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| Status |
Public on Feb 08, 2011 |
| Title |
Feces, Untreated 4 |
| Sample type |
other |
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| Source name |
Feces
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| Organism |
Mus musculus |
| Characteristics |
strain: C57BL/6
gender: Female
treatment: untreated
source: feces
molecule type: metabolites
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| Treatment protocol |
No treatment
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| Extracted molecule |
other |
| Extraction protocol |
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.
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| Label |
Not applicable
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| Label protocol |
Not applicable
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| Hybridization protocol |
Not applicable
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| Scan protocol |
Not applicable
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| Description |
Each sample was measured twice in negative and twice in positive ionization modes.
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| Data processing |
Raw mass spectrometry data were processed using a custom-developed software package, as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140). First, raw mass spectra acquired from each sample group were batch-processed using the instrument vendor’s data analysis software, DataAnalysis®, but with a home-written VBA script to do automatic internal mass calibration with the reference masses of the spiked calibration standards and a known contaminant, N-butylbenzensulfonamide. Monoisotopic peaks corresponding to the isotopic pattern distributions were then automatically determined and those with a signal/noise ratio above 3 were picked. Their m/z values were converted to neutral masses by subtracting 1.007276 for positive ion mode or adding 1.007276 for negative ion mode. Next, the resulting mass lists from all the mass spectra within each set of untreated or treated groups detected in positive or negative ion modes were further processed with another customized software program developed with LabVIEW® (National Instruments, Austin, USA). Adduct ions were recognized and converted to neutral masses from the mass lists based on the expected mass differences between protonated (M+H)+, (M+Na)+ and/or (M+K)+ ions for positive ion mode or deprotonated (M-H)- and (M+Cl)- ions for negative ion mode, within 2 ppm, to yield a list of unique biochemical component masses together with the sum of their peak intensities. The peak intensities of all the monoisotopic neutral masses are subsequently normalized to the intra-sample total ion intensity. Masses observed in at least three of four samples from one of the sample groups (untreated or treated) were aligned and then combined into unique metabolite features from the masses that matched within 2 ppm across all the data. Finally, a two-dimensional data matrix (mass vs. relative intensity) was generated for each sample group and saved in a format amenable for further data analysis. Heat maps were then created using the freely-available softwares Cluster and Java TreeView (http://rana.lbl.gov/eisensoftware.htm). 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 using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg/). Masses were searched against the Mus musculus database within a mass error of 3 ppm.
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| Submission date |
Nov 29, 2010 |
| Last update date |
Feb 09, 2011 |
| Contact name |
L. Caetano M. Antunes |
| E-mail(s) |
antunes@mail.ubc.ca
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| Phone |
604-827-3921
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| Organization name |
The University of British Columbia
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| Department |
Michael Smith Laboratories
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| Lab |
Finlay Lab
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| Street address |
#367 - 2185 East Mall
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| City |
Vancouver |
| State/province |
BC |
| ZIP/Postal code |
V6T 1Z4 |
| Country |
Canada |
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| Platform ID |
GPL10454 |
| Series (1) |
| GSE25687 |
The effect of antibiotic treatment on the intestinal metabolome |
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| Supplementary file |
Size |
Download |
File type/resource |
| GSM630882_U4_ESI+1.baf.gz |
3.2 Mb |
(ftp)(http) |
BAF |
| GSM630882_U4_ESI+2.baf.gz |
3.2 Mb |
(ftp)(http) |
BAF |
| GSM630882_U4_ESI-1.baf.gz |
3.2 Mb |
(ftp)(http) |
BAF |
| GSM630882_U4_ESI-2.baf.gz |
3.2 Mb |
(ftp)(http) |
BAF |
| Processed data are available on Series record |
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