Fig. 1

Schematics of the spatial multi-omics technologies, analysis workflow, and example data. A Schematics of workflows for spatial transcriptomics, proteomics, and metabolic analyses. Upper: Spatial transcriptomics platforms are classified into those based on next-generation sequencing and those based on in situ hybridization and in situ sequencing. The next-generation sequencing-based approaches use chips covered by a matrix of the barcoded oligonucleotides to capture mRNAs from the overlaid tissue. After tissue removal and probe harvest, a cDNA library with coordinate barcodes is prepared and sequenced. The in situ hybridization-based methods use fluorescently labeled probes that hybridize to the target transcripts. The in situ sequencing method uses probes to capture target transcripts, and sequencing is performed after rolling circle amplification. Middle: The spatial proteomic platforms utilize fluorescent reporters or metal-conjugated antibodies to recognize target proteins. For fluorescent reporters, repeated imaging and stripping to remove probes allow detection of many antibodies. In the methods that employ metal-conjugated antibodies, tissue is systematically ablated by a laser or an ion beam and analysis by mass spectrometry yields spatial and molecular information. Lower: For the spatial metabolomics, metabolites can be ionized and detected after sputtering from a spot or pixel on the tissue by a laser. B An example of a data analysis workflow for image processing and downstream analyses (clustering, spatial network analysis, or evaluation of cell–cell interactions) applicable to spatial multi-omics data. During image processing, information on the position of each cell is obtained by algorithmic definition. Clustering and neighborhood analyses can then be performed on the segmented images to obtain information about how cell types interact. C Example of results obtained from a multiplexed immunofluorescence imaging study performed using the CODEX method. The composite image of six key antibodies staining from the panel is shown on the left. The cell segmentation is shown in the middle. Cellular clustering and neighborhood analyses were performed, as shown on the right. Clusters are color coded. A chord diagram is used to represent the interactions between cell clusters. The size of the arc is proportional to the strength of the cell–cell interactions