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  Synaptic and peptidergic connectome of a neurosecretory center in the annelid brain

Williams, E., Verasztó, C., Jasek, S., Conzelmann, M., Shahidi, R., Bauknecht, P., et al. (2017). Synaptic and peptidergic connectome of a neurosecretory center in the annelid brain. eLife, 6: e26349. doi:10.7554/eLife.26349.

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 Creators:
Williams, EA1, Author           
Verasztó, C1, Author           
Jasek, S1, Author           
Conzelmann, M1, Author           
Shahidi, R1, Author           
Bauknecht, P1, Author           
Mirabeau, O, Author
Jékely, G1, Author           
Affiliations:
1Research Group Neurobiology of Marine Zooplankton, Max Planck Institute for Developmental Biology, Max Planck Society, ou_3379109              

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 Abstract: Neurosecretory centers in animal brains use peptidergic signaling to influence physiology and behavior. Understanding neurosecretory center function requires mapping cell types, synapses, and peptidergic networks. Here we use transmission electron microscopy and gene expression mapping to analyze the synaptic and peptidergic connectome of an entire neurosecretory center. We reconstructed 78 neurosecretory neurons and mapped their synaptic connectivity in the brain of larval Platynereis dumerilii, a marine annelid. These neurons form an anterior neurosecretory center expressing many neuropeptides, including hypothalamic peptide orthologs and their receptors. Analysis of peptide-receptor pairs in spatially mapped single-cell transcriptome data revealed sparsely connected networks linking specific neuronal subsets. We experimentally analyzed one peptide-receptor pair and found that a neuropeptide can couple neurosecretory and synaptic brain signaling. Our study uncovered extensive networks of peptidergic signaling within a neurosecretory center and its connection to the synaptic brain.

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Language(s): eng - English
 Dates: 2017-12
 Publication Status: Published online
 Pages: 22
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.7554/eLife.26349
PMID: 29199953
 Degree: -

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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: 22 Volume / Issue: 6 Sequence Number: e26349 Start / End Page: - Identifier: ISSN: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X