Latest methods in lipidomics; Extraction: Quo vadis?

I was thrilled to have Gerhard Liebisch from Regensburg and Denise Wolrab with us on sample extraction. Both exciting talks gave our students great detail about what can go wrong in sample extraction during lipidomics experiments.

Gerhard Liebisch, Institute of Clinical Chemistry, Regensburg, Germany

PD Dr. Gerhard Liebisch obtained his Ph.D. at the University of Regensburg. His research interests focus on the development of MS methods for the quantification of lipid species. For more than 20 years, these methods have been applied in large-scale clinical studies and basic research. https://lipidomics-regensburg.de/

 

Denise Wolrab, University of Pardubice, Czech Republic

Dr. Denise Wolrab is an analytical chemist focusing on separation science and the application for the analysis of biomolecules, mainly using supercritical fluid chromatography hyphenated to mass spectrometry. After her Ph.D. at the University of Vienna in 2017, she obtained a postdoc position at the University of Pardubice responsible for the method development and application of lipidomics for cancer screening, mainly using UHPSFC/MS. Since 2020, Denise Wolrab has been PI and Grant Project manager at the University of Pardubice, evaluating the applicability of UHPSFC/MS for the metabolomic analysis of clinical samples.

GOSLIN 2.0

The next version of GOSLIN is there! Goslin is the first grammar-based computational library for the recognition/parsing and normalization of lipid names following the hierarchical lipid shorthand nomenclature. The new version Goslin 2.0 implements the latest nomenclature and adds an additional grammar to recognize systematic IUPAC-IUB fatty acyl names as stored, e.g., in the LIPID MAPS database and is perfectly suited to update lipid names in LIPID MAPS or HMDB databases to the latest nomenclature. Goslin 2.0 is available as a standalone web application with a REST API as well as C++, C#, Java, Python 3, and R libraries. Importantly, it can be easily included in lipidomics tools and scripts providing direct access to translation functions. All implementations are open source. https://pubs.acs.org/doi/10.1021/acs.analchem.1c05430

Computational Lipidomics

Lipidomics encompasses analytical approaches that aim to identify and quantify the complete set of lipids, defined as lipidome in a given cell, tissue, or organism, and their interactions with other molecules. Most lipidomics workflows are based on mass spectrometry and have been proven a powerful tool in system biology in concert with other Omics disciplines. Unfortunately, computational approaches for this relatively young discipline are limited and only accessible to some specialists. Search engines, quantification algorithms, visualization tools, and databases developed by the ‘Lipidomics Informatics for Life-Science’ (LIFS) initiative will provide a structured and standardized format for broad access to these specialized bioinformatics pipelines. Many medical challenges related to lipid metabolic alterations will be highly supported by such capacity-building.  Within LIFS, we already provide access to several tools, workflows, tutorials, and training via a unified web portal (https://lifs-tools.org/).

HFSP Award goes to our lab!

With great pleasure, I announce that we were awarded through the Human Frontier Science Program. We are eager to start the chapter of synaptoneurolipidomics, and we are thrilled to start this great project with labs around the globe:

We Love Lipids

We are delighted to contribute to the “We Love Lipids” Tutorial in 2022, introducing lipidomics and lipid sciences. Please save the dates and meet us again soon!

100 min with ILS

It is with great pleasure to announce the 2022 100 min with ILS podcast again. Stay tuned!  https://lipidomicssociety.org/2021/05/17/100-minutes-with-ils-podcast/