Dataset Information

Lipidomics Reveals a Tissue-Specific Fingerprint.

ABSTRACT: In biological systems lipids generate membranes and have a key role in cell signaling and energy storage. Therefore, there is a wide diversity of molecular lipid expressed at the compositional level in cell membranes and organelles, as well as in tissues, whose lipid distribution remains unclear. Here, we report a mass spectrometry study of lipid abundance across 7 rat tissues, detecting and quantifying 652 lipid molecular species from the glycerolipid, glycerophospholipid, fatty acyl, sphingolipid, sterol lipid and prenol lipid categories. Our results demonstrate that every tissue analyzed presents a specific lipid distribution and concentration. Thus, glycerophospholipids are the most abundant tissue lipid, they share a similar tissue distribution but differ in particular lipid species between tissues. Sphingolipids are more concentrated in the renal cortex and sterol lipids can be found mainly in both liver and kidney. Both types of white adipose tissue, visceral and subcutaneous, are rich in glycerolipids but differing the amount. Acylcarnitines are mainly in the skeletal muscle, gluteus and soleus, while heart presents higher levels of ubiquinone than other tissues. The present study demonstrates the existence of a rat tissue-specific fingerprint.

SUBMITTER: Pradas I

PROVIDER: S-EPMC6121266 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lipidomics Reveals a Tissue-Specific Fingerprint.

Pradas Irene I Huynh Kevin K Cabré Rosanna R Ayala Victòria V Meikle Peter J PJ Jové Mariona M Pamplona Reinald R

Frontiers in physiology 20180828

In biological systems lipids generate membranes and have a key role in cell signaling and energy storage. Therefore, there is a wide diversity of molecular lipid expressed at the compositional level in cell membranes and organelles, as well as in tissues, whose lipid distribution remains unclear. Here, we report a mass spectrometry study of lipid abundance across 7 rat tissues, detecting and quantifying 652 lipid molecular species from the glycerolipid, glycerophospholipid, fatty acyl, sphingoli ...[more]

PMID: 30210358

Similar Datasets

Project description:Background and aimsAdipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person's lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, we developed a lipidomic method for analyzing human subcutaneous adipose biopsies. We applied the method to four body areas to understand the differences in lipid composition between these areas.Materials and methodsAdipose tissue biopsies from 10 participants were analyzed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The sample preparation optimization included the optimization of the lipid extraction, the sample amount and the sample dilution factor to detect lipids in an appropriate concentration range. Lipidomic analyses were performed for adipose tissue collected from the abdomen, breast, thigh and lower back. Differences in lipid levels between tissues were visualized with heatmaps.ResultsLipidomic analysis on human adipose biopsies lead to the identification of 186lipids in 2 mg of sample. Technical variation of the lipid-class specific internal standards were below 5%, thus indicating acceptable repeatability. Triacylglycerols were highly represented in the adipose tissue samples, and lipids from 13 lipid classes were identified. Long polyunsaturated triacylglycerols in higher levels in thigh (q<0.05), when compared with the abdomen, breast and lower back, indicating that the lipidome was area-specific.ConclusionThe method presented here is suitable for the analysis of lipid profiles in 2 mg of adipose tissue. The amount of fat across the body is important for health but we argue that also the distribution and the particular profile of the lipidome may be relevant for metabolic outcomes. We suggest that the method presented in this paper could be useful for detecting such aberrations.

Dataset Information

Lipidomics Reveals a Tissue-Specific Fingerprint.

Publications

Lipidomics Reveals a Tissue-Specific Fingerprint.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets