Plasticity of dendritic spines: Molecular function and dysfunction in neurodevelopmental disorders

Nishiyama, Jun

doi:10.1111/pcn.12899

Cited by 69 publications

(58 citation statements)

References 168 publications

(409 reference statements)

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“…Dendritic spine-based synapses account for the bulk of excitatory neurotransmission in the cerebral cortex and have been implicated in neurodevelopmental and neuropsychiatric disorders (Forrest et al, 2018;Kwon et al, 2019;Lima-Caldeira et al, 2019;Nishiyama, 2019). Although the mechanisms underlying plasticity of existing dendritic spines have been well characterized (Araya et al, 2014;Holtmaat et al, 2005;Sala & Segal, 2014;Schätzle et al, 2018), the processes involved in their formation are less well understood (Sando et al, 2017;Sigler et al, 2017; reviewed in Südhof, 2018 94.5 ± 1.2%; WT-Panx1EGFP: 91.1% ± 1.9%, p = 0.2034, c1 ; Panx1-EGFP: 97.7% ± 0.5%; Panx1 KO-Panx1EGFP: 87.3% ± 1.9%, p = 0.00028, Kruskal-Wallis test, c1 ).…”

Section: Discussionmentioning

confidence: 99%

Pannexin 1 regulates spiny protrusion dynamics in cortical neurons

Sanchez-Arias

Candlish

Swayne

2020

Preprint

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The integration of neurons into networks relies on the formation of dendritic spines. These specialized structures arise from dynamic filopodia-like spiny protrusions. Recently, it was discovered that cortical neurons lacking the channel protein Pannexin 1 (Panx1) exhibited larger and more complicated neuronal networks, as well as, higher dendritic spine densities. Here, we expanded on those findings to investigate whether the increase in dendritic spine density associated with lack of Panx1 was due to differences in the rates of spine dynamics. Using a fluorescent membrane tag (mCherry-CD9-10) to visualize spiny protrusions in developing neurons (at 10 days-in-vitro, DIV10) we confirmed that lack of Panx1 leads to higher spiny protrusion density while transient transfection of Panx1 leads to decreased spiny protrusion density. To quantify the impact of Panx1 expression on spiny protrusion formation, elimination, and motility, we used live cell imaging in DIV10 neurons (1 frame every 5 seconds for 10 minutes). We discovered, that at DIV10, lack of Panx1 KO stabilized spiny protrusions. Notably, re-expression of Panx1 in Panx1 knockout neurons resulted in a significant increase in spiny protrusion motility and turnover. In summary, these new data revealed that Panx1 regulates the development of dendritic spines by controlling protrusion dynamics.Significance statementCells in the brain form intricate and specialized networks - neuronal networks - in charge of processing sensations, executing movement commands, and storing memories. To do this, brain cells extend microscopic protrusions - spiny protrusions - which are highly dynamic and survey the local environment to contact other cells. Those contact sites are known as synapses and undergo further stabilization and maturation establishing the function and efficiency of neuronal networks. Our work shows that removal of Panx1 increases the stability and decreases the turnover of spiny protrusion on young neurons.

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Section: Discussionmentioning

confidence: 99%

Pannexin 1 regulates spiny protrusion dynamics in cortical neurons

Sanchez-Arias

Candlish

Swayne

2020

Preprint

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“…Neuronal migration and morphogenesis defects in ASD contribute to an altered cortical connectivity in different brain regions [45] [46], as the well-known prefrontal area [47]. Therefore, in the developing brain, a premature alteration in neuronal plasticity, affecting mostly cortical regions involved in cognitive and behavioral functions, might trigger the autistic phenotype [48] [49].…”

Section: Discussionmentioning

confidence: 99%

A novel data-driven approach reveals gene networks and biological processes underlying autism

Gialloreti¹,

Enea²,

Micco³

et al. 2020

Preprint

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Background: Developments in gene-hunting techniques identified several ASD associated genes. The considerable significance of cluster analysis associated with gene network studies has led to reveal many disrupted key pathways in ASD, even if its genetic underpinnings remain a challenging task. This study aims to determine, through a novel data-driven approach, how networks of mutated genes impact biological processes underlying autism. Methods: We analyzed the VariCarta dataset, which presents more than 200,000 genomic variant events collected from 13,069 people with ASD. Firstly, we created a whole-genome and an exome sequencing subset. Then, for each subset we compared pairwise patients of each group to build “patient similarity matrices”. Hierarchical-agglomerative-clustering and heatmap were performed to identify clusters of patients with common occurrences of gene networks within these matrices. The subsequent enrichment analysis (EA) highlighted biological processes that might be impacted by the mutated genes of each subgroup. Results: Considering the whole-genome matrix, we identified three main genetic clusters of ASD patients, each one characterized by a network of shared genetic variants. We isolated 11,609 genetic variants shared by at least two subjects in each cluster; 4,187 of these variants (36.1%) were common to the three clusters. Only 331 patients (2.5%) shared none or very few mutated genes with anyone else. The EA highlighted common or cluster-specific biological processes related to the variants. Most of the common abnormal processes were involved in neuron projections guidance and morphogenesis, cell junctions and synapse assembly. Exome sequencing alone was not effectual in identifying ASD subgroups. Limitations: Caution is warranted when interpreting our results, as we did not compare them with a control group and did not verify if the identified subgroups where actually associated with different phenotypes. Future work will have to ascertain the strength and reproducibility of these results. Conclusions: Itemizing not just single mutated genes, but also gene networks and specific biological processes that characterize different ASD subpopulations might allow to better understand which networks of genetic variants play a major role in the etiopathology of ASD. The proposed methodology may represent a novel approach to help disentangle ASD complexity and an instrument to boost more focused genotype-phenotype studies.

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“…For example, activity-regulated cytoskeleton-associated protein (ARC), a synaptic protein critical for the internalization of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor trafficking at synapses, is one mRNA target of FMRP at the synapses (Waung et al, 2008 ; Ebert and Greenberg, 2013 ). For more information regarding the molecular mechanisms of synaptic dysfunction in Fmr1 knockout mice, please refer to Nishiyama ( 2019 ).…”

Section: Dysregulation Of Spine Dynamics In Neuropathologiesmentioning

confidence: 99%

“…Second, CamKII activates mechanisms numerous small GTPases including Cdc42, Rac1, RhoA, and H-Ras to reorganize actin networks in the spine. This was demonstrated thanks to the introduction of FRET and two-photon fluorescence lifetime imaging microscopy (2pFLIM), which made it possible to study dynamic signaling responses in stimulated spines at least in acute slice paradigms (Nishiyama and Yasuda, 2015 ; Nishiyama, 2019 ). CaMKIIα activity in individual stimulated spines has been imaged using 2pFLIM of a FRET-based biosensor (Okamoto et al, 2004 ; Lee et al, 2009 ).…”

Section: Molecular Mechanisms Of Dendritic Spine Plasticitymentioning

confidence: 99%

Dendritic Spine Plasticity: Function and Mechanisms

Runge

Cardoso

Chevigny

2020

Front. Synaptic Neurosci.

141

125

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Dendritic spines are small protrusions studding neuronal dendrites, first described in 1888 by Ramón y Cajal using his famous Golgi stainings. Around 50 years later the advance of electron microscopy (EM) confirmed Cajal’s intuition that spines constitute the postsynaptic site of most excitatory synapses in the mammalian brain. The finding that spine density decreases between young and adult ages in fixed tissues suggested that spines are dynamic. It is only a decade ago that two-photon microscopy (TPM) has unambiguously proven the dynamic nature of spines, through the repeated imaging of single spines in live animals. Spine dynamics comprise formation, disappearance, and stabilization of spines and are modulated by neuronal activity and developmental age. Here, we review several emerging concepts in the field that start to answer the following key questions: What are the external signals triggering spine dynamics and the molecular mechanisms involved? What is, in return, the role of spine dynamics in circuit-rewiring, learning, and neuropsychiatric disorders?

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Plasticity of dendritic spines: Molecular function and dysfunction in neurodevelopmental disorders

Cited by 69 publications

References 168 publications

Pannexin 1 regulates spiny protrusion dynamics in cortical neurons

Pannexin 1 regulates spiny protrusion dynamics in cortical neurons

A novel data-driven approach reveals gene networks and biological processes underlying autism

Dendritic Spine Plasticity: Function and Mechanisms

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