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Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids

The plasma membrane (PM) is a complex environment consisting of > 700 species of lipids and many different types of membrane-associating proteins. These lipids and membrane proteins are distributed heterogeneously into nanometer-sized domains, called nanoclusters. The lateral spatial segregation...

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Detalles Bibliográficos
Autores principales: Zhou, Yong, Hancock, John F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276063/
https://www.ncbi.nlm.nih.gov/pubmed/30596140
http://dx.doi.org/10.1007/s41048-018-0060-4
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author Zhou, Yong
Hancock, John F.
author_facet Zhou, Yong
Hancock, John F.
author_sort Zhou, Yong
collection PubMed
description The plasma membrane (PM) is a complex environment consisting of > 700 species of lipids and many different types of membrane-associating proteins. These lipids and membrane proteins are distributed heterogeneously into nanometer-sized domains, called nanoclusters. The lateral spatial segregation in the PM gives rise to different curvature and lipid composition, which determines the efficiency of effector binding and signal transmission. Here, we describe an electron microscopy (EM)-spatial mapping technique to quantify the extent of nanoclusters formation in the PM. The nano-assemblies in the PM are quantified via expressing the GFP-tagged proteins or lipid-binding domains in the cells, which are then immunolabeled with the gold nanoparticles pre-coupled to the anti-GFP antibody. The gold nanoparticles are visualized via the transmission EM at high magnification. The statistical analysis of the Ripley’s K-function calculates the spatial distribution of the gold nanoparticles. Important spatial parameters, such as the extent of nanoclustering, the clustered fraction, the number of proteins per cluster, the optimal size of a nanocluster, and the number of proteins localized to the PM, can be calculated. Further detailed aggregation pattern, such as the populations of monomers, dimers, trimers, and higher ordered oligomers, can also be extracted from the spatial analysis. The EM-bivariate analysis quantifies the extent of co-localization between two different components in the PM and provides key information on the protein–protein and the protein–lipid interactions over a long-distance scale from 8 to 240 nm.
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spelling pubmed-62760632018-12-26 Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids Zhou, Yong Hancock, John F. Biophys Rep Protocol The plasma membrane (PM) is a complex environment consisting of > 700 species of lipids and many different types of membrane-associating proteins. These lipids and membrane proteins are distributed heterogeneously into nanometer-sized domains, called nanoclusters. The lateral spatial segregation in the PM gives rise to different curvature and lipid composition, which determines the efficiency of effector binding and signal transmission. Here, we describe an electron microscopy (EM)-spatial mapping technique to quantify the extent of nanoclusters formation in the PM. The nano-assemblies in the PM are quantified via expressing the GFP-tagged proteins or lipid-binding domains in the cells, which are then immunolabeled with the gold nanoparticles pre-coupled to the anti-GFP antibody. The gold nanoparticles are visualized via the transmission EM at high magnification. The statistical analysis of the Ripley’s K-function calculates the spatial distribution of the gold nanoparticles. Important spatial parameters, such as the extent of nanoclustering, the clustered fraction, the number of proteins per cluster, the optimal size of a nanocluster, and the number of proteins localized to the PM, can be calculated. Further detailed aggregation pattern, such as the populations of monomers, dimers, trimers, and higher ordered oligomers, can also be extracted from the spatial analysis. The EM-bivariate analysis quantifies the extent of co-localization between two different components in the PM and provides key information on the protein–protein and the protein–lipid interactions over a long-distance scale from 8 to 240 nm. Springer Berlin Heidelberg 2018-07-25 2018 /pmc/articles/PMC6276063/ /pubmed/30596140 http://dx.doi.org/10.1007/s41048-018-0060-4 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Protocol
Zhou, Yong
Hancock, John F.
Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids
title Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids
title_full Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids
title_fullStr Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids
title_full_unstemmed Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids
title_short Electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids
title_sort electron microscopy combined with spatial analysis: quantitative mapping of the nano-assemblies of plasma membrane-associating proteins and lipids
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276063/
https://www.ncbi.nlm.nih.gov/pubmed/30596140
http://dx.doi.org/10.1007/s41048-018-0060-4
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