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A prototypic small molecule database for bronchoalveolar lavage-based metabolomics

The analysis of bronchoalveolar lavage fluid (BALF) using mass spectrometry-based metabolomics can provide insight into lung diseases, such as asthma. However, the important step of compound identification is hindered by the lack of a small molecule database that is specific for BALF. Here we descri...

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Autores principales: Walmsley, Scott, Cruickshank-Quinn, Charmion, Quinn, Kevin, Zhang, Xing, Petrache, Irina, Bowler, Russell P., Reisdorph, Richard, Reisdorph, Nichole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5903367/
https://www.ncbi.nlm.nih.gov/pubmed/29664467
http://dx.doi.org/10.1038/sdata.2018.60
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author Walmsley, Scott
Cruickshank-Quinn, Charmion
Quinn, Kevin
Zhang, Xing
Petrache, Irina
Bowler, Russell P.
Reisdorph, Richard
Reisdorph, Nichole
author_facet Walmsley, Scott
Cruickshank-Quinn, Charmion
Quinn, Kevin
Zhang, Xing
Petrache, Irina
Bowler, Russell P.
Reisdorph, Richard
Reisdorph, Nichole
author_sort Walmsley, Scott
collection PubMed
description The analysis of bronchoalveolar lavage fluid (BALF) using mass spectrometry-based metabolomics can provide insight into lung diseases, such as asthma. However, the important step of compound identification is hindered by the lack of a small molecule database that is specific for BALF. Here we describe prototypic, small molecule databases derived from human BALF samples (n=117). Human BALF was extracted into lipid and aqueous fractions and analyzed using liquid chromatography mass spectrometry. Following filtering to reduce contaminants and artifacts, the resulting BALF databases (BALF-DBs) contain 11,736 lipid and 658 aqueous compounds. Over 10% of these were found in 100% of samples. Testing the BALF-DBs using nested test sets produced a 99% match rate for lipids and 47% match rate for aqueous molecules. Searching an independent dataset resulted in 45% matching to the lipid BALF-DB compared to<25% when general databases are searched. The BALF-DBs are available for download from MetaboLights. Overall, the BALF-DBs can reduce false positives and improve confidence in compound identification compared to when general databases are used.
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spelling pubmed-59033672018-05-01 A prototypic small molecule database for bronchoalveolar lavage-based metabolomics Walmsley, Scott Cruickshank-Quinn, Charmion Quinn, Kevin Zhang, Xing Petrache, Irina Bowler, Russell P. Reisdorph, Richard Reisdorph, Nichole Sci Data Data Descriptor The analysis of bronchoalveolar lavage fluid (BALF) using mass spectrometry-based metabolomics can provide insight into lung diseases, such as asthma. However, the important step of compound identification is hindered by the lack of a small molecule database that is specific for BALF. Here we describe prototypic, small molecule databases derived from human BALF samples (n=117). Human BALF was extracted into lipid and aqueous fractions and analyzed using liquid chromatography mass spectrometry. Following filtering to reduce contaminants and artifacts, the resulting BALF databases (BALF-DBs) contain 11,736 lipid and 658 aqueous compounds. Over 10% of these were found in 100% of samples. Testing the BALF-DBs using nested test sets produced a 99% match rate for lipids and 47% match rate for aqueous molecules. Searching an independent dataset resulted in 45% matching to the lipid BALF-DB compared to<25% when general databases are searched. The BALF-DBs are available for download from MetaboLights. Overall, the BALF-DBs can reduce false positives and improve confidence in compound identification compared to when general databases are used. Nature Publishing Group 2018-04-17 /pmc/articles/PMC5903367/ /pubmed/29664467 http://dx.doi.org/10.1038/sdata.2018.60 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Walmsley, Scott
Cruickshank-Quinn, Charmion
Quinn, Kevin
Zhang, Xing
Petrache, Irina
Bowler, Russell P.
Reisdorph, Richard
Reisdorph, Nichole
A prototypic small molecule database for bronchoalveolar lavage-based metabolomics
title A prototypic small molecule database for bronchoalveolar lavage-based metabolomics
title_full A prototypic small molecule database for bronchoalveolar lavage-based metabolomics
title_fullStr A prototypic small molecule database for bronchoalveolar lavage-based metabolomics
title_full_unstemmed A prototypic small molecule database for bronchoalveolar lavage-based metabolomics
title_short A prototypic small molecule database for bronchoalveolar lavage-based metabolomics
title_sort prototypic small molecule database for bronchoalveolar lavage-based metabolomics
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5903367/
https://www.ncbi.nlm.nih.gov/pubmed/29664467
http://dx.doi.org/10.1038/sdata.2018.60
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