Summary of Study ST003799
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 PR002363. The data can be accessed directly via it's Project DOI: 10.21228/M8653M 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 | ST003799 |
| Study Title | Molecular fingerprint inference reveals bioactive lipids and microbial metabolites in colitis. Study 2. |
| Study Type | Bacterial cell cultures |
| Study Summary | Untargeted metabolomics provides a sensitive readout of small molecules in biofluids, but requires targeted approaches to resolve ~90% of features for which tandem mass spectra (MS/MS) are not collected. By training on a subset of verified metabolites and their profiles in LC-MS, we derive a probabilistic model to predict molecular fingerprints in human stool and blood samples. These predictions, which do not utilize MS/MS, were accurate for >44% (correct top ranked candidate) or >75% (correct within top 3) of test metabolites, drastically reducing the number of reference standards that would need to be to be tested. These predictions revealed markers and drivers of inflammation, including amino acid derivatives and lysophospholipids with herein demonstrated platelet-activating factor receptor (PAF-R) activity. Integration with bacterial culturomics facilitates tracking the source of inflammation-associated metabolites to their origins in the gut microbiome. |
| Institute | Broad Institute of MIT and Harvard |
| Last Name | Avila-Pacheco |
| First Name | Julian |
| Address | 415 Main Street |
| jravilap@broadinstitute.org | |
| Phone | (617) 714-1729 |
| Submit Date | 2025-03-04 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzML, raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2025-08-04 |
| Release Version | 1 |
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Project:
| Project ID: | PR002363 |
| Project DOI: | doi: 10.21228/M8653M |
| Project Title: | Molecular fingerprint inference reveals bioactive lipids and microbial metabolites in colitis |
| Project Summary: | Untargeted metabolomics provides a sensitive readout of small molecules in biofluids, but requires targeted approaches to resolve ~90% of features for which tandem mass spectra (MS/MS) are not collected. By training on a subset of verified metabolites and their profiles in LC-MS, we derive a probabilistic model to predict molecular fingerprints in human stool and blood samples. These predictions, which do not utilize MS/MS, were accurate for >44% (correct top ranked candidate) or >75% (correct within top 3) of test metabolites, drastically reducing the number of reference standards that would need to be to be tested. These predictions revealed markers and drivers of inflammation, including amino acid derivatives and lysophospholipids with herein demonstrated platelet-activating factor receptor (PAF-R) activity. Integration with bacterial culturomics facilitates tracking the source of inflammation-associated metabolites to their origins in the gut microbiome. |
| Institute: | Broad Institute of MIT and Harvard |
| Last Name: | Avila-Pacheco |
| First Name: | Julian |
| Address: | 415 Main Street |
| Email: | jravilap@broadinstitute.org |
| Phone: | +1 (617) 714-1729 |
