Abstract
Convergent and divergent evolution lead to plants with stronger adaptability to higher temperatures, thus averting crop biomass yield reductions. NADP-dependent malate dehydrogenase (NADP-MDH) is a redox-regulated enzyme that catalyzes the reversible reduction of oxaloacetate to malate. The sole NADP-MDH gene in rice, OsMDH8.2, is expressed in mesophyll cells of photosynthetic organs and various sink tissues. However, it is unknown whether NADP-MDH functions in heat stress in rice. We characterized a transgenic OsMDH8.2 overexpression line under thermal stress treatment (40 °C). The transgenic line exhibited better adaptability to heat stress than the wild type; it better maintained biomass and a lower surface temperature through stomatal closure, and photosynthetic activity was less affected. OsMDH8.2 was found to affect peroxidase activity by reducing the hydrogen peroxide content in flag leaves after 3 and 5 days of thermal stress. Analysis results of OsMDH8.2 knockout lines confirmed that OsMDH8.2 contributes to heat tolerance. Transcriptome and metabolome analyses demonstrated that OsMDH8.2 plays a key role in energy homeostasis by reducing tricarboxylic acid cycle activity while inducing the glyoxylate cycle to produce more energy, and by regulating amino acid metabolism to rescue heat-stress damage. Collectively, these results suggest that OsMDH8.2 enhances glyoxylate cycle efficiency, resulting in lower carbon dioxide release into the environment through stomatal closure, providing an excellent strategy for improving plant heat tolerance through genetic engineering.
Key words: Heat temperature, Adaptability, Stoma, OsMDH8.2, Rice
Graphical abstract
1. Introduction
Rice (Oryza sativa) is a major food crop in China. However, recent rapid climate changes have led to extremely high temperatures, posing a threat to rice production. The global temperature has been predicted to increase by up to 3–6 °C by 2100, which seriously threatens crop growth and production [1], [2], [3]. During photosynthesis, energy absorption from the environment by the leaves is limited by dissipation due to long wavelength radiation, conduction, and convection, as well as evaporative cooling from water loss. To maintain canopy and leaf surface temperatures under heat stress, plants have developed complex physiological and metabolic mechanisms to withstand the heat stress by adjusting stomatal opening to generate a more negative leaf‐to‐air temperature difference, which in turn activates signaling cascades to readjust cellular metabolism to avoid heat-induced damage cause by excess reactive oxygen species (ROS), amino acid, and organic acid contents [4], [5], [6]. Plants are able to sense and adapt to heat stress by inducing adaptive responses by altering various physiological and molecular processes, such as the ROS scavenging system [7], [8], [9], glycinebetaine osmolyte synthesis genes [10,11], and lipid metabolism [12], [13], [14], to enhance their heat tolerance. In plants, ROS are scavenged by an enzymatic anti-oxidative system comprising catalase (CAT), ascorbate peroxidase (APX), glutathione peroxidase, and superoxide dismutase (SOD), and a non-enzymatic anti-oxidative system, including ascorbic acid, glutathione, tocopherols, and phenolic compounds [4]. Additionally, leaf soluble proteins, proline, and soluble sugars are important factors and adaptive components in heat tolerance [6]. Suppression of OsMDHAR4 (Monodehydroascorbate reductase 4) enhances heat tolerance by mediating H2O2-induced stomatal closure in rice leaves [15]. A thorough understanding of plant responses to heat stress at the physiological, genetic, and molecular biological levels would aid in alleviating this vexed question.
Convergent and divergent evolution by natural selection have enabled plants to respond to heat by activating heat-regulated genes and secondary signaling pathways [16]. The C3 and C4 photosynthetic pathways evolved independently from multiple sources within families and genera of angiosperms, and it has been suggested that the evolutionary transition from the C3 pathway to the C4 pathway was relatively simple [17,18]. Interestingly, C4 plants are more adaptable to high temperatures than C3 plants owing to lower photorespiration rates and better water use efficiency. Compared with C3 plants, C4 plants conduct photosynthesis in the mesophyll and bundle sheath cells through various steps. Carbon is primarily fixed by phosphoenolpyruvate carboxylase located in the mesophyll cells, followed by secondary fixation by Rubisco in the bundle sheath cells [19]. The key enzymes in the C4 pathway include phosphoenolpyruvate carboxylase and pyruvate orthophosphate dikinase, which depend on NAD(P) malic enzyme, NAD(P) malate dehydrogenase (NAD(P)-MDH), and carbonic anhydrase. The structure and enzymatic activities of C4 plants enhance photosynthetic product transport efficiency and water distribution, as well as responses to drought, salt, cold, pH, and osmotic stress by modulating ROS levels and the balance between carbon and nitrogen metabolism [19], [20], [21], [22], [23], [24], [25]. Among monocotyledonous gramineous crops, corn and rice are thought to have diverged approximately 50 million years ago, and the maize and rice genomes show high levels of chromosome collinearity and gene sequence conservation [18]. In China, indica rice is farmed in the southern areas and japonica rice in the northern areas. Indica is more resistant than japonica to heat, strong light, and moisture, indicating that japonica rice potentially has C4-like heat resistance [17].
MDH is a key enzyme in the C4 cycle that catalyzes the reversible conversion between malic acid and oxaloacetate, and participates in the tricarboxylic acid cycle, glyoxylate cycle, and other metabolic pathways. We previously reported on the functions of C4 carbon-concentrating mechanism-related homologous genes in stress responses in C3 plants [26]. Here, we report that NADP-MDH in O. sativa, encoded by OsMDH8.2, is involved in heat stress tolerance by inhibiting the tricarboxylic acid cycle while inducing the glyoxylate cycle and promoting organic acid synthesis.
2. Materials and methods
2.1. Phylogenetic tree construction, plant materials, and growth conditions
A BLAST search against the NCBI (http://www.ncbi.nlm.nih.gov) and UniProtKB (http://www.uniprot.org) databases was performed using the amino acid sequence of OsMDH from NCBI as a query. The retrieved protein sequences were used to construct a phylogenetic tree, using CLUSTALW2 (http://www.clustal.org). T-DNA-tagged osmdh8.2 mutants in the Dongjin background (Oryza sativa L. ssp. japonica) were identified from the rice T-DNA Insertion Sequence Database [27]. A homozygous mutant was identified by PCR using genomic DNA. Full-length OsMDH8.2 cDNA was generated by PCR. The PCR products were cloned into the vector pcambia1301, which contains the 35S promoter, a synthetic GFP coding region, and a nopaline synthase terminator. The construct was transformed into Agrobacterium tumefaciens LBA4404. Transgenic rice plants on the Dongjin background were generated through stable transformation with the construct via Agrobacterium-mediated co-cultivation, as previously reported [27]. All primer sets used are listed in Table S1. Seeds were germinated in soil and transferred to pots in a paddy field on day 28 after germination at Yangzhou University, China. For heat treatment, the rice plants were transferred to growth chambers at 40 °C for 7 days.
2.2. Thermal imaging of rice flag leaves
Using a FLIR E54 (FLIR Systems, Wilsonville, OR, USA) thermal imaging camera, thermal infrared and RBG images were acquired simultaneously. The wavelength range of the thermal imaging camera is 7.5–14 µm, and the thermal sensitivity is < 40 mK below 30 °C. The camera can detect a temperature difference of less than 0.15 °C, and the infrared resolution is 320 × 240 pixels. We recorded three values from each flag leaf during the sampling period, and we used the averages as the final data. The rice temperature data were analyzed using the Flir® Tools software (version 6.2, FLIR Systems).
2.3. Determination of the H2O2 content
Rice flag leaves (0.5 g) were ground into a fine powder in an ice bath using a pestle and a mortar. The powder was homogenized in 5 mL of acetone (4 °C). The homogenate was centrifuged at 6000 g/min at 4 °C for 20 min, and 1 mL of 0.1% titanium tetrachloride in 20% H2SO4 was added to 2 mL of supernatant. The absorbance of the reaction solution at 410 nm against a blank was recorded.
2.4. Determination of the malondialdehyde (MDA) content
Rice flag leaves (0.2 g) were ground into a fine powder in liquid nitrogen using a pestle and a mortar. The powder was homogenized in a 5 mL of 10% (w/v) trichloroacetic acid. The homogenate was centrifuged at 10,000 g/min at 4 °C for 15 min, and 1.5 mL of supernatant was added to the same volume of 0.5% (w/v) thiobarbituric acid. The mixture was incubated in a water bath at 100 °C for 30 min, and the reaction was stopped by placing the mixture in an ice bath. The cooled solution was centrifuged at 10,000 g/min for 10 min, and the absorbance of the supernatant at 450, 532, and 600 nm was measured. The MDA concentration was measured as MDA concentration (µM) = 6.452 × (OD532−OD600) − 0.559 × OD450.
2.5. Antioxidant enzyme activity determination
Rice flag leaves were sampled, immersed in liquid nitrogen, and stored at –80 °C. Samples of 0.2 g were homogenized in 5 mL of 50 mmol/L phosphoric acid buffer (pH 7.0). The homogenates were centrifuged at 12,000 g/min at 4 °C for 20 min, and the supernatants were used for SOD, peroxidase (POD), APX, and CAT activity determinations (Supplemental method 1).
2.6. Quantitative reverse transcription (RT-qPCR) analysis
Total RNA was isolated from seedlings at 7 days after germination using RNAisoPlus (TaKaRa, Shiga, Japan). cDNA was synthesized from the RNA, and RT-qPCR was performed as previously described [28]. Target gene expression levels were normalized to that of rice OsUBQ5 (LOC_Os01g22490). All experiments were conducted at least three times, with three or more samples per time point. Melting curves were generated to ensure primer specificity, observed as a single, sharp peak. The PCR products were sequenced to verify primer specificity [27]. All primers are used listed in Table S1.
2.7. Histochemical β-glucuronidase (GUS) staining analysis
GUS staining was conducted as previously described [27]. GUS-stained samples were fixed in 3% (w/v) paraformaldehyde, 5% (v/v) acetic acid, and 63% (v/v) ethanol. Plant organs were imaged using a microscope (OLYMPUS BX61; Olympus, Tokyo, Japan), under bright-field illumination.
2.7.1. RNA-sequencing and data analysis
Total RNA was extracted from three flag leaves of wild-type (WT) and OsMDH8.2-OX1 plants after heat treatment for 3 days and was used for transcriptome analysis, as previously reported [28]. After cDNA library construction and quality control using a bioanalyzer (Agilent 2100, Palo Alto, USA), transcriptome sequencing was performed on an Illumina HiSeq 2500 sequencing platform (Illumina, San Diego, CA, USA).
Read quality was assessed using the FastQC tool. Sequence reads were assembled using StringTie (version 1.3.0, Baltimore, MD, USA) and mapped to the reference genome. Read distribution and coverage on the reference sequence were examined. Gene expression levels were measured and Ballgown was used for differential expression. Genes with a q-value < 0.05 and a fold-change > 2 between the WT and OsMDH8.2-OX samples were considered significantly differentially expressed. GO functional enrichment analysis of target genes was performed using Goatools (https://github.com/tanghaibao/goatools). Corrected P-values < 0.05 were considered to indicate significant enrichment. Gene set enrichment analysis was used to identify genes with no significant difference in expression but with biological implications.
2.8. Metabolome analysis
Flag leaves of WT and OsMDH8.2-OX1 plants exposed to heat treatment for 3 days were used for metabolome analysis by gas chromatography-mass spectrometry (GC–MS). The acquired MS data were converted to the common data format (.mzdata) using the Agilent MassHunter Qualitative Analysis software (version B.08.00; Agilent Technologies, Palo Alto, CA, USA). The xcms package in R (https://www.r-project.org/, Lucent Technologies, New Providence, NJ, USA) was used for data pretreatment, including nonlinear retention time alignment, peak discrimination, filtering, alignment, matching, and identification. Visualization matrices containing sample names, m/z–retention time pairs, and peak areas were obtained. Then, multivariate analyses, including principal components analysis, partial least squares discriminant analysis (PLS-DA), and orthogonal PLS-DA, were conducted. Differential metabolites were screened out based on a variable importance in projection value ≥ 1 in the OPLS-DA model and P < 0.05 (Student's t-test). The differential metabolites were mapped to KEGG pathways using the MetaboAnalyst software (https://www.metaboanalyst.ca/), using O. sativa L. ssp. japonica as the model organism. Pathways with P < 0.05 were selected [23].
2.9. Statistical analysis
Student's t-test was used to determine statistically significant differences among WT, osmdh8.2, and OsMDH8.2-OX samples in each experiment.
3. Results
3.1. NADP-MDH gene in rice
MDH, a key enzyme in the C4 carbon concentrating-mechanism pathway, is involved in plant tricarboxylic acid and glyoxylate cycles and regulates the synthesis of organic ammonia compounds to alleviate stress [29]. To gain knowledge about MDH genes in rice, we constructed a phylogenetic tree. We found only one NADP-MDH gene in rice (LOC_Os08g44810), OsMDH8.2, which was found to be homologous to the NADP-MDH genes of Zea mays L. and Sorghum bicolor L. among monocotyledonous crops (Fig. 1a) [30].
Fig. 1.
Expression pattern of the rice malate dehydrogenase Gene OsMDH8.2. (a) NADPH—CLMDH analysis of phylogenetic tree among Zea mays L., Sorghum bicolor L., Brachypodium distachyon L., Triticum aestivum L. and Oryza sativa L. in Monocotyledons crops. (c-f) GUS-staining of transgenic plants expressing OsMDH8.2-GUS fusion protein. b Leaf blade. Bar = 20 µm. c Stem. Bar = 2 mm. d Mature spikelet. Bar = 500 µm. e Inner organs of spikelet. Bar = 1 mm. f seed of 2 days after germination.
3.2. OsMDH8.2 is a key gene in the response to high-temperature stress
We screened two rice (japonica cultivar Dongjin) T-DNA insertion mutant lines, osmdh8.2–1 (KO-1) and osmdh8.2–2 (KO-2) . In the osmdh8.2–1 mutant, a promoterless GUS reporter gene present in the T-DNA generated an OsMDH8.2-GUS fusion transcript that could be PCR-amplified using a primer within the first exon of OsMDH8.2 and another primer in GUS (Fig. S1A). Sequencing of the PCR product revealed that OsMDH8.2 was fused in frame with the GUS transcript, generating a fusion protein. This enabled us to examine the OsMDH8.2 expression pattern by analyzing reporter expression. Histochemical GUS activity assays indicated that OsMDH8.2 was expressed in mesophyll cells of the leaf blade, stem, spikelets, and germinated seeds (Fig. 1b–f), which was in line with RiceXPro data (Fig. S1).
We grew osmdh8.2 mutant plants in pots and transferred them to a growth chamber at 40 °C for 7 days at the reproductive stage. The temperatures of the negative control treatment (CT) and heat treatment (HT) were set as shown in Fig. 2a. Compared with those of WT plants, the seed setting rate and 1000-grain weight (including hulls) of the mutant plants were decreased by ∼4% and 15.52%–17.03%, respectively (Fig. 2b, c). High-temperature treatment reduced the seed setting rate and 1000 grain weight of osmdh8.2 mutant plants further by ∼70.37% and 80.88%–82.73%, respectively (Fig. 2d–e). We also constructed transgenic OsMDH8.2 overexpression plants, OsMDH8.2-OX-1 (OX-1) and OsMDH8.2-OX-2 (OX-2), driven by the cauliflower mosaic virus 35S promoter (Fig. S2), and subjected them to control and heat treatments. Interestingly, the seed setting rate and 1000-grain weight of the OsMDH8.2 overexpression lines did not significantly differ from those of WT plants in the control and heat treatments (Fig. 2b–e). These findings indicated that OsMDH8.2 is involved in resilience to high-temperature stress.
Fig. 2.
Phenotypes of osmdh8.2 mutants and OsMDH8.2-OX plants. (a) The temperature of negative control (NT) and heat treatment (HT) in a day. (b-d) Phenotypes of osmdh8.2 mutants and OsMDH8.2-OX plants compared with WT under the 40 °C heat treatment for 5 days. b,. seed setting rate under the negative control; c, 1000 grain weight (with hull) under the negative control, d, seed setting rate under the 40 °C heat treatment for 5 day; e, 1000 grain weight (with hull) under the 40 °C heat treatment for 5 day. Error bars represent STDEV of at least 5 samples. Student's t-test was used for statistical analysis. *, P < 0.05; **, P < 0.01.
3.3. OsMDH8.2 affects photosynthetic activity via peroxidase activity under heat stress
To analyze the physiological heat-tolerance mechanism of OsMDH8.2-OX plants, we measured the plant canopy temperature, which is jointly determined by crop genetic characteristics and environmental conditions [31], in the transgenic lines and WT. We found that the canopy temperature of the osmdh8.2 mutants was 35.9 °C on average, which was higher than that of WT plants (34.9 °C) (Fig. 3a–c). In OsMDH8.2-OX lines exposed to heat stress for 3 days, it was reduced by approximately 0.5 °C (Fig. 3a–c). However, there was no obvious difference in heat stress among OsMDH8.2 lines exposed to heat stress for 5 days (Fig. S3). We further found that the surface temperature of the flag leaf was similar to the plant canopy temperature (Fig. 3d).
Fig. 3.
OsMDH8.2 is a key gene response to high temperature stress. (a-b) Plant canopy temperature under the negative control for 3 days. (c) Plant canopy temperature under the 40 °C heat treatment for 3 days. (d) stomatal opening under the negative control for 3 days. (e) stomatal opening under the 40 °C heat treatment for 3 days. (f) stomatal opening under the 40 °C heat treatment. (g) Leaf blade temperature under the 40 °C heat treatment. (h-j) Photosynthesis analysis under the 40 °C heat treatment for 3 days or 5 days. h, Transpiration rate of the flag leaf under the 40 °C heat treatment for 3 days or 5 days. i, Stomatal conductance of the flag leaf under the 40 °C heat treatment for 3 days or 5 days. j, Intercellular carbon dioxide concentration of the flag leaf under the 40 °C heat treatment for 3 days or 5 days. Error bars represent STDEV of at least 5 samples. Student's t-test was used for statistical analysis. *, P < 0.05; **, P < 0.01.
Stomata are key organs responsible for gas and water exchange between the plant and the environment, and they affect the plant temperature. OsMDH8.2 did not affect stomatal numbers, but it did affect stomatal opening (Fig. S4). After exposure to heat stress for 3 days, the degree of stomatal opening was increased in WT and osmdh8.2 mutant plants, but decreased in the OsMDH8.2-OX lines (Fig. 1n–o, r). After 5 days of heat stress, the degree of stomatal opening in WT and OsMDH8.2-OX lines was decreased (Fig. S4), whereas it was further increased in the osmdh8.2 mutant lines to maintain stomatal opening (Fig. S4). After 3 days of heat stress, the net photosynthetic rate and intercellular carbon dioxide concentration in the flag leaf in osmdh8.2 increased rapidly, and they were recovered at 5 days (Fig. 3f, g). In WT and OsMDH8.2-OX lines, the net photosynthetic rate and intercellular carbon dioxide concentration in the flag leaf were not affected at 3 days, but they were decreased at 5 days (Fig. 3f, g). Furthermore, the transpiration rate and stomatal conductance increased rapidly in the mutant lines, but the increase was the slowest in the overexpression lines (Fig. 3f, g). These results indicated that OsMDH8.2 is involved in the regulation of the plant surface temperature via stomatal opening, which further affects the photosynthesis activity.
An increased leaf surface temperature induces oxidative stress [15]. We found that H2O2 levels in leaf blade were not affected by 3 days of heat treatment, but were reduced after 5 days in WT and OsMDH8.2-OX plants (Fig. 4b). MDA, SOD, POD, and APX activities in osmdh8.2 mutants were increased on day 3, but decreased after 5 days of heat stress (Fig. 4). CAT was not obviously changed (Fig. 4e). In OsMDH8.2-OX plants, CAT activity was induced in both the negative control and heat stress treatments, whereas MDA, SOD, POD, and APX activities were not affected (Fig. 4a–f). These data demonstrated that OsMDH8.2 is involved in the regulation of CAT activity under heat stress to maintain the H2O2 concentration. Therefore, rice may induce MDA, SOD, POD, and APX activities.
Fig. 4.
OsMDH8.2 maintains photosynthetic activity via peroxidase pctivity under heat stress. (a-f) ration Antioxidant reduction capacity of the flag leaf at 3 days and 5 days between WT and OsMDH8.2 over-expression after the 40 °C heat treatment. a, MDA; b, H2O2; c, APX; d, POD; e, CAT; f, SOD. Error bars represent STDEV of at least 5 samples. Student's t-test was used for statistical analysis. *, P < 0.05; **, P < 0.01.
3.4. Transcriptome and metabolome analyses of plants under heat stress
To determine how OsMDH8.2 responds to heat stress, we performed transcriptome and metabolome analyses of flag leaf blades of OsMDH8.2-OX and WT plants after 3-day heat treatment. We identified 19, 502 annotated genes in total. Compared to those in WT plants, 113 genes had at least two-fold higher transcript levels and 93 genes had at least two-fold lower transcript levels in OsMDH8.2-OX plants (Fig. S5A, B). The differentially expressed genes in OsMDH8.2-OX plants were enriched in starch and sucrose metabolism, pyruvate metabolism, plant photosynthesis carbon fixation, ascorbic acid and aldonate metabolism, glutathione metabolism, plant hormone signal transduction, and other metabolic pathways (Fig. S5C; Table S2), as well as heat stress-mediating genes, such as rice annexin 3 (OsANN3), rice annexin 4 (OsANN4), heat shock protein 17.9A (Oshsp17.9A), heat shock protein 18 (OsHsp18.0), and heat shock protein 82A (Oshsp82A) (Figs. 5a and S6).
Fig. 5.
Transcriptome and metabolome association analysis under heat stress. (a) Enrichment chord analysis; (b) expression profiles and VIP of metabolites; (c) key pathway gene or metabolites number under transcriptome and metabolome association analysis; (d) number of transcription/metabolites pathways; (e) Metabolites content about tricarboxylic acid and Glyoxylate cycles in WT and OsMDH8.2-OX-1 at 3 days after the 40 °C heat treatment. (f) Model of OsMDH8.2 functions in Glyoxylate and dicarboxylate metabolism under heat stress. Black cycle indicates Glyoxylate cycle metabolism, Green cycle indicates dicarboxylate cycle metabolism. Blue arrow indicates content decreased; purple arrow indicates content.
Metabolome analysis identified a total of 1223 metabolites. Fifty-eight metabolites were significantly differentially accumulated in OsMDH8.2-OX vs. WT plants, including 28 upregulated and 10 downregulated metabolites (Fig. S7, S8; Table S3). KEGG analysis revealed that the differentially accumulated metabolites were mainly involved in oxidative phosphorylation, glyoxylic acid and dicarboxylic acid metabolism, butyric acid metabolism, aminoacyl tRNA biosynthesis, nitrogen metabolism, and amino acid biosynthesis and metabolism (Fig. 5b and S8; Table S4).
Through further analysis of the combined transcriptome and metabolome data, we identified eight genes and six metabolites in four differentially enriched KEGG pathways, including glycerophospholipid metabolism, glyoxylate and dicarboxylate metabolism, glutathione metabolism, and butanoate metabolism (Fig. 2c, d). OsMDH8.2 (LOC_Os08g44810) catalyzes malic acid into oxalacetic acid, which participates in the citrate cycle, cysteine and methionine metabolism, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, carbon fixation in photosynthetic organisms, metabolic pathways, biosynthesis of secondary metabolites, and carbon metabolism. In the citrate cycle/glyoxylate and dicarboxylate metabolism pathway, we found that malic acid, citrate acid, and isocitric acid contents were decreased, whereas that of succinate acid was increased (Fig. 5e). Meanwhile, amino acid metabolism was induced, particularly, phosphoenolpyruvate transition into phenylalanine, which caused the contents of phenylalanine, trans-cinnamic acid, benzoic acid, and salicylic acid to increase (Fig. 5e, f). The transcript levels of phenylalanine ammonia lyase genes (OsPALs), which encode enzymes that catalyze the transition of phenylalanine into trans-cinnamic acid, were also increased (Fig. 5e, f).
4. Discussion
4.1. OsMDH8.2 plays a vital role in the evolutionary adaptation of rice to heat stress
The rice genome contains 12 MDH members, OsMDH1–OsMDH12.1, which can be divided into three subgroups. OsMDH4.1, OsMDH10.1, and OsMDH8.2 in group I have four types of motifs; OsMDH6.1 and OsMDH2.1 in group II have two types of motifs, and the remaining genes have seven types of motifs [30]. However, only OsMDH8.2 is an NADP-malate dehydrogenase gene, and it is expressed at higher levels in the vegetative stage than in the reproductive stage. The expression of the OsMDH8.2 homologs OsMDH10.1 and OsMDH4.1 is maintained at similar levels throughout the life cycle. It has been reported that NADP-MDH activity in C4 plants is approximately 10 times higher than that in C3 plants [32]. We found that at 40 °C, OsMDH8.2-OX transgenic plants closed their stomata and lowered their intracellular CO2 concentrations, transpiration rate, and stomatal conductance to maintain the plant surface temperature. Meanwhile, heat stress promoted glyoxylate and dicarboxylate metabolic activity, while decreasing citrate cycle activity, to provide more energy and CO2 for photosynthesis. The increase in temperature resulted in stomatal closure, a reduction in the intracellular CO2 concentration, and enhanced respiration, decreasing the ratio of carboxylation reactions to oxygenation reactions in the process of photosynthetic carbon assimilation, resulting in photorespiration to release more energy [33]. Overexpression of ZmNADP-MDH led to increases in chlorophyll and protein contents, and reductions in the production of H2O2 and MDA via membrane lipid peroxidation [34]. The C4 pathway evolved independently in angiosperm families and genera, and the transformation from the C3 pathway to the C4 pathway was relatively simple [17]. Therefore, environmental high temperatures may have been one of the main driving forces behind the evolution of the C4 pathway, which would explain why C4 plants are more abundantly found in tropical and subtropical areas.
4.2. OsMDH8.2 responses to heat stress involving amino acid metabolic pathways
MDHs catalyze the reversible interconversion of malate and oxaloacetate using NAD(H)/NADP(H) as a cofactor, participating in the citrate cycle and glyoxylate and dicarboxylate metabolic pathways. Under heat stress, OsMDH8.2-OX plants induced leaf stomatal closure to maintain surface temperature by reducing gas exchange with the ambient air. OsMDH8.2 mediated peroxidase reactions early in the response to heat stress to mitigate cell damage induced by higher temperatures. Meanwhile, photorespiration was enhanced in OsMDH8.2-OX plants, whereas citrate cycle metabolic activity was reduced. The CO2 released by photorespiration can be immediately refixed through photosynthesis, which can protect the photosynthetic reaction center. Based on the transcriptome and metabolome analysis results, we consider that photorespiration may be the key metabolic pathway in response to heat stress. The tricarboxylic acid and glyoxylic acid cycles partially overlap from malic acid to isocitric acid, and the induced photorespiration metabolic pathway resulted in amino acid metabolic pathway enhancement. The enrichment of both the glutathione and salicylic acid metabolic pathways can alleviate heat stress through peroxidase activity and stomatal closure, respectively. In the glutathione metabolic pathway, the content of 2-(S-glutathionyl)acetyl glutathione was increased, and the transcript levels of OsGSTU11 (encoding glutathione S-transferase 11), APX2 (encoding ascorbate peroxidase gene), and OsDHAR1 (encoding cytosolic dehydroascorbate reductase) were increased to scavenge free radicals and thus maintain metabolic activity. The transcript levels of Oshsp17.9A (encoding a class I low-molecular-weight heat shock protein 17.9) (Fig. S10) and OsHsp18.0 (encoding a class II small heat shock protein), which protect plant tissues against high-temperature injury by inducing stomatal closure to maintain the leaf surface temperature were increased.
Based on our findings in the present study, we suggest that OsMDH8.2 mediates both carbon assimilation and carbon alienation metabolic pathways. OsMDH8.2 has dual functions under heat stress in preventing damage via stomatal closure and increased peroxidase activity and providing the photosynthetic raw material (CO2) from photorespiration. Our findings provide novel insights into the adaptive evolution from C3 plants to C4 plants.
Declaration of competing interest
The authors declare that they have no conflicts of interest in this work.
Acknowledgments
This study was supported by the Natural Science Foundation of Jiangsu Province (BK20190889), the China Postdoctoral Science Foundation (2019M660130), a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). We would like to thank Editage (www.editage.cn) for English language editing.
Biographies
Min Jiang is an associate professor in Yangzhou University. His current research interests include agroecology and physiological and ecological mechanisms of rice cultivation.
Yunfei Wu received his doctor's degree from KyungHee University in College of Life Science in 2018. He is in College of Bioscience and Biotechnology in Yangzhou University as an associate professor. His research interests include crops nutrition, especially in carbon and nitrogen transport, assimilation and metabolism. In past 5 years, his papers published in Molecular Plant, ISME Communications, Plant Physiology and so on.
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.fmre.2023.12.010.
Appendix. Supplementary materials
References
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