Nanoscale 3D EM Reconstructions Reveal Intrinsic Mechanisms of Structural Diversity of Chemical Synapses

Yingguo, Zhu; Uytiepo, Marco; Bushong, Eric A.; Haberl, Matthias G.; Beutter, Elizabeth; Scheiwe, Frederieke; Zhang, Weiheng; Chang, Lyanne; Luu, Danielle; Chui, Brandon; Ellisman, Mark H.; Maximov, Anton

doi:10.2139/ssrn.3727618

Cited by 3 publications

(3 citation statements)

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“…The appearance of SP clusters likely reflects the elaboration and the stabilization of the spine apparatus (Perez‐Alvarez et al , 2020), that is, together with the presence of polyribosomes, predictive of activity‐dependent spine enlargement (Chirillo et al , 2019). In agreement with our results, a recent electron microscopy study performed in the intact hippocampus revealed that mushroom spines but not smaller protrusions (e.g., thin, stubby, or filopodial) exhibit higher volume and PSD size when contacted by TetTx + presynaptic terminals and more likely contained a spine apparatus (Zhu et al , 2021). The input‐specificity of SP recruitment upon activity perturbation is also supported by previous reports showing that high‐frequency stimulation in the dentate gyrus enhances SP immunoreactivity selectively in the corresponding stimulated layers (Yamazaki et al , 2008; de Solis et al , 2017).…”

Section: Discussionsupporting

confidence: 93%

miR‐124‐dependent tagging of synapses by synaptopodin enables input‐specific homeostatic plasticity

et al. 2022

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Homeostatic synaptic plasticity is a process by which neurons adjust their synaptic strength to compensate for perturbations in neuronal activity. Whether the highly diverse synapses on a neuron respond uniformly to the same perturbation remains unclear. Moreover, the molecular determinants that underlie synapse‐specific homeostatic synaptic plasticity are unknown. Here, we report a synaptic tagging mechanism in which the ability of individual synapses to increase their strength in response to activity deprivation depends on the local expression of the spine‐apparatus protein synaptopodin under the regulation of miR‐124. Using genetic manipulations to alter synaptopodin expression or regulation by miR‐124, we show that synaptopodin behaves as a “postsynaptic tag” whose translation is derepressed in a subpopulation of synapses and allows for nonuniform homeostatic strengthening and synaptic AMPA receptor stabilization. By genetically silencing individual connections in pairs of neurons, we demonstrate that this process operates in an input‐specific manner. Overall, our study shifts the current view that homeostatic synaptic plasticity affects all synapses uniformly to a more complex paradigm where the ability of individual synapses to undergo homeostatic changes depends on their own functional and biochemical state.

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Section: Discussionsupporting

confidence: 93%

miR‐124‐dependent tagging of synapses by synaptopodin enables input‐specific homeostatic plasticity

et al. 2022

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“…In agreement with our results, a recent electron microscopy study performed in the intact hippocampus revealed that mushroom spines but not smaller protrusions (e.g. thin, stubby or filopodial) exhibit higher volume and PSD size when contacted by TetTx+ presynaptic terminals and more likely contained a spine apparatus (Zhu et al, 2021). The input-specificity of SP recruitment upon activity perturbation is also supported by previous reports showing that high-frequency stimulation in the dentate gyrus enhances SP immunoreactivity selectively in the corresponding stimulated layers (de Solis et al, 2017;Yamazaki et al, 2008).…”

Section: Sp As a Molecular Tag To Promote Input-specific Synaptic Plasticitysupporting

confidence: 93%

mir124-dependent tagging of glutamatergic synapses by synaptopodin controls non-uniform and input-specific homeostatic synaptic plasticity

Dubes

Soula

Benquet

et al. 2021

Preprint

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Homeostatic synaptic plasticity (HSP) is a process by which neurons adjust synaptic strengths to compensate for various perturbations and which allows to stabilize neuronal activity. Yet, whether the highly diverse synapses harboring a neuron respond uniformly to a same perturbation is unclear and the underlying molecular determinants remain to be identified. Here, using patch-clamp recordings, immunolabeling and imaging approaches, we report that the ability of individual synapses to undergo HSP in response to activity-deprivation paradigms depends on the local expression of the spine apparatus related protein synaptopodin (SP) acting as a synaptic tag to promote AMPA receptor synaptic accumulation and spine growth. Gain and loss-of-function experiments indicate that this process relies on the local de-repression of SP translation by miR124 which supports both non-uniform and synapse-autonomous HSP induced by global or input-specific activity deprivation, respectively. Our findings uncover an unexpected synaptic-tagging mechanism for HSP, whose molecular actors are intriguingly shared with Hebbian plasticity and linked to multiple neurological diseases.

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“…1A) 2,3 . The combined presence of these features allows for highly contextualized analysis of cellular-level neuronal connectivity, and for various organisms, this approach has led to new insights into topics like cell-type-specific nervous system connectivity ; development-or learning-mediated changes in neural circuitry [31][32][33][34] ; and the fine structure of neuronal and non-neuronal cells [35][36][37][38][39][40] .…”

Section: Introductionmentioning

confidence: 99%

Uncovering features of synapses in primary visual cortex through contrastive representation learning

Wilson

Babadi

2022

Preprint

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3D EM connectomics image volumes are now surpassing sizes of 1 mm3, and are therefore beginning to contain multiple meaningful spatial scales of brain circuitry simultaneously. However, the sheer density of information in such datasets makes the development of unbiased, scalable machine learning techniques a necessity for extracting novel insights without extremely time-consuming, intensive labor. In this paper, we present SynapseCLR, a self-supervised contrastive representation learning method for 3D electron microscopy (EM) data, and use the method to extract feature representations of synapses from a 3D EM dataset from mouse visual cortex. We show that our representations separate synapses according to both their overall physical appearance and structural annotations of known functional importance. We further demonstrate the utility of our methodology for several valuable downstream tasks for the growing field of 3D EM connectomics. These include one-shot identification of defective synapse segmentations, dataset-wide similarity-based querying, and accurate imputation of annotations for unlabeled synapses, using only manual annotation of 0.2% of synapses in the dataset. In particular, we show that excitatory vs. inhibitory neuronal cell types can be assigned to individual synapses and highly truncated neurites with accuracy exceeding 99.8%, making this population accessible to connectomics analysis. Finally, we present a data-driven and unsupervised study of the manifold of synaptic structural variation, revealing its intrinsic axes of variation and showing that synapse structure is also strongly correlated with inhibitory neuronal subtypes.

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Nanoscale 3D EM Reconstructions Reveal Intrinsic Mechanisms of Structural Diversity of Chemical Synapses

Cited by 3 publications

References 0 publications

miR‐124‐dependent tagging of synapses by synaptopodin enables input‐specific homeostatic plasticity

miR‐124‐dependent tagging of synapses by synaptopodin enables input‐specific homeostatic plasticity

mir124-dependent tagging of glutamatergic synapses by synaptopodin controls non-uniform and input-specific homeostatic synaptic plasticity

Uncovering features of synapses in primary visual cortex through contrastive representation learning

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