Microelectrode Array Fabrication and Optimization for Selective Neurochemical Detection

Phasic oxygen dynamics confounds fast choline-sensitive biosensor signals in the brain of behaving rodents

Cholinergic fast time-scale modulation of cortical physiology is critical for cognition, but direct local measurement of neuromodulators in vivo is challenging. Choline oxidase (ChOx)-based electrochemical biosensors have been used to capture fast cholinergic signals in behaving animals. However, these transients might be biased by local field potential and O₂-evoked enzymatic responses. Using a novel Tetrode-based Amperometric ChOx (TACO) sensor, we performed highly sensitive and selective simultaneous measurement of ChOx activity (COA) and O₂. In vitro and in vivo experiments, supported by mathematical modeling, revealed that non-steady-state enzyme responses to O₂ give rise to phasic COA dynamics. This mechanism accounts for most of COA transients in the hippocampus, including those following locomotion bouts and sharp-wave/ripples. Our results suggest that it is unfeasible to probe phasic cholinergic signals under most behavioral paradigms with current ChOx biosensors. This confound is generalizable to any oxidase-based biosensor, entailing rigorous controls and new biosensor designs.

LY379268 Does Not Have Long-Term Procognitive Effects nor Attenuate Glutamatergic Signaling in AβPP/PS1 Mice

Chronically elevated basal glutamate levels are hypothesized to attenuate detection of physiological signals thereby inhibiting memory formation and retrieval, while inducing excitotoxicity-mediated neurodegeneration observed in Alzheimer's disease (AD). However, current medication targeting the glutamatergic system, such as memantine, shows limited efficacy and is unable to decelerate disease progression, possibly because it modulates postsynaptic N-methyl-D-aspartate receptors rather than glutamate release or clearance. To determine if decreasing presynaptic glutamate release leads to long-term procognitive effects, we treated AβPP/PS1 mice with LY379268 (3.0 mg/kg; i.p.), a metabotropic glutamate receptor (mGluR)2/3 agonist from 2-6 months of age when elevated glutamate levels are first observed but cognition is unaffected. C57BL/6J genetic background control mice and another cohort of AβPP/PS1 mice received normal saline (i.p.) as vehicle controls. After 6 months off treatment, mice receiving LY379268 did not show long-term improvement as assessed by the Morris water maze (MWM) spatial learning and memory paradigm. Following MWM, mice were isoflurane anesthetized and a glutamate selective microelectrode was used to measure in vivo basal and stimulus-evoked glutamate release and clearance independently from the dentate, CA3, and CA1 hippocampal subregions. Immunohistochemistry was used to measure hippocampal astrogliosis and plaque pathology. Similar to previous studies, we observed elevated basal glutamate, stimulus evoked glutamate release, and astrogliosis in AβPP/PS1 vehicle mice versus C57BL/6J mice. Treatment with LY379268 did not attenuate these responses nor diminish plaque pathology. The current study builds upon previous research demonstrating hyperglutamatergic hippocampal signaling in AβPP/PS1 mice; however, long-term therapeutic efficacy of LY379268 in AβPP/PS1 was not observed.

A Detailed Model of Electroenzymatic Glutamate Biosensors To Aid in Sensor Optimization and in Applications in Vivo

Simulations conducted with a detailed model of glutamate biosensor performance describe the observed sensor performance well, illustrate the limits of sensor performance, and suggest a path toward sensor optimization. Glutamate is the most important excitatory neurotransmitter in the brain, and electroenzymatic sensors have emerged as a useful tool for the monitoring of glutamate signaling in vivo. However, the utility of these sensors currently is limited by their sensitivity and response time. A mathematical model of a typical glutamate biosensor consisting of a Pt electrode coated with a permselective polymer film and a top layer of cross-linked glutamate oxidase has been constructed in terms of differential material balances on glutamate, H₂O₂, and O₂ in one spatial dimension. Simulations suggest that reducing thicknesses of the permselective polymer and enzyme layers can increase sensitivity ∼6-fold and reduce response time ∼7-fold, and thereby improve resolution of transient glutamate signals. At currently employed enzyme layer thicknesses, both intrinsic enzyme kinetics and enzyme deactivation likely are masked by mass transfer. However, O₂-dependence studies show essentially no reduction in signal at the lowest anticipated O₂ concentrations for expected glutamate concentrations in the brain and that O₂ transport limitations in vitro are anticipated only at glutamate concentrations in the mM range. Finally, the limitations of current biosensors in monitoring glutamate transients is simulated and used to illustrate the need for optimized biosensors to report glutamate signaling accurately on a subsecond time scale. This work demonstrates how a detailed model can be used to guide optimization of electroenzymatic sensors similar to that for glutamate and to ensure appropriate interpretation of data gathered using such biosensors.

Enhanced Cognition and Hypoglutamatergic Signaling in a Growth Hormone Receptor Knockout Mouse Model of Successful Aging

Growth hormone receptor knockout (GHR-KO) mice are long lived with improved health span, making this an excellent model system for understanding biochemical mechanisms important to cognitive reserve. The purpose of the present study was to elucidate differences in cognition and glutamatergic dynamics between aged (20- to 24-month-old) GHR-KO and littermate controls. Glutamate plays a critical role in hippocampal learning and memory and is implicated in several neurodegenerative disorders, including Alzheimer's disease. Spatial learning and memory were assessed using the Morris water maze (MWM), whereas independent dentate gyrus (DG), CA3, and CA1 basal glutamate, release, and uptake measurements were conducted in isoflurane anesthetized mice utilizing an enzyme-based microelectrode array (MEA) coupled with constant potential amperometry. These MEAs have high temporal and low spatial resolution while causing minimal damage to the surrounding parenchyma. Littermate controls performed worse on the memory portion of the MWM behavioral task and had elevated DG, CA3, and CA1 basal glutamate and stimulus-evoked release compared with age-matched GHR-KO mice. CA3 basal glutamate negatively correlated with MWM performance. These results support glutamatergic regulation in learning and memory and may have implications for therapeutic targets to delay the onset of, or reduce cognitive decline, in Alzheimer's disease.

Modeling microelectrode biosensors: free-flow calibration can substantially underestimate tissue concentrations

Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue environment and experimentally verify our key predictions.

Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments.

NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue environment and experimentally verify our key predictions.