The long-term goal of our research is to construct and characterize a realistic three-dimensional model of the brain extracellular space (ECS), in order to predict the impact of microstructural changes on the transport of signaling molecules, nutrients and therapeutic agents. ECS comprises the narrow channels that separate brain cells but cannot be directly visualized in the living brain. It is essential for normal brain function and influences many critical processes including intercellular signaling, nutrient delivery and neurotrophic effects. Significantly, the ECS also forms the final route for all drug delivery to brain cells. To develop quantitative understanding of any of these diffusion mediated processes, essential structural parameters of the complex ECS environment must be identified and characterized. Traditional diffusion measurements, made over large distances and long times, extract two macroscopic parameters, volume fraction and tortuosity. Volume fraction is the proportion of tissue volume occupied by the ECS, and tortuosity quantifies average hindrance imposed on diffusing molecules by the complex ECS environment. Both parameters are affected by ECS manipulations, pathological conditions, and cellular activity. However, interpretation of the traditional macroscopic diffusion experiments in terms of the microscopic tissue properties is difficult and ambiguous. The principal goal of this proposal is to develop and deploy diffusion measurements with much higher spatial and time resolutions, in order to better match the ECS microstructure.
In Aim 1, we propose to develop a new diffusion method with spatial resolution improved by a factor of 10 compared to the traditional methods. Preliminary high-resolution experiments document transient anomalous diffusion on a scale of tens of micrometers. Diffusion stabilizes only after the molecules fully experience the complexity of the ECS environment. We call the smallest volume containing all of the ECS structural complexity a Dynamic Microdomain (DM). The size of the DM represents an important new tissue parameter, which will be measured and evaluated in addition to the traditional tortuosity and volume fraction.
Aims 2 −4 explore important aspects of the DMs.
Aim 2 examines how the beta2-adrenergic signaling invokes glia plasticity and alters the DM diffusion properties, which ultimately leads to modulation of neuronal excitability and signaling.
Aim 3 tests the hypothesis that perineuronal nets function as charge discriminating components within the DMs. Perineuronal nets, formed by negatively charged glycans of extracellular matrix, are found close to neurons in specialized ECS regions surrounded by glia. We propose that this high negative charge density attracts polyvalent cations but repulses polyvalent anions.
Aim 4 will establish the average width of the spaces separating the cells. Very few estimates of this basic parameter exist in a living cortical tissue. The scaling theory of polymer diffusion predicts the pore width from the diameter of a flexible polymer compelled to diffuse in the reptation regime. The characteristic pore width is essential for any realistic model of the DM and ECS, and equally so for construction of efficient drug carriers.
Brain cells, comprising neurons and glia, are surrounded by extracellular space (ECS), a system of interconnected pores that channels chemical signals between cells and is an essential route for delivery of nutrients and drugs. This project combines experiments to measure diffusion in brain tissue with mathematical modeling to characterize the microstructure of the ECS and how it is regulated. The results will be important both for understanding how altered ECS structure in neuropathological states disrupts the chemical traffic of the brain, and for designing effective strategies to deliver drugs in patients suffering from neurological disorders and brain tumors.
