Summary of Study ST002911
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 PR001811. The data can be accessed directly via it's Project DOI: 10.21228/M8MQ7C 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 | ST002911 |
| Study Title | LiLA: Lipid Lung-based ATLAS built Through a Comprehensive Workflow Designed for an Accurate Lipid Annotation |
| Study Summary | Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present an optimized lipid annotation workflow based on the combination of LC-MS and MS/MS strategies, four bioinformatic tools, and a decision-tree-based approach to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The developed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis (Mtb) infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue. |
| Institute | Universidad CEU San Pablo |
| Department | Centro de MEtabolómica y Bioanálisis (CEMBIO) |
| Last Name | González |
| First Name | Carolina |
| Address | km 0, Universidad CEU-San Pablo Urbanización Montepríncipe. M-501 |
| carolina.gonzalezriano@ceu.es | |
| Phone | 646251045 |
| Submit Date | 2023-10-02 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzXML |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-10-20 |
| Release Version | 1 |
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Project:
| Project ID: | PR001811 |
| Project DOI: | doi: 10.21228/M8MQ7C |
| Project Title: | LiLA: Lipid Lung-based ATLAS built Through a Comprehensive Workflow Designed for an Accurate Lipid Annotation |
| Project Type: | Untargeted Lipidomics to build a Lung Tissue ATLAS |
| Project Summary: | Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present an optimized lipid annotation workflow based on the combination of LC-MS and MS/MS strategies, four bioinformatic tools, and a decision-tree-based approach to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The developed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis (Mtb) infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue. |
| Institute: | Universidad CEU San Pablo |
| Department: | Centro de MEtabolómica y Bioanálisis (CEMBIO) |
| Last Name: | Gonzalez-Riano |
| First Name: | Carolina |
| Address: | Facultad de Farmacia, Universidad CEU San Pablo, Campus Monteprincipe, Boadilla del Monte, Boadilla del Monte, Madrid, 28668, Spain |
| Email: | car.gonzalez@ceindo.ceu.es |
| Phone: | 00 34 91 3724753 |
| Funding Source: | This work was supported by grants from the following entities: Ministry of Science and Innovation of Spain (MICINN) and the European Regional Development Fund FEDER, grant number PID2021-122490NB-I00; and National Institute of Allergy and Infectious Diseases (NIAID)-University of Alabama (USA), grant number MUSUAB2. |
