Single-cell transcriptomics allows the analysis of biological systems at multiple scales of resolution, from single cells to whole organs. This technology has allowed the discovery of novel cell subsets and the identification of pathogenic activation states. However, to profile the transcriptome of cells, researchers must first obtain a single-cell suspension of their tissue of interest. In doing so, one of the most essential aspects of biology is lost: the spatial context of cells. Moreover, the specific method utilized to digest the tissue and generate a single-cell suspension can result in the lack of specific cell subsets. To fully understand how a given cell functions within a tissue, detailed information on its position in relation to other cells and to the structures that make up the organ is required alongside its transcriptional profile. The liver is the largest solid organ in the body, yet for many liver cells we still lack this crucial spatial information.

A spatial proteogenomic atlas of the healthy human and murine liver, combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics, has now been generated. Integrating these multiomic datasets allows all liver cells to be profiled. Moreover, this integration has enabled the identification of validated strategies to reliably discriminate, purify, and localize all hepatic cells, as well as identification of the respective cellular niches of all hepatic macrophage subtypes—which has further allowed the microenvironmental circuits driving the unique transcriptomic identities of these distinct cells to be identified, including an evolutionarily conserved cell–cell circuit between stellate cells and Kupffer cells, crucial for regulating Kupffer cell identity.

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