High-resolution and differential analysis of rat microglial markers in traumatic brain injury: conventional flow cytometric and bioinformatics analysis

Traumatic brain injury (TBI) results in a cascade of cellular responses, which produce neuroinflammation, partly due to microglial activation. Transforming from surveying to primed phenotypes, microglia undergo considerable molecular changes. However, specific microglial profiles in rat remain elusive due to tedious methodology and limited availability of reagents. Here, we present a flow cytometry-based analysis of rat microglia 24 h after TBI using the controlled cortical impact model, validated with a bioinformatics approach. Isolated microglia are analyzed for morphological changes and their expression of activation markers using flow cytometry, traditional gating-based analysis methods and support the data by employing bioinformatics statistical tools. We use CD45, CD11b/c, and p2y12 receptor to identify microglia and evaluate their activation state using CD32, CD86, RT1B, CD200R, and CD163. The results from logic-gated flow cytometry analysis was validated with bioinformatics-based analysis and machine learning algorithms to detect quantitative changes in morphology and marker expression in microglia due to activation following TBI.