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First published online June 5, 2009; 10.1104/pp.109.135327 Plant Physiology 150:1972-1980 (2009) © 2009 American Society of Plant Biologists OPEN ACCESS ARTICLE
Metabolic Pathways Involved in Cold Acclimation Identified by Integrated Analysis of Metabolites and Transcripts Regulated by DREB1A and DREB2A1,[W],[OA]Biological Resources Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Ibaraki 305–8686, Japan (K.M., S.K., K.Y., Y.S., K.Y., S.M., K.Y.-S.); Kazusa DNA Research Institute, Kisarazu, Chiba 292–0818, Japan (M.T., Y.M., R.S., H.S., K. Saito, D.S.); Laboratory of Plant Molecular Physiology, Graduate School of Agricultural and Life Sciences, University of Tokyo, Bunkyo-ku, Tokyo 113–8657, Japan (S.K., K.Y., Y.S., S.M., K.Y.-S.); Gene Discovery Research Group, RIKEN Plant Science Center, Tsukuba, Ibaraki 305–0074, Japan (K.U., M.F., K. Shinozaki); and Department of Molecular Biology and Biotechnology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 263–8522, Japan (K. Saito)
DREB1A/CBF3 and DREB2A are transcription factors that specifically interact with a cis-acting dehydration-responsive element (DRE), which is involved in cold- and dehydration-responsive gene expression in Arabidopsis (Arabidopsis thaliana). Overexpression of DREB1A improves stress tolerance to both freezing and dehydration in transgenic plants. In contrast, overexpression of an active form of DREB2A results in significant stress tolerance to dehydration but only slight tolerance to freezing in transgenic plants. The downstream gene products for DREB1A and DREB2A are reported to have similar putative functions, but downstream genes encoding enzymes for carbohydrate metabolism are very different between DREB1A and DREB2A. We demonstrate that under cold and dehydration conditions, the expression of many genes encoding starch-degrading enzymes, sucrose metabolism enzymes, and sugar alcohol synthases changes dynamically; consequently, many kinds of monosaccharides, disaccharides, trisaccharides, and sugar alcohols accumulate in Arabidopsis. We also show that DREB1A overexpression can cause almost the same changes in these metabolic processes and that these changes seem to improve freezing and dehydration stress tolerance in transgenic plants. In contrast, DREB2A overexpression did not increase the level of any of these metabolites in transgenic plants. Strong freezing stress tolerance of the transgenic plants overexpressing DREB1A may depend on accumulation of these metabolites.
Low temperature and dehydration are adverse environmental conditions that affect plant growth and productivity. Many genes have been described that respond to both stresses at the transcriptional level, and their gene products are thought to function in stress tolerance and response even though these stresses are quite different (Thomashow, 1999  ; Zhu, 2002; Shinozaki and Yamaguchi-Shinozaki, 2003; Bartels and Sunkar, 2005). These genes include key metabolic enzymes, late embryogenesis-abundant (LEA) proteins, detoxification enzymes, chaperones, protein kinases, and transcription factors (Thomashow, 1999; Zhu, 2002; Shinozaki and Yamaguchi-Shinozaki, 2003; Bartels and Sunkar, 2005). The cis-acting elements that function in stress-responsive gene expression have been analyzed to elucidate the molecular mechanisms of gene expression in response to these stresses (Yamaguchi-Shinozaki and Shinozaki, 2006). The dehydration-responsive element (DRE), containing the core sequence A/GCCGAC, was identified as a cis-acting element that regulates gene expression in response to both dehydration and cold in Arabidopsis (Arabidopsis thaliana; Yamaguchi-Shinozaki and Shinozaki, 1994). A similar motif was identified as the C-repeat and low temperature-responsive element in promoter regions of low temperature-inducible genes (Baker et al., 1994; Jiang et al., 1996).
Arabidopsis cDNAs encoding the ethylene-responsive element-binding factor/APETALA2 (ERF/AP2)-type DRE-binding (DREB) proteins CBF1, DREB1A, and DREB2A have been isolated by yeast one-hybrid screening (Stockinger et al., 1997
Overexpression of DREB1/CBFs driven by the cauliflower mosaic virus 35S promoter increases stress tolerance to freezing, dehydration, and high salinity in transgenic Arabidopsis (Jaglo-Ottosen et al., 1998
Promoter analysis of DREB1A- and DREB2A-regulated genes and gel mobility shift assays revealed that DREB1A and DREB2A have different DNA-binding specificities. DREB1A has highest affinity for A/GCCGACNT, whereas DREB2A preferentially binds ACCGAC (Maruyama et al., 2004 Here, we performed integrated analysis of both metabolites and transcripts in dehydration-exposed and 35S:DREB2A-CA plants and compared them with those in cold-exposed and 35S:DREB1A plants. We also analyzed the expression of genes involved in carbohydrate metabolism under both cold and dehydration conditions.
Identification of Metabolites in Various Plants We measured metabolites using gas chromatography-time of flight-mass spectrometry (GC-TOF-MS), capillary electrophoresis-mass spectrometry (CE-MS), and liquid chromatography-ion trap-mass spectrometry (LC-IT-MS) in eight kinds of plants: untreated, cold exposed (1 and 4 d), dehydration exposed (2 and 3 d), 35S:DREB1A, 35S:DREB2A-CA, and control plants containing pGreen. In GC-TOF-MS and CE-MS analyses, 254 independent metabolites were identified by retention time indices and specific mass fragments (Supplemental Fig. S1). The levels of 155, 162, 37, and 28 metabolites increased significantly in cold-exposed, dehydration-exposed, 35S:DREB1A, and 35S:DREB2A-CA plants, respectively (Benjamini and Hochberg false discovery rate [FDR]; P < 0.01). The levels of 50, 85, nine, and 38 metabolites decreased significantly in cold-exposed, dehydration-exposed, 35S:DREB1A, and 35S:DREB2A-CA plants, respectively (FDR; P < 0.01; Supplemental Table S1). Venn diagrams illustrate the identified metabolites in the plants (Fig. 1 ; Supplemental Fig. S2). The levels of 102 metabolites increased in both cold-exposed and dehydration-exposed plants. The levels of 17 metabolites increased in both 35S:DREB1A and 35S:DREB2A-CA plants. Most metabolites (89%) that increased in 35S:DREB1A plants also increased in cold-exposed plants. These metabolites contained sugars such as Suc, galactinol, myoinositol, raffinose, and unknown metabolites. Likewise, most metabolites (89%) that increased in 35S:DREB2A-CA plants also increased in dehydration-exposed plants. In this case, these metabolites contained organic acids such as argininosuccinate, fumarate, malic acid, and unknown metabolites. In addition, most metabolites that were almost unchanged in 35S:DREB1A plants were also unchanged in 35S:DREB2A-CA plants; unfortunately, these metabolites are unknown (Fig. 1).
LC-IT-MS analyses showed that accumulation of three secondary metabolites increased significantly in the cold-exposed, 35S:DREB1A, and 35S:DREB2A-CA plants but not in the dehydration-exposed plants (Supplemental Fig. S3). Mass fragment/retention time comparisons revealed these three secondary metabolites as kaempferol 3-[6'-(glucosyl) rhamnoside] 7-rhamnoside, kaempferol 3-glucoside 7-rhamnoside, and kaempferol 3-rhamnoside 7-rhamnoside.
We compared the metabolite profiles of the eight analyzed plants by principal component analysis (PCA; Fig. 2A ; Supplemental Tables S2–S6). The cumulative contribution ratio of the PCA reached 61.4% up to the second principal component (PC2), indicating correct application of PCA to the metabolite profiles of the analyzed plants. The PCA showed the following. First, the first principal component (PC1) reflected increases of metabolites in the eight kinds of plants. The PC1 value of plants exposed to 3 d of dehydration was the highest in the eight kinds of plants. Plants exposed to 4 d of cold had the second highest PC1 value. The PC1 value of untreated plants was similar to that of control plants, and that value was the lowest in the eight kinds of plants. Second, PC2 reflected differences in the variety of metabolites according to different environmental conditions. The PC2 value of cold-exposed plants was positive, but PC2 for dehydration-exposed plants was negative. The PC2 values of both untreated and control plants were nearly zero. Third, the metabolite profile of the 35S:DREB1A plants was similar to that of cold-exposed plants, and the PC2 values of the plants were positive. Fourth, the metabolite profile of 35S:DREB2A-CA plants was similar to that of dehydration-exposed plants, and PC2 values were negative.
We selected representative metabolites for which the eigenvector values were the first and second highest or lowest, and those values are displayed in bar charts (Fig. 2B). The PC1 eigenvector value of metabolite 190 was the highest. The level of metabolite 190 increased significantly in plants exposed to 3 d of dehydration or 4 d of cold. This metabolite was also detected in 35S:DREB1A plants but not in 35S:DREB2A-CA plants. Raffinose had the second highest PC1 eigenvector value. The level of raffinose increased significantly in plants exposed to 3 d of dehydration or 4 d of cold and in 35S:DREB1A plants. The level of raffinose in the 35S:DREB1A plants was the highest of those in the eight kinds of plants. We did not detect raffinose in either untreated or control plants. Raffinose was detectable in 35S:DREB2A-CA plants, but its level was very low compared with 35S:DREB1A plants. Metabolite 70 had the highest PC2 eigenvector value. The level of metabolite 70 increased significantly in both cold-exposed and 35S:DREB1A plants but not in dehydration-exposed or 35S:DREB2A-CA plants. Metabolite 73 had the second highest PC2 eigenvector value. The level of metabolite 73 increased significantly in cold-exposed, 35S:DREB1A, and 35S:DREB2A-CA plants. Metabolite 72 had the lowest PC2 eigenvector value. Metabolite 72 increased significantly in plants exposed to 3 d of dehydration and decreased significantly in both cold-exposed and 35S:DREB1A plants. Metabolite 4 had the second lowest PC2 eigenvector. The level of metabolite 4 increased significantly in plants exposed to 3 d of dehydration. To identify candidates that play vital roles under low-temperature conditions, we tried to select metabolites that were unique to both cold-exposed and 35S:DREB1A plants but were not affected in 35S:DREB2A-CA plants. Seventeen such metabolites were selected, and their values are displayed in bar charts (Fig. 2, B and C). Among the 17 metabolites, 13 are unknown and four are myoinositol (metabolite 247), galactinol (metabolite 239), raffinose (metabolite 251), and Suc (metabolite 253). The levels of metabolites 55, 70, 92, 155, 156, and 189 increased significantly in both cold-exposed and 35S:DREB1A plants but not in dehydration-exposed plants. The levels of raffinose, galactinol, myoinositol, Suc, and metabolites 19, 80, 85, 100, 193, 200, and 209 increased significantly in not only cold-exposed and 35S:DREB1A plants but also in dehydration-exposed plants. Among the 17 metabolites, raffinose, galactinol, myoinositol, Suc, and metabolite 70 were detectable in 35S:DREB2A-CA plants at very low levels; however, the other 12 metabolites were undetectable in 35S:DREB2A-CA plants.
To identify cold- or dehydration-responsive genes and downstream genes of DREB1A and DREB2A, we performed array analyses using an Agilent Arabidopsis 2 Oligo Microarray. In the cold-exposed, dehydration-exposed, 35S:DREB1A, and 35S:DREB2A-CA plants, 945, 2,641, 259, and 373 genes were significantly up-regulated, respectively (FDR; P < 0.05 and fold change [FC] > 2; Supplemental Tables S7–S12). In contrast, 732, 2,999, 174, and 234 genes were down-regulated significantly in the cold-exposed, dehydration-exposed, 35S:DREB1A, and 35S:DREB2A-CA plants, respectively (FDR; P < 0.05 and FC <
Expression Patterns of Genes for Starch-Degrading Enzymes and Sugar Alcohol Synthases in 35S:DREB1A Plants Were Similar to Those in Plants Exposed to Cold for 4 d
We reconstructed a metabolic enzyme database for Arabidopsis. First, we downloaded all of the amino acid sequence data from The Arabidopsis Information Resource and searched enzyme motifs using the HMMER program (Eddy, 1998
Expression levels of genes encoding starch-degrading enzymes, Suc metabolism enzymes, and sugar alcohol synthases correlated positively with the accumulation of monosaccharides, disaccharides, trisaccharides, and sugar alcohols in cold- and dehydration-exposed plants (Fig. 4
). Genes encoding starch-degrading enzymes, such as
We then focused on genes for starch-degrading enzymes and sugar alcohol synthase (Fig. 5A ). We confirmed expression levels of these genes using quantitative reverse transcription (qRT)-PCR (Fig. 5B). The genes for starch-degrading enzymes were divided into two groups: one included cold-inducible genes, and the other included dehydration-inducible genes. Expression of AMY3 and BAM3/BMY8 increased specifically under cold conditions. In contrast, expression of AMY2, BAM1/BMY7, BAM2/BMY9, BAM6, and BAM9/BMY3 increased specifically under dehydration conditions. Furthermore, most of these genes were regulated oppositely under dehydration and cold conditions (Fig. 5). Whereas expression of AMY3, BAM3/BMY8, PHS1/PHO1, PHS2/PHO2, ISA3, DPE1, DPE2, and GWD1/SEX1 increased under cold conditions, these transcripts decreased under dehydration conditions. In addition, expression of BAM1/BMY7, BAM6, and BAM9/BMY3 increased under dehydration conditions but decreased under cold conditions. Within the galactinol synthase gene family, expression of AtGolS3 and AtGolS2 increased significantly in cold- and dehydration-exposed plants, respectively (Fig. 5). Expression patterns of genes for starch-degrading enzymes and sugar alcohol synthase in 35S:DREB1A plants were similar to those in plants exposed to cold for 4 d (Fig. 5). However, expression of these genes did not increase in 35S:DREB2A-CA plants, except for AtGolS3 and AtGolS2 (Fig. 5).
Previously, we showed that overexpression of DREB1A improved both dehydration and freezing stress tolerance, whereas overexpression of DREB2A-CA improved dehydration stress tolerance but not freezing tolerance in transgenic plants (Sakuma et al., 2006a ). In this study, we used microarrays to analyze genes that are regulated by DREB1A and DREB2A under the same conditions as used for metabolite analyses and found that 259 and 373 genes were significantly increased in 35S:DREB1A and 35S:DREB2A-CA plants, respectively, in comparison with vector control plants (Fig. 1). The putative functions of most of the DREB1A- and DREB2A-targeted genes were similar, but certain genes were specific to DREB2A, such as molecular chaperones and enzymes for toxin catabolic processes. We also found that most putative functions of DREB1A downstream gene products were included in those of the DREB2A downstream gene products, but the number of DREB1A downstream genes encoding enzymes for carbohydrate metabolism was much higher than that of DREB2A downstream genes. Thus, expression of these DREB1A-specific downstream genes encoding enzymes for carbohydrate metabolism may be involved in freezing tolerance in 35S:DREB1A plants.
We aimed to detect many kinds of metabolites that are regulated by abiotic stress using GC-TOF-MS, LC-IT-MS, and CE-MS. GC-TOF-MS and LC-IT-MS are suitable for analysis of polar metabolites and secondary metabolites, respectively. CE-MS was used to analyze charged metabolites. We identified 254 independent metabolites using GC-TOF-MS and CE-MS. Among them, 61.0%, 63.7%, 14.5%, and 11.0% of metabolites increased significantly in cold-exposed, dehydration-exposed, 35S:DREB1A, and 35S:DREB2A-CA plants, respectively (Fig. 1). Detected metabolites were compared by PCA (Fig. 2A). The metabolite profiles were classified into three groups according to plant growth conditions: cold, dehydration, and untreated/control. The metabolite profile of the 35S:DREB1A plants was similar to that of the cold class but not to that of the dehydration class. The metabolite profile of the 35S:DREB2A-CA plants resembled that of the dehydration class more than that of the cold class. Because 35S:DREB1A plants, but not 35S:DREB2A-CA plants, were freezing tolerant, the metabolites for which the level increased in the cold-exposed and 35S:DREB1A plants but not in the 35S:DREB2A-CA plants probably participate in improvement of freezing stress tolerance. Seventeen metabolites were selected as candidates. Among them, 13 are unknown and four are myoinositol, Suc, galactinol, and raffinose. Although both transgenic plants showed strong dehydration tolerance, the metabolite profiles in these plants were very different. These results suggest that the dehydration-specific metabolites appearing on the negative side of the PC2 axis may not be important for dehydration-specific tolerance in 35S:DREB1A plants. Several unknown metabolites that increased under both cold and dehydration conditions and also in both transgenic plants might be involved in dehydration tolerance in the transgenic plants (Supplemental Table S5). We determined using LC-IT-MS that accumulation of only three secondary metabolites increased significantly in the cold-exposed and 35S:DREB1A plants (Supplemental Fig. S3). These secondary metabolites also increased in the 35S:DREB2A-CA plants but not in the dehydration-exposed plants. Korn et al. (2008) Our integrated analysis of metabolites and transcripts indicated that expression of many genes encoding starch-degrading enzymes, Suc metabolism enzymes, and sugar alcohol synthases changed dynamically and resulted in the accumulation of monosaccharides, disaccharides, trisaccharides, and sugar alcohols, including Suc, myoinositol, galactinol, and raffinose, in cold-exposed and dehydration-exposed plants. Because most of these genes are targets of DREB1A, expression of these genes also changed dynamically and the metabolites also accumulated in the 35S:DREB1A plants. In contrast, because these genes are not regulated by DREB2A (except the genes for galactinol synthase and raffinose synthase), none of these metabolites accumulated in 35S:DREB2A-CA plants (Fig. 4). Expression of these genes and accumulation of these metabolites correlated with differences in freezing tolerance between the 35S:DREB1A and 35S:DREB2A-CA plants. These results suggest that dynamic transcriptional regulation of the carbohydrate network is necessary for the accumulation of specific carbohydrates, such as Suc, galactinol, myoinositol, and raffinose, and that the accumulation of these carbohydrates may be important for improving freezing tolerance in transgenic plants overexpressing DREB1A. Moreover, it is likely that DREB1A is one of the major factors regulating carbohydrate metabolism under cold conditions, whereas DREB2A is not.
A cold-inducible galactinol synthase, AtGolS3, plays a key role in the accumulation of galactinol and raffinose under cold conditions (Taji et al., 2002
Plant Materials and Growth Conditions Both wild-type and transgenic Arabidopsis (Arabidopsis thaliana) plants were grown in plastic pots filled with peat moss for 3 weeks (principal growth stage 1.07–1.08) under a 16-h-light/8-h-dark regimen (40 ± 10 µmol photons m–2 s–1) at 22°C. The light intensity was the same at 22°C and 4°C. Plants were harvested 2 h later after lights were turned on. For cold treatment, 3-week-old plants were transferred from 22°C to 4°C and were grown for 1 or 4 d. For dehydration treatment, 3-week-old plants were grown for 2 or 3 d without watering. To obtain accurate results, we carefully raised single plants in petri dishes, each containing an equal amount of soil. Soil moisture contents were calculated from soil dry weight. Untreated, the soil moisture content was 84.3%. Under dehydration, on the 2nd d, the soil moisture content was 51.1%. Under dehydration, on the 3rd d, the moisture content was 11.6% (Supplemental Fig. S5).
GC-TOF-MS Analysis
CE-MS Analysis
LC-IT-MS Analysis
Microarray and qRT-PCR Analyses
Cold- or dehydration-responsive genes and downstream genes of DREB1A and DREB2A were annotated according to results of motif (HMMER) and similarity (PSI-BLAST) searches and were classified according to Gene Ontology annotation at The Arabidopsis Information Resource, KEGG, and Kappa-view.
The following materials are available in the online version of this article.
We are grateful to E. Ohgawara, K. Murai, E. Kishi, K. Amano, and H. Sado for their excellent technical support and to M. Toyoshima for skillful editorial assistance. We also thank the Rice Genome Resource Center at the National Institute of Agrobiological Sciences for use of the 22 K microarray analysis system and the technical support provided by Dr. Y. Nagamura and R. Motoyama. Received January 5, 2009; accepted June 3, 2009; published June 5, 2009.
1 This work was supported by project grants from the Ministry of Agriculture, Forestry, and Fisheries of Japan, grants-in-aid from the Ministry of Education, Culture, Sports, Science, and Technology of Japan, and project grants from the New Energy and Industrial Technology Development Organization of Japan.  The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Kazuko Yamaguchi-Shinozaki (kazukoys{at}jircas.affrc.go.jp).
[W] The online version of this article contains Web-only data.
[OA] Open Access articles can be viewed online without a subscription. www.plantphysiol.org/cgi/doi/10.1104/pp.109.135327 * Corresponding author; e-mail kazukoys{at}jircas.affrc.go.jp.
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ABSTRACT
RESULTS
and β) and 35S:DREB2A-CA (
; Supplemental Tables S7–S12). Of the 259 up-regulated genes in 35S:DREB1A plants, 125 were unknown and the other gene products included dehydrin, LEA protein, starch-degrading enzymes, transcription factors, and protein kinases. Of the 373 up-regulated genes in 35S:DREB2A-CA plants, 158 were unknown and the other gene products included dehydrin, LEA protein, HS protein family, enzymes for toxin catabolic processes, transcription factors, and protein kinases (
-fold increase. Dark blue squares show less than