奥地利科学技术研究所Johann G. Danzl团队近期取得重要工作进展。他们研究提出了活体脑组织的致密4D纳米级重建方案。相关研究成果2023年7月10日在线发表于《自然—方法学》杂志上。
据介绍，将活体脑组织三维重建到单个突触水平，将为解码大脑复杂而密集的信息处理网络的动力学和结构功能关系创造机会。然而，这一过程受到了光学成像中3D分辨率不足、信噪比不足和光负担过高的阻碍，而电子显微镜本质上是静态的。
研究人员通过开发集成的光学/机器学习技术LIONESS（实时信息优化纳米拷贝，实现饱和分割）解决了这些挑战。这一技术利用了对全面、细胞外标记组织中的受激发射耗尽显微镜的光学修改，以及通过机器学习获得的样本结构的先前信息，同时实现各向同性超分辨率、高信噪比和与活体组织的兼容性。这允许在突触水平上进行密集的基于深度学习的实例分割和3D重建，结合分子、活动和形态动力学信息。
总之，LIONESS技术为研究活体脑组织的动态功能（纳米）结构开辟了途径。
附：英文原文
Title: Dense 4D nanoscale reconstruction of living brain tissue
Author: Velicky, Philipp, Miguel, Eder, Michalska, Julia M., Lyudchik, Julia, Wei, Donglai, Lin, Zudi, Watson, Jake F., Troidl, Jakob, Beyer, Johanna, Ben-Simon, Yoav, Sommer, Christoph, Jahr, Wiebke, Cenameri, Alban, Broichhagen, Johannes, Grant, Seth G. N., Jonas, Peter, Novarino, Gaia, Pfister, Hanspeter, Bickel, Bernd, Danzl, Johann G.
Issue&Volume: 2023-07-10
Abstract: Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure–function relationships of the brain’s complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.
DOI: 10.1038/s41592-023-01936-6
Source: https://www.nature.com/articles/s41592-023-01936-6
Nature Methods：《自然—方法学》，创刊于2004年。隶属于施普林格·自然出版集团，最新IF：47.99
官方网址：https://www.nature.com/nmeth/
投稿链接：https://mts-nmeth.nature.com/cgi-bin/main.plex
本期文章：《自然—方法学》：Online/在线发表
