ArticleMolecular & cellular proteomics : MCP2013
Unraveling sterol-dependent membrane phenotypes by analysis of protein abundance-ratio distributions in different membrane fractions under biochemical and endogenous sterol depletion.
Article in Molecular & cellular proteomics : MCP, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- Cytoskeletal Components Define Protein Location to Membrane Microdomains.Molecular & cellular proteomics : MCP · 2015Article
- Plasma membrane lipid-protein interactions affect signaling processes in sterol-biosynthesis mutants in Arabidopsis thaliana.Frontiers in plant science · 2014Article
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Authors and funding
3 authors at 1 institution in 1 country.
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Abstract
During the last decade, research on plasma membrane focused increasingly on the analysis of so-called microdomains. It has been shown that function of many membrane-associated proteins involved in signaling and transport depends on their conditional segregation within sterol-enriched membrane domains. High throughput proteomic analysis of sterol-protein interactions are often based on analyzing detergent resistant membrane fraction enriched in sterols and associated proteins, which also contain proteins from these microdomain structures. Most studies so far focused exclusively on the characterization of detergent resistant membrane protein composition and abundances. This approach has received some criticism because of its unspecificity and many co-purifying proteins. In this study, by a label-free quantitation approach, we extended the characterization of membrane microdomains by particularly studying distributions of each protein between detergent resistant membrane and detergent-soluble fractions (DSF). This approach allows a more stringent definition of dynamic processes between different membrane phases and provides a means of identification of co-purifying proteins. We developed a random sampling algorithm, called Unicorn, allowing for robust statistical testing of alterations in the protein distribution ratios of the two different fractions. Unicorn was validated on proteomic data from methyl-β-cyclodextrin treated plasma membranes and the sterol biosynthesis mutant smt1. Both, chemical treatment and sterol-biosynthesis mutation affected similar protein classes in their membrane phase distribution and particularly proteins with signaling and transport functions.
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