QUANTITATIVE AND SPATIAL METHODS TO ANALYZE MICROGLIAL MORPHOLOGY AFTER INFLAMMATORY TRIGGERS

Abstract

Microglial reactivity in response to a pathological microenvironment is hallmarked by a change in cellular morphology. Microglia have a distinctive morphology that changes based on their reactivity and function. After an inflammatory insult, microglial reactivity is initially beneficial in restoring brain health. However, when microglial reactivity progresses chronically, it can increase cellular damage and worsen functional outcomes. New advancements in pharmacological and genetic manipulations of microglia have made targeting microglia after infection or injury a leading research area. However, understanding microglial population dynamics, under different physiological and inflammatory conditions, is essential for designing microglia-targeted therapeutics. In this dissertation, the morphology of microglia was examined after inflammatory stimuli; traumatic brain injury (TBI), cortical kainic acid injection, and lipopolysaccharide (LPS)/PLX5622 treatment. Although these are distinct inflammatory triggers, with different associated mechanical and chemical processes, each triggered robust microglial reactivity. The extent of de-ramification varied depending on other physiological variables, such as rodent age and whether the microglial cell was dividing. We applied and compared commonly used methods for examining microglial morphology and found multiple inconsistencies and issues among the different approaches. The experiments in this dissertation aimed to elucidate the morphological details of the microglial response to TBI in juvenile rats, in order to improve the efficacy of therapeutically targeting reactive microglia while considering age as an important biological variable. We also aimed to characterize different microglial morphologies during cell division after kainic acid injection, an inflammatory stimulus that causes high microglial reactivity. Finally, we highlight the discrepancies in morphological analysis techniques and highlight the need for standardization across the field of neuroscience.