Multi-modal Data Synthesis from Organotypic Whole Hemisphere Brain Slice Models to Investigate Cellular-Extracellular Interactions

Abstract

The brain microenvironment is exceedingly complex and governed by interactions between and functions of cellular and extracellular components. These interactions and functions change across age, region, and under pathological conditions. Understanding how the brain microenvironment differs across these variables enables the development of therapeutics for neurological injuries and disorders. Microglia, the resident immune cells of the brain, and the extracellular matrix (ECM), a scaffold that supports tissue structure, are both implicated in disease and injury and offer therapeutics targets. While it is known that microglia and the ECM interact, the extent and mechanisms of interactions in injury and pathology is unclear, necessitating the development of tools and methods that can simultaneously detect changes of microglia and the ECM. In this dissertation, we first develop a suite of open-source software tools that apply data science and statistical methods to data collected in the brain microenvironment. By developing these tools, we increase the complexity of the analysis that can be done on these datasets while maintaining the reproducibility of the analysis and enabling other research to build from our software. We use these tools to then demonstrate the capability of multiple particle tracking as a proxy for changes to the ECM. We show that multiple particle tracking can detect changes to diffusion in the extracellular space (ECS) that vary with biological age and region and align with known changes to the ECM during neurodevelopment and across regions. In the same study, we demonstrate that multiple particle tracking can detect changes in an oxygen-glucose deprivation (OGD) brain slice model of hypoxic-ischemic injury and explainable machine learning can be used to determine region and treatment severity changes to nanoparticle diffusion. Next, we use confocal microscopy to investigate the heterogeneity of microglia morphologies in healthy brain tissue across six species, including human. We demonstrate that while the change in microglia morphology is conserved during neurodevelopment across species, there is regional heterogeneity based on species. We then compare microglia morphologies from white matter and gray matter regions at sexual maturity. Our results show that the differences between white and gray matter microglia in humans is distinct from the difference in rats and mice, an important translational finding. Lastly, we develop a collagen-based hydrogel mimic of brain tissue to demonstrate the feasibility of simultaneously and specially aligned multiple particle tracking and confocal microscopy of microglia. The work presented in this thesis establishes a computational framework for characterizing changes to the brain microenvironment across aging, region, and pathology at the microstructural and cellular level, and provides an experimental methodology for simultaneously investigating the interactions of microglia with the local extracellular environment in a tunable hydrogel mimic of brain tissue.