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Article

Metabolomic Analysis of Arabidopsis ost1-4 Mutant Revealed the Cold Response Regulation Mechanisms by OPEN STOMATA 1 (OST1) at Metabolic Level

by
Fangming Wu
1,†,
Zhimin Du
2,†,
Zhengrong Hu
3,
Lu Gan
1,
Abul Bashar Mohammad Khaldun
4,
Erick Amombo
5,
Xuebing Huang
6,* and
Jibiao Fan
1,*
1
College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
2
School of Environmental Engineering, Henan University of Technology, Zhengzhou 450001, China
3
Hunan Tobacco Research Institute, Changsha 410004, China
4
Bangladesh Agricultural Research Institute (BARC), Farmgate, Dhaka 1701, Bangladesh
5
African Sustainable Agriculture Research Institute (ASARI), Mohammed VI Polytechnic University (UM6P), Laayoune 43150, Morocco
6
Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2023, 13(10), 2567; https://doi.org/10.3390/agronomy13102567
Submission received: 14 August 2023 / Revised: 22 September 2023 / Accepted: 25 September 2023 / Published: 6 October 2023
(This article belongs to the Special Issue Advances in Environmental Stress Biology: From Omics Approaches)
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Abstract

:
Cold stress is one of the major abiotic stresses that limits the growth and development of plants. Improving the cold tolerance of plants is essential to enhance crop productivity in the changing environment. OPEN STOMATA 1 (OST1), also known as sucrose non-fermenting 1 related protein kinases 2.6/2E (SnRK2.6/SnRK2E), has been reported to involved in cold stress response in plants. This interesting protein is confined to expressed in guard cells and vascular system. However, the detailed mechanism of how OST1 regulates cold stress, especially at the metabolomic level is largely unknown. In this study, metabolomic profiling of ost1 mutant and WT Arabidopsis plants under cold stress was investigated. The results showed that ost1-4 mutants displayed cold sensitive phenotypes compared with the WT plant, as evidenced by higher MDA content and electrolyte leakage and lower photosynthetic characteristics. Next, the metabolic changes between ost1-4 and WT plants in response to cold stress was analyzed by using the GC-TOF-MS system. The results showed that numbers of metabolites were identified to be related to OST1 regulated cold stress response. A large portion of the metabolites were carbohydrates and organic acids. The KEGG enrichment analysis revealed that the alanine, aspartate and glutamate metabolism, cyanoamino acid metabolism and citrate cycle (TCA cycle) were presumptive pathways that most related to OST1 regulated cold stress response. Gene expression such as AtGDHs, AtPPC1 and AtAK1 was also in line with the metabolic changes in the presumed pathways. Overall, this study provides fundamental knowledge for understanding the underlying metabolic mechanisms of OST1 mediated cold stress response in plants.

1. Introduction

In their natural environment, plants are predominantly affected by different abiotic stresses. Cold stress is one of the main abiotic stresses that affect plant growth, development and productivity worldwide. Previous investigations revealed that cold stress could alter various plant processes and results in inhibition of germination, growth of seedlings and leaves, change in biochemical composition, plasma membrane fluidity and disturbed ion homeostasis of cells [1,2]. Due to their genetic makeup, different plants have different adaptive capacities to cold stress. In the long process of evolution, plants have developed complex mechanisms at genetic and physiological levels to cope with the negative effects of cold stress [3]. When exposed to cold stress, plant will increase the activities of antioxidant enzymes [4] and close the stomata [5] to protect the cells from being injured. Besides, expressions of many genes are regulated under cold stress conditions. It is reported that GRFs (GROWTH REGULATORY FACTOR) can regulate plant growth in cold stress via interact with DELLAs [6]. DREBs/CBFs (dehydration-response element-binding protein 1/C-repeat binding factors) signaling pathway plays a central role in cold stress response of plant, and it is connected with cold response related genes such as CAMTAs, PIFs and RVEs [7]. Omics analysis has revealed that cold stress response in plant refers to a complex transcriptional regulatory network [8]. Therefore, the mechanism of cold stress response involves extensive reprograming of gene expression and metabolism.
Open Stomatal 1 (OST1) kinase, also known as sucrose non-fermenting 1 related protein kinases 2.6/2E (SnRK2.6/SnRK2E), was reported to play important roles in abiotic stresses response of plant, i.e., drought [9] and low CO2 [10] stresses. This interesting protein is confined to expressed in guard cells and vascular system [11]. It was a key kinase to mediate stomatal closure of the plants [12]. In recent years, OST1 was reported to play roles in cold stress response [4]. When exposed to cold stress, OST1 phosphorylated other proteins such as BASIC TRANSCRIPTION FACTOR 3 (BTF3), BTF3L (BTF3-like) and Inducer of CBF EXPRESSION 1 (ICE1) to enhance cold tolerance of the plant [13,14]. In plants, ICE1-CBF-COR is a well-known signaling pathway in cold response [15]. The OST1 protein acts upstream of CBFs during cold stress via phosphorylation of the core component of ICE1. Besides, OST1 is also involved in suppressing HIGH EXPRESSION OF OSMOTICALLY RESPONSIVE GENE 1 (HOS1) mediated ICE1 degradation to enhance the freezing tolerance of Arabidopsis [16]. Therefore, OST1 should play an important role in cold stress response of plant.
Studies have shown that stress-induced metabolites could play a remarkable role in plants stress tolerance [17]. Under cold stress, several protective substances such as soluble sugars, proline and cold-resistance proteins are accumulated in plants [18]. However, the detail mechanism that how OST1 regulate cold stress response in plants, especially at metabolomics level is still largely unclear. Nowadays, global metabolite profiling has been performed to identify metabolites and products of metabolic pathways in Arabidopsis [19], Siberian spruce (Picea obovata) [20], perennial ryegrass (Lolium perenne) [21] under stress conditions, and a mass of compounds had been identified to be involved in stress response in different plants [22,23]. Although Arabidopsis ost1 mutant was characterized as a low temperature sensitive genotype, its metabolic profile in response to cold stress was not well documented. Therefore, given the crucial role of OST1 and metabolites in plants stress tolerance, understanding of the OST1 regulated metabolic changes in response to cold stress could be helpful to revealing the regulation mechanisms of stress response in plant. This study was aimed to identify OST1 regulated metabolites under cold stress in Arabidopsis and understand the cold stress response mechanism at metabolome level by the GC-TOF/MS platform.

2. Materials and Methods

2.1. Plant Material, Growth Condition and Treatment

The Arabidopsis thaliana ecotype Columbia (Col-0) was used as a wild-type (WT). The ost1-4 (GK516B05) mutant used in this study was obtained from Prof. Shuhua Yang (China Agricultural University). After surface sterilized with 75% ethanol, Arabidopsis seeds were sown on the Murashige and Skoog (MS) medium which contained 3% sucrose and 0.8% (w/v) agar. The seeds were kept at 4 °C for two days in the dark and then transferred into the growth chamber with 22 °C, 60% relative humidity, and 16 h light/8 h dark. One-week-old seedlings were transplanted to soil. For cold treatment, four-week-old seedlings were exposed to 4 °C. For metabolomic analysis and gene expression, the rosette leaves were collected after 3 h cold treatment. For physiological index measurement, the leaves were collected after 3 d cold treatment. Six biological replicates were set for metabolomic analysis and three biological replicates were set for gene expression analysis and other measurements.

2.2. Physiological Indexes Measurements

Malondialdehyde (MDA) content and relative electrical leakage (EL) of plants were measured according to Fan et al. (2014) [24]. Briefly, MDA content was determined after preparation of crude enzyme solution. The crude enzyme was extracted according to our previous study. The MDA content was measured with thiobarbituric acid (TBA) method. Relative electrical leakage was obtained by measurement of electrical conductivity after and before autoclave treatment, and the ratio of the two values was the relative EL.

2.3. Chlorophyll a Fluorescence (OJIP) Kinetics Measurement

Chlorophyll a fluorescence was analyzed by the pulse-amplitude modulation (PAM) portable chlorophyll fluorometer (PAM-2500) according to Fan et al. (2015) [25]. Briefly, WT and ost1-4 mutant leaves were kept in the dark for 30 min and the OJIP transients were measured at 3000 μmol photons m−2 s−1. The Chl a fluorescence between 10 μs and 320 ms was recorded.

2.4. Metabolites Extraction

A total of 50 mg leaf sample was transferred into a 2 mL EP tube, and 450 μL pre-cold extraction mixture (Vmethanol/VdH2O = 3:1) with 10 μL internal standard (L-2-Chlorophenylalanine, 1 mg/mL stock) were added.
Samples were vortexed for 30 s and then homogenized with a ball mill at 35 Hz for 4 min, after that the mixture was treated with ultrasonication in ice water for 5 min. After centrifugation at 4 °C for 15 min at 12,000 rpm, 200 μL supernatant was transferred to a new tube. For the quality control (QC) sample preparation, 60 μL of each sample was combined together.
The samples were evaporated in a vacuum concentrator, and then incubated in 30 μL of Methoxyamination hydrochloride (20 mg/mL in pyridine) for 30 min at 80 °C. For derivatization, 40 μL of BSTFA regent (1% TMCS, v/v) was applied at 70 °C for 1.5 h.
Samples were cooled to 25 °C and 5 μL of the FAMEs (in chloroform) was added to the QC sample. All of the samples were analyzed by gas chromatograph coupled with a time-of-flight mass spectrometer (GC-TOF-MS).

2.5. GC-TOF/MS Analysis

The gas chromatograph (Agilent 7890, Wilmington, DE, USA) coupled with a time-of-flight mass spectrometer was applied for the GC-TOF/MS analysis, and a DB-5MS capillary column was used in this system.
Exactly, 1 μL aliquot of samples was injected in splitles mode. The carrier gas used in this study was helium. The front inlet purge flow and the gas flow rate through the column were set as 3 mL min−1 and 1 mL min−1, respectively. The initial temperature was set as 50 °C and kept this temperature for 1 min. Then, the temperature was raised at a rate of 10 °C min−1 until to 310 °C and kept for 8 min. The temperatures of injection and transfer line were set as 280 °C, and the ion source temperature was 250 °C. The energy in electron impact mode was −70 eV. The data of the mass spectrometry were obtained in full-scan mode with the m/z range of 50–500 at a rate of 12.5 spectra per second after a solvent delay of 6.25 min.

2.6. Data Preprocessing and Annotations

Raw data analysis, such as peak extraction, baseline adjustment, deconvolution, alignment and integration were performed with the Chroma TOF (V 4.3x, LECO, MI, USA) software. The database of LECO-Fiehn Rtx5 was used to identify the metabolites by matching the mass spectrum and retention index. The peaks that detected in less than half of the QC samples or RSD > 30% in the QC samples were filtered out. To ensure the reliability of metabolite identification the metabolites were selected by similarity value (SV) above 700. The identification was regarded as a putative annotation, for SV was between 200 and 700, while samples with the SV value below 200 were discarded.
For principal component analysis (PCA), the data of peak number, sample name and normalized peak area were inputted into SIMCA software (V15.0.2, Sartorius Stedim Data Analytics AB, Umea, Sweden) to analyze the distribution of the original data. Furthermore, the orthogonal projections to latent structures-discriminant analysis (OPLS-DA) to get more reliable difference between groups and understand the variables responsible for classification. To identify the significantly different metabolites (SDMs), the OPLS-DA model was used with the first principal component of variable importance in the projection values (VIP > 1), and combined with the p value of Student’s t-test (p < 0.05). The fold change (FC) values of the metabolites were calculated by comparison the mean values of the peaks. The pathways of the metabolites were searched by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database.

2.7. RNA Extraction and Gene Expression Analysis

Total RNA was extracted from leaves with Trizol reagent (Invitrogen, Carlsbad, CA, USA) and digested with DNase I (Beyotime, Shanghai, China). The cDNA was synthesized by M-MLV cDNA synthesis kit (Promega, Shanghai, China). The qRT-PCR was conducted with a SYBR Green PCR Master Mix kit (Monad, Wuhan, China) on ABI StepOneplus Real-Time PCR System (Applied Biosystems, Thermo Fisher Scientific Corp. MA, USA). The relative value of each gene expression was calculated as Chen et al. (2010) [26]. The primers used in this study were listed in Table S1.

2.8. Data Analysis

The physiological data were analyzed by SPSS Statistics 16.0 (IBM, Chicago, IL, USA), the significant differences (p < 0.05) were determined by one-way ANOVA, Tukey’s method.

3. Results

3.1. Arabidopisis ost1-4 Mutant Was Sensitive to Cold Stress

To evaluate the cold tolerance of Arabidopisis ost1-4 mutant, we measured MDA content, relative EL and chlorophyll a fluorescence in ost1-4 and WT Arabidopsis plants. The results showed that both MDA content and relative EL remarkably increased in both WT and ost1-4 plants after cold treatment. However, the increasement was quite higher in ost1-4 mutant relative to the WT (Figure 1A,B). In addition, cold stress dramatically disturbed the OJIP curve and significantly reduced the FV/FM in both genotypes. Comparatively, the photosynthesis indexes were remarkably lower in ost1-4 mutant than that of the WT (Figure 1C,D). These results suggested that mutation of OST1 in Arabidopsis induced cold stress sensitivity of the plant.

3.2. Overall Metabolic Response to Cold Stress in ost1-4 Arabidopsis

Initially, a total of 622 chromatography peaks were obtained. After data filtering and missing value recoding, 607 peaks were retained (Table S2). Metabolites matching analysis revealed that among the 607 peaks 257 had no match with metabolites and 118 peaks were unknown (more than one peak matching to one metabolite) which should be filtered out for further analysis. Finally, 232 peaks that matched with metabolites were successfully identified. Generally, the 232 metabolites were divided into 34 categories (Table S3). The top three categories with the most metabolites were carbohydrates and carbohydrate conjugates, carboxylic acids and derivatives as well as amino acids and derivatives which had 59, 41 and 20 metabolites, respectively (Figure 2A).
Next, principal component analysis (PCA) was performed on the metabolic data of both ost1-4 mutant and WT plants. As shown in Figure 2B. WT and ost1-4 mutant showed distinct clustering trend in the first and second principal component. Briefly, metabolites of non-cold treated WT and ost1-4 plants were assigned into the second quadrant and the fourth quadrant, respectively. After cold treatment, the metabolites of ost1 mutant and WT plants were placed in the same first quadrant, but clearly separated into two groups. This result suggested that the metabolites in ost1-4 mutant were different from that of the WT regardless of the growth condition. Moreover, the OPLS-DA model was employed to differentiate groups by evaluating metabolic patterns. The OPLS-DA score plot showed that the metabolites could be separated clearly between ost1-4 mutant and WT no matter whether it was exposed to cold stress (Figure 2C,D). The values of classification parameters in different comparison groups were shown in Table 1.

3.3. Changes of Metabolite Profiles in WT and ost1-4 Mutant

Further analysis was performed to identify SDMs in both genotypes. A total of 114 SDMs were identified in comparison ost1-4CKvsWTCK, of which 58 and 55 SDMs were up- and down- regulated, respectively. However, unexpectedly, less SDMs were identified in the comparison ost1-4coldvsWTcold, of which 65 and 37 SDMs were up- and down- regulated, respectively (Figure 3A).
Furthermore, heat map was constructed using the hierarchical clustering analysis to explore the pattern of metabolite changes between the ost1-4 mutant and WT genotypes. Under normal condition, dozens of metabolites such as sucrose, galactose, ascorbate and aspartic acid were decreased in ost1-4 mutant compared to the WT, while several metabolites such as pyruvic acid, citric acid, malonic acid and malic acid were increased in ost1-4 mutant compared to the WT. When exposed to cold stress, profiles of many metabolites changed in both genotypes. The results showed that after cold exposure, the content of some metabolites, including aspartic acid, asparagine, 2,4-diaminobutyric acid, citrulline, citric acid and mannitol, were significantly lower in ost1-4 mutant than that in WT. Interestingly, these metabolites were much higher in ost1-4 mutant than that in WT under normal condition. On the contrary, the metabolites such as erythrose, linoleic acid and lipoic acid got higher in ost1-4 mutant than that in WT, while content of these substances were lower in ost1-4 mutant than that in WT under normal condition (Figure 3B and Figure S1, the data was showed in Table S4). Besides, contents of several metabolites, i.e., proline, phosphate and pipecolinic acid, decreased further in ost1-4 mutant after cold treatment (Figure 3B).

3.4. Metabolic Pathways Affected by Cold Stress in WT and ost1-4 Mutant

To explore the potential metabolic pathways affected by cold stress in WT and ost1 mutant, the SDMs of both genotypes were subjected to MetaboAnalyst, Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway database (http://www.kegg.jp/kegg/pathway.html, accessed on 11 February 2020) and PubChem analysis revealed that 40 and 34 pathways were found in comparisons ost1-4CKvsWTCK and ost1-4coldvsWTcold, respectively. To facilitate the later analysis, the data were further screened using the cutoff −lnp>2 or pathway impact score > 0.25, and found 10 and 11 most relevant metabolic pathway in the two comparisons, respectively. In detail, pathways such as alanine, aspartate and glutamate metabolism, cyanoamino acid metabolism, citrate cycle (TCA cycle) and linoleic acid metabolism were identified in comparison of ost1-4CKvsWTCK. Besides, pathways including glycine, serine and threonine metabolism, glycerolipid metabolism and sphingolipid metabolism got more significant after cold treatment (Figure 4, Table S5).
In order to further study the most important metabolites regulated by OST1, the profiles of metabolites in different pathways were analyzed. Under normal condition, contents of N-Acetyl-d-galactosamine, aspartic acid, 3-hydroxynorvaline, mannitol and sophorose were upregulated more than 5-folds in ost1-4 compared to WT. While, contents of erythrose, linoleic acid, glutamic acid and ascorbate were downregulated remarkably in ost1-4 compare to WT. Interestingly, metabolites contents changed remarkably in the plants after cold treatment. Contents of digitoxose, lactic acid, raffinose and pelargonic acid were more than 2-fold higher in ost1-4 than that in WT plant. While, contents of 1,5-anhydroglucitol, sulfuric acid, mannitol, malonic acid and citrulline were less than 0.5-fold lower in ost1-4 than that in WT plant (Figure 3B; Table S2). The KEGG analysis showed that these substances especially N-Acetyl-d-galactosamine, aspartic acid, glutamic acid, ascorbate, lactic acid, raffinose, mannitol and citrulline were key compounds in different pathways such as alanine, aspartate and glutamate metabolism, ascorbate and aldarate metabolism and arginine and proline metabolism. These results implied the complex regulation mechanisms of OST1 in cold stress response of plant. In detail, for alanine, aspartate and glutamate metabolism pathway, aspartate and glutamine were two central metabolites. Interestingly, the contents of aspartic acid and asparagine decreased significantly in ost1-4 mutant after cold treatment, while both of them got increased in WT plant. Not the same as aspartate, the contents of glutamine increased after cold treatment in both genotypes. However, the change fluctuations were lower in ost1-4 mutant than that in WT plant. Citrate cycle, also be known as TCA cycle, was a typical pathway for cellular energy metabolism and carbon cycling. Under normal condition, contents of pyruvic acid, malic acid and α-ketoglutaric acid were higher in ost1-4 mutant than that in WT plant. On the contrary, the content of succinic acid was lower in ost1-4 mutant than that in WT plant. After cold treatment, the citric acid content was higher in WT plant after cold treatment than that under normal condition. But it was dramatically decreased in ost1-4 mutant after cold treatment compare to that of normal condition. Meanwhile, the contents of other metabolites in citrate cycle such as malic acid, fumaric acid, succinic acid and α-ketoglutaric acid were also decreased in ost1-4 mutant after cold treatment compare to that of normal condition. However, the contents of citric acid and fumaric acid in ost1-4 mutant were still higher than that in WT plant under cold stress.

3.5. Gene Expression Analysis in ost1-4 Mutant

Pathway analysis suggested that pathways of alanine, aspartate and glutamate metabolism, cyanoamino acid metabolism, and citrate cycle (TCA cycle) were related to OST1 regulation. Moreover, contents of metabolites in these pathways changed significantly in ost1-4 mutant before and after cold treatment. To explore the regulation mechanisms further, genes expression related to these pathways were measured. The results showed that both of the candidate AtGDH (glutamate dehydrogenase) genes that encoded glutamate dehydrogenease were upregulated remarkably after cold treatment for 1 h in ost1-4 mutant compared to WT plant (Figure 5A,B). After cold treatment, the genes were upregulated faster and higher in ost1-4 mutant than that in WT plant. Similar profiles were also detected in the expressions of AtPPC1 (phosphoenolpyruvate carboxylase 1) (Figure 5C). However, the expression of AtAK1 (aspartate kinase 1) was much higher in ost1-4 mutant than that in WT plant at normal temperature. After cold treatment for 6 h it was upregulated in WT plant, but severely downregulated in ost1-4 mutant after 3 h of cold treatment. (Figure 5D).

4. Discussion

Cold stress is one of the most important environmental stresses that plants face in their natural environment. To cope with the adverse impacts of stress conditions, plants evolved a series of complex response mechanisms. It has been proved that ABA signaling is a central signaling pathway that play a significant role in plants stress response [27]. The plant specific protein kinases SnRK2 played critical roles in ABA-dependent and independent signaling pathway [28,29]. Besides, as a member of SnRK2 family, OST1/SnRK2.6 especially expressed in stomata and mediated stomatal closure. Stomatal closure was a crucial in regulating stress response of the plant. Therefore, OST1 must play a very important role in stress response regulation. Recently, several lines of study had proved this hypothesis. For instance, overexpression of Brassica oleracea OST1 gene BolOST1 had been reported to positively modulate drought response in transgenic Arabidopsis [30]. OST1 could also improve cold tolerance in Arabidopsis by enhancing ICE1 stability [16]. Despite several studies have been carried out to investigate the function of OST1 in plant stress response, the detailed metabolic profiles regulated by OST1, especially in response to cold stress was lacking. In this study, metabolic profiling of ost1-4 mutant and WT plants under cold stress were investigated. Two most important stress indicators, such as MDA and EL were measured after cold treatment. The results showed that ost1-4 mutant Arabidopsis exhibited significantly higher MDA content and relative EL after cold treatment, indicating that ost1-4 mutant was more sensitive to cold stress than the WT. In support to the above results, the OJIP curve and FV/FM were declined remarkably in ost1-4 mutant Arabidopsis after cold treatment, indicating a noticeable effect on photosynthesis. Taken together, physiological analysis showed that OST1 loss-of-function mutation could enhance cold stress sensitivity in plants. In support, a study revealed that OST1 plays a positive in cold stress response by phosphorylating BTF3 and BTF3L in Arabidopsis [14]. Moreover, it was also noticed that there no significant growth and physiological phenotype differences between ost1-4 mutant and WT, this might be because of the functional redundancy of SnRK2 family and other proteins.
When plants exposed to abiotic stress, immediate responses could be induced at molecular, biochemical and physiological levels to establish a new homeostasis [31]. This new homeostasis, including change in metabolites could help plants to cope with damages caused by stresses. Therefore, understanding the metabolic profiles changed in response to abiotic stress is imperative significant to uncover complex tolerance mechanisms. Recently metabolomic analysis has been performed to uncover cold stress response in different plant species, including maize (Zea mays) [32], wheat (Triticum aestivum) [33] and Eucalyptus species [34]. Given the crucial role of OST1 in cold stress response and the important of metabolomics analysis, here we carried out metabolomics profiling of ost1 mutant and WT plants under cold stress. As expected, cold stress induced several metabolic changes in both ost1 mutant and WT Arabidopsis plants. Many SDMs were identified in comparison of ost1-4CKvsWTCK, and most of the SDMs were carbohydrates and organic acids. This suggested that the mutation of OST1 induced the rearrangement of the metabolites in plant cell even under normal condition. When exposed to cold stress, although less SDMs were identified in comparison of ost1-4coldvsWTcold than that of ost1-4CKvsWTCK, larger percentage of the SDMs had higher content in ost1-4 mutant than that in WT plant compare to that of normal condition. This result was counterintuitive because higher contents of soluble substances in cells usually implied better adaptability of the plant. And hundreds fold of upregulation of some metabolites were indeed detected in comparisons of WTcoldvsWTCK and ost1-4coldvsost1-4CK. However, the physiological investigation revealed that ost1-4 mutant was sensitive to cold stress. These results were understandable when the trait of ost1 mutant was considered. The typical phenotype of ost1 mutant was stay-open stomata even under stress condition [35]. Cold stress could induce stomatal closure in WT plant, so that the plant could avoid water loss. But in ost1-4 mutant, the stomata keep opening under cold stress condition, the relative high content of the metabolites might be play roles in keeping the water potential of the cells which induced stay opening of the stomata. Resent study reported that OST1 regulated the stomatal movement via regulating the ion channels [36]. Considering that the stomatal movement was control by hydraulic and chemical signaling, so whether OST1 was involved in regulating the water potential was needed to study further.
The changes of massive metabolites in ost1-4 mutant and WT plant before and after cold stress treatment were too complex. The KEGG analysis could be used as a useful tool to reveal the deep regulation mechanisms. With the KEGG analysis, several pathways that related to OST1 involved cold stress response were identified. Under normal temperature, pathways of alanine, aspartate and glutamate metabolism, citrate cycle (TCA cycle) and cyanoamino acid metabolism were found to be significantly changed in ost1-4 mutant and WT plant which implied that these pathways were regulated by OST1. Alanine, aspartate and glutamate metabolism pathway was related to numbers of metabolism pathways; hence it was one of the core metabolism pathways to regulate the material and energy cycle in the cell. As the results showed, contents of two core metabolites including aspartate and glutamine were remarkably decreased in ost1-4 mutant after cold treatment, which was distinguished from the change in WT plant. This indicated that aspartate metabolism was severely suppressed in ost1-4 mutant when exposed to cold stress. Although the contents of glutamine increased after cold treatment in both genotypes, the difference of change fluctuations suggested the disruption by mutation of OST1 in Arabidopsis. Therefore, the integrate changes of the key metabolites content resulted in regulation of alanine, aspartate and glutamate metabolism pathway. Previous studies showed that alanine, aspartate and glutamate metabolism pathway was involved in the regulation of drought stress in Salvadora persica [37] and heat stress in Sargassum fusiforme [38]. which suggested the crucial roles of this pathway in stress response of plant. Besides, 3-cyanoalanine was exactly the upstream metabolite of aspartate and asparagine in cyanoamino acid metabolism pathway, and contents changes of these three metabolites were coincident. So, the pathway of cyanoamino acid metabolism should also be regulated by OST1. Citrate cycle was a crucial pathway for energy metabolism and carbon cycle in cells, and it also connected aspartate and glutamate metabolisms. Citrate cycle had been reported in cold stress response of strawberry [39]. In the present study the results showed that under normal condition, increase of citric acid content maybe induced by high content of pyruvic acid in ost1-4 mutant under normal condition, which further induced increase of malic acid and α-ketoglutaric acid contents. Depside that the contents of metabolites in citrate cycle were downregulated by cold stress, they are still higher in ost1-4 mutant than WT plant after cold treatment. High activity of citrate cycle could provide energy and osmosis substances which might be contributed to keep continuously stomatal opening. Furthermore, KEGG pathways of ascorbate and aldarate metabolism and arginine and proline metabolism were also enriched in the present study which was in accorded with the results that was found in pumpkin (Cucurbita maxima) [40].
Gene expression could reveal more information of metabolites regulation. Given that the pathways of alanine, aspartate and glutamate metabolism and citrate cycle (TCA cycle) were presumptive pathways which the most be related to OST1 regulated cold stress response. Several genes expressions related to these pathways were investigated further. The results showed that both AtGDHs were upregulated in ost1-4. AtGDH genes encoded glutamate dehydrogenase [41], and this enzyme catalyzed the deamination of l-glutamate to 2-oxoglutarate. This result suggested that the metabolic direction of glutamate was changed in ost1-4 mutant, it preferred be catalyzed into glutamine other than 4-aminobutanoate. Maybe this could explain why the contents of α-ketoglutaric acid and glutamine were upregulated, but downregulation of 4-aminobutyric acid and succinic acid contents in ost1-4 mutant compare to WT plant. AK1 was a kinase that catalyzed aspartate to aspartylphosphate [42], its activity was related to the content of aspartate. The results of this study also showed that under normal condition, the content of aspartate was higher in ost1-4 mutant than that in WT plant. When the plants were exposed to cold stress, the content of aspartate increased in WT plant but decreased in ost1-4 mutant. AtPPC1 encoded phosphoenolpyruvate carboxylase which catalyzed phosphoenolpyruvate and CO2 to oxaloacetate [43]. The oxaloacetate could be catalyzed to citrate and malate. Hence, upregulation of AtPPC1 expression could induce upregulation of citric acid and malic acid contents which results were detected by metabolic analysis.

5. Conclusions

Although OST1 was confined to expressed in guard cells and vascular system and regulated stomata closure, it played an important role in regulating cold stress response of the plants. Mutation of OST1 could induce cold sensitivity of plant. Massive of SDMs were identified to be related to cold stress response of Arabidopsis. Most of the SDMs with high contents in ost1-4 mutant after cold treatment were soluble carbohydrates and organic acids that might be contribute to keep continuous stomatal opening of the mutate plant under cold stress. The KEGG analysis revealed that pathways of alanine, aspartate and glutamate metabolism, citrate cycle (TCA cycle) and cyanoamino acid metabolism were most related to OST1 regulated cold stress response of Arabidopsis. The gene expression analysis of AtGDH, AtPPC1 and AtAK1 validated the presumption of metabolic analysis further. Overall, the present study provided some information on the metabolomic regulation of OST1 related cold stress response in plant, but the mechanisms of OST1 related cold stress response was still largely unknown in plant, and it should to study further in the future.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13102567/s1, Figure S1: Hierarchical clustering analysis for the SDMs in comparisons of ost1-4coldvsost1-4CK and WTcoldvsWTCK; Table S1: Primer sequences used in this study; Table S2: Metabolites identified in this study; Table S3: Classification of the metabolisms; Table S4: Data of hierarchical clustering analysis of the SDMs; Table S5: Pathway analysis of the SDMs.

Author Contributions

Conceptualization, X.H. and J.F.; methodology, X.H. and L.G.; validation, F.W., Z.D. and Z.H.; investigation, J.F., F.W.; resources, X.H.; writing—original draft preparation, J.F., F.W.; writing—review and editing, A.B.M.K., E.A.; visualization, J.F.; supervision, J.F. and X.H.; funding acquisition, J.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by [the National Natural Science Foundation of China (NSFC)] grant number [31702165 and 31672482].

Data Availability Statement

Data is contained within the article or supplementary material.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (NSFC) (Grant Nos. 31702165 and 31672482). We would like to thank professor Shuhua Yang in State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University for the gift of ost1-4 mutant of Arabidopsis. We would like to thank Biotree Biotech Co., Ltd. (Shanghai, China) for GC-TOF/MS analysis.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Physiological change of ost1-4 mutant and WT Arabidopsis under cold stress. (A) MDA content; (B) relative EL; (C) FV/FM; (D) OJIP curve; CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line. Means with the same letters represent no significant difference (p > 0.05).
Figure 1. Physiological change of ost1-4 mutant and WT Arabidopsis under cold stress. (A) MDA content; (B) relative EL; (C) FV/FM; (D) OJIP curve; CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line. Means with the same letters represent no significant difference (p > 0.05).
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Figure 2. Total statistical analysis of the metabolite profiles. (A) classification statistics; (B) PCA analysis; (C) OPLS-DA analysis between ost1-4 mutant and WT under normal condition; (D) OPLS-DA analysis between ost1-4 mutant and WT under cold stress. The R2X value of the PCA model was 52.3%, and all the samples from both genotypes fall inside the Hotelling’s T2 tolerance ellipse which represents 95% confidence limit. CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line.
Figure 2. Total statistical analysis of the metabolite profiles. (A) classification statistics; (B) PCA analysis; (C) OPLS-DA analysis between ost1-4 mutant and WT under normal condition; (D) OPLS-DA analysis between ost1-4 mutant and WT under cold stress. The R2X value of the PCA model was 52.3%, and all the samples from both genotypes fall inside the Hotelling’s T2 tolerance ellipse which represents 95% confidence limit. CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line.
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Figure 3. SDMs analysis between ost1-4 mutant and WT under different conditions. (A) volcano plot of the metabolite; (B) Hierarchical clustering analysis for the SDMs. The relative metabolite content was depicted with color scale. Red means upregulated, blue means downregulated. CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line.
Figure 3. SDMs analysis between ost1-4 mutant and WT under different conditions. (A) volcano plot of the metabolite; (B) Hierarchical clustering analysis for the SDMs. The relative metabolite content was depicted with color scale. Red means upregulated, blue means downregulated. CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line.
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Figure 4. Metabolome view map of significant metabolic pathways identified between ost1-4 mutant and WT. (A) Significant pathways between different genotypes under normal condition; (B) Significant pathways between different genotypes after cold treatment. The x-axis represents pathway enrichment, and the y-axis represents pathway impact. Large sizes and dark colors represent major pathway enrichment and high pathway impact values, respectively. CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line.
Figure 4. Metabolome view map of significant metabolic pathways identified between ost1-4 mutant and WT. (A) Significant pathways between different genotypes under normal condition; (B) Significant pathways between different genotypes after cold treatment. The x-axis represents pathway enrichment, and the y-axis represents pathway impact. Large sizes and dark colors represent major pathway enrichment and high pathway impact values, respectively. CK = control; cold = cold treatment; WT = wild type; ost1-4 = ost1-4 mutant line.
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Figure 5. Gene expression in ost1-4 mutant and WT plant after cold treatment. WT = wild type; ost1-4 = ost1-4 mutant line. *** = significant different (p < 0.01). (A) Relative expression of AtGDH1; (B) Relative expression of AtGDH2; (C) Relative expression of AtPPC; (D) Relative expression of AtAK1.
Figure 5. Gene expression in ost1-4 mutant and WT plant after cold treatment. WT = wild type; ost1-4 = ost1-4 mutant line. *** = significant different (p < 0.01). (A) Relative expression of AtGDH1; (B) Relative expression of AtGDH2; (C) Relative expression of AtPPC; (D) Relative expression of AtAK1.
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Table 1. Classification parameter values of PCA and OPLS-DA model.
Table 1. Classification parameter values of PCA and OPLS-DA model.
TitleTypeANR2XR2YQ2
TOTAL with QCPCA7270.527
ost1-4CKvsWTCKOPLS-DA1+1+0120.5730.9990.981
ost1-4coldvsWTColdOPLS-DA1+1+0120.530.9990.965
A = number of principal components of the model; N = sample size; R2X = explanatory properties of the model for the X variable; R2Y = explanatory properties of the model for the Y variable; Q2 = predictability of the model.
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MDPI and ACS Style

Wu, F.; Du, Z.; Hu, Z.; Gan, L.; Khaldun, A.B.M.; Amombo, E.; Huang, X.; Fan, J. Metabolomic Analysis of Arabidopsis ost1-4 Mutant Revealed the Cold Response Regulation Mechanisms by OPEN STOMATA 1 (OST1) at Metabolic Level. Agronomy 2023, 13, 2567. https://doi.org/10.3390/agronomy13102567

AMA Style

Wu F, Du Z, Hu Z, Gan L, Khaldun ABM, Amombo E, Huang X, Fan J. Metabolomic Analysis of Arabidopsis ost1-4 Mutant Revealed the Cold Response Regulation Mechanisms by OPEN STOMATA 1 (OST1) at Metabolic Level. Agronomy. 2023; 13(10):2567. https://doi.org/10.3390/agronomy13102567

Chicago/Turabian Style

Wu, Fangming, Zhimin Du, Zhengrong Hu, Lu Gan, Abul Bashar Mohammad Khaldun, Erick Amombo, Xuebing Huang, and Jibiao Fan. 2023. "Metabolomic Analysis of Arabidopsis ost1-4 Mutant Revealed the Cold Response Regulation Mechanisms by OPEN STOMATA 1 (OST1) at Metabolic Level" Agronomy 13, no. 10: 2567. https://doi.org/10.3390/agronomy13102567

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