基于光学显微镜的哺乳动物脑组织连接组重建，这一成果由奥地利科学技术研究所Johann G. Danzl研究小组经过不懈努力而取得。该项研究成果发表在2025年5月7日出版的《自然》上。

在这里，该研究组描述了基于光学显微镜的连接组学（LICONN）。该课题组人员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。

研究人员表示，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。

附：英文原文

Title: Light-microscopy-based connectomic reconstruction of mammalian brain tissue

Author: Tavakoli, Mojtaba R., Lyudchik, Julia, Januszewski, Micha, Vistunou, Vitali, Agudelo Dueas, Nathalie, Vorlaufer, Jakob, Sommer, Christoph, Kreuzinger, Caroline, Oliveira, Brbara, Cenameri, Alban, Novarino, Gaia, Jain, Viren, Danzl, Johann G.

Issue&Volume: 2025-05-07

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.

DOI: 10.1038/s41586-025-08985-1

Source: https://www.nature.com/articles/s41586-025-08985-1