Electroenzymatic glutamate sensing at near the theoretical performance limit

Abstract

Optimized sensors will enable more accurate monitoring of glutamate signaling in vivo.

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

“…For Glut released farther from the sensor surface, response is lower and broader. For distances greater than 30 μm, even with the 1-D simplifications that overestimate response, simulated response remains below the limit of detection (LOD), which has been determined experimentally as ∼0.7 μM for such sensors . However, this 1-D simulation cannot provide a quantitative prediction of the maximum sensor/release site separation distance that could give rise to a detectable signal, yet the sensor sampling distance likely is far less than the range for electrophysiological recordings (100–200 μm) .…”

“…Although the transient, one-dimensional model employed is an approximation, it is known to be a reasonably good one for the description of transport to typical sensors with characteristic dimension >25 μm . The sensor parameters used in this study correspond to a theoretically optimized design of the sort shown in Figure with a sensitivity of 364 nA μM –1 cm –2 and a response time of 8 ms, whereas the best measured intrinsic response time (in the absence of external mass transfer resistance) is ∼80 ms . These simulation results therefore correspond to aspirational sensor performance metrics, yet they illustrate well the key issues encountered in the interpretation of sensor data in what may be the best-case scenario.…”

“…The intrinsic response time for these sensors is defined in accordance with common practice in the field, namely, the time required for the sensor to reach 90% of the steady-state response to a step change in bulk Glut concentration in a system where external mass transfer resistance between the sensor and the bulk solution essentially is eliminated (by rapid stirring for example). The simulations presented here (Figure ) suggest that much longer times generally are required to approach steady state in vivo, typically >90 ms versus 8 ms in vitro for an ideal optimized sensor of the design shown in Figure , depending on sensor proximity to the Glut source and H 2 O 2 clearance rate. This order-of-magnitude difference between the simulated sensor response in vivo and the intrinsic sensor response time also arises from the slow rate of diffusive transport between the brain and the sensor surface.…”

“…A detailed, transient mathematical model in one spatial dimension (1-D) was developed to provide an approximate description of Glut sensor performance in vivo and to study the sensitivity of simulation results to parameters describing the clearance rate of Glut and H 2 O 2 from the brain ECS. This model builds upon a previously published mathematical description of sensor performance in vitro under conditions where external mass transfer resistance is minimal , to include an additional, brain ECS domain where the rates of chemical diffusion to and from the sensor as well as the biological clearance rates of Glut and H 2 O 2 are included. These rates of external mass transfer and clearance are generally not considered when a Glut sensor is calibrated in a stirred beaker, yet they play an important role in sensor performance in vivo.…”

“…Prior simulations of sensor calibration in vitro (using the same sensor parameters but including convective mass transfer at the sensor surface and a mass transfer coefficient of 0.05 cm/s for H 2 O 2 ) indicate that only ∼15% of the H 2 O 2 arising from Glut oxidation catalyzed by GlutOx immobilized in the sensor surface layer diffuses to the underlying Pt electrode where it is electrooxidized to give a current signal; most of the H 2 O 2 diffuses to the sensor surface where it is flushed away rapidly to the bulk solution by convective mass transfer. , In the brain, mass transfer of H 2 O 2 from the sensor surface to the ECS occurs primarily by much slower diffusion, augmented somewhat by biological mechanisms that clear H 2 O 2 at relatively slow rates. H 2 O 2 clearance results primarily from catalase activity and the glutathione system and exhibits characteristic times ranging from 0.1 s to minutes. − Nevertheless, the slower removal rates of H 2 O 2 can lead to not only higher sensor signals in vivo than expected from calibrations in vitro (as mentioned above), but also to a moderate accumulation of H 2 O 2 in the brain in the vicinity of the sensor.…”