Max Delbrück Center
Publishes on RNA Research and Splicing, Receptor Mechanisms and Signaling, RNA and protein synthesis mechanisms. 9 papers and 693 citations.
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The extent of translational control of gene expression in mammalian tissues remains largely unknown. Here we perform genome-wide RNA sequencing and ribosome profiling in heart and liver tissues to investigate strain-specific translational regulation in the spontaneously hypertensive rat (SHR/Ola). For the most part, transcriptional variation is equally apparent at the translational level and there is limited evidence of translational buffering. Remarkably, we observe hundreds of strain-specific differences in translation, almost doubling the number of differentially expressed genes. The integration of genetic, transcriptional and translational data sets reveals distinct signatures in 3'UTR variation, RNA-binding protein motifs and miRNA expression associated with translational regulation of gene expression. We show that a large number of genes associated with heart and liver traits in human genome-wide association studies are primarily translationally regulated. Capturing interindividual differences in the translated genome will lead to new insights into the genes and regulatory pathways underlying disease phenotypes.
Fatty acid esters of hydroxy fatty acids (FAHFAs) are lipid mediators with promising antidiabetic and anti-inflammatory properties that are formed in white adipose tissue (WAT) via de novo lipogenesis, but their biosynthetic enzymes are unknown. Using a combination of lipidomics in WAT, quantitative trait locus mapping, and correlation analyses in rat BXH/HXB recombinant inbred strains, as well as response to oxidative stress in murine models, we elucidated the potential pathway of biosynthesis of several FAHFAs. Comprehensive analysis of WAT samples identified ∼160 regioisomers, documenting the complexity of this lipid class. The linkage analysis highlighted several members of the nuclear factor, erythroid 2 like 2 (Nrf2)-mediated antioxidant defense system (Prdx6, Mgst1, Mgst3), lipid-handling proteins (Cd36, Scd6, Acnat1, Acnat2, Baat), and the family of flavin containing monooxygenases (Fmo) as the positional candidate genes. Transgenic expression of Nrf2 and deletion of Prdx6 genes resulted in reduction of palmitic acid ester of 9-hydroxystearic acid (9-PAHSA) and 11-PAHSA levels, while oxidative stress induced by an inhibitor of glutathione synthesis increased PAHSA levels nonspecifically. Our results indicate that the synthesis of FAHFAs via carbohydrate-responsive element-binding protein–driven de novo lipogenesis depends on the adaptive antioxidant system and suggest that FAHFAs may link activity of this system with insulin sensitivity in peripheral tissues.
G-protein coupled receptors (GPCRs) are key players in signal transduction and therefore a large proportion of pharmaceutical drugs target these receptors. Structural data of GPCRs are sparse yet important for elucidating the molecular basis of GPCR-related diseases and for performing structure-based drug design. To ameliorate this problem, GPCR-SSFE 2.0 (http://www.ssfa-7tmr.de/ssfe2/), an intuitive web server dedicated to providing three-dimensional Class A GPCR homology models has been developed. The updated web server includes 27 inactive template structures and incorporates various new functionalities. Uniquely, it uses a fingerprint correlation scoring strategy for identifying the optimal templates, which we demonstrate captures structural features that sequence similarity alone is unable to do. Template selection is carried out separately for each helix, allowing both single-template models and fragment-based models to be built. Additionally, GPCR-SSFE 2.0 stores a comprehensive set of pre-calculated and downloadable homology models and also incorporates interactive loop modeling using the tool SL2, allowing knowledge-based input by the user to guide the selection process. For visual analysis, the NGL viewer is embedded into the result pages. Finally, blind-testing using two recently published structures shows that GPCR-SSFE 2.0 performs comparably or better than other state-of-the art GPCR modeling web servers.