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Gcms 2010se

Manufactured by Shimadzu
Sourced in Japan

The GCMS-2010SE is a gas chromatography-mass spectrometry (GC-MS) system developed by Shimadzu. It combines gas chromatography for sample separation with mass spectrometry for compound identification and quantification. The GCMS-2010SE provides high-sensitivity and high-speed analysis capabilities for a wide range of applications.

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10 protocols using gcms 2010se

1

Comprehensive Analysis of Organic Acids and Sugars

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Organic acid and sugar content were evaluated using GC–MS (gas chromatography–mass spectrometry) following the procedures as described by Li et al. [29 (link)]. Soluble sugars and organic acids were extracted with 1.4 mL of 75% (V/V) methanol for 0.1 g of sample, with 400 ppm ribitol was used as internal standard, by shaking at 900 rpm at 70°C for 30 min. The supernatants were separated and transferred into a mixture of 750 μL chloroform (CHCl3) and 1.4 mL ddH2O. After mixing and centrifugation, samples of 2 μL and 50 μL of the supernatant were dried and then derivatized with 40 μL methoxyamine hydrochloride and 60 μL N-methyl-N-trimethylsilyl-trifluoroace-tamide (MSTFA). Analysis of soluble sugar and organic acid contents was conducted on a GCMS-2010SE instrument (Shimadzu Corporation, Kyoto, Japan).
The determination of starch content was performed as described by Li et al. [28 (link)]. The remaining precipitate after the extraction with 75% methanol for the determination of sugar and acid was repeatedly cleaned with 80% (v/v) ethanol three times, mixed with 0.1 M KOH and boiled for 30 min to gelatinize the starch. α-amylase at pH 4.5 was added and incubated at 55°C for 1 h. Reducing sugar content was determined by 3, 5-dinitrosalicylic acid (DNS), and then converted to starch content.
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2

Metabolite Profiling of Plant Leaves

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Soluble sugars were extracted and derivatized sequentially with methoxamine hydrochloride and N-methyl-N-trimethylsilyl-trifluoroacetamide, as described previously (Hu et al., 2018 (link)). The metabolites were analyzed with a Shimadzu GCMS-2010 SE (Shimadzu Corp., Kyoto, Japan). Values were calculated based on their corresponding standard curves and internal standards.
Amino acids were extracted and measured as described previously (Huo et al., 2020b (link)). Briefly, 200 mg of frozen leaf samples were extracted in 2 ml 50% ethanol (including 0.1 M HCl) and centrifuged at 13,000 g for 10 min. The supernatant was added to methanol at a final volume of 10 ml. The samples were filtered through a 0.22 μm filter to analyze the metabolites with a liquid chromatography-mass spectrometry system (QTRAP5500; SCIEX, Concord, ONT, Canada) equipped with an Inertsil ODS-4 C18 column (4.6 × 250 mm, 5 μm) at a flow rate of 0.3 ml/min. The solvent system consisted of water containing 0.1% (v/v) formic acid (A) and acetonitrile (B). Data were quantified by comparing the peak surface areas with those obtained using standard amino acids (Sigma-Aldrich, St. Louis, MO, United States).
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3

Quantitative GC-MS Metabolite Analysis

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Soluble sugars and hexose phosphates were obtained and derivatized as described by Wang et al. (2010 (link)). Briefly, samples (0.09–0.11 g) were extracted in 1.4 mL of 75% methanol, with ribitol added as the internal standard. After the non-polar metabolites were fractionated into chloroform, 2 μl of the polar phase was transferred into 2.0-mL Eppendorf vials for measurements of the metabolites (Sor, Fru, Glc, Suc, galactose: Gal and myo-inositol) of each sample. They were dried under vacuum without heating and then derivatized sequentially with methoxyamine hydrochloride and N-methyl-N-trimethylsilyl-trifluoroacetamide (Lisec et al., 2006 (link)). Afterward, the metabolites were analyzed with a Shimadzu GCMS-2010SE (Shimadzu Corporation, Tyoto, Japan). These metabolites were identified by comparing their fragmentation patterns with those from a mass spectral library generated on our GC/MS system, and from an annotated quadrupole GC–MS spectral library downloaded from the Golm Metabolome Database (http://csbdb.mpimp-golm. mpg.de/csbdb/gmd/msri/gmd_msri.html. Quantifications were based on standard curves generated for each metabolite and internal standard.
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4

GC-MS Analysis of Soluble Sugars and Starch

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As previously described (Li et al., 2018; Yang et al., 2018), soluble sugars and hexose phosphates were extracted in 75% methanol with ribitol added as an internal standard and then derivatized sequentially with methoxyamine hydrochloride and N‐methyl‐N‐trimethylsilyl‐trifluoroacetamide. After derivatization, the metabolites were analysed using a Shimadzu GCMS‐2010SE (Shimadzu Corporation, Tokyo, Japan) with a DB‐5MS capillary column (20 m × 0.18 mm × 0.18 μm) and a 5‐m Duraguard column (Agilent Technology, California, USA). The residue after 75% methanol extraction for GC‐MS analysis was re‐extracted three times with 80% (v/v) ethanol at 80 °C, and the pellet was retained for the enzymatic determination of starch as Glc equivalents.
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5

Metabolic Analysis of Seedling Leaves

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As we described previously30 (link), soluble sugars were extracted and derivatized sequentially with methoxyamine hydrochloride and N-methyl-N-trimethylsilyl-trifluoroacetamide. Then, the metabolites were analyzed with a Shimadzu GCMS-2010 SE (Shimadzu Corporation, Kyoto, Japan). The tissue residue that remained after 75% methanol extraction for GC‒MS analysis was re-extracted three times with 80% (v/v) ethanol at 80 °C, and the pellet was retained for starch determinations30 (link). The assimilation of CO2 in seedling leaves was monitored between 9:30 and 11:30 A.M. using a LI-COR 6400 portable photosynthesis system (LI-COR, Huntington Beach, CA, USA).
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6

Metabolite and CO2 Assimilation Analysis

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Soluble sugars and sorbitol were extracted and derivatized sequentially with methoxyamine hydrochloride and N-methyl-N-trimethylsilyl-trifluoroacetamide, as previously described (51 (link)). Thereafter, the metabolites were analyzed with a Shimadzu GCMS-2010SE (Shimadzu Corporation, Kyoto, Japan). The tissue residue that remained after 75% methanol extraction for gas chromatography-mass spectrometry (GC‒MS) analysis was re-extracted three times with 80% (volume/volume) ethanol at 80 °C, and the pellet was retained for starch determinations (23 (link)). Additionally, the assimilation of CO2 in seedling leaves was monitored between 9:30 and 11:30 AM, using a LI-COR 6400 portable photosynthesis system (LI-COR, Huntington Beach, CA).
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7

Fatty Acid Composition Analysis

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The total fat in the samples was extracted according to published methods [32 ], and the fatty acid composition was determined by using a Shimadzu instrument (GC-MS 2010 SE, Kyoto, Japan). The map was queried against the National Institute of Standards and Technology (NIST) database (https://www.nist.gov/, accessed on 4 February 2022) for qualitative search, and the area normalization method was used for percentage quantification.
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8

Derivatization and GC/MS Analysis

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As recently described [40 ], soluble sugars and hexose phosphates were extracted and then derivatized with methoxyamine hydrochloride and Nmethyl-N-trimethylsilyl-trifluoroacetamide. After derivatization, the metabolites were analyzed using a Shimadzu GC/MS-2010SE (Shimadzu Corporation, Tokyo, Japan).
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9

Genetic Mapping of Fructose Content

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In accordance with previously described methods (Li et al., 2018) , soluble sugars were extracted with 75% methanol, and ribitol was added as an internal standard. The sugars were derivatized sequentially with methoxyamine hydrochloride and N-methyl-Ntrimethylsilyl-trifluoroacetamide. After derivatization, the analysis was performed with a Shimadzu GCMS-2010 SE (Shimadzu Corporation, Tokyo, Japan) equipped with a DB-5 MS capillary column (20 m 9 0.18 mm 9 0.18 µm) and a 5-m guard column (Agilent Technology, Santa Clara, CA, USA).
A high-density genetic linkage map was used for QTL detection of Fru contents. QTL analysis was conducted with MapQTL 6.0 (Kyazma, Wageningen, Netherlands) and was initially run with interval mapping (IM) computation. After a permutation test with 1000 replicates, a LOD threshold of 3.0 was used to find significant QTLs at the 95% confidence level (Wang et al., 2018) . Multiple QTL model (MQM) mapping was then performed using the loci nearest the QTL peaks as cofactors. The linkage map was graphed by MapChart 2.3 (Wageningen, Netherlands) (Voorrips, 2002) . Designations for QTLs were based on the years (2015 or 2016), parental genetic linkage map names (HC for 'Honeycrisp', QG for 'Qinguan'), and genetic positions (LG number). For LGs that had more than one QTL, the designation also included a dot and number suffix (Wang et al., 2018) .
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10

GC/MS Analysis of Soluble Metabolites

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As recently described [40] , soluble sugars and hexose phosphates were extracted and then derivatized with methoxyamine hydrochloride and Nmethyl-N-trimethylsilyl-tri uoroacetamide. After derivatization, the metabolites were analyzed using a Shimadzu GC/MS-2010SE (Shimadzu Corporation, Tokyo, Japan).
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