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Gc ms 5975

Manufactured by Agilent Technologies
Sourced in United States

The GC/MS 5975 is a gas chromatography-mass spectrometry (GC/MS) system manufactured by Agilent Technologies. It is designed to provide high-performance analytical capabilities for the identification and quantification of chemical compounds in a variety of sample types. The GC/MS 5975 combines gas chromatography for the separation of complex mixtures with mass spectrometry for the identification and quantification of individual components.

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8 protocols using gc ms 5975

1

GC-MS Analysis of T. peruviana Extracts

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To remove interfering matrices, the samples were first cleaned up using sample cleanup procedure, the analyte concentrated and the sample matrix changed to GC grade before analysis. Briefly, the solid phase extraction procedure employed C18 cartilage conditioned with 3 mL of methanol then 3 mL of sample was loaded to allow it flow slowly out of the cartilage giving it enough time to interact with adsorbent. The sample was then allowed to dry in a stream of air for 10 min and thereafter eluted with 3 mL methanol into a 4 mL vial, concentrated using genetic concentrator, reconstituted with 1 mL of methanol, filtered using nylon micro filters size 0.22 μM into 1.5 mL vials and taken to GC-MS for analysis. GC–MS analysis of crude T. peruviana was evaluated using a shimadzu GC–MS at JKUAT, Analytical laboratory. 5 g of the powdered plant samples was extracted with Acetonitrile, then solvent exchanged with 2, 2, 4-Trimethylpentane before GCMS analysis. GC–MS technique was used for identification of the chemical compounds present in the extracts and it was carried out on Agilent 5975 GC–MS operating in EI mode at 70 eV with a mass range of 40–400 m/z. A capillary column 30 m × 0.25 mm (id) and Helium gas was used as carrier gas with flow rate of 1.2 mL/min and oven temperature of 60 °C [27 (link)].
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2

Free Amino Acid Analysis by GC-MS

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The EZ:Faast GC-MS kit was used for free amino acid analysis as described previously (Elmore, Mottram, Muttucumaru, Dodson, Parry, & Halford, 2007) . Samples were analysed using an Agilent 5975 GC-MS equipped with a ZB-AAA capillary column (10 m x 250 µm x 0.25 µm). Samples (2 µL) were injected at 250 °C in split mode (10:1) using helium as a carrier gas at a flow rate of 1.1 mL/min. The initial oven temperature was set at 110 °C and immediately followed by a temperature ramp to 320 °C at 30 °C /min. The transfer line, ion source and quadrupole temperatures were set at 280 °C, 240 °C and 180 °C, respectively. The mass spectrometer was operated in the total ion scan mode (m/z 45-450) and m/z 155 and 160 were used as the quantitation ions for asparagine and 13 C-asparagine, respectively.
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3

GC-MS Analysis of Ethyl Acetate Crude

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The active ethyl acetate crude was subjected to GC-MS analysis on GC-MS- 5975 (AGILENT), column DB 5 ms Agilent, dimension length- 30.0 m, ID- 0.2 mm, flim thickness- 0.25 μm with temperature program- 70–300°C, 10°C/min, injection temperature- 240°C, carrier gas- helium, flowrate- 1.51 ml/min, equipped with GC-MS NIST-II library.
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4

GC/MS Data Analysis Pipeline

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Raw GC/MS data were converted into the CDF format (NetCDF) using Agilent GC/MS 5975 data analysis software and were subsequently processed with XCMS (http://www.bioconductor.org) using XdCMS default settings with the following changes: xcmsSet (fwhm = 3, snthresh = 3, max = 300, mzdiff = 0.5, step = 0.1, steps = 2), rector (method = “linear”, family = “gaussian”, plottype = “mdevden”), and bandwidth (bw) of five. The identities of the compounds responsible for specific resolved peaks in the mass spectra were determined by performing database searches based on the mass spectra and the compounds’ chromatographic retention indices. The databases used were the NIST 2011 Mass Spectra Library, an in-house database established by Ume a Plant Science Centre (UPSC), and the mass spectra library maintained by the Max Planck Institute in Golm, Germany (http://csbdb.mpimp-golm.mpg.de/csbdb/gmd/gmd.html).
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5

Metabolite Extraction and GC/MS Analysis

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Extraction of metabolites from gut content samples was according to Lisec et al. (2006) (link) with some modification. Gas chromatography was performed on a HP-5MS capillary column [5% phenyl/95% methylpolysiloxane (30 m × 250 μm i.d., 0.25 μm film thickness, Agilent J&W Scientific, Folsom, CA, USA)] to separate the derivatives at a constant flow of 1 mL/min helium. Raw gas chromatography/mass spectrometry data (GC/MS) data were converted into CDF format (NetCDF) files by Agilent GC/MS 5975. Data Analysis was processed by the XCMS2. Detailed protocols for metabolite extraction and GC/MS analyses were provided in Supporting Information Methods.
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6

Isotopic Enrichment Analysis of Glucose

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Isotopic enrichment of [6,6-2H2]-glucose and [U-13C6]glucose was measured by electron impact ionisation on a GC/MS 5975 (Agilent Technologies, USA) using a 30 m× 0.25 mm HP-5MS column by monitoring ions at m/z 202/200 and 205/200, as previously described [22 ]. For all GC/MS analyses, instrument response was calibrated using standards of known enrichment. Glucose enrichment was good; the lowest average (mean) tracer-to-tracee ratio was 1%.
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7

GC-MS Metabolite Identification Protocol

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For the metabolite identification, the Agilent GC–MS 5975 Data Analysis software was used to convert the raw GC–MS data into NetCDF format. The peaks were identified, filtered and aligned via XCMS software version 1.42.0 using XCMS's default settings with the following changes: xcmsSet (fwhm = 3, snthresh = 3, mzdiff = 0.5, step = 0.1, steps = 2, max = 300), group (bw = 2, minfrac = 0.3, max = 300)75 (link). Metabolites were annotated using the Automatic Mass Spectral Deconvolution and Identification System (AMIDS) version 2.73 based on Wiley Registry and National Institute of Standards and Technology (NIST). Metabolites were confirmed via comparison of mass spectra and retention indices to the Golm Metabolome Database (GMD, http://gmd.mpimp-golm.mpg.de/) using a cut-off value of 70%. The signal integration area of each metabolite was normalized to the internal standard (Nonadecylic acid and d4-Alanine) for each sample.
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8

GC-MS Metabolite Identification Protocol

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Raw GC-MS data were converted into CDF format (NetCDF) files by Agilent GC/MS 5975 Data Analysis software and subsequently processed using XCMS (www.bioconductor.org), implementing the default settings with the following modifications: xcmsSet (fwhm = 3, snthresh = 3, mzdiff = 0.5, step = 0.1, steps = 2, max = 300) and group (bw = 2, minfrac = 0.3, max = 300). The signal integration area of each metabolite was normalized to the internal standard (ribitol) for each sample. Identification of metabolites using the Automatic Mass Spectral Deconvolution and Identification System (AMIDS) was searched against commercial available databases such as the National Institute of Standards and Technology (NIST) and Wiley libraries. Metabolites were confirmed by comparison of mass spectra and retention indices to the spectra library using a cut-off value of 70% (Dawud et al. 2012 ).
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