Skip to main content
Download PDF

Genome-wide identification of SWEET family genes and functional analysis of NtSWEET12i under drought and saline-alkali stresses in tobacco

BMC Plant Biology volume 25, Article number: 195 (2025) Cite this article

Abstract

Background

SWEET (Sugar Will Eventually be Exported Transporter) proteins play vital roles in the transport of sugars, contributing to the regulation of plant development, hormone signaling, and responses to abiotic stress.

Results

In this study, we identified 57 NtSWEETs in tobacco (Nicotiana tabacum L.), and then their physicochemical properties, chromosomal localization, synteny, phylogenetic relationships, genomic structure, promoter cis-elements, protein interaction network, tissue specificity, and expression pattern were systematically analyzed. In addition, NtSWEET12i improves drought and saline-alkali tolerance in tobacco by enhancing soluble sugars transport, ABA signaling, proline biosynthesis, and ROS scavenging. These findings illuminate the role of NtSWEETs, particularly NtSWEET12i, in regulating plant tolerance to drought and saline-alkali stresses.

Conclusions

This study offers new insights to enhance our understanding of the roles of NtSWEETs and identify potential genes involved in drought and saline-alkali tolerance of plants.

Clinical trial number

Not applicable.

Peer Review reports

Background

As global climate change, abiotic stress, particularly drought and saline-alkali stresses, exert a detrimental impact on crop productivity, thus threatening global food security [1, 2]. Identifying and characterizing stress–related genes in plants are crucial for improving drought and saline-alkali stresses tolerance [3]. With the application of plant biotechnology in plant breeding, the transcriptional regulatory mechanisms of plant resistance genes is gradually clear [4]. Nevertheless, the regulation network governing plants’ response to abiotic stress remain largely elusive and need further investigation [5].

Sugar is a crucial organic compound found in plants, constituting over 50% of the plants’ dry weight. It can be categorized into soluble and insoluble forms, with glucose, sucrose, and maltose falling under the former, and starch and cellulose among the latter [6]. Sugar functions not only as a carbon source, energy and structural substance, but also as signaling molecules that play vital roles in plant development [7, 8] and the adaptation of plants to environmental stress [9, 10]. Sugar not only acts as osmoregulator in itself, but also improves ABA and proline biosynthesis in plants, thereby enhancing plant tolerance to the abiotic stress [9, 11].

Plants regulate the transport, distribution, and supply of sugars via sugar transporters to adapt stress [12]. In the majority of plants, three categories of sugar transporters are commonly found: sucrose transporters (SUTs), monosaccharide transporters (MSTs), and sugars will eventually be exported transporters (SWEETs) [13]. SWEETs are identified as a newly discovered group of transporters present in plants with the ability to transport sugars, sugar alcohols, and hormones [14]. It is anticipated that the eukaryotic SWEET proteins possess two conserved MtN3/saliva domains, each comprising seven α-helical transmembrane domains (TMs). Based on evolutionary relationships, SWEETs are categorized into four groups (groups I, II, III, and IV) in plants [15]. SWEETs are vital in facilitating the transport of sugar between cells and exert a significant influence on various essential physiological processes, including plant development [14], nectar secretion [16], hormone regulation [17], abiotic stress response [18] and so on. SWEETs have been reported to be involved in plant abiotic stress, however, the transcriptional regulatory mechanisms underlying of SWEETs in drought and saline-alkali stresses remain largely unknown and need further study.

The identification of the SWEET family has been widely characterized in many plant species such as Triticum aestivum [19], Solanum tuberosum [20], Ipomoea batatas [21], Capsicum annuum [22], Allium sativum [23], Prunus mume [24], Punica granatum [25], Medicago polymorpha [26], and others. Moreover, little is known about this gene family in tobacco. Tobacco, as the most widely planted leafy crop and an important model plant in plant science, possesses a good foundation of molecular genetic technology and crop technology. Therefore, Nicotiana tabacum and Nicotiana benthamiana are widely used to study genes functional diversity and create new germplasm [27, 28]. Nevertheless, the potential biological function and molecular mechanism of NtSWEETs in tobacco remain largely unknown and need further study.

Results

Identification and characterization of NtSWEETs

To comprehensively and accurately identify all SWEET genes in tobacco, three common strategies were employed based on the published genes in Arabidopsis (AtSWEETs). Subsequently, a total of 57 NtSWEET genes were identified from the tobacco genome database and named as “NtSWEET” [27]. Furthermore, their physicochemical properties were analyzed (Table 1). The coding sequences (CDS) length of the 57 NtSWEETs exhibited a wide distribution, ranging from 351 bp (NtSWEET4b) to 948 bp (NtSWEET12n), encoding 117–316 amino acids, with the molecular weight (MW) varying from 12.78 to 35.26 kDa. Meanwhile, the isoelectric point (pI) of the 57 NtSWEETs ranged from 8.45 (NtSWEET4b) to 10.68 (NtSWEET11b), and the grand average of hydropathicity (GRAVY) ranged from 0 (NtSWEET12f) to 1.061 (NtSWEET17c), suggesting that they are hydrophobic proteins. The findings of subcellular localization predictions reveal that many NtSWEETs are localized in the cell membrane except seven NtSWEETs, including NtSWEET1a (localized in chloroplast and peroxisome), NtSWEET3b (localized in endoplasmic reticulum), NtSWEET9a (localized in endoplasmic reticulum), NtSWEET9b (localized in endoplasmic reticulum), NtSWEET12a (localized in cytoplasm), NtSWEET16b (localized in chloroplast), and NtSWEET16c (localized in chloroplast). The diversity of three-dimensional structure of NtSWEETs indicate the NtSWEETs may have functional redundancy and sub/neo-functionalization in tobacco (Fig. S1).

Table 1 Characterization of NtSWEETs in tobacco
Full size table

Chromosome location and synteny analysis of NtSWEETs

NtSWEETs exhibited a random distribution across 17 chromosomes, with each chromosome harboring between one and eleven genes. Notably, the number of genes are eleven in chromosome 5, and chromosomes 6 contained nine genes (Fig. 1A).

Fig. 1
figure 1

Chromosome location and synteny analysis of NtSWEETs. (A) Chromosomal location of NtSWEETs. The bars represent chromosome. The chromosome members are displayed on the left side, and the gene names are displayed on the right side. (B) Synteny analysis of NtSWEETs. Different chromosomes are shown in different colors. The approximate positions of NtSWEETs are marked with black lines on the chromosomes. Gray curves denote the syntenic relationships within Nicotiana tabacum

Full size image

Based on previous studies, there are two main ways, which are segmental and tandem duplication events, to expand the gene family. In order to understand the expansion mode of NtSWEETs in tobacco, the synteny analysis of NtSWEETs was performed. The genome duplication events within Nicotiana tabacum were investigated using TBtools-II software. As Fig. 1B showed, we identified a total of 33 collinear gene pairs in Nt-Nt. Furthermore, there were 7 tandem and 26 segmental duplication events. For instance, NtSWEET12e and NtSWEET12f (NtSWEET12g and NtSWEET12k) were likely originated from tandem duplication events, and NtSWEET2a and NtSWEET2c (NtSWEET10a and NtSWEET10e) were likely originated from segmental duplication events. Furthermore, the 33 gene pairs were analyzed by calculating the non-synonymous (Ka) and synonymous (Ks). These findings show that the substitution ratios (Ka/Ks) of all gene pairs is less than 1, demonstrating these genes are purified during evolution (Table S1).

Phylogenetic relationship of NtSWEETs

To further explore the evolutionary relationship of NtSWEETs in Nicotiana tabacum, Arabidopsis thaliana, Solanum lycopersicum, and Solanum tuberosum, we used the MEGA 11 software to generate a phylogenetic tree for 129 SWEETs from the four species (57 in Nicotiana tabacum, 17 in Arabidopsis thaliana, 24 in Solanum lycopersicum, and 31 in Solanum tuberosum) based on their protein sequences. Based on the evolutionary divergence, the phylogenetic tree was categorized into four distinct clades (Fig. 2). All SWEETs were grouped together with their respective orthologs, indicating the evolutionary relationships of the SWEET transporters have been relatively conserved across various species.

Fig. 2
figure 2

Phylogenetic analysis of the SWEET proteins in Nicotiana tabacum, Arabidopsis thaliana, Solanum lycopersicum, and Solanum tuberosum. SWEETs were divided into four clades (clades I, II, III, and IV) according to the evolutionary distance. The red squares, blue circles, green star and orange triangle represent the SWEETs in Nicotiana tabacum, Arabidopsis thaliana, Solanum lycopersicum, and Solanum tuberosum, respectively

Full size image

Motif and structural analyses of NtSWEETs

To investigate the genomic structure of NtSWEETs, we analyzed the conserved motifs, and then 20 conserved motifs were identified (Fig. S2). The results indicate that most members possess alike motifs compositions except NtSWEET1h, NtSWEET4b, and NtSWEET6 in groups I-IV (Fig. 3A). To analyze the conserved domains in the different NtSWEET groups, we identified the conserved domains of NtSWEETs using the Batch CD-Search tool. The results suggest that NtSWEETs are composed of two domains (Fig. 3B). Furthermore, the distributions of exon–intron in the genome were analyzed to gain deeper insights into the evolution of the NtSWEET family, Most NtSWEETs had six exons and five introns, however, a few NtSWEETs were different such as NtSWEET6 (containing three exons), NtSWEET5a (containing four exons), and NtSWEET7 (containing five exons). The number of exons among each member exhibited differences, indicating the function of NtSWEET family genes might have become more intricate during the process of evolution (Fig. 3C).

Fig. 3
figure 3

Conserved motifs and exon–intron structure analysis of NtSWEETs. (A) The phylogenetic tree shows that the NtSWEETs are distributed in four groups (I-IV), which indicated by pink, blue, green, and orange, respectively. Different colors boxes represent different motifs. (B) Conserved domain structures of NtSWEETs. Different domains are shown using boxes with different colors. (C) Exon–intron structures of NtSWEETs. The green and yellow boxes indicate UTR and CDS, respectively

Full size image

Cis-acting elements in NtSWEETs

The regulation of gene expression in response to hormonal signals and abiotic stress is frequently linked to the spatial distribution of relevant elements within the promoter regions of genes [4]. In order to explore the potential biological function of NtSWEETs, we conducted an analysis of the NtSWEET promoters. As the Fig. 4 showed, the cis-elements in NtSWEET promoter regions were systematically segmented into six distinct components: core/binding, abiotic/biotic, development, hormone, light, and other unknown elements, based on the predictions of PlantCARE website. All of the NtSWEET promoters contained CAAT-box and TATA-box. In addition, the abiotic/biotic elements MYB, MYC, and STRE existed in most of the NtSWEET promoters, meanwhile, a few of NtSWEET promoters contained other abiotic/biotic elements (ARE, as-1, MBS, and so on). The majority of NtSWEET promoter regions contained at least one developmental element; nevertheless, the development–related cis-acting elements were not found in 8 NtSWEETs (NtSWEET1h, 1j, 2d, 3a, 4a, 11b, 15, and 16a). The number of abscisic acid response element (ABRE) was the most among the hormone–related elements, suggesting most of the NtSWEETs might correlate with ABA response [29]. Furthermore, light-responsive elements have been identified in the promoters of NtSWEETs, including Box 4, G-box, AAGAA-motif, among others (Fig. 4). The above results reveal that NtSWEETs play key roles in plant development, hormone signaling, abiotic stress tolerance, and other essential processes in plants.

Fig. 4
figure 4

Cis-element analysis in the promoters of NtSWEETs. The degree of green colors represents the number of cis-elements in the promoter of NtSWEETs

Full size image

Protein interaction network of NtSWEETs

SWEET could form homodimers with itself or heterodimers with others to engage in a multitude of critical physiological processes within plants [30]. We constructed an interaction network for NtSWEETs using orthologous proteins in Arabidopsis to investigate their potential regulatory network. It is evident that NtSWEETs can interact with each other as well as with other proteins (Fig. 5). Moreover, NtSWEETs can interact with sugar–related proteins (STP15, MSSP2, SUC2, SUC3, and SUC4) [31,32,33], development–related proteins (SGR1 and SGR2) [34], stress response–associated proteins (bHLH13 and bHLH14) [35], grain quality–related proteins (MYB305 and NAC92) [36, 37], and so on (Fig. 5). These findings suggest that NtSWEETs are crucial in modulating sugar transport, development, and stress tolerance in plants.

Fig. 5
figure 5

Functional interaction networks of NtSWEETs according to orthologues in Arabidopsis. Network nodes represent proteins, and gray lines represent protein–protein associations. The node color/size represents the number of proteins that interact with each other

Full size image

Tissue-specific expression analysis of NtSWEETs

For the purpose of exploring the biological functions of NtSWEETs in tobacco plants, the expression of NtSWEETs were examined in nine representative tobacco tissues (i.e. root, stem, young, mature, and senescent leaves, young, mature, and senescent flowers, and dry caps) using RNA-seq data, which was extracted from the NCBI SRA repository. NtSWEETs were expressed in different tobacco tissues, respectively. Additionally, a few of NtSWEETs showed tissue-specific expression such as NtSWEET1c, 1f, 10b, 10c, 10d, 12e, 12f, 12k, 12i, and 12j (highly expressed in the leaf and flower tissues), NtSWEET2a, 4a, 5a, 5b, 10a, 12n, 15, 16b, and 16c (highly expressed in the flower and dry capsule tissues), NtSWEET9c and 11c (highly expressed in the leaf tissue) (Fig. 6). Above all, these findings demonstrate that NtSWEETs exhibit distinct expression patterns and are vital to plant development.

Fig. 6
figure 6

Expression analysis of NtSWEETs in different tissues using RNA-seq. The log2 (FPKM) values are showed in boxes

Full size image

Expression analysis under different treatments of NtSWEETs

The growth and development of plants are limited by abiotic stress, particularly drought and saline-alkali stresses [4]. To explore the roles of NtSWEETs in response to drought and saline-alkali stresses, we analyzed the expression levels of NtSWEETs using RNA-seq data of tobacco under 200 mM mannitol, 100 mM NaCl, and 100 mM NaHCO3 treatment. Under 200 mM mannitol treatment, the expression levels of many NtSWEETs were significantly upregulated or downregulated such as NtSWEET1d, 1e, 2c, 10b, 10c, 10d, 12e, 12i, 12j, 12k, and 12n (Fig. 7A). Consistent with that, the expression levels of NtSWEETs were also significantly induced under 100 mM NaCl or 100 mM NaHCO3 treatment, including NtSWEET1j, 2a, 11b, 11c, 12d, 12f, 12 g, 12i, 12k, 12 L, 12 m, 12n, and 15 (Fig. 7B). Abscisic acid (ABA) has a regulatory role in abiotic stress tolerance in plants [38]. To investigate the functions of NtSWEETs in ABA-mediated responses to abiotic stress, we conducted an analysis of NtSWEETs expression patterns through RNA-seq data from tobacco subjected to ABA treatment. Comparatively to the control (CK), the expression levels of several NtSWEETs, including NtSWEET9c, 10b, 10c, 10d, 11c, 12e, 12f, 12i, 12j, and 12k, were significantly induced following ABA treatment (Fig. 7C). The above findings demonstrate the pivotal role NtSWEETs play in stress adaptation of plants (Fig. 7).

Fig. 7
figure 7

Expression analysis of NtSWEETs under (A) mannitol, (B) NaCl, NaHCO3, and (C) ABA treatment using RNA-seq. The log2 (FPKM) values are showed in boxes

Full size image

NtSWEET12i is a key regulator of abiotic stress responses

It is remarkable that the expression levels of certain NtSWEETs, especially some members of NtSWEET12, were significantly induced under all treatment conditions, suggesting these NtSWEETs might be more important (Fig. 7). Among all members of NtSWEET12, NtSWEET12i were significantly upregulated under all treatment conditions. Therefore, we speculated that NtSWEET12i might be pivotal in enhancing abiotic stress tolerance in plants. The relative transcript levels of NtSWEET12i was quantified via qRT-PCR in tobacco under various stress conditions (Table S2). Under mannitol, NaCl, NaHCO3, and ABA treatments, the expression levels of NtSWEET12i were upregulated nearly 17.21-fold (at 1 h), 6.72-fold (at 6 h), 6.73-fold (at 6 h), and 5.38-fold (at 48 h), respectively, in tobacco (Fig. 8A).

Fig. 8
figure 8

Sequence analysis, expression analysis, and subcellular localization of NtSWEET12i. (A) Expression analysis of NtSWEET12i in tobacco upon exposure to mannitol, NaCl, NaHCO3, and ABA over a 48-h period. Data are shown as mean ± SD (n = 3). Different letters indicate statistically significant differences at P < 0.05 according to one-way ANOVA followed by post-hoc Tukey’s test for each treatment. The tobacco NtACTIN gene was used as a reference. (B) The genomic structure of NtSWEET12i. Boxes indicate exons, and lines indicate introns. (C) Subcellular localization of NtSWEET12i. N. benthamiana leaf epidermal cells were transformed with the fusion construct (NtSWEET12i-GFP) and the membrane marker PIP2-mCherry. Bars = 25 μm

Full size image

To further identify potential regulators of NtSWEET12i, we cloned NtSWEET12i. It encodes a protein of 292 amino acids with a predicted molecular weight of 32.57 kDa, encoded by an 876-base pair open reading frame (ORF) (Table 1). As shown in Figs. 3 and 8B, the genomic sequence of NtSWEET12i comprises six exons and five introns. Furthermore, NtSWEET12i exhibited high expression levels in young leaf (Fig. 6). We conducted an investigation into the subcellular localization of NtSWEET12i by transiently expressing the NtSWEET12i-GFP fusion protein in N. benthamiana epidermal cells. Analysis of the fluorescent signal reveals that NtSWEET12i is specifically localized to the cell membrane (Fig. 8C), and the outcome aligns precisely with the forecast on the website (Table 1).

The NtSWEET12i promoter regions in tobacco contain various cis-elements (Fig. 9A) such as abiotic stress–responsive elements (ABRE, MYC, STRE, and TC-rich repeats), MeJA response elements (CGTCA-motif and TGACG-motif), IAA response elements (AuxRR-core), GA response elements (TATC-box), and sugar response elements (G-box) [39,40,41]. To investigate whether NtSWEET12i is induced by MeJA, IAA, GA, glucose, fructose, and sucrose, we conducted RT-qPCR assays. The expression levels of NtSWEET12i were upregulated almost 9.83-fold (at 12 h), 5.62-fold (at 24 h), 11.22-fold (at 3 h), 5.43-fold (at 24 h), 9.24-fold (at 12 h), and 6.99-fold (at 6 h) in tobacco under MeJA, IAA, GA, glucose, fructose, and sucrose treatment, respectively (Fig. 9B, C). Collectively, these findings reveal that NtSWEET12i plays a crucial role in abiotic stress, hormone, and sugar responses in tobacco.

Fig. 9
figure 9

Promoter analysis and expression analysis of NtSWEET12i. (A) Diagrammatic representation of the NtSWEET12i promoter showing the positions of various cis-acting elements. (B, C) Expression analysis of NtSWEET12i in tobacco upon exposure to MeJA, IAA, GA, glucose, fructose, and sucrose over a 48-h period. Data are shown as mean ± SD (n = 3). Different letters indicate statistically significant differences at P < 0.05 according to one-way ANOVA followed by post-hoc Tukey’s test for each treatment. The tobacco NtACTIN gene was used as a reference

Full size image

NtSWEET12i enhances drought and saline-alkali tolerance of tobacco

To explore whether NtSWEET12i affects the drought and saline-alkali response in tobacco, we generated overexpression (named as OE-1 and OE-2) and VIGS (named as VIGS-1 and VIGS-2) lines via Agrobacterium-mediated transformation for drought and saline-alkali tolerance assays (Fig. S3) [42]. Under control condition, there were no obvious morphological differences in transgenic and WT plants. After treatment with 200 mM mannitol (for 24 h), 200 mM NaCl (for 48 h), and 100 mM NaHCO3 (for 48 h), the NtSWEET12i-OE plants exhibited better growth, whereas the NtSWEET12i-VIGS lines became wilt earlier than WT plants (Fig. 10A; S4). According to the results, overexpression of NtSWEET12i improves tobacco’s drought resistance and saline-alkali tolerance.

Fig. 10
figure 10

Overexpression of NtSWEET12i enhance drought and saline-alkali tolerance in tobacco by activating soluble sugars transport, ABA signaling pathway, proline biosynthesis, and ROS scavenging. (A) Responses of NtSWEET12i transgenic and WT tobacco plants under control condition or mannitol, NaCl, and NaHCO3 stresses. Bars = 5 cm. (B) soluble sugars content, (C) ABA content, (D) proline content, (E) POD activity, (F) SOD activity, (G) H2O2 content, and (H) MDA content in leaves of NtSWEET12i transgenic and WT plants under control condition or mannitol, NaCl, and NaHCO3 stresses. Data are shown as mean ± SD (n = 3). **, P < 0.01; Student’s t-test

Full size image

The SWEET proteins can improve the adaptability of plants to abiotic stress by regulating the transport of soluble sugars [43]. To explore the soluble sugars of transgenic and WT plants, we measured total soluble sugars content. Under drought and saline-alkali stresses conditions, the contents of soluble sugars were significantly elevated in NtSWEET12i-OE plants but reduced in NtSWEET12i-VIGS plants compared to WT plants (Fig. 10B). ABA serves a pivotal function as a hormone in facilitating plant adaptation to abiotic stress [4]. Therefore, we quantified endogenous ABA levels in the WT and transgenic plants. Under drought and saline-alkali stresses, the ABA contents were significantly higher in NtSWEET12i-OE but lower in NtSWEET12i-VIGS versus WT plants (Fig. 10C). The above findings indicate that NtSWEET12i can enhance the soluble sugars and ABA contents in tobacco.

When plants are subjected to abiotic stress, plants produce excess ROS, which further leads to plant injury [44]. Proline functions as an osmotic regulator and a scavenger of ROS during abiotic stress [45]. A significantly higher level of POD and SOD activities, as well as proline contents, were observed in NtSWEET12i-OE, but lower in NtSWEET12i-VIGS than WT plants (Fig. 10D-F); moreover, the levels of H2O2 and MDA accumulation were found to be lower in NtSWEET12i-OE, by contrast, higher in NtSWEET12i-VIGS (Fig. 10G, H). These results reveal that overexpression of NtSWEET12i can activate the ROS scavenging system of tobacco.

Underlying mechanism through which NtSWEET12i confers drought and saline-alkali tolerance

To clarify the fundamental mechanisms by which NtSWEET12i contributes to drought and saline-alkali tolerance, we performed qRT-PCR analysis of genes associated with the ABA signaling pathway, proline biosynthesis, and the ROS scavenging system. Under drought and saline-alkali conditions, key genes related to ABA biosynthesis (NtNCED3), ABA signaling (NtRD26, and NtRD29), proline biosynthesis (NtP5CS), and ROS scavenging (NtSOD and NtAPX3) were significantly upregulated in NtSWEET12i-OE plants but significantly downregulated in NtSWEET12i-VIGS plants compared to the WT (Fig. 11A). NtABI1 functions as a negative regulator of stress resistance [46], consequently, the expression levels of NtABI1 exhibited opposite pattern in the NtSWEET2i transgenic lines (Fig. 11A).

Fig. 11
figure 11

Expression analysis and proposed working model of NtSWEET12i. (A) Expression analysis of relevant genes in the leaves of NtSWEET12i transgenic and WT plants under control condition or mannitol, NaCl, and NaHCO3 stresses. (B) Proposed working model of NtSWEET12i in the drought and saline-alkali response of tobacco. NtSWEET12i enhances drought and saline-alkali tolerance in tobacco by directly increase soluble sugars transport and indirectly regulating the expression of ABA signaling pathway related-genes (NtNCED3, NtABI1, NtRD26, and NtRD29), proline biosynthesis–related gene (NtP5CS), as well as ROS scavenging–related genes (NtSOD and NtAPX3)

Full size image

In conclusion, this study elucidates the mechanism by which NtSWEET12i responds to drought and saline-alkali stresses in tobacco. The overexpression of NtSWEET12i in tobacco plants enhances their tolerance to drought and saline-alkali stresses by directly increasing the transport of soluble sugars and indirectly regulating the expression of genes associated with the ABA signaling pathway (NtNCED3, NtABI1, NtRD26, and NtRD29), proline biosynthesis (NtP5CS), as well as ROS scavenging (NtSOD and NtAPX3) (Fig. 11).

Discussion

The SWEET family plays vital roles in in various physiological processes of plant development. Furthermore, the presence of the SWEET family has been documented in different plant species such as Triticum aestivum [19], Solanum tuberosum [20], Ipomoea batatas [21], Capsicum annuum [22], Allium sativum [23], and so on. Nevertheless, Many NtSWEETs remain largely unknown in terms of their biological functions and underlying regulatory mechanisms. Hence it is essential to perform a comprehensive genome-wide identification and analysis of the SWEET family genes in order to enhance our comprehension of their functions and the molecular mechanism of tobacco.

The Nicotiana tabacum genome published by Huazhong Agricultural University in 2024 represents the highest quality among all publicly available Nicotiana tabacum genome [27]. Based on the Nicotiana tabacum genome, a total of 57 NtSWEETs were identified in this study (Table 1). Due to the large size of the tobacco genome, which is as large as 4.3 Gb, the number of NtSWEETs exceeds that of most plants such as potato (33), sweet potato (27), and pepper (33). Based on the chromosomal localization of NtSWEETs, genes were evenly distributed across all chromosomes (Fig. 1A). We speculated that segmental and tandem duplications were the primary drivers behind the increased copy number of NtSWEETs, potentially leading to functional redundancy and differentiation (Fig. 1B). Based on the phylogenetic relationship of NtSWEETs, there are similar numbers and types of NtSWEETs distributed in each group in Nicotiana tabacum, Arabidopsis thaliana, Solanum lycopersicum, and Solanum tuberosum, indicating evolutionary conservation within the plant SWEET family (Fig. 2).

The genomic structure is typically conserved throughout the course of plant evolution [47]. In our investigation, as shown in Fig. 3A, NtSWEETs exhibit conserved motifs (Fig. S2). Additionally, the domains of NtSWEETs also demonstrate relative conservation (Fig. 3B). The majority of homologous NtSWEETs possess six exons and five introns, however, a few display variations in exon-intron structure. For instance, the exon–intron structures of NtSWEET6 (containing three exons), NtSWEET5a (containing four exons), and NtSWEET7 (containing five exons) differ from that of other NtSWEETs (Fig. 3C). Consequently, alterations in the exon-intron structures of NtSWEETs may contribute to increased functional diversification.

SWEETs, acting as a sugar transporter, have the ability to enhance sugar transportation [14]. Sugar can enhance ABA signaling and ROS scavenging, thereby improving the plants’ abiotic stress tolerance [9]. In this study, there are numerous cis-acting elements associated with abiotic stress in the NtSWEETs promoter regions, indicating the involvement of NtSWEETs in responses to abiotic stress (Fig. 4). The sugar transport and abiotic stress related proteins (STP15, MSSP2, SUC2, SUC3, SUC4, IbbHLH13, and IbbHLH14) are capable of interacting with NtSWEETs, thereby providing further validation for the significance of NtSWEETs in the response to abiotic stress (Fig. 5). The RNA-seq data exhibited significant upregulation or downregulation in the expression of numerous NtSWEETs, including NtSWEET1d, 1e, 2c, 10b, 10c, 10d, 12e, 12i, 12j, 12k, and 12n under 200 mM mannitol treatment (Fig. 7A), NtSWEET1j, 2a, 11b, 11c, 12d, 12f, 12 g, 12i, 12k, 12 L, 12 m, 12n, and 15 under 100 mM NaCl or NaHCO3 treatment (Fig. 7B), and NtSWEET9c, 10b, 10c, 10d, 11c, 12e, 12f, 12i, 12j, and 12k under ABA treatment (Fig. 7C). It is important to highlight that the expression levels of certain members of NtSWEET12 from different groups were notably induced across all treatments: specifically, NtSWEET12i. These findings suggest that particular attention should be paid to the mechanisms underlying of these genes in response to drought and saline-alkaline stresses in plants (Fig.7).

In the current study, the NtSWEET12i promoter regions contain abiotic stress–responsive, hormone–responsive, and sugar–responsive cis-elements promoter (Fig. 9A); furthermore, RT-qPCR analysis indicate that NtSWEET12i can be significantly induced by mannitol, NaCl, NaHCO3, ABA, MeJA, IAA, GA, sucrose, glucose, and fructose (Figs. 8A and 9B and C). According to the site’s subcellular localization predictions, many SWEET proteins are predicted to be localized in cell membranes (Table 1); consistent with this, NtSWEET12i is specifically localized in the cellular membranes (Fig. 8C). Abiotic stress tolerance assays revealed that overexpressing NtSWEET12i enhanced drought and saline-alkali tolerance, whereas virus-induced NtSWEET12i silencing reduced drought and saline-alkali tolerance in tobacco (Fig. 10A; S4). Under drought and saline-alkali conditions, soluble sugars, ABA, proline, H2O2, and malondialdehyde (MDA) contents, peroxidase (POD) and superoxide dismutase (SOD) activities in the leaves of the transgenic and WT plants exhibited significantly different (Fig. 10B-H). In addition, key genes correlated with ABA biosynthesis (NtNCED3), ABA signaling (NtABI1, NtRD26, and NtRD29), proline biosynthesis (NtP5CS), and ROS scavenging (NtSOD and NtAPX3) were significantly induced in transgenic plants (Fig. 11A). Consequently, NtSWEET12i enhances drought and saline-alkali tolerance in tobacco through soluble sugars transport, ABA signaling, proline biosynthesis, and ROS scavenging (Fig. 11).

In summary, we provide genome-wide results of the tobacco SWEET genes and the expression pattern analyses under drought, saline-alkali, and ABA treatments. In addition, we perform functional analysis of NtSWEET12i and demonstrate NtSWEET12i can improve drought and saline-alkali tolerance of tobacco. The information described here could contribute to further studies investigating NtSWEET family genes (especially NtSWEET12i) in the context of abiotic stress.

Conclusions

In this study, NtSWEETs were identified from tobacco (Nicotiana tabacum L.), and then we systematically analyzed their basic information. Their expression pattern analyses under drought, saline-alkali, and ABA treatments were performed using RNA-seq. We conducted a screening for potential NtSWEETs that may exert a regulatory function in enhancing abiotic stress tolerance. Subsequently, we generated NtSWEET12i transgenic tobacco plants to investigate its function, and found that NtSWEET12i could enhance drought and saline-alkali tolerance. The purpose of this study was to offer novel insights for advancing our comprehension of the functions of NtSWEETs and identifying potential genes linked to environmental stress tolerance in plants.

Materials and methods

Plant materials

The tobacco (Nicotiana tabacum) cultivar ‘Honghuadajinyuan’ was employed for cloning NtSWEET12i, and the tobacco (Nicotiana benthamiana) was used to characterize its functions. The tobacco plants were grown in a substrate consisting of a 1:1 mixture of peat soil and vermiculite, and were cultivated in a greenhouse at the Tobacco Research Institute of the Chinese Academy of Agricultural Sciences, Qingdao, China. The greenhouse conditions included a light intensity of 400 µmol m− 2·s− 1, a temperature regime of 25 °C during the light period and 23 °C during the dark period, a photoperiod of 16 h of light and 8 h of darkness, and a relative humidity of 65%. After 4 weeks of growth, healthy tobacco seedlings of the same size were selected for further study.

Identification of NtSWEETs

All tobacco SWEET protein sequences were extracted from the tobacco genome downloaded from http://lifenglab.hzau.edu.cn/Nicomics/ [27]. We used the different screening strategies to correctly identify all members of the SWEET family. Firstly, we obtained all sequences of AtSWEET through the Arabidopsis genome database (https://www.arabidopsis.org/), that were used as decoys to retrieve the tobacco genome database at the genome-wide level using BLASTP. Subsequently, we surveyed all tobacco SWEET proteins via the HMM profiles (Hidden Markov Model) of the specific MtN3/saliva conserved domains, which were sourced from the Pfam database (http://pfam.xfam.org/) [48]. Finally, all candidate genes were checked by using SMART (http://smart.embl-heidelberg.de/) and Conserved Domains Database (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) [49].

Property prediction of NtSWEETs

The information about each NtSWEETs, including the molecular weight (MW), isoelectric point (pI), and the average value of hydrophilicity (GRAVY), was calculated by ProtProm tool on the Expasy server (https://www.expasy.org/) [50]. The Plant-mPLoc website was employed to predict the subcellular localization (http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/) [51]. The three-dimensional structure of NtSWEETs was predicted and visualized using the AlphaFold 3 model (https://alphafoldserver.com/) and PyMOL software [52].

Chromosomal location and identification of homologous genes

Based on the information of chromosomal locations provided by the tobacco genome database (http://lifenglab.hzau.edu.cn/Nicomics/), TBtools-II software was employed to generate the chromosomal locations map and synteny analysis of the NtSWEETs [53]. The non-synonymous (Ka) and synonymous (Ks) were computed using TBtools-II software (Table S1).

Phylogenetic analysis of SWEETs

The SWEET protein sequences of different species [54], including Nicotiana tabacum, Arabidopsis thaliana, Solanum tuberosum, and Solanum lycopersicum, were imported into the MEGA 11 software for the construction of a phylogenetic tree using the neighbor-joining method with 1000 bootstrap replicates [55]. The phylogenetic tree was further optimized through the iTOL online tool (https://itol.embl.de/) and Adobe Illustrator software [56].

Conserved motifs and domain identification analysis of NtSWEETs

The conserved motifs of NtSWEETs were analyzed using the MEME online tool (https://meme-suite.org/meme/tools/meme) [57]. The number of motifs were set to search for 20 motifs. In addition, the conserved domains of NtSWEETs were identified using the Batch CD-Search tool (https://www.ncbi.nlm.nih.gov/Structure/bwrpsb/bwrpsb.cgi) [58]. TBtools-II and Adobe Illustrator software were used for the visual tools.

Motif and structural analyses of NtSWEETs

The exon–intron structure was performed using TBtools-II software and the GSDS2.0 online website (https://gsds.gao-lab.org/) based on the genomic and coding sequences of NtSWEETs [59]. The cis-elements in the 2000 bp (or 3000 bp) promoter regions of NtSWEETs (NtSWEET12i) extracted from the tobacco genome were analyzed on the PlantCARE website (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) and TBtools-II software [60].

Protein interaction network of NtSWEETs

The protein interaction network of the NtSWEETs was analyzed on STRING website (https://cn.string-db.org/) based on Arabidopsis AtSWEETs proteins [61]. The network map was constructed utilizing Cytoscape 3.10.0 software.

Transcriptome analysis

The RNA-seq data of NtSWEETs in different tissue of tobacco were obtained from the NCBI SRA repository (PRJNA208209). In addition, the RNA-seq data of NtSWEETs in tobacco under 200 mM mannitol (PRJNA883680), 100 mM NaCl (PRJNA532660), 100 mM NaHCO3 (PRJNA532660), and 0.1 mM ABA spraying (PRJNA684346) treatment were downloaded from the NCBI SRA repository [62,63,64].

Expression analysis

After four leaves have formed, the leaves of Honghuadajinyuan plants were sampled at 0, 0.5, 1, 3, 6, 12, 24, and 48 h after treatment with 200 mM mannitol, 100 mM NaCl, 100 mM NaHCO3, 2% sucrose, 2% glucose, 2% fructose, 0.1 mM ABA spraying, 0.1 mM MeJA spraying, 0.1 mM GA spraying, and 0.1 mM IAA spraying in half-strength Hoagland solution. Expression pattern were quantified by quantitative reverse-transcription (qRT)-PCR. The tobacco NtACTIN gene served as an internal control (Table S2).

Subcellular localization

The complete coding regions of NtSWEET12i, excluding the stop codon, were inserted into pCAMBIA1300. These constructs, along with the membrane marker PIP2A-mCherry, were introduced into N. benthamiana leaf epidermal cells via Agrobacterium-mediated infiltration (WEIDIbio, CAT#:AC1003). Subsequently, the fluorescent signals were visualized using a confocal laser-scanning microscope (TCS SP8; Leica).

Transgenic plants generation

pTRV2-NtSWEET12i and pCAMBIA1300-NtSWEET12i-GFP were transferred into Agrobacterium strain EHA105 for tobacco rattle virus (TRV)-based virus-induced gene silencing (VIGS) and transiently overexpressing in Nicotiana benthamiana. The transgenic plants were generated via Agrobacterium-mediated transformation, with the specific injection parameters referenced from previous studies [42, 65]. Agrobacterium containing pTRV2-NtSWEET12i and Agrobacterium containing pCAMBIA1300-NtSWEET12i-GFP were injected into 50 tobacco plants, respectively. After PCR analysis of the tobacco plants, we selected 24 overexpression (designated as OE-1 and OE-2) and 24 VIGS (designated as VIGS-1 and VIGS-2) lines for further study.

Drought and saline-alkali tolerance assays

The CK (pure wild type), NtSWEET12i-VIGS, and NtSWEET12i-OE plants were grown in pots and irrigated with Hoagland solution with or without 200 mM mannitol (for 24 h), 200 mM NaCl (for 48 h), and 100 mM NaHCO3 (for 48 h) every four hours. Three independent biological replicates were taken.

Measurement of abiotic stress tolerance indices

The ABA (ADS-0003PL2), soluble sugars (ADS-W-TDX039), proline (ADS-W-AJS004), H2O2 (ADS-W-YH001), and malondialdehyde (MDA) (ADS005TO1) contents, peroxidase (POD) (ADS049TE0) and superoxide dismutase (SOD) (ADS-F-KY001) activities in the leaves of the WT and transgenic plants were measured using assay kits (Jiangsu Aidisheng Biological Technology Co., Ltd).

Statistical analysis

The Student’s t-test was used to determine the significance of differences between two samples, and the significance of multiple groups was analyzed using SPSS Statistics 27 in this study.

Data availability

The data that support the findings of this study are available within the article and supporting information.

References

  1. Rivero RM, Mittler R, Blumwald E, Zandalinas SI. Developing climate-resilient crops: improving plant tolerance to stress combination. Plant J. 2022;109:373–89.

    Article  PubMed  CAS  Google Scholar 

  2. Zhu JK. Abiotic stress signaling and responses in plants. Cell. 2016;167:313–24.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Esmaeili N, Shen G, Zhang H. Genetic manipulation for abiotic stress resistance traits in crops. Front Plant Sci. 2022;13:1011985.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Zhang H, Zhu J, Gong Z, Zhu JK. Abiotic stress responses in plants. Nat Rev Genet. 2022;23:104–19.

    Article  PubMed  Google Scholar 

  5. Dixit S, Sivalingam PN, Baskaran RKM, Senthil-Kumar M, Ghosh PK. Plant responses to concurrent abiotic and biotic stress: unravelling physiological and morphological mechanisms. Plant Physiol Rep. 2024;29:6–17.

    Article  CAS  Google Scholar 

  6. Saddhe AA, Manuka R, Penna S. Plant sugars: homeostasis and transport under abiotic stress in plants. Physiol Plant. 2021;171:739–55.

    Article  PubMed  CAS  Google Scholar 

  7. Mishra BS, Sharma M, Laxmi A. Role of sugar and auxin crosstalk in plant growth and development. Physiol Plant. 2022;174:e13546.

    Article  PubMed  CAS  Google Scholar 

  8. Marquardt A, Henry RJ, Botha FC. Effect of sugar feedback regulation on major genes and proteins of photosynthesis in sugarcane leaves. Plant Physiol Biochem. 2021;158:321–33.

    Article  PubMed  CAS  Google Scholar 

  9. Kaur H, Manna M, Thakur T, Gautam V, Salvi P. Imperative role of sugar signaling and transport during drought stress responses in plants. Physiol Plant. 2021;171:833–48.

    Article  PubMed  CAS  Google Scholar 

  10. Salvi P, Agarrwal R, Kajal, Gandass N, Manna M, Kaur H, Deshmukh R. Sugar transporters and their molecular tradeoffs during abiotic stress responses in plants. Physiol Plant. 2022;174:e13652.

    Article  PubMed  CAS  Google Scholar 

  11. Sami F, Yusuf M, Faizan M, Faraz A, Hayat S. Role of sugars under abiotic stress. Plant Physiol Biochem. 2016;109:54–61.

    Article  PubMed  CAS  Google Scholar 

  12. Chen Y, Miller AJ, Qiu B, Huang Y, Zhang K, Fan G, Liu X. The role of sugar transporters in the battle for carbon between plants and pathogens. Plant Biotechnol J. 2024.

  13. Misra VA, Wafula EK, Wang Y, dePamphilis CW, Timko MP. Genome-wide identification of MST, SUT and SWEET family sugar transporters in root parasitic angiosperms and analysis of their expression during host parasitism. BMC Plant Biol. 2019;19:196.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Singh J, Das S, Jagadis Gupta K, Ranjan A, Foyer CH, Thakur JK. Physiological implications of SWEETs in plants and their potential applications in improving source–sink relationships for enhanced yield. Plant Biotechnol J. 2023;21:1528–41.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Zhu Y, Tian Y, Han S, Wang J, Liu Y, Yin J. Structure, evolution, and roles of SWEET proteins in growth and stress responses in plants. Int J Biol Macromol. 2024;263:130441.

    Article  PubMed  CAS  Google Scholar 

  16. Lin IW, Sosso D, Chen LQ, Gase K, Kim SG, Kessler D, Klinkenberg PM, Gorder MK, Hou BH, Qu XQ, Carter CJ, Baldwin IT, Frommer WB. Nectar secretion requires sucrose phosphate synthases and the sugar transporter SWEET9. Nature. 2014;508:546–9.

    Article  PubMed  CAS  Google Scholar 

  17. Kanno Y, Oikawa T, Chiba Y, Ishimaru Y, Shimizu T, Sano N, Koshiba T, Kamiya Y, Ueda M, Seo M. AtSWEET13 and AtSWEET14 regulate gibberellin-mediated physiological processes. Nat Commun. 2016;7:13245.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Misra V, Mall AK. 7 - plant sugar transporters and their role in abiotic stress. Transporters Plant Osmotic Stress. 2021;101–12.

  19. Gao Y, Wang ZY, Kumar V, Xu XF, Yuan DP, Zhu XF, Li TY, Jia B, Xuan YH. Genome-wide identification of the SWEET gene family in wheat. Gene. 2018;642:284–92.

    Article  PubMed  CAS  Google Scholar 

  20. Li M, Xie H, He M, Su W, Yang Y, Wang J, Ye G, Zhou Y. Genome-wide identification and expression analysis of the StSWEET family genes in potato (Solanum tuberosum L). Genes Genom. 2020;42:135–53.

    Article  CAS  Google Scholar 

  21. Dai Z, Yan P, He S, Jia L, Wang Y, Liu Q, Zhai H, Zhao N, Gao S, Zhang H. Genome-wide identification and expression analysis of SWEET family genes in sweet potato and its two diploid relatives. Int J Mol Sci. 2022;23:15848.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Han X, Han S, Zhu Y, Liu Y, Gao S, Yin J, Wang F, Yao M. Genome-wide identification and expression analysis of the SWEET gene family in Capsicum annuum L. Int J Mol Sci. 2023;24:17408.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Filyushin MA, Anisimova OK, Shchennikova AV, Kochieva EZ. Genome-wide identification, expression, and response to fusarium infection of the SWEET gene family in garlic (Allium sativum L). Int J Mol Sci. 2023;24:7533.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Wen Z, Li M, Meng J, Li P, Cheng T, Zhang Q, Sun L. Genome-wide identification of the SWEET gene family mediating the cold stress response in Prunus mume. PeerJ. 2022;10:e13273.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Zhang X, Wang S, Ren Y, Gan C, Li B, Fan Y, Zhao X, Yuan Z. Identification, analysis and gene cloning of the SWEET gene family provide insights into sugar transport in pomegranate (Punica granatum). Int J Mol Sci. 2022;23.

  26. Liu N, Wei Z, Min X, Yang L, Zhang Y, Li J, Yang Y. Genome-wide identification and expression analysis of the SWEET gene family in annual alfalfa (Medicago polymorpha). Plants (Basel). 2023;12.

  27. Wang J, Zhang Q, Tung J, Zhang X, Liu D, Deng Y, Tian Z, Chen H, Wang T, Yin W, Li B, Lai Z, Dinesh-Kumar SP, Baker B, Li F. High-quality assembled and annotated genomes of Nicotiana tabacum and Nicotiana benthamiana reveal chromosome evolution and changes in defense arsenals. Mol Plant. 2024;17:423–37.

    Article  PubMed  CAS  Google Scholar 

  28. Ranawaka B, An J, Lorenc MT, Jung H, Sulli M, Aprea G, Roden S, Llaca V, Hayashi S, Asadyar L, LeBlanc Z, Ahmed Z, Naim F, de Campos SB, Cooper T, de Felippes FF, Dong P, Zhong S, Garcia-Carpintero V, Orzaez D, Dudley KJ, Bombarely A, Bally J, Winefield C, Giuliano G, Waterhouse PM. A multi-omic Nicotiana benthamiana resource for fundamental research and biotechnology. Nat Plant. 2023;9:1558–71.

    Article  CAS  Google Scholar 

  29. Narusaka Y, Nakashima K, Shinwari ZK, Sakuma Y, Furihata T, Abe H, Narusaka M, Shinozaki K, Yamaguchi-Shinozaki K. Interaction between two cis-acting elements, ABRE and DRE, in ABA-dependent expression of Arabidopsis rd29A gene in response to dehydration and high-salinity stresses. Plant J. 2003;34:137–48.

    Article  PubMed  CAS  Google Scholar 

  30. Zhang Q, Chen C, Guo R, Zhu X, Tao X, He M, Li Z, Shen L, Li Q, Ren D, Hu J, Zhu L, Zhang G, Qian Q. Plasma membrane-localized hexose transporter OsSWEET1b, affects sugar metabolism and leaf senescence. Plant Cell Rep. 2024;43:29.

    Article  PubMed  CAS  Google Scholar 

  31. Li M, Li H, Zhu Q, Liu D, Li Z, Chen H, Luo J, Gong P, Ismail AM, Zhang Z. Knockout of the sugar transporter OsSTP15 enhances grain yield by improving tiller number due to increased sugar content in the shoot base of rice (Oryza sativa L). New Phytol. 2024;241:1250–65.

    Article  PubMed  CAS  Google Scholar 

  32. Zhang M, Lv D, Ge P, Bian Y, Chen G, Zhu G, Li X, Yan Y. Phosphoproteome analysis reveals new drought response and defense mechanisms of seedling leaves in bread wheat (Triticum aestivum L). J Proteom. 2014;109:290–308.

    Article  CAS  Google Scholar 

  33. Iftikhar J, Lyu M, Liu Z, Mehmood N, Munir N, Ahmed MAA, Batool W, Aslam MM, Yuan Y, Wu B. Sugar and hormone dynamics and the expression profiles of SUT/SUC and SWEET sugar transporters during flower development in petunia axillaris. Plants. 2020;9:1770.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Fukaki H, Fujisawa H, Tasaka M. SGR1, SGR2, and SGR3: novel genetic loci involved in shoot gravitropism in Arabidopsis thaliana. Plant Physiol. 1996;110:945–55.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Song S, Qi T, Fan M, Zhang X, Gao H, Huang H, Wu D, Guo H, Xie D. The bHLH subgroup IIId factors negatively regulate jasmonate-mediated plant defense and development. PLoS Genet. 2013;9:e1003653.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Zhang S, Wang H, Wang T, Liu W, Zhang J, Fang H, Zhang Z, Peng F, Chen X, Wang N. MdMYB305–MdbHLH33–MdMYB10 regulates sugar and anthocyanin balance in red-fleshed apple fruits. Plant J. 2023;113:1062–79.

    Article  PubMed  CAS  Google Scholar 

  37. Luo F, Cai J-H, Kong X-M, Zhou Q, Zhou X, Zhao Y-B, Ji S-J. Transcriptome profiling reveals the roles of pigment mechanisms in postharvest broccoli yellowing. Hortic Res. 2019;6.

  38. Chen K, Li G-J, Bressan RA, Song C-P, Zhu J-K, Zhao Y. Abscisic acid dynamics, signaling, and functions in plants. J Integr Plant Biol. 2020;62:25–54.

    Article  PubMed  CAS  Google Scholar 

  39. Rezaee S, Ahmadizadeh M, Heidari P. Genome-wide characterization, expression profiling, and post-transcriptional study of GASA gene family. Gene Rep. 2020;20:100795.

    Article  CAS  Google Scholar 

  40. Yan Y, Yan Z, Zhao G. Genome-wide identification of WRKY transcription factor family members in Miscanthus sinensis (Miscanthus sinensis Anderss). Sci Rep. 2024;14:5522.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Rolland F, Baena-Gonzalez E, Sheen J. Sugar sensing and signaling in plants: conserved and novel mechanisms. Annu Rev Plant Biol. 2006;57:675–709.

    Article  PubMed  CAS  Google Scholar 

  42. Xue L, Wei Z, Zhai H, Xing S, Wang Y, He S, Gao S, Zhao N, Zhang H, Liu Q. The IbPYL8–IbbHLH66–IbbHLH118 complex mediates the abscisic acid-dependent drought response in sweet potato. New Phytol. 2022;236:2151–71.

    Article  PubMed  CAS  Google Scholar 

  43. Chen Q, Hu T, Li X, Song C-P, Zhu J-K, Chen L, Zhao Y. Phosphorylation of SWEET sucrose transporters regulates plant root:shoot ratio under drought. Nat Plant. 2022;8:68–77.

    Article  CAS  Google Scholar 

  44. Castro B, Citterico M, Kimura S, Stevens DM, Wrzaczek M, Coaker G. Stress-induced reactive oxygen species compartmentalization, perception and signalling. Nat Plant. 2021;7:403–12.

    Article  CAS  Google Scholar 

  45. Zulfiqar F, Ashraf M. Proline alleviates abiotic stress induced oxidative stress in plants. J Plant Growth Regul. 2023;42:4629–51.

    Article  CAS  Google Scholar 

  46. Gosti F, Beaudoin N, Serizet C, Webb AAR, Vartanian N, Giraudat J. ABI1 protein phosphatase 2 C is a negative regulator of abscisic acid signaling. Plant Cell. 1999;11:1897–909.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  47. Bai G, Yang D-H, Cao P, Yao H, Zhang Y, Chen X, Xiao B, Li F, Wang Z-Y, Yang J, Xie H. Genome-wide identification, gene structure and expression analysis of the MADS-box gene family indicate their function in the development of tobacco (Nicotiana tabacum L). Int J Mol Sci. 2019;20:5043.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Mistry J, Chuguransky S, Williams L, Qureshi M, Salazar GA, Sonnhammer ELL, Tosatto SCE, Paladin L, Raj S, Richardson LJ, Finn RD, Bateman A. Pfam: the protein families database in 2021. Nucleic Acids Res. 2021;49:D412–9.

    Article  PubMed  CAS  Google Scholar 

  49. Wang J, Chitsaz F, Derbyshire MK, Gonzales NR, Gwadz M, Lu S, Marchler GH, Song JS, Thanki N, Yamashita RA, Yang M, Zhang D, Zheng C, Lanczycki CJ, Marchler-Bauer A. The conserved domain database in 2023. Nucleic Acids Res. 2023;51:D384–8.

    Article  PubMed  CAS  Google Scholar 

  50. Gasteiger E, Hoogland C, Gattiker A, Duvaud Se, Wilkins MR, Appel RD, Bairoch A. Protein identification and analysis tools on the ExPASy server. Proteom Protocols Handb. 2005;112:571–607.

    Article  Google Scholar 

  51. Chou KC, Shen HB. Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization. PLoS ONE. 2010;5:e11335.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Abramson J, Adler J, Dunger J, Evans R, Green T, Pritzel A, Ronneberger O, Willmore L, Ballard AJ, Bambrick J, Bodenstein SW, Evans DA, Hung CC, O’Neill M, Reiman D, Tunyasuvunakool K, Wu Z, Žemgulytė A, Arvaniti E, Beattie C, Bertolli O, Bridgland A, Cherepanov A, Congreve M, Cowen-Rivers AI, Cowie A, Figurnov M, Fuchs FB, Gladman H, Jain R, Khan YA, Low CMR, Perlin K, Potapenko A, Savy P, Singh S, Stecula A, Thillaisundaram A, Tong C, Yakneen S, Zhong ED, Zielinski M, Žídek A, Bapst V, Kohli P, Jaderberg M, Hassabis D, Jumper JM. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature. 2024;630:493–500.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  53. Chen C, Wu Y, Li J, Wang X, Zeng Z, Xu J, Liu Y, Feng J, Chen H, He Y, Xia R. TBtools-II: a one for all, all for one bioinformatics platform for biological big-data mining. Mol Plant. 2023;16:1733–42.

    Article  PubMed  CAS  Google Scholar 

  54. Feng C, Han J, Han X, Jiang J. Genome-wide identification, phylogeny, and expression analysis of the SWEET gene family in tomato. Gene. 2015;573:261–72.

    Article  PubMed  CAS  Google Scholar 

  55. Tamura K, Stecher G, Kumar S. MEGA11: molecular evolutionary genetics analysis version 11. Mol Biol Evol. 2021;38:3022–7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Letunic I, Bork P. Interactive tree of life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics. 2006;23:127–8.

    Article  PubMed  Google Scholar 

  57. Bailey TL, Boden M, Buske FA, Frith M, Grant CE, Clementi L, Ren J, Li WW, Noble WS. MEME suite: tools for motif discovery and searching. Nucleic Acids Res. 2009;37:W202–8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Gilchrist CLM, Chooi Y-H. Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases. Fungal Biol Biotechnol. 2021;8:13.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Hu B, Jin J, Guo AY, Zhang H, Luo J, Gao G. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics. 2015;31:1296–7.

    Article  PubMed  Google Scholar 

  60. Rombauts S, Déhais P, Van Montagu M, Rouzé P. PlantCARE, a plant cis-acting regulatory element database. Nucleic Acids Res. 1999;27:295–6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, Gable AL, Fang T, Doncheva Nadezhda T, Pyysalo S, Bork P, Jensen Lars J, von Mering C. The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2022;51:D638–46.

    Article  PubMed Central  Google Scholar 

  62. Xu J, Chen Q, Liu P, Jia W, Chen Z, Xu Z. Integration of mRNA and miRNA analysis reveals the molecular mechanism underlying salt and alkali stress tolerance in tobacco. Int J Mol Sci. 2019;20:2391.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Liu T, Li C, Zhong J, Shu D, Luo D, Li Z, Zhou J, Yang J, Tan H, Ma X. Exogenous 1’,4’-trans-Diol-ABA induces stress tolerance by affecting the level of gene expression in tobacco (Nicotiana tabacum L). Int J Mol Sci. 2021;22:2555.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Hu Z, He Z, Li Y, Wang Q, Yi P, Yang J, Yang C, Borovskii G, Cheng X, Hu R, Zhang W. Transcriptomic and metabolic regulatory network characterization of drought responses in tobacco. Front Plant Sci. 2022;13:1067076.

    Article  PubMed  Google Scholar 

  65. Zhang Y, Chen M, Siemiatkowska B, Toleco MR, Jing Y, Strotmann V, Zhang J, Stahl Y, Fernie AR. A highly efficient agrobacterium-mediated method for transient gene expression and functional studies in multiple plant species. Plant Commun. 2020;1:100028.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 31801021), The Natural Science Foundation of Shandong Province (ZR2024QC155), The Agricultural Science and Technology Innovation Program (ASTIP-TRIC02), and Fundamental Research Funds for Central Non-profit Scientific Institution (1610232024009).

Author information

Author notes

  1. Wenting Song and Luyao Xue contributed equally to this work.

Authors and Affiliations

  1. Tobacco Research Institute, Chinese Academy of Agricultural Sciences, Qingdao, China

    Wenting Song, Luyao Xue, Xiaoshan Jin, Xiaoqing Liu, Xinru Wu, Mengmeng Cui, Qianyu Liu & Dawei Wang

  2. Key Laboratory for Tobacco Gene Resources, State Tobacco Monopoly Administration, Qingdao, China

    Wenting Song, Luyao Xue, Xiaoshan Jin, Xiaoqing Liu, Xinru Wu, Mengmeng Cui, Qianyu Liu & Dawei Wang

  3. Graduate School of Chinese Academy of Agricultural Science, Beijing, China

    Wenting Song

  4. Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, China

    Xiaoxia Chen

Authors
  1. Wenting Song
    View author publications

    Search author on:PubMed Google Scholar

  2. Luyao Xue
    View author publications

    Search author on:PubMed Google Scholar

  3. Xiaoshan Jin
    View author publications

    Search author on:PubMed Google Scholar

  4. Xiaoqing Liu
    View author publications

    Search author on:PubMed Google Scholar

  5. Xiaoxia Chen
    View author publications

    Search author on:PubMed Google Scholar

  6. Xinru Wu
    View author publications

    Search author on:PubMed Google Scholar

  7. Mengmeng Cui
    View author publications

    Search author on:PubMed Google Scholar

  8. Qianyu Liu
    View author publications

    Search author on:PubMed Google Scholar

  9. Dawei Wang
    View author publications

    Search author on:PubMed Google Scholar

Contributions

D.W., W.S., and L.X. conceived and designed the research. W.S., L.X., X.J., X.L., X.C., and X.W. performed the experiments. W.S., L.X., X.J., X.L., X.C., M.C., and Q.L. analyzed the data. W.S. and L.X. wrote the paper. D.W., and L.X. revised the paper. All authors read and approved the final version of the paper.

Corresponding authors

Correspondence to Luyao Xue or Dawei Wang.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, W., Xue, L., Jin, X. et al. Genome-wide identification of SWEET family genes and functional analysis of NtSWEET12i under drought and saline-alkali stresses in tobacco. BMC Plant Biol 25, 195 (2025). https://doi.org/10.1186/s12870-025-06190-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12870-025-06190-w

Keywords

BMC Plant Biology

ISSN: 1471-2229

Contact us