Spatial partitioning of cell and extracellular matrix in multiplexed fluorescence imaging of defined bone compartments in whole-femur cross-sections.

Multiplexed fluorescence imaging (MFI) is a unique method for bone tissue structural analysis that provides a large field-of-view spatial map of proteins visualized by immunofluorescence. Relative to traditional spatial proteomics, immunohistochemistry, or flow cytometry, these highly detailed images allow for structural analysis, combined with contextual mapping of both tissue and cells. This method produces large datasets in both size and scale, but existing methods to convert these large, fluorescence staining maps into quantitative data are often based on user-defined ROI and are not readily capable of distinguishing cellular and extracellular matrix (ECM)-related contributions of individual protein targets. Deconvoluting cellular from ECM-derived protein signatures is critical for characterizing specific microenvironments within bone and marrow to identify remodeling that occurs in disease, cancer, or changes in physiological status (eg, in development or the course of aging). Finally, cataloging the composition and organization of discrete regulatory niches is a prerequisite for reconstituting tissue-specific microphysiological systems ex vivo that recapitulate distinct tissue compartments present within bone and marrow. To address this critical gap, we developed an approach using QuPath and other open-source tools to analyze multiplexed images of bone sections containing multiple, structurally distinct tissue compartments. In this proof-of-concept study, cross-sections of whole mouse femurs were used to demonstrate spatial analysis and relative quantification of cellular and ECM markers across 4 tissue compartments: periosteum, cortical bone, trabecular bone, and BM, while also partitioning cell- and ECM-derived signals within each compartment.