Summary of project PR001099
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 PR001099. The data can be accessed directly via it's Project DOI: 10.21228/M8N97J This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
Project ID: | PR001099 |
Project DOI: | doi: 10.21228/M8N97J |
Project Title: | Large-scale enzyme-based xenobiotic identification for exposomics |
Project Type: | Xenobiotic Metabolism |
Project Summary: | Exposomics methods are limited by low abundance of xenobiotic metabolites and lack of authentic standards, which precludes identification using solely mass spectrometry-based criteria. Here, we validate a method for enzymatic generation of xenobiotic metabolites for use with high-resolution mass spectrometry for chemical identification. Generated xenobiotic metabolites were used to confirm identities of respective metabolites in mice and human samples based upon accurate mass, retention time, and co-occurrence with related xenobiotic metabolites. The data shared here are high-resolution Orbitrap MS data for S9 incubations of 140 xenobiotic compounds with 0 and 24 hour time points for all reactions. |
Institute: | Emory University |
Department: | Medicine |
Laboratory: | Clinical Biomarkers Laboratory (Dean Jones, Ph.D PI) |
Last Name: | Liu |
First Name: | Ken |
Address: | 615 Michael Street, Suite 225, Atlanta, GA, 30329, USA |
Email: | hkliu@emory.edu |
Phone: | 4047275091 |
Funding Source: | U2CES026560 |
Summary of all studies in project PR001099
Study ID | Study Title | Species | Institute | Analysis(* : Contains Untargted data) | Release Date | Version | Samples | Download(* : Contains raw data) |
---|---|---|---|---|---|---|---|---|
ST001715 | Large-scale enzyme-based xenobiotic identification for exposomics | Homo sapiens | Emory University | MS* | 2021-06-01 | 1 | 1232 | Uploaded data (63.4G)* |