美国艾伦脑科学研究所Staci A. Sorensen课题组宣布他们开发出小鼠视觉皮层预测Sst转录组型的连接组学。相关论文于2025年4月9日发表在《自然》杂志上。

该课题组研究人员利用来自Patch-seq的形态学信息来预测大规模EM数据集中转录组定义的细胞亚类和/或met类型的抑制性神经元。该课题组研究人员进一步分析了Martinotti细胞——一种生长抑素（Sst）阳性的形态学细胞类型，成功地将其分类为具有不同轴突髓鞘形成和突触输出连接模式的Sst met类型。研究组证明形态特征可以通过实验方式连接细胞类型，从而进一步比较基因表达和电生理的连接。研究组观察到预测海温细胞类型的独特连接规则。

据悉，神经回路的功能是由构成回路的细胞类型和它们之间的连接决定的。神经细胞类型以前是通过形态学、电生理学、转录组表达、连通性或这些模式的组合来定义的。Patch-seq技术能够表征单个细胞的形态、电生理和转录组特性。这些特性被整合在一起，定义了同主题视觉皮层中28种抑制性、形态-电-转录（MET）细胞类型，其中不包括突触连通性。相反，大规模电子显微镜（EM）能够形态学重建和对神经元局部突触连接的近乎完整的描述，但不包括转录组学或电生理信息。

附：英文原文

Title: Connectomics of predicted Sst transcriptomic types in mouse visual cortex

Author: Gamlin, Clare R., Schneider-Mizell, Casey M., Mallory, Matthew, Elabbady, Leila, Gouwens, Nathan, Williams, Grace, Mukora, Alice, Dalley, Rachel, Bodor, Agnes L., Brittain, Derrick, Buchanan, JoAnn, Bumbarger, Daniel J., Joyce, Emily, Kapner, Daniel, Kinn, Sam, Mahalingam, Gayathri, Seshamani, Sharmishtaa, Takeno, Marc, Torres, Russel, Yin, Wenjing, Nicovich, Philip R., Bae, J. Alexander, Castro, Manuel A., Dorkenwald, Sven, Halageri, Akhilesh, Jia, Zhen, Jordan, Chris, Kemnitz, Nico, Lee, Kisuk, Li, Kai, Lu, Ran, Macrina, Thomas, Mitchell, Eric, Mondal, Shanka Subhra, Mu, Shang, Nehoran, Barak, Popovych, Sergiy, Silversmith, William, Turner, Nicholas L., Wong, William, Wu, Jingpeng, Yu, Szi-chieh, Berg, Jim, Jarsky, Tim, Lee, Brian, Seung, H. Sebastian, Zeng, Hongkui, Reid, R. Clay, Collman, Forrest, da Costa, Nuno Maarico, Sorensen, Staci A.

Issue&Volume: 2025-04-09

Abstract: Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between them1. Neural cell types have previously been defined by morphology2,3, electrophysiology4, transcriptomic expression5,6, connectivity7,8,9 or a combination of such modalities10,11,12. The Patch-seq technique enables the characterization of morphology, electrophysiology and transcriptomic properties from individual cells13,14,15. These properties were integrated to define 28 inhibitory, morpho-electric-transcriptomic (MET) cell types in mouse visual cortex16, which do not include synaptic connectivity. Conversely, large-scale electron microscopy (EM) enables morphological reconstruction and a near-complete description of a neuron’s local synaptic connectivity, but does not include transcriptomic or electrophysiological information. Here, we leveraged morphological information from Patch-seq to predict the transcriptomically defined cell subclass and/or MET-type of inhibitory neurons within a large-scale EM dataset. We further analysed Martinotti cells—a somatostatin (Sst)-positive17 morphological cell type18,19—which were classified successfully into Sst MET-types with distinct axon myelination and synaptic output connectivity patterns. We demonstrate that morphological features can be used to link cell types across experimental modalities, enabling further comparison of connectivity to gene expression and electrophysiology. We observe unique connectivity rules for predicted Sst cell types.

DOI: 10.1038/s41586-025-08805-6

Source: https://www.nature.com/articles/s41586-025-08805-6