Dataset Information

Interrogating Synaptic Architecture: Approaches for Labeling Organelles and Cytoskeleton Components.

ABSTRACT: Synaptic transmission has been studied for decades, as a fundamental step in brain function. The structure of the synapse, and its changes during activity, turned out to be key aspects not only in the transfer of information between neurons, but also in cognitive processes such as learning and memory. The overall synaptic morphology has traditionally been studied by electron microscopy, which enables the visualization of synaptic structure in great detail. The changes in the organization of easily identified structures, such as the presynaptic active zone, or the postsynaptic density, are optimally studied via electron microscopy. However, few reliable methods are available for labeling individual organelles or protein complexes in electron microscopy. For such targets one typically relies either on combination of electron and fluorescence microscopy, or on super-resolution fluorescence microscopy. This review focuses on approaches and techniques used to specifically reveal synaptic organelles and protein complexes, such as cytoskeletal assemblies. We place the strongest emphasis on methods detecting the targets of interest by affinity binding, and we discuss the advantages and limitations of each method.

SUBMITTER: Reshetniak S

PROVIDER: S-EPMC6716447 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Interrogating Synaptic Architecture: Approaches for Labeling Organelles and Cytoskeleton Components.

Reshetniak Sofiia S Rizzoli Silvio O SO

Frontiers in Synaptic Neuroscience 20190823

Synaptic transmission has been studied for decades, as a fundamental step in brain function. The structure of the synapse, and its changes during activity, turned out to be key aspects not only in the transfer of information between neurons, but also in cognitive processes such as learning and memory. The overall synaptic morphology has traditionally been studied by electron microscopy, which enables the visualization of synaptic structure in great detail. The changes in the organization of easi ...[more]

PMID: 31507402

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Project description:BackgroundThe identification and characterization of interacting domain pairs is an important step towards understanding protein interactions. In the last few years, several methods to predict domain interactions have been proposed. Understanding the power and the limitations of these methods is key to the development of improved approaches and better understanding of the nature of these interactions.ResultsBuilding on the previously published Parsimonious Explanation method (PE) to predict domain-domain interactions, we introduced a new Generalized Parsimonious Explanation (GPE) method, which (i) adjusts the granularity of the domain definition to the granularity of the input data set and (ii) permits domain interactions to have different costs. This allowed for preferential selection of the so-called "co-occurring domains" as possible mediators of interactions between proteins. The performance of both variants of the parsimony method are competitive to the performance of the top algorithms for this problem even though parsimony methods use less information than some of the other methods. We also examined possible enrichment of co-occurring domains and homo-domains among domain interactions mediating the interaction of proteins in the network. The corresponding study was performed by surveying domain interactions predicted by the GPE method as well as by using a combinatorial counting approach independent of any prediction method. Our findings indicate that, while there is a considerable propensity towards these special domain pairs among predicted domain interactions, this overrepresentation is significantly lower than in the iPfam dataset.ConclusionThe Generalized Parsimonious Explanation approach provides a new means to predict and study domain-domain interactions. We showed that, under the assumption that all protein interactions in the network are mediated by domain interactions, there exists a significant deviation of the properties of domain interactions mediating interactions in the network from that of iPfam data.

Dataset Information

Interrogating Synaptic Architecture: Approaches for Labeling Organelles and Cytoskeleton Components.

Publications

Interrogating Synaptic Architecture: Approaches for Labeling Organelles and Cytoskeleton Components.

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