Guo Yunxia, Ma Junjie, Qi Ruicheng, Ma Rongrong, Ma Xiaoying, Xu Jitao, Ye Kaiqiang, Huang Yan, Yang Xi, Zhang Jianyou, Wang Guangzhong, Zhao Xiangwei
State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing, China.
Department of Anesthesiology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.
Nat Commun. 2025 May 2;16(1):4101. doi: 10.1038/s41467-025-59464-0.
Recent advances have shown that single-nucleus RNA sequencing (snRNA-seq) can be applied to formalin-fixed, paraffin-embedded (FFPE) tissues, opening avenues for transcriptomic analysis of archived specimens. Yet, isolating intact nuclei remains difficult due to RNA cross-linking. Here, we introduce a cryogenic enzymatic dissociation (CED) strategy for rapid, high-yield and fidelity nuclei extraction from FFPE samples and validate its utility with snRandom-seq (snCED-seq) using male C57/BL6 mice. Compared with conventional approaches, CED delivers a tenfold increase in nuclei yield with significantly reduced hands-on time, while minimizing secondary RNA degradation and preserving intranuclear transcripts. snCED-seq enhances gene detection sensitivity, lowers mitochondrial and ribosomal contamination, and increases overall gene expression quantification. In Alzheimer's disease studies, it distinguished two astrocyte subpopulations, microglia, and oligodendrocytes, revealing cellular heterogeneity. Additionally, snCED-seq identify major cell types in a single 50 μm FFPE human lung section. Our results demonstrate that snCED-seq is robust for FFPE specimens and poised to enable multi-omics analyses of clinical samples.
最近的进展表明，单细胞核RNA测序（snRNA-seq）可应用于福尔马林固定、石蜡包埋（FFPE）组织，为存档标本的转录组分析开辟了道路。然而，由于RNA交联，分离完整的细胞核仍然很困难。在这里，我们介绍了一种低温酶解（CED）策略，用于从FFPE样本中快速、高产且保真地提取细胞核，并使用雄性C57/BL6小鼠通过snRandom-seq（snCED-seq）验证其效用。与传统方法相比，CED使细胞核产量提高了十倍，显著减少了操作时间，同时最大限度地减少了二次RNA降解并保留了核内转录本。snCED-seq提高了基因检测灵敏度，降低了线粒体和核糖体污染，并增加了整体基因表达定量。在阿尔茨海默病研究中，它区分了两种星形胶质细胞亚群、小胶质细胞和少突胶质细胞，揭示了细胞异质性。此外，snCED-seq在单个50μm FFPE人肺切片中识别出主要细胞类型。我们的结果表明，snCED-seq对FFPE标本具有强大的适用性，并有望实现临床样本的多组学分析。
