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超越核边界:利用细胞特征对原位测序的人类脑组织进行单细胞分析。

Beyond the nuclear border: single-cell analysis of in situ sequenced human brain tissue using cellular features.

作者信息

Kotah Janssen M, Rust Thomas, van Weering Hilmar R J, Bosma Janneke, Woudstra Amber L, Kooistra Susanne M, Eggen Bart J L

机构信息

Department of Biomedical Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

MS Centrum Noord Nederland, Groningen, The Netherlands.

出版信息

Commun Biol. 2025 Jul 22;8(1):1089. doi: 10.1038/s42003-025-08518-6.

Abstract

Spatial transcriptomics has advanced our understanding of cellular heterogeneity at single-cell resolution. Here, we assess the suitability of in situ sequencing (ISS) for analyzing formalin-fixed, paraffin-embedded (FFPE) postmortem human brain tissue. A key challenge in ISS data analysis is optimizing transcript allocation while minimizing misallocation, particularly in the morphologically complex central nervous system (CNS). We compared geospatial methods using nuclear and expanded nuclear boundaries for segmentation and transcript allocation. While overall cell-type proportions remained comparable, transcript allocation methods affected specific cell types, including microglia, neurons, and neurovascular cells. To enhance specificity, we integrated fluorescent imaging data targeting 18S RNA and IBA1 protein to direct transcript allocation toward RNA-rich cells (e.g., neurons) and microglia, respectively. We demonstrate how this approach, paired with secondary allocation of transcripts outside imaging masks, improved both the number of microglia detected and the specificity of microglial transcripts assigned. Our method offers a flexible and efficient strategy for targeted transcript allocation based on cellular morphology, optimizing CNS cell segmentation in FFPE-preserved human brain tissue.

摘要

空间转录组学提升了我们在单细胞分辨率下对细胞异质性的理解。在此,我们评估原位测序(ISS)用于分析福尔马林固定、石蜡包埋(FFPE)的人类死后脑组织的适用性。ISS数据分析中的一个关键挑战是优化转录本分配,同时尽量减少错误分配,尤其是在形态复杂的中枢神经系统(CNS)中。我们比较了使用核边界和扩展核边界进行分割和转录本分配的地理空间方法。虽然总体细胞类型比例保持可比,但转录本分配方法影响了特定细胞类型,包括小胶质细胞、神经元和神经血管细胞。为了提高特异性,我们整合了靶向18S RNA和IBA1蛋白的荧光成像数据,分别将转录本分配导向富含RNA的细胞(如神经元)和小胶质细胞。我们展示了这种方法与成像掩膜外转录本的二次分配相结合,如何提高了检测到的小胶质细胞数量以及分配的小胶质细胞转录本的特异性。我们的方法提供了一种基于细胞形态的靶向转录本分配的灵活高效策略,优化了FFPE保存的人类脑组织中的CNS细胞分割。

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