Summary of Study ST001192
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 PR000804. The data can be accessed directly via it's Project DOI: 10.21228/M8RM32 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 | ST001192 |
| Study Title | A library of human gut bacterial isolates paired with longitudinal multiomics data enables mechanistic microbiome research |
| Study Type | Stool metabolite profiling |
| Study Summary | Fecal microbiota transplantation (FMT) is used in the treatment of microbiome-associated diseases such as Clostridium difficile infections. In order to develop synthetic therapeutics and customized disease treatments we will need to understand the bacterial communities in the stool samples used in such treatments. For this purpose, a microbiome library was generated using human stool obtained from healthy human FMT recruited by OpenBiome, a non-profit organization that provides fecal microbiome therapeutics. In addition to characterizing the bacterial populations and obtaining bacterial isolates from FMT samples, we conducted metabolite profiling with the goal of: (1) generating a library of metabolites in FMT samples, (2) Identifying metabolites associated with defined bacterial populations, and (3) identifying microbial metabolites with immunoregulatory functions. We conducted metabolite profiling on a subset consisting of 180 stool samples from 84 donors using four nontargeted liquid chromatography mass spectrometry (LC-MS) methods. Generated data were processed, isotopes removed, and adducts and fragments clustered. The identity of known metabolites was determined based on matching retention times of neat standards run in parallel with the study. |
| Institute | Broad Institute of MIT and Harvard |
| Last Name | Avila-Pacheco |
| First Name | Julian |
| Address | 415 Main Street |
| jravilap@broadinstitute.org | |
| Phone | 617-714-8264 |
| Submit Date | 2019-06-10 |
| Total Subjects | 84 |
| Raw Data Available | Yes |
| Analysis Type Detail | LC-MS |
| Release Date | 2019-07-17 |
| Release Version | 1 |
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Subject:
| Subject ID: | SU001259 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens |
| Taxonomy ID: | 9606 |
