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Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics
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DOI：10.1038/s41467-018-03053-x.png)
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摘要
En 中文
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.
Keyword:
POSTSYNAPTIC DENSITY
HIPPOCAMPAL-NEURONS
CLUSTER-ANALYSIS
SUPERRESOLUTION MICROSCOPY
COLOCALIZATION ANALYSIS
EXCITATORY SYNAPSES
SYNAPTIC VESICLES
LIGHT-MICROSCOPY
PROTEIN
PSD-95
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期刊
IF:
15.7
论文数:
9.4W
被引数:
91.2W
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引用论文
A Bayesian cluster analysis method for single-molecule localization microscopy data.png)
NATURE PROTOCOLS
NATURE PROTOCOLSIF16
PREAI
分享收藏Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)通过随机光学重建显微镜 (STORM) 进行亚衍射极限成像NATURE METHODSOAAI
NATURE METHODSIF32.1
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