A GATA Transcription Factor Modulates Melatonin Production and Drought Resistance in Hypericum perforatum

Melatonin, a key bioactive compound in Hypericum perforatum, is synthesized through a cascade of enzymatic reactions catalyzed by serotonin N -acetyltransferase (SNAT) and N -acetylserotonin O -methyltransferase (ASMT). Although its biosynthetic pathway has been elucidated, the regulatory mechanisms controlling melatonin production remain poorly understood. This study investigates the potential role of GATA transcription factors in melatonin biosynthesis, given their critical regulatory functions in various plant physiological processes. We focused on characterizing the functional role of HpGATA7 in H. perforatum . Bioinformatics analyses predicted the physicochemical properties, subcellular localization, and phylogenetic relationships of HpGATA7. Yeast one-hybrid assays, luciferase reporter analyses, and subcellular localization experiments demonstrated that HpGATA7 possesses strong transcriptional activation activity and is localized in the nucleus. Expression profiling revealed that HpGATA7 exhibits significantly higher transcript levels in floral organs and is markedly induced under various abiotic stress conditions. Molecular interaction assays further confirmed that HpGATA7 directly binds to the HpSNAT1 promoter and activates its transcription. Functional validation through genetic transformation showed that HpGATA7 overexpression significantly increased melatonin levels, whereas RNA interference (RNAi)-mediated silencing reduced melatonin content in transgenic H. perforatum . Under drought stress, overexpression lines exhibited enhanced antioxidant enzyme activity, mitigating oxidative damage. In summary, this study identifies HpGATA7 as a positive regulator of melatonin biosynthesis in H. perforatum by directly activating HpSNAT1 expression. These findings provide novel insights into the transcriptional regulation of plant melatonin synthesis and antioxidant mechanisms, offering valuable references for further research on GATA-mediated secondary metabolism regulation in plants. A GATA Transcription Factor Modulates Melatonin Production and Drought Resistance in Hypericum perforatum Shuai Zhou 1, Liu Yang 1, Siru Chen 1, Xue Wang 1, Yi Qiang 1, Jianke Yang 2, Wen Zhou 1, * 1 Key Laboratory of the Ministry of Education for Medicinal Resources and Natural Pharmaceutical Chemistry, National Engineering Laboratory for Resource Development of Endangered Chinese Crude Drugs in Northwest China, College of Life Sciences, Shaanxi Normal University, Xi’an, Shaanxi 710119, China 2 School of Basic Medical Sciences, Wannan Medical College, Wuhu 241002, China * Correspondence: Wen Zhou, [email protected] Work telephone number: +86-29-85310260 Work fax number: +86-29-85310260

Melatonin, a key bioactive compound in Hypericum perforatum, is synthesized through a cascade of enzymatic reactions catalyzed by serotonin N -acetyltransferase (SNAT) and N -acetylserotonin O -methyltransferase (ASMT). Although its biosynthetic pathway has been elucidated, the regulatory mechanisms controlling melatonin production remain poorly understood. This study investigates the potential role of GATA transcription factors in melatonin biosynthesis, given their critical regulatory functions in various plant physiological processes. We focused on characterizing the functional role of HpGATA7 in H. perforatum . Bioinformatics analyses predicted the physicochemical properties, subcellular localization, and phylogenetic relationships of HpGATA7. Yeast one-hybrid assays, luciferase reporter analyses, and subcellular localization experiments demonstrated that HpGATA7 possesses strong transcriptional activation activity and is localized in the nucleus. Expression profiling revealed that HpGATA7 exhibits significantly higher transcript levels in floral organs and is markedly induced under various abiotic stress conditions. Molecular interaction assays further confirmed that HpGATA7 directly binds to the HpSNAT1 promoter and activates its transcription. Functional validation through genetic transformation showed that HpGATA7 overexpression significantly increased melatonin levels, whereas RNA interference (RNAi)-mediated silencing reduced melatonin content in transgenic H. perforatum . Under drought stress, overexpression lines exhibited enhanced antioxidant enzyme activity, mitigating oxidative damage. In summary, this study identifies HpGATA7 as a positive regulator of melatonin biosynthesis in H. perforatum by directly activating HpSNAT1 expression. These findings provide novel insights into the transcriptional regulation of plant melatonin synthesis and antioxidant mechanisms, offering valuable references for further research on GATA-mediated secondary metabolism regulation in plants.

Hypericum perforatum ; GATA transcription factor; Melatonin biosynthesis; Abiotic stress response Itroduction Hypericum perforatum L ., commonly known as St. John’s Wort, is a perennial herbaceous plant belonging to the genus Hypericum in the family Clusiaceae. As an internationally recognized medicinal plant for treating depression, its use dates back to ancient Greece(Zhou et al., 2024). In recent years, with the growing global application of natural medicines and botanical health products, H. perforatum has demonstrated substantial market demand and development potential as a natural antidepressant herb. An increasing number of individuals are opting for herbal supplements, notably those derived from H. perforatum, to support emotional well-being (Xiao et al., 2023; Zhou et al., 2022). Its low adverse reaction rates and common use as an over-the-counter dietary supplement in the U.S. and Europe have made it a focus of global research.(Linde, Berner, & Kriston, 2008) Melatonin, a core active constituent of H. perforatum, is present at concentrations of 1–4 μg per gram of dry weight.(Murch & Saxena, 2006) As a light-regulated bioactive indole compound, melatonin acts as a plant growth regulator and antioxidant.(Arnao & Hernández-Ruiz, 2019) It not only acts synergistically with hyperforin in alleviating depressive symptoms but also serves as a critical agent in the management of insomnia. In 2021, melatonin was officially included in China’s Health Food Raw Material Directory, which has subsequently driven market expansion at an average annual growth rate of 10%(Arnao et al., 2023). However, its conventional chemical synthesis relies on highly toxic reagents such as cyanides, leading to concerns over heavy metal residues and persistent ecological contamination, thereby posing significant health risks (Williamson, Tomlinson, Mishra, Gleich, & Naylor, 1998; Williamson, Tomlinson, Naylor, & Gleich, 1997). In contrast, plant-based systems offer a promising platform for synthetic biology. They harness photosynthetic carbon fixation for the production of desired compounds while inherently accumulating additional bioactive metabolites beneficial to human health. Furthermore, plant-based production demonstrates advantages such as a reduced ecological footprint and lower manufacturing costs (Arnao & Hernández-Ruiz, 2018; Burnett & Burnett, 2019; Golubova, Tansley, Su, & Patron, 2024). Our team has completed a whole-genome analysis of the melatonin biosynthesis pathway in H. perforatum .(Zhou, Wang, et al., 2021) However, the regulation of melatonin biosynthesis, particularly by upstream transcription factors, remains underexplored. Investigating transcription factors involved in melatonin biosynthesis is therefore of significant importance. Melatonin is synthesized from serotonin through two enzymatic reactions catalyzed by 5-hydroxytryptamine N-acetyltransferase (SNAT) and 5-hydroxytryptamine O-methyltransferase (ASMT), which add acetyl and methyl groups, respectively, to serotonin.(Yolcu, Fidan, Kaya, Aksoy, & Turkan, 2025) While extensive research has been conducted on downstream metabolic pathways, knowledge about upstream regulatory factors remains scarce. In this study, we characterized the transcription factor HpGATA7, which was initially identified through yeast one-hybrid screening. By integrating genomic and transcriptomic data from Hypericum perforatum, we first constructed a phylogenetic tree of the GATA gene family and systematically analyzed the molecular characteristics of HpGATA7, including its evolutionary relationships, tissue-specific expression patterns, transcriptional activation activity, and nuclear localization properties. Further investigation revealed that HpGATA7 specifically regulates the expression of the key melatonin biosynthesis genes HpSNAT1 . Functional analyses demonstrated that HpGATA7 significantly enhances plant drought tolerance by promoting melatonin biosynthesis. The GATA protein was identified due to its strong induction by light and nitrate, containing a type IV zinc finger domain (C-X2-C-X17-20-C-X2-C), which binds to the W-G-A-T-A-R region of DNA sequences.(Reyes, Muro-Pastor, & Florencio, 2004) In 1988, Evans et al. first demonstrated that the (T/A)GATA(A/G) sequence was located in the promoter of the chicken globin gene, confirming this transcription factor’s role in hematopoietic processes.(Evans, Reitman, & Felsenfeld, 1988) Subsequently, multiple GATA proteins, including GATA1 to GATA6, were identified. In 1993, the GATA transcription factor was first discovered in tobacco (Nicotiana tabacum) and named NTL1, indicating its involvement in nitrogen metabolism. (Daniel-Vedele & Caboche, 1993)This finding established that GATA genes are present not only in higher animals but also in plants. To date, GATA family members have been identified at the genome-wide level in various plants, including Arabidopsis thaliana, Oryza sativa (rice), Malus domestica (apple), and Solanum lycopersicum (tomato).(Feng, Yu, Zeng, He, & Liu, 2022) The GATA gene family in Arabidopsis comprises 30 genes, categorized into four subfamilies, each playing critical roles in diverse biological processes.(M. Kim, Xi, & Park, 2021) For example, AtGATA25 encodes conserved cysteine residues (C-X2-C-X20-C-X2-C) within the zinc finger domain and a CCT domain, accelerating flowering under prolonged sunlight when overexpressed.(K. Kim, Shin, Kang, Kim, & Kim, 2023) AtGATA2 integrates light and brassinolide signaling pathways, regulating brassinolide-mediated growth.(Luo et al., 2010) In rice, OsGATA1 interacts with auxin signaling pathway genes, promoting root development. Meanwhile, OsGATA2, OsGATA10, and OsGATA16 function as dual regulators, inhibiting or promoting plant growth depending on the context.(Gupta, Nutan, Singla-Pareek, & Pareek, 2017; Lim et al., 2024) In contrast, the animal and microbial genomes harbor fewer GATA family members; for instance, only six GATA proteins have been identified in humans, primarily regulating cardiovascular and nervous system embryonic differentiation.(Lentjes et al., 2016; Stefanovic & Christoffels, 2015)With advancements in structural and functional research,(Hwarari, Radani, Guan, Chen, & Liming, 2023; M. Kim, 2024) angiosperm GATA proteins have been categorized into four groups (A-D) based on their zinc finger domain variations. Class A GATA proteins are the most extensively studied, as they regulate photomorphogenesis and influence root development and differentiation.(Manzoor et al., 2021) Class B GATA proteins are subdivided into HAN and LLM domains, both affecting plant branching and flowering when overexpressed independently.(Ranftl, Bastakis, Klermund, & Schwechheimer, 2016)Research on Class C GATA proteins remains limited, but available data suggest functional similarities to Class A.(Xia et al., 2025) Class D GATA proteins, the smallest group, are the least understood. To date, most research on GATA proteins has focused on model plants, leaving their roles in other species largely unexplored.(Schwechheimer, Schröder, & Blaby-Haas, 2022)

2.1 Identification and sequence analysis The hidden Markov model (HMM) of the GATA protein domain (PF00320) was obtained from the Pfam database (http://pfam.xfam.org/) as a reference sequence. HMMER 3.0 software was used to search the entire genome database of H. perforatum, with the E-value threshold set to 1e-10 to identify candidate sequences. Additionally, the integrity of conserved domains in the candidate sequences was assessed using the online tools SMART and NCBI-CDD (https://www.ncbi.nlm.nih.gov/cdd/). Amino acid sequences containing complete GATA domains were then selected. From the TAIR database (https://www.arabidopsis.org/), 42 amino acid sequences belonging to the GATA gene family in Arabidopsis thaliana were retrieved. The physicochemical properties of candidate proteins in the GATA gene family of H. perforatum, including molecular weight, amino acid number, and isoelectric point, were analyzed using the ProtParam tool (https://web.expasy.org/protparam/) in the ExPASy online software suite. Subcellular localization predictions were performed using WoLF PSORT online software (https://wolfpsort.hgc.jp/). 2.2 Phylogenetic analysis The amino acid sequences of GATA gene family members in mulberry and Arabidopsis were aligned using the multiple sequence alignment function of Clustal W software. Subsequently, a phylogenetic tree was constructed using the neighbor-joining method in MEGA 7 software, with the Bootstrap value set at 1000. Gene structure analysis for GATA gene family members in H. perforatum was performed using TBtools (https://github.com/CJ-Chen/TBtools) and GSDS (http://gsds.gao-lab.org/). The conserved protein motifs of GATA gene family members in H. perforatum were analyzed with the online tool MEME (http://meme-suite.org/tools/meme), with the number of motifs set to six. 2.3 Plant materials and growth conditions Wild-type diploid H. perforatum seeds preserved in our laboratory were sterilized with a 12% chlorox solution and transferred to Murashige and Skoog (MS) agar medium (Solarbio, Beijing, China). The seeds were incubated at 4°C in darkness for 3 days and subsequently placed in a growth chamber maintained at 23°C with 60% relative humidity under cool white LED light at a light intensity of 108 μmol m⁻²s⁻¹. The seedlings were grown under a 12 h light/12 h dark cycle (12L/12D). After two months, some seedlings were subjected to stress treatments to investigate gene expression levels, while others had their roots used as explants for Agrobacterium-mediated transformation to generate transgenic H. perforatum lines. Seedlings were treated with 200 mM NaCl for salinity stress and 20% PEG (PEG6000) solution for drought stress. For cold stress, the cultured plantlets were maintained at 4 °C. 2.4 Gene cloning and vector construction Genomic DNA and RNA were isolated with the Plant RNA/DNA Kit (Vazyme, China), and cDNA was generated using the SuperScript™ IV First-Strand cDNA Synthesis Kit (Invitrogen, Shanghai, China). CDS for H. perforatum Scaf 434.29 ( HpGATA7 ) and the promoter of Scaf 151.204 ( proHpSNAT1 ) and Scaf 447.395 ( proHpASMT3 ) were amplified by PCR using the gene-specific primers (Table S1). To generate overexpression and RNAi constructs for HpGATA7, the 1,014 bp coding sequence and a 296 bp fragment of HpGATA7 were inserted into the vectors pK7WG2D,1 and pK7GWIWG2D(Ⅱ), respectively. The mentioned vectors were introduced into Agrobacterium rhizogenes strain K599 (Weidi, Shanghai, China) and then used to infect H. perforatum roots. The coding sequence of HpGATA7 cloned into pGBKT7 was used as the prey vector. A 1,522 bp proHpSNAT1 and 1,500 bp proHpASMT3 cloned into pHIS2 was used as the bait vector. For subcellular localization analysis, the CDS of HpGATA7 was inserted into the pEarlyGate103 vector, leading to the creation of a 35S::HpGATA7-GFP construct. For transcriptional activation, the CDS of HpGATA7 was inserted into the pGBKT7 vector. The resulting pGBKT7- HpGATA7, along with pGBKT7-VP16 (positive control) and the empty pGBKT7 vector (negative control), was separately transformed into AH109 yeast-competent cells (Weidi, Shanghai, China). For self-activation validation and yeast-one-hybrid assay, CDS of HpGATA7 was cloned into pGADT7 and the promoter fragments were cloned into pHIS2 vector. For luciferase assay, the CDS of HpGATA7 were cloned into pGreenII62-SK and the promoter fragments cloned into pGreenII0800-LUC vector. To generate overexpression and RNAi constructs for HpGATA7, the coding sequence and a 325bp fragment of HpGATA7 were inserted into the vectors pEarleyGate202 and pHELLSGATE12, respectively. 2.5 qRT-PCR analysis GenScript (https://www.genscript.com/) was used to design the quantitative primers (Table S1). The qRT-PCR experiment involves detailed instructions, reaction systems, and calculation methods, as described previously. The relative expression levels of the genes were determined using the 2−ΔΔCt method, with HpACT2 (GenBank: MK054303) serving as the internal control, as previously described.(Zhou et al., 2019) 2.6 Subcellular localization The coding sequence of HpGATA7 was cloned into pEarlyGate103 vector with a fluorescent tag (GFP) to produce a fusion protein. The recombinant plasmid was transformed into A. tumefaciens (GV3101). After harvesting, the bacterial cells were resuspended in an infiltration buffer (10 mM MgCl₂, 10 mM MES, and 100 μM acetosyringone) to an OD600 of 1.5. The suspension was injected into the abaxial side of leaves from 5-week-old Nicotiana benthamiana plants using a needleless syringe. The plants were kept in darkness for 24 h and then grown under normal conditions (16 h light/8 h dark) for an additional two days. Fluorescence signals were observed using a Nikon C2-ER laser confocal microscope to determine subcellular localization, with the empty vector used as a control. 2.7 Transcriptional activation The transformants were cultured on SD/-Trp (SD-T) and SD/-Trp/-Ade/-His/X-α-gal (SD-TAH+X-α-gal) selective media. The transcriptional activity of HpGATA7 was assessed based on growth performance after three days of incubation at 28 °C in the dark. Positive activity is indicated by colony growth on selective media or color development on X-α-gal plates. 2.8 Self-activation validation Before performing the yeast one-hybrid (Y1H) assay, the self-activation potential of the promoter and the appropriate concentration of 3-amino-1,2,4-triazole (3-AT) must be determined. The pHIS2- proHpSNAT1 / proHpASMT3 recombinant was transformed into Y187 yeast-competent cells (Weidi, Shanghai, China). Single colonies were picked from the transformation plates, diluted, and streaked onto corresponding selective plates lacking histidine (-His) but containing different concentrations of 3-AT (0, 10, 20, 30, 100, 160, and 220 mM). The plates were incubated at a constant temperature of 30°C for 3 days. The growth of yeast colonies is observed to evaluate the self-activation level of the promoter. The lowest 3-AT concentration that effectively suppresses self-activation without affecting genuine signal detection is identified. 2.9 Yeast one-hybrid assay The Y1H assay was conducted to identify HpGATA7- proHpSNAT1 / proHpASMT3 interactions. The DNA sequence of proHpSNAT1 / proHpASMT3 was cloned upstream of a reporter gene (HIS3) to create a reporter strain (pHIS2- proHpSNAT1 / proHpASMT3 ). The CDS sequence of HpGATA7 was cloned into pGBKT7 was fused to a GAL4 activation domain (AD) in a prey vector. The recombinant vectors pGADT7- HpGATA7, and the pHIS2- proHpSNAT1 / proHpASMT3 were transferred into the Y187 yeast-competent cells (Weidi, Shanghai, China), respectively. Moreover, three replicates of the GATA motif within HpSNAT1 promoter was individually integrated into the pHIS2. The transformants were grown on SD/-Trp/-Leu and SD/-His/-Trp/-Leu deficiency media. Then, the transcriptional activities were tested according to their growth status at 28 ℃ for three days in darkness. The surviving colonies were then transferred to SD-TLH containing 3AT to observe the interaction between HpGATA7 protein and the elements in promoters. 2.10 Luciferase assay The LUC assay was performed using transient expression in Nicotiana benthamiana. Plasmids containing the target promoter fused to the firefly luciferase reporter gene and an internal control plasmid (pGreenII 0800-LUC) were transformed into Agrobacterium tumefaciens (GV3101). A single colony was cultured in LB medium (10 g/L tryptone, 5 g/L yeast extract, and 10 g/L NaCl) at 28°C to an OD600 of 1.5. The bacterial culture was pelleted by centrifugation and resuspended in an infiltration buffer (10 mM MgCl₂, 10 mM MES, 100 μM acetosyringone) to an OD600 of 1.0. The bacterial suspension was infiltrated into fully expanded leaves of 5-week-old N. benthamiana plants using a needleless syringe. The plants were kept in the dark for 24 h and then transferred to normal growth conditions (16 h light/8 h dark) for 48 h. The leaves were treated with 0.1 M luciferase substrate (Chemstan, Wuhan, China) and incubated in the dark for 10 minutes to allow complete luciferase reaction. Luciferase activity was captured using a CCD camera (Spectral, Colorado, USA). Leaf tissue from the infiltration sites was harvested 48 h post-inoculation, homogenized in lysis buffer, and centrifuged to collect the supernatant. Firefly luciferase and internal control activities was measured using the One-Lumi assay kit (Beyotime, Shanghai, China). 2.11 Agrobacterium-mediated transformation The correctly inserted pEarleyGate202- HpGATA7 and pHellsgate12- HpGATA7 plasmids were transformed into Agrobacterium rhizogenes strain K599 (Weidi, Shanghai, China). Taproots from 4-6-month-old aseptic H. perforatum seedlings served as explants for inducing hairy roots. The resulting positive hairy root lines were utilized for the induction of both buds and roots. The specific steps can be referenced from the study by Zhou et al.(Zhou, Yang, et al., 2021) The positive lines were identified using specific primers (Table S1). 2.12 Extraction and detection of melatonin After three months of cultivation from hairy roots, the aboveground parts of H. perforatum seedlings from EV, OE, and RNAi lines were harvested, flash-frozen in liquid nitrogen, and dried using a vacuum freeze dryer (labCAN, Jiangsu, China) until a constant weight was achieved. Following this, 150 mg of each sample was extracted with 500 µL of 70% methanol and subjected to 40 minutes of sonication. The supernatant was then filtered through a 0.22 μm filter (Millipore, USA) and collected for further analysis. High-performance liquid chromatography (HPLC, Agilent 1260 Infinity II, USA) coupled with liquid chromatography-mass spectrometry (LC-MS, Agilent 6460, USA) was used for subsequent analyses. 2.13 Drought treatment and physiological measurement Three-month-old WT, OE, and RNAi lines were cultured in liquid medium containing 1/2 MS + 20 g L⁻¹ sucrose + 250 mmol/L D-mannitol for drought simulation, with the same medium containing 0 mM D-mannitol serving as the control. After one week of culture, physiological indices and photosynthetic parameters were measured, with each treatment comprising at least three biological replicates. Malondialdehyde (MDA) and H₂O₂ concentrations, as well as superoxide dismutase (SOD) and catalase (CAT) activities, were determined using the Plant Micro Assay Kit (Solarbio, Beijing, China). The Fv/Fm values of different lines were measured using the PlantView230F photosynthesis fluorescence imaging system (BLT, Guangzhou, China). 2.14 Statistics All experiments were conducted with three biological and three technical replicates unless stated otherwise. Results are presented as means ± standard error of the mean, and statistical analyses were performed using GraphPad Prism 8.0.2.

3.1 Identification and phylogenetic analysis The GATA domain HMM (PF00320) was used to search the H. perforatum genome database, identifying 33 HpGATA genes, designated HpGATA1 to HpGATA33 . Pfam and SMART analyses confirmed that these proteins contained complete GATA domains. The basic physicochemical properties are summarized in Table S2. The HpGATA gene lengths ranged from 535 bp ( HpGATA16 ) to 3,847 bp ( HpGATA26 ), while the cDNA and protein lengths varied from 381 bp and 127 amino acids ( HpGATA15 and HpGATA16 ) to 1,596 bp and 532 amino acids ( HpGATA26 ). The predicted molecular weights (MW) of the proteins ranged from 14.2 kDa ( HpGATA15 and HpGATA16 ) to 58.5 kDa ( HpGATA26 ), with isoelectric points (pI) spanning 4.75 ( HpGATA4 ) to 10.22 ( HpGATA14 ). Subcellular localization predictions indicated that, except for HpGATA, which was expressed in both the nucleus and cytoplasm, all other HpGATA proteins were exclusively located in the nucleus. To investigate the evolutionary relationships among HpGATA family members, we performed a phylogenetic analysis of 33 HpGATA and 42 AtGATA genes based on variations in their zinc finger domains. The resulting phylogenetic tree and multiple sequence alignment (Figure 1 and Figure S1) revealed that AT4G36240.1 ( AtGATA7 ) exhibited the highest sequence homology with HpGATA7 . These findings suggest that HpGATA7 may share functional similarities with AtGATA7, potentially playing a role in light-responsive mechanisms. 3.2 Subcellular localization and transcriptional activity of HpGATA7 Confocal microscopy analysis demonstrated that HpGATA7 exhibits predominant nuclear localization (Figure 2A), consistent with bioinformatic predictions of its subcellular targeting. This spatial partitioning suggests potential nucleocytoplasmic shuttling of HpGATA7, possibly mediated through protein-protein interactions or post-translational modifications that regulate its cellular trafficking and function (Bottardi et al., 2013).To characterize the transcriptional regulatory potential of HpGATA7, we performed yeast one-hybrid (Y1H) assays. The pGBKT7- HpGATA7 transformants exhibited robust β-galactosidase activity, as evidenced by distinct blue colony formation on SD/-Trp/-Ade/-His medium supplemented with X-α-Gal (Figure 2B). The transcriptional activation capability, comparable to positive controls, confirms HpGATA7 functions as a bona fide transcription factor. 3.3 Expression analysis of HpGATA7 Tissue-specific profiling by qRT-PCR demonstrated ubiquitous expression of HpGATA7 across all examined organs (Figure 2C). Notably, floral tissues exhibited the highest transcript abundance (approximately 4-fold greater than leaves), while leaf expression was comparatively reduced. Stem and root tissues showed intermediate expression levels. Expression analysis of HpGATA7 in two-month-old H. perforatum seedlings grown under 12-h light/12-h dark (12L/12D) conditions revealed significant light-dependent regulation (Figure 2D). While nocturnal expression levels remained stable, we observed a rapid induction of HpGATA7 transcription at ZT1 (1 h after light onset), suggesting photoresponsive control of gene expression. Stress response experiments revealed significant upregulation of HpGATA7 under various abiotic challenges (Figure 2E-3H). NaCl treatment induced the strongest transcriptional response (3.2-fold increase versus control), followed by drought (2.1-fold) and cold stress (1.8-fold). MeJA elicitation produced the most modest induction (1.5-fold), indicating differential regulatory mechanisms under distinct stress conditions. 3.4 HpGATA7 directly binds the promoter of HpSNAT1 As shown in Figure 3A and 3B, the self-activation potential of the HpSNAT1 and HpASMT3 promoters was assessed. The positive control group, pHIS2-p53 + pGAD53m, exhibited normal growth on plates supplemented with the HIS3 inhibitor 3-AT, indicating successful activation of the HIS3 reporter gene. In contrast, transformants harboring proHpSNAT1 and proHpASMT3 showed no colony growth on plates containing 20 mM and 220 mM 3-AT, respectively, suggesting that these promoters did not autonomously activate the HIS3 reporter gene. Based on these results, yeast one-hybrid screening was subsequently conducted using 20 mM and 220 mM 3-AT for proHpSNAT1 and proHpASMT3, respectively. The Y1H assay results indicated that HpGATA7 did not interact with the HpASMT3 promoter (Figure 4A). However, HpGATA7 was able to bind the HpSNAT1 (-542~ -529) promoter through the GATA motif (ACAAAGATAGACCT) (Figure 4B). To further validate whether HpGATA7 regulates HpSNAT1, a luciferase complementation assay was conducted. A reporter gene construct with a proHpSNAT1 -driven LUC plasmid was constructed and used CaMV-35S promoter-driven GFP or HpGATA7-GFP plasmids as effectors, with pGreenII 0800-LUC and pGreenII62-SK empty vectors as negative controls. As shown in Figure 4C and 4D, the luciferase activity in tobacco co-transformed with pGREEN II-62SK and the proHpSNAT1 -driven LUC reporter gene was higher than in other groups, indicating that the HpSNAT1 promoter has strong self-activation activity. The luciferase activity was highest in the HpGATA7-GFP effector and the proHpSNAT1 -driven LUC reporter region, suggesting that HpGATA7 positively regulates the expression of HpSNAT1 . These results demonstrate HpGATA7 transcription is subject to significant light-dependent regulation under 12L/12D photoperiod conditions, peaking at ZT1. Through GATA motif targeting, HpGATA7 positively regulates the melatonin synthase gene HpSNAT1, thereby enhancing melatonin biosynthesis (Figure 4E). 3.5 Generation of HpGATA7 transgenic lines HpGATA7 overexpression and silencing were achieved in wild-type H. perforatum . Following DNA extraction from various transgenic lines, PCR amplification was performed. The resulting amplicons were visualized via agarose gel electrophoresis. The overexpression lines were identified as depicted in Figure S2A, with O1, O2, O5, O7, O8, O11, O13, and O15 demonstrating positive results among the 15 overexpression lines. Silencing lines were identified as depicted in Figure S2B, with R1, R3, R4, R5, R8, and R10 exhibiting positive results among the 10 silencing lines. The positive lines were subsequently labeled and maintained for subsequent experimental assays. Following callus induction of the H. perforatum overexpression and silencing lines, mature H. perforatum overexpression (OE) and silencing (RNAi) plants were successfully generated. RNAi plants are comparatively dwarf relative to the wild type (WT), while the OE lines exhibit increased stature compared to the WT and RNAi lines (Figure 5A). 3.6 qRT-PCR and melatonin content analyses To comprehensively elucidate the transcriptional regulation of HpGATA7 in H. perforatum, qRT-PCR analysis was performed on HpGATA7 overexpression lines (O1, O2, O5, O7, O8, O11, O13, O15) and RNAi lines (R1, R3, R4, R5, R8, R10), alongside control lines (WT, EV). Based on the qRT-PCR analysis, three independent overexpression lines with higher HpGATA7 expression (O2, O8, O15) and three independent RNAi lines with lower expression (R1, R5, and R10) were selected for further investigation (Figure 5B and 5D). Subsequent qRT-PCR analysis revealed that the expression of HpSNAT1 was significantly higher in the three independent overexpression lines compared to the wild-type and empty vector controls, while the expression of HpASMT3 did not significantly differ compared to the control group (Figure 5C). In the three independent RNAi lines, the expression of HpSNAT1 was significantly lower than that of the control group, whereas the expression of HpASMT3 did not significantly differ compared to the control group (Figure 5E). These results further validate that HpGATA7 can regulate the expression of HpSNAT1 . Subsequently, the melatonin content in the six transgenic HpGATA7 lines was determined using high-performance liquid chromatography-mass spectrometry (Figure 5F). Compared with the WT and Agrobacterium-empty vector control (EV) lines, melatonin accumulation was significantly increased in the OE lines. Conversely, the melatonin content in the RNAi transgenic lines showed a significant decrease compared to the EV and WT lines. These results indicate that HpGATA7 plays a positive role in promoting melatonin synthesis in H. perforatum . 3.7 HpGATA7 improves plant drought resistance As shown in Figure 6A, no significant differences in growth morphology were observed among the three lines under normal conditions. However, under drought stress induction, both WT and RNAi lines exhibited obvious wilting symptoms, whereas the OE line maintained normal growth with minimal leaf curling. As illustrated in Figure 6B-6E, under normal growth conditions, there were no significant differences in MDA and H₂O₂ content among the three lines, except for a slightly higher MDA level in the RNAi line. Under drought stress, the OE line showed significantly lower MDA and H₂O₂ accumulation compared to RNAi and WT, while its CAT and SOD activities were markedly higher than those of the RNAi line. The maximum photochemical efficiency of PSII (Fv/Fm) was measured. Under normal conditions, the Fv/Fm values of WT and OE seedlings were approximately 0.9, while that of the RNAi line was around 0.8. After mannitol treatment, no significant change in Fv/Fm was detected in the OE line. In contrast, chlorophyll fluorescence imaging revealed that the RNAi line displayed extensive green fluorescence, and its Fv/Fm value (0.6) was significantly lower than that of WT (0.7) (Figure 6F and 6G). In brief, drought treatment reduced Fv/Fm levels in both WT and RNAi lines, with a more pronounced decrease in the RNAi line. These results suggest that HpGATA7 positively regulates plant drought tolerance. 4.Discussion H.perforatum, a widely utilized nutritional supplement in North America and Europe, is also clinically employed in countries like Germany for treating mild to moderate depression.(Linde et al., 2008; Szegedi, Kohnen, Dienel, & Kieser, 2005) Currently, Hypericum is approved in the Chinese Pharmacopoeia for use as an antidepressant, either alone or in combination with other herbal preparations, highlighting its significant medicinal value.(Szegedi et al., 2005) Murch et al. identified Hypericum as having the highest melatonin content among various plants.(Murch & Saxena, 2006) Melatonin, a crucial multifunctional signaling molecule in plants, is involved in inducing various important physiological responses to adverse environmental conditions.(Zeng, Mostafa, Lu, & Jin, 2022; Zhan et al., 2019) Research has shown that melatonin acts as an anti-stress agent against abiotic stressors such as drought, salinity, low and high temperatures, ultraviolet radiation, and toxic chemicals, and participates in regulating plant development through processes like growth, rhizogenesis, and photosynthesis, indicating its promising application in crop improvement.(Hassan et al., 2022; Khan, Hussain, Yun, & Mun, 2024; Sun et al., 2021) Genes involved in melatonin biosynthesis have been identified in several plants, and the synthesis pathway in Hypericum has been elucidated.(Back, Tan, & Reiter, 2016) However, the expression of upstream regulatory transcription factors in plants remains unclear, placing the molecular regulatory mechanisms of melatonin in their early stages. Transcription factors serve as regulators of many critical biological processes during plant growth and development.(Schwechheimer et al., 2022; Spitz & Furlong, 2012) They can regulate abiotic stress responses and plant growth and development by modulating plant hormone signaling pathways and can also promote or inhibit the expression of downstream genes by binding to motifs in the promoters of target genes.(Thilakarathne, Liu, & Zou, 2025) Transcription factors not only interact with other transcription factor families but also recruit proteins and form complexes to activate specific gene expression by recognizing and binding to motifs in their target genes, thereby regulating plant defense responses to abiotic stress.(Chen, Zhang, Wang, Zhao, & Guo, 2025; Kumari, Ojha, Varshney, Gupta, & Salvi, 2024; Pan et al., 2024; Schwechheimer et al., 2022) Previously, our research group constructed a cDNA library from Hypericum . Employing proHpSNAT1 as bait, we utilized yeast one-hybrid (Y1H) technology to screen for upstream regulatory proteins. The results revealed that HpSNAT1 is regulated by multiple transcription factors, which may participate in melatonin synthesis. Ultimately, we identified 12 transcription factors with regulatory relationships with HpSNAT1 .(Zhou et al., 2024) These included GATA-binding proteins, which are evolutionarily conserved transcription factors found in animals, fungi, and plants.(Hu, Zhao, Lin, & Jiang, 2025) GATA factors play crucial roles in plant growth, development, and response to abiotic stresses.(Abdulla, Mostafa, Aydin, Kavas, & Aksoy, 2024; Zhao et al., 2025) Individual family members are associated with photomorphogenesis, chlorophyll biosynthesis, chloroplast development, photosynthesis, stomatal formation, and the regulation of root, leaf, and flower development.(Schwechheimer et al., 2022) Ming et al. elucidated the mechanism by which the photoresponsive transcription factor VvGATA24 acts as a terpene biosynthesis activator, promoting light-mediated biosynthesis of terpenoids.(Yang et al., 2024) Yingying Shao et al. found that UrGATA7 and UrGATA8, in response to altered light treatments, share similar expression profiles with key TIA gene enzymes, participating in the regulation of terpene indole alkaloid (TIA) content.(Shao et al., 2024) Yanyan Wang et al. discovered that GATA genes may play a significant role in regulating fruit anthocyanin biosynthesis by integrating light signaling pathways.(Wang et al., 2024) These analyses indicate that GATA genes can be regulated by light and can influence the content of secondary metabolites in plants by regulating other genes. Therefore, further investigation into the molecular mechanisms of HpGATA7 in Hypericum will provide a clearer understanding of how transcription factors regulate the content of their own secondary metabolites under the influence of physical factors and enrich the upstream regulatory mechanisms of transcription factors. In summary, our phylogenetic analysis and diurnal expression profiling revealed that HpGATA7 shares structural and functional similarities with the A-class members of the GATA family, demonstrating photoresponsive control. Its expression was upregulated upon increased light exposure, providing critical insights for subsequent functional characterization of HpGATA7 . Background screening identified self-activation in both HpSNAT1 and HpASMT3, with HpASMT3 potentially exhibiting greater activity, which warrants further experimental validation. Yeast one-hybrid assays indicated that the HpGATA7 protein does not interact with HpASMT3, suggesting no direct regulatory role. Conversely, HpGATA7 protein interacted with HpSNAT1, indicating its regulatory influence on HpSNAT1 in H. perforatum . qRT-PCR analysis of transgenic lines and melatonin content measurements further suggest that the HpGATA7 protein may indirectly affect melatonin synthesis in H. perforatum by regulating HpSNAT1 expression. Drought-induced damage in plants primarily results from the accumulation of oxidative stress. The effective scavenging of reactive oxygen species (ROS) and reduction of oxidative damage represent crucial mechanisms for enhancing plant tolerance to abiotic stress. As a potent antioxidant molecule, melatonin confers significant drought protection by markedly alleviating oxidative stress. In this study, overexpression of the HpGATA7 gene in H. perforatum resulted in OE plants exhibiting approximately twice the melatonin content of WT and RNAi lines. Phenotypic analysis revealed that OE lines displayed significantly enhanced drought tolerance compared to controls. These findings confirm that the improved drought resistance in transgenic plants is directly associated with the reinforced antioxidant capacity conferred by melatonin. These findings establish a foundation for further investigation into the regulatory mechanisms of HpGATA7 protein in melatonin biosynthesis, while also providing novel insights into the upstream regulatory network of melatonin synthesis. Graphical abstract Figure 1. Isolation and characterization of HpGATA. (A) Phylogenetic analysis of HpGATA and Arabidopsis GATA. (B) Multiple sequence alignment of the HpGATA7 and AtGATA proteins. Figure 2. Subcellular localization, transcriptional activity and expression analysis of HpGATA7. (A) HpGATA7 subcellular localization analysis. The pEarlyGate103 empty vector was the negative control. (B) Y1H assays verified the transcriptional activity of HpGATA7. (C) Tissue-specific expression analysis of HpGATA7 . (D) 12-h light/12-h dark (12L/12D) conditions expression analysis of HpGATA7 . (E) MeJA treatment expression analysis of HpGATA 7. (F) 4℃ treatment expression analysis of HpGATA7. (G) Drought treatment expression analysis of HpGATA7 . (H) NaCl treatment expression analysis of HpGATA7 . Different letters indicate signiffcant differences (P < 0.05) between each group according one-way ANOVA. Figure 3. Self-activation potential verification of the HpSNAT1 and HpASMT3 promoter. Figure 4. Y1H and LUC assays revealed HpGATA7 binds to the HpSNAT1 promoter. (A) Yeast one-hybrid assays showing the no interaction of HpGATA7 with the promoter of HpASMT3 . (B) Yeast one-hybrid assays showing the interaction of HpGATA7 with the promoter of HpSNAT1 through GATA Motif. (C and D)Transient dual-luciferase assays in N. benthamiana leaves showed that HpGATA7 enhanced the expression of HpSNAT1 . Data are presented as the means ± SD (n=3). (E) A working model of HpGATA7 regulating melatonin biosynthesis. HpGATA7 exhibits high expression under light conditions and low expression in darkness, functioning independently of HpASMT3. It co-regulates melatonin biosynthesis by binding to the GATA motif in the HpSNAT1 promoter alongside HpASMT3. Melatonin levels increase proportionally with the expression of HPGATA7 . Different letters indicate significant differences (P < 0.05) between each group tested by one-way ANOVA. Figure 5. Expression analysis of HpGATA7 transgenic lines and melatonin content analyses. Phenotype of WT, RNAi, and OE transgenic lines of H. perforatum, bar = 1 cm. (B) The HpGATA7 expression levels in WT, EV and OE transgenic lines analyzed by qRT-PCR. Data were normalized to HpACT2 and presented as the means ± SD (n=3). (C) The HpSNAT1 and HpASMT3 expression levels in WT, EV, and OE transgenic lines analyzed by qRT-PCR. Data were normalized to HpACT2 and presented as the means ± SD (n=3). (D) The HpGATA7 expression levels in WT,EV, and RNAi transgenic lines analyzed by qRT-PCR. Data were normalized to HpACT2 and presented as the means ± SD (n=3). (E) The HpSNAT1 and HpASMT3 expression levels in WT,EV, and RNAi transgenic lines analyzed by qRT-PCR. Data were normalized to HpACT2 and presented as the means ± SD (n=3). (F) Melatonin accumulation in WT, EV, OE, and RNAi transgenic lines analyzed by LC-MS. Different letters indicate significant differences (P < 0.05) between each group tested by one-way ANOVA. Figure 6. The effects of HpGATA7 on H. perforatum plants under drought stress. (A)The phenotype of three-month-old WT, OE, and RNAi transgenic plants under normal treatment and drought stress, bar = 1 cm. (B, C) H 2 O 2 and MDA accumulation and (D, E) CAT and SOD activity in WT, OE, and RNAi lines under normal conditions and D-mannitol stress. (F, G) The chlorophyll fluorescence and Fv/Fm value of three-month-old WT, OE, and RNAi transgenic plants under normal treatment and D-mannitol stress. Data are presented as the means ± SD (n=3) Different letters indicate significant differences from the control (P < 0.05) tested by one-way ANOVA. Supplementary material Figure S1 . Phylogenetic analysis and multiple sequence alignment of HpGATA7. Analysis of Grouping and Domain Structure of the 33 HpGATA7 Genes. Figure S2 . Positive identification of genetically modified plant lines. M, DL2000 Marker; N, negative control. Table S1 . All Primers used in this study. (file type, Excel) Table S2 . The sequence feature of 33 HpGATA genes. (file type, Excel) Author contributions: CRediT Shuai Zhou: Writing - Original Draft, Validation, Investigation Liu Yang: Writing - Original Draft,Resources Siru Chen: Investigation, Data Curation Xue Wang: Investigation, Formal analysis Yi Qiang: Conceptualization, Visualization，Funding acquisition Jianke Yang: Methodology, Writing - Review &Editing Wen Zhou: Supervision, Project administration，Writing - Review &Editing Funding Sources This study was supported by grants from the National Natural Science Foundation of China (nos. 32100308); Shaanxi Province Traditional Chinese Medicine Scientific Research and Innovation Team Project (nos.TZKN-CXTD-08). Conflicts of interests The authors declare no competing interests.

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Authors Metrics & Citations Metrics Article Usage 148views 132downloads Citations Download citation Shuai Zhou, Liu Yang, Siru Chen, et al. A GATA Transcription Factor Modulates Melatonin Production and Drought Resistance in Hypericum perforatum. Authorea. 29 September 2025. DOI: https://doi.org/10.22541/au.175913491.12145154/v1 DOI: https://doi.org/10.22541/au.175913491.12145154/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.