Spatial Partitioning of Cell and Extracellular Matrix in Multiplex Fluorescence Imaging of Defined Bone Compartments in Whole-Femur Cross-Sections

Abstract

Multiplex 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, fluorescent staining maps into quantitative data are often based on user-defined regions-of-interest (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 which occurs in disease, cancer, or changes in physiological status (e.g., in development or course of aging). Finally, cataloguing 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 multiplex images of bone sections c–ontaining 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 makers across four tissue compartments: periosteum, cortical bone, trabecular bone and bone marrow, while also partitioning cell- and ECM-derived signals within each compartment.