Dataset Information

Software tool for internal standard based normalization of lipids, and effect of data-processing strategies on resulting values

ABSTRACT:

BACKGROUND: Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply individual internal standards to a broad range of related lipids. To aid in standardizing and automating this relative quantitation process, we developed LipidMatch Normalizer (LMN) http://secim.ufl.edu/secim-tools/ which can be used in most open source lipidomics workflows.

RESULTS: LMN uses a ranking system (1-3) to assign lipid standards to target analytes. A ranking of 1 signifies that both the lipid class and adduct of the internal standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class match. If multiple internal standards are provided for a lipid class, standards with the closest retention time to the target analyte will be chosen. The user can also signify which lipid classes an internal standard represents, for example indicating that ether-linked phosphatidylcholine can be semi-quantified using phosphatidylcholine. LMN is designed to work with any lipid identification software and feature finding software, and in this study is used to quantify lipids in NIST SRM 1950 human plasma annotated using LipidMatch and MZmine.

CONCLUSIONS: LMN can be integrated into an open source workflow which completes all data processing steps including feature finding, annotation, and quantification for LC-MS/MS studies. Using LMN we determined that in certain cases the use of peak height versus peak area, certain adducts, and negative versus positive polarity data can have major effects on the final concentration obtained.

INSTRUMENT(S): Liquid Chromatography Tandem MS (LC-MS/MS)

SUBMITTER: Jeremy Koelmel

PROVIDER: MTBLS710 | MetaboLights | 2022-05-17

REPOSITORIES: MetaboLights

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Dataset's files

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			Action	DRS
	MTBLS710	Other
	FILES	Other
	a_MTBLS710_NEG_metabolite_profiling_mass_spectrometry.txt	Txt
	a_MTBLS710_POS_metabolite_profiling_mass_spectrometry.txt	Txt
	files-all.json	Other

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Publications

Software tool for internal standard based normalization of lipids, and effect of data-processing strategies on resulting values.

Koelmel Jeremy P JP Cochran Jason A JA Ulmer Candice Z CZ Levy Allison J AJ Patterson Rainey E RE Olsen Berkley C BC Yost Richard A RA Bowden John A JA Garrett Timothy J TJ

BMC bioinformatics 20190429 1

<h4>Background</h4>Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and disease. While lipids diverse biological roles contribute to their clinical utility, the diversity of lipid structure and concentrations prove to make lipidomics analytically challenging. Without internal standards to match each lipid species, researchers often apply ind ...[more]

PMID: 31035918

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