Project description:Protein O-mannosyltransferases (PMTs) are conserved endoplasmic reticulum membrane embedded enzymes responsible for the transfer of mannose from dolichol phosphate-mannose (Dol-P-Man) to serine/threonine-rich protein substrates or unfolded proteins. PMTs from three subfamilies form obligate dimers with different substrate specificities, and require the concerted action of their transmembrane domains (TMDs) and a luminal MIR domain for catalysis. Here, we present structures, native mass spectrometry and structure-based mutagenesis of the Chaetomium thermophilum and Saccharomyces cerevisiae Pmt4 homodimers. The core fold of the TMDs and MIR domain is conserved with the Pmt1-Pmt2 heterodimer, indicating a shared catalytic mechanism. Distinct to Pmt4, the MIR domain interacts in cis with the TMDs of the same subunit and has a beta-hairpin insertion required for O-mannosylation of substrates. We further identify a cytosolic binding site for substrate Dol33 P-Man within the Pmt4 TMDs, which is conserved amongst PMTs and important for in vivo activity. Thus, we provide a framework to understand the substrate specificity and regulation of the Pmt4 homodimer.
Project description:We investigated a panel of 21 genes by parallel sequencing on the Ion Torrent Personal Genome Machine platform. We sequenced 65 CRCs that were treated with cetuximab or panitumumab ( 37 samples were responsive and 28 were resistant).
Project description:Changes in cellular metabolism contribute to the development and progression of tumors, and can render tumors vulnerable to interventions. However, studies of human cancer metabolism remain limited due to technical challenges of detecting and quantifying small molecules, the highly interconnected nature of metabolic pathways, and the lack of designated tools to analyze and integrate metabolomics with other âomics data. Our study generates the largest comprehensive metabolomics dataset on a single cancer type, and provides a significant advance in integration of metabolomics with sequencing data. Our results highlight the massive re-organization of cellular metabolism as tumors progress and acquire more aggressive features. The results of our work are made available through an interactive public data portal for cancer research community. 10 RNA samples from human ccRCC tumors analyzed from the high glutathione cluster