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Pegasus ht tof ms

Manufactured by Agilent Technologies
Sourced in Canada, Sweden

The Pegasus HT TOF-MS is a high-throughput time-of-flight mass spectrometer (TOF-MS) designed for analytical laboratories. It provides accurate mass measurements and high-speed data acquisition for a range of applications.

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4 protocols using pegasus ht tof ms

1

Metabolomic Analysis of Colonic Contents

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Metabolomic analysis of colonic contents was conducted by multiple mass spectrometry (MS) platforms, including gas chromatography mass spectrometry/time-of-flight (GC-MS/TOF) and ultrahigh-performance liquid chromatography/mass spectrometry (UHPLC/MS). GC-MS/TOF analysis was performed on the Agilent 7890A gas chromatograph system coupled with the Pegasus HT TOF MS (Leco) while UHPLC/MS analysis was conducted on the Agilent 1290 UHPLC system coupled to TripleTOF 6600 system (Q-TOF, AB Sciex, Concord, ON, Canada). Further multivariate statistical analysis was performed on the SIMCA software (Version 14.1, MKS Data Analytics Solutions, Concord, ON, Canada). Group differences and group separation variables were analyzed using Orthogonal projections to latent structures-discriminate analysis (OPLS-DA). The predictive ability parameter Q2 and goodness-of-fit parameter R2Y were obtained for estimating the model quality after seven-fold cross validation. The metabolite set enrichment analysis and pathway analysis were carried out to generate the related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of each differential metabolite and biomarker metabolic pathways, separately, on the web-based tool MetaboAnalyst (http://www.meta-boanalyst.ca, accessed on 17 March 2021).
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2

GC-MS Analysis of Metabolite Samples

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GC-MS analysis was performed on a Leco Pegasus HT TOF-MS equipped with an Agilent 7890A gas chromatograph at the Swedish Metabolomics Center, Umeå, Sweden, https://www.swedishmetabolomicscentre.se/. The derivatized samples, 1 μl, were auto-injected (splittless) at a temperature of 270 °C. The ion source temperature was 200 °C and the ionization energy was 70 eV. Mass spectra were collected in the mass range 50 to 800 m/z. n-alkanes (C8-C40) were used as external retention index standards.
For samples J1_1–6 a 30 m GC-column with an inner diameter of 0.25 mm was used. The purge delay time was 75 seconds and the rate was 20 mL/min. Helium was used as carrier gas (1 mL/min). The GC oven temperature was 70 °C for 2 minutes and then increased 20 °C/minute to 320 °C, where it was held constant for 8 minutes. The detector voltage was 1670 V.
All other samples employed a 10 m GC-column with an inner diameter of 0.18 mm. The purge delay time was 60 seconds and the rate was 20 mL/min. Helium was used as carrier gas (1 mL/min). The GC oven temperature was 70 °C for 2 minutes and then increased 40 °C/minute to 320 °C, where it was held constant for 2 minutes. The detector voltage was 1920 V.
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3

GC-TOF-MS Quantification of Fecal Metabolites

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The metabolomics data of human faecal samples were quantified by GC–TOF–MS (Agilent 6890N GC coupled with a LECO Pegasus HT TOF–MS). The details of analytical condition as described in previous study65 (link).
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4

Metabolomic Analysis of Hepatopancreas Extracts

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Samples (0.05 g, n = 8) in each group were extracted with 0.4 mL methanol-chloroform (v:v, 4:1). l-2-chlorophenylalanine (20 μL) was added as an internal standard and then centrifuged (11,000 × g, 15 min, 4°C). The supernatant was then transferred to a 2-ml GC/MS glass vial, and 15 μL from each sample were analyzed for quality control purposes. The hepatopancreas extracts were processed using a method described in a recent study (Li et al., 2017 (link)).
GC-time-of-flight (TOF)-MS analysis was conducted using an Agilent 7890 GC system coupled with a Pegasus HT TOF-MS, as previously described (Li et al., 2017 (link)). Each sample in the present study was analyzed eight times. Chroma TOF4.3X software (LECO Corporation, USA) and the LECO-Fiehn Rtx5 database were used for raw peak extraction, data baseline filtering and calibration, peak alignment, deconvolution analysis, peak identification, and integration of peak areas (Kind et al., 2009 (link)). Metabolomics data have been deposited to the EMBL-EBI MetaboLights database (Haug et al., 2013 (link)) with the identifier MTBLS481. The complete dataset can be accessed https://www.ebi.ac.uk/metabolights/MTBLS584.
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