微阵列集成空间转录组学（MIST）用于负担得起且强大的数字病理学。

Microarray integrated spatial transcriptomics (MIST) for affordable and robust digital pathology.

机构信息

Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, New Delhi, India.

Department of Pathology, All India Institute of Medical Sciences, New Delhi, India.

出版信息

NPJ Syst Biol Appl. 2024 Nov 30;10(1):142. doi: 10.1038/s41540-024-00462-1.

DOI:10.1038/s41540-024-00462-1

PMID:39616155

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11608264/

Abstract

10X Visium, a popular Spatial transcriptomics (ST) method, faces limited adoption due to its high cost and restricted sample usage per slide. To address these issues, we propose Microarray Integrated Spatial Transcriptomics (MIST), combining conventional tissue microarray (TMA) with Visium, using laser-cutting and 3D printing to enhance slide throughput. Our design facilitates independent replication and customization in individual labs to suit specific experimental needs. We provide a step-by-step guide from designing TMAs to the library preparation step. We demonstrate MIST's cost-effectiveness and technical benefits over Visium and GeoMx Nanostring. We also introduce 'AnnotateMap', a novel computational tool for efficient analysis of multiple ROIs processed through MIST.

摘要

10X Visium 是一种流行的空间转录组学 (ST) 方法，但由于其成本高和每个载玻片的样本使用受限，限制了其应用。为了解决这些问题，我们提出了 Microarray Integrated Spatial Transcriptomics (MIST)，将传统的组织微阵列 (TMA) 与 Visium 相结合，使用激光切割和 3D 打印来提高载玻片通量。我们的设计便于在各个实验室中进行独立的复制和定制，以满足特定的实验需求。我们提供了从设计 TMA 到文库制备步骤的分步指南。我们展示了 MIST 在成本效益和技术优势方面相对于 Visium 和 GeoMx Nanostring 的优势。我们还介绍了'AnnotateMap'，这是一种用于通过 MIST 处理的多个 ROI 进行高效分析的新型计算工具。