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Sample Set Information

ID TSE1302
Title Effects of Combined Low Glutathione with Mild Oxidative and Low Phosphorus Stress on the Metabolism of Arabidopsis thaliana
Description Plants possess highly sensitive mechanisms that monitor environmental stress levels for a dose-dependent fine-tuning of their growth and development. Differences in plant responses to severe and mild abiotic stresses have been recognized. Although many studies have revealed that glutathione can contribute to plant tolerance to various environmental stresses, little is known about the relationship between glutathione and mild abiotic stress, especially the effect of stress-induced altered glutathione levels on the metabolism. Here, we applied a systems biology approach to identify key pathways involved in the gene-to-metabolite networks perturbed by low glutathione content under mild abiotic stress in Arabidopsis thaliana. We used glutathione synthesis mutants (cad2-1 and pad2-1) and plants overexpressing the gene encoding γ-glutamylcysteine synthetase, the first enzyme of the glutathione biosynthetic pathway. The plants were exposed to two mild stress conditions—oxidative stress elicited by methyl viologen and stress induced by the limited availability of phosphate. We observed that the mutants and transgenic plants showed similar shoot growth as that of the wild-type plants under mild abiotic stress. We then selected the synthesis mutants and performed multi-platform metabolomics and microarray experiments to evaluate the possible effects on the overall metabolome and the transcriptome. As a common oxidative stress response, several flavonoids that we assessed showed overaccumulation, whereas the mild phosphate stress resulted in increased levels of specific kaempferol- and quercetin-glycosides. Remarkably, in addition to a significant increased level of sugar, osmolytes, and lipids as mild oxidative stress-responsive metabolites, short-chain aliphatic glucosinolates over-accumulated in the mutants, whereas the level of long-chain aliphatic glucosinolates and specific lipids decreased. Coordinated gene expressions related to glucosinolate and flavonoid biosynthesis also supported the metabolite responses in the pad2-1 mutant. Our results suggest that glutathione synthesis mutants accelerate transcriptional regulatory networks to control the biosynthetic pathways involved in glutathione-independent scavenging metabolites, and that they might reconfigure the metabolic networks in primary and secondary metabolism, including lipids, glucosinolates, and flavonoids. This work provides a basis for the elucidation of the molecular mechanisms involved in the metabolic and transcriptional regulatory networks in response to combined low glutathione content with mild oxidative and nutrient stress in A. thaliana.
Authors Fukushima A, Iwasa M, Nakabayashi R, Kobayashi M, Nishizawa T, Okazaki Y, Saito K, Kusano M.
Reference Front Plant Sci. 2017 Aug 28;8:1464.

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Sample Information

Title Arabidopsis ecotype Columbia (Col-0)
Organism - Scientific Name Arabidopsis thaliana
Organism - ID NCBI taxonomy:3702
Compound - ID
Compound - Source
Preparation 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.
Sample Preparation Details ID SS1

Sample Preparation Details Information

Title Growth conditions
Description Plants were grown in MS agar medium except for the oxidative and phosphorous limited condition. Sterilized seeds were stratified at 5°C for 2 days, and were sown on Murashige and Skoog (MS) medium containing 1% sucrose (Control). Oxidative and Phosphorous limited conditions were produced adding 0.05μM Methyl Viologen and reducing phosphate concentration to 1/5 of MS medium. Seedlings of Arabidopsis Col-0 and the mutants were cultivated in growth chambers at 22°C in the 16-h light and 8-h dark condition for 18 days (light strength, 80 μmol m-2 s-1 of photosynthetic photon flux (PPF)). We sampled 20 independent plants (n = 20, biological replicates) for measurement of shoot biomass (flesh weight), 8 for metabolite profiling, and 3 for absolute glutathione quantification as follows.

Analytical Method Information

Title LC-q-TOF-MS (to detect lipids)
Method Details ID MS3
Sample Amount 1 μl

Analytical Method Details Information

Title LC-q-TOF-MS (to detect lipids)
Instrument HPLC, Waters Acquity UPLC system; MS, Waters Xevo G2 Qtof
Instrument Type UPLC-QTOF-MS
Ionization ESI
Ion Mode Positive
Description Extraction for LC-q-TOF-MS to detect lipids

Each frozen samplewas milled using mixer mill MM301 (Retsch) at a frequency of 20 Hz for 2 min at 4°C. After that, frozen powder was extracted with 20 fold volume of extraction solvent (chloroform/methanol/waer[50 : 100 : 31.45, v/v])containing 0.25mM of 1,2-dioctanoyl-sn-glycero-3-phosphocholine (SIGMA). Samples were vigorously mixed using a vortex mixture. 52.5 μl of water and 52.5 μl of chloroform were added to 200 μl of extract and then vigorously mixed for 5 min at room temperature. After standing for 15 min on ice, the samples were centrifuged at 1,000 ×g at 5°C for 5 min. The supernatant (85 μl) was transferred to a 2 ml tube with insert. Each extract was evaporated to dryness by SPD2010 SpeedVac® concentrator (Thermo Fisher Scientific). The residue was dissolved in 162μl of ethanol, and centrifuged at 10,000×g at 45°C for 15 min. Two hundred microliter of the supernatant was transferred to a glass tube for lipid analysis.

LC-q-TOF-MS conditions to detect lipids
Sample extracts (1 μl) were analyzed using an LC-MS system equipped with an electrospray ionization (ESI) interface (HPLC, Waters Acquity UPLC system; MS, Waters Xevo G2 Qtof). Two-solvent (A and B) system was used for separation of each metabolite. Compositions of these solvents were as follows: solvent A, acetonitrile: water:1 M ammonium acetate:formic acid = (158 g:800g:10 ml:1 ml); solvent B, acetonitrile:2-propanol:water:1 M ammonium acetate:formic acid = (79 g:711 g:10 ml:1 ml). The analytical conditions were as follows. HPLC: column, Acquity UPLC HSS T3 (pore size 1.8 μm, 1.0 i.d × 50 mm long, Waters); gradient program, 35% B at 0 min, 70% B at 3 min, 85% B at 7 min, 90% B at 10 min, 90% B at 12 min and 35% B at 12.5 min; flow rate, 0.15 ml/min; temperature, 55°C; MS detection: capillary voltage, +3.0 kV; cone voltage, 20 V for positive mode and 40 V for negative mode; source temperature, 120°C; desolvation temperature, 450°C; cone gas flow, 50 l/h; desolvation gas flow, 450 l/h; collision energy, 6 V; detection mode, scan (m/z 100–2000; scan time, 0. 5 sec; centroid). The scans were repeated for 15 min in a single run. The data were recorded using MassLynx version 4.1 software (Waters).


Data Analysis Information

Title Data processing for LC-q-TOF-MS data to detect lipids
Data Analysis Details ID DS3
Recommended decimal places of m/z

Data Analysis Details Information

Title Data processing for LC-q-TOF-MS data to detect lipids
Description The data matrix was generated using the Makerlynx XS (Waters) using the profiling data files recorded in the MassLynx format (raw). The data matrices were processed using in-house Perl script. The original peak intensity values were divided with that of the internal standard (didecanoyl-sn-glycerophosphocholine at m/z 566.382 [M + H]+ and at m/z 610.372 [M + HCOO]– for the positive and negative ion modes, respectively) to normalize the peak intensity values among the metabolic profile data.
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