Microglial Metamorphosis in Three Dimensions in Virus Limbic Encephalitis: An Unbiased Pictorial Representation Based on a Stereological Sampling Approach of Surveillant and Reactive Microglia

Abstract

Microglia influence pathological progression in neurological diseases, reacting to insults by expressing multiple morphofunctional phenotypes. However, the complete morphological spectrum of reactive microglia, as revealed by three-dimensional microscopic reconstruction, has not been detailed in virus limbic encephalitis. Here, using an anatomical series of brain sections, we expanded on an earlier Piry arbovirus encephalitis study to include CA1/CA2 and assessed the morphological response of homeostatic and reactive microglia at eight days post-infection. Hierarchical cluster and linear discriminant function analyses of multimodal morphometric features distinguished microglial morphology between infected animals and controls. For a broad representation of the spectrum of microglial morphology in each defined cluster, we chose representative cells of homeostatic and reactive microglia, using the sum of the distances of each cell in relation to all the others. Based on multivariate analysis, reactive microglia of infected animals showed more complex trees and thicker branches, covering a larger volume of tissue than in control animals. This approach offers a reliable representation of microglia dispersion in the Euclidean space, revealing the morphological kaleidoscope of surveillant and reactive microglia morphotypes. Because form precedes function in nature, our findings offer a starting point for research using integrative methods to understand microglia form and function.

Influenza vaccine is able to prevent neuroinflammation triggered by H7N7 IAV infection

“…In addition to increased numbers of microglial cells as a hallmark of neuroinflammation, one of the common metrics used to assess microglial activation is a broad morphological change from a small soma with branched processes in homeostasis to an amoeboid with thicker and less complex processes during neuroinflammation ( Woodburn et al, 2021 ). Indeed, initial reports indicated that viral infections, including IAV infection, cause microglial activation based mainly on changes in morphological features ( Hosseini et al, 2018 ; da Silva Creão et al, 2021 ). The main phenotypic changes in activated microglia are an increase in soma volume, retraction of processes, and loss of uniform tissue distribution ( Arcuri et al, 2017 ).…”

Dissecting Reactive Astrocyte Responses: Lineage Tracing and Morphology-based Clustering

“…Finally, in this work we are pioneers in establishing a method to classify astrocytes based on their morphology changes in response to injury, correlating different morphological parameters with their intensity of the response. Previous works have introduced this type of approaches to study neuronal subpopulations for example in the nucleus of the solitary tract (Schweitzer et Renehan, 1997) or to categorize diverse subpopulations of hippocampal astrocytes in migratory birds (Carvalho-Paulo et al, 2018;Henrique et al, 2021;de Almeida et al, 2022), reactive microglia in models of encephalitis (de Sousa et al, 2015;da Silva Creão et al, 2021) or in models of neuroinflammation (Fernández-Arjona et al, 2017); and immune cells in starfishes (Karetin, 2021). Here, we developed a multimodality index (MMI) to select parameters that best describe the population heterogenicity, and subsequently applied hierarchical clustering (HC), and principal component analysis (PCA) to identify and construct a dendrogram of reactive responses.…”

Contrasting Disease Progression, Microglia Reactivity, Tolerance, and Resistance to <em>Toxoplasma gondii</em> Infection in Two Mouse Strains

“…Microscopic three-dimensional reconstruction techniques, coupled with hierarchical cluster analysis of morphometric features, have been pivotal in classifying microglia across diverse species, elucidating their states under both homeostatic and non-homeostatic conditions (37,50,64,65). This methodology provides an objective framework to characterize and quantify the observed morphological changes, offering insights into microglial alterations during normal homeostasis and neuropathological states [66][67][68].…”