Microdosing ketamine in Drosophila does not block serotonin reuptake, but causes complex behavioral changes mediated by glutamate and serotonin receptors.

Microdosing ketamine is a novel antidepressant for treatment-resistant depression. Traditional antidepressants, like selective serotonin reuptake inhibitors (SSRIs), inhibit serotonin reuptake, but it is not clear if ketamine shows a similar mechanism. Here, we tested the effects of feeding ketamine and SSRIs to Drosophila melanogaster larvae, which has a similar serotonin system to mammals and is a good model to track depressive behaviors, such as locomotion and feeding. Fast-scan cyclic voltammetry (FSCV) was used to measure optogenetically stimulated serotonin changes, and locomotion tracking software and blue dye feeding to monitor behavior. We fed larvae various doses (1-100 mM) of antidepressants for 24 h and found that 1 mM ketamine did not affect serotonin, but increased locomotion and feeding. Low doses (≤10 mM) of escitalopram and fluoxetine inhibited dSERT and also increased feeding and locomotion behaviors. At 100 mM, ketamine inhibited dSERT and increased serotonin concentrations, but decreased locomotion and feeding because of its anesthetic properties. Since microdosing ketamine causes behavioral effects, we further investigated behavioral changes with a SERT16 mutant and low doses of other NMDA receptor antagonists and 5-HT1A and 2 agonists. Feeding and locomotion changes were similar to ketamine in the mutant, and we found NMDA receptor antagonism increased feeding, while serotonin receptor agonism increased locomotion, which could explain these effects with ketamine. Ultimately, this work shows that Drosophila is a good model to discern antidepressant mechanisms, and that ketamine does not work on dSERT like SSRIs, but effects behavior with other mechanisms that should be investigated further.

Electrochemical treatment in KOH improves carbon nanomaterial performance to multiple neurochemicals.

Carbon-fiber microelectrodes (CFMEs) are primarily used to detect neurotransmitters in vivo with fast-scan cyclic voltammetry (FSCV) but other carbon nanomaterial electrodes are being developed. CFME sensitivity to dopamine is improved by applying a constant 1.5 V vs. Ag/AgCl for 3 minutes while dipped in 1 M KOH, which etches the surface and adds oxygen functional groups. However, KOH etching of other carbon nanomaterials and applications to other neurochemicals have not been investigated. Here, we explored KOH etching of CFMEs and carbon nanotube yarn microelectrodes (CNTYMEs) to characterize sensitivity to dopamine, epinephrine, norepinephrine, serotonin, and 3,4-dihydroxyphenylacetic acid (DOPAC). With CNTYMEs, the potential was applied in KOH for 1 minute because the electrode surface cracked with the longer time. KOH treatment increased electrode sensitivity to each cationic neurotransmitter roughly 2-fold for CFMEs, and 2- to 4-fold for CNTYMEs. KOH treatment decreased the background current of the CFMEs by etching the surface carbon; however, KOH-treatment increased the CNTYME background current because the potential separates individual nanotubes. For DOPAC, the current increase was smaller at CNTYMEs because it is anionic and was repelled by the negative holding potential and did not access the crevices. XPS and Raman spectroscopy showed that KOH treatment changed the CNTYME surface chemistry by increasing defect sites and adding oxide functional groups. KOH-treated CNTYMEs had less fouling to serotonin than normal CNTYMEs. Therefore, KOH treatment activates both CFMEs and CNTYMEs and could be used in biological measurements to increase the sensitivity and decrease fouling for neurochemical measurements.

Electrochemical and biosensor techniques to monitor neurotransmitter changes with depression.

Depression is a common mental illness. However, its current treatments, like selective serotonin reuptake inhibitors (SSRIs) and micro-dosing ketamine, are extremely variable between patients and not well understood. Three neurotransmitters: serotonin, histamine, and glutamate, have been proposed to be key mediators of depression. This review focuses on analytical methods to quantify these neurotransmitters to better understand neurological mechanisms of depression and how they are altered during treatment. To quantitatively measure serotonin and histamine, electrochemical techniques such as chronoamperometry and fast-scan cyclic voltammetry (FSCV) have been improved to study how specific molecular targets, like transporters and receptors, change with antidepressants and inflammation. Specifically, these studies show that different SSRIs have unique effects on serotonin reuptake and release. Histamine is normally elevated during stress, and a new inflammation hypothesis of depression links histamine and cytokine release. Electrochemical measurements revealed that stress increases histamine, decreases serotonin, and leads to changes in cytokines, like interleukin-6. Biosensors can also measure non-electroactive neurotransmitters, including glutamate and cytokines. In particular, new genetic sensors have shown how glutamate changes with chronic stress, as well as with ketamine treatment. These techniques have been used to characterize how ketamine changes glutamate and serotonin, and to understand how it is different from SSRIs. This review briefly outlines how these electrochemical techniques work, but primarily highlights how they have been used to understand the mechanisms of depression. Future studies should explore multiplexing techniques and personalized medicine using biomarkers in order to investigate multi-analyte changes to antidepressants.

3D-Printed Carbon Nanoneedle Electrodes for Dopamine Detection in Drosophila.

In vivo electrochemistry in small brain regions or synapses requires nanoelectrodes with long straight tips for submicron scale measurements. Nanoelectrodes can be fabricated using a Nanoscribe two-photon printer, but annealed tips curl if they are long and thin. We propose a new pulling-force strategy to fabricate a straight carbon nanoneedle structure. A micron-width bridge is printed between two blocks. The annealed structure shrinks during pyrolysis, and the blocks create a pulling force to form a long, thin, and straight carbon bridge. Parameterization study and COMSOL modeling indicate changes in the block size, bridge size and length affect the pulling force and bridge shrinkage. Electrodes were printed on niobium wires, insulated with aluminum oxide, and the bridge cut with focused ion beam (FIB) to expose the nanoneedle tip. Annealed needle diameters ranged from 400 nm to 5.25 µm and length varied from 50.5 µm to 146 µm. The electrochemical properties are similar to glassy carbon, with good performance for dopamine detection with fast-scan cyclic voltammetry. Nanoelectrodes enable biological applications, such as dopamine detection in a specific Drosophila brain region. Long and thin nanoneedles are generally useful for other applications such as cellular sensing, drug delivery, or gas sensing.

Carbon nanospikes have improved sensitivity and antifouling properties for adenosine, hydrogen peroxide, and histamine.

Carbon nanospikes (CNSs) are a new nanomaterial that has enhanced surface roughness and surface oxide concentration, increasing the sensitivity for dopamine detection. However, CNS-modified electrodes (CNSMEs) have not been characterized for other neurochemicals, particularly those with higher oxidation potentials. The purpose of this study was to evaluate CNSMEs for the detection of adenosine, hydrogen peroxide (H2O2), and histamine. The sensitivity increased with CNSs, and signals at CNSMEs were about 3.3 times higher than CFMEs. Normalizing for surface area differences using background currents, CNSMEs show an increased signal of 4.8 times for adenosine, 1.5 times for H2O2, and 2 times for histamine. CNSMEs promoted the formation of secondary products for adenosine and histamine, which enables differentiation from other analytes with similar oxidation potentials. CNSs also selectively enhance the sensitivity for adenosine and histamine compared to H2O2. A scan rate test reveals that adenosine is more adsorption-controlled at CNS electrodes than CFMEs. CNSMEs are antifouling for histamine, with less fouling because the polymers formed after histamine electrooxidation do not adsorb due to an elevated number of edge planes. CNSMEs were useful for detecting each analyte applied in brain slices. Because of the hydrophilic surface compared to CFMEs, CNSMEs also have reduced biofouling when used in tissue. Therefore, CNSMEs are useful for tissue measurements of adenosine, hydrogen peroxide, and histamine with high selectivity and low fouling.

SSRI antidepressants differentially modulate serotonin reuptake and release in Drosophila.

Selective serotonin reuptake inhibitor (SSRI) antidepressants are commonly prescribed treatments for depression, but their effects on serotonin reuptake and release are not well understood. Drosophila melanogaster, the fruit fly, expresses the serotonin transporter (dSERT), the major target of SSRIs, but real-time serotonin changes after SSRIs have not been characterized in this model. The goal of this study was to characterize effects of SSRIs on serotonin concentration and reuptake in Drosophila larvae. We applied various doses (0.1-100 µM) of fluoxetine (Prozac), escitalopram (Lexapro), citalopram (Celexa), and paroxetine (Paxil), to ventral nerve cord (VNC) tissue and measured optogenetically-stimulated serotonin release with fast-scan cyclic voltammetry (FSCV). Fluoxetine increased reuptake from 1 to 100 µM, but serotonin concentration only increased at 100 µM. Thus, fluoxetine occupies dSERT and slows clearance but does not affect concentration. Escitalopram and paroxetine increased serotonin concentrations at all doses, but escitalopram increased reuptake more. Citalopram showed lower concentration changes and faster reuptake profiles compared with escitalopram, so the racemic mixture of citalopram does not change reuptake as much as the S-isomer. Dose response curves were constructed to compare dSERT affinities and paroxetine showed the highest affinity and fluoxetine the lowest. These data demonstrate SSRI mechanisms are complex, with separate effects on reuptake or release. Furthermore, dynamic serotonin changes in Drosophila are similar to previous studies in mammals. This work establishes how antidepressants affect serotonin in real-time, which is useful for future studies that will investigate pharmacological effects of SSRIs with different genetic mutations in Drosophila.

Atomistic Simulations of Dopamine Diffusion Dynamics on a Pristine Graphene Surface.

Carbon microelectrodes enable in vivo detection of neurotransmitters, and new electrodes aim to optimize the carbon surface. However, atomistic detail on the diffusion and orientation of neurotransmitters near these surfaces is lacking. Here, we employ molecular dynamics simulations to investigate the surface diffusion of dopamine (DA), its oxidation product dopamine-o-quinone (DOQ), and their protonated forms on the pristine basal plane of flat graphene. We find that all DA species rapidly adsorb to the surface and remain adsorbed, even without a holding potential or graphene surface defects. We also find that the diffusivities of the adsorbed and the fully solvated DA are similar and that the protonated species diffuse more slowly on the surface than their corresponding neutral forms, while the oxidized species diffuse more rapidly. Structurally, we find that the underlying graphene lattice has little influence over the molecular adsorbate's lateral position, and the vertical placement of the amine group on dopamine is highly dependent upon its charge. Finally, we find that solvation has a large effect on surface diffusivities. These first results from molecular dynamics simulations of dopamine at the aqueous-graphene interface show that dopamine diffuses rapidly on the surface, even without an applied potential, and provide a basis for future simulations of neurotransmitter structure and dynamics on advanced carbon materials electrodes.

Carbon nanospike coated nanoelectrodes for measurements of neurotransmitters.

Carbon nanoelectrodes enable the detection of neurotransmitters at the level of single cells, vesicles, synapses and small brain structures. Previously, the etching of carbon fibers and 3D printing based on direct laser writing have been used to fabricate carbon nanoelectrodes, but these methods lack the ability of mass manufacturing. In this paper, we mass fabricate carbon nanoelectrodes by growing carbon nanospikes (CNSs) on metal wires. CNSs have a short, dense and defect-rich surface that produces remarkable electrochemical properties, and they can be mass fabricated on almost any substrate without using catalysts. Tungsten wires and niobium wires were electrochemically etched in batch to form sub micrometer sized tips, and a layer of CNSs was grown on the metal wires using plasma-enhanced chemical vapor deposition (PE-CVD). The thickness of the CNS layer was controlled by the deposition time, and a thin layer of CNSs can effectively cover the entire metal surface while maintaining the tip size within the sub micrometer scale. The etched tungsten wires produced tapered conical nanotips, while the etched niobium wires were long and thin. Both showed excellent sensitivity for the detection of outer sphere ruthenium hexamine and the inner sphere test compound ferricyanide. The CNS nanosensors were used for the measurement of dopamine, serotonin, ascorbic acid and DOPAC with fast-scan cyclic voltammetry. The CNS nanoelectrodes had a large surface area and numerous defect sites, which improved the sensitivity, electron transfer kinetics and adsorption. Finally, the CNS nanoelectrodes were compared with other nanoelectrode fabrication methods, including flame etching, 3D printing, and nanopipettes, which are slower to make and more difficult for mass fabrication. Thus, CNS nanoelectrodes are a promising strategy for the mass fabrication of nanoelectrode sensors for neurotransmitters.

Pannexin1 channels regulate mechanically stimulated but not spontaneous adenosine release.

Fast-scan cyclic voltammetry (FSCV) is a rapid technique to measure neuromodulators, and using FSCV, two modes of rapid adenosine have been discovered. Spontaneous transients occur randomly in the brain, while mechanical stimulation also causes a rapid adenosine event. Pannexin1 channels are membrane channels that transport ions, including ATP, out of the cell where it is rapidly broken down into adenosine. Pannexin 1 channels (Panx1) have a flickering mode of rapid opening and are also mechanically stimulated. Here, we test the extent to which pannexin channels, specifically pannexin1 (Panx1) channels, are responsible for rapid adenosine events. Spontaneous adenosine release or mechanosensitive adenosine release were measured using fast-scan cyclic voltammetry in hippocampal (CA1) brain slices. In global Panx1KO mice, there is no significant difference in the frequency or concentration of spontaneous adenosine release, indicating Panx1 is not a release mechanism for spontaneous adenosine. Spontaneous adenosine frequency decreased slightly after administration of a large (100 µM) dose of carbenoxolone, a nonspecific inhibitor of many pannexin and connexin channels, suggesting other hemichannels only play a small role at most. For mechanically stimulated adenosine release, the concentration of each adenosine event significantly decreased 30% in Panx1KO mice and the frequency of stimulations that evoked adenosine also decreased. The response was similar in WT mice with carbenoxolone. Thus, Panx1 is a release mechanism for mechanically stimulated adenosine release, but not the only mechanism. These results demonstrate that pannexin channels differentially regulate rapid adenosine release and could be targeted to differentially affect mechanically stimulated adenosine due to brain damage.

Different Electrochemical Behavior of Cationic Dopamine from Anionic Ascorbic Acid and DOPAC at CNT Yarn Microelectrodes.

Carbon nanotube yarn microelectrodes (CNTYMEs) have micron-scale surface crevices that momentarily trap molecules. CNTYMEs improve selectivity among cationic catecholamines because secondary reactions are enhanced, but no anions have been studied. Here, we compared fast-scan cyclic voltammetry (FSCV) of dopamine and anionic interferents 3,4 dihydroxyphenylacetic acid (DOPAC) and L-ascorbic acid (AA) at CNTYMEs and carbon fiber microelectrodes (CFMEs). At CFMEs, dopamine current decreases with increasing FSCV repetition frequency at pH 7.4, whereas DOPAC and AA have increasing currents with increasing frequency, because of less repulsion at the negative holding potential. Both DOPAC and AA have side reactions after being oxidized, which are enhanced by trapping. At pH 4, the current increases for DOPAC and AA because they are not repelled. In addition, AA has a different oxidation pathway at pH 4, and an extra peak in the CV is enhanced by trapping effects at CNTYMEs. At pH 8.5, co-detection of dopamine in the presence of DOPAC and AA is enhanced at 100 Hz frequency because of differences in secondary peaks. Thus, the trapping effects at CNTYMEs affects anions differently than cations and secondary peaks can be used to identify dopamine in mixture of AA and DOPAC with FSCV.

Structure and Dynamics of Adsorbed Dopamine on Solvated Carbon Nanotubes and in a CNT Groove.

Advanced carbon microelectrodes, including many carbon-nanotube (CNT)-based electrodes, are being developed for the in vivo detection of neurotransmitters such as dopamine (DA). Our prior simulations of DA and dopamine-o-quinone (DOQ) on pristine, flat graphene showed rapid surface diffusion for all adsorbed species, but it is not known how CNT surfaces affect dopamine adsorption and surface diffusivity. In this work, we use molecular dynamics simulations to investigate the adsorbed structures and surface diffusion dynamics of DA and DOQ on CNTs of varying curvature and helicity. In addition, we study DA dynamics in a groove between two aligned CNTs to model the spatial constraints at the junctions within CNT assemblies. We find that the adsorbate diffusion on a solvated CNT surface depends upon curvature. However, this effect cannot be attributed to changes in the surface energy roughness because the lateral distributions of the molecular adsorbates are similar across curvatures, diffusivities on zigzag and armchair CNTs are indistinguishable, and the curvature dependence disappears in the absence of solvent. Instead, adsorbate diffusivities correlate with the vertical placement of the adsorbate's moieties, its tilt angle, its orientation along the CNT axis, and the number of waters in its first hydration shell, all of which will influence its effective hydrodynamic radius. Finally, DA diffuses into and remains in the groove between a pair of aligned and solvated CNTs, enhancing diffusivity along the CNT axis. These first studies of surface diffusion on a CNT electrode surface are important for understanding the changes in diffusion dynamics of dopamine on nanostructured carbon electrode surfaces.

Fast-Scan Cyclic Voltammetry (FSCV) Reveals Behaviorally Evoked Dopamine Release by Sugar Feeding in the Adult Drosophila Mushroom Body.

Drosophila melanogaster, the fruit fly, is an excellent model organism for studying dopaminergic mechanisms and simple behaviors, but methods to measure dopamine during behavior are needed. Here, we developed fast-scan cyclic voltammetry (FSCV) to track in vivo dopamine during sugar feeding. First, we employed acetylcholine stimulation to evaluate the feasibility of in vivo measurements in an awake fly. Next, we tested sugar feeding by placing sucrose solution near the fly proboscis. In the mushroom body medial tip, 1 pmol acetylcholine and sugar feeding released 0.49±0.04 µM and 0.31±0.06 µM dopamine, respectively but sugar-evoked release lasted longer than with acetylcholine. Administering the dopamine transporter inhibitor nisoxetine or D2 receptor antagonist flupentixol significantly increased sugar-evoked dopamine. This study develops FSCV to measure behaviorally evoked release in fly, enabling Drosophila studies of neurochemical control of reward, learning, and memory behaviors.

Spontaneous, transient adenosine release is not enhanced in the CA1 region of hippocampus during severe ischemia models.

Ischemic stroke causes damage in the brain, and a slow buildup of adenosine is neuroprotective during ischemic injury. Spontaneous, transient adenosine signaling, lasting only 3 s per event, has been discovered that increases in frequency in the caudate-putamen during early stages of mild ischemia-reperfusion injury. However, spontaneous adenosine changes have not been studied in the hippocampus during ischemia, an area highly susceptible to stroke. Here, we investigated changes of spontaneous, transient adenosine in the CA1 region of rat hippocampus during three different models of the varied intensity of ischemia. During the early stages of the milder bilateral common carotid artery occlusion (BCCAO) model, there were fewer spontaneous, transient adenosine, but no change in the concentration of individual events. In contrast, during the moderate 2 vertebral artery occlusion (2VAO) and severe 4 vessel occlusion (4VO) models, both the frequency of spontaneous, transient adenosine and the average event adenosine concentration decreased. Blood flow measurements validate that the ischemia models decreased blood flow, and corresponding pathological changes were observed by transmission electron microscopy (TEM). 4VO occlusion showed the most severe damage in histology and BCCAO showed the least. Overall, our data suggest that there is no enhanced spontaneous adenosine release in the hippocampus during moderate and severe ischemia, which could be due to depletion of the rapidly releasable adenosine pool. Thus, during ischemic stroke, there are fewer spontaneous adenosine events that could inhibit neurotransmission, which might lead to more damage and less neuroprotection in the hippocampus CA1 region. Read the Editorial Highlight for this article on page 800.

Influence of Geometry on Thin Layer and Diffusion Processes at Carbon Electrodes.

The geometric structure of carbon electrodes affects their electrochemical behavior, and large-scale surface roughness leads to thin layer electrochemistry when analyte is trapped in pores. However, the current response is always a mixture of both thin layer and diffusion processes. Here, we systematically explore the effects of thin layer electrochemistry and diffusion at carbon fiber (CF), carbon nanospike (CNS), and carbon nanotube yarn (CNTY) electrodes. The cyclic voltammetry (CV) response to the surface-insensitive redox couple Ru(NH3)63+/2+ is tested, so the geometric structure is the only factor. At CFs, the reaction is diffusion-controlled because the surface is smooth. CNTY electrodes have gaps between nanotubes that are about 10 µm deep, comparable with the diffusion layer thickness. CNTY electrodes show clear thin layer behavior due to trapping effects, with more symmetrical peaks and ΔEp closer to zero. CNS electrodes have submicrometer scale roughness, so their CV shape is mostly due to diffusion, not thin layer effects. However, even the 10% contribution of thin layer behavior reduces the peak separation by 30 mV, indicating ΔEp is influenced not only by electron transfer kinetics but also by surface geometry. A new simulation model is developed to quantitate the thin layer and diffusion contributions that explains the CV shape and peak separation for CNS and CNTY electrodes, providing insight on the impact of scan rate and surface structure size. Thus, this study provides key understanding of thin layer and diffusion processes at different surface structures and will enable rational design of electrodes with thin layer electrochemistry.

Electrochemical treatment in KOH renews and activates carbon fiber microelectrode surfaces.

Carbon fiber microelectrodes (CFMEs) are the standard electrodes for fast-scan cyclic voltammetry (FSCV) detection of neurotransmitters. CFMEs are generally used untreated but the surface can be activated with different treatments to improve electrochemical performance. In this work, we explored electrochemical treatments to clean and activate the CFME surface. We used different solution conditions for electrochemical treatment and found that electrochemical pretreatment in KOH outperforms treatment in KCl, H2O2, or HCl by accelerating the surface renewal process. The etching rate of carbon with electrochemical treatment in KOH is 37 nm/min, which is 10 times faster than that in the other solutions. Electrochemical treatment in KOH for several minutes regenerates a new carbon surface, which introduces more oxygen functional groups beneficial for adsorption and electron transfer. The KOH-treated CFMEs improved the limit of detection (LOD) to 9 ± 2 nM from 14 ± 4 nM for untreated CFMEs, and they successfully detected stimulated dopamine release in rat brain slices, demonstrating that they are stable and sensitive enough to use in biological systems. Electrochemical treatment in KOH completely restores the electrode sensitivity after biofouling. The proposed electrochemical treatment is simple and fast and can be applied prior to using CFMEs or after use to restore the surface. Thus, the method has potential to be a standard step to clean the carbon surface, or restore the sensitivity of electrodes from biofouling.

3D-Printed Carbon Nanoelectrodes for In Vivo Neurotransmitter Sensing.

Direct laser writing, a nano 3D-printing approach, has enabled fabrication of customized carbon microelectrode sensors for neurochemical detection. However, to detect neurotransmitters in tiny biological organisms or synapses, submicrometer nanoelectrodes are required. In this work, we used 3D printing to fabricate carbon nanoelectrode sensors. Customized structures were 3D printed and then pyrolyzed, resulting in free-standing carbon electrodes with nanotips. The nanoelectrodes were insulated with atomic layer deposition of Al2O3 and the nanotips were polished by a focused ion beam to form 600 nm disks. Using fast-scan cyclic voltammetry, the electrodes successfully detected stimulated dopamine in the adult fly brain, demonstrating that they are robust and sensitive enough to use in tiny biological systems. This work is the first demonstration of 3D printing to fabricate free-standing carbon nanoelectrode sensors and will enable batch fabrication of customized nanoelectrode sensors with precise control and excellent reproducibility.

Complex sex and estrous cycle differences in spontaneous transient adenosine.

Adenosine is a ubiquitous neuromodulator that plays a role in sleep, vasodilation, and immune response and manipulating the adenosine system could be therapeutic for Parkinson's disease or ischemic stroke. Spontaneous transient adenosine release provides rapid neuromodulation; however, little is known about the effect of sex as a biological variable on adenosine signaling and this is vital information for designing therapeutics. Here, we investigate sex differences in spontaneous, transient adenosine release using fast-scan cyclic voltammetry to measure adenosine in vivo in the hippocampus CA1, basolateral amygdala, and prefrontal cortex. The frequency and concentration of transient adenosine release were compared by sex and brain region, and in females, the stage of estrous. Females had larger concentration transients in the hippocampus (0.161 ± 0.003 µM) and the amygdala (0.182 ± 0.006 µM) than males (hippocampus: 0.134 ± 0.003, amygdala: 0.115 ± 0.002 µM), but the males had a higher frequency of events. In the prefrontal cortex, the trends were reversed. Males had higher concentrations (0.189 ± 0.003 µM) than females (0.170 ± 0.002 µM), but females had higher frequencies. Examining stages of the estrous cycle, in the hippocampus, adenosine transients are higher concentration during proestrus and diestrus. In the cortex, adenosine transients were higher in concentration during proestrus, but were lower during all other stages. Thus, sex and estrous cycle differences in spontaneous adenosine are complex, and not completely consistent from region to region. Understanding these complex differences in spontaneous adenosine between the sexes and during different stages of estrous is important for designing effective treatments manipulating adenosine as a neuromodulator.

Real-Time Measurement of Stimulated Dopamine Release in Compartments of the Adult Drosophila melanogaster Mushroom Body.

Drosophila melanogaster, a fruit fly, is an exquisite model organism to understand neurotransmission. Dopaminergic signaling in the Drosophila mushroom body (MB) is involved in olfactory learning and memory, with different compartments controlling aversive learning (heel) vs. appetitive learning (medial tip). Here, the goal was to develop techniques to measure endogenous dopamine in compartments of the MB for the first time. We compared three stimulation methods: acetylcholine (natural stimulus), P2X2 (chemogenetics), and CsChrimson (optogenetics). Evoked dopamine release was measured with fast-scan cyclic voltammetry in isolated adult Drosophila brains. Acetylcholine stimulated the largest dopamine release (0.40 µM) followed by P2X2 (0.14 µM) and CsChrimson (0.07 µM). With the larger acetylcholine and P2X2 stimulations, there were no regional or sex differences in dopamine release. However, with CsChrimson, dopamine release was significantly higher in the heel than the medial tip, and females had more dopamine than males. Michaelis-Menten modeling of the single-light pulse revealed no significant regional differences in Km, but the heel had a significantly lower Vmax (0.12 µM/s vs. 0.19 µM/s) and higher dopamine release (0.05 µM vs. 0.03 µM). Optogenetic experiments are challenging because CsChrimson is also sensitive to blue light used to activate green fluorescent protein, and thus, light exposure during brain dissection must be minimized. These experiments expand the toolkit for measuring endogenous dopamine release in Drosophila, introducing chemogenetic and optogenetic experiments for the first time. With a variety of stimulations, different experiments will help improve our understanding of neurochemical signaling in Drosophila.

Structural Similarity Image Analysis for Detection of Adenosine and Dopamine in Fast-Scan Cyclic Voltammetry Color Plots.

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.

Recent advances in fast-scan cyclic voltammetry.

Fast-scan cyclic voltammetry (FSCV) at carbon-fiber microelectrodes (CFMEs) is a versatile electrochemical technique to probe neurochemical dynamics in vivo. Progress in FSCV methodology continues to address analytical challenges arising from biological needs to measure low concentrations of neurotransmitters at specific sites. This review summarizes recent advances in FSCV method development in three areas: (1) waveform optimization, (2) electrode development, and (3) data analysis. First, FSCV waveform parameters such as holding potential, switching potential, and scan rate have been optimized to monitor new neurochemicals. The new waveform shapes introduce better selectivity toward specific molecules such as serotonin, histamine, hydrogen peroxide, octopamine, adenosine, guanosine, and neuropeptides. Second, CFMEs have been modified with nanomaterials such as carbon nanotubes or replaced with conducting polymers to enhance sensitivity, selectivity, and antifouling properties. Different geometries can be obtained by 3D-printing, manufacturing arrays, or fabricating carbon nanopipettes. Third, data analysis is important to sort through the thousands of CVs obtained. Recent developments in data analysis include preprocessing by digital filtering, principal components analysis for distinguishing analytes, and developing automated algorithms to detect peaks. Future challenges include multisite measurements, machine learning, and integration with other techniques. Advances in FSCV will accelerate research in neurochemistry to answer new biological questions about dynamics of signaling in the brain.