(249c) Nanotechnology-Based Probes of Structure-Function in Living Tissue

The human brain is highly connected over a number of different length and time scales, spanning communication between neurons to communication across distant brain regions. The study of how the structure of the brain is connected to its many functions is an emerging approach to understanding neurological and psychiatric disorders. However, while advances in brain imaging methods are producing maps of structure or function with unprecedented accuracy and resolution, the ways in which structure shapes function is still not known. Our lab develops methods that can integrate multiple types of data to better understand and predict structural and functional relationships in the brain. In this talk, we will discuss our use of nanotechnology, neurobiology, and data science tools to characterize changes in extracellular matrix (ECM) structure in living brain tissue. We first establish the utility and sensitivity of our toolbox.

Using multiple particle tracking, we track 100,000’s of nanoparticles in organotypic brain slices, extract nanoparticle trajectories, and apply machine learning to predict aspects of nanoparticle behavior in tissue slices. For example, we measure nanoparticle size, surface charge, and protein corona formation in vitro, and based on the diffusion of these nanoparticles, we predict whether a particle will internalize or not into cells in the brain. We validate our findings with FACS and immunofluorescent imaging. We next show modulation of organotypic brain slices to capture disease pathways common in many neurological disorders. We use RT-PCR, ELISAs, and live cell imaging to quantify molecular and functional changes in microglia and neurons in response to these induced pathological conditions. Finally, we show how the integration of these techniques can map structural changes of specific ECM structures that regulate neuronal plasticity and the associated functional changes observed in normal development and in the presence of injury.

This work demonstrates that multiple particle tracking of nanoparticle probes in the brain can be used in combination with molecular, cellular, and functional techniques to extract new insights in region-dependent or pathology-dependent structure-function relationships. The long-term goal of this work is to change the way researchers combine diverse data with advanced imaging by integrating outputs from multiple experimental sources using machine learning and data science tools.