Single Cell Analysis of High-Parameter Histology Images Using Histoflow Cytometry

Abstract

Abstract Immunofluorescence histology is commonly used to study immune cells in tissues where the number of fluorescence parameters is normally limited to four or less. This makes it impossible to interrogate multiple subsets of immune cells in tissue with the same precision as flow cytometry. The latter, however, dissociates tissues and loses spatial information. To bridge the gap between these technologies, we developed a workflow to expand the number of fluorescence parameters that can be imaged on widely available microscopes. We instituted a method for identifying single cells in tissue and exporting the data for flow cytometry–based analysis. This histoflow cytometry technique successfully separates spectrally overlapping dyes and identifies similar numbers of cells in tissue sections as manual cell counts. Populations identified through flow cytometry–like gating strategies are mapped to the original tissue to spatially localize gated subsets. We applied histoflow cytometry to immune cells in the spinal cords of mice with experimental autoimmune encephalomyelitis. We ascertained that B cells, T cells, neutrophils, and phagocytes differed in their frequencies in CNS immune cell infiltrates and were increased relative to healthy controls. Spatial analysis determined that B cells and T cells/phagocytes preferentially localized to CNS barriers and parenchyma, respectively. By spatially mapping these immune cells, we inferred their preferred interacting partners within immune cell clusters. Overall, we demonstrate the ease and utility of histoflow cytometry, which expands the number of fluorescent channels used in conventional immunofluorescence and enables quantitative cytometry and spatial localization of histological analyses.