国家基因组分析中心（CNAG）Luciano G. Martelotto团队近日取得一项新成果。经过不懈努力，他们报道了通过成像进行单细胞转录组学分析和多模式分析。该项研究成果发表在2025年6月17日出版的《细胞》上。
为了克服这些挑战，该研究团队开发了STAMP（单细胞转录组学分析和多模态分析），这是一种高度可扩展的单细胞分析方法。通过利用转录组学和蛋白质组学成像平台，STAMP消除了测序成本，使数百万细胞的单细胞基因组学具有成本效益。在成像载玻片上固定（冲压）smthempension细胞，STAMP支持多模态（RNA，蛋白质和H&E）分析，同时保留细胞结构和形态。研究小组通过分析外周血单个核细胞、细胞系和干细胞来证明STAMP的多功能性。该研究组强调STAMP识别超罕见细胞群的能力，模拟临床应用，并展示其在大规模摄动研究中的实用性。课题组总共提供了10,962,092个高质量细胞/细胞核和6,030,429,954个转录本的数据。STAMP使高分辨率的细胞分析更容易获得，可扩展和负担得起。
研究人员表示，单细胞RNA测序已经彻底改变了他们对细胞多样性的理解，但仍然受到可扩展性、高成本和分析过程中细胞破坏的限制。
附：英文原文
Title: STAMP: Single-cell transcriptomics analysis and multimodal profiling through imaging
Author: Emanuele Pitino, Anna Pascual-Reguant, Felipe Segato-Dezem, Kellie Wise, Irepan Salvador-Martinez, Helena Lucia Crowell, Maycon Maro, Max Ruiz, Elise Courtois, William F. Flynn, Santhosh Sivajothi, Emily Soja, Ginevra Caratù, German Atzin Mora-Roldan, B. Kate Dredge, Yutian Liu, Hannah Chasteen, Monika Mohenska, Juan C. Nieto, Raymond K.H. Yip, Ruvimbo D. Mishi, José M. Polo, Mohmed Abdalfttah, Adrienne E. Sullivan, Jasmine T. Plummer, Holger Heyn, Luciano G. Martelotto
Issue&Volume: 2025-06-17
Abstract: Single-cell RNA sequencing has revolutionized our understanding of cellular diversity but remains constrained by scalability, high costs, and the destruction of cells during analysis. To overcome these challenges, we developed STAMP (single-cell transcriptomics analysis and multimodal profiling), a highly scalable approach for the profiling of single cells. By leveraging transcriptomics and proteomics imaging platforms, STAMP eliminates sequencing costs, enabling cost-efficient single-cell genomics of millions of cells. Immobilizing (stamping) cells in suspension onto imaging slides, STAMP supports multimodal (RNA, protein, and H&E) profiling, while retaining cellular structure and morphology. We demonstrate STAMP’s versatility by profiling peripheral blood mononuclear cells, cell lines, and stem cells. We highlight the capability of STAMP to identify ultra-rare cell populations, simulate clinical applications, and show its utility for large-scale perturbation studies. In total, we present data for 10,962,092 high-quality cells/nuclei and 6,030,429,954 transcripts. STAMP makes high-resolution cellular profiling more accessible, scalable, and affordable.
DOI: 10.1016/j.cell.2025.05.027
Source: https://www.cell.com/cell/abstract/S0092-8674(25)00577-X