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.

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Study IDST001192
Study TitleA library of human gut bacterial isolates paired with longitudinal multiomics data enables mechanistic microbiome research
Study TypeStool metabolite profiling
Study SummaryFecal 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 NameAvila-Pacheco
First NameJulian
Address415 Main Street
Emailjravilap@broadinstitute.org
Phone617-714-8264
Submit Date2019-06-10
Total Subjects84
Raw Data AvailableYes
Analysis Type DetailLC-MS
Release Date2019-07-17
Release Version1
Julian Avila-Pacheco Julian Avila-Pacheco
https://dx.doi.org/10.21228/M8RM32
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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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
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