Summary of Study ST001075
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000720. The data can be accessed directly via it's Project DOI: 10.21228/M8M977 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST001075 |
| Study Title | Integrated metabolome and transcriptome analyses provide novel insight into colon cancer modulation by the gut microbiota |
| Study Summary | Colon cancer onset and progression is strongly associated with the presence, absence, or relative abundances of certain microbial taxa in the gastrointestinal tract. However, specific mechanisms affecting disease susceptibility related to complex commensal bacterial mixtures are poorly understood. We used a multi-omics approach to determine how differences in the complex gut microbiome (GM) influence the metabolome and host transcriptome and ultimately affect susceptibility to adenoma development. Fecal samples collected from a preclinical rat model of colon cancer harboring distinct complex GMs were analyzed using ultra-high performance liquid chromatography mass spectrometry (UHPLC-MS). We collected samples prior to observable disease onset and identified putative metabolite profiles that predicted future disease severity, independent of GM status. Transcriptome analyses performed after disease onset from normal epithelium and tumor tissues between the high and low tumor GMs suggests that the GM is also correlated with altered host gene expression. Integrated pathway (IP) analyses of the metabolome and transcriptome based on putatively identified metabolic features indicate that bile acid biosynthesis was enriched in rats with high tumors (GM:F344) along with increased fatty acid metabolism and mucin biosynthesis. These data emphasize the utility of using untargeted metabolomics to reveal signatures of susceptibility and resistance and integrated analysis reveals common pathways that are likely to be universal targets for intervention. |
| Institute | University of Missouri-Columbia |
| Last Name | Busi |
| First Name | Susheel Bhanu |
| Address | 4011 Discovery Drive N121 |
| SB6F4@MAIL.MISSOURI.EDU | |
| Phone | 2404094390 |
| Submit Date | 2018-10-10 |
| Num Groups | 3 |
| Total Subjects | 13 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | cdf |
| Analysis Type Detail | GC-MS |
| Release Date | 2019-01-22 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN001757 |
|---|---|
| Analysis type | MS |
| Chromatography type | Reversed phase |
| Chromatography system | Agilent 1290 |
| Column | Waters Acquity BEH C18 (150 x 2.1mm,1.7um) |
| MS Type | ESI |
| MS instrument type | QTOF |
| MS instrument name | Bruker maXis Impact qTOF |
| Ion Mode | NEGATIVE |
| Units | Peak Area |
Chromatography:
| Chromatography ID: | CH001241 |
| Instrument Name: | Agilent 1290 |
| Column Name: | Waters Acquity BEH C18 (150 x 2.1mm,1.7um) |
| Chromatography Type: | Reversed phase |
