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Curvature- and Phase-Induced Protein Sorting Quantified in Transfected Cell-Derived Giant Vesicles
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
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Number of Authors: 112019 (English)In: ACS Nano, ISSN 1936-0851, E-ISSN 1936-086X, Vol. 13, no 6, p. 6689-6701Article in journal (Refereed) Published
Abstract [en]

Eukaryotic cells possess a dynamic network of membranes that vary in lipid composition. To perform numerous biological functions, cells modulate their shape and the lateral organization of proteins associated with membranes. The modulation is generally facilitated by physical cues that recruit proteins to specific regions of the membrane. Analyzing these cues is difficult due to the complexity of the membrane conformations that exist in cells. Here, we examine how different types of membrane proteins respond to changes in curvature and to lipid phases found in the plasma membrane. By using giant plasma membrane vesicles derived from transfected cells, the proteins were positioned in the correct orientation and the analysis was performed in plasma membranes with a biological composition. Nanoscale membrane curvatures were generated by extracting nanotubes from these vesicles with an optical trap. The viral membrane protein neuraminidase was not sensitive to curvature, but it did exhibit strong partitioning (coefficient of K = 0.16) disordered membrane regions. In contrast, the membrane repair protein annexin 5 showed a preference for nanotubes with a density up to 10-15 times higher than that on the more flat vesicle membrane. The investigation of nanoscale effects in isolated plasma membranes provides a quantitative platform for studying peripheral and integral membrane proteins in their natural environment.

Place, publisher, year, edition, pages
2019. Vol. 13, no 6, p. 6689-6701
Keywords [en]
plasma membrane proteins, annexin, neuraminidase, membrane curvature, nanotubes, phase sorting, giant plasma membrane vesicles
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:su:diva-170871DOI: 10.1021/acsnano.9b01052ISI: 000473248300053PubMedID: 31199124OAI: oai:DiVA.org:su-170871DiVA, id: diva2:1338571
Available from: 2019-07-23 Created: 2019-07-23 Last updated: 2019-07-23Bibliographically approved

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Østbye, HenrikNylandsted, JesperDaniels, Robert
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