STAMP: Single-cell transcriptomics analysis and multimodal profiling through imaging

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.

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Publication Details

Journal
Cell
Published
2025-06-17
DOI
https://doi.org/10.1016/j.cell.2025.05.027
Citations
15
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
12.09
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STAMP: Single-cell transcriptomics analysis and multimodal profiling through imaging

Jasmine Plummer, Monika Mohenska, Adrienne E. Sullivan, B. Kate Dredge, Maycon Marção, Luciano G. Martelotto, Helena L. Crowell, Ginevra Caratù, Juan C. Nieto, Elise T. Courtois, German Atzin Mora-Roldan, Yutian Liu, William F. Flynn, Holger Heyn, Raymond K. H. Yip, Anna Pascual Reguant, Irepan Salvador‐Martínez, Santhosh Sivajothi, Kellie Wise, Ruvimbo D Mishi, Emily Soja, Hannah Chasteen, María Teresa Gil Ruiz, Emanuele Pitino, Felipe Segato-Dezem, J. M. Polo, Mohmed Abdalfttah
article en
15 citations

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.

CellVol. 188(18)
St. Jude Children's Research Hospital (US), Walter and Eliza Hall Institute of Medical Research (AU), Spanish National Cancer Research Centre (ES), Jackson Laboratory (US), Centre for Cancer Biology (AU), Centro Nacional de Análisis Genómico (ES), The University of Adelaide (AU)
Openalex Percentile: Top 1%
Single-cell and spatial transcriptomics
12.09
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