SE148:/MS2

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Sample Set Information

ID TSE1321
Title Assessing metabolomic and chemical diversity of a soybean lineage representing 35 years of breeding
Description Information on crop genotype- and phenotype-metabolite associations can be of value to trait development as well as to food security and safety. The unique study presented here assessed seed metabolomic and ionomic diversity in a soybean lineage representing ~35 years of breeding (launch years 1972–2008) and increasing yield potential. Selected varieties included six conventional and three genetically modified (GM) glyphosate-tolerant lines. A metabolomics approach utilizing capillary electrophoresis (CE)-time-of-flight-mass spectrometry (TOF-MS), gas chromatography (GC)-TOF-MS and liquid chromatography (LC)-quadrupole (q)-TOFMS resulted in measurement of a total of 732 annotated peaks. Ionomics through inductively-coupled plasma (ICP)-MS profiled twenty mineral elements. Orthogonal partial least squares-discriminant analysis (OPLS-DA) of the seed data successfully differentiated newer higher-yielding soybean from earlier lower-yielding accessions at both field sites. This result reflected genetic fingerprinting data that demonstrated a similar distinction between the newer and older soybean. Correlation analysis also revealed associations between yield data and specific metabolites. There were no clear metabolic differences between the conventional and GM lines. Overall, observations of metabolic and genetic differences between older and newer soybean varieties provided novel and significant information on the impact of varietal development on biochemical variability. Proposed applications of omics in food and feed safety assessments will need to consider that GM is not a major source of metabolite variability and that trait development in crops will, of necessity, be associated with biochemical variation.
Authors Miyako Kusano, Ivan Baxter, Atsushi Fukushima, Akira Oikawa, Yozo Okazaki, Ryo Nakabayashi, Denise J. Bouvrette, Frederic Achard, Andrew R. Jakubowski, Joan M. Ballam, Jonathan R. Phillips, Angela H. Culler, Kazuki Saito, George G. Harrigan
Reference Metabolomics April 2015, Volume 11, Issue 2, pp 261–270
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Analytical Method Details Information

ID MS2
Title LC-TOF-MS (Lipid profiling)
Instrument LC, Waters Acquity UPLC system; MS, Waters Xevo G2 Q-Tof
Instrument Type UPLC-QTOF-MS
Ionization ESI
Ion Mode positive and negative
Description BioSource amount

We weighed 70 mg dry weight (DW) of the lyophilized samples for CE-TOF-MS analysis, 5 mg DW for GC-TOF-MS analysis, 50 mg DW for LC-q-TOF-MS analysis to detect polar metabolites, and 15 mg DW for lipid profiling.

Extraction for LC-q-TOF-MS to detect lipids
Each sample (15 mg DW) was extracted with 80 volume of methyl tert-butyl ether /methanol (3:1, v/v) containing 20 μM of 1,2-dioctanoyl-sn-glycero-3-phosphocholine (SIGMA. After adding the extraction solvent, samples were vigorously mixed using a vortex mixture. To each sample, 25 volume of water was added, 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 (50μl) was transferred to a 2 ml tube. Each extract was evaporated to dryness by SPD2010 SpeedVac® concentrator (Thermo Fisher Scientific). The residue was dissolved in 1,250 μl of ethanol, and centrifuged at 10,000 x 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).

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