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使用Open-ST进行高分辨率3D空间转录组学的方案。

Protocol for high-resolution 3D spatial transcriptomics using Open-ST.

作者信息

Schott Marie, León-Periñán Daniel, Splendiani Elena, Ferretti Elisabetta, Macino Giuseppe, Karaiskos Nikos, Rajewsky Nikolaus

机构信息

Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany.

Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany; Department of Experimental Medicine, Sapienza University, Rome, Italy.

出版信息

STAR Protoc. 2025 Mar 21;6(1):103521. doi: 10.1016/j.xpro.2024.103521. Epub 2024 Dec 19.

DOI:10.1016/j.xpro.2024.103521
PMID:39708325
原文链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC11731217/
Abstract

Spatial transcriptomics (ST) is fundamental for understanding molecular mechanisms in health and disease. Here, we present a protocol for efficient and high-resolution ST in 2D/3D with Open-ST. We describe all steps for repurposing Illumina flow cells into spatially barcoded capture areas and preparing ST libraries from stained cryosections. We detail the computational workflow for generating 2D/3D molecular maps ("virtual tissue blocks"), aligned with histological data, unlocking molecular pathways in space. Open-ST is applicable to any tissue, including clinical samples. For complete details on the use and execution of this protocol, please refer to Schott et al..

摘要

空间转录组学（ST）对于理解健康和疾病中的分子机制至关重要。在此，我们展示了一种使用Open-ST在二维/三维中进行高效和高分辨率ST的方案。我们描述了将Illumina流动槽重新用于空间条形码捕获区域以及从染色的冷冻切片制备ST文库的所有步骤。我们详细介绍了生成与组织学数据对齐的二维/三维分子图谱（“虚拟组织块”）、揭示空间分子途径的计算工作流程。Open-ST适用于任何组织，包括临床样本。有关本方案使用和执行的完整详细信息，请参考肖特等人的文献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/871cb770dbe5/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/a1acb970eeff/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/212ae3a853a5/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/0ac37065beae/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/c52c23600fc5/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/a6375c30d57f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/c4c5b9eb6235/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/af50b2ba17c2/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/5ed6a74f99ee/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/36ee036c195b/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/7cd43f6607af/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/871cb770dbe5/gr10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/a1acb970eeff/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/212ae3a853a5/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/0ac37065beae/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/c52c23600fc5/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/a6375c30d57f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/c4c5b9eb6235/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/af50b2ba17c2/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/5ed6a74f99ee/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/36ee036c195b/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/7cd43f6607af/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63d7/11731217/871cb770dbe5/gr10.jpg

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本文引用的文献

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Spatiotemporal omics for biology and medicine.
生物与医学的时空组学
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