Vondrackova, M. | bioRxiv Science

bioRxiv2023

Tissue-specific sex difference in the metabolism of fatty acid esters of hydroxy fatty acids

Fatty acid esters of hydroxy fatty acids (FAHFAs) are endogenous bioactive lipids known for their anti-inflammatory and anti-diabetic properties. Despite their therapeutic potential, little is known about the sex-specific variations in FAHFA metabolism. This study investigated the role of Androgen Dependent TFPI Regulating Protein (ADTRP), a FAHFA hydrolase. Additionally, tissue-specific differences in FAHFA levels, focusing on the perigonadal white adipose tissue (pgWAT), subcutaneous white adipose tissue (scWAT), brown adipose tissue (BAT), plasma, and liver, were evaluated using metabolomics and lipidomics. We found that female mice exhibited higher FAHFA levels in pgWAT, scWAT, and BAT compared to males. FAHFA levels were inversely related to Adtrp mRNA, which showed significantly lower expression in females compared with males in pgWAT and scWAT. However, no significant differences between the sexes were observed in plasma and liver FAHFA levels. Adtrp deletion had minimal impact on both sexes metabolome and lipidome of pgWAT. However, we discovered higher endogenous levels of triacylglycerol estolides containing FAHFAs, a FAHFA metabolic reservoir, in the pgWAT of female mice. These findings suggest that sex-dependent differences in FAHFA levels occur primarily in specific WAT depots and may modulate local insulin sensitivity in adipocytes. However, further investigations are warranted to fully comprehend the underlying mechanisms and implications of sex effects on FAHFA metabolism in humans.

biochemistry↗

bioRxiv2023

LORA, Lipid Over-Representation Analysis based on structural information

With the increasing number of lipidomic studies, there is a need for efficient and automated analysis of lipidomic data. One of the challenges faced by most existing approaches to lipidomic data analysis is lipid nomenclature. The systematic nomenclature of lipids contains all available information about the molecule, including its hierarchical representation, which can be used for statistical evaluation. The Lipid Over-Representation Analysis (LORA) web application (https://lora.metabolomics.fgu.cas.cz) analyzes this information using the Java-based Goslin framework, which translates lipid names into a standardized nomenclature. Goslin provides the level of lipid hierarchy, including information on headgroups, acyl chains, and their modifications, up to the complete structure level. LORA allows the user to upload the experimental query and universe datasets, select a grammar for lipid name normalization, and then process the data. The user can then interactively explore the results and perform lipid overrepresentation analysis based on selected criteria. The results are graphically visualized according to the lipidome hierarchy. The lipids present in the most over-represented terms (lipids with the highest number of enriched shared structural features) are defined as Very Important Lipids (VILs). For example, the main result of a demo dataset is the information that the query is significantly enriched with glycerophospholipids containing acyl 20:4 at sn-2 position. These terms define a set of VILs (e.g., PC 18:2/20:4;O and PE 16:0/20:4(5,8,10,14);OH). All results, graphs, and visualizations are summarized in a report. LORA is a tool focused on the smart mining of epilipidomics datasets to facilitate their interpretation at the molecular level.

bioinformatics↗