Overexpression of SlERF.F4 in Tomato Delays Fruit Ripening and Enhances Drought Tolerance

Abstract

The AP2/ERF transcription factor family plays pivotal roles in regulating plant growth, development, and responses to environmental stimuli. In this study, we identified and functionally characterized SlERF.F4, a tomato (Solanum lycopersicum) ERF gene encoding a nuclear-localized protein with a conserved AP2/ERF domain. SlERF.F4 transcript levels were rapidly induced by diverse abiotic stresses and phytohormones, including drought, salinity, temperature extremes, abscisic acid (ABA), and brassinosteroids (BR). Overexpression of SlERF.F4 in tomato resulted in reduced plant height, delayed fruit ripening, and downregulation of key ripening-associated genes (RIN, CNR, E4, E8, and PG). Furthermore, SlERF.F4 transgenic lines exhibited enhanced drought tolerance, characterized by reduced wilting, lower malondialdehyde (MDA) accumulation, and significantly higher survival rates under water-deficit conditions. Collectively, these results indicate that SlERF.F4 functions as a negative regulator of fruit ripening and a positive modulator of drought tolerance, highlighting its potential as a target for tomato genetic improvement.

1. Introduction

The APETALA2/ethylene-responsive factor (AP2/ERF) transcription factor family is one of the largest and most widely distributed gene families in plants, playing essential roles in regulating growth, development, and adaptation to environmental cues [1]. A defining feature of this family is the presence of a highly conserved AP2/ERF DNA-binding domain, typically comprising 60–70 amino acids, which facilitates the recognition of cis-acting elements such as the GCC-box and the dehydration-responsive element (DRE) in the promoters of target genes [2,3,4]. Based on sequence similarity and domain architecture, the AP2/ERF family is further classified into AP2, ERF, DREB (Dehydration Responsive Element-Binding), RAV (Related to ABI3/VP) and Soloist subfamilies [5]. The ERF subfamily is particularly notable for its involvement in ethylene signaling and stress-responsive transcriptional regulation, where its members function as either activators or repressors to fine-tune plant developmental and physiological processes [6,7].

In climacteric fruits, ripening is largely driven by ethylene biosynthesis and signaling, a process extensively modulated by ERF transcription factors. They exert their regulatory effects through interacting with ripening regulators such as RIPENING INHIBITOR (RIN) and COLORLESS NON-RIPENING (CNR), or by directly binding to the promoters of ethylene biosynthesis genes (e.g., ACS, ACO) and ripening-associated genes (e.g., polygalacturonase, expansins) [8,9,10]. For example, tomato SlERF.B3 transcription factor regulates fruit ripening by modulating ethylene production and carotenoid accumulation. Fruits expressing a dominant repressor version of SlERF.B3 (ERF.B3-SRDX) accelerated softening and increased climacteric ethylene production, concomitant with the upregulation of ethylene biosynthesis genes (ACS2, ACS4, and ACO1), cell wall-modifying genes (E4, E8, and PG2A), and key ripening regulators (RIN, CNR, NOR, and HB-1) [11,12]. Similarly, SlERF6 has been demonstrated to integrate ethylene signaling with carotenoid synthesis pathways during ripening [13]. Conversely, SlERF.F12, a member of the ERF.F subfamily containing ERF-associated Amphiphilic Repression (EAR) motifs, negatively regulates the onset of tomato fruit ripening [14]. In addition, SlAP2a has been identified as a negative regulator of fruit ripening and ethylene production [15,16]. Despite these significant advances, the functions of numerous other ripening-induced ERFs in tomato remain largely uncharacterized.

Beyond their roles in development, AP2/ERF transcription factors are central mediators of plant adaptation to abiotic stresses such as drought, salinity, and temperature extremes. Many ERFs are rapidly induced under stress conditions and function downstream of hormone signaling pathways, including abscisic acid (ABA), jasmonic acid (JA), and brassinosteroids (BR), thereby integrate environmental signals into transcriptional programs that enhance stress tolerance [17]. In Arabidopsis, AtERF1 confers broad-spectrum stress tolerance by binding to GCC or DRE/CRT cis-elements and integrating JA, ET, and ABA signaling pathways [18]. BR signaling components also interact with ERF-mediated networks; for example, BZR1 positively regulates freezing tolerance through both CBF-dependent and CBF-independent pathways [19], while BIN2 interacts with and phosphorylates ICE1 to fine-tune CBF expression, thereby balancing growth with cold stress responses [20]. In crop species, OsERF71 in rice enhances drought tolerance by modulating the expression of cell wall-related genes, which in turn improves root architecture and water uptake [21]. In maize, ZmEREB57 promotes salt tolerance by activating ZmAOC2, a gene involved in JA biosynthesis [22]. In wheat, TaERF3 confers tolerance to both drought and salinity by directly binding to GCC-box motifs in the promoters of stress-related genes [23]. Functional diversity among ERFs is also evident in tomato; for instance, SlERF84 enhances drought and salt tolerance by promoting reactive oxygen species (ROS) scavenging [24], whereas SlERF.B1 acts as a negative regulator of drought and salt tolerance by binding to the DRE in the promoters of SlARF5 and SlER24 and repressing their expression [25]. Collectively, these findings underscore the role of ERFs as critical molecular nodes that integrate hormonal and environmental signals into adaptive responses, often involving sophisticated crosstalk between stress regulation and developmental processes.

In the previous study, we found that overexpression of AtBES1D, a dominant gain-of-function mutant of the Arabidopsis BES1 gene, enhances tomato fruit ripening, whereby SlERF.F4 (Solyc07g053740) was identified as a highly enriched target [26]. However, its role in fruit ripening and stress adaptation remains unknown. In the present study, we characterized SlERF.F4, a putative ERF protein containing a conserved AP2/ERF domain. Expression analyses revealed responsiveness to multiple abiotic stresses and hormone treatments. Functional investigations using transgenic overexpression lines revealed that SlERF.F4 acts as a negative regulator of fruit ripening and concurrently enhances drought tolerance in tomato.

2. Materials and Methods

2.1. Plant Growth and Stress Treatments

Tomato (Solanum lycopersicum cv. Micro-Tom) plants were used in this study. Seeds were sown in small pots containing a peat-to-vermiculite mixture (3:1, v/v) and grown in a controlled growth chamber conditions (25 °C, 16 h light/8 h dark photoperiod, light intensity 150 μmol·m⁻²·s⁻¹). Seedlings were irrigated with half-strength Hoagland’s nutrient solution twice a week. To examine the expression pattern of SlERF.F4, three-week-old wild-type (WT) seedlings were subjected to various treatments. For dehydration treatment, plants were carefully removed from the soil, roots were excised, and seedlings were placed on dry filter paper under standard growth conditions. For temperature stress, seedlings were exposed to either 4 °C (cold) or 42 °C (heat). For salt stress, seedlings were irrigated with 200 mM NaCl solution. For hormone treatments, seedlings were sprayed with 100 μM abscisic acid (ABA) or 0.1 μM 24-epibrassinolide (EBL), while control plants were sprayed with distilled water. Samples were collected at 0, 1, 3, 6, 12, and 24 h after treatment, immediately frozen in liquid nitrogen, and stored at −80 °C for subsequent analyses. Each treatment included three independent biological replicates.

2.2. Gene Cloning and Sequence Analysis

Total RNA was extracted from breaker-stage tomato fruits using the RNAprep Pure Plant Total RNA Extraction Kit (TIANGEN, Beijing, China), following the manufacturer’s protocol. First-strand cDNA was synthesized from 1 μg total RNA using the PrimeScript™ RT Reagent Kit (Takara, Dalian, China). The full-length coding sequence (CDS) of SlERF.F4 (excluding the stop codon) was amplified with gene-specific primers (SlERF.F4-L and SlERF.F4-R, Supplementary Table S1) and ligated into the pCAMBIA1300-YFP binary vector using the pEASY^®-Basic Seamless Cloning and Assembly Kit (TransGen, Beijing, China).

The deduced amino acid sequence was analyzed with the ExPASy ProtParam tool to predict the molecular weight and isoelectric point. A phylogenetic tree was constructed using MEGA 11.0.13 software with the neighbor-joining method and 1000 bootstrap replicates. The conserved AP2/ERF domain was identified using DNAMAN 6.0 software. For promoter analysis, a 2000 bp genomic sequence upstream of the SlERF.F4 start codon was obtained from the Tomato Genome Database https://solgenomics.net/ (accessed on 2 September 2025), and putative cis-acting regulatory elements were predicted using the PlantCARE database http://bioinformatics.psb.ugent.be/webtools/plantcare/html/ (accessed on 2 September 2025).

2.3. Quantitative Real-Time PCR (qRT-PCR) Analysis

Total RNA extraction and cDNA synthesis were carried out as described above. qRT-PCR was performed on a CFX96 Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) using TB Green^® Premix Ex Taq™ II (Takara, Japan). The tomato SlACTIN (Solyc03g078400) was used as an internal reference for normalization. Relative expression levels were calculated using the 2^−ΔΔCt method [27]. This calculation is based on the assumption of ideal PCR amplification efficiency (E = 2.0) for all targets. To enhance the reliability of this approach, primer pairs were designed under stringent criteria (amplicon size 80–150 bp, Tm ~60 °C) and validated to produce a single amplification product via melt curve analysis. Each reaction (20 μL) contained 1 μL of cDNA, 1 μL of each gene-specific primer (10 μM), 10 μL TB Green^® Premix Ex Taq™ II, and 7 μL nuclease-free water. All primer sequences are listed in Supplementary Table S1.

2.4. Subcellular Localization

The pCAMBIA1300-SlERF.F4-YFP plasmid and the empty pCAMBIA1300-YFP vector (control) were transiently expressed in Arabidopsis thaliana (Col-0) mesophyll protoplasts. Protoplasts were isolated from the leaves of 4-week-old seedlings using an enzymatic digestion method as previously described [28]. After purification and counting, freshly isolated mesophyll protoplasts were transfected with 10 μg of plasmid DNA via polyethylene glycol (PEG)-mediated transformation [29]. The experiment was performed with three independent biological replicates. After transfection, protoplasts were incubated in the dark at room temperature for 22 h. For confocal imaging, at least 4 successfully transformed protoplasts were examined per replicate. YFP fluorescence was imaged using a laser scanning confocal microscope (Nikon-C2plus) equipped with a 100× oil-immersion objective (Plan Apo λ 100× Oil). YFP was excited at 488 nm, and emission was collected between 490 and 560 nm. The images are representative of the consistent localization pattern observed across all replicates.

2.5. Generation of Transgenic Tomato Plants

The recombinant pCAMBIA1300-SlERF.F4-YFP plasmid was introduced into Agrobacterium tumefaciens strain GV3101. Tomato transformation was performed according to the method described by Shao et al. [30] with modifications. Briefly, cotyledon explants from 6- to 8-day-old seedlings were pre-cultured for 2 days and then incubated for 12 min in Agrobacterium suspension. After 2 days of co-cultivation, explants were transferred to shoot selection medium, containing Murashige and Skoog (MS) medium supplemented with 1 mg L⁻¹ trans-zeatin, 0.2 mg L⁻¹ IAA, 250 mg L⁻¹ timentin, and 10 mg L⁻¹ hygromycin. Regenerated shoots were subsequently rooted on medium containing 0.05 mg L⁻¹ NAA and 250 mg L⁻¹ timentin. Putative transgenic lines were initially screened by PCR and further confirmed by qRT-PCR to assess SlERF.F4 expression levels. Homozygous T₂ or T₃ progeny were used for all subsequent phenotypic analyses. All primers are listed in Supplementary Table S1.

2.6. Phenotype Analysis

Transgenic and WT plants were cultivated under the standard growth conditions described above. Plant height and flowering time were recorded during the growth period. Fruit development was monitored by assessing the number of fruits per plant, fruit size, and the number of days from anthesis to the breaker stage. Breaker-stage fruits from transgenic and WT plants were harvested for RNA extraction, and the expression levels of key ripening-related genes were analyzed by qRT-PCR as described previously.

2.7. Drought Stress Treatment and Measurement of Physiological Indicators

Drought stress experiments were conducted using four-week-old plants. For each genotype (WT, OE-6#, OE-7#), 36 plants were divided into three biological replicates of 12 plants each. Water was withheld for 9 d, after which plants were re-watered to assess recovery. Phenotypic changes were recorded daily, and survival rates were calculated 3 d after re-watering. A plant was considered alive if it showed renewed turgor and new leaf growth. Survival rate for each replicate was calculated as: (Number of surviving plants/Total plants in each replicate) × 100%. The presented survival rates are the mean ± SD of three independent biological replicates. Leaf samples were collected after 5 days of drought stress for physiological measurements. RWC was calculated using the formula: RWC (%) = [(Fresh weight-Dry weight)/(Turgid weight-Dry weight)] × 100. Malondialdehyde (MDA) content was measured using a commercial assay kit (Solarbio, Beijing, China) according to the manufacturer’s instructions.

2.8. Statistical Analysis

All experiments were performed with at least three independent biological replicates. Data were analyzed using SPSS version 19.0 (IBM, Armonk, NY, USA). Statistical differences were assessed by Student’s t-test. A probability value of * p < 0.05 was considered statistically significant, and ** p < 0.01 was considered highly significant.

3. Results

3.1. Sequence Analysis and Domain Characterization of SlERF.F4

We successfully isolated the full-length coding sequence of SlERF.F4 from tomato (GenBank accession number: XM_004243323), which spans 678 bp and encodes a protein of 225 amino acids. Bioinformatic analysis predicted a molecular weight of 24.1 kDa and an isoelectric point (pI) of 9.30, indicating that SlERF.F4 is a basic protein. The protein was classified as moderately hydrophobic, with an instability index of 44.51, suggesting potential instability in vitro. Phylogenetic analysis revealed that SlERF.F4 shares high sequence similarity with SlERF.F7 and AtERF4, implying potential functional conservation (Figure 1A). Multiple sequence alignment confirmed the presence of a conserved AP2/ERF DNA-binding domain, which is characteristic of the AP2/ERF family. Notably, the alanine at position 14 and the aspartic acid at position 19 were conserved in SlERF.F4, SlERF.F7, and AtERF4, confirming its classification within the ERF subfamily (Figure 1B).

3.2. Subcellular Localization of SlERF.F4

To determine the subcellular localization of SlERF.F4, we transiently expressed a SlERF.F4-YFP fusion protein and a YFP-only control in Arabidopsis protoplasts. Fluorescence signal from the control was distributed throughout the cytoplasm and nucleus. In contrast, the SlERF.F4-YFP fusion protein was exclusively detected in the nucleus (Figure 2). This clear nuclear localization supports the predicted role of SlERF.F4 as a transcription factor.

3.3. Expression Profile of SlERF.F4 in Response to Stresses and Hormones

Analysis of the SlERF.F4 promoter region (approximately 2.0 kb) identified multiple putative cis-acting elements, including light-responsive elements (3-AF1 binding site, G-box, Box 4, and TCT-motif), hormone-related motifs (six ABREs for ABA response, two CGTCA-motifs and two TGACG-motifs for MeJA response, and one P-box for gibberellin response), ten MYC binding sites (E-box), and stress-associated elements such as ARE (anaerobic induction) and circadian regulatory elements (Supplementary Table S2). This suggests that SlERF.F4 expression is likely regulated by diverse hormonal and environmental signals. We then examined the transcript dynamics of SlERF.F4 under various abiotic stresses and hormone treatments using qRT-PCR. The results showed that SlERF.F4 expression was strongly induced by drought and salt stress, with transcript levels peaking at 12 h post-treatment (Figure 3A,B). Under cold stress, the expression of SlERF.F4 increased rapidly, reaching a maximum at 3 h before declining (Figure 3C). Heat stress led to a steady increase in transcript accumulation, also peaking at 6 and 12 h (Figure 3D). Furthermore, SlERF.F4 expression was upregulated by treatment with ABA and brassinosteroid (BR), albeit with distinct temporal patterns (Figure 3E,F). Collectively, these findings indicate that SlERF.F4 is responsive to multiple abiotic stresses and phytohormone signals.

3.4. Phenotypic Analysis of SlERF.F4 Transgenic Plants

To investigate the biological function of SlERF.F4, we generated transgenic tomato plants overexpressing the gene. Two homozygous T₂ lines, OE-6# and OE-7#, exhibiting approximately 2.3-fold and 2.6-fold higher SlERF.F4 transcript levels, respectively, were selected for detailed analysis (Figure 4A). Both overexpression lines displayed a significant reduction in plant height compared to the wild-type (WT) controls (Figure 4B,C). No obvious difference in flowering time was observed between transgenic and WT plants. In addition, both fruit number and total yield per plant were significantly lower in the transgenic lines than in the WT (Figure 4D–F).

3.5. Overexpression of SlERF.F4 Delays Fruit Ripening and Suppresses the Expression of Ripening-Related Genes

To further elucidate the role of SlERF.F4 in tomato fruit ripening, fruit phenotypes were recorded at different time points after anthesis. At 35 days post-anthesis (DPA), WT fruits had reached the breaker stage, whereas fruits from the OE-6# and OE-7# lines remained at the pink stage (Figure 5A). Overall, fruit ripening in the transgenic lines was delayed by approximately 4–5 d compared with WT plants. The expression patterns of key ripening-related genes were subsequently examined in fruits at the mature green (MG), breaker (BR), BR+4, and BR+7 stages. In both OE-6# and OE-7# fruits, transcript levels of RIN and CNR were consistently lower than those in WT across all examined stages (Figure 5B,C). For ethylene-related genes, E4 expression in transgenic fruits was significantly reduced at BR and BR+4 stages, whereas E8 was significantly lower at MG and BR stages (Figure 5D,E). The cell wall degrading gene PG exhibited significantly reduced expression in transgenic fruits at MG, BR+4, and BR+7 stages compared with WT (Figure 5F). These results suggest that SlERF.F4 overexpression delays fruit ripening, potentially through the suppression of key ripening- and ethylene-related genes.

3.6. Overexpression of SlERF.F4 Enhances Drought Tolerance in Tomato

For the strong induction of SlERF.F4 by drought stress, we further evaluated the drought tolerance of the overexpression lines. After 3 d of water withholding, WT plants exhibited slight wilting symptoms, whereas OE-6# and OE-7# plants retained normal (Figure 6A). After 6 d and 9 d, both transgenic and WT seedlings exhibited obvious wilting phenotype; however, the severity remained markedly lower in the OE lines compared with WT (Figure 6A). Leaf relative water content (RWC) in the OE lines was significantly higher than in WT, whereas MDA accumulation was consistently lower under drought conditions (Figure 6B,C). Following 9 d of drought and 3 d of re-watering, the survival rates of OE-6# and OE-7# exceeded 80%, significantly higher than about 20% survival rate observed for WT plants (Figure 6D). These data conclusively show that overexpression of SlERF.F4 enhances drought tolerance in tomato. Taken together, these findings demonstrate that SlERF.F4 overexpression confers enhanced drought tolerance in tomato.

4. Discussion

ERF transcription factors are well-established as multifunctional regulators of plant growth, development, and environmental adaptation. In tomato, 77 ERF subfamily genes have been identified and phylogenetically classified into nine subclasses (A–J) [8]. However, the biological functions of most members remain uncharacterized. In this study, we provide functional evidence that SlERF.F4, a nuclear-localized transcription factor, modulates plant architecture, fruit ripening, and drought tolerance, thereby offering new insights into the functional diversity of the ERF family in tomato.

A notable finding of this study is that SlERF.F4 overexpression led to a significant reduction in plant height (Figure 4B,C), suggesting that it acts as a negative regulator of shoot elongation. This observation aligns with reports of other ERFs that restrict plant growth. For example, in rice, OsRPH1 and OsDREB2B suppress plant height by modulating gibberellin (GA) metabolism, either through the upregulation of GA inactivation genes or repression of GA biosynthesis [31,32]. Similarly, SlERF.J2 has been shown to inhibit hypocotyl elongation and plant height by integrating light, auxin, and GA signaling pathways [33]. In contrast, some ERFs, such as NtERF10 in tobacco, promote plant height by regulating photosynthesis- and glycolysis-related genes [34]. Similarly, ERF11 in Arabidopsis promotes internode elongation by activating gibberellin biosynthesis and signaling pathways [35]. The presence of one GA-responsive P-box and ten BZR1-binding E-box (CANNTG) cis-elements in the SlERF.F4 promoter suggests that the SlERF.F4-mediated inhibition of plant growth may be associated with GA and BR signaling pathways (Supplementary Table S2). These comparative analyses highlight that the growth-regulatory functions of ERF transcription factors are highly gene- and species-specific.

The most pronounced phenotypic effect of SlERF.F4 overexpression was the marked delay in fruit ripening (Figure 4D and Figure 5A). This was accompanied by the significant downregulation of pivotal ripening regulators, including RIN and CNR, as well as ethylene-responsive genes (E4, E8) and the cell wall metabolism gene PG (Figure 5B–F). This transcriptional repression profile strongly suggests that SlERF.F4 functions as a negative regulator of fruit ripening. This functional role is consistent with other ERFs in tomato. For instance, RNAi-mediated suppression of SlERF6 was shown to enhance both carotenoid accumulation and ethylene levels during fruit ripening, indicating its role in integrating ethylene signaling with carotenoid biosynthesis [13]. SlERF.F12, another member of the ERF.F subgroup containing an EAR motif, delays ripening by recruiting the co-repressor TOPLESS 2 (TPL2) and the histone deacetylases (HDAs) HDA1/HDA3 to repress the transcript levels of ripening-related genes [14]. Similarly, heterologous overexpression of Ficus carica ERF12, an EAR motif-containing repressor that binds ripening gene promoters and interacts with TPL/HDA co-repressors, significantly increased tomato fruit firmness and decreased ethylene evolution [36]. The presence of an EAR motif in SlERF.F4 (LDLNL at the 215th amino acid) further supports its potential to act as a transcriptional repressor, possibly through the recruitment of co-repressor complexes. Therefore, we propose that SlERF.F4 integrates into the transcriptional network that finely controls progression of tomato fruit ripening, primarily by suppressing the expression of critical ripening-related genes.

The AP2/ERF transcription factor family is a central regulator of plant drought adaptation, exhibiting functional variety with members acting as either positive or negative regulators. For example, overexpression of ZmERF21 [37], GmERF9 [38], OsERF48 [39], OsERF71 [21], and MhERF113 [40] has been shown to enhance drought tolerance in their respective plants. In contrast, ERF transcription factors such as SlERF.B1 and OsERF109 function as negative regulators of the drought stress response [25,41]. Consistent with this paradigm, our findings identified SlERF.F4 as a positive regulator of drought tolerance in tomato. This conclusion is supported by the robust performance of SlERF.F4-overexpressing lines under water deficit, which was characterized by reduced wilting, enhanced water retention, attenuated oxidative damage, and significantly higher survival rates (Figure 6). The role of SlERF.F4 as a stress-responsive transcription factor is corroborated by its rapid induction in response to drought, ABA, and BR (Figure 3), with the presence of ABA-responsive elements (ABREs) in its promoter providing a plausible basis for this regulation. Thus, we propose that SlERF.F4 serves as a molecular nexus, integrating ABA and potentially BR signaling pathways to activate downstream gene networks that enhance osmotic adjustment and oxidative stress management, thereby positioning it within the cohort of ERF factors that positively modulate drought resilience.

A compelling aspect of this study is the dual functionality of SlERF.F4 in regulating both a key developmental process and an essential stress response. Such multifunctionality is not uncommon among ERF transcription factors, which often serve as key nodes in the cross-talk between development and stress adaptation. For instance, in poplar, PtaERF194 has been shown to confer drought tolerance at the cost of reduced plant height and leaf area [42]. Although SlERF.F4 overexpression confers enhanced drought tolerance, its concomitant delay in fruit ripening and reduction in yield under standard conditions pose a significant challenge for its direct application in breeding. To resolve this trade-off, stress-responsive promoters or CRISPR-based genome editing are needed to precisely regulate SlERF.F4 expression, thus enhancing its protective role without compromising agricultural productivity.

5. Conclusions

In conclusion, our study identifies SlERF.F4 as a key transcriptional regulator that concurrently delays fruit ripening and enhances drought tolerance in tomato. While this trade-off presents a challenge for direct application, SlERF.F4 represents a promising target for future breeding strategies aimed at improving drought resilience, potentially through the use of stress-inducible expression systems.