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HISSTA：一个人类原位单细胞转录组图谱。

HISSTA: a human in situ single-cell transcriptome atlas.

作者信息

Yu Jiwon, Moon Jiwoo, Kim Minseo, Han Gyeol, Jang Insu, Lim Jinyoung, Lee Seungmook, Yoon Seok-Hwan, Park Woong-Yang, Lee Byungwook, Lee Sanghyuk

机构信息

Department of Life Science, Ewha Womans University, Seoul 03760, Republic of Korea.

Korean Bioinformation Center (KOBIC), Korean Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.

出版信息

Bioinformatics. 2025 Mar 29;41(4). doi: 10.1093/bioinformatics/btaf142.

DOI:10.1093/bioinformatics/btaf142
PMID:40163697
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12002909/
Abstract

MOTIVATION

Spatial transcriptomics holds great promise for revolutionizing biology and medicine by providing gene expression profiles with spatial information. Until recently, spatial resolution has been limited, but advances in high-throughput in situ imaging technologies now offer new opportunities by covering thousands of genes at a single-cell or even subcellular resolution, necessitating databases dedicated to comprehensive coverage and analysis with user-friendly intefaces.

RESULTS

We introduce the HISSTA database, which facilitates the archival and analysis of in situ transcriptome data at single-cell resolution from various human tissues. We have collected and annotated spatial transcriptome data generated by MERFISH, CosMx SMI, and Xenium techniques, encompassing 112 samples and 28 million cells across 16 tissue types from 63 studies. To decipher spatial contexts, we have implemented advanced tools for cell type annotation, spatial colocalization, spatial cellular communication, and niche analyses. Notably, all datasets and annotations are interactively accessible through Vitessce, allowing users to focus on regions of interest and examine gene expression in detail. HISSTA is a unique database designed to manage the rapidly growing dataset of in situ transcriptomes at single-cell resolution. Given its comprehensive data content and advanced analysis tools with interactive visualizations, HISSTA is poised to significantly impact cancer diagnosis, precision medicine, and digital pathology.

AVAILABILITY AND IMPLEMENTATION

HISSTA is freely accessible at https://kbds.re.kr/hissta/. The source code is available at https://doi.org/10.5281/zenodo.14904523.

摘要

动机

空间转录组学通过提供带有空间信息的基因表达谱，有望给生物学和医学带来变革。直到最近，空间分辨率一直受到限制，但高通量原位成像技术的进步现在提供了新的机会，能够以单细胞甚至亚细胞分辨率覆盖数千个基因，这就需要有专门的数据库，以便全面覆盖并通过用户友好的界面进行分析。

结果

我们推出了HISSTA数据库，该数据库有助于存档和分析来自各种人体组织的单细胞分辨率原位转录组数据。我们收集并注释了通过MERFISH、CosMx SMI和Xenium技术生成的空间转录组数据，涵盖来自63项研究的16种组织类型的112个样本和2800万个细胞。为了解析空间背景，我们实施了用于细胞类型注释、空间共定位、空间细胞通讯和生态位分析的先进工具。值得注意的是，所有数据集和注释都可以通过Vitessce进行交互式访问，使用户能够专注于感兴趣的区域并详细检查基因表达。HISSTA是一个独特的数据库，旨在管理快速增长的单细胞分辨率原位转录组数据集。鉴于其全面的数据内容和具有交互式可视化的先进分析工具，HISSTA有望对癌症诊断、精准医学和数字病理学产生重大影响。

可用性和实施

可通过https://kbds.re.kr/hissta/免费访问HISSTA。源代码可在https://doi.org/10.5281/zenodo.14904523获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/3773e739b9c4/btaf142f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/af8ee0d7e747/btaf142f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/7cb647095c07/btaf142f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/a711f3b249dd/btaf142f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/adddb57eacae/btaf142f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/257791b0c6c2/btaf142f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/3773e739b9c4/btaf142f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/af8ee0d7e747/btaf142f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/7cb647095c07/btaf142f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/a711f3b249dd/btaf142f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/adddb57eacae/btaf142f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/257791b0c6c2/btaf142f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fd1/12002909/3773e739b9c4/btaf142f6.jpg

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本文引用的文献

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Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows.通过质量评估和最佳实践分析工作流程优化Xenium原位数据效用。
Nat Methods. 2025 Apr;22(4):813-823. doi: 10.1038/s41592-025-02617-2. Epub 2025 Mar 13.
2
Vitessce: integrative visualization of multimodal and spatially resolved single-cell data.Vitessce：多模态和空间分辨单细胞数据的整合可视化
Nat Methods. 2025 Jan;22(1):63-67. doi: 10.1038/s41592-024-02436-x. Epub 2024 Sep 27.
3
CellChat for systematic analysis of cell-cell communication from single-cell transcriptomics.
CellChat用于从单细胞转录组学进行细胞间通讯的系统分析。
Nat Protoc. 2025 Jan;20(1):180-219. doi: 10.1038/s41596-024-01045-4. Epub 2024 Sep 16.
4
Spatially resolved analysis of pancreatic cancer identifies therapy-associated remodeling of the tumor microenvironment.胰腺癌的空间分辨分析确定了治疗相关的肿瘤微环境重塑。
Nat Genet. 2024 Nov;56(11):2466-2478. doi: 10.1038/s41588-024-01890-9. Epub 2024 Sep 3.
5
Automatic cell-type harmonization and integration across Human Cell Atlas datasets.自动细胞类型协调和整合人类细胞图谱数据集。
Cell. 2023 Dec 21;186(26):5876-5891.e20. doi: 10.1016/j.cell.2023.11.026.
6
High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis.利用集成的单细胞、空间和原位分析技术对肿瘤微环境进行高分辨率图谱绘制。
Nat Commun. 2023 Dec 19;14(1):8353. doi: 10.1038/s41467-023-43458-x.
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SORC: an integrated spatial omics resource in cancer.SORC：癌症综合空间组学资源。
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