Dataset features

Specifications


Dataset type: Other
Number of samples: 8
Release date: Feb 8 2011
Last update date: Mar 22 2012
Access: Public
Chemicals: Bile Acids and Salts, Steroids, Streptomycin
Dataset link The effect of antibiotic treatment on the intestinal metabolome

Experimental Protocol


Age-matched female C57BL/6 mice were used. Fresh feces were collected and stored at -80 oC. Mice were then treated with 20 mg of streptomycin through oral gavage and fresh feces were collected 24 hours after treatment and stored at -80 oC until used. To extract metabolites from feces, acetonitrile was added to samples (approximately 10-25 μL of acetonitrile per 1 mg of tissue), which were then homogenized. The samples were then cleared by centrifugation and the supernatant was collected and dried at room temperature using a centrifuge equipped with a vacuum pump. All extracts were kept at -80 oC until used. For metabolic profiling, the dried extracts from mouse feces were suspended in a 2:3 mixture of water and acetonitrile (10 μL per 1 mg of tissue), vortexed and cleared by centrifugation. Supernatants were collected and used as described below. Extracts were diluted 1:5 with 60% acetonitrile containing either 0.2% formic acid (for positive ion mode) or 0.5% ammonium hydroxide (for negative ion mode) and spiked with predefined amounts of the "ES tuning mix" solution as the internal standard for mass calibration. The solutions were then infused, using a syringe pump (KDS Scientific, Holliston, USA) at a flow rate of 2.5 µL per minute, into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer (Bruker Daltonics, Billerica, USA) equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Data were recorded in positive and negative ion modes with broadband detection and an FT acquisition size of 1024 kilobytes per second, within a range of m/z 150 to 1100. Under these settings, a mass resolution of ca. 100,000 (full width at half maximum, FWHM) at m/z 400 and a mass accuracy within 2 ppm or less for all detected components, following internal mass calibration, were observed. Other experimental parameters were: capillary electrospray voltage of 3600-3750 V, spray shield voltage of 3300-3450 V, source ion accumulation time of 0.1 s and collision cell ion accumulation time of 0.2 s. To increase detection sensitivity, survey scan mass spectra in positive and negative ion modes were acquired from the accumulation of 200 scans per spectrum, and duplicate acquisitions per sample were carried out to ensure data reproducibility. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140). To identify differences in metabolite composition between untreated and treated samples, we first filtered our list of masses for metabolites that were present on one set of samples (untreated or treated) but not the other. Additionally, we averaged the mass intensities of metabolites in each group and calculated the ratios between averaged intensities of metabolites from untreated and treated samples. To assign possible metabolite identities to the masses present in only one of the sample groups or showing at least a 2-fold change in intensities between the sample groups, the monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org), a free-access software designed to incorporate masses into metabolic pathways. Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.

Repositories


GEO

GSE25687

ArrayExpress

E-GEOD-25687

BioProject

PRJNA135837

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Contact


L. Caetano Antunes
L. Caetano M. Antunes