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. 2024 Sep;65(9):100621.
doi: 10.1016/j.jlr.2024.100621. Epub 2024 Aug 14.

The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data

Affiliations

The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data

Dominik Kopczynski et al. J Lipid Res. 2024 Sep.

Abstract

The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

Keywords: FAIR; checklist; lipid metabolism; lipidomics; mass spectrometry; metabolomics; quality control; reference standards.

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Conflict of interest statement

Conflict of interests Kaddurah-Daouk is an inventor on key patents in the field of metabolomics and hold equity in Metabolon, a biotech company in North Carolina. In addition, she holds patents licensed to Chymia LLC and PsyProtix with royalties and ownership. Kim Ekroos is the owner of Lipidomics Consulting Ltd.

Figures

Fig. 1
Fig. 1
Scope and aim of the lipidomics reporting checklist.
Fig. 2
Fig. 2
Outline of lipidomics workflow.
Fig. 3
Fig. 3
Preanalytics, sample handling and preservation.
Fig. 4
Fig. 4
A: Methods and conditions applied for lipid extraction. B: Solubility and recovery in lipid extractions are determined by the polarity of the lipids and solvents. Solvents (polarity index) and lipid classes are ordered by increasing polarity (gray triangle).
Fig. 5
Fig. 5
Definition of the analytical platform.
Fig. 6
Fig. 6
Reducing the complexity of the lipidome using mass spectrometry and separation-based analysis. For this computational experiment, all phospholipids, sphingolipids, sterols, and free fatty acids from LIPID MAPS (46) were considered. Here, PC 16:1_18:0 serves as a reference. For computing precursor masses, combinations of both lipid class common adducts and up to two 13C isotopes were taken into consideration. Interfering lipids are lipids that share the same set of features (mass-to-charge ratio; m/z) with the reference lipid within a given mass tolerance. Features are: positive/negative precursor ions, positive fragment ions m/z 184.07 (head group HG), negative fragment ions at m/z 255.23 (fatty acyl FA1) and m/z 281.24 (FA2). With increasing resolution and pre-separation the number of interfering lipids clearly can be reduced. Separation in the reversed phase is related to the lipophilicity or hydrophobicity of the compound displayed as a logP value.
Fig. 7
Fig. 7
Sufficient mass resolving power (R) can separate isobaric overlaps that are commonly present in lipidomic analysis, such as (A) Type-II overlaps occurring for double bond series and (B) isobars resulting from different bond types as seen for diacyl PC 16:0/17:1 and alkyl/acyl PC O-16:1/18:0.
Fig. 8
Fig. 8
Elucidation of lipid molecule structure and related annotation/structure level. Source: Adapted from Zhang et al. (31).
Fig. 9
Fig. 9
Lipid molecule quantification.
Fig. 10
Fig. 10
Blank and QC samples used for analytical evaluation of the workflow. Blanks provide insight into background lipids/contaminants and their origin. Quality Control (QC) samples are used to evaluate the reliability of the analysis.
Fig. 11
Fig. 11
Parameters that are typically evaluated in method validations and related guidelines.
Fig. 12
Fig. 12
Reporting of data.
Fig. 13
Fig. 13
Reporting checklist data handling.

References

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