Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Untargeted lipidomics of hypertrophic cardiomyopathy (part II)

ABSTRACT:

ORGANISM(S): Homo Sapiens

TISSUE(S): Heart

DISEASE(S): Cardiomyopathy

PROVIDER: ST001887 | MetabolomicsWorkbench |

REPOSITORIES: MetabolomicsWorkbench

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	mwtab	Other

Items per page:

1 - 1 of 1

Similar Datasets

Structural characterisation of the fungal Pmt4 homodimer - native MS and lipidomics

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.

2025-11-19 | PXD061837 | Pride

Systematic analysis of protein turnover in primary cells - Part II

Project description:To better understand proteostasis in health and disease, determination of protein half-lives is essential. We improved the precision and accuracy of peptide-ion intensity based quantification in order to enable accurate determination of protein turnover in non-dividing cells using dynamic-SILAC. This enabled precise and accurate protein half-life determination ranging from 10 to more than 1000 hours. We achieve good proteomic coverage ranging from four to six thousand proteins in several types of non-dividing cells, corresponding to a total of 9699 unique proteins over the entire dataset. Good agreement was observed in half-lives between B-cells, natural killer cells and monocytes, while hepatocytes and mouse embryonic neurons showed substantial differences. Our comprehensive dataset enabled extension and statistical validation of the previous observation that subunits of protein complexes tend to have coherent turnover. Furthermore, we observed complex architecture dependent turnover within complexes of the proteasome and the nuclear pore complex. Our method is broadly applicable and might be used to investigate protein turnover in various cell types.

2018-06-08 | PXD008515 | Pride