, alongside one downregulated SUS and one downregulated TPS. In SA_24h/CT, one SUS, one otsB, and one INV were upregulated, while the contents of trehalose-6P and D-glucose were decreased. In glycolysis/gluconeogenesis and biosynthesis of amino acids, 12 h of SA treatment decreased the contents of α-D-glucose-1, 6P2, glycerone-P, phosphoenolpyruvate, and 2-oxoglutarate. Additionally, the serine content increased, while the contents of aspartate, methyl aspartate, and ornithine were decreased in SA_24h. After 12 h of SE treatment, both 2-oxoglutarate and methyl aspartate levels decreased (Fig. 5).

Fig. 4
figure 4

Genes and DAMs involved in the phenylpropanoid biosynthesis pathway in C. equisetifolia after exposure to SA and SE stress for 2 and 24 h for genes, and for 12 and 24 h for metabolites (values are relative to exposure for 0 h). The original figure of phenylpropanoid biosynthesis pathway was cited from the Kanehisa laboratories [96, 97]. Blue asterisks indicated genes with significantly down-regulated expression and red asterisks indicated genes with significantly up-regulated expression. DAMs: Differentially accumulated metabolites; SA: Seawater atomization; SE: Seawater encroachment; PAL: Phenylalanine ammonia lyase; 4CL: 4-coumarate-CoA ligases; CYP73A: Cinnamate 4-hydroxylase; HCT: Hydroxycinnamoyl transferase; CCR: Cinnamoyl-CoA reductase; COMT: Caffeic acid O-methyltransferase; CAD: Cinnamyl alcohol dehydrogenase

Fig. 5
figure 5

Genes and DAMs involved in starch and sucrose metabolism, glycolysis/gluconeogenesis, and biosynthesis of amino acids in C. equisetifolia after exposure to SA and SE stress for 2 and 24 h for genes, and 12 and 24 h for metabolites (values are relative to exposure for 0 h). The original figure of starch and sucrose metabolism, glycolysis/gluconeogenesis, and biosynthesis of amino acids pathway was cited from the Kanehisa laboratories [96, 97]. Blue asterisks indicated genes with significantly down-regulated expression and red asterisks indicated genes with significantly up-regulated expression

DAMs: Differentially accumulated metabolites; SA: Seawater atomization; SE: Seawater encroachment; otsB: Trehalose-6-phosphate phosphatase; TPS: Terpene synthase; SUS: Sucrose synthase; INV: Invertase

Discussion

Effects of SA and SE stress on plant hormone signal transduction

Plant hormones are integral not only to growth and development but also in mediating responses to both biotic and abiotic stress [39, 40]. Phytohormones are crucial in stress responses, primarily operating through signal transduction mechanisms [39]. The KEGG enrichment analysis revealed that DEGs were enriched in plant signal transduction pathways following with SA and SE treatments, which were linked to auxin, cytokinin, ABA, and JA signaling pathways. Salt stress results in the accumulation of ABA in plants, which is detected by ABA receptors such as PYR/SnRK2, subsequently influencing the expression of genes involved in the ABA signaling pathway [41]. PP2Cs encode key enzymes in the ABA signaling pathway. Previous studies have shown that overexpression of AtPP2CG1 in Arabidopsis can improve its salt tolerance [42]. The expression of ZmPP2Cs was induced by salt stress in Zea mays [43], whereas CsPP2Cs exhibited both increase and decrease in expression levels in Camellia sinensis under similar conditions. [44]. SnRK2 proteins have the capacity to phosphorylate ABFs, which play a pivotal role in regulating stomatal closure. [41, 45]. ABA mitigates aqueous depletion by modulating stomatal occlusion, a crucial mechanism for plants experiencing salt stress [2, 46]. In this study, the expression levels of PP2Cs and SnRK2s were upregulated, suggesting that the ABA signaling pathway is crucial in mediating the response of C. equisetifolia to SA and SE stress.

JA is a crucial phytohormone that plays a vital role in the responses of plants to salt stress [47]. In the JA signaling pathway, COI1 engages with JAZ proteins and facilitates their ubiquitination, leading to degradation via the 26 S proteasome pathway. This process releases transcription factors such as MYC2, thereby enhancing the expression of stress responsive genes [47, 48]. JAZ proteins serve as crucial negative regulators within the JA signaling pathway [49]. The genes encoding JAZ in Ricinus communis [50], Arabidopsis [51], and Gossypium hirsutum [52] were found to be upregulated by salt stress. Moreover, overexpression of MdJAZ2 from apple in Arabidopsis improved its drought and salt tolerance [53]. The overexpression of JAZ9 in rice has been shown to enhance salt tolerance by modulating the expression of the K+ transporter [54]. In our study, the expression of JAZ was enhanced under both SA and SE stress, whereas MYC2 exhibited downregulation in SA_24h and SE samples. Additionally, we observed that COI1s were downregulated only in SE samples. These results indicate that JA signaling pathway was involved in the response of C. equisetifolia to SA and SE treatments.

Effects of SA and SE stress on the plant–pathogen interaction

In response to saline stress, plant cells exhibit an accumulation of ROS, which serve as signal transducers across multiple signaling pathways, notably those involved in plant–pathogen interactions [55, 56]. In this study, several DEGs were enriched in plant–pathogen interaction pathways in C. equisetifolia under SA and SE treatments. Rboh genes are responsible for the encoding of NADPH oxidase, a critical enzyme involved in ROS-mediated signaling pathways [57]. Environmental stress leads to changes in Ca2+ concentration in plants, which are recognized by specific sensors and then regulated by cascade reactions to regulate the expression of stress-related genes [58, 59]. Notably, CDPK, CAM, and CML proteins serve as crucial Ca2+ sensors capable of binding Ca2+ through EF-hand motifs [59, 60]. Previous studies have shown that salt stress can activate NADPH oxidase, forming a ROS-Ca2+ hub, which is an effective self-amplifying mechanism [61,62,63,64]. In this study, the expression of CDPK was increased under SA and SE treatments, and the Rboh gene was upregulated in SA_2h, SA_24h, and SE_24h samples. The ROS-Ca2+ hub possibly participated in the response of C. equisetifolia to SA and SE treatments. The WRKY TFs have been identified as playing vital roles in plant responses to abiotic stressors, particularly in relation to salt stress [65, 66]. The CdWRKY50 was found to be induced by salt stress in Cynodon dactylon [67]. Salt stress upregulated the expression of WRKY86 in maize, subsequently promoting the expression of Zm00001d020840 and Zm00001d046813 [68]. The Overexpression of BcWRKY33 from B. rapa in Arabidopsis improved the latter’s salt tolerance. Moreover, BcWRKY33 interacted with BcHSFA4A odulate gene expression cascades that respond to salt stress [69]. In our study, the expression of WRKY33 increased under SA and SE treatments, and WRKY22 and WRKY29 were upregulated in SA_24h and SE_24h samples. These results suggest that WRKY family genes in C. equisetifolia seedlings may activate downstream response transcriptional networks under SA and SE stress.

Effects of SA and SE stress on phenylpropanoid biosynthesis

The phenylpropanoid biosynthesis pathway is vital for plant survival and development. It produces essential precursors, including flavonoids, lignin, and tannin [1, 70]. Studies have shown that phenylpropanoid metabolism positively influences plant responses to salt stress [12, 71, 72]. The initial phase of the phenylpropanoid biosynthesis pathway involves two key enzymes: PAL and 4CL. PAL plays a crucial role in modulating the levels of secondary metabolites like flavonoids and lignin when facing environmental stress [1, 73]. Additionally, HCT serves as a vital enzyme, facilitating the transfer of the caffeoyl group back to CoA [1]. Within this metabolic pathway, the enzyme CCR catalyzes the reduction of synthetic caffeoyl aldehyde, while CAD is responsible for synthesizing sinapyl alcohol [74, 75]. In this study, two PALs and two HCTs showed increased expression following SA and SE treatments. CCR exhibited upregulation in SA_24h and all SE samples. Additionally, two CADs were upregulated across all SE samples. Previous studies indicate that plants accumulate phenolic compounds in response to salt stress. These phenols enhance the plants’ antioxidant capacity by effectively scavenging ROS [76, 77]. In our study, the accumulation of caffeoyl aldehyde and sinapyl alcohol increased in SA_12h and SE_24h samples. These results indicate that the phenylpropanoid biosynthesis pathway may play an important role in scavenging ROS in C. equisetifolia under SA and SE stress.

Effects of SA and SE stress on primary and secondary metabolism

Soluble sugars play a critical role in plants growth, development, and their responses to environmental stress by mediating sugar signaling pathways [78]. The overexpression of NINV in tobacco significantly reduced sucrose content while increased enhancing salt tolerance, suggesting that NINV genes can may facilitate plant adaptation to environmental stress through modulation of sugar metabolism [79]. Trehalose protects plant cells from salt, temperature, and drought stress by forming a glassy structure under dehydration conditions [80, 81]. The expression of TPSs can enhance the salt tolerance of plants by promoting trehalose biosynthesis [82]. Sucrose acts as a signaling molecule that modulates plant metabolism and triggers stress response mechanisms in plants [83]. SUS can facilitate the reversible transformation of sucrose and UDP into fructose and UDP-glucose [84]. In this study, upregulation of genes encoding INV, SUS, and TPS may contribute to the response of C. equisetifolia to SA and SE stress.

Respiration supplies the energy and carbon essential for plant growth and development [85]. Glycolysis plays a crucial role in this process by generating ATP under anaerobic conditions and offering precursors for the biosynthesis of proteins, sugars, and lipids [86]. In this study, the content of glycerone-P and phosphoenolpyruvate decreased in SA_12h sample, which may provide energy for the response of C. equisetifolia to SA stress. In addition to functioning as the fundamental building blocks of proteins, amino acids can also serve as osmotic regulators, enhancing plant resilience to osmotic stress [10]. The contents of valine, leucine, and isoleucine increased in the SE_24h sample, indicating that these amino acids may help maintain the osmotic pressure of C. equisetifolia under SE treatment. Taken together, these results indicated that starch and sucrose metabolism, glycolysis/gluconeogenesis, and amino acid biosynthesis were important in the response of C. equisetifolia to SA and SE treatments.

Differences in response of C. equisetifolia to SA and SE stress

The plant hormone signal transduction pathway is crucial in stress perception and response [87]. In this study, we found that the number of DEGs in the plant hormone signal transduction pathway under SA stress was lower than that under SE stress, and these DEGs were mainly concentrated in the later stage of SA treatment (24 h). Since SE treatment involves flooding and salinity stress, C. equisetifolia may perceive it more strongly. Previous studies have shown that plants respond to flooding by regulating the expression of genes in hormone signaling, phenylpropanoid, amino acid and primary sugars biosynthesis [88, 89]. The SA treatment was achieved by directly applying salt spray to the aboveground parts of C. equisetifolia. In the early stage of SA treatment (2 h), only a few genes showed significant changes in expression, which may be due to the alleviation of stress response by the morphological structure of branchlets [90]. Furthermore, the salinity stress induced by SA treatment is likely to be less intense than the combined effects of flooding and salinity stress from SE treatment, which accounts for the number of DEGs in SA_24h were less compared to those in SE_24h.

In the plant–pathogen interaction pathway, the CAM/CML family participates in the regulation of stomatal closure process [91]. In this study, six DEGs belonging to the CAM/CML family were identified in SA_24h, SE_2h, and SE_24h. Different from SA treatment, the expression of three DEGs was significantly upregulated in the entire stage of SE treatment (2 and 24 h). It was found that seawater flooding reduced the stomatal conductance of Phoenix dactylifera [92]. In this study, the extent of stomatal closure induced by SE treatment may exceed that of SA treatment. Previous studies have shown that salt stress alters PR1 expression by inducing ROS accumulation [93]. Compared with SA treatment, the expression of PR1s was significantly upregulated in the entire stage of SE treatment (2 and 24 h), which might be due to the additive effects of flooding and salinity.

The phenylpropanoid biosynthesis pathway is vital in plant response to salt stress [12, 71, 72]. We found that there were more DEGs in the phenylpropanoid biosynthesis pathway under SE treatment, which may indicate that C. equisetifolia was subjected to more severe oxidative stress. Moreover, we found that DAMs were mainly concentrated in the late stage of SE treatment (24 h), which indicated that C. equisetifolia may clear excess ROS by accumulating phenolic compounds.

The starch and sucrose metabolism can provide energy and carbon storage for plants under stress [94]. The DEGs in starch and sucrose metabolism were mainly concentrated in the late stage of SA treatment (24 h) and the entire stage of SE treatment (2 and 24 h). It may be that C. equisetifolia requires more energy to cope with SE stress. The accumulation of amino acids helps plants adapt to osmotic stress [2, 4]. We found that various amino acids (valine, leucine, isoleucine, and phenylalanine) accumulated in SE_24h, which may be a strategy for C. equisetifolia to cope with osmotic stress caused by SE treatment.

Conclusion

In this study, the transcript and metabolic profiles were analyzed to reveal the mechanisms underlying C. equisetifolia’s response to SA and SE stress. The KEGG enrichment analysis showed that SA and SE stress significantly changed the expression of genes involved in plant hormone signal transduction, plant–pathogen interaction, and starch and sucrose metabolism pathways. Our results also showed that SA and SE stress increased the accumulation of amino acids and phenolic compounds, such as serine, valine, and caffeoyl aldehyde, which could help C. equisetifolia cope with osmotic and oxidative stress. Compared with SA stress, C. equisetifolia had a stronger perception and response to SE stress, which required more genes and metabolites to be regulated. These results increase our understanding how C. equisetifolia responds to SA and SE stress at transcriptional and metabolic levels and offer a theoretical framework for effective coastal vegetation management.

Data availability

The sequenced raw reads generated in this study have been submitted to NCBI w-ith BioProject ID: PRJNA983994 (https://dataview.ncbi.nlm.nih.gov/object/PRJNA983994?reviewer=9l7862c0ce35e9ad0jrtt8t87b).

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Acknowledgements

We thank Kanehisa Laboratories for copyright permission of KEGG and Dr. Yuheng Zhou for technical assistance.

Funding

This study was supported the National Key R&D Program of China (2021YFC3100401, 2022YFC3103700), the High-level Talent Research Start-up Project Funding of Henan Academy of Sciences (Project NO. 241801041, Project NO. 231801034), the Science and Technology Research Project of Henan Province (242102320323), the Joint Fund of Henan Province Science and Technology R&D Program (Project NO. 225200810104), the Forestry Science and Technology Innovation Fund Project of Guangdong Province (2021KYXM09, 2022KYXM09, 2022KJCX005), Natural Science Foundation of Guangdong Province (2021A1515011670), and Guangdong Science and Technology Plan Project (Grant No. 2023B1212060046).

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Contributions

N. L., S. J., and S. Z. conceived and designed the project. S. Z., N. L., and S. J. analyzed the data and wrote the manuscript. N. L., S. J., L. W., G. W., W. Y., C. G., D. L., L. G., and J. Y. supervised and revised the manuscript. All authors read and approved the manuscript.

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Correspondence to Shuguang Jian or Nan Liu.

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The C. equisetifolia ssp. incana seedlings were collected from South China Botanical Garden and were identified by professor Shuguang Jian and Nan Liu. The methods involved in this study were carried out in compliance with local and national regulations.

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The authors declare no competing interests.

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Zhang, S., Wang, G., Yu, W. et al. Multi-omics analyses reveal the mechanisms underlying the responses of Casuarina equisetifolia ssp. incana to seawater atomization and encroachment stress. BMC Plant Biol 24, 854 (2024). https://doi.org/10.1186/s12870-024-05561-z

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