Published: 31-01-2019| Version 1 | DOI: 10.17632/kv6bh2zkht.1
Michal Grzybek,
Alessandra Palladini,
Vasileia Ismini Alexaki,
Michal Surma,
Kai Simons,
Triantafyllos Chavakis,
Christian Klose,
Uenal Coskun


Shotgun lipidomics enables the detection of lipids from theoretically all kinds of substrate, provided that extraction and processing procedures are adapted, to ensure good coverage and reproducible quantification of the lipidome. The quantification of lipids from Adipose tissue (AT) is particularly challenging due to the predominance of triacylglycerides, which elicit high ion suppression of the remaining lipid classes. We generated this data by applying a new and validated method for shotgun lipidomics of AT, which tailors the lipid extraction procedure to the target specimen. In particular, we analysed three AT types (brown - BAT; gonadal - GAT; inguinal subcutaneous - SAT) from 10 lean (chow diet - CD) and 10 obese (high fat diet - HFD) mice. We observed tissue-specific and diet-related differences, with Brown AT exhibiting a distinct lipidomic profile with the greatest lipid class diversity and responding to high-fat diet by altering its lipid composition, so that it becomes more similar to that of white AT. Moreover, diet-induced obesity promoted an overall remodelling of the lipidome, where all three AT types featured a significant increase in longer and more unsaturated triacylglyceride and phospholipid species. By presenting our method we intend to facilitate reproducible systematic lipidomic profiling of AT. The data generated within this project is intended as a proof of concept that the method works and gives results that are compatible with what was found in other papers. In addition, we provide a first explorative analysis of the effects of overnutrition on the AT lipidome.


Steps to reproduce

The dataset contains the picomol amount of the lipid species detected in 60 samples (3 types of AT from 10 female mice on chow diet and from 10 female mice on HFD). It is already filtered, i.e. all lipids missing in at least 50% of the samples in a cohort were removed from that cohort. Each TAG species' name features the first acyl chain that was detected. This kind of nomenclature implies, on one hand, that when a TAG species is particularly rich in a given acyl chain, then we are more likely to obtain a TAG species with that given acyl chain. On the other hand this kind of nomenclature can feature TAG species that are not unique: since each TAG contains 3 acyl chains, then <TAG_60:4-FA_18:2> and <TAG_60:4-FA_24:1> may be the same species. To reproduce the descriptive statistics presented in the article, picomol data should be transformed to percent.