Abstract：
Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.
摘要：
空间转录组学（ST）方法解锁组织发育的分子机制，稳态，或疾病。然而,需要易于使用，高分辨率,成本效益高，和3D可扩展方法。这里,我们报告Open-ST,基于测序的，开源实验和计算资源，以解决这些挑战，并研究二维和三维组织的分子组织。在老鼠的大脑中，开放ST以亚细胞分辨率和重建的细胞类型捕获转录本。在原发性头颈部肿瘤和患者匹配的健康/转移性淋巴结中，开放ST捕获了免疫的多样性，基质,和太空中的肿瘤群体，通过基于成像的ST验证。不同的细胞状态组织在肿瘤中的细胞-细胞通讯热点周围，而不是转移。引人注目的是，转移性淋巴结的3D重建和多模态分析显示,在2D中不可见的空间上连续的结构和精确位于3D肿瘤/淋巴结边界的潜在生物标志物.所有协议和软件均可在https://rajewsky-lab获得。github.io/openst.
