Optimized Fabrication of Carbon-Fiber Microbiosensors for Codetection of Glucose and Dopamine in Brain Tissue.

Dopamine (DA) signaling is critically important in striatal function, and this metabolically demanding process is fueled largely by glucose. However, DA and glucose are typically studied independently and, as such, the precise relationship between DA release and glucose availability remains unclear. Fast-scan cyclic voltammetry (FSCV) is commonly coupled with carbon-fiber microelectrodes to study DA transients. These microelectrodes can be modified with glucose oxidase (GOx) to generate microbiosensors capable of simultaneously quantifying real-time and physiologically relevant fluctuations of glucose, a nonelectrochemically active substrate, and DA, which is readily oxidized and reduced at the electrode surface. A chitosan hydrogel can be electrodeposited to entrap the oxidase enzyme on the sensor surface for stable, sensitive, and selective codetection of glucose and DA using FSCV. This strategy can also be used to entrap lactate oxidase on the carbon-fiber surface for codetection of lactate and DA. However, these custom probes are individually fabricated by hand, and performance is variable. This study characterizes the physical nature of the hydrogel and its effects on the acquired electrochemical data in the detection of glucose (2.6 mM) and DA (1 µM). The results demonstrate that the electrodeposition of the hydrogel membrane is improved using a linear potential sweep rather than a direct step to the target potential. Electrochemical impedance spectroscopy data relate information on the physical nature of the electrode/solution interface to the electrochemical performance of bare and enzyme-modified carbon-fiber microelectrodes. The electrodeposition waveform and scan rate were characterized for optimal membrane formation and performance. Finally, codetection of both DA/glucose and DA/lactate was demonstrated in intact rat striatum using probes fabricated according to the optimized protocol. Overall, this work improves the reliable fabrication of carbon-fiber microbiosensors for codetection of DA and important energetic substrates that are locally delivered to the recording site to meet metabolic demand.

Exploring Electrochemistry: A Hydrogen Peroxide Sensor Based on a Screen-Printed Carbon Electrode Modified with Prussian Blue.

There is an increasing need for fundamental electrochemistry concepts to be taught in the undergraduate curriculum, given the broad applicability of electrochemical technologies in addressing a wide range of global issues from critical energy shortages to real-time medical diagnostics. However, many electrochemical concepts are often taught in disparate laboratory experiments, spread out through the curriculum, which can be intimidating to students (and instructors). This experiment, which has been tested and optimized in the undergraduate classroom over multiple semesters, covers a wide range of electrochemistry topics in realizing the construction of a hydrogen peroxide (H2O2) sensor that is based on Prussian blue electrochemistry. The experiment introduces the fundamentals of cyclic voltammetry by prompting students to distinguish faradaic and capacitive components of voltammograms and to investigate their relationship with scan rate as per electrochemical theory. Students also evaluate electrocatalysis through electrodeposition of a thin film of Prussian blue on the sensor surface and the effects of this modification on electron transfer and sensor performance. Finally, students combine amperometric measurements with the method of standard additions to determine H2O2 concentrations in an unknown sample. Overall, this experiment offers an integrated and cohesive experience that connects many important electroanalytical concepts that are often taught individually into one 3 h, hands-on laboratory experiment that requires minimal resources.

Simultaneous, Real-Time Detection of Glutamate and Dopamine in Rat Striatum Using Fast-Scan Cyclic Voltammetry.

Glutamate and dopamine (DA) represent two key contributors to striatal functioning, a region of the brain that is essential to motor coordination and motivated behavior. While electroanalytical techniques can be utilized for rapid, spatially resolved detection of DA in the interferent-rich brain environment, glutamate, a nonelectroactive analyte, cannot be directly detected using electroanalytical techniques. However, it can be probed using enzyme-based sensors, which generate an electroactive reporter in the presence of glutamate. The vast majority of glutamate biosensors have relied on amperometric sensing, which is an inherently nonselective detection technique. This approach necessitates the use of complex and performance-limiting modifications to ensure the desired single-analyte specificity. Here, we present a novel glutamate microbiosensor fabricated on a carbon-fiber microelectrode substrate and coupled with fast-scan cyclic voltammetry (FSCV) to enable the simultaneous quantification of glutamate and DA at single recording sites in the brain, which is impossible when using typical amperometric approaches. The glutamate microbiosensors were characterized for sensitivity, stability, and selectivity by using a voltammetric waveform optimized for the simultaneous detection of both species. The applicability of these sensors for the investigation of neural circuits was validated in the rat ventral striatum. Electrically evoked glutamate and DA release were recorded at single-micrometer-scale locations before and after pharmacological manipulation of glutamatergic signaling. Our novel glutamate microbiosensor advances the state of the art by providing a powerful tool for probing coordination between these two species in a way that has previously not been possible.

Untapped Potential: Real-Time Measurements of Opioid Exocytosis at Single Cells.

The endogenous opioid system is commonly targeted in pain treatment, but the fundamental nature of neuropeptide release remains poorly understood due to a lack of methods for direct detection of specific opioid neuropeptides in situ. These peptides are concentrated in, and released from, large dense-core vesicles in chromaffin cells. Although catecholamine release from these neuroendocrine cells is well characterized, the direct quantification of opioid peptide exocytosis events has not previously been achieved. In this work, a planar carbon-fiber microelectrode served as a "postsynaptic" sensor for probing catecholamine and neuropeptide release dynamics via amperometric monitoring. A constant potential of 500 mV was employed for quantification of catecholamine release, and a higher potential of 1000 mV was used to drive oxidation of tyrosine, the N-terminal amino acid in the opioid neuropeptides released from chromaffin cells. By discriminating the results collected at the two potentials, the data reveal unique kinetics for these two neurochemical classes at the single-vesicle level. The amplitude of the peptidergic signals decreased with repeat stimulation, as the halfwidth of these signals simultaneously increased. By contrast, the amplitude of catecholamine release events increased with repeat stimulation, but the halfwidth of each event did not vary. The chromogranin dense core was identified as an important mechanistic handle by which separate classes of transmitter can be kinetically modulated when released from the same population of vesicles. Overall, the data provide unprecedented insight into key differences between catecholamine and opioid neuropeptide release from isolated chromaffin cells.

Exploiting Microelectrode Geometry for Comprehensive Detection of Individual Exocytosis Events at Single Cells.

Carbon fiber microelectrodes are commonly used for real-time monitoring of individual exocytosis events at single cells. Since the nature of an electrochemical signal is fundamentally governed by mass transport to the electrode surface, microelectrode geometry can be exploited to achieve precise and accurate measurements. Researchers traditionally pair amperometric measurements of exocytosis with a ∼10-µm diameter, disk microelectrode in an "artificial synapse" configuration to directly monitor individual release events from single cells. Exocytosis is triggered, and released molecules diffuse to the "post-synaptic" electrode for oxidation. This results in a series of distinct current spikes corresponding to individual exocytosis events. However, it remains unclear how much of the material escapes detection. In this work, the performance of 10- and 34-µm diameter carbon fiber disk microelectrodes was directly compared in monitoring exocytosis at single chromaffin cells. The 34-µm diameter electrode was more sensitive to catecholamines and enkephalins than its traditional, 10-µm diameter counterpart, and it more effectively covered the entire cell. As such, the larger sensor detected more exocytosis events overall, as well as a larger quantal size, suggesting that the traditional tools underestimate the above measurements. Both sensors reliably measured l-DOPA-evoked changes in quantal size, and both exhibited diffusional loss upon adjustment of cell-electrode spacing. Finite element simulations using COMSOL support the improved collection efficiency observed using the larger sensor. Overall, this work demonstrates how electrode geometry can be exploited for improved detection of exocytosis events by addressing diffusional loss─an often-overlooked source of inaccuracy in single-cell measurements.

Neurotransmitter Readily Escapes Detection at the Opposing Microelectrode Surface in Typical Amperometric Measurements of Exocytosis at Single Cells.

For decades, carbon-fiber microelectrodes have been used in amperometric measurements of neurotransmitter release at a wide variety of cell types, providing a tremendous amount of valuable information on the mechanisms involved in dense-core vesicle fusion. The electroactive molecules that are released can be detected at the opposing microelectrode surface, allowing for precise quantification as well as detailed kinetic information on the stages of neurotransmitter release. However, it remains unclear how much of the catecholamine that is released into the artificial synapse escapes detection. This work examines two separate mechanisms by which released neurotransmitter goes undetected in a typical amperometric measurement. First, diffusional loss is assessed by monitoring exocytosis at single bovine chromaffin cells using carbon-fiber microelectrodes fabricated in a recessed (cavity) geometry. This creates a microsampling vial that minimizes diffusional loss of analyte prior to detection. More molecules were detected per exocytotic release event when using a recessed cavity sensor as compared to the conventional configuration. In addition, pharmacological inhibition of the norepinephrine transporter (NET), which serves to remove catecholamine from the extracellular space, increased both the size and the time course of individual amperometric events. Overall, this study characterizes distinct physical and biological mechanisms by which released neurotransmitter escapes detection at the opposing microelectrode surface, while also revealing an important role for the NET in "presynaptic" modulation of neurotransmitter release.

Interpreting Dynamic Interfacial Changes at Carbon Fiber Microelectrodes Using Electrochemical Impedance Spectroscopy.

Carbon-fiber microelectrodes are instrumental tools in neuroscience used for the electroanalysis of neurochemical dynamics and recordings of neural activity. However, performance is variable and dependent on fabrication strategies, the biological response to implantation, and the physical and chemical composition of the recording environment. This presents an analytical challenge, as electrode performance is difficult to quantitatively assess in situ, especially when electrodes are permanently implanted or cemented in place. We previously reported that electrode impedance directly impacts electrochemical performance for molecular sensing. In this work, we investigate the impacts of individual components of the electrochemical system on impedance. Equivalent circuit models for glass- and silica-insulated carbon-fiber microelectrodes were determined using electrochemical impedance spectroscopy (EIS). The models were validated based on the ability to assign individual circuit elements to physical properties of the electrochemical system. Investigations were performed to evaluate the utility of the models in providing feedback on how changes in ionic strength and carbon fiber material alter impedance properties. Finally, EIS measurements were used to investigate the electrode/solution interface prior to, during, and following implantation in live brain tissue. A significant increase in impedance and decrease in capacitance occur during tissue exposure and persist following implantation. Electrochemical conditioning, which occurs continually during fast-scan cyclic voltammetry recordings, etches and renews the carbon surface, mitigating these effects. Overall, the results establish EIS as a powerful method for characterization of carbon-fiber microelectrodes, providing unprecedented insight into how real-world factors affect the electrode/solution interface.

Carbon-Fiber Nanoelectrodes for Real-Time Discrimination of Vesicle Cargo in the Native Cellular Environment.

Carbon-fiber microelectrodes have proven to be an indispensable tool for monitoring exocytosis events using amperometry. When positioned adjacent to a cell, a traditional microdisc electrode is well suited for quantification of discrete exocytotic release events. However, the size of the electrode does not allow for intracellular electrochemical measurements, and the amperometric approach cannot distinguish between the catecholamines that are released. In this work, carbon nanoelectrodes were developed to permit selective electrochemical sampling of nanoscale vesicles in the cell cytosol. Classical voltammetric techniques and electron microscopy were used to characterize the nanoelectrodes, which were ∼5 µm long and sharpened to a nanometer-scale tip that could be wholly inserted into individual neuroendocrine cells. The nanoelectrodes were coupled with fast-scan cyclic voltammetry to distinguish secretory granules containing epinephrine from other catecholamine-containing granules encountered in the native cellular environment. Both vesicle subtypes were encountered in most cells, despite prior demonstration of populations of chromaffin cells that preferentially release one of these catecholamines. There was substantial cell-to-cell variability in relative epinephrine content, and vesicles containing epinephrine generally stored more catecholamine than the other vesicles. The carbon nanoelectrode technology thus enabled analysis of picoliter-scale biological volumes, revealing key differences between chromaffin cells at the level of the dense-core granule.

Drift Subtraction for Fast-Scan Cyclic Voltammetry Using Double-Waveform Partial-Least-Squares Regression.

Background-subtracted fast-scan cyclic voltammetry (FSCV) provides a method for detecting molecular fluctuations with high spatiotemporal resolution in the brain of awake and behaving animals. The rapid scan rates generate large background currents that are subtracted to reveal changes in analyte concentration. Although these background currents are relatively stable, small changes do occur over time. These changes, referred to as electrochemical drift, result in background-subtraction artifacts that constrain the utility of FSCV, particularly when quantifying chemical changes that gradually occur over long measurement times (minutes). The voltammetric features of electrochemical drift are varied and can span the entire potential window, potentially obscuring the signal from any targeted analyte. We present a straightforward method for extending the duration of a single FSCV recording window. First, we have implemented voltammetric waveforms in pairs that consist of a smaller triangular sweep followed by a conventional voltammetric scan. The initial, abbreviated waveform is used to capture drift information that can serve as a predictor for the contribution of electrochemical drift to the subsequent full voltammetric scan using partial-least-squares regression (PLSR). This double-waveform partial-least-squares regression (DW-PLSR) paradigm permits reliable subtraction of the drift component to the voltammetric data. Here, DW-PLSR is used to improve quantification of adenosine, dopamine, and hydrogen peroxide fluctuations occurring >10 min from the initial background position, both in vitro and in vivo. The results demonstrate that DW-PLSR is a powerful tool for evaluating and interpreting both rapid (seconds) and gradual (minutes) chemical changes captured in FSCV recordings over extended durations.

Carbon-Fiber Microbiosensor for Monitoring Rapid Lactate Fluctuations in Brain Tissue Using Fast-Scan Cyclic Voltammetry.

Recent studies have described a role for lactate in brain energy metabolism and energy formation, challenging the conventional view that glucose is the principle energy source for brain function. To date, lactate dynamics in the brain are largely unknown, limiting insight into function. We addressed this by developing and characterizing a lactate oxidase-modified carbon-fiber microelectrode coupled with fast-scan cyclic voltammetry. This new tool boasts a sensitivity for lactate of 22 ± 1 nA·mM-1 and LOD of 7.0 ± 0.7 µM. The approach has enabled detection of rapid lactate fluctuations with unprecedented spatiotemporal resolution as well as excellent stability, selectivity, and sensitivity. The technology was characterized both in vitro and in vivo at discrete recording sites in rat striatum. We provide evidence that striatal lactate availability increases biphasically in response to electrical stimulation of the dopaminergic midbrain in the anesthetized rat. This new tool for real-time detection of lactate dynamics promises to improve understanding of how lactate availability underscores neuronal function and dysfunction.

Quantitative Comparison of Enzyme Immobilization Strategies for Glucose Biosensing in Real-Time Using Fast-Scan Cyclic Voltammetry Coupled with Carbon-Fiber Microelectrodes.

Electrochemical monitoring of non-electroactive species requires a biosensor that is stable and selective, with sensitivity to physiological concentrations of targeted analytes. We have combined glucose oxidase-modified carbon-fiber microelectrodes with fast-scan cyclic voltammetry for real-time measurements of glucose fluctuations in brain tissue. Work presented herein quantitatively compares three approaches to enzyme immobilization on the microelectrode surface-physical adsorption, hydrogel entrapment, and entrapment in electrospun nanofibers. The data suggest that each of these methods can be used to create functional microbiosensors. Immobilization of glucose oxidase by physical adsorption generates a biosensor with poor sensitivity to glucose and unstable performance. Entrapment of glucose oxidase in poly(vinyl alcohol) nanofibers generates microbiosensors that are effective for glucose measurements over a large linear range, and that may be particularly useful when targeting glucose concentrations in excess of 3 mm, such as in blood. Hydrogel entrapment is the most effective in terms of sensitivity and stability. These microbiosensors can be used for simultaneous monitoring of glucose and dopamine in real time. The findings outlined herein should be applicable to other oxidase enzymes, and thus they are broadly important for the development of new tools for real-time measurements of fluctuating molecules that are not inherently electroactive.

Electrochemical Selectivity Achieved Using a Double Voltammetric Waveform and Partial Least Squares Regression: Differentiating Endogenous Hydrogen Peroxide Fluctuations from Shifts in pH.

Hydrogen peroxide (H2O2) is a reactive oxygen species that serves as an important signaling molecule in normal brain function. At the same time, excessive H2O2 concentrations contribute to myriad pathological consequences resulting from oxidative stress. Studies to elucidate the diverse roles that H2O2 plays in complex biological environments have been hindered by the lack of robust methods for probing dynamic H2O2 fluctuations in living systems with molecular specificity. Background-subtracted fast-scan cyclic voltammetry at carbon-fiber microelectrodes provides a method of detecting rapid H2O2 fluctuations with high temporal and spatial resolution in brain tissue. However, H2O2 fluctuations can be masked by local changes in pH (ΔpH), because the voltammograms for these species can have significant peak overlap, hindering quantification. We present a method for removing ΔpH-related contributions from complex voltammetric data. By employing two distinct potential waveforms per scan, one in which H2O2 is electrochemically silent and a second in which both ΔpH and H2O2 are redox active, a clear distinction between H2O2 and ΔpH signals is established. A partial least-squares regression (PLSR) model is used to predict the ΔpH signal and subtract it from the voltammetric data. The model has been validated both in vitro and in vivo using k-fold cross-validation. The data demonstrate that the double waveform PLSR model is a powerful tool that can be used to disambiguate and evaluate naturally occurring H2O2 fluctuations in vivo.

Spectroelectrochemical Characterization of the Dynamic Carbon-Fiber Surface in Response to Electrochemical Conditioning.

The effects of electrochemical preconditioning of P-55 pitch-based carbon-fiber microelectrodes were quantitatively examined in this study. Microstructural characterization of the electrode surface was done using Raman spectroscopy and scanning electron microscopy. Electrochemical performance was evaluated using cyclic voltammetry. The data show that application of positive potentials provides beneficial structural modifications to the electrode surface. Electrodes that were preconditioned using a static potential of +1.0 V exhibited enhanced sensitivity and electron transfer properties when compared to electrodes conditioned for the same amount of time with dynamic (triangular) waveforms reaching +1.0 V. Conditioning elicited microstructural changes to the electrode surface that were dependent on the amount of time spent at potentials greater than ∼1.0 V. Importantly, the data demonstrate that the carbon-fiber microstructure is dynamic. It is able to quickly and continuously undergo rapid structural reorganization as potential is applied, repeatedly alternating between a relatively ordered state and one that exhibits greater disorder in response to applied electrochemical potentials that span the range commonly used in voltammetric experiments.

Background Signal as an in Situ Predictor of Dopamine Oxidation Potential: Improving Interpretation of Fast-Scan Cyclic Voltammetry Data.

Background-subtracted fast-scan cyclic voltammetry (FSCV) has emerged as a powerful analytical technique for monitoring subsecond molecular fluctuations in live brain tissue. Despite increasing utilization of FSCV, efforts to improve the accuracy of quantification have been limited due to the complexity of the technique and the dynamic recording environment. It is clear that variable electrode performance renders calibration necessary for accurate quantification; however, the nature of in vivo measurements can make conventional postcalibration difficult, or even impossible. Analyte-specific voltammograms and scaling factors that are critical for quantification can shift or fluctuate in vivo. This is largely due to impedance changes, and the effects of impedance on these measurements have not been characterized. We have previously reported that the background current can be used to predict electrode-specific scaling factors in situ. In this work, we employ model circuits to investigate the impact of impedance on FSCV measurements. Additionally, we take another step toward in situ electrode calibration by using the oxidation potential of quinones on the electrode surface to accurately predict the oxidation potential for dopamine at any point in an electrochemical experiment, as both are dependent on impedance. The model, validated both in adrenal slice and live brain tissue, enables information encoded in the shape of the background voltammogram to determine electrochemical parameters that are critical for accurate quantification. This improves data interpretation and provides a significant next step toward more automated methods for in vivo data analysis.

Simultaneous Voltammetric Measurements of Glucose and Dopamine Demonstrate the Coupling of Glucose Availability with Increased Metabolic Demand in the Rat Striatum.

Cerebral blood flow ensures delivery of nutrients, such as glucose, to brain sites with increased metabolic demand. However, little is known about rapid glucose dynamics at discrete locations during neuronal activation in vivo. Acute exposure to many substances of abuse elicits dopamine release and neuronal activation in the striatum; however, the concomitant changes in striatal glucose remain largely unknown. Recent developments have combined fast-scan cyclic voltammetry with glucose oxidase enzyme modified carbon-fiber microelectrodes to enable the measurement of glucose dynamics with subsecond temporal resolution in the mammalian brain. This work evaluates several waveforms to enable the first simultaneous detection of endogenous glucose and dopamine at single recording sites. These molecules, one electroactive and one nonelectroactive, were found to fluctuate in the dorsal striatum in response to electrical stimulation of the midbrain and systemic infusion of cocaine/raclopride. The data reveal the second-by-second dynamics of these species in a striatal microenvironment, and directly demonstrate the coupling of glucose availability with increased metabolic demand. This work provides a foundation that will enable detailed investigation of local mechanisms that regulate the coupling of cerebral blood flow with metabolic demand under normal conditions, and in animal studies of drug abuse and addiction.

Design and characterization of a microfabricated hydrogen clearance blood flow sensor.

BACKGROUND: Modern cerebral blood flow (CBF) detection favors the use of either optical technologies that are limited to cortical brain regions, or expensive magnetic resonance. Decades ago, inhalation gas clearance was the choice method of quantifying CBF, but this suffered from poor temporal resolution. Electrolytic H2 clearance (EHC) generates and collects gas in situ at an electrode pair, which improves temporal resolution, but the probe size has prohibited meaningful subcortical use. NEW METHOD: We microfabricated EHC electrodes to an order of magnitude smaller than those existing, on the scale of 100µm, to permit use deep within the brain. RESULTS: Novel EHC probes were fabricated. The devices offered exceptional signal-to-noise, achieved high collection efficiencies (40-50%) in vitro, and agreed with theoretical modeling. An in vitro chemical reaction model was used to confirm that our devices detected flow rates higher than those expected physiologically. Computational modeling that incorporated realistic noise levels demonstrated devices would be sensitive to physiological CBF rates. COMPARISON WITH EXISTING METHOD: The reduced size of our arrays makes them suitable for subcortical EHC measurements, as opposed to the larger, existing EHC electrodes that would cause substantial tissue damage. Our array can collect multiple CBF measurements per minute, and can thus resolve physiological changes occurring on a shorter timescale than existing gas clearance measurements. CONCLUSION: We present and characterize microfabricated EHC electrodes and an accompanying theoretical model to interpret acquired data. Microfabrication allows for the high-throughput production of reproducible devices that are capable of monitoring deep brain CBF with sub-minute resolution.

Microfabricated Collector-Generator Electrode Sensor for Measuring Absolute pH and Oxygen Concentrations.

Fast-scan cyclic voltammetry (FSCV) has attracted attention for studying in vivo neurotransmission due to its subsecond temporal resolution, selectivity, and sensitivity. Traditional FSCV measurements use background subtraction to isolate changes in the local electrochemical environment, providing detailed information on fluctuations in the concentration of electroactive species. This background subtraction removes information about constant or slowly changing concentrations. However, determination of background concentrations is still important for understanding functioning brain tissue. For example, neural activity is known to consume oxygen and produce carbon dioxide which affects local levels of oxygen and pH. Here, we present a microfabricated microelectrode array which uses FSCV to detect the absolute levels of oxygen and pH in vitro. The sensor is a collector-generator electrode array with carbon microelectrodes spaced 5 µm apart. In this work, a periodic potential step is applied at the generator producing transient local changes in the electrochemical environment. The collector electrode continuously performs FSCV enabling these induced changes in concentration to be recorded with the sensitivity and selectivity of FSCV. A negative potential step applied at the generator produces a transient local pH shift at the collector. The generator-induced pH signal is detected using FSCV at the collector and correlated to absolute solution pH by postcalibration of the anodic peak position. In addition, in oxygenated solutions a negative potential step at the generator produces hydrogen peroxide by reducing oxygen. Hydrogen peroxide is detected with FSCV at the collector electrode, and the magnitude of the oxidative peak is proportional to absolute oxygen concentrations. Oxygen interference on the pH signal is minimal and can be accounted for with a postcalibration.

Multiple scan rate voltammetry for selective quantification of real-time enkephalin dynamics.

Methionine-enkephalin (M-ENK) and leucine-enkephalin (L-ENK) are small endogenous opioid peptides that have been implicated in a wide variety of complex physiological functions, including nociception, reward processing, and motivation. However, our understanding of the role that these molecules play in modulating specific brain circuits remains limited, largely due to challenges in determining where, when, and how specific neuropeptides are released in tissue. Background-subtracted fast-scan cyclic voltammetry coupled with carbon-fiber microelectrodes has proven to be sensitive and selective for detecting rapidly fluctuating neurochemicals in vivo; however, many challenges exist for applying this approach to the detection of neuropeptides. We have developed and characterized a novel voltammetric waveform for the selective quantification of small tyrosine-containing peptides, such as the ENKs, with rapid temporal (subsecond) and precise spatial (10s of micrometers) resolution. We have established that the main contributor to the electrochemical signal inherent to M-ENK is tyrosine and that conventional waveforms provide poor peak resolution and lead to fouling of the electrode surface. By employing two distinct scan rates in each anodic sweep of this analyte-specific waveform, we have selectively distinguished M-ENK from common endogenous interfering agents, such as ascorbic acid, pH shifts, and even L-ENK. Finally, we have used this approach to simultaneously quantify catecholamine and M-ENK fluctuations in live tissue. This work provides a foundation for real-time measurements of endogenous ENK fluctuations in biological locations, and the underlying concept of using multiple scan rates is adaptable to the voltammetric detection of other tyrosine-containing neuropeptides.

In situ electrode calibration strategy for voltammetric measurements in vivo.

Technological advances have allowed background-subtracted fast-scan cyclic voltammetry to emerge as a powerful tool for monitoring molecular fluctuations in living brain tissue; however, there has been little progress to date in advancing electrode calibration procedures. Variability in the performance of these handmade electrodes renders calibration necessary for accurate quantification; however, experimental protocol makes standard postcalibration difficult or in some cases impossible. We have developed a model that utilizes information contained in the background charging current to predict electrode sensitivity to dopamine, ascorbic acid, hydrogen peroxide, and pH shifts at any point in an electrochemical experiment. Analysis determined a high correlation between predicted sensitivity and values obtained using the traditional postcalibration method, across all analytes. To validate this approach in vivo, calibration factors obtained with this model at electrodes in brain tissue were compared to values obtained at these electrodes using a traditional ex vivo calibration. Both demonstrated equal power of predictability for dopamine concentrations. This advance enables in situ electrode calibration, allowing researchers to track changes in electrode sensitivity over time and eliminating the need to generalize calibration factors between electrodes or across multiple days in an experiment.

Microfabricated Microelectrode Sensor for Measuring Background and Slowly Changing Dopamine Concentrations.

The electrochemical detection of neurotransmitters in vivo has centered on fast scan cyclic voltammetry (FSCV) due to its temporal resolution, sensitivity and chemical selectivity. FSCV is a differential technique that records phasic (second-to-second) changes in the concentration of electroactive neurotransmitters such as dopamine (DA). To isolate the currents due to fluctuations in analyte concentration, in other words to make these phasic measurements, requires the subtraction of a large background current. The subtraction of this background and its volatility renders FSCV unable to determine background or slowly varying concentrations of electroactive analytes. However, there is still a need to readily determine the background and slowly changing concentrations of electroactive analytes in tissue. For example, the background concentrations of DA vary throughout the brain and can affect the dynamics of dopaminergic systems. So, this report presents a microfabricated electrochemical sensor for measuring background and slowly changing concentrations of DA in vitro with the selectivity and sensitivity of FSCV. The sensor is comprised of two microfabricated microelectrodes which are spaced 8 µm apart. Varying the applied potential of the outer electrode manipulates the local concentration of electroactive species including concentration at the inner electrode. These changes are measured at the inner electrode using FSCV. The resulting signal with calibration can determine the background and slowly changing concentration of DA with the selectivity and sensitivity of FSCV. In this study the background of DA is determined in vitro using this sensor. The DA signal is shown to be the result of adsorption/desorption at the outer electrode. Interference from ascorbate on the DA signal is shown to be minimal for this approach.