Cargando…
Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics
Elucidating protein functions and molecular organisation requires to localise precisely single or aggregated molecules and analyse their spatial distributions. We develop a statistical method SODA (Statistical Object Distance Analysis) that uses either micro- or nanoscopy to significantly improve on...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5814551/ https://www.ncbi.nlm.nih.gov/pubmed/29449608 http://dx.doi.org/10.1038/s41467-018-03053-x |
_version_ | 1783300370566479872 |
---|---|
author | Lagache, Thibault Grassart, Alexandre Dallongeville, Stéphane Faklaris, Orestis Sauvonnet, Nathalie Dufour, Alexandre Danglot, Lydia Olivo-Marin, Jean-Christophe |
author_facet | Lagache, Thibault Grassart, Alexandre Dallongeville, Stéphane Faklaris, Orestis Sauvonnet, Nathalie Dufour, Alexandre Danglot, Lydia Olivo-Marin, Jean-Christophe |
author_sort | Lagache, Thibault |
collection | PubMed |
description | Elucidating protein functions and molecular organisation requires to localise precisely single or aggregated molecules and analyse their spatial distributions. We develop a statistical method SODA (Statistical Object Distance Analysis) that uses either micro- or nanoscopy to significantly improve on standard co-localisation techniques. Our method considers cellular geometry and densities of molecules to provide statistical maps of isolated and associated (coupled) molecules. We use SODA with three-colour structured-illumination microscopy (SIM) images of hippocampal neurons, and statistically characterise spatial organisation of thousands of synapses. We show that presynaptic synapsin is arranged in asymmetric triangle with the 2 postsynaptic markers homer and PSD95, indicating a deeper localisation of homer. We then determine stoichiometry and distance between localisations of two synaptic vesicle proteins with 3D-STORM. These findings give insights into the protein organisation at the synapse, and prove the efficiency of SODA to quantitatively assess the geometry of molecular assemblies. |
format | Online Article Text |
id | pubmed-5814551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-58145512018-02-20 Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics Lagache, Thibault Grassart, Alexandre Dallongeville, Stéphane Faklaris, Orestis Sauvonnet, Nathalie Dufour, Alexandre Danglot, Lydia Olivo-Marin, Jean-Christophe Nat Commun Article Elucidating protein functions and molecular organisation requires to localise precisely single or aggregated molecules and analyse their spatial distributions. We develop a statistical method SODA (Statistical Object Distance Analysis) that uses either micro- or nanoscopy to significantly improve on standard co-localisation techniques. Our method considers cellular geometry and densities of molecules to provide statistical maps of isolated and associated (coupled) molecules. We use SODA with three-colour structured-illumination microscopy (SIM) images of hippocampal neurons, and statistically characterise spatial organisation of thousands of synapses. We show that presynaptic synapsin is arranged in asymmetric triangle with the 2 postsynaptic markers homer and PSD95, indicating a deeper localisation of homer. We then determine stoichiometry and distance between localisations of two synaptic vesicle proteins with 3D-STORM. These findings give insights into the protein organisation at the synapse, and prove the efficiency of SODA to quantitatively assess the geometry of molecular assemblies. Nature Publishing Group UK 2018-02-15 /pmc/articles/PMC5814551/ /pubmed/29449608 http://dx.doi.org/10.1038/s41467-018-03053-x Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lagache, Thibault Grassart, Alexandre Dallongeville, Stéphane Faklaris, Orestis Sauvonnet, Nathalie Dufour, Alexandre Danglot, Lydia Olivo-Marin, Jean-Christophe Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics |
title | Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics |
title_full | Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics |
title_fullStr | Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics |
title_full_unstemmed | Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics |
title_short | Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics |
title_sort | mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5814551/ https://www.ncbi.nlm.nih.gov/pubmed/29449608 http://dx.doi.org/10.1038/s41467-018-03053-x |
work_keys_str_mv | AT lagachethibault mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics AT grassartalexandre mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics AT dallongevillestephane mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics AT faklarisorestis mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics AT sauvonnetnathalie mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics AT dufouralexandre mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics AT danglotlydia mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics AT olivomarinjeanchristophe mappingmolecularassemblieswithfluorescencemicroscopyandobjectbasedspatialstatistics |