Light-microscopy-based connectomic reconstruction of mammalian brain tissue

IF 50.5 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Nature Pub Date : 2025-05-07 DOI:10.1038/s41586-025-08985-1
Mojtaba R. Tavakoli, Julia Lyudchik, Michał Januszewski, Vitali Vistunou, Nathalie Agudelo Dueñas, Jakob Vorlaufer, Christoph Sommer, Caroline Kreuzinger, Bárbara Oliveira, Alban Cenameri, Gaia Novarino, Viren Jain, Johann G. Danzl
{"title":"Light-microscopy-based connectomic reconstruction of mammalian brain tissue","authors":"Mojtaba R. Tavakoli, Julia Lyudchik, Michał Januszewski, Vitali Vistunou, Nathalie Agudelo Dueñas, Jakob Vorlaufer, Christoph Sommer, Caroline Kreuzinger, Bárbara Oliveira, Alban Cenameri, Gaia Novarino, Viren Jain, Johann G. Danzl","doi":"10.1038/s41586-025-08985-1","DOIUrl":null,"url":null,"abstract":"<p>The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution<sup>1,2</sup> with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules, but dense, synapse-level circuit reconstruction by light microscopy has been out of reach, owing to limitations in resolution, contrast and volumetric imaging capability. Here we describe light-microscopy-based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning-based segmentation and analysis of connectivity, thereby directly incorporating molecular information into synapse-level reconstructions of brain tissue. LICONN will allow synapse-level phenotyping of brain tissue in biological experiments in a readily adoptable manner.</p>","PeriodicalId":18787,"journal":{"name":"Nature","volume":"286 1","pages":""},"PeriodicalIF":50.5000,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41586-025-08985-1","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution1,2 with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules, but dense, synapse-level circuit reconstruction by light microscopy has been out of reach, owing to limitations in resolution, contrast and volumetric imaging capability. Here we describe light-microscopy-based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning-based segmentation and analysis of connectivity, thereby directly incorporating molecular information into synapse-level reconstructions of brain tissue. LICONN will allow synapse-level phenotyping of brain tissue in biological experiments in a readily adoptable manner.

Abstract Image

基于光学显微镜的哺乳动物脑组织连接组重建
大脑细胞网络的信息处理能力取决于神经元之间的物理连线模式及其分子和功能特征。通过纳米级分辨率的体积成像和密集的细胞标记,可以绘制神经元和解析它们的单个突触连接。光学显微镜在可视化特定分子方面具有独特的定位,但由于分辨率、对比度和体积成像能力的限制,光学显微镜无法实现密集的突触级电路重建。在这里,我们描述了基于光学显微镜的连接组学(LICONN)。我们将专门设计的水凝胶嵌入和扩展与全面的基于深度学习的连接分割和分析相结合,从而直接将分子信息纳入脑组织的突触级重建中。LICONN将允许在生物学实验中以易于采用的方式对脑组织进行突触水平的表型分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Nature
Nature 综合性期刊-综合性期刊
CiteScore
90.00
自引率
1.20%
发文量
3652
审稿时长
3 months
期刊介绍: Nature is a prestigious international journal that publishes peer-reviewed research in various scientific and technological fields. The selection of articles is based on criteria such as originality, importance, interdisciplinary relevance, timeliness, accessibility, elegance, and surprising conclusions. In addition to showcasing significant scientific advances, Nature delivers rapid, authoritative, insightful news, and interpretation of current and upcoming trends impacting science, scientists, and the broader public. The journal serves a dual purpose: firstly, to promptly share noteworthy scientific advances and foster discussions among scientists, and secondly, to ensure the swift dissemination of scientific results globally, emphasizing their significance for knowledge, culture, and daily life.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信