James G. Roberts

Voltammetric Detection of Hydrogen Peroxide at Carbon Fiber Microelectrodes

Hydrogen peroxide is a reactive oxygen species that is implicated in a number of neurological disease states and that serves a critical role in normal cell function. It is commonly exploited as a reporter molecule enabling the electrochemical detection of nonelectroactive molecules at electrodes modified with substrate-specific oxidative enzymes. We present the first voltammetric characterization of rapid hydrogen peroxide fluctuations at an uncoated carbon fiber microelectrode, demonstrating unprecedented chemical and spatial resolution. The carbon surface was electrochemically conditioned on the anodic scan and the irreversible oxidation of peroxide was detected on the cathodic scan. The oxidation potential was dependent on scan rate, occurring at +1.2 V versus Ag/AgCl at a scan rate of 400 V.s(-1). The relationship between peak oxidation current and concentration was linear across the physiological range tested, with deviation from linearity above 2 mM and a detection limit of 2 muM. Peroxide was distinguished from multiple interferents, both in vitro and in brain slices. The enzymatic degradation of peroxide was monitored, as was peroxide evolution in response to glucose at a glucose oxidase modified carbon fiber electrode. This novel approach provides the requisite sensitivity, selectivity, spatial and temporal resolution to study dynamic peroxide fluctuations in discrete biological locations.

Specific Oxygen-Containing Functional Groups on the Carbon Surface Underlie an Enhanced Sensitivity to Dopamine at Electrochemically Pretreated Carbon Fiber Microelectrodes

The in vivo use of carbon-fiber microelectrodes for neurochemical investigation has proven to be selective and sensitive when coupled with background-subtracted fast-scan cyclic voltammetry (FSCV). Various electrochemical pretreatments have been established to enhance the sensitivity of these sensors; however, the fundamental chemical mechanisms underlying these enhancement strategies remain poorly understood. We have investigated an electrochemical pretreatment in which an extended triangular waveform from -0.5 to 1.8 V is applied to the electrode prior to the voltammetric detection of dopamine using a more standard waveform ranging from -0.4 to 1.3 V. This pretreatment enhances the electron-transfer kinetics and significantly improves sensitivity. To gain insight into the chemical mechanism, the electrodes were studied using common analytical techniques. Contact atomic force microscopy (AFM) was used to demonstrate that the surface roughness was not altered on the nanoscale by electrochemical pretreatment. Raman spectroscopy was utilized to investigate oxide functionalities on the carbon surface and confirmed that carbonyl and hydroxyl functional groups were increased by electrochemical conditioning. Spectra collected after the selective chemical modification of these groups implicate the hydroxyl functionality, rather than the carbonyl, as the major contributor to the enhanced electrochemical signal. Finally, we have demonstrated that this electrochemical pretreatment can be used to create carbon microdisc electrodes with sensitivities comparable to those associated with larger, conventionally treated cylindrical carbon fiber microelectrodes.

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.

Enzyme-Modified Carbon-Fiber Microelectrode for the Quantification of Dynamic Fluctuations of Nonelectroactive Analytes Using Fast-Scan Cyclic Voltammetry

Neurotransmission occurs on a millisecond time scale, but conventional methods for monitoring nonelectroactive neurochemicals are limited by slow sampling rates. Despite a significant global market, a sensor capable of measuring the dynamics of rapidly fluctuating, nonelectroactive molecules at a single recording site with high sensitivity, electrochemical selectivity, and a subsecond response time is still lacking. To address this need, we have enabled the real-time detection of dynamic glucose fluctuations in live brain tissue using background-subtracted, fast-scan cyclic voltammetry. The novel microbiosensor consists of a simple carbon fiber surface modified with an electrodeposited chitosan hydrogel encapsulating glucose oxidase. The selectivity afforded by voltammetry enables quantitative and qualitative measurements of enzymatically generated H2O2 without the need for additional strategies to eliminate interfering agents. The microbiosensors possess a sensitivity and limit of detection for glucose of 19.4 ± 0.2 nA mM(-1) and 13.1 ± 0.7 μM, respectively. They are stable, even under deviations from physiological normoxic conditions, and show minimal interference from endogenous electroactive substances. Using this approach, we have quantitatively and selectively monitored pharmacologically evoked glucose fluctuations with unprecedented chemical and spatial resolution. Furthermore, this novel biosensing strategy is widely applicable to the immobilization of any H2O2 producing enzyme, enabling rapid monitoring of many nonelectroactive enzyme substrates.

The Hydroxyl Radical is a Critical Intermediate in the Voltammetric Detection of Hydrogen Peroxide

Cyclic voltammetry is a widely used and powerful tool for sensitively and selectively measuring hydrogen peroxide (H2O2). Herein, voltammetry was combined with electron paramagnetic resonance spectroscopy to identify and define the role of an oxygen-centered radical liberated during the oxidation of H2O2. The spin-trap reagents, 5,5-dimethyl-1-pyrroline N-oxide (DMPO) and 2-ethoxycarbonyl-2-methyl-3,4-dihydro-2H-pyrrole-1-oxide (EMPO), were employed. Spectra exhibit distinct hyperfine patterns that clearly identify the DMPO(•)-OH and EMPO(•)-OH adducts. Multiple linear regression analysis of voltammograms demonstrated that the hydroxyl radical is a principal contributor to the voltammetry of H2O2, as signal is attenuated when this species is trapped. These data incorporate a missing, fundamental element to our knowledge of the mechanisms that underlie H2O2 electrochemistry.

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.

Real-Time Chemical Measurements of Dopamine Release in the Brain

Rapid changes in extracellular dopamine concentrations in freely moving or anesthetized rats can be detected using fast-scan cyclic voltammetry (FSCV). Background-subtracted FSCV is a real-time electrochemical technique that can monitor neurochemical transmission in the brain on a subsecond timescale, while providing chemical information on the analyte. Also, this voltammetric approach allows for the investigation of the kinetics of release and uptake of molecules in the brain. This chapter describes, completely, how to make these measurements and the properties of FSCV that make it uniquely suitable for performing chemical measurements of dopaminergic neurotransmission in vivo.

Reducing the Sampling Rate of Biochemical Measurements Using Fast-Scan Cyclic Voltammetry for In Vivo Applications

Recent advances in science and technology have permitted the development of wireless systems that can make biochemical measurements within functioning tissue in behaving animals. However, data transfer requirements and power limitations have significantly limited the applicability of these systems. In an effort to create protocols that will reduce the density of the data to be transferred and the power consumption of wireless systems, this paper evaluates reducing the sampling rate of a proven in vivo measurement technology, fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes. Existing FSCV protocols to measure biochemical signaling in the brain were created without consideration for data density or power consumption. In this paper, the sampling rate of the FSCV protocol for detecting the neurotransmitter dopamine in functioning brain tissue was reduced from 10 to 1 Hz. In vitro experiments showed that the 1-Hz protocol did not negatively affect sensor responsivity or selectivity. The reduced sampling rate was verified in vivo by directly monitoring dopamine fluctuations in intact brain tissue. The 1-Hz sampling rate reduces the quantity of data generated by an order of magnitude compared with the existing protocol, and with duty cycling is expected to decrease power consumption by a similar value in wireless systems.

Fast-Scan Cyclic Voltammetry: Chemical Sensing in the Brain and Beyond

In this review we describe the electroanalytical method known as fast-scan cyclic voltammetry (FSCV), how it has advanced over the years, and in what way(s) it is impacting other sciences. To begin, a brief history will be discussed. The various means to enhance chemical selectivity by manipulating the applied potential will be covered. Some limitations of this electroanalytical method will be highlighted to inform and provide clarity to the scientific community. The intent is to seek out effective solutions to the difficult problems associated with the technique, so that the field will continue to flourish. Rounding out the review, the utility and adaptability of this powerful bioanalytical technique will be addressed, as new frontiers of research are established for FSCV outside the scope of the neuroscience community.

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.