SE148:/MS4

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
Comment

doi: 10.1007/s11306-014-0702-6

Analytical Method Details Information

ID	MS4
Title	GC-TOF-MS
Instrument	GC:Agilent 6890N gas chromatograph (Agilent Technologies, Wilmingston, USA) MS:Pegasus IV TOF mass spectrometer (LECO, St. Joseph, MI, USA)
Instrument Type
Ionization	EI
Ion Mode	Positive
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 and derivatization for GC-TOF-MS Each sample with a 5-mm zirconia bead was extracted with a concentration of 100 mg DW of powder per ml extraction medium (methanol/chloroform/water [3:1:1 v/v/v]) containing 10 stable isotope reference compounds at 4°C in a mixer mill (MM301; Retsch, Haan, Germany) at a frequency of 15 Hz. Each isotope compound was adjusted to a final concentration of 15 ng per 1-μl injection volume. After 5-min centrifugation at 15,100 x g, a 200-μl aliquot of the supernatant was transferred to a glass insert vial. The extracts were evaporated to dryness in an SPD2010 SpeedVac® concentrator (Thermo Fisher, Scientific, Waltham, MA, USA). We used extracts from 1-mg DW samples for derivatization, i.e., methoxymation and silylation. For methoxymation, 30 μl of methoxyamine hydrochloride (20 mg/ml in pyridine) were added to the sample. After 17 h of derivatization at room temperature the sample was trimethylsilylated for 1 h using 30 µl of MSTFA at 37°C with shaking. All derivatization steps were performed in a vacuum glove box VSC-100 (Sanplatec, Osaka, Japan) filled with 99.9995% (G3 grade) dry nitrogen. GC-TOF-MS conditions Using the splitless mode of a CTC CombiPAL autosampler (CTC Analytics, Zwingen, Switzerland), 1 μl of each sample (equivalent to 1.4 µg DW) was injected into an Agilent 6890N gas chromatograph (Agilent Technologies, Wilmingston, DE, USA) featuring a 30 m × 0.25 mm inner diameter fused-silica capillary column and a chemically bound 0.25-μl film Rxi-5 Sil MS stationary phase (RESTEK, Bellefonte, PA, USA) with a tandem connection to a fused silica tube (1 m, 0.15 mm). An MS column change interface (ms NoVent-J; SGE, Yokohama, Japan) was used to prevent air and water from entering the MS during column change-over. Helium was the carrier gas at a constant flow rate of 1 ml min-1. The temperature program for GC-MS analysis started with a 2-min isothermal step at 80°C followed by 30°C temperature-ramping to a final temperature of 320°C that was maintained for 3.5 min. The transfer line and the ion source temperatures were 250 and 200°C, respectively. Ions were generated by a 70-eV electron beam at an ionization current of 2.0 mA. The acceleration voltage was turned on after a solvent delay of 222 sec. Data acquisition was on a Pegasus IV TOF mass spectrometer (LECO, St. Joseph, MI, USA); the acquisition rate was 30 spectra s-1 in the mass range of a mass-to-charge ratio of m/z = 60–800. Alkane standard mixtures (C8 - C20 and C21 - C40) purchased from Sigma-Aldrich (Tokyo, Japan) were used for calculating the retention index (RI) (Schauer N, et al. (2005) GC-MS libraries for the rapid identification of metabolites in complex biological samples. FEBS lett 579(6):1332-1337). For quality control we injected methylstearate into every 6th sample. The sample run order was randomized in single-sequence analyses. We analyzed the standard compound mixtures using the same sequence analysis procedures.
Comment_of_details