Automated Analysis of a Diverse Synapse Population

Article (PDF Available)inPLoS Computational Biology 9(3):e1002976 · March 2013with16 Reads
DOI: 10.1371/journal.pcbi.1002976 · Source: PubMed
Abstract
Synapses of the mammalian central nervous system are highly diverse in function and molecular composition. Synapse diversity per se may be critical to brain function, since memory and homeostatic mechanisms are thought to be rooted primarily in activity-dependent plastic changes in specific subsets of individual synapses. Unfortunately, the measurement of synapse diversity has been restricted by the limitations of methods capable of measuring synapse properties at the level of individual synapses. Array tomography is a new high-resolution, high-throughput proteomic imaging method that has the potential to advance the measurement of unit-level synapse diversity across large and diverse synapse populations. Here we present an automated feature extraction and classification algorithm designed to quantify synapses from high-dimensional array tomographic data too voluminous for manual analysis. We demonstrate the use of this method to quantify laminar distributions of synapses in mouse somatosensory cortex and validate the classification process by detecting the presence of known but uncommon proteomic profiles. Such classification and quantification will be highly useful in identifying specific subpopulations of synapses exhibiting plasticity in response to perturbations from the environment or the sensory periphery.
    • "Furthermore, species differences (rat, monkey, cat, and guinea pig) and the use of different labeling techniques and markers for 5-HTergic axons [antibodies directed against 5-HT, the serotonin transporter (SERT), the synthesis enzyme tryptophan hydroxylase 2 (TPH2), or radiolabeling with [3H] 5-HT] have made differences in 5-HT axonal distribution and 5-HTergic triadic connectivity difficult to interpret. Recently, improved automated or semi-automated techniques have been developed for in vitro and in vivo quantification of synapses using fluorescence microscopy (Ippolito and Eroglu 2010; Schätzle et al. 2012; Dumitriu et al. 2012; Busse and Smith 2013; Fogarty et al. 2013; Danielson and Lee 2014; Sanders et al. 2015; Klenowski et al. 2015; Sigal et al. 2015 ). The combination of fluorescence microscopy, immunolabeling of key pre-and postsynaptic markers of excitatory/inhibitory synapses and automated software analysis, has afforded new highthroughput methodology allowing for rapid quantification of putative neurochemical synapses. "
    [Show abstract] [Hide abstract] ABSTRACT: Serotonin neurons arise from the brainstem raphe nuclei and send their projections throughout the brain to release 5-HT which acts as a modulator of several neuronal populations. Previous electron microscopy studies in rats have morphologically determined the distribution of 5-HT release sites (boutons) in certain brain regions and have shown that 5-HT containing boutons form synaptic contacts that are either symmetric or asymmetric. In addition, 5-HT boutons can form synaptic triads with the pre- and postsynaptic specializations of either symmetrical or asymmetrical synapses. However, due to the labor intensive processing of serial sections required by electron microscopy, little is known about the neurochemical properties or the quantitative distribution of 5-HT triads within whole brain or discrete subregions. Therefore, we used a semi-automated approach that combines immunohistochemistry and high-resolution confocal microscopy to label serotonin transporter (SERT) immunoreactive axons and reconstruct in 3D their distribution within limbic brain regions. We also used antibodies against key pre- (synaptophysin) and postsynaptic components of excitatory (PSD95) or inhibitory (gephyrin) synapses to (1) identify putative 5-HTergic boutons within SERT immunoreactive axons and, (2) quantify their close apposition to neurochemical excitatory or inhibitory synapses. We provide a 5-HTergic axon density map and have determined the ratio of synaptic triads consisting of a 5-HT bouton in close proximity to either neurochemical excitatory or inhibitory synapses within different limbic brain areas. The ability to model and map changes in 5-HTergic axonal density and the formation of triadic connectivity within whole brain regions using this rapid and quantitative approach offers new possibilities for studying neuroplastic changes in the 5-HTergic pathway.
    Full-text · Article · Aug 2016
    • "To detect synapse candidates in pixel probability maps produced in the previous step, we threshold the synapse probability map at 0.5, run connected components analysis and discard very small (less than 100 pixels in our test dataset) and very large (more than 1000000 pixels) connected components. For the remaining components we extract the bounding boxes and enlarge them in such a way that the enlarged bounding box can be assumed to contain the full extent of the detected synapse (500 nm according to [36]). In each enlarged box a synapse candidate is then segmented using the standard graph cut algorithm [31]. "
    [Show abstract] [Hide abstract] ABSTRACT: We describe a method for fully automated detection of chemical synapses in serial electron microscopy images with highly anisotropic axial and lateral resolution, such as images taken on transmission electron microscopes. Our pipeline starts from classification of the pixels based on 3D pixel features, which is followed by segmentation with an Ising model MRF and another classification step, based on object-level features. Classifiers are learned on sparse user labels; a fully annotated data subvolume is not required for training. The algorithm was validated on a set of 238 synapses in 20 serial 7197×7351 pixel images (4.5×4.5×45 nm resolution) of mouse visual cortex, manually labeled by three independent human annotators and additionally re-verified by an expert neuroscientist. The error rate of the algorithm (12% false negative, 7% false positive detections) is better than state-of-the-art, even though, unlike the state-of-the-art method, our algorithm does not require a prior segmentation of the image volume into cells. The software is based on the ilastik learning and segmentation toolkit and the vigra image processing library and is freely available on our website, along with the test data and gold standard annotations (http://www.ilastik.org/synapse-detection/sstem).
    Full-text · Article · Feb 2014
  • [Show abstract] [Hide abstract] ABSTRACT: A major question in neuroscience is how diverse subsets of synaptic connections in neural circuits are affected by experience dependent plasticity to form the basis for behavioral learning and memory. Differences in protein expression patterns at individual synapses could constitute a key to understanding both synaptic diversity and the effects of plasticity at different synapse populations. Our approach to this question leverages the immunohistochemical multiplexing capability of array tomography (ATomo) and the columnar organization of mouse barrel cortex to create a dataset comprising high resolution volumetric images of spared and deprived cortical whisker barrels stained for over a dozen synaptic molecules each. These dataset has been made available through the Open Connectome Project for interactive online viewing, and may also be downloaded for offline analysis using web, Matlab, and other interfaces.
    Full-text · Article · Dec 2014
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