High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging.

Resolving the spatial distribution of RNA and protein in tissues at subcellular resolution is a challenge in the field of spatial biology. We describe spatial molecular imaging, a system that measures RNAs and proteins in intact biological samples at subcellular resolution by performing multiple cycles of nucleic acid hybridization of fluorescent molecular barcodes. We demonstrate that spatial molecular imaging has high sensitivity (one or two copies per cell) and very low error rate (0.0092 false calls per cell) and background (~0.04 counts per cell). The imaging system generates three-dimensional, super-resolution localization of analytes at ~2 million cells per sample. Cell segmentation is morphology based using antibodies, compatible with formalin-fixed, paraffin-embedded samples. We measured multiomic data (980 RNAs and 108 proteins) at subcellular resolution in formalin-fixed, paraffin-embedded tissues (nonsmall cell lung and breast cancer) and identified >18 distinct cell types, ten unique tumor microenvironments and 100 pairwise ligand-receptor interactions. Data on >800,000 single cells and ~260 million transcripts can be accessed at http://nanostring.com/CosMx-dataset .

Spatially resolved whole transcriptome profiling in human and mouse tissue using Digital Spatial Profiling.

Emerging spatial profiling technology has enabled high-plex molecular profiling in biological tissues, preserving the spatial and morphological context of gene expression. Here, we describe expanding the chemistry for the Digital Spatial Profiling platform to quantify whole transcriptomes in human and mouse tissues using a wide range of spatial profiling strategies and sample types. We designed multiplexed in situ hybridization probes targeting the protein-coding genes of the human and mouse transcriptomes, referred to as the human or mouse Whole Transcriptome Atlas (WTA). Human and mouse WTAs were validated in cell lines for concordance with orthogonal gene expression profiling methods in regions ranging from ∼10-500 cells. By benchmarking against bulk RNA-seq and fluorescence in situ hybridization, we show robust transcript detection down to ∼100 transcripts per region. To assess the performance of WTA across tissue and sample types, we applied WTA to biological questions in cancer, molecular pathology, and developmental biology. Spatial profiling with WTA detected expected gene expression differences between tumor and tumor microenvironment, identified disease-specific gene expression heterogeneity in histological structures of the human kidney, and comprehensively mapped transcriptional programs in anatomical substructures of nine organs in the developing mouse embryo. Digital Spatial Profiling technology with the WTA assays provides a flexible method for spatial whole transcriptome profiling applicable to diverse tissue types and biological contexts.