Arabidopsis ecotype Columbia (Col-0) was used. The mutant cad2-1 (Cobbett et al., 1998) was used as an allelic mutant of pad2-1 (Parisy et al., 2007). Further, 35S::GSH1 transgenic plants, 7-5 and 13-6 (Cheng et al., 2015), were also used to evaluate the shoot phenotypic changes. Plants other than those exposed to MV stress and P-lim were grown in Murashige and Skoog agar medium. Sterilized seeds were stratified at 5°C for 2 days and then sown on Murashige and Skoog medium containing 1% sucrose. Oxidative stress was produced by adding 0.05 μM MV to the Murashige and Skoog medium. The low phosphorus condition was created using P-lim medium in which the phosphate concentration was 20% of that in the Murashige and Skoog medium. Seedlings of Arabidopsis Col-0 and mutants were cultivated in growth chambers at 22°C under 16-h light/8-h dark conditions for 18 days (light strength, 80 μmol⋅m^-2⋅s^-1 of the photosynthetic photon flux). GSH1-overexpression lines were cultivated under the same condition for 20 days.

Harvested aerial parts of WT and mutant plants (n = 8, biological replicates) were frozen immediately in liquid nitrogen to quench enzymatic activity. Primary and secondary metabolites were extracted according to previously established methods; we performed GC-TOF-MS analysis (Kusano et al., 2007a,b) for primary metabolites and LC-q-TOF-MS analysis for secondary metabolites (Matsuda et al., 2009; Nakabayashi et al., 2014) and lipids (Kimbara et al., 2013). The details of metabolite profiling are shown in Supplementary Document S1. Principal component analysis (PCA) was performed using SIMCA-P 12.0 (UmetricsAB¹) with log₁₀ transformation and autoscaling. For stress treatment- and genotype comparison, differentially abundant metabolites were identified using linear regression models in the LIMMA method (Smyth, 2005), which yields false discovery rate (FDR)-adjusted p-values for multiple testing problems (Benjamini and Hochberg, 1995). The significance level was set at FDR < 0.05. Our data are reported in a manner compliant with the guidelines recommended by Fernie et al. (2011), as shown in Supplementary Table S4. VENNY² was used to generate the Venn diagram.

Plant samples (n = 3, biological replicates) were frozen immediately in liquid nitrogen and stored at -80°C until analysis. Each frozen sample was extracted with a 20-fold amount of solvent [methanol/water (8:2 v/v)]. Aerial parts were mashed for 6 min in a 2-mL tube by using a mixer mill (MM400; Retsch, Haan, Germany) at a frequency of 20 Hz. The mixture was centrifuged at 15,000 rpm, and then supernatant containing glutathione was taken out. The supernatant was used for the quantification of GSH and GSSG by using ultra high performance liquid chromatography (UHPLC-MS; Nexera, Shimadzu, Kyoto, Japan) coupled with a triple quadrupole mass spectrometer (TSQ Quantum Ultra Thermo; Fisher Scientific, San Jose, CA, United States). UHPLC separation was performed on an Acquity UPLC BEH C18 column (50 mm × 2.1 mm, 1.7 μm particle size; Waters) maintained at 40°C. Other LC conditions were as follows: flow rate, 0.4 mL/min; injection volume, 5 μL (GSH) and 20 μL (GSSG); solvent system, acetonitrile (0.1% formic acid):water (0.1% formic acid); and gradient program, 2:98 v/v at 0–3 min, 98:2 at 7–10 min. For mass spectrometry (MS) detection, heated-electrospray ionization was used as the ionization source in the positive mode. Other conditions were as follows: sheath gas pressure, 50 arbitrary units; ion sweep cone gas, 0 arbitrary units; vaporizer temperature, 450°C; aux gas pressure, 20 arbitrary units; and spray voltage, 3,000 V. Selected reaction monitoring (SRM) was used to quantify GSH and GSSG. SRM was conducted by scanning the product ions at m/z 162.070 obtained from the fragmentation of the parent ions at m/z 308.167 of GSH. SRM was conducted by scanning the product ions at m/z 231.010 obtained from the fragmentation of the parent ions at m/z 613.244 of GSSG. The collision energy for MS/MS was 27 V. Identities were confirmed by comparing the MS/MS spectra with authentic standards [reduced glutathione (GSH, 97.0%) and oxidized glutathione (GSSG, 98.0%)] purchased from Tokyo Chemical Industry (Tokyo, Japan). Statistical data analysis and plotting were performed using Microsoft Excel and the unpaired Welch’s t-test by using the R-function t.test().³

We performed analysis of mRNA as described previously (Kusano et al., 2011). Briefly, total RNA was extracted from the 18-day-old aerial part of each mutant and WT sample using the RNeasy plant mini kit (Qiagen⁴) according to the manufacturer’s instructions. Three independent hybridizations were performed using the Affymetrix ATH1 GeneChip microarray, according to the manufacturer’s instructions (Affymetrix).⁵ A single biological replicate was used for each hybridization. Preprocessing and normalization/summarization of all CEL files were performed using R, the Bioconductor (Gentleman et al., 2004), and a robust multi-chip average (RMA) (Bolstad et al., 2003; Irizarry et al., 2003). The quality of the GeneChip data was assessed using the AFFYPLM package (Bolstad et al., 2005). The annotation of each gene in the CSV file ATH1-121501.na31.annot.csv (downloaded in April 2012)⁶ released by Affymetrix was used. For stress treatment- and genotype comparison, differentially expressed genes were detected using linear regression models in the LIMMA method (Smyth, 2005), which provides FDR-adjusted p-values for multiple testing problems (Benjamini and Hochberg, 1995). The significance level was set at FDR < 0.05. Genevenn⁷ was used to generate the Venn diagram.

The transcript profiles were visualized using MAPMAN (v3.5.1R2) (Thimm et al., 2004) to inspect coordinated changes in metabolism and other biological process. GO enrichment analysis was performed using Cytoscape (v3.2.1) App BiNGO (Maere et al., 2005). The resulting enriched GO categories were visualized using the Enrichment Map (v2.2.0) (Merico et al., 2010; Isserlin et al., 2014) and AutoAnnotate (Kucera et al., 2016).

Previously, we reported that, under no-stress condition, the shoot phenotype of the pad2-1 mutant was similar to that of WT plants (background, Col-0), but showed significant changes in the levels of primary metabolites (Fukushima et al., 2014) (Supplementary Figure S1 and Table S1). To further understand the relationship between the GSH1 mutation related to glutathione content and mild abiotic stress, we selected two GSH1 mutants, pad2-1 and cad2-1, and two GSH1-overexpressing plants, 7-5 and 13-6 (Cheng et al., 2015). We first assessed the phenotypic changes of individual WT plants and the GSH1 mutants under different concentrations of MV (Supplementary Figure S2). Our current experimental setup was based on these pilot experiments and findings from MV treatment to isolate MV-resistant mutants in the previous studies [for example, see (Fujibe et al., 2004; Sukrong et al., 2012; Egert et al., 2013)]. GSH1 mutants and GSH1-overexpressing plants were grown on untreated medium (control condition), on medium containing a low concentration (0.05 μM) of MV compared to that used in previous studies [e.g., 10 μM MV treatment in AtGenExpress (Kilian et al., 2007)], or on P-lim medium that had a phosphate concentration of 20% of that in the medium (Supplementary Figure S3). We evaluated the shoot phenotypic changes in the GSH1 mutants (Figure 1) and GSH1-overexpressing plants (Supplementary Figure S4). No plants exhibited chlorosis and/or necrosis attributable to treatment with the low MV medium (Figure 1A and Supplementary Figure S4A). MV treatment of the mutants and WT plants resulted in an approximately 50% growth reduction (Figure 1B). The fresh weight of the aerial parts of the mutants grown under control- and P-lim conditions was approximately 70% of that of the WT plants. These findings suggest that, under the no-stress condition, the GSH1 mutations were silent at the aerial parts, although the mutants were shown to have impaired lateral root density (Schnaubelt et al., 2013, 2015). Therefore, since the applied stress treatments did not result in severe growth inhibition in the assayed plants, we considered them as mild stress treatments (Figures 1A,B and Supplementary Figure S2).

The GSH and GSSG contents were lower in the mutant than in the WT plants under the no-stress condition (GSH, approximately 20%; GSSG, approximately 50%). Changes in GSH and GSSG contents differed with stress conditions (Figures 1C,D). The level of GSH was decreased significantly in WT plants subjected to MV stress, whereas that of GSSG was increased (arrows in Figures 1C,D); the GSH and GSSG contents were almost identical under the P-lim and control conditions. The two GSH1-overexpressing plants manifested no changes at the phenotypic level under the no-stress condition (Supplementary Figure S4A). The fresh weight of the shoot biomass of the GSH1 mutants, WT plants, and transgenic lines grown under the two mild stress conditions showed similar trends (Supplementary Figure S4B). Increased levels of GSH and GSSG failed to rescue the shoot biomass of the GSH1-overexpressing plants under the MV condition (Supplementary Figures S4C,D). The GSH:GSSG ratio can be regarded as an indirect determinant of oxidative stress; the GSSG level increases and the GSH:GSSG ratio decreases, when the plant cells are exposed to oxidative stress (Queval et al., 2007; Noctor et al., 2012). Under the MV and P-lim conditions, the measured GSH:GSSG ratio was lower in the two GSH1 mutants than in the WT plants (Figure 1E). The GSH:GSSG ratio was largely unaltered in the transgenic lines (Supplementary Figure S4E). On the other hand, the overexpression transgenic plants showed high GSH:GSSG ratio under P-lim conditions. Taken together, our findings suggest that, under both mild abiotic conditions, neither low nor high concentrations of glutathione elicited critical changes in the shoot growth and biomass of the examined plants. In our subsequent analysis, we focused on the GSH1 mutants to avoid pleiotropic effects from 35S-mediated overexpression.

To assess the wide range of metabolic impacts attributed to genotypic differences and types of mild abiotic stresses, we performed multi-platform metabolite profiling (Supplementary Table S2). For a visual inspection of the extent of metabolomic changes under the MV and P-lim stress conditions, we subjected the metabolite profile data to PCA. On the PCA score scatter plot (Figure 2A), the samples were clustered according to the applied abiotic stress conditions, as evidenced by the separation of PC1. We observed a genotype-dependent separation in the score scatter plot in the PC1/PC3 or PC2/PC3 direction (Supplementary Figure S5). These results indicate that global perturbations due to abiotic stress strongly affected the changes in the metabolite level of the mutant and WT plants.

We compared the metabolic responses in the metabolite profiles of the WT plants and GSH1 mutants grown under the no-stress condition or exposed to MV or P-lim stress. Under MV-induced oxidative stress, a total of 285 significantly changed metabolites was identified (Figure 2B), of which 223 were increased and 62 were decreased, respectively, including the commonly and exclusively accumulated metabolites. In all, 110 metabolite levels increased in the WT plant and GSH1 mutants after MV treatment, whereas 11 metabolite levels decreased (Figure 2B). For P-lim, we identified 178 increased and 70 decreased metabolites, respectively. The levels of 41 metabolites increased in the 3 genotypes under P-lim condition, whereas 21 metabolite levels decreased (Figure 2C). The number of significantly altered metabolites between GSH1 mutants and WT plants under mild abiotic stress was smaller than that of the treatment (Supplementary Figure S6), indicating consistency with the results of PCA score plots.

Among the DEGs, we focused on “marker genes” that are highly induced by stress treatments (Claeys et al., 2014). They include marker genes elicited under oxidative stress [NAC DOMAIN-CONTAINING PROTEIN32 (NAC032) and ALDO-KETO REDUCTASE 4C9 (AKR4C9)], those induced by abscisic acid (ABA) [NINE-CIS-EPOXYCAROTENOID DIOXYGENASE3 (NCED3) and CYP707A3] and dehydration [LATE EMBRYOGENESIS ABUNDANT-LIKE5 (LEA5), also known as SAG21], mild osmotic stress markers [MYB51, ERF5, and WRKY DNA-BINDING PROTEIN33 (WRKY33)], and genes overexpressed in response to phosphate starvation [SQD1 and SQD2] (Table 1). We found that the expression of the oxidative stress markers NAC032 and AKR4C9 was remarkably up-regulated in pad2-1 grown under MV stress and control conditions. Under P-lim stress, NAC032 and AKR4C9 genes were up-regulated in WT plants; genotype comparison showed the up-regulation of the AKR4C9 gene in pad2-1 plants. Marker gene expressions associated with ABA and mild osmotic stress were largely unaltered except for LEA5/SAG21 (up-regulated in pad2-1 under control conditions) and WRKY33 (down-regulated in pad2-1 by MV treatment). With respect to stress marker responses to phosphate starvation, both SQD1 and SQD2 genes were up-regulated in pad2-1 under P-lim stress; the SQD1 gene was only up-regulated in WT plants.

To assess the changes in other stress-responsive genes, including well-known transcription factors, in the WT plants and the GSH1 mutants exposed to abiotic stress, we investigated the general patterns of gene expression associated with DREB/CBF (dehydration-responsive-element binding protein/C-repeat-binding factor) and AREB/ABF (ABA-responsive element-binding/ABA-responsive element-binding factor) protein. They play a crucial role in the adaptation to various stresses (Yamaguchi-Shinozaki and Shinozaki, 2006). Among DREB/CBF and AREB/ABF genes, the transcript level of DREB2A was down-regulated (log₂ fold-change, approximately -1) in the WT and pad2-1 plants grown under both stress conditions. The expression of DREB2A was gradually induced by H₂O₂ (Sakuma et al., 2006). Under the MV condition, the mutants showed slight up-regulation of DREB1A/CBF3, DREB1C/CBF2, and DREB2A. The expression of AREB2/ABF4 in the WT and pad2-1 plants was unchanged under the three growth conditions. An abiotic stress-responsive gene in Arabidopsis is Responsive to Desiccation (RD) (Yamaguchi-Shinozaki and Shinozaki, 1993). Both WT and pad2-1 plants showed down-regulation of RD29A under both stress conditions; the expression of RD29B in WT and pad2-1 plants was unaltered under the three conditions (Table 1). The expression of two genes encoding ZAT12 (Davletova et al., 2005; Vogel et al., 2005) and STZ (Sakamoto et al., 2004) was markedly higher in the MV-treated pad2-1 than in WT plants (Table 1).

To assess the coordinated responses of glucosinolate and flavonoid biosynthesis under mild stress conditions, we performed pathway analysis of combined metabolite and transcript profile data. The integrated metabolomic and transcriptomic responses in WT and pad2-1 plants under the two stress conditions are shown in Figure 6. As pad2-1-specific metabolite responses, the level of short-chain aliphatic methylsulphinylalkyl glucosinolates [4-MSOB, and 5-MSOP] and 6-MSOH (6-methylsulfinyl-n-hexylglucosinolate) was increased in pad2-1 under both stress conditions; the difference was a significant but moderate effect size (all the ranges from 0.39 to 0.97 in log₂ fold-change) (Figure 6A, left). The level of 8-MTO and 8-MSOO was decreased by MV treatment, irrespective of the genotype (all the ranges from -1.37 to -0.56 in log₂ fold-change). The level of 5-MTP, 7-MSOH, 8-MTO, and 8-MSOO was increased in pad2-1 under P-lim condition (all the ranges from 0.45 to 0.82 in log₂ fold-change). Gene expressions associated with glucosinolate biosynthesis were up-regulated in pad2-1 grown under abiotic stress conditions. These included some genes encoding methylthioalkylmalate synthase (MAM) (Textor et al., 2007), MYB29 (Hirai et al., 2007; Sonderby et al., 2007; Gigolashvili et al., 2008), branched chain aminotransferase (BCAT) (Schuster et al., 2006), flavin-containing monooxygenase (FMO) (Hansen et al., 2007), and other genes involved in glucosinolate biosynthesis. Under the MV condition, the transcript levels of these genes were significantly higher in pad2-1 mutants than in WT plants, except for the MAM gene (Figure 6B, left). Compared to that in WT plants, the level of 8-MSOO was decreased in pad2-1 mutants under all conditions, whereas that of 3-MSOP was increased under no-stress and MV conditions.

In WT and pad2-1 plants, MV treatment triggered the up-regulation of the transcript levels of dihydroflavonol reductase (DFR), 2OG-Fe(II) oxygenase, and PAP1 after a remarkable increase in flavonols and anthocyanins (Figure 6A, right). As discussed previously (Saito et al., 2008; Fukushima and Kusano, 2014; Nakabayashi and Saito, 2015), the metabolomic and transcriptomic responses in the anthocyanin pathway in Arabidopsis were well correlated under oxidative stress conditions. In contrast to mild MV-induced oxidative stress, the increased level of kaempferols mentioned above was not correlated with the transcript levels in the pathway under P-lim condition. Compared to that in WT plants, pad2-1 mutants under MV and P-lim conditions showed a significant increase in two genes encoding SENESCENCE-RELATED GENE 1 (SRG1) and DON-GLUCOSYLTRANSFERASE 1 (DOGT1) in the flavonol biosynthetic pathway; the level of flavonols was largely unaltered (Figure 6B, right). When we focused on genotype-dependent changes, we found that, in the anthocyanin synthetic pathway, a remarkable decrease in the transcript level of 2OG-Fe(II) oxygenase and the anthocyanin level in pad2-1 mutant was noted compared to that in WT plants. Our finding that the anthocyanin level was lower in the mutant was consistent with that of previous findings on GSH1-antisense transgenic plants reported by (Xiang et al., 2001).

In this study, we investigated the changes in metabolite and transcript levels that reflect regulatory networks compensating for the reduction in the glutathione levels to enable the survival of GSH1 mutants under two mild abiotic stress conditions. We chose MV because the reduction of GSSG to GSH plays an important role in maintaining and regulating the cellular redox status during oxidative stress induced by MV. GSH1 is localized in plastids (Wachter et al., 2005), and MV is a fairly specific stimulus for ROS production in the chloroplast (Noctor et al., 2015). We chose the P-lim condition because phosphorus is an important component of the phospholipid membrane in the chloroplast (Hartel et al., 2000; Andersson et al., 2003; Jouhet et al., 2004; Okazaki et al., 2013). While phosphorus is also involved in plant growth and metabolism as one of the major nutrient ions, the molecular basis of plant adaptation to deal with a low phosphorus environment has not been completely elucidated. Although the series of genes and enzymes that are associated with these plant responses and adaptations (GSH1 is an example) are known, the comprehensive molecular mechanisms of their regulation and control are less well understood. Therefore, we applied the integrated omic approach by using high-throughput molecular phenotyping to GSH1 mutants grown under mild MV and P-lim conditions.

GSH1 mutants, cad2-1 (Cobbett et al., 1998) and pad2-1 (Parisy et al., 2007), showed differences in sensitivity to cadmium and biotic stresses from that of WT plants (Bednarek et al., 2009; Clay et al., 2009; Schlaeppi et al., 2010). Generally, glutathione synthesis mutants show shorter primary roots and lower levels of lateral root density compared to that in WT plants because of glutathione depletion (Schnaubelt et al., 2015). Low glutathione levels do not largely affect the shoot phenotypes of glutathione synthesis mutants under no-stress conditions. The characterization of leaf area phenotypes by using a high-resolution phenomic approach showed that glutathione synthesis mutants, except for an allele of GSH1 mutant called regulator of APX2 1-1 (rax1-1) (Ball et al., 2004), were not as sensitive as the WT plants under 1 μM MV treatment (Schnaubelt et al., 2013). We found that the two GSH1 mutants (cad2-1 and pad2-1), GSH1-overexpressing plants [7-5 and 13-6 (Cheng et al., 2015)], and WT plants exhibited a similar level of growth reduction under the mild MV stress condition (Figure 1 and Supplementary Figure S4). This suggests that neither a low nor high content of glutathione can compensate for the reduction in the shoot biomass of Arabidopsis under MV treatment. In WT plants, the level of GSH was slightly lower in the MV than in the no-stress condition and the GSSG level was increased (Figures 1C,D). The GSH:GSSG ratio in WT plants was similar under the control and P-lim condition, suggesting that the oxidative stress status was low in both (Figure 1E). Since glutathione peroxidase catalyzes the changes from GSH to GSSG, tracing the GSH:GSSG ratio by measuring GSH and GSSG might yield a specific marker of oxidative stress, e.g., increased H₂O₂ metabolism (Queval et al., 2007; Noctor et al., 2012).

Our metabolite and transcript profiling revealed distinctive metabolic and transcriptional responses against two mild abiotic stresses. Genetic perturbation of metabolic responses in the WT plants and the two allelic mutants subjected to oxidative stress by MV clearly showed a specific enhancement in metabolite production in the sugar and flavonoid metabolism (Figure 3 and Supplementary Figure S7). This type of stress might result in an altered metabolic status to compensate for the reduced ROS scavenging ability by reprogramming the sugar and flavonoid metabolism to produce specific antioxidant metabolites that consist of aglycone with sugar conjugates, i.e., flavonols and anthocyanins, as a common oxidative stress response. We observed that our P-lim condition resulted in increased levels of specific flavonol-glycosides, kaempferol 3-O-rhamnoside-7-O-rhamnoside (F1), kaempferol 3-O-[glucosyl(1 → 6)glucoside] 7-O-rhamnoside (F4), and quercetin 3-O-rhamnoside-7-O-rhamnosides (F5). Previous transcript- and flavonoid profiling demonstrated that the LATERAL ORGAN BOUNDARY DOMAIN (LBD) gene family of transcription factors (LBD37, LBD38, and LBD39) regulate the late steps of anthocyanin-specific biosynthesis and flavonol glycosides [F1 to F6, see (Tohge et al., 2005)] derived from kaempferol or quercetin were largely unaltered in the LBD-overexpression or mutant seedlings irrespective of nitrogen supply (Rubin et al., 2009). Another report also demonstrated that flavonoid overaccumulation [e.g., flavonols (F1, F2, F3, F5, and F8) and anthocyanin] was important to enhanced tolerance to oxidative- and drought stresses (Nakabayashi et al., 2014). Together these observations suggest that specific flavonols and anthocyanins play a distinct role in mitigating abiotic stress in Arabidopsis.

Changes in the GSH level under each stress condition (MV or P-lim vs. control) were almost identical in WT plants and the mutants (Figure 1 and Supplementary Figure S7). Antioxidants such as ascorbate and glutathione play a central role in plant defense under oxidative stress conditions (for example, see Foyer and Noctor, 2009). Conversely, phytochelatins, polymerized to form GSH, protect plants from heavy metal toxicity (Xiang et al., 2001; Schat et al., 2002). In general, GSH is maintained at a high concentration in the sulfur assimilation pathway (Saito, 2000, 2004). Glucosinolates and phytochelatins are downstream metabolites in the pathway. No accumulation of phytochelatins was noted in the cad2-1 mutant (Jozefczak et al., 2015). Our metabolite profiling showed that, with the exception of 8-MTO and 8-MSOO, the level of glucosinolates was higher under both stress conditions than under no-stress in pad2-1 and cad2-1 mutants (Figures 3A, 5A, left). The accumulation patterns of glucosinolates under the applied stress conditions might be explained by metabolic perturbation resulting in a decrease of phytochelatin and an increase of glucosinolate levels to compensate for the reduced glutathione level against mild oxidative stress. Glucosinolates might protect against oxidative stress in the GSH1 mutants.

As mentioned above, our results imply that coordinated responses of glucosinolate and flavonoid biosynthesis at the metabolite and transcript levels are associated with the plant response to MV-induced oxidative stress and to stress elicited by P-lim (Figure 6). We found that, in the GSH1 mutants, a short-chain aliphatic glucosinolate (3-MSOP) was over-accumulated under mild oxidative stress, and the level of long-chain aliphatic glucosinolates was decreased (Figures 3B, 6B, left). Glucosinolate biosynthesis involves the breakdown of methionine to produce short-chain glucosinolates that harbor three carbons in their moiety (3C-glucosinolates) in the first round of glucosinolate chain elongation. Subsequently, 4C- and long-chain glucosinolates are synthesized by further rounds of elongation (Field et al., 2004). These elongation reactions are mediated by genes depicted in Figure 6 (left). The increase in the 3-MSOP level together with a decrease in the level of long-chain glucosinolates might be due to the gap and could result in the production of glucosinolates exhibiting different chain lengths. By using the insect herbivore Spodoptera littoralis, Schlaeppi et al. (2008) found that the pad2-1 mutant exhibited a reduction of two 3C- and 4C-glucosinolates, 4-methylsulfinylbutylglucosinolate and indolyl-3-methylglucosinolate, and that their reduction was correlated with the reduced GSH level (approximately 20% of that in WT plants). In addition, glutathione has possible roles as an s atom donor for glucosinolates (Noctor et al., 2012). It could be a reason of the decrease of long-chain glucosinolate level in pad2-1 mutants. In the flavonoid biosynthetic pathway in pad2-1 mutants, the decrease in the anthocyanin level is likely due to a reduction in the transcript level of genes encoding 2OG-Fe(II) oxygenase and PAP1 (Figure 6B, right). Under the control condition, the accumulation patterns of GSH and anthocyanins were roughly correlated in Arabidopsis (Xiang et al., 2001). Our results suggest that the correlation between GSH content and anthocyanin level is regulated at the transcript level.

In this study, we imposed mild stress conditions to obtain a better understanding of the fundamental basis of plant responses to abiotic stress. Changes in the GSH:GSSG ratio reflected their oxidative stress status under the assayed conditions (Figure 1). Clauw et al. (2015) who used an automated phenotyping system and genome-wide transcriptome analysis based on RNA sequencing showed that six Arabidopsis accessions exhibited common and specific response to mild drought stress (Clauw et al., 2015). Our comparative transcript profiling of the GSH1 mutants and WT plants revealed common as well as specific stress responses, particularly against mild oxidative stress induced by a low concentration of MV and against mild stress elicited by low phosphorus (Table 1, Figure 5, and Supplementary Figure S12). We also evaluated the specific changes in transcript levels in response to environmental and genetic perturbations (Figure 5). We showed that stress-inducible genes included those encoding specific GSTs, UGTs, or CYPs that were associated with a well-known detoxification and transcriptome response when plants are exposed to oxidative stress. Our transcriptome results are in agreement with previous findings obtaining by conducting expression analysis of known “severe” oxidative stress-related genes (Dubreuil-Maurizi et al., 2011). However, we were able to find the pad2-specific transcript and metabolic responses under mild oxidative stress; an example is related to glucosinolate biosynthesis. The pad2-1 mutant clearly reprograms the cellular metabolic networks and the transcriptome in response to the applied mild abiotic stress, but whether they can be reversible is unclear and needs further studies. Very severe stress causes visible symptoms in plant growth and development, for example, stunted growth, light yellow or green leaves, and rolled leaves. Such phenotypic changes generally affect metabolite profiles (for example, see Fiehn et al., 2000). In addition, we were able to see significant metabolic fluctuation even under the strictly controlled conditions (Weckwerth et al., 2004; Kusano et al., 2007a). Combined metabolite- and transcript profiling has important implications for the diagnostic characterization of the “mild” stress level and fine-tuning molecular responses in plants.

WRKY-type transcription factors play an important role in the response to biotic and abiotic stress and are also important components of a plant signaling pathway that controls developmental processes (Eulgem et al., 2000; Ulker and Somssich, 2004; Rushton et al., 2010). Interplay among three types of group I WRKY proteins, WRKY33, WRKY25, and WRKY26, is crucial for promoting heat and salt tolerance in Arabidopsis (Li et al., 2011). Arabidopsis sigma factor-binding proteins (SIB1 and SIB2) stimulate the DNA binding activity of the WRKY33 transcription factor in plant defense (Lai et al., 2011). MV treatment also induces WRKY33 expression (Zheng et al., 2006; Miller et al., 2008). Our microarray experiment showed remarkable down-regulation of WRKY33 gene expression in pad2-1 by mild MV treatment (Table 1). Cross-talk between glutathione and phytohormones is also important for abiotic stress responses in Arabidopsis. Datta and colleagues showed that glutathione regulates the transcription levels of genes involved in ethylene biosynthesis via WRKY33 (Datta et al., 2015). Ethylene is known to regulate a wide range of plant processes, including growth, ripening, and responses to environmental stress (Kieber, 1997; Guo and Ecker, 2004; Klee, 2004; Yoo et al., 2009; Wang et al., 2013). As genotype-dependent altered genes and pad2-1-specific responsive genes, we detected changes in transcript levels of genes, including GSTs, UGTs, CYPs, HSPs, and SAGs, and transcription factors such as ERF6 and HSFA2. Our findings suggest that WRKY33 protein plays a vital role either as positive or negative transcriptional regulators, perceiving direct or indirect signal transduction in different ways under mild oxidative stress, though detailed regulatory mechanisms are still unclear.

Although the glutathione biosynthetic pathway can be considered as a key component in the sulfur assimilation pathway (Saito, 2000, 2004; Kopriva, 2006; Takahashi et al., 2011), except for the gene encoding SUFE2 that was up-regulated in pad2-1 compared with that in WT plants under all conditions, we observed no significant changes in the transcript level of genes involved in this pathway. Unlike our MV treatment and P-lim condition, earlier transcriptome analysis of cadmium-treated plants showed the induction of genes associated with sulfur assimilation reduction and glutathione pathways in Arabidopsis roots (Herbette et al., 2006). During oxidative stress elicited by MV and under P-lim conditions, DREB1A, DREB1B, DREB1C, and DREB2A genes were slightly up-regulated in pad2-1, but not in WT plants (Table 1). This suggests that DREB/CBF factors contribute, at least partly, to plant survival by increasing resistance under the imposed mild stress conditions. DREB2A interacts with the Radical-Induced Cell Death1 (RCD1) protein (Jaspers et al., 2010; Vainonen et al., 2012) that is involved in programmed cell death signaling and regulates plant stress responses (Overmyer et al., 2000; Ahlfors et al., 2004). The rcd1 mutant exhibits MV and UV-B tolerance (Fujibe et al., 2004). UV-B also elicits oxidative stress, resulting in changes in photomorphogenesis, photosynthesis, membranes, and secondary metabolism (Landry et al., 1995; Mittler, 2002; Frohnmeyer and Staiger, 2003; Kusano et al., 2011). Our current understanding of the molecular mechanisms controlling programmed cell death (PCD) in plants is limited, particularly with regard to how signaling by ROS drives/regulates the changes in expression leading to PCD (Kragelund et al., 2012). These mechanisms have not yet been identified. Genes encoding ZAT12 and STZ were also up-regulated in pad2-1 under both stress conditions (Table 1). ZAT12 is related to the control of cold-responsive gene expression and to the adaptation of plants to a freezing environment (Vogel et al., 2005). STZ is related to the Cys2/His2-type zinc-finger transcriptional repressor that involves drought stress tolerance (Sakamoto et al., 2004). These findings suggest that ZAT12 and STZ are also involved in plant responses to mild oxidative and low phosphorus stress.