data archive for: Thiele, Wunderling, Leyendecker (2019) Multiplexed and single cell tracing of lipid metabolism, Nature Methods, https://doi.org/10.1038/s41592-019-0593-6

DOI

Abstact of the publication: Cellular lipid metabolism is a complex network process comprising dozens of enzymes, multiple organelles and more than a thousand lipid species. Tracing metabolic reactions in this network is a major technological and scientific challenge. Using a novel click-chemistry mass spectrometry reporter strategy, we have developed a specific, highly sensitive and robust tracing procedure for alkyne-labeled lipids. The method enables sample multiplexing, saving time and costs and improving sample comparison. We demonstrate this by a time-resolved analysis of hepatocyte glycerolipid metabolism with parallel quantitiative monitoring of 120 labeled lipid species. The sub-femtomole sensitivity enabled the first single cell analysis of fatty acid incorporation into neutral and membrane lipids. The results demonstrate the robustness of lipid homeostasis at the single cell level. Content: This archive contains the primary Mass Spectrometry .raw files of all relevant data shown in the paper. Further, it contains the masterscan .sc files of the LipidXplorer software that result from the import of the .raw files into the software. Thes .sc files can be searched using LipidXplorer, using the .mfql files that are also part of this archive. Data are organized in folders according to the Figures and Supplementary Items of the original publication. Each folder contains a separate readme file that explaines the type of files, their origin and possible use.

Identifier
DOI http://dx.doi.org/doi:10.22000/251
Metadata Access https://www.radar-service.eu/oai/provider?verb=GetRecord&metadataPrefix=oai_dc&identifier=44fdc9ec-b5bb-5dd4-9b40-6976b0023298
Provenance
Creator Thiele, Christoph
Publisher Thiele, Christoph
Publication Year 2019
Rights CC BY-NC-SA 4.0 Attribution-NonCommercial-ShareAlike;Christoph Thiele
Contact Thiele, Christoph
Representation
Resource Type Dataset
Format application/zip
Coverage
Discipline Biochemistry