Purity matters: A workflow for the valid high-resolution lipid profiling of mitochondria from cell culture samples

Subcellular lipidomics is a novel field of research that requires the careful combination of several pre-analytical and analytical steps. To define a reliable strategy for mitochondrial lipid profiling, we performed a systematic comparison of different mitochondria isolation procedures by western blot analyses and comprehensive high-resolution lipidomics. Using liver-derived HepG2 cells, we compared three common mitochondria isolation methods, differential centrifugation (DC), ultracentrifugation (UC) and a magnetic bead-assisted method (MACS). In total, 397 lipid species, including 32 cardiolipins, could be quantified in only 100 μg (by protein) of purified mitochondria. Mitochondria isolated by UC showed the highest enrichment in the mitochondria-specific cardiolipins as well as their precursors, phosphatidylglycerols. Mitochondrial fractions obtained by the commonly used DC and the more recent MACS method contained substantial contaminations by other organelles. Employing these isolation methods when performing lipidomics analyses from cell culture mitochondria may lead to inaccurate results. To conclude, we present a protocol how to obtain reliable mitochondria-specific lipid profiles from cell culture samples and show that quality controls are indispensable when performing mitochondria lipidomics

Simultaneous extraction of metabolome and lipidome with methyl tert-butyl ether from a single small tissue sample for ultra-high performance liquid chromatographymass spectrometry

Simultaneous extraction of metabolome and lipidome with methyl tert-butyl ether from a single small tissue sample for ultra-high performance liquid chromatographymass spectrometr

Identification of genetic elements in metabolism by high-throughput mouse phenotyping

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome