Fast Selective Detection of Pyocyanin Using Cyclic Voltammetry.
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ABSTRACT:
SUBMITTER: Alatraktchi FA
PROVIDER: S-EPMC4813983 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Fast-scan cyclic voltammetry (FSCV) is used with carbon-fiber microelectrodes for the real-time detection of neurotransmitters on the subsecond time scale. With FSCV, the potential is ramped up from a holding potential to a switching potential and back, usually at a 400 V s-1 scan rate and a frequency of 10 Hz. The plot of current vs. applied potential, the cyclic voltammogram (CV), has a very different shape for FSCV than for traditional cyclic voltammetry collected at scan rates which are 1000-fold slower. Here, we explore the theory of FSCV, with a focus on dopamine detection. First, we examine the shape of the CVs. Background currents, which are 100-fold higher than faradaic currents, are subtracted out. Peak separation is primarily due to slow electron transfer kinetics, while the symmetrical peak shape is due to exhaustive electrolysis of all the adsorbed neurotransmitters. Second, we explain the origins of the dopamine waveform, and the factors that limit the holding potential (oxygen reduction), switching potential (water oxidation), scan rate (electrode instability), and repetition rate (adsorption). Third, we discuss data analysis, from data visualization with color plots, to the automated algorithms like principal components regression that distinguish dopamine from pH changes. Finally, newer applications are discussed, including optimization of waveforms for analyte selectivity, carbon nanomaterial electrodes that trap dopamine, and basal level measurements that facilitate neurotransmitter measurements on a longer time scale. FSCV theory is complex, but understanding it enables better development of new techniques to monitor neurotransmitters in vivo.
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Project description:Carbon fiber microelectrodes (CFMEs) have been extensively used to measure neurotransmitters with fast-scan cyclic voltammetry (FSCV) due to their ability to adsorb cationic monoamine neurotransmitters. Although FSCV, in tandem with CFMEs, provides high temporal and spatial resolution, only single-channel potentiostats and electrodes have been primarily utilized. More recently, the need and use of carbon fiber multielectrode arrays has risen to target multiple brain regions. Previous studies have shown the ability to detect dopamine using multielectrode arrays; however, they are not readily available to the scientific community. In this work, we interfaced a carbon fiber multielectrode array (MEA or multielectrode array), to a commercially available four-channel potentiostat for multiplexing neurochemical measurements. The MEA's relative performance was compared to single CFMEs where dopamine detection was found to be adsorption controlled to the electrode's surface. Multiple waveforms were applied to each fiber of the multielectrode array simultaneously to detect different analytes on each electrode of the array. A proof of concept ex vivo experiment showed that the multielectrode array could record redox activity in different areas within the mouse caudate putamen and detect dopamine in a 3-mm2 area. To our knowledge, this is the first use of the multielectrode array paired with a commercially available multichannel potentiostat for multi-waveform application and neurotransmitter co-detection. This novel array may aid in future studies to better understand complex brain heterogeneity, the dynamic neurochemical environment, and how disease states or drugs affect separate brain areas concurrently. Graphical abstract.
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Project description:Although N-shaped fast scan cyclic voltammetry (N-FSCV) is well-established as an electroanalytical method to measure extracellular serotonin concentrations in vivo, it is in need of improvement in both sensitivity and selectivity. Based on our previous studies using fast cyclic square-wave voltammetry (FCSWV) for in vivo dopamine measurements, we have modified this technique to optimize the detection of serotonin in vivo. A series of large amplitude square-shaped potentials was superimposed onto an N-shaped waveform to provide cycling through multiple redox reactions within the N-shaped waveform to enhance the sensitivity and selectivity to serotonin measurement when combined with a two-dimensional voltammogram. N-Shaped fast cyclic square-wave voltammetry (N-FCSWV) showed significantly higher sensitivity to serotonin compared to conventional N-FSCV. In addition, N-FCSWV showed better performance than conventional N-shaped FSCV in differentiating serotonin from its major interferents, dopamine and 5-hydroxyindoleascetic acid (5-HIAA). It was also confirmed that the large amplitude of the square waveform did not influence local neuronal activity, and it could monitor electrical stimulation evoked phasic release of serotonin in the rat substantia nigra pars reticulata (SNr) before and after systemic injection of escitalopram (ESCIT, 10 mg/kg i.p.), a serotonin selective reuptake inhibitor.
| S-EPMC7478172 | biostudies-literature
Project description:Serotonin is a neuromodulator implicated in depression that is often measured in real-time by fast-scan cyclic voltammetry (FSCV). A specialized "Jackson" waveform (JW, 0.2, 1.0 V, -0.1 V, 0.2 V, 1000 V s-1) was developed to reduce serotonin fouling, but the 1.0 V switching potential limits sensitivity and electrodes still foul. The goal of this study was to test the effects of extending the FSCV switching potential to increase serotonin sensitivity and decrease fouling. We compared the Jackson waveform, the dopamine waveform (DA, -0.4 V, 1.3 V, 400 V s-1), and two new waveforms: the extended serotonin waveform (ESW, 0.2, 1.3, -0.1, 0.2, 1000 V s-1) and extended hold serotonin waveform (EHSW, 0.2, 1.3 (hold 1 ms), -0.1, 0.2, 400 V s-1). The EHSW was the most sensitive (LOD = 0.6 nM), and the JW the least sensitive (LOD = 2.4 nM). With the Jackson waveform, electrode fouling was significant with repeated injections of serotonin or exposure to its metabolite, 5-hydroxyindoleacetic acid (5-HIAA). Using the extended waveforms, electrodes fouled 50% less than with the Jackson waveform for both analytes. No electrode fouling was observed with the dopamine waveform because of the negative holding potential. The Jackson waveform was the most selective for serotonin over dopamine (800×), and the ESW was also highly selective. All waveforms were useful for measuring serotonin with optogenetic stimulation in Drosophila larvae. These results provide new FSCV waveforms to measure dynamic serotonin changes with different experimental requirements, like high sensitivity (EHSW), high selectivity (ESW, JW), or eliminating electrode fouling (DA).
| S-EPMC7655692 | biostudies-literature
Project description: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.
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Project description:Melatonin (MT) has been recently considered an excellent candidate for the treatment of sleep disorders, neural injuries, and neurological diseases. To better investigate the actions of MT in various brain functions, real-time detection of MT concentrations in specific brain regions is much desired. Previously, we have demonstrated detection of exogenously administered MT in anesthetized mouse brain using square wave voltammetry (SWV). Here, for the first time, we show successful detection of exogenous MT in the brain using fast scan cyclic voltammetry (FSCV) on electrochemically pre-activated carbon fiber microelectrodes (CFEs). In vitro evaluation showed the highest sensitivity (28.1 nA/?M) and lowest detection limit (20.2 ± 4.8 nM) ever reported for MT detection at carbon surface. Additionally, an extensive CFE stability and fouling assessment demonstrated that a prolonged CFE pre-conditioning stabilizes the background, in vitro and in vivo, and provides consistent CFE sensitivity over time even in the presence of a high MT concentration. Finally, the stable in vivo background, with minimized CFE fouling, allows us to achieve a drift-free FSCV detection of exogenous administered MT in mouse brain over a period of 3 min, which is significantly longer than the duration limit (usually < 90 s) for traditional in vivo FSCV acquisition. The MT concentration and dynamics measured by FSCV are in good agreement with SWV, while microdialysis further validated the concentration range. These results demonstrated reliable MT detection using FSCV that has the potential to monitor MT in the brain over long periods of time.
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Project description:Due to its high spatiotemporal resolution, fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes enables the localized in vivo monitoring of subsecond fluctuations in electroactive neurotransmitter concentrations. In practice, resolution of the analytical signal relies on digital background subtraction for removal of the large current due to charging of the electrical double layer as well as surface faradaic reactions. However, fluctuations in this background current often occur with changes in the electrode state or ionic environment, leading to nonspecific contributions to the FSCV data that confound data analysis. Here, we both explore the origin of such shifts seen with local changes in cations and develop a model to account for their shape. Further, we describe a convolution-based method for removal of the differential capacitive contributions to the FSCV current. The method relies on the use of a small-amplitude pulse made prior to the FSCV sweep that probes the impedance of the system. To predict the nonfaradaic current response to the voltammetric sweep, the step current response is differentiated to provide an estimate of the system's impulse response function and is used to convolute the applied waveform. The generated prediction is then subtracted from the observed current to the voltammetric sweep, removing artifacts associated with electrode impedance changes. The technique is demonstrated to remove select contributions from capacitive characteristics changes of the electrode both in vitro (i.e., in flow-injection analysis) and in vivo (i.e., during a spreading depression event in an anesthetized rat).
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Project description:Fast-scan cyclic voltammetry (FSCV) is widely used for in vivo detection of neurotransmitters, but identifying analytes, particularly mixtures, is difficult. Data analysis has focused on identifying dopamine from cyclic voltammograms, but it would be better to analyze all the data in the three-dimensional FSCV color plot. Here, the goal was to use image analysis-based analysis of FSCV color plots for the first time, specifically the structural similarity index (SSIM), to identify rapid neurochemical events. Initially, we focused on identifying spontaneous adenosine events, as adenosine cyclic voltammograms have a primary oxidation at 1.3 V and a secondary oxidation peak that grows in over time. Using SSIM, sample FSCV color plots were compared with reference color plots, and the SSIM cutoff score was optimized to distinguish adenosine. High-pass digital filtering was also applied to remove the background drift and lower the noise, which produced a better LOD. The SSIM algorithm detected more adenosine events than a previous algorithm based on current versus time traces, with 99.5 ± 0.6% precision, 95 ± 3% recall, and 97 ± 2% F1 score (n = 15 experiments from three researchers). For selectivity, it successfully rejected signals from pH changes, histamine, and H2O2. To prove it is a broad strategy useful beyond adenosine, SSIM analysis was optimized for dopamine detection and is able to detect simultaneous events with dopamine and adenosine. Thus, SSIM is a general strategy for FSCV data analysis that uses three-dimensional data to detect multiple analytes in an efficient, automated analysis.
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Project description:Octopamine is an endogenous biogenic amine neurotransmitter, neurohormone, and neuromodulator in invertebrates and has functional analogy with norepinephrine in vertebrates. Fast-scan cyclic voltammetry (FSCV) can detect rapid changes in neurotransmitters, but FSCV has not been optimized for octopamine detection in situ. The goal of this study was to characterize octopamine release in the ventral nerve cord of Drosophila larvae for the first time. A FSCV waveform was optimized so that the potential for octopamine oxidation would not be near the switching potential where interferences can occur. Endogenous octopamine release was stimulated by genetically inserting either the ATP sensitive channel, P2X2, or the red-light sensitive channelrhodopsin, CsChrimson, into cells expressing tyrosine decarboxylase (TDC), an octopamine synthesis enzyme. To ensure that release is due to octopamine and not the precursor tyramine, the octopamine synthesis inhibitor disulfiram was applied, and the signal decreased by 80%. Stimulated release was vesicular, and a 2 s continuous light stimulation of CsChrimson evoked 0.22 ± 0.03 μM of octopamine release in the larval ventral nerve cord. Repeated stimulations were stable with 2 or 5 min interstimulation times. With pulsed stimulations, the release was dependent on the frequency of applied light pulse. An octopamine transporter has not been identified, and blockers of the dopamine transporter and serotonin transporter had no significant effect on the clearance time of octopamine, suggesting that they do not take up octopamine. This study shows that octopamine can be monitored in Drosophila, facilitating future studies of how octopamine release functions in the insect brain.
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