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Article

Caffeic Acid O-Methyltransferase Gene Family in Mango (Mangifera indica L.) with Transcriptional Analysis under Biotic and Abiotic Stresses and the Role of MiCOMT1 in Salt Tolerance

1
Key Laboratory of Green Prevention and Control of Tropical Plant Diseases and Pests (Hainan University), Ministry of Education, Key Laboratory of Biotechnology of Salt Tolerant Crops of Hainan Province, Hainan University, Haikou 570228, China
2
National Key Laboratory for Tropica1 Crop Breeding, Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, Chinese Academy of Tropical Agricultural Sciences Environment and Plant Protection Institute, Haikou 571101, China
3
Chinese Academy of Tropical Agricultural Sciences Tropical Crops Genetic Resources Institute, National Key Laboratory for Tropical Crop Breeding, Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Ministry of Agriculture and Rural Affairs, Key Laboratory of Tropical Crops Germplasm Resources Genetic Improvement and Innovation of Hainan Province, Haikou 571101, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Mol. Sci. 2024, 25(5), 2639; https://doi.org/10.3390/ijms25052639
Submission received: 20 January 2024 / Revised: 13 February 2024 / Accepted: 19 February 2024 / Published: 24 February 2024

Abstract

:
Caffeic acid O-methyltransferase (COMT) participates in various physiological activities in plants, such as positive responses to abiotic stresses and the signal transduction of phytohormones. In this study, 18 COMT genes were identified in the chromosome-level reference genome of mango, named MiCOMTs. A phylogenetic tree containing nine groups (I-IX) was constructed based on the amino acid sequences of the 71 COMT proteins from seven species. The phylogenetic tree indicated that the members of the MiCOMTs could be divided into four groups. Quantitative real-time PCR showed that all MiCOMT genes have particularly high expression levels during flowering. The expression levels of MiCOMTs were different under abiotic and biotic stresses, including salt and stimulated drought stresses, ABA and SA treatment, as well as Xanthomonas campestris pv. mangiferaeindicae and Colletotrichum gloeosporioides infection, respectively. Among them, the expression level of MiCOMT1 was significantly up-regulated at 6–72 h after salt and stimulated drought stresses. The results of gene function analysis via the transient overexpression of the MiCOMT1 gene in Nicotiana benthamiana showed that the MiCOMT1 gene can promote the accumulation of ABA and MeJA, and improve the salt tolerance of mango. These results are beneficial to future researchers aiming to understand the biological functions and molecular mechanisms of MiCOMT genes.

1. Introduction

Caffeic acid O-methyltransferase (COMT) is a multifunctional enzyme that catalyzes O-methylation with various substrates [1,2]. Previous studies have shown that the COMT gene family is generally composed of multiple members, such as rapeseed (Brassica napus) (25) [3], catalpa bungei (Catalpa bungei) (23) [4], birch (Betula pendula) (25) [5], blueberry (Vaccinium corymbosum) (92) [6], soybean (Glycine max) (55) [7], and rice (Oryza sativa) (33) [8]. COMT plays a regulatory role in various stress responses in plants, such as salt [9], cold [7], drought [10], and the signal transduction of phytohormones. Bugos and colleagues were the first to clone the COMT gene from poplar (Populus) [11]. At present, the COMT genes of many plants have been studied, such as Arabidopsis (Arabidopsis thaliana) [12] and barley (Hordeum vulgare) [13]. In rice roots, COMT gene expression was down-regulated under salt treatment [8]. Under salt stress, CrCOMT (Carex rigescens-COMT) transgenic Arabidopsis has higher salt-responsive gene transcriptional activity than wild-type samples [14]. TaCOMT (Triticum aestivum-COMT) transgenic Arabidopsis seedlings were treated with different concentrations of mannitol and PEG6000, and their total root length, number of lateral roots, and fresh weight were significantly greater than those of the wild-type sample [15]. The overexpression of SlCOMT in tomato (Solanum lycopersicum) could inhibit the accumulation of H2O2 and improve salt tolerance [16]. It can be seen that COMT consistently improves the salt tolerance of plants, which is mainly due to the significantly increased osmotic regulatory and antioxidant capacity in these transgenic plants under salt stress [17]. However, there is currently no report on the identification and functional analysis of mango COMT genes.
Mango (Mangifera indica L., 2n = 2x = 40) is one of the most important economic tropical fruits in the world [18], and it is grown in more than 100 countries and regions. Mango fruit is highly appreciated for its delicious taste, exotic flavor, and nutritional value [19]. Fruits are important sources of carbohydrates, proteins, fats, energy, vitamins, micronutrients, dietary fiber, phenolic compounds, and other phytochemicals [20]. Mango is mainly cultivated in salinized hilly, mountainous, and coastal areas. Soil salinization is a key obstacle to sustainable mango production [21]. The main symptoms are varying degrees of leaf tip or leaf edge wilt, premature fall of branches and leaves, fewer flowers and fruits, and even the death of the whole plant [22]. In recent years, due to the changes in climate and human factors, the situation regarding global soil salinization has been deteriorating, and more than 800 million hectares of land have been affected by soil salinization [23]. Soil salinization is also one of the main abiotic stress factors in global agricultural production [24]. High concentrations of salt ions in soil will reduce the water potential of soil [25]. Excessive salt ions passively transported into plant cells through ion channels and transpiration will directly damage plant leaf cells [26,27], inhibit nutrient absorption and photosynthesis [28], reduce plant water absorption capacity, and hinder plant growth [29]. In rice, salt stress may stunt growth [30]. In apple (Malus domestica) growing areas, high concentrations of salt ions in soil reduce fruit yield and quality [31]. This is mainly caused by the toxicity of ions and the accumulation of reactive oxygen species (ROS) during salt stress [32], including hydrogen peroxide (H2O2), superoxide anion (O2−), and malondialdehyde (MDA) [33]. Thus, the physiological and biochemical indices of plants may be altered. For example, the contents of water and chlorophyll are decreased, but the content of MDA is increased following salt stress in JUNCAOs (Pennisetum giganteum) [34]. In hyssop (Hyssopus officinalis) plants, phenols and anthocyanins are significantly increased upon salt stress treatment [35]. SA- and MeJA-pretreated sorghum (Sorghum bicolor) plants show substantial decreases in ROS accumulation under salt stress [36,37]. Excess salt leads to an increase in the content of ABA in rice [38]. Therefore, understanding the mechanisms of plant tolerance to salt stress is essential to the growth and development of plants in salinized soils.
In this study, we aimed to explore the molecular characteristics and phylogenetic tree of the COMT gene family in mango. Their differential expression patterns were analyzed in different mango tissues and under different stress treatments. In particular, the function of the MiCOMT1 gene in regulating salt stress tolerance was revealed. The outcomes of this study will provide a fundamental basis for the functional characterization of MiCOMT gene members, especially regarding salt tolerance.

2. Results

2.1. Identification and Phylogenetic Tree Analysis of MiCOMT Gene Family

To understand the evolutionary expansion of the mango COMT gene family, a phylogenetic tree was constructed using MEGA 11 software, based on multiple alignments. We attempted to characterize the phylogenetic relationship among 71 COMT (Table S1) proteins of M. indica (Mi) (18 MiCOMTs), A. thaliana (At) (17 members), Manihot esculenta (Me) (10 members), Nicotiana tabacum (Nt) (8 members), S. lycopersicum (Sl) (5 members), O. sativa (Os) (1 member), and Pyrus bretschneideri (Pb) (12 members), as shown in Figure 1 and Figure S1. According to the phylogenetic tree, 71 COMT proteins could be categorized into nine groups (I-IX). MiCOMT4, MiCOMT7, MiCOMT8, MiCOMT9, MiCOMT10, MiCOMT11, MiCOMT12, MiCOMT14, MiCOMT15, and MiCOMT16 were distributed in group VII, which is equivalent to 55.56% of the total number of MiCOMT proteins. MiCOMT2 and MiCOMT5 were distributed in group VIII. MiCOMT1, MiCOMT3, MiCOMT6, MiCOMT17, and MiCOMT18 were distributed in group IX. Only MiCOMT13 was distributed in group V, which is equivalent to 5.56% of the total number of MiCOMT proteins. From the phylogenetic tree (Figure 1), it can be seen that there were seven pairs of direct homologous genes of MiCOMT proteins, and one pair of direct homologous genes in cassava and mango were identified.

2.2. Structural and Motif Analysis of MiCOMT Proteins

To explore the structural characteristics and motif conservation of COMT proteins, phylogenetic analysis and MEME were used. We further investigated the structural diversity of MiCOMT proteins. The results of the motif analysis showed that all MiCOMTs contained Motif 4, Motif 5, Motif 6, Motif 7, and Motif 8 (Figure 2A,B), forming the conserved domain of the COMT protein. Thus, it was proved that 18 MiCOMT proteins belonged to the COMT protein family. MiCOMT2 failed to exhibit Motif 1, Motif 2, and Motif 3, while Motif 2 was not detected in MiCOMT13. More than 88.89% of MiCOMT proteins contained seven motifs.

2.3. Chromosomal Distribution and Syntenic Analysis of MiCOMT Genes

To analyze the positions of the MiCOMT genes in the mango genome, chromosomal mapping was performed, and gene duplication events were analyzed. The results suggest that 18 MiCOMT genes were heterogeneously distributed on 8 of the 20 chromosomes. Among these genes, the figure shows seven genes in chr 11; two genes in chrs. 2, 5, 12, and 20; and one gene in chrs. 1, 3, and 19, which correspond to the 18 genes identified. The Ka value, Ks value, and Ka/Ks ratios for the paralog MiCOMT gene pairs were calculated using Tbtools. The MiCOMT genes had 98 duplicate pairs (Table S2), of which 50 (51.0%) had Ka/Ks values less than 1, and the remaining 48 had Ka/Ks values between 1.0 and 1.8, indicating that MiCOMT genes underwent neutral selection during the rapid evolution stage (Figure 3B). To explore the phylogenetic mechanism of the MiCOMTs, a comparison of interspecific synteny among mango and Arabidopsis was conducted. A direct comparison of the homologous gene pairs for all chromosomes showed that three MiCOMT genes were synonymous with Arabidopsis. It can be observed that the COMT gene of mango had a high sequence similarity and close homologous evolutionary relationship with Arabidopsis (Figure 3C).

2.4. Analysis of the Tissue Expression Patterns of MiCOMT Genes

The expression profiles of 18 MiCOMT genes in six tissues (root, stem, leaf, flower, fruit, and seed) were estimated using qRT-PCR, with the root as the control group (Figure 4 and Table S3). All MiCOMT genes members were significantly up-regulated in flower, and MiCOMT1, MiCOMT2, MiCOMT5, MiCOMT6, MiCOMT7, MiCOMT13, MiCOMT16, and MiCOMT18 were significantly up-regulated in all tissues. However, the relative expressions of MiCOMT4, MiCOMT8, MiCOMT9, MiCOMT10, MiCOMT11, MiCOMT14, and MiCOMT15 in leaf and stem were significantly down-regulated. Comprehensive analysis showed that the different members of MiCOMTs had specific expression patterns in different tissues, and 18 MiCOMT members had high transcription levels in flower.

2.5. Differential Expression Analysis of MiCOMT Genes under Salt Stress and Drought Stress

We analyzed the expression patterns of MiCOMT genes under salt stress and simulated drought stress using qRT-PCR. Under salt stress (Figure 5A and Table S4), MiCOMT7 and MiCOMT10 were significantly down-regulated at all time points in mango leaves, while MiCOMT1 and MiCOMT3 were significantly up-regulated between 6 and 72 h. Under drought stress (Figure 5B and Table S5), all MiCOMT genes were significantly up-regulated at 12 and 48 h in mango leaves. The expression of 13 members (72.2%) increased significantly at all time points. These results showed that the expression patterns of MiCOMT genes were different under salt and drought stresses, but MiCOMT1 had the potential to exhibit an up-regulation response to both types of stress.

2.6. Differential Expression Analysis of MiCOMT Genes in Response to ABA and SA Treatments

ABA and SA activated the MiCOMT genes’ transcription levels. During ABA treatment (Figure 6A and Table S6), MiCOMT12, -13, -14, and -15 were significantly up-regulated between 6 and 72 h in mango leaves. A total of 15 MiCOMT gene members showed significant increases in transcription levels at 24 h in mango leaves. More than 66% of MiCOMT genes were up-regulated at 24-72 h in mango leaves. During SA treatment (Figure 6B and Table S7), MiCOMT6 was significantly up-regulated at all time points in mango leaves. A total of 16 MiCOMT gene members were significantly up-regulated at 72 h in mango leaves, while MiCOMT1 was significantly down-regulated at 6, 12, and 72 h. Twelve MiCOMT genes were significantly down-regulated at 12-48 h in mango leaves. These results suggest that the MiCOMT gene responds to ABA and SA treatments.

2.7. Differential Expression Analysis of MiCOMT Gene Responses to Pathogen Infection

To investigate the possible role of MiCOMTs in plant-pathogen interactions, qRT–PCR was used to analyze the response of mango leaves infected with X. campestris pv. mangiferaeindicae and C. gloeosporioides in comparison to 0 h. During infection with X. campestris pv. mangiferaeindicae (Figure 7A and Table S8), MiCOMT5 was significantly up-regulated at all time points in mango leaves. At 24-72 h, the transcription levels of 15 MiCOMT gene members were significantly increased in mango leaves, and the MiCOMT1 and MiCOMT3 genes were significantly down-regulated at 0-12 h. During infection with C. gloeosporioides (Figure 7B and Table S9), the transcriptional levels of MiCOMT17 were consistently up-regulated at all time points in mango leaves. MiCOMT1 and MiCOMT3 were significantly down-regulated at 6 h in mango leaves, while 16 members were significantly up-regulated at 6 h in mango leaves. These results showed that MiCOMT genes had different expression patterns in response to both pathogenic bacteria and fungi.

2.8. Transient Overexpression of MiCOMT1 in N. benthamiana Increased Salt Tolerance

In vivo, to further reveal the role of the MiCOMT1 gene in salt tolerance, the phenotype was analyzed via the transient overexpression of MiCOMT1 in N. benthamiana leaves. For that, the recombinant plasmid 35S::MiCOMT1 and the empty vector were introduced into N. benthamiana using the heat shock method (Figure 8A). N. benthamiana leaves were infected with Agrobacterium containing 35S::MiCOMT1 or control for 3 days. MiCOMT1-gene-overexpressing N. benthamiana leaves were used for physiological assays, including Oligomeric Proanthocyanidin (OPC), chlorophyll (CHL), hydrogen peroxide (H2O2), methyl jasmonic acid (MeJA), salicylic acid (SA), malondialdehyde (MDA), abscisic acid (ABA), ethylene (ETH), and auxin (IAA) contents (Figure 8B–J). Using the control group as the x-axis and the 35S::MiCOMT1 group as the y-axis, simple linear regression analysis was performed using GraphPad Prism 9 software, and the results showed a significant positive correlation (y = 0.9559x + 10.05, R2 = 0.9619, p < 0.0001; Figure S2). These results showed that compared with the control group, the contents of anthocyanins, chlorophyll, and hydrogen peroxide were not significantly different; the contents of ETH were significantly decreased; and the contents of MeJA, SA, MDA, ABA, ETH, and IAA were significantly increased.
In order to evaluate salt tolerance, N. benthamiana seedlings were exposed to 300 mmol·L−1 NaCl when transient overexpression occurred for 3 days (Figure S3). The results showed that there was no significant difference between OPC and CHL contents after salt stress (Figure 9A,B), and the content of hydrogen peroxide also changed significantly (Figure 9C). In contrast to the control, the content of MeJA increased by more than 30% (Figure 9D), while the differences in the SA and MDA contents were fewer (Figure 9E,F). At 6 h, the ABA content increased by more than 145% compared to the control group (Figure 9G). Moreover, the contents of ETH and IAA were significantly higher in the 35S::MiCOMT1 group than in the control group at 1 h and 12 h (Figure 9H,I). Furthermore, using the control group as the x-axis and the 35S::MiCOMT1 group as the y-axis, simple linear regression analysis was performed using GraphPad Prism 9 software, and the result showed a significant positive correlation (y = 1.026x + 0.8835, R2 = 0.9944, p < 0.0001; Figure S4). It was confirmed that MiCOMT1 activated phytohormone signals, affected the accumulation of anthocyanins and chlorophyll, and improved the salt tolerance of plants.

3. Discussion

In this study, for the first time, 18 COMT gene family members were systematically identified from the chromosome-level reference genome of mango. The number of COMT members in mango is smaller than that in B. rapa [4] and G. max [7]. The results of bioinformatic analysis showed that the 18 MiCOMT genes were divided into four groups, being unevenly distributed on 8 of the 20 chromosomes. As a comparison, 16 COMT genes were found in the Citrullus lanatus genome, and they were unevenly distributed on chromosomes 2, 7, 9, and 10. Some of the ClCOMTs were mapped to neighboring regions on the same chromosomes [9]. The rice COMT duplication gene pairs were concentrated on four chromosomes [8]. In addition, most MiCOMTs were found to be in the same group as A. thaliana and M. esculenta. Collinearity analysis showed that the MiCOMT1 gene shares high homology with A. thaliana.
The expression pattern of the COMT genes varies among different plant organs. In general, the expression of the COMT gene was higher in roots [7]. The COMT gene in Larix gmelinii was expressed in rhizomes and leaves, but the highest expression level was in stems [39]. The expression patterns of OsCOMTs in rice were tissue-specific, with high expression in the stem and low or no expression in the roots [8]. However, MiCOMTs are highly expressed in mango flowers. These results suggest that COMT exhibits different functions in different plants. It is possible that the different structures and growth patterns of woody and herbaceous plants lead to different expression patterns of COMT in different plant organs.
Plants are often subjected to various biotic and abiotic stresses during their growth and development, such as high-temperature stress [40], drought stress [41], pathogen stress [42], and salt stress [43]. The plant response to stresses involves complex regulatory mechanisms. For example, OsASR6 in rice enhances tolerance to salt stress [44]; in Arabidopsis, MBF1c is a highly conserved transcriptional co-activator that plays an important role in the heat stress response (HSR) [45]. It is known that COMT gene expression is responsive to salt [46], drought [15], and pathogens [47]. However, COMT genes were down-regulated in salt-treated roots of rice [48]. The expression of Ligusticum chuanxiong LcCOMT genes remained unchanged after salt stress [49]. The expression of the MiCOMT genes was significantly increased after drought stress in mango. The discrepancy between these results might illustrate a response variation among different stress conditions and plant species. Meanwhile, ABA and SA play important roles in plant stress resistance, and SA regulates the heat and photo-oxidative stress of leaves [50]. ABA functions as a central integrator that links and reprograms the complex developmental process and salt stress, and especially osmotic stress, and adaptive signaling cascades in plants [51]. In mango, X. campestris pv. mangiferaeindicae and C. gloeosporioides are the most representative bacterium and pathogenic fungus of mango, respectively [52]. We analyzed the MiCOMT genes’ expression levels during infection of the leaves with X. campestris pv. mangiferaeindicae and C. gloeosporioides at 0–72 h. The expression of MiCOMT genes was significantly up-regulated upon X. campestris pv. mangiferaeindicae infection. This may be because C. gloeosporioides is a fungus and X. campestris pv. mangiferaeindicae is a bacterium, and the mechanism of infection is different, resulting in different resistance patterns in mango. Similarly, the expression of HbCOMT increased rapidly after Hevea brasiliensis suffered from tapping panel dryness [53]. These results suggest that COMT may participate in the plant stress response.
Plants absorb various nutrients from the soil during growth and development [54], but high concentrations of salt ions in the soil inhibit the growth of plants [55]. So, it is important to study the molecular mechanisms of salt tolerance in plants [56]. The plant COMT protein is widely recognized as a stress response protein under salt stress [57]. Impaired photosynthetic systems could impede photosynthetic electron transport, resulting in the accumulation of excessive ROS (H2O2) under salt stress conditions [58]. This excess reactive oxygen species activates anthocyanins, which protect plants from damage from reactive oxygen species [59]. At the same time, it integrates and coordinates various phytohormones’ levels and functions, such as ABA [60], SA, MeJA, and ETH [51]. In this study, low H2O2 concentrations were detected in the MiCOMT1-overexpressing lines after 1–6 h salt treatment. Compared with the control group, the H2O2 content at 12 h and MDA at 1 h were significantly increased. When tomato seeds were tested with salt treatment, H2O2 and MDA contents increased by approximately 66% and 33%, respectively [61]. This was consistent with the concentration of H2O2 and MDA detected in the SlCOMT1-overexpression line after salt treatment [62]. Studies have shown that application of MeJA has a positive effect on antioxidant enzymes to protect plant under abiotic stress conditions [63]. MeJA protects wheat seedlings from salt stress by inhibiting excess reactive oxygen species [64]. In this study, the content of MeJA increased by more than 30%. Many studies have shown that SA is involved in plant salt stress [65,66]. Moreover, the contents of SA were significantly higher in the 35S::MiCOMT1 group than in the control group at 1–6 h. ABA plays an important role in salt stress by regulating stomatal opening or closure [67]. In the salt treatment of N. benthamiana overexpressing MiCOMT1, after 6 h, the ABA content increased by more than 145% compared to the control group. In leaves and roots, the CrCOMT gene positively responded to ABA treatment [14]. The content of the MiCOMT1 gene in mango increased significantly at 24–72 h, suggesting that COMT may be involved in the ABA-dependent stress tolerance pathway. In rice, transcriptome analysis has shown that the expression of IAA-responsive genes is up-regulated under salt stress condition [68]. Exogenously applied ethylene can significantly increase salt stress tolerance in Arabidopsis seedlings [69]. Moreover, the contents of ETH and IAA were significantly higher in the 35S::MiCOMT1 group than in the control group at 1 h and 12 h. In addition, other phytohormones were also increased after salt stress compared to the control group. Thus, it is likely that MiCOMT1 might be a positive regulator of the response to salt by influencing the expression of stress-responsive genes.

4. Materials and Methods

4.1. Plant Materials and Growth Conditions

The Danzhou Mango Germplasm Resource Bank of the Ministry of Agriculture and Rural Affairs provided various tissues and annual seedlings such as roots, young leaves, young stems, flowers, fruits, and seeds, and the variety was “Guifei”. Seedlings were potted in soil (professional growing mix, soil/vermiculite = 2:1) in a greenhouse at 28 °C under a 16/8 h light/dark photoperiod [70,71,72].
Mango leaves were sprayed with a 2 × 107 conidia·mL−1 suspension of C. gloeosporioides, 2 × 106 cfu·mL−1 X. campestris pv. Mangiferaeindicae suspension, 5 mmol·L−1 salicylic acid solution, and 5 mmol·L−1 abscisic acid solution, until the leaves were all wet, and then protected from light. And the mango seedlings were irrigated with 300 mmol·L−1 NaCl and 30% PEG6000 [73,74] until the soil in the pot was completely soaked. We observed the mango leaves at 0, 3, 6, 12, 24, 48, and 72 h (Figure S5). Then, we quickly froze the samples in liquid nitrogen and stored them in a refrigerator at −80 °C. Each treatment was repeated in three replicates [75].

4.2. Identification Analysis of MiCOMT Genes

The chromosome mapping information of the COMT gene family in mango (Taxonomy ID 29780) was gained from the NCBI (https://www.ncbi.nlm.nih.gov/, accessed on 12 November 2022) database, and the map was drawn using Tbtools v1.098768 software [76]. A total of 18 COMT genes were retrieved after performing BLAST, as well as identifying and removing identical genes in the mango genome (genome assembly: CATAS_Mindica_2.1, NCBI RefSeq assembly: GCF_011075055.1), based on the fact that they have the same domain, named MiCOMT1 to MiCOMT18. Syntenic analysis of COMT genes in mango, Arabidopsis thaliana, was conducted by the Tbtools v1.098768 software, which embeds Mcscan (https://github.com/wyp1125/MCScanX, accessed on 15 November 2022) software with the default parameters. The genome of Arabidopsis thaliana was downloaded from the Arabidopsis (https://www.ncbi.nlm.nih.gov/datasets/taxonomy/3702/, accessed on 20 November 2022) databases. The Ka value, Ks value, and Ka/Ks ratios for the paralog COMT gene pairs were calculated using Tbtools, and the rate of divergence was calculated by using the following formula: T = Ks/2r, where Ks represents the synonymous substitutions per site and r is the rate of divergence. We evaluated the values of Ks (synonymous) and Ka (nonsynonymous) as well as the ratio of Ka/Ks. Ka/Ks < 1, Ka/Ks = 1, and Ka/Ks > 1 generally indicate negative, neutral, and positive selection, respectively [76,77,78].

4.3. Phylogenetic and Motif Analysis of MiCOMT Genes

The protein sequences of COMT from M. indica, A. thaliana, M. esculenta, N. tabacum, S. lycopersicum, O. sativa, and P. bretschneideri (Table S1) were analyzed with MEGA 11 software, based on multiple sequence alignment; the phylogenetic tree was constructed according to the method of Salih and colleagues [79] and Li and colleagues [80], and using the neighbor-joining (NJ) method in MEGA 11 software. The robustness of each node in the tree was determined using 1000 bootstrap replicates, and the default parameter for the remaining parameters was selected.
The gene structures of the COMT gene family members in mango were visualized using the mango genome’s annotation information using Tbtools v1.098768 software. The classic mode motifs of COMT proteins were analyzed by the MEME website (http://meme-suite.org; accessed on 30 November 2022) and Tbtools v1.098768 software [81,82].

4.4. RNA Isolation and Quantitative Real-Time PCR (qRT-PCR)

We ground the plant material into a powder in liquid nitrogen and extracted it using an RNA extraction kit (centrifugal column type) (TIANGEN, Beijing, China) [83]. We used QuantStudio 6 Flex (Applied Biosystems, Waltham, MA, USA) to determine the expression of the gene and 2−ΔΔCT to calculate it [52,73]. The qRT–PCR primers of the MiCOMT genes were designed via Primer3 Plus (https://www.bioinformatics.nl/cgi–bin/primer3 plus/primer3 plus.cgi, accessed on 14 March 2023) to determine the specific primers (Table S10) [84].

4.5. Construction of the Expression Vectors and Transient Expression

The full-length coding regions of MiCOMT1 were PCR-amplified using Pfu polymerase with primers (Table S11) and cloned into an overexpression pEGAD vector via appropriate restriction enzyme digestion with Bam HⅠ, Hind III, and T4 DNA ligase [85]. The recombinant plasmid was named 35S::MiCOMT1. The recombinant plasmid and control vector (vector) were transformed into Agrobacterium GV3101 by the heat shock method [85].
The A. tumefaciens suspension was used to infect the leaves of N. benthamiana. N. benthamiana leaves were injected with Agrobacterium GV3101 for 3 days. Next, for the 300 mmol·L−1 NaCl treatment in N. benthamiana, the plants were photographed, and the leaves were harvested for physiological index and gene expression analyses.

4.6. Determination of Related Physiological and Biochemical Parameters

According to the experimental method of Chiriboga and colleagues [86], anthocyanins were extracted by a mixed solution of HCl with a solvent of 1.5 mol/L and a volume fraction of 95% ethyl alcohol (volume ratio of 15:85), and calculated with the following formula: OPC contents (nmol/g·FW) =   ( O D 530 O D 620 0.1 × O D 650 O D 620 4.62   ×   10 6 × V m × 1 , 000 , 000 ) . This study referred to Zhang’s method to extract chlorophyll with 95% alcohol in the dark for 24 h, and this was calculated with the following formula: CHL content (mg/g·FW) =   ( 17.32 × O D 649 + 7.18 × O D 665 ) 1000 × V m [14].
Following the method of Wei and colleagues [87], the leaves were flash-frozen in liquid nitrogen and ground to a very fine powder. The catalase activity was extracted from 0.1 g powder using phosphate-buffered solution (PBS, pH 7.4, 0.15 mol·L−1) on ice. Catalase activity in the supernatant was determined by quantifying the decomposition of H2O2. The endogenous H2O2 level in plant leaves was quantified using 0.1% titanium sulphate at a wavelength of 410 nm.
The leaves were flash-frozen in liquid nitrogen and ground to a very fine powder. The endogenous phytohormones were extracted from 0.1 g powder using phosphate-buffered solution (PBS, pH 7.4, 0.15 mol·L−1) on ice. Extraction and content determination of MeJA, SA, MDA, ABA, ETH, and IAA were performed using the ELISA Kit (Jiangsu Meimian Industrial, Yancheng, China), according to Zhang and colleagues’ method [88], and the article numbers sequentially are MM-6291801, MM-3372201, MM-200901, MM-118501, MM-088801, and MM-095301.

4.7. Statistical Analysis

All the data were processed using GraphPad Prism 9 and IBM SPSS Statistics 26, and we used the one-way ANOVA test for analysis. Equal variance was assumed and Duncan’s multiple range test was used for mean comparisons. In this study, lowercase letters indicate a significant difference (p < 0.05). “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.

5. Conclusions

In the current study, a total of 18 COMT genes were identified from the mango genome, which had high sequence similarity and a close evolutionary relationship with Arabidopsis gene homologs. Through tissue-specific expression analysis, it was found that the expression level was the highest in mango flowers. In addition, we reported a mango COMT gene (MiCOMT1) that plays a role in regulating salt stress tolerance. We also confirmed that MiCOMT1 is a positive regulator of plant salinity tolerance to abiotic stresses. To our knowledge, MiCOMT1 is the first COMT family gene cloned in the mango. The findings presented here could be exploited to benefit mango production in favorable and unfavorable environmental conditions. This paper can provide a reference for researchers engaged in studies on gene function and mechanism identification in mango and other fruits’ disease resistance. It also provides ideas for researchers engaged in COMT gene research.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijms25052639/s1.

Author Contributions

Conceptualization, H.Z. and A.G.; methodology, H.W., Z.C. and R.L.; software, H.Z.; validation, Z.C.; resources, Z.C.; data curation, C.L., H.W. and M.Z.; writing—original, H.W.; writing—review and editing, H.Z. and J.P.; visualization, R.L.; project administration, H.Z. and A.G.; funding acquisition, H.Z. and A.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key R&D Program of China (grant number 2021YFD1600805), the Open Project of Guangxi Key Laboratory of Biology for Mango (grant numbers GKLBM02201), the Central Public–Interest Scientific Institution Basal Research Fund for Chinese Academy of Tropical Agricultural Sciences (grant numbers 16300320220007), the earmarked fund for CARS (grant number CARS–31), and the Open Project of Key Laboratory of Biotechnology of Salt Tolerant Crops of Hainan Province (grant numbers KLBSTCHN2022–3).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Byeon, Y.; Choi, G.; Lee, H.; Back, K. Melatonin biosynthesis requires N-acetylserotonin methyltransferase activity of Caffeic acid O-methyltransferase in rice. J. Exp. Bot. 2015, 66, 6917–6925. [Google Scholar] [CrossRef]
  2. Vanholme, R.; De Meester, B.; Ralph, J.; Boerjan, W. Lignin biosynthesis and its integration into metabolism. Curr. Opin. Biotechnol. 2019, 56, 230–239. [Google Scholar] [CrossRef] [PubMed]
  3. Li, W.; Lu, J.; Lu, K.; Yuan, J.; Huang, J.; Du, H.; Li, J. Cloning and phylogenetic analysis of Brassica napus L. Caffeic acid O-methyltransferase 1 gene family and its expression pattern under drought stress. PLoS ONE 2016, 11, e0165975. [Google Scholar] [CrossRef] [PubMed]
  4. Lu, N.; Ma, W.; Han, D.; Liu, Y.; Wang, Z.; Wang, N.; Yang, G.; Qu, G.; Wang, Q.; Zhao, K.; et al. Genome-wide analysis of the Catalpa bungei Caffeic acid O-methyltransferase (COMT) gene family: Identification and expression profiles in normal, tension, and opposite wood. PeerJ 2019, 7, e6520. [Google Scholar] [CrossRef] [PubMed]
  5. Chen, S.; Zhao, Y.; Zhao, X.; Chen, S. Identification of putative lignin biosynthesis genes in Betula pendula. Trees 2020, 34, 1255–1265. [Google Scholar] [CrossRef]
  6. Liu, Y.; Wang, Y.; Pei, J.; Li, Y.; Sun, H. Genome-wide identification and characterization of COMT gene family during the development of blueberry fruit. BMC Plant Biol. 2021, 21, 5. [Google Scholar] [CrossRef] [PubMed]
  7. Zhang, X.; Chen, B.; Wang, L.; Ali, S.; Guo, Y.; Liu, J.; Wang, J.; Xie, L.; Zhang, Q. Genome-wide identification and characterization of Caffeic acid O-methyltransferase gene family in soybean. Plants 2021, 10, 2816. [Google Scholar] [CrossRef] [PubMed]
  8. Liang, S.; Xu, S.; Qu, D.; Yang, L.; Wang, J.; Liu, H.; Xin, W.; Zou, D.; Zheng, H. Identification and functional analysis of the Caffeic acid O-methyltransferase (COMT) gene family in rice (Oryza sativa L.). Int. J. Mol. Sci. 2022, 23, 8491. [Google Scholar] [CrossRef] [PubMed]
  9. Chang, J.; Guo, Y.; Yan, J.; Zhang, Z.; Yuan, L.; Wei, C.; Zhang, Y.; Ma, J.; Yang, J.; Zhang, X.; et al. The role of watermelon Caffeic acid O-methyltransferase (ClCOMT1) in melatonin biosynthesis and abiotic stress tolerance. Hortic. Res. 2021, 8, 210. [Google Scholar] [CrossRef]
  10. Yao, Z.; Zhang, X.; Liang, Y.; Zhang, J.; Xu, Y.; Chen, S.; Zhao, D. NtCOMT1 responsible for phyto melatonin biosynthesis confers drought tolerance in Nicotiana tabacum. Phytochemistry 2022, 202, 113306. [Google Scholar] [CrossRef]
  11. Bugos, R.; Chiang, V.; Campbell, W. cDNA cloning, sequence analysis and seasonal expression of lignin-bispecific Caffeic acid/5-hydroxyferulic acid O-methyltransferase of aspen. Plant Mol. Biol. 1991, 17, 1203–1215. [Google Scholar] [CrossRef] [PubMed]
  12. Byeon, Y.; Lee, H.Y.; Lee, K.; Back, K. Caffeic acid O-methyltransferase is involved in the synthesis of melatonin by methylating N-acetylserotonin in Arabidopsis. J. Pineal. Res. 2014, 57, 219–227. [Google Scholar] [CrossRef]
  13. Daly, P.; McClellan, C.; Maluk, M.; Oakey, H.; Lapierre, C.; Waugh, R.; Stephens, J.; Marshall, D.; Barakate, A.; Tsuji, Y.; et al. RNAi-suppression of barley Caffeic acid O-methyltransferase modifies lignin despite redundancy in the gene family. Plant Biotechnol. J. 2019, 17, 594–607. [Google Scholar] [CrossRef] [PubMed]
  14. Zhang, K.; Cui, H.; Cao, S.; Yan, L.; Li, M.; Sun, Y. Overexpression of CrCOMT from Carex rigescens increases salt stress and modulates melatonin synthesis in Arabidopsis thaliana. Plant Cell Rep. 2019, 38, 1501–1514. [Google Scholar] [CrossRef]
  15. Yang, W.; Du, Y.; Zhou, Y.; Chen, J.; Xu, Z.; Ma, Y.; Chen, M.; Min, D. Overexpression of TaCOMT improves melatonin production and enhances drought tolerance in transgenic Arabidopsis. Int. J. Mol. Sci. 2019, 20, 652. [Google Scholar] [CrossRef] [PubMed]
  16. Liu, D.; Sun, X.; Liu, L.; Shi, H.; Chen, S.; Zhao, D. Overexpression of the melatonin synthesis-related gene SlCOMT1 improvesthe resistance of tomato to salt stress. Molecules 2019, 24, 1514. [Google Scholar] [CrossRef] [PubMed]
  17. Li, M.; Zhang, K.; Sun, Y.; Cui, H.; Cao, S.; Yan, L.; Xu, M. Growth, physiology, and transcriptional analysis of two contrasting carex rigescens genotypes under salt stress reveals salt-tolerance mechanisms. J. Plant Physiol. 2018, 229, 77–88. [Google Scholar] [CrossRef]
  18. Khadivi, A.; Mirheidari, F.; Saeidifar, A.; Moradi, Y. Identification of the promising mango (Mangifera indica L.) genotypes based on morphological and pomological characters. Food Sci. Nutr. 2022, 10, 3638–3650. [Google Scholar] [CrossRef]
  19. Lebaka, V.; Wee, Y.; Ye, W.; Korivi, M. Nutritional Composition and bioactive compounds in three different parts of mango fruit. Int. J. Environ. Res. Public Health 2021, 18, 741. [Google Scholar] [CrossRef]
  20. Jahurul, M.; Zaidul, I.; Ghafoor, K.; Al-Juhaimi, F.; Nyam, K.; Norulaini, N.; Sahena, F.; Mohd, O.A. Mango (Mangifera indica L.) by-products and their valuable components: A review. Food Chem. 2015, 183, 173–180. [Google Scholar] [CrossRef]
  21. Perveen, N.; Dinesh, M.R.; Sankaran, M.; Ravishankar, K.V.; Krishnajee, H.G.; Hanur, V.S.; Alamri, S.; Kesawat, M.S.; Irfan, M. Comparative transcriptome analysis provides novel insights into molecular response of salt-tolerant and sensitive polyembryonic mango genotypes to salinity stress at seedling stage. Front. Plant Sci. 2023, 14, 1152485. [Google Scholar] [CrossRef] [PubMed]
  22. Wang, L.; Wang, W.; Wang, J. Investigation of salt damage in mango. J. Trop. Subtrop. Bot. 2000, 4, 333–338. (In Chinese) [Google Scholar]
  23. Rabhi, M.; Ferchichi, S.; Jouini, J.; Hamrouni, M.; Koyro, H.; Ranieri, A.; Abdelly, C.; Smaoui, A. Phytodesalination of a salt-affected soil with the halophyte Sesuvium portulacastrum L. to arrange in advance the requirements for the successful growth of a glycophytic crop. Bioresour. Technol. 2010, 101, 6822–6828. [Google Scholar] [CrossRef] [PubMed]
  24. Liu, H.; Tang, X.; Zhang, N.; Li, S.; Si, H. Role of bZIP Transcription factors in plant salt stress. Int. J. Mol. Sci. 2023, 24, 7893. [Google Scholar] [CrossRef] [PubMed]
  25. Wang, L.; Qin, L.; Sun, X.; Zhao, S.; Yu, L.; Chen, S.; Wang, M. Salt stress-induced changes in soil metabolites promote cadmium transport into wheat tissues. J. Environ. Sci. 2023, 127, 577–588. (In Chinese) [Google Scholar] [CrossRef] [PubMed]
  26. Van, Z.E.; Zhang, Y.; Testerink, C. Salt solerance mechanisms of plants. Annu. Rev. Plant Biol. 2020, 71, 403–433. [Google Scholar]
  27. Deng, P.; Jing, W.; Cao, C.; Sun, M.; Chi, W.; Zhao, S.; Dai, J.; Shi, X.; Wu, Q.; Zhang, B.; et al. Transcriptional repressor RST1 controls salt tolerance and grain yield in rice by regulating gene expression of asparagine synthetase. Proc. Natl. Acad Sci. USA 2022, 119, e2210338119. [Google Scholar] [CrossRef] [PubMed]
  28. Ma, Y.; Xue, H.; Zhang, F.; Jiang, Q.; Yang, S.; Yue, P.; Wang, F.; Zhang, Y.; Li, L.; He, P.; et al. The miR156/SPL module regulates apple salt stress tolerance by activating MdWRKY100 expression. Plant Biotechnol. J. 2021, 19, 311–323. [Google Scholar] [CrossRef]
  29. Hussain, S.; Hussain, S.; Ali, B.; Ren, X.; Chen, X.; Li, Q.; Saqib, M.; Ahmad, N. Recent progress in understanding salinity tolerance in plants: Story of Na/K balance and beyond. Plant Physiol. Biochem. 2021, 160, 239–256. [Google Scholar] [CrossRef]
  30. Zhao, H.; Li, Z.; Wang, Y.; Wang, J.; Xiao, M.; Liu, H.; Quan, R.; Zhang, H.; Huang, R.; Zhu, L.; et al. Cellulose synthase-like protein OsCSLD4 plays an important role in the response of rice to salt stress by mediating abscisic acid biosynthesis to regulate osmotic stress tolerance. Plant Biotechnol. J. 2022, 20, 468–484. [Google Scholar] [CrossRef]
  31. Chen, K.; Song, M.; Guo, Y.; Liu, L.; Xue, H.; Dai, H.; Zhang, Z. MdMYB46 could enhance salt and osmotic stress tolerance in apple by directly activating stress-responsive signals. Plant Biotechnol. J. 2019, 17, 2341–2355. [Google Scholar] [CrossRef] [PubMed]
  32. Hazzouri, K.M.; Base, L.K.; Amiri, K.M.A.; Pauli, D.; Blake, T.; Shahid, M.; Mullath, S.K.; Nelson, D.; Mansour, A.L.; Salehi-Ashtiani, K.; et al. Mapping of HKT1; 5 gene in barley using GWAS approach and its impli, cation in salt tolerance mechanism. Front. Plant Sci. 2018, 9, 156. [Google Scholar] [CrossRef] [PubMed]
  33. Chawla, S.; Jain, S.; Jain, V. Salinity induced oxidative stress and antioxidant system in salt-tolerant and salt-sensitive cultivars of rice (Oryza sativa L.). J. Plant Biochem. Biotechnol. 2011, 22, 27–34. [Google Scholar] [CrossRef]
  34. Weng, H.; Wu, M.; Li, X.; Wu, L.; Li, J.; Atoba, T.O.; Zhao, J.; Wu, R.; Ye, D. High-throughput phenotyping salt tolerance in JUNCAOs by combining prompt chlorophyll a fluorescence with hyperspectral spectroscopy. Plant Sci. 2023, 330, 111660. [Google Scholar] [CrossRef] [PubMed]
  35. Jahantigh, O.; Najafi, F.; Badi, H.N.; Khavari-Nejad, R.A.; Sanjarian, F. Changes in antioxidant enzymes activities and proline, total phenol and anthocyanin contents in Hyssopus officinalis L. plants under salt stress. Acta Biol. Hung. 2016, 67, 195–204. [Google Scholar] [CrossRef] [PubMed]
  36. Mulaudzi, T.; Sias, G.; Nkuna, M.; Ndou, N.; Hendricks, K.; Ikebudu, V.; Koo, A.J.; Ajayi, R.F.; Iwuoha, E. Seed priming with MeJA prevents salt-induced growth inhibition and oxidative damage in Sorghum bicolor by inducing the expression of jasmonic acid biosynthesis genes. Int. J. Mol. Sci. 2023, 24, 10368. [Google Scholar] [CrossRef]
  37. Jangra, M.; Devi, S.; Satpal, K.N.; Goyal, V.; Mehrotra, S. Amelioration effect of salicylic acid under salt stress in Sorghum bicolor L. Appl. Biochem. Biotechnol. 2022, 194, 4400–4423. [Google Scholar] [CrossRef]
  38. Liu, Z.; Ma, C.; Hou, L.; Wu, X.; Wang, D.; Zhang, L.; Liu, P. Exogenous SA affects rice seed germination under salt stress by regulating Na+/K+ balance and endogenous gas and ABA homeostasis. Int. J. Mol. Sci. 2022, 23, 3293. [Google Scholar] [CrossRef]
  39. Qiao, M.X.; Lin, X.F.; Zhang, W.B. Isolation and characterization of Caffeic acid O-methyltransferase gene from Larix gmelinii. Mol Plant Breed. 2016, 14, 1684–1690. (In Chinese) [Google Scholar]
  40. Chen, Z.; Galli, M.; Gallavotti, A. Mechanisms of temperature-regulated growth and thermotolerance in crop species. Curr. Opin. Plant Biol. 2022, 65, 102134. [Google Scholar] [CrossRef]
  41. Sitko, K.; Opała-Owczarek, M.; Jemioła, G.; Gieroń, Ż.; Szopiński, M.; Owczarek, P.; Rudnicka, M.; Małkowski, E. Effect of drought and heavy metal contamination on growth and photosynthesis of silver birch trees growing on post-industrial heaps. Cells 2022, 11, 53. [Google Scholar] [CrossRef] [PubMed]
  42. Khan, M.; Gao, J.; Zhang, M.; Xue, J.; Zhang, X. Pseudomonas aeruginosa Ld-08 isolated from Lilium davidii exhibits antifungal and growth-promoting properties. PLoS ONE 2022, 17, e0269640. [Google Scholar] [CrossRef] [PubMed]
  43. Wang, Z.; Yan, L.; Wan, L.; Huai, D.; Kang, Y.; Shi, L.; Jiang, H.; Lei, Y.; Liao, B. Genome-wide systematic characterization of bZIP transcription factors and their expression profiles during seed development and in response to salt stress in peanut. BMC Genom. 2019, 20, 51. [Google Scholar] [CrossRef] [PubMed]
  44. Zhang, Q.; Liu, Y.; Jiang, Y.; Li, A.; Cheng, B.; Wu, J. OsASR6 enhances salt stress tolerance in rice. Int. J. Mol. Sci. 2022, 23, 9340. [Google Scholar] [CrossRef] [PubMed]
  45. Zandalinas, S.I.; Balfagón, D.; Arbona, V.; Gómez-Cadenas, A.; Inupakutika, M.A.; Mittler, R. ABA is required for the accumulation of APX1 and MBF1c during a combination of water deficit and heat stress. J. Exp. Bot. 2016, 67, 5381–5390. [Google Scholar] [CrossRef] [PubMed]
  46. Chun, H.; Baek, D.; Cho, H.; Lee, S.; Jin, B.; Yun, D.; Hong, Y.; Kim, M. Lignin biosynthesis genes play critical roles in the adaptation of Arabidopsis plants to high-salt stress. Plant Signal. Behav. 2019, 14, 1625697. [Google Scholar] [CrossRef]
  47. Khasin, M.; Bernhardson, L.; O’Neill, P.; Palmer, N.; Scully, E.; Sattler, S.; Funnell-Harris, D. Pathogen and drought stress affect cell wall and phytohormone signaling to shape host responses in a sorghum COMT bmr12 mutant. BMC Plant Biol. 2021, 21, 391. [Google Scholar] [CrossRef] [PubMed]
  48. Li, X.; Yang, M.; Chen, H.; Qu, L.; Chen, F.; Shen, S. Abscisic acid pretreatment enhances salt tolerance of rice seedlings: Proteomic evidence. Biochim. Biophys. Acta 2010, 1804, 929–940. [Google Scholar] [CrossRef]
  49. Li, J.; Zhang, G.; Yu, J.; Li, Y.; Huang, X.; Wang, W.; Tan, R.; Zhou, J.; Liao, H. Molecular cloning and characterization of Caffeic acid 3-O-methyltransferase from the rhizome of Ligusticum chuanxiong. Biotechnol. Lett. 2015, 37, 2295–2302. [Google Scholar] [CrossRef]
  50. Rachappanavar, V.; Padiyal, A.; Sharma, J.; Gupta, S. Plant hormone-mediated stress regulation responses in fruit crops areview. Sci. Hortic. 2022, 304, 111302. [Google Scholar] [CrossRef]
  51. Golldack, D.; Li, C.; Mohan, H.; Probst, N. Tolerance to drought and salt stress in plants: Unraveling the signaling networks. Front. Plant Sci. 2014, 5, 151. [Google Scholar] [CrossRef]
  52. Xia, Y.; Luo, R.; Sun, R.; Yang, N.; Pu, J.; Gao, A.; Zhang, H. Genome-wide characterization and identification of the YABBY gene family in mango (Mangifera indica). Diversity 2022, 14, 861. [Google Scholar] [CrossRef]
  53. Qi, J.Y.; Fang, Y.J.; Long, X.Y.; Tang, C.R. Cloning and characterization of a Caffeic acid O-methyltransferase gene (COMT) from Hevea brasiliensis. J. Agric. Biotechnol. 2013, 21, 838–846. (In Chinese) [Google Scholar]
  54. Silver, W.; Perez, T.; Mayer, A.; Jones, A. The role of soil in the contribution of food and feed. Philos. Trans. R Soc. Lond. B Biol. Sci. 2021, 376, 20200181. [Google Scholar] [CrossRef] [PubMed]
  55. Singh, A.; Roychoudhury, A. Gene regulation at transcriptional and post-transcriptional levels to combat salt stress in plants. Physiol. Plant. 2021, 173, 1556–1572. [Google Scholar] [CrossRef] [PubMed]
  56. Zhao, C.; Zhang, H.; Song, C.; Zhu, J.; Shabala, S. Mechanisms of plant responses and adaptation to soil salinity. Innovation 2020, 1, 100017. [Google Scholar] [CrossRef]
  57. Zhao, Q.; Zhang, H.; Wang, T.; Chen, S.; Dai, S. Proteomics-based investigation of salt-responsive mechanisms in plant roots. J. Proteom. 2013, 82, 230–253. [Google Scholar] [CrossRef] [PubMed]
  58. Gong, B.; Wen, D.; Vandenlangenberg, K.; Wei, M.; Yang, F.; Shi, Q.; Wang, X. Comparative efects of NaCl and NaHCO3 stress on photosynthetic parameters, nutrient metabolism, and the antioxidant system in tomato leaves. Sci. Hortic. 2013, 157, 1–12. [Google Scholar] [CrossRef]
  59. Dabravolski, S.A.; Isayenkov, S.V. The role of anthocyanins in plant tolerance to drought and salt stresses. Plants 2023, 12, 2558. [Google Scholar] [CrossRef]
  60. Zhao, S.; Zhang, Q.; Liu, M.; Zhou, H.; Ma, C.; Wang, P. Regulation of plant responses to salt stress. Int. J. Mol. Sci. 2021, 22, 4609. [Google Scholar] [CrossRef]
  61. Ge, L.; Yang, X.; Liu, Y.; Tang, H.; Wang, Q.; Chu, S.; Hu, J.; Zhang, N.; Shi, Q. Improvement of seed germination under salt stress via overexpressing Caffeic acid O-methyltransferase 1 (SlCOMT1) in Solanum lycopersicum L. Int. J. Mol. Sci. 2023, 24, 734. [Google Scholar] [CrossRef] [PubMed]
  62. Sun, S.; Wen, D.; Yang, W.; Meng, Q.; Shi, Q.; Gong, B. Overexpression of Caffeic acid O-methyltransferase 1 (COMT1) increases melatonin level and salt stress tolerance in tomato plant. J. Plant Growth Regul. 2020, 39, 1221–1235. [Google Scholar] [CrossRef]
  63. Farhangi-Abriz, S.; Ghassemi-Golezani, K. Jasmonates: Mechanisms and functions in abiotic stress tolerance of plants. Biocatal. Agric. Biotechnol. 2019, 20, 101210. [Google Scholar] [CrossRef]
  64. Qiu, Z.B.; Guo, J.L.; Zhu, A.J.; Zhang, L.; Zhang, M.M. Exogenous jasmonic acid can enhance tolerance of wheat seedlings to salt stress. Ecotoxicol. Environ. Saf. 2014, 104, 202–208. [Google Scholar] [CrossRef]
  65. Mimouni, H.; Wasti, S.; Manaa, A.; Gharbi, E.; Chalh, A.; Vandoorne, B.; Lutts, S.; Ben, A.H. Does salicylic acid (SA) improve tolerance to salt stress in plants? A study of SA effects on tomato plant growth, water dynamics, photosynthesis, and biochemical parameters. OMICS 2016, 20, 180–190. [Google Scholar] [CrossRef]
  66. Roshdy, A.E.-D.; Alebidi, A.; Almutairi, K.; Al-Obeed, R.; Elsabagh, A. The effect of salicylic acid on the performances of salt stressed strawberry plants, enzymes activity, and salt tolerance index. Agronomy 2021, 11, 775. [Google Scholar] [CrossRef]
  67. Yu, Z.; Duan, X.; Luo, L.; Dai, S.; Ding, Z.; Xia, G. How plant hormones mediate salt stress responses. Trends Plant Sci. 2020, 25, 1117–1130. [Google Scholar] [CrossRef]
  68. Jain, M.; Khurana, J.P. Transcript profiling reveals diverse roles of auxin-responsive genes during reproductive development and abiotic stress in rice. FEBS J. 2009, 276, 3148–3162. [Google Scholar] [CrossRef] [PubMed]
  69. Peng, J.; Li, Z.; Wen, X.; Li, W.; Shi, H.; Yang, L.; Zhu, H.; Guo, H. Salt-induced stabilization of EIN3/EIL1 confers salinity tolerance by deterring ROS accumulation in Arabidopsis. PLoS Genet. 2014, 10, e1004664. [Google Scholar] [CrossRef]
  70. Wei, Y.; Zhu, B.; Ma, G.; Shao, X.; Xie, H.; Cheng, X.; Zeng, H.; Shi, H. The coordination of melatonin and anti-bacterial activity by EIL5 underlies ethylene-induced disease resistance in cassava. Plant J. 2022, 111, 683–697. [Google Scholar] [CrossRef] [PubMed]
  71. Liu, Z.; Luo, C.; Dong, L.; Van Toan, C.; Wei, P.; He, X. Molecular characterization and expression analysis of a GTP-binding protein (MiRab5) in Mangifera indica. Gene 2014, 540, 86–91. [Google Scholar] [CrossRef]
  72. Pandey, K.; Karthik, K.; Singh, S.; Vinod; Sreevathsa, R.; Srivastav, M. Amenability of an Agrobacterium tumefaciens-mediated shoot apical meristem-targeted in planta transformation strategy in mango (Mangifera indica L.). GM Crops Food 2022, 13, 342–354. [Google Scholar] [CrossRef]
  73. Zhang, H.; Liu, Z.; Luo, R.; Sun, Y.; Yang, C.; Li, X.; Gao, A.; Pu, J. Genome-wide characterization, identification and expression profile of MYB transcription factor gene family during abiotic and biotic stresses in mango (Mangifera indica). Plants 2022, 11, 3141. [Google Scholar] [CrossRef]
  74. Fan, R.; Su, X.; Guo, Y.; Sun, F.; Qu, Y.; Chen, Q. Cotton seedling drought tolerance is improved via salt preconditioning. Protoplasma 2021, 258, 263–277. [Google Scholar] [CrossRef]
  75. Ma, Q.; Xia, Z.; Cai, Z.; Li, L.; Cheng, Y.; Liu, J.; Nian, H. GmWRKY16 enhances drought and salt tolerance through an ABA-mediated pathway in Arabidopsis thaliana. Front. Plant Sci. 2019, 9, 1979. [Google Scholar] [CrossRef]
  76. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.; Frank, M.; He, Y.; Xia, R. TBtools: An integrative toolkit developed for interactiveanalyses of big biological data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef]
  77. Kesawat, M.; Kherawat, B.; Singh, A.; Dey, P.; Routray, S.; Mohapatra, C.; Saha, D.; Ram, C.; Siddique, K.; Kumar, A.; et al. Genome-wide analysis and characterization of the proline-rich extensin-like receptor kinases (PERKs) gene family reveals theirrole in different developmental stages and stress conditions in wheat (Triticum aestivum L.). Plants 2022, 11, 496. [Google Scholar] [CrossRef] [PubMed]
  78. Wu, Z.; Shen, S.; Wang, Y.; Tao, W.; Zhao, Z.; Hu, X.; Yu, P. Genome-wide identification and expression analysis of the zinc finger protein gene subfamilies under drought stress in Triticum aestivum. Plants 2022, 11, 2511. [Google Scholar] [CrossRef] [PubMed]
  79. Salih, H.; Tan, L.; Htet, N. Genome-wide identification, characterization of bHLH transcription factors in mango. Trop. Plant Biol. 2021, 14, 72–81. [Google Scholar] [CrossRef]
  80. Li, J.; Wang, T.; Han, J.; Ren, Z. Genome-wide identification and characterization of cucumber bHLH family genes and the functional characterization of CsbHLH041 in NaCl and ABA tolerance in Arabidopsis and cucumber. BMC Plant Biol. 2020, 20, 272. [Google Scholar] [CrossRef] [PubMed]
  81. Sun, H.; Pang, B.; Yan, J.; Wang, T.; Wang, L.; Chen, C.; Li, Q.; Ren, Z. Comprehensive analysis of cucumber gibberellin oxidase family genes and functional characterization of CsGA20ox1 in root development in Arabidopsis. Int. J. Mol. Sci. 2018, 19, 3135. [Google Scholar] [CrossRef]
  82. Li, J.; Li, H.; Quan, X.; Shan, Q.; Wang, W.; Yin, N.; Wang, S.; Wang, Z.; He, W. Comprehensive analysis of cucumber C-repeat/dehydration-responsive element binding factor family genes and their potential roles in cold tolerance of cucumber. BMC Plant Biol. 2022, 22, 270. [Google Scholar] [CrossRef] [PubMed]
  83. Zhang, M.; Xiao, C.; Tan, Q.; Dong, L.; Liu, X.; Pu, J.; Zhang, H. The involvement of the laccase gene Cglac13 in mycelial growth, germ tube development, and the pathogenicity of Colletotrichum gloeosporioides from mangoes. J. Fungi 2023, 9, 503. [Google Scholar] [CrossRef] [PubMed]
  84. Untergasser, A.; Nijveen, H.; Rao, X.; Bisseling, T.; Geurts, R.; Leunissen, J. Primer3Plus, an enhanced web interface to Primer3. Nucleic Acids Res. 2007, 35, W71–W74. [Google Scholar] [CrossRef]
  85. Xie, Y.; Tan, H.; Ma, Z.; Huang, J. DELLA proteins promote anthocyanin biosynthesis via sequestering MYBL2 and JAZ suppressors of the MYB/bHLH/WD40 complex in Arabidopsis thaliana. Mol. Plant 2016, 9, 711–721. [Google Scholar] [CrossRef] [PubMed]
  86. Chiriboga, C.; Francis, F.J. An Anthocyanin Recovery System from Cranberry Pomace. J. Am. Soc. Hortic. Sci. 1970, 95, 233–236. [Google Scholar] [CrossRef]
  87. Wei, Y.; Liu, W.; Hu, W.; Yan, Y.; Shi, H. The chaperone MeHSP90 recruits MeWRKY20 and MeCatalase1 to regulate drought stress resistance in cassava. New Phytol. 2020, 226, 476–491. [Google Scholar] [CrossRef]
  88. Zhang, J.; Shi, Y.; Zhang, X.; Du, H.; Xu, B.; Huang, B. Melatonin suppression of heat-induced leaf senescence involves changes in abscisic acid and cytokinin biosynthesis and signaling path ways in perennial ryegrass (Lolium perenne L.). Environ. Exp. Bot 2017, 138, 36–45. [Google Scholar] [CrossRef]
Figure 1. Phylogenetic relationship of COMTs in different species using complete protein sequences. The neighbor-joining (NJ) phylogenetic tree was constructed with the Poisson model with 1000 bootstrap replicates using MEGA 11 software. The tree was generated from an amino acid sequence alignment of M. indica (Mi) (18 MiCOMTs), A. thaliana (At) (17 members), M. esculenta (Me) (10 members), N. tabacum (Nt) (8 members), S. lycopersicum (Sl) (5 members), O. sativa (Os) (1 member), and P. bretschneideri (Pb) (12 members). The phylogenetic tree was categorized into nine groups, highlighted using different colors. The numerical value on the branch indicates the genetic distance. I–IX indicates grouping.Red star means emphasized that the later MiCOMT1 is the main body of research in this article.
Figure 1. Phylogenetic relationship of COMTs in different species using complete protein sequences. The neighbor-joining (NJ) phylogenetic tree was constructed with the Poisson model with 1000 bootstrap replicates using MEGA 11 software. The tree was generated from an amino acid sequence alignment of M. indica (Mi) (18 MiCOMTs), A. thaliana (At) (17 members), M. esculenta (Me) (10 members), N. tabacum (Nt) (8 members), S. lycopersicum (Sl) (5 members), O. sativa (Os) (1 member), and P. bretschneideri (Pb) (12 members). The phylogenetic tree was categorized into nine groups, highlighted using different colors. The numerical value on the branch indicates the genetic distance. I–IX indicates grouping.Red star means emphasized that the later MiCOMT1 is the main body of research in this article.
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Figure 2. The structural and motif analysis of the MiCOMTs: (A) The phylogenetic tree was constructed with MEGA 11 software using protein sequences of the 18 MiCOMT proteins. The motifs were characterized using the MEME website and TBtools v1.098768 software with the number of motifs set to 8, and the motif discovery mode was classic mode. The eight motifs are named Motif 1 to Motif 8, and are represented with different color boxes. (B) The consensus sequence of 8 motifs.
Figure 2. The structural and motif analysis of the MiCOMTs: (A) The phylogenetic tree was constructed with MEGA 11 software using protein sequences of the 18 MiCOMT proteins. The motifs were characterized using the MEME website and TBtools v1.098768 software with the number of motifs set to 8, and the motif discovery mode was classic mode. The eight motifs are named Motif 1 to Motif 8, and are represented with different color boxes. (B) The consensus sequence of 8 motifs.
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Figure 3. The collinearity and Ka/Ks of COMT proteins: (A) Collinearity analysis of the COMT gene family in mango. Each colored square on the edge of the circle represents mango chromosomes. The gray lines indicate collinear pairs of all mango genes, and the red lines represent collinear pairs of MiCOMTs. (B) Distribution of the Ka/Ks values of MiCOMTs. (C) Collinearity analysis of COMT genes among mango and Arabidopsis. The gray lines represent the collinear blocks in the genomes of mango and Arabidopsis, and the red line represents the collinear COMT gene pairs.
Figure 3. The collinearity and Ka/Ks of COMT proteins: (A) Collinearity analysis of the COMT gene family in mango. Each colored square on the edge of the circle represents mango chromosomes. The gray lines indicate collinear pairs of all mango genes, and the red lines represent collinear pairs of MiCOMTs. (B) Distribution of the Ka/Ks values of MiCOMTs. (C) Collinearity analysis of COMT genes among mango and Arabidopsis. The gray lines represent the collinear blocks in the genomes of mango and Arabidopsis, and the red line represents the collinear COMT gene pairs.
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Figure 4. The expression of MiCOMT genes in different mango tissues. The colors spanning from blue to orange represent increasing levels of gene expression. The level of expression in root was used as a reference to determine up- or down-regulation in the other plant tissues. The horizontal axis represents the different tissue parts of the mango, and the vertical axis represents the MiCOMT genes. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
Figure 4. The expression of MiCOMT genes in different mango tissues. The colors spanning from blue to orange represent increasing levels of gene expression. The level of expression in root was used as a reference to determine up- or down-regulation in the other plant tissues. The horizontal axis represents the different tissue parts of the mango, and the vertical axis represents the MiCOMT genes. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
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Figure 5. Expression patterns of MiCOMT genes under salt and drought stresses. Mango seedlings were treated with 300 mmol·L−1 NaCl (A) and 30% PEG6000 (B) for 0, 3, 6, 12, 24, 48, and 72 h. The level of expression at 0 h was used as a reference to determine up- or down-regulation at other time points. The colors spanning from blue to orange represent increasing levels of gene expression. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
Figure 5. Expression patterns of MiCOMT genes under salt and drought stresses. Mango seedlings were treated with 300 mmol·L−1 NaCl (A) and 30% PEG6000 (B) for 0, 3, 6, 12, 24, 48, and 72 h. The level of expression at 0 h was used as a reference to determine up- or down-regulation at other time points. The colors spanning from blue to orange represent increasing levels of gene expression. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
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Figure 6. Expression patterns of MiCOMT genes under ABA and SA treatment. Mango seedling leaves were treated with 5 mmol·L−1 ABA (A) and 5 mmol·L−1 SA (B) for 0, 3, 6, 12, 24, 48, and 72 h. The level of expression at 0 h was used as a reference to determine up- or down-regulation at other time points. The colors spanning from blue to orange represent increasing levels of gene expression. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
Figure 6. Expression patterns of MiCOMT genes under ABA and SA treatment. Mango seedling leaves were treated with 5 mmol·L−1 ABA (A) and 5 mmol·L−1 SA (B) for 0, 3, 6, 12, 24, 48, and 72 h. The level of expression at 0 h was used as a reference to determine up- or down-regulation at other time points. The colors spanning from blue to orange represent increasing levels of gene expression. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
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Figure 7. Expression patterns of MiCOMT genes during infection with X. campestris pv. mangiferaeindicae and C. gloeosporioides. Mango seedling leaves were treated with 2 × 106 cfu·mL−1 of X. campestris pv. mangiferaeindicae suspension (A) and 2 × 107 conidia·mL−1 suspension of C. gloeosporioides (B) for 0, 3, 6, 12, 24, 48, and 72 h. The level of expression at 0 h was used as a reference to determine up- or down-regulation at other time points. The colors spanning from blue to orange represent increasing levels of gene expression. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
Figure 7. Expression patterns of MiCOMT genes during infection with X. campestris pv. mangiferaeindicae and C. gloeosporioides. Mango seedling leaves were treated with 2 × 106 cfu·mL−1 of X. campestris pv. mangiferaeindicae suspension (A) and 2 × 107 conidia·mL−1 suspension of C. gloeosporioides (B) for 0, 3, 6, 12, 24, 48, and 72 h. The level of expression at 0 h was used as a reference to determine up- or down-regulation at other time points. The colors spanning from blue to orange represent increasing levels of gene expression. “#” represents significantly up-regulated gene expression. “*” represents significantly down-regulated gene expression.
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Figure 8. At 3 dpi, gene-overexpressing N. benthamiana leaves were used for physiological and biochemical analysis. (A) Schematic diagram of the control (vector) and 35S::MiCOMT1. (BJ) Each experiment had three replicates and six N. benthamiana seedlings per replicate. Oligomeric Proanthocyanidin (OPC), chlorophyll (CHL), hydrogen peroxide (H2O2), methyl jasmonic acid (MeJA), salicylic acid (SA), malondialdehyde (MDA), abscisic acid (ABA), ethylene (ETH), and auxin (IAA) contents of N. benthamiana seedlings were treated as described. All data represent mean ± SE for three biological replications. Statistical significance was determined using Duncan’s test, and “a and b” represent significant differences.
Figure 8. At 3 dpi, gene-overexpressing N. benthamiana leaves were used for physiological and biochemical analysis. (A) Schematic diagram of the control (vector) and 35S::MiCOMT1. (BJ) Each experiment had three replicates and six N. benthamiana seedlings per replicate. Oligomeric Proanthocyanidin (OPC), chlorophyll (CHL), hydrogen peroxide (H2O2), methyl jasmonic acid (MeJA), salicylic acid (SA), malondialdehyde (MDA), abscisic acid (ABA), ethylene (ETH), and auxin (IAA) contents of N. benthamiana seedlings were treated as described. All data represent mean ± SE for three biological replications. Statistical significance was determined using Duncan’s test, and “a and b” represent significant differences.
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Figure 9. Overexpression of MiCOMT1 confers salt tolerance in N. benthamiana: (AI) MiCOMT1 was overexpressed in N. benthamiana seedlings for three days, and then treated with 300 mmol·L−1 NaCl solution. Each experiment had three replicates and six N. benthamiana seedlings per replicate. Oligomeric Proanthocyanidin (OPC), chlorophyll (CHL), hydrogen peroxide (H2O2), methyl jasmonic acid (MeJA), salicylic acid (SA), malondialdehyde (MDA), abscisic acid (ABA), ethylene (ETH), and auxin (IAA) contents of N. benthamiana seedlings were treated as described. All data represent mean ± SE for three biological replications. Statistical significance was determined via Duncan’s test, and “a, b, c, d, and e” represent significant differences.
Figure 9. Overexpression of MiCOMT1 confers salt tolerance in N. benthamiana: (AI) MiCOMT1 was overexpressed in N. benthamiana seedlings for three days, and then treated with 300 mmol·L−1 NaCl solution. Each experiment had three replicates and six N. benthamiana seedlings per replicate. Oligomeric Proanthocyanidin (OPC), chlorophyll (CHL), hydrogen peroxide (H2O2), methyl jasmonic acid (MeJA), salicylic acid (SA), malondialdehyde (MDA), abscisic acid (ABA), ethylene (ETH), and auxin (IAA) contents of N. benthamiana seedlings were treated as described. All data represent mean ± SE for three biological replications. Statistical significance was determined via Duncan’s test, and “a, b, c, d, and e” represent significant differences.
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MDPI and ACS Style

Wang, H.; Chen, Z.; Luo, R.; Lei, C.; Zhang, M.; Gao, A.; Pu, J.; Zhang, H. Caffeic Acid O-Methyltransferase Gene Family in Mango (Mangifera indica L.) with Transcriptional Analysis under Biotic and Abiotic Stresses and the Role of MiCOMT1 in Salt Tolerance. Int. J. Mol. Sci. 2024, 25, 2639. https://doi.org/10.3390/ijms25052639

AMA Style

Wang H, Chen Z, Luo R, Lei C, Zhang M, Gao A, Pu J, Zhang H. Caffeic Acid O-Methyltransferase Gene Family in Mango (Mangifera indica L.) with Transcriptional Analysis under Biotic and Abiotic Stresses and the Role of MiCOMT1 in Salt Tolerance. International Journal of Molecular Sciences. 2024; 25(5):2639. https://doi.org/10.3390/ijms25052639

Chicago/Turabian Style

Wang, Huiliang, Zhuoli Chen, Ruixiong Luo, Chen Lei, Mengting Zhang, Aiping Gao, Jinji Pu, and He Zhang. 2024. "Caffeic Acid O-Methyltransferase Gene Family in Mango (Mangifera indica L.) with Transcriptional Analysis under Biotic and Abiotic Stresses and the Role of MiCOMT1 in Salt Tolerance" International Journal of Molecular Sciences 25, no. 5: 2639. https://doi.org/10.3390/ijms25052639

APA Style

Wang, H., Chen, Z., Luo, R., Lei, C., Zhang, M., Gao, A., Pu, J., & Zhang, H. (2024). Caffeic Acid O-Methyltransferase Gene Family in Mango (Mangifera indica L.) with Transcriptional Analysis under Biotic and Abiotic Stresses and the Role of MiCOMT1 in Salt Tolerance. International Journal of Molecular Sciences, 25(5), 2639. https://doi.org/10.3390/ijms25052639

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