Flow Cytometry Characterization and Analysis of Glial and Immune Cells from the Spinal Cord

Abstract

Several protocols have been developed with the aim of characterizing glial and immune cells from the central and peripheral nervous systems. However, a small number of these protocols have demonstrated the ability to yield satisfactory results following conventional isolation. Considering this necessity and the difficulties encountered in enzymatic and bead isolation, our work proposes a method for the isolation of glial and immune cells from the spinal cord utilizing a Percoll gradient. For this purpose, C57BL/6J spinal cords were dissected, and the lumbar intumescence was dissociated and subjected to a Percoll gradient centrifugation (70%, 50%, 37%, and 10%). Each layer was then separated and labeled for astrocytes (anti-GFAP, TNF-α, IFN-γ, IL-10, IL-4), microglia (anti-CD45, CD11b, CD206, CD68, TNF-α, IFN-γ), and lymphocytes (anti-CD3, CD4, IFN-γ, IL-4). The gate detections were mathematically performed by computational analysis utilizing the K-means clustering algorithm. The results demonstrated that astrocytes were concentrated at the Percoll 10/37 interface, microglia at the Percoll 37/50 layer, and lymphocytes at the Percoll 50/70 layer. Our findings indicate that astrocytes in healthy animals are putative of the A1 profile, while microglia and lymphocytes are more frequently labeled with M1 and Th1 markers, suggesting a propensity towards inflammatory responses. The computational method enabled the semi-autonomous gate detection of flow cytometry data, which might facilitate and expedite the processing of large amounts of data.

Keywords

• flow cytometry
• spinal cord
• central nervous system
• glial cells
• immune cells