Electroenzymatic choline sensing at near the theoretical performance limit.

A high performance, electroenzymatic microsensor for choline based on choline oxidase (ChOx) immobilized on Pt coated with permselective polymer layers has been created that exhibits sensitivity approaching the theoretical performance limit. Sensor construction was guided by simulations performed with a detailed mathematical model. Implantable microsensors with an array of electroenzymatic sensing sites provide a means to record concentration changes of choline, an effective surrogate for acetylcholine due to its very rapid turnover in the brain, and other neurochemicals in vivo. However, electroenzymatic sensors generally have insufficient sensitivity and response time to monitor neurotransmitter signaling on the millisecond timescale with cellular-level spatial resolution. Model simulations suggested that choline sensor performance can be improved significantly by optimizing immobilized ChOx layer thickness and minimizing the thicknesses of permselective polymer coatings as well. Electroenzymatic choline sensors constructed with a ∼5 µm-thick crosslinked ChOx layer atop 200 nm-thick permselective films (poly(m-phenylenediamine) and Nafion) exhibited unprecedented sensitivity and response time of 660 ± 40 nA µM-1 cm-2 at 37 °C and 0.36 ± 0.05 s, respectively, while maintaining excellent selectivity. Such performance characteristics provide greater flexibility in the design of microelectrode array (MEA) probes with near cellular-scale sensing sites arranged in more dense arrays. Also, faster response times enable better resolution of transient acetylcholine signals and better correlation of these events with electrophysiological recordings so as to advance study of brain function.

Electroenzymatic glutamate sensing at near the theoretical performance limit.

The sensitivity and response time of glutamate sensors based on glutamate oxidase immobilized on planar platinum microelectrodes have been improved to near the theoretical performance limits predicted by a detailed mathematical model. Microprobes with an array of electroenzymatic sensing sites have emerged as useful tools for the monitoring of glutamate and other neurotransmitters in vivo; and implemented as such, they can be used to study many complex neurological diseases and disorders including Parkinson's disease and drug addiction. However, less than optimal sensitivity and response time has limited the spatiotemporal resolution of these promising research tools. A mathematical model has guided systematic improvement of an electroenzymatic glutamate microsensor constructed with a 1-2 µm-thick crosslinked glutamate oxidase layer and underlying permselective coating of polyphenylenediamine and Nafion reduced to less than 200 nm thick. These design modifications led to a nearly 6-fold improvement in sensitivity to 320 ± 20 nA µM-1 cm-2 at 37 °C and a ∼10-fold reduction in response time to 80 ± 10 ms. Importantly, the sensitivity and response times were attained while maintaining a low detection limit and excellent selectivity. Direct measurement of the transport properties of the enzyme and polymer layers used to create the biosensors enabled improvement of the mathematical model as well. Subsequent model simulations indicated that the performance characteristics achieved with the optimized biosensors approach the theoretical limits predicted for devices of this construction. Such high-performance glutamate biosensors will be more effective in vivo at a size closer to cellular dimension and will enable better correlation of glutamate signaling events with electrical recordings.

Simulated Performance of Electroenzymatic Glutamate Biosensors In Vivo Illuminates the Complex Connection to Calibration In Vitro.

Detailed simulations show that the relationship between electroenzymatic glutamate (Glut) sensor performance in vitro and that modeled in vivo is complicated by the influence of both resistances to mass transfer and clearance rates of Glut and H2O2 in the brain extracellular space (ECS). Mathematical modeling provides a powerful means to illustrate how these devices are expected to respond to a variety of conditions in vivo in ways that cannot be accomplished readily using existing experimental techniques. Through the use of transient model simulations in one spatial dimension, it is shown that the sensor response in vivo may exhibit much greater dependence on H2O2 mass transfer and clearance in the surrounding tissue than previously thought. This dependence may lead to sensor signals more than double the expected values (based on prior sensor calibration in vitro) for Glut release events within a few microns of the sensor surface. The sensor response in general is greatly affected by the distance between the device and location of Glut release, and apparent concentrations reported by simulated sensors consistently are well below the actual Glut levels for events occurring at distances greater than a few microns. Simulations of transient Glut concentrations, including a physiologically relevant bolus release, indicate that detection of Glut signaling likely is limited to events within 30 µm of the sensor surface based on representative sensor detection limits. It follows that important limitations also exist with respect to interpretation of decays in sensor signals, including relation of such data to actual Glut concentration declines in vivo. Thus, the use of sensor signal data to determine quantitatively the rates of Glut uptake from the brain ECS likely is problematic. The model is designed to represent a broad range of relevant physiological conditions, and although limited to one dimension, provides much needed guidance regarding the interpretation in general of electroenzymatic sensor data gathered in vivo.

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.