Microglia are the resident macrophages of the central nervous system (CNS) and play a pivotal role in immune surveillance and CNS homeostasis. Morphological transitions in microglia are indicative for local changes in the CNS microenvironment and serve as a proxy for the detection of alterations in the CNS, both in health and disease. Current strategies to 'measure' microglia combine advanced morphometrics with clustering approaches to identify and categorize microglia morphologies. However, these studies are labor intensive and clustering approaches are often subject to relevant feature selection bias. Here, we provide a morphometrics pipeline with user-friendly computational tools for image segmentation, automated feature extraction and morphological categorization of microglia by means of hierarchical clustering on principal components (HCPC) without the need for feature inclusion criteria. With this pipeline we provide new and detailed insights in the distribution of microglia morphotypes across sixteen CNS regions along the rostro-caudal axis of the adult C57BL/6J mouse CNS. Although regional variations in microglia morphologies were evident, we found no evidence for male-female dimorphism at any CNS region investigated, indicating that - by and large - microglia in adult male and female mice are morphometrically indistinguishable. Taken together, our newly developed pipeline provides valuable tools for objective and unbiased identification and categorization of microglia morphotypes and can be applied to any CNS (disease) model.
Keywords: PCA; categorization; hierarchical clustering; microglia; morphology; morphometrics; principal component.
© 2023 The Authors. GLIA published by Wiley Periodicals LLC.