Abstract

Recently developed approaches for highly-multiplexed 2-dimensional (2D) and 3D imaging have revealed complex patterns of cellular positioning and cell-cell interactions with important roles in both cellular and tissue level physiology. However, robust and accessible tools to quantitatively study cellular patterning and tissue architecture are currently lacking. Here, we developed a spatial analysis toolbox, Histo-Cytometric Multidimensional Analysis Pipeline (CytoMAP), which incorporates neural network based data clustering, positional correlation, dimensionality reduction, and 2D/3D region reconstruction to identify localized cellular networks and reveal fundamental features of tissue organization. We apply CytoMAP to study the microanatomy of innate immune subsets in murine lymph nodes (LNs) and reveal mutually exclusive segregation of migratory dendritic cells (DCs), regionalized compartmentalization of SIRPa-dermal DCs, as well as preferential association of resident DCs with select LN vasculature. These studies provide new insights into the organization of myeloid cells in LNs, and demonstrate that CytoMAP is a comprehensive analytics toolbox for revealing fundamental features of tissue organization in quantitative imaging datasets.

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