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 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR000804 |
Project DOI: | doi: 10.21228/M8RM32 |
Project Title: | A large library of gut bacterial isolates paired with longitudinal multiomics data enables mechanistic microbiome studies |
Project Type: | Metabolite profiling of human stool from a healthy cohort |
Project Summary: | Here, we present the Broad Institute-OpenBiome Microbiome Library (BIO-ML), a comprehensive collection of 7,758 gut bacterial isolates with 3,632 paired genome sequences, and densely sampled multi-omic time series from many individual humans. Our longitudinal data reveal (1) that microbial species maintain stable population sizes within and across humans, (2) that commonly used ‘omic survey methods are more reliable when using averages over multiple days of sampling, (3) that variation of gut metabolites within people over time is driven by amino acid levels, while differences across people are driven by differences in bile acids, and (4) that functional evolution and genomic diversification can be used to infer eco-evolutionary dynamics and in vivo selection pressures for strains within individual people. The BIO-ML is a unique resource that will enable hypothesis-driven microbiome research and the rational design of microbial therapeutics. |
Institute: | Broad Institute of MIT and Harvard |
Department: | Metabolomics Platform |
Last Name: | Avila-Pacheco |
First Name: | Julian |
Address: | 415 Main Street, Rm 7175, Cambridge, MA, 02142, USA |
Email: | jravilap@broadinstitute.org |
Phone: | 6177148264 |
Contributors: | Mathilde Poyet, Mathieu Groussin, Sean M Gibbons, Julian Avila-Pacheco, Xiaogang Jiang, Sean M Kearney, Allison R Perrotta, Shijie Zhao, Tammi Lieberman, P K Swanson, Mark Smith, Shane Roesemann, Jessica E Alexander, Scott A. Rich, Jonathan Livny, Hera Vlamakis, Clary Clish, Kevin Bullock, Amy Deik, Justin Scott, Kerry Pierce, Ramnik Xavier, Eric J Alm |