Gcmssolution

Manufactured by Shimadzu

Sourced in Japan

GCMSsolution is a software package developed by Shimadzu for the operation and data analysis of gas chromatography-mass spectrometry (GC-MS) systems. The software provides a comprehensive suite of tools for instrument control, data acquisition, and data processing.

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Shimadzu GCMSsolution software Version 2.53 (1 citations) GCMSsolution software (58 citations) GCMS Postrun Analysis (GCMSsolution Version 4.45, (2 citations)

14 protocols using gcmssolution

GC/MS Data Processing Pipeline

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GC/MS raw data files were converted into netCDF (*.cdf) format according to the ANDI (Analytical Data Interchange Protocol) specification using the proprietary software GCMSsolution (Shimadzu, Kyoto, Japan) before peak detection, baseline correction and retention time alignment using the freely available data processing tool MetAlign [41 (link)]. MSClust [42 (link)] was used to assign putative compound memberships in an unsupervised manner to each mass peak, and the peak retention times were adjusted according to compound membership. The adjusted data matrices were then imported into AIoutput2 ver.1.29 [31 (link)] for automated RI-based compound identification and quantification. The parameters used for MetAlign, MSClust and AIoutput2 are provided in Additional file 1: Table S4. To account for deviations in overall intensity due to volumetric errors in sample collection and preparation as well as systematic drift or random fluctuations in ionization efficiency and mass detector sensitivity, peak intensities of each sample were normalized to the internal standard (ribitol) peak.

Teoh S.T., Putri S., Mukai Y., Bamba T, & Fukusaki E. (2015). A metabolomics-based strategy for identification of gene targets for phenotype improvement and its application to 1-butanol tolerance in Saccharomyces cerevisiae. Biotechnology for Biofuels, 8, 144.

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SCFA Analysis by GC-MS with Shimadzu

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Analysis of the SCFA was performed using a Shimadzu GC-2010 gas chromatography system coupled with a QP20 10 EI mass spectrometric detector (GCMS-QP2010, Shimadzu, Kyoto, Japan). Propylated derivatives of the SCFA were separated using a Supelco SPB-5 fused silica column (30 m length, 0.25mm diameter, 0.25 μm thickness, Supelco, Bellefonte, PA). One microliter of derivative dissolved in hexane was injected using split mode (1:6 split ratio), a solvent delay of 2.5 min, and a gas flow rate of 0.42 mL/min with helium as the carrier gas. The injection port temperature was set at 220°C. The initial oven temperature of 50°C was held for 3 min and then increased at a rate of 7°C/min until 150°C was achieved. Then the rate was raised to 16°C/min and held at 250°C for 10 min. Mass spectral data were collected in scan mode, and both the interface and detector temperature were set at 200°C.
Shimadzu Post-Run Analysis software was used to process raw chromatogram data (GC-MS solution, Shimadzu, Kyoto, Japan). Multiple ion counts (MIC) were used to reduce noise and improve signal-to-noise ratios by selecting ions that were representative of the six targeted analytes. These ion counts were added together to obtain the MIC, and peaks areas were calculated. Areas of analyte peaks were compared to the internal standard (d3-caproate) and a standard mix to determine concentrations.

Singh V., Yeoh B.S., Chassaing B., Xiao X., Saha P., Olvera R.A., Lapek JD J.r., Zhang L., Wang W.B., Hao S., Flythe M.D., Gonzalez D.J., Cani P.D., Conejo-Garcia J.R., Xiong N., Kennett M.J., Joe B., Patterson A.D., Gewirtz A.T, & Vijay-Kumar M. (2018). Dysregulated Microbial Fermentation of Soluble Fiber Induces Cholestatic Liver Cancer. Cell, 175(3), 679-694.e22.

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Quantitative Analysis of Phytocannabinoids via GC-MS

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Quantitative analysis of phytocannabinoids was performed using the Shimadzu GC-MS QP2010 system (Shimadzu, Japan). A 30 m long Rxi-5ms (Restek, Bellefonte, PA, USA) column was used for cannabinoids separation. Column thickness—0.25 µm; inner diameter—0.25 µm. Helium was used as the carrier gas. Gas chromatograph conditions: initial column temperature of 110 °C maintained for 2 min, then raised to 190 °C at a rate of 10 °C/min and maintained for 10 min; at a rate of 10 °C/min, the temperature was raised to 280 °C and held for 10 min. The total analysis time for one sample was 39 min. The temperature of the injector was 250 °C, the samples were inserted using an autoinjector (AOC-5000 Plus, Shimadzu, Japan), and the injection was performed by the split 1:10 method. An injection volume of 1 µL was used. The following mass spectrometer conditions were set: ion source temperature: 200 °C, interface temperature: 280 °C, solvent exit time: 2.5 min, and sample ionization energy: 70 eV. Scan speed: 1666; scan interval: start 35.00 m/z, end: 500.00 m/z. The obtained sample chromatograms were analyzed using GCMS solution (Shimadzu, Japan) software. The compounds were identified according to the mass-to-charge ratio by comparing the mass spectra of standard and identified compounds. The quantitative analysis was performed using the external standard method.

Motiejauskaitė D., Ullah S., Kundrotaitė A., Žvirdauskienė R., Bakšinskaitė A, & Barčauskaitė K. (2023). Isolation of Biologically Active Compounds from Cannabis sativa L. Inflorescences by Using Different Extraction Solvents and Evaluation of Antimicrobial Activity. Antioxidants, 12(5), 998.

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GC-MS Based Metabolite Profiling

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GC/MS analysis was performed as previous reported (Putri et al., 2018 (link)). Briefly, a GCMS-QP2010 Ultra (Shimadzu, Kyoto, Japan) gas chromatograph coupled with quadrupole mass spectrometer equipped with an AOC-20i/s auto injector (Shimadzu) was used with a CP-SIL 8 CB Low Bleed/MS column (30 m × 0.25 mm i.d., film thickness 0.25 mm, Agilent, Santa Clara, CA, United States). The raw data files were converted into netCDF (*.cdf) format according to the ANDI (Analytical Data Interchange Protocol) specification using the proprietary software GCMS solution (Shimadzu) before peak detection, baseline correction and retention time alignment using the freely available data processing tool MetAlign (Lommen, 2009 (link)). Data matrices from the alignment were then imported into AIoutput2 ver. 1.29 (Tsugawa et al., 2011 (link)) for automated Retention Index-based target compound identification and quantification.

Ohtake T., Kawase N., Pontrelli S., Nitta K., Laviña W.A., Shen C.R., Putri S.P., Liao J.C, & Fukusaki E. (2022). Metabolomics-Driven Identification of the Rate-Limiting Steps in 1-Propanol Production. Frontiers in Microbiology, 13, 871624.

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GC/MS Data Analysis Protocol

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GC/MS results were evaluated with the associated software GCMSsolution from Shimadzu. Further analysis employed statistical analysis using GraphPad Prism Version 5 (GraphPad Software, Inc., USA). T-Tests were performed followed by Welch’s test. Statistical significance was assumed if p was < 0.05.

Feuerecker B., Biechl P., Seidl C., Bruchertseifer F., Morgenstern A., Schwaiger M, & Eisenreich W. (2021). Diverse metabolic response of cancer cells treated with a 213Bi-anti-EGFR-immunoconjugate. Scientific Reports, 11, 6227.

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GC-MS Analysis of Organic Compounds

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The GC/MS-QP2010 Plus (Shimadzu®) fitted with a Zebron ZB 5MS column (Phenomenex®; 30 m × 0.25 mm × 0.25 μm) was used. An injection temperature of 230 °C was used, and 1 μL of each sample was injected with split 10 mode. The temperature program was initiated with a hold at 40 °C for 1 min, followed by a ramp of 6 °C/min to 210 °C, another 20 °C/min ramp till 330 °C, and a bake-out at 330 °C for 5 min, with helium as a carrier gas with constant linear velocity. The MS was employed with ion source and interface temperatures of 250 °C. A scan range (m/z) of 40–700 with a 0.2 s event time was used. For data processing, the “GCMS solution” software (Shimadzu®) was utilized.

Abu el Maaty M.A., Dabiri Y., Almouhanna F., Blagojevic B., Theobald J., Büttner M, & Wölfl S. (2018). Activation of pro-survival metabolic networks by 1,25(OH)2D3 does not hamper the sensitivity of breast cancer cells to chemotherapeutics. Cancer & Metabolism, 6, 11.

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Polar Metabolite Profiling of Plants

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Measurement of polar metabolites was carried out as it was described earlier (Marček et al. 2019) . Briefly, 200 mg FW of plant material was pulverised in a Qiagen (Germany) liquid nitrogen cooled TissueLyser. Sample extraction and GC-MS analysis was carried out according to Schauer et al. (2005) and Juhász et al. (2015) . The analyses were carried out with a GCMS-QP2010 system (Shimadzu, Japan) using a J&W HP5ms UI 30m × 0.25mm × 0,25μm capillary column (Agilent Technologies, USA). Data analysis was carried out using Shimadzu GC-MS Solution Postrun analysis software with searching the Wiley 9 th edition mass spectral database and using the Kovats retention index (RI) with a C7-40 n-alkane mixture. For identification the NIST17 Mass spectral and RI database was also used through the use of the AMDIS and MS Search v.2.3 software. Identified and quantified compounds were summarized in Table S1 with their respective retention time, retention index and their respective EIC quantitative ion or indication of TIC quantitation and reference material availability.

Janda T., Tajti J., Hamow K.Á., Marček T., Ivanovska B., Szalai G., Pál M., Zalewska E.D, & Darkó É. (2021). Acclimation of photosynthetic processes and metabolic responses to elevated temperatures in cereals. Physiologia plantarum, 171(2).

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Quantifying Methylmercury Species by GC/MS

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DMeHg (4 mM) or MeHgCl (4 mM) in 0.5 N HCl-50% methanol was incubated for 3 h or 4 days at room temperature in a glass vial, and then the sample was analyzed by GC/MS. Gas in the headspace of the sample tube was injected using a gas-tight syringe and separated by TC-BOND Q (30 m long, 0.32 mm i.d., 10 µm df; GL Sciences) with a PLOT column particle trap (2.5 m long, 0.25 mm i.d.; GL Sciences). The temperature was set as follows: 35 °C for 5 min; a linear increase to 220 °C (12 °C/min); and hold at 220 °C for 5 min. The eluted compounds were then transferred to the EI source of the system and analyzed using GCMSsolution (Shimadzu) as described above.

Abiko Y., Katayama Y., Zhao W., Horai S., Sakurai K, & Kumagai Y. (2021). The fate of methylmercury through the formation of bismethylmercury sulfide as an intermediate in mice. Scientific Reports, 11, 17598.

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GC-MS Compound Identification Protocol

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Data were processed with Agilent MSD ChemStation version D.03.00.611 and Shimadzu GCMSsolution version 2.51. GC peaks were identified by comparing their linear retention indices (calculated versus a C9–C25 hydrocarbon mixture) and their MS by comparison with those present in commercially available libraries (Wiley, Adams, NIST).

Azzollini A., Boggia L., Boccard J., Sgorbini B., Lecoultre N., Allard P.M., Rubiolo P., Rudaz S., Gindro K., Bicchi C, & Wolfender J.L. (2018). Dynamics of Metabolite Induction in Fungal Co-cultures by Metabolomics at Both Volatile and Non-volatile Levels. Frontiers in Microbiology, 9, 72.

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Quantitative GC-MS Isotopologue Analysis

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GC-MS data were evaluated with the software “GCMSsolution” from Shimadzu. Overall ¹³C-enrichments and isotopologue compositions were calculated by comparing with unlabeled samples using Excel scripts according to Ahmed et al. [46 (link)]: (https://www.uni-wuerzburg.de/forschung/spp1316/bioinformatics/isotopo/, accessed on 4 February 2022). All ¹³C-enrichment values were corrected for ¹³C-natural abundance. Cellular ¹³C-labeling experiments were performed at least twice; figures show the experimental averages with error bars denoting the range of data points.

Grashei M., Biechl P., Schilling F, & Otto A.M. (2022). Conversion of Hyperpolarized [1-13C]Pyruvate in Breast Cancer Cells Depends on Their Malignancy, Metabolic Program and Nutrient Microenvironment. Cancers, 14(7), 1845.

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