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空间转录组学:整合肾脏疾病的形态学与分子机制

Spatial Transcriptomics: Integrating Morphology and Molecular Mechanisms of Kidney Diseases.

作者信息

Isnard Pierre, Humphreys Benjamin D

机构信息

Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri.

Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri; Department of Developmental Biology, Washington University in St. Louis, St. Louis, Missouri.

出版信息

Am J Pathol. 2025 Jan;195(1):23-39. doi: 10.1016/j.ajpath.2024.06.012. Epub 2024 Aug 5.

DOI:10.1016/j.ajpath.2024.06.012
PMID:39097166
Abstract

The recent arrival of high-resolution spatial transcriptomics (ST) technologies is generating a veritable revolution in life sciences, enabling biomolecules to be measured in their native spatial context. By integrating morphology and molecular biology, ST technologies offer the potential of improving the understanding of tissue biology and disease and may also provide meaningful clinical insights. This review describes the main ST technologies currently available and the computational analysis for data interpretation and visualization, and illustrate their scientific and potential medical interest in the context of kidney disease. Finally, we discuss the perspectives and challenges of these booming new technologies.

摘要

高分辨率空间转录组学(ST)技术的近期出现正在生命科学领域引发一场名副其实的革命,使生物分子能够在其原生空间背景下进行测量。通过整合形态学和分子生物学,ST技术提供了增进对组织生物学和疾病理解的潜力,还可能提供有意义的临床见解。本综述描述了当前可用的主要ST技术以及用于数据解释和可视化的计算分析,并阐述了它们在肾脏疾病背景下的科学及潜在医学价值。最后,我们讨论了这些蓬勃发展的新技术的前景和挑战。

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本文引用的文献

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Spatial transcriptomics defines injury specific microenvironments and cellular interactions in kidney regeneration and disease.空间转录组学定义了肾脏再生和疾病中损伤特异性的微环境和细胞相互作用。
Nat Commun. 2024 Sep 5;15(1):7010. doi: 10.1038/s41467-024-51186-z.
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Single-cell multi-omic and spatial profiling of human kidneys implicates the fibrotic microenvironment in kidney disease progression.单细胞多组学和空间分析揭示了人类肾脏纤维化微环境在肾脏疾病进展中的作用。
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Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology.通过将空间转录组学与组织学相结合来推断超分辨率组织结构。
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