Light-microscopy-based connectomic reconstruction of mammalian brain tissue

• 成果类型: Article
• 署名作者: Tavakoli, Mojtaba R.; Lyudchik, Julia; Januszewski, Michal; Vistunou, Vitali; Duenas, Nathalie Agudelo; Vorlaufer, Jakob; Sommer, Christoph; Kreuzinger, Caroline; Oliveira, Barbara; Cenameri, Alban; Novarino, Gaia; Jain, Viren; Danzl, Johann G.
• 署名单位: Institute of Science & Technology - Austria; Alphabet Inc.; Google Incorporated; Alphabet Inc.; Google Incorporated
• 刊物名称: Nature
• ISSN/ISSBN: 0028-1340
• DOI: 10.1038/s41586-025-08985-1
• 发表日期: 2025-06-12
• 关键词: expansion microscopy; proteins; volume

摘要

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.