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Series GSE21720 Query DataSets for GSE21720
Status Public on Feb 08, 2011
Title A metabolomics analysis of Salmonella infection
Organism Mus musculus
Experiment type Other
Summary The interplay between pathogens and hosts has been studied for decades using targeted approaches such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods such as transcriptomics and proteomics have been used to study host-pathogen interactions. Recently, metabolomics was established as a new method to study changes in the biochemical composition of host tissues.

We report a metabolomics study of Salmonella enterica serovar Typhimurium infection. We used Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Direct Infusion to reveal that dozens of host metabolic pathways are affected by Salmonella in a murine infection model. In particular, multiple host hormone pathways are disrupted. Our results identify unappreciated effects of infection on host metabolism and shed light on mechanisms used by Salmonella to cause disease, and by the host to counter infection.
Overall design Female C57BL/6 mice were infected with Salmonella enterica serovar Typhimurium SL1344 cells by oral gavage. Feces and livers were collected and metabolites extracted using acetonitrile. For experiments with feces, samples were collected from 4 mice before and after infection. For liver experiments, 11 uninfected and 11 infected mice were used. Samples were combined into 3 groups of 3-4 mice each, resulting in the analysis of 3 group samples of uninfected and 3 of infected mice. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140 [PMID 19081807]). To identify differences in metabolite composition between uninfected and infected samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from uninfected and infected mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix ( 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.
Contributor(s) Antunes LC, Arena ET, Menendez A, Han J, Ferreira RB, Buckner MM, Lolić P, Borchers CH, Finlay BB
Citation(s) 21321075
Submission date May 06, 2010
Last update date Mar 22, 2012
Contact name L. Caetano M. Antunes
Phone 604-827-3921
Organization name The University of British Columbia
Department Michael Smith Laboratories
Lab Finlay Lab
Street address #367 - 2185 East Mall
City Vancouver
State/province BC
ZIP/Postal code V6T 1Z4
Country Canada
Platforms (1)
GPL10454 Mouse metabolomics mass spec data
Samples (14)
GSM546206 Feces, Uninfected, 1
GSM546207 Feces, Uninfected, 2
GSM546208 Feces, Uninfected, 3
BioProject PRJNA127359

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE21720_RAW.tar 176.3 Mb (http)(custom) TAR (of BAF)
GSE21720_feces_masses.txt.gz 71.4 Kb (ftp)(http) TXT
GSE21720_liver_masses.txt.gz 39.7 Kb (ftp)(http) TXT
GSE21720_readme.txt 941 b (ftp)(http) TXT
Processed data are available on Series record

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