将基于代谢 RNA 标记的时间分辨单细胞 RNA 测序与空间转录组学结合起来进行时空转录组学分析

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL Small Methods Pub Date : 2024-10-10 DOI:10.1002/smtd.202401297
Xiaoyong Chen, Shichao Lin, Honghai You, Jinyuan Chen, Qiaoyi Wu, Kun Yin, Fanghe Lin, Yingkun Zhang, Jia Song, Chenyu Ding, Dezhi Kang, Chaoyong Yang
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引用次数: 0

摘要

基于代谢 RNA 标记的时间分辨单细胞 RNA 测序(scRNA-seq)为剖析基因表达的时间动态和复杂的基因调控网络提供了前所未有的工具。然而,这种技术无法揭示组织中细胞的空间组织,而细胞间的交流也会调控基因的表达。本文证明,将时间分辨 scRNA-seq 与空间转录组学相结合是一种新的时空分析范式。基于代谢RNA标记的时间分辨Well-TEMP-seq首先被用于分析胶质母细胞瘤(GBM)细胞的转录动态,并发现了EZH2介导的GBM间质转化的两条潜在途径。通过空间转录组学,进一步揭示了肿瘤微环境中 CCL2+ 恶性细胞和 IL10+ 肿瘤相关巨噬细胞之间通过 EZH2-FOSL2-CCL2 轴的串联作用促成了 GBM 的间质转化。这些发现显示了综合时空 scRNA-seq 在阐明复杂的基因调控机制和促进对疾病细胞过程的理解方面的强大作用。
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Integrating Metabolic RNA Labeling-Based Time-Resolved Single-Cell RNA Sequencing with Spatial Transcriptomics for Spatiotemporal Transcriptomic Analysis.

Metabolic RNA labeling-based time-resolved single-cell RNA sequencing (scRNA-seq) has provided unprecedented tools to dissect the temporal dynamics and the complex gene regulatory networks of gene expression. However, this technology fails to reveal the spatial organization of cells in tissues, which also regulates the gene expression by intercellular communication. Herein, it is demonstrated that integrating time-resolved scRNA-seq with spatial transcriptomics is a new paradigm for spatiotemporal analysis. Metabolic RNA labeling-based time-resolved Well-TEMP-seq is first applied to profile the transcriptional dynamics of glioblastoma (GBM) cells and discover two potential pathways of EZH2-mediated mesenchymal transition in GBM. With spatial transcriptomics, it is further revealed that the crosstalk between CCL2+ malignant cells and IL10+ tumor-associated macrophages in the tumor microenvironment through an EZH2-FOSL2-CCL2 axis contributes to the mesenchymal transition in GBM. These discoveries show the power of integrative spatiotemporal scRNA-seq to elucidate the complex gene regulatory mechanism and advance the understanding of cellular processes in disease.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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