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Learn about Stereo-cell, a groundbreaking spatial single-cell sequencing platform that overcomes traditional limitations in cellular analysis through this comprehensive conference talk by Xun Xu. Discover how high-density DNA nanoball (DNB)-patterned arrays enable in situ transcript capture without compartmentalized encapsulation, supporting direct profiling of cells ranging from small to large sizes, extracellular vesicles, and complex microstructures. Explore the platform's ability to accurately capture transcriptomes from 200 to nearly 1 million cells per chip with high reproducibility and minimal doublet rates, enhanced by deep learning-based cell segmentation and imaging-based doublet elimination. Examine benchmarking studies using human peripheral blood mononuclear cells (PBMCs) that demonstrate how Stereo-cell generates gene expression profiles matching established droplet-based methods while more faithfully recovering cell-type proportions compared to flow cytometry reference data. Understand how the platform identifies rare immune populations such as hematopoietic stem and progenitor cells from large-scale samples and enables integration with multiplex immunofluorescence and oligo-barcoded antibodies for concurrent mRNA and protein profiling. Investigate applications in profiling cultured fibroblasts to capture microenvironmental cues, extracellular vesicle-like structures, and cellular responses to stimulation, as well as sequencing structurally complex samples including mouse oocytes and multinucleated skeletal myofibers while preserving subcellular transcript localization. Gain insights into how this integrative framework advances high-throughput single-cell transcriptomics with enhanced spatial and multimodal capabilities, improving scalability, flexibility, and precision in analyzing cell-cell interactions, microenvironments, and subcellular gene expression patterns.
