Carbon-Fiber Microbiosensor for Monitoring Rapid Lactate

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Carbon-Fiber Microbiosensor for Monitoring Rapid Lactate Fluctuations in Brain Tissue Using Fast-Scan Cyclic Voltammetry Samantha K. Smith, Saahj P. Gosrani, Christie A. Lee, Gregory S. McCarty, and Leslie A. Sombers Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b03694 • Publication Date (Web): 08 Oct 2018 Downloaded from http://pubs.acs.org on October 12, 2018

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Analytical Chemistry

Carbon-Fiber Microbiosensor for Monitoring Rapid Lactate Fluctuations in Brain Tissue Using Fast-Scan Cyclic Voltammetry Smith Samantha K.; Gosrani Saahj P.; Lee Christie A.; McCarty Gregory S.; Sombers Leslie A.* *Department

of Chemistry, North Carolina State University, 2620 Yarbrough Dr., Raleigh, North Carolina 27695-8204; [email protected]

Abstract 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 have addressed this by developing and characterizing a lactate oxidase-modified carbon-fiber microelectrode coupled with FSCV. 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.

Key Words: enzyme, neuroenergetics, dopamine, biosensor, FSCV

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Introduction The brain makes up roughly 2% of the body’s mass, but it accounts for ~ 25% of the body’s energy consumption.1 Investigation of brain energy metabolism, or neuroenergetics, has traditionally focused on glucose as the principal fuel source for brain function, based on its role in the formation of adenosine triphosphate (ATP). Lactate can yield 2 ATP after conversion to pyruvate,1 yet neuroenergetics research conventionally minimizes the role of lactate in energy production. Indeed, lactate is often described simply as a metabolic byproduct of glucose metabolism. However, there are several additional studies that have identified lactate as a key energy substrate in the brain.2-8 The different perspectives regarding the sources and function of lactate necessitate a simple, robust and powerful analytical tool with excellent spatiotemporal resolution that can enable selective, real-time detection of lactate in situ. Significant advances in understanding the role of lactate in neurotransmission have been made using first-generation biosensors.9-16 Amperometry is the electrochemical technique that is typically coupled with biosensors. With this approach, a constant potential is applied to the sensor and any redox reactions driven by this potential produce current. Upon calibration, this current can be used to quantify analyte concentration. While amperometry is advantageous due to a rapid temporal response, chemical selectivity becomes an issue when working in a complex chemical environment. All redox processes occurring at the electrode surface contribute to the current generated, including the oxidation/reduction of interferents. Without complicated subtraction schemes or the inclusion of chemically selective polymeric layers to exclude unwanted analytes, deconvolution of the data proves difficult.17-18 While these and other methods are effective to improve selectivity, they increase response time and often result in spatial averaging across recording sites that are chemically heterogeneous on the micron scale.19-20 2 ACS Paragon Plus Environment

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When working within a complex recording environment, such as the brain, selectivity, sensitivity, size and responsivity are critical sensor characteristics. Fast-scan cyclic voltammetry (FSCV) is a powerful electroanalytical technique that is often coupled with carbon-fiber microelectrodes to monitor rapid fluctuations of electroactive neurochemicals in live brain tissue with precise spatiotemporal resolution.21-24 Enzyme-modified carbon-fiber microelectrodes coupled with FSCV have enabled selective glucose monitoring in spatially discrete regions of brain tissue.25-28 These measurements are completed on a sub-second time scale, as selectivity is an advantage of FSCV, eliminating the need for additional physical barriers to exclude interferents. Indeed, this voltammetric approach transforms interferents into co-analytes and, as such, a glucose oxidase based microbiosensor can be used to simultaneously monitor glucose (nonelectroactive) and dopamine (DA, electroactive) in real time at the same micron-scale recording site.25-26 In this work, the previously optimized enzyme immobilization protocol27 was used to encapsulate lactate oxidase (LaOx) on the electrode surface , creating a microbiosensor for real-time lactate monitoring. Microbiosensor performance was fully characterized (sensitivity, selectivity, and stability) and validated. Dynamic concentrations of lactate were recorded in the extracellular space of rat striatum following electrical stimulation of the dopaminergic midbrain. Striatal DA release was monitored with a near simultaneous increase in lactate availability in response to increased metabolic demand. This tool will provide the means to further examine the role of lactate in the scope of brain neuroenergetics, and thus promises to aid in guiding the development of therapies targeting disease states that involve dysfunctional brain energy regulation.



Experimental Section Chemicals All chemicals were obtained from Sigma-Aldrich (St. Louis, MO) unless otherwise noted. Lactate oxidase (LaOx; specific activity: 20 U/mg at 37⁰C) originated from Aerococcus viridans. Chitosan originated from shrimp shells with a deacetylation percentage of ≥ 75% and an approximate molecular weight of 190,000-375,000 Da. All aqueous solutions were prepared using >18 MΩ·cm distilled water (Millipore Milli-Q, Billerica, MA). Microelectrode Fabrication Glass insulated carbon-fiber microelectrodes were prepared as described.29 Briefly, a single T-650 carbon fiber (7-μm diameter, Cytec Industries, West Patterson, NJ) was aspirated through a glass capillary (1.0 x 0.5 mm, A-M Systems, Carlsburg, WA). The capillary was pulled in a micropipette puller (Narishige, Tokyo, Japan) to create two glass tapered ends. The exposed carbon fiber was cut under a microscope to a length of 100 ± 10 μm. Once cut, a wire lead (Squires Electronics, Inc., Cornelius, OR) coated with a thin layer of silver conductive paint (GC Electronics, Rockford, IL) was inserted into the open end of the capillary to establish an electrical connection. Microbiosensor Fabrication A 2% chitosan solution was prepared in 87 mM acetic acid was utilized for enzyme entrapment as described in 26-27. 30 mg LaOx was dissolved in 200 μL of deionized water. Then, 800 μL of the chitosan solution was added to the LaOx solution. The mixture was slowly stirred until homogenous at 37°C and was stored for at least 24 hrs before use (4°C). Microelectrodes 4 ACS Paragon Plus Environment

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were electrochemically conditioned for 15 mins with a triangular voltammetric waveform (-0.4 V to +1.4 V) applied at a scan rate of 400 V·s-1 and with a frequency of 60 Hz, followed by 10 Hz for 5 mins.

Immediately after conditioning, the electrode was immersed in the

enzyme/chitosan solution and an electrodeposition potential of -3.0 V was applied to the electrode for 30 sec before it was slowly removed from solution. Each lactate microbiosensor was visually inspected then stored in phosphate buffer saline (PBS) at 4°C prior to use. Microbiosenor Characterization All in vitro data were collected in a flow-injection apparatus, at room temperature, in a custom-built grounded Faraday cage, using freely available High Definition Cyclic Voltammetry (HDCV) software (University of North Carolina at Chapel Hill, Department of Chemistry, Electronics Facility). A micromanipulator (World Precision Instruments Inc., Sarasota, FL) was used to position the biosensor in a custom electrochemical cell supplied with a continuous flow of 0.01 M PBS (0.5 mL/min, pH 7.4) via a syringe pump (New Era Pump Systems, Inc., Wantagh, NY). A 6-port HPLC valve was mounted on a two-position air actuator that was controlled by a digital pneumonic solenoid valve (Valco Instruments Co., Inc., Houston, TX). This allowed for two-second bolus injections of analyte to be reliably introduced to the lactate microbiosensor surface. After conditioning using a triangular voltammetric waveform (+ 0.1 V to + 1.4 V, 400 V·s-1) at a frequency of 60 Hz, electrochemical measurements were performed at a frequency of 10 Hz. 25-27 Animal Experiments Drug-naïve, male Sprague–Dawley rats (n=3; 275–300 g, Charles River Laboratories, Raleigh, NC) were allowed to acclimate to the facility for several days before experiments 5 ACS Paragon Plus Environment


commenced. Animals were individually housed on a 12:12 hr light/dark cycle with free access to food and water. Animal care and use was in complete accordance with the NC State University institutional guidelines (IACUC) and the NIH’s Guide for the Care and Use of Laboratory Animals. Rats were anesthetized with 4 % isoflurane (Zoetis, US LLC) and positioned in a stereotaxic frame (Kopf Instrumentation, Tujunga, CA) where isoflurane was maintained at ~ 1.5 - 2.0 % for the duration of the experiment. A heating pad (Harvard Apparatus, Holliston, MA) was used to maintain body temperature at ~ 37 °C. Holes were drilled for electrode placement according to coordinates from the Paxinos and Watson30 rat brain atlas. Working electrodes were placed in the dorsal striatum (anteroposterior (AP): +1.2 mm and mediolateral (ML): +2.0 mm, relative to bregma; dorsoventral (DV): -5.0 mm, relative to skull), and a Ag/AgCl reference electrode was placed in the contralateral forebrain. A bipolar stimulating electrode was placed in the ventral tegmental area/ substantia nigra complex (VTA/SN, AP: -5.8 mm, ML: +1.0 ± 0.2 mm, DV: -8.0-8.3 mm). The stimulating and reference electrodes were permanently affixed with screws and dental cement. Electrical stimulations were delivered to the VTA/SN (60 Hz, 120 pulses with 2 ms width, 118 µA) and voltammetric data were recorded with a WaveNeuro Potentiostat (Pine Instrument Company; Grove City, PA). Data Analysis and Statistics HDCV Analysis software (University of North Carolina at Chapel Hill, Department of Chemistry, Electronics Facility) was used for data analysis. GraphPad Prism 5 (GraphPad Software, Inc., La Jolla, CA) was used to determine statistical differences. One-way or two-way analysis of variance (ANOVA) with a Bonferroni’s post-hoc test was used as appropriate. Statistical significance was identified as p < 0.05. 6 ACS Paragon Plus Environment

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Results and Discussion Background-Subtracted Fast-scan Cyclic Voltammetry In this study, we adapted our real-time glucose monitoring protocol to quantitatively monitor lactate dynamics. Lactate microbiosensors were fabricated following a fully characterized approach.25-27 Briefly, the solubility of a 2% chitosan solution containing LaOx was controlled through electrodeposition. This generated a steep pH gradient at the electrode surface, thereby polymerizing the chitosan and entrapping the enzyme. Lactate microbiosensors were placed in a flow-injection apparatus and in vitro voltammetric data were recorded during 2sec injections, which introduced lactate to the surface of the electrode. As shown in Figure 1A, a triangular waveform from +0.1 V to +1.4 V was applied at 400 V·s-1. In the presence of lactate and molecular oxygen, pyruvate and hydrogen peroxide (H2O2) were produced by the activity of LaOx. The enzymatically generated H2O2 was voltammetrically detected in real time, serving as a reporter molecule for lactate.31-32 The high scan rates employed with FSCV generate a large non-faradaic background current (Figure 1B and Figure 1C) that is stable over tens of seconds and can be subtracted from the overall current collected. This reveals the faradaic contribution to the signal, and results in a background-subtracted cyclic voltammogram (CV) indicative of enzymatically generated H2O2 (Figure 1D), the reporter molecule to identify lactate detection. 32



Figure 1. Voltammetric detection using the lactate microbiosensor. (a) A representative scanning electron micrograph (scale bar 100 µm) of the microbiosensor, and the waveform applied. H2O2 is enzymatically generated at the electrode surface in the presence of lactate and molecular O2.(b) The fast scan rate generates a large non-faradaic current. (c) Oxidation of H2O2 generates faradaic current (red) which adds to the background current (black). (d) Background-subtracted CVs enable selective detection of enzymatically generated H2O2, indicative of lactate detection. Voltammetric Lactate Monitoring – Sensitivity A series of experiments was conducted to assess sensitivity to lactate. Representative data are shown in Figure 2A in the form of a color plot, which provides a method to easily view data (300 CVs) collected over a 30 sec. Individual CVs can be extracted to provide qualitative identification of H2O2, the electroactive substrate (Figure 2A, inset). The current collected over time can be extracted from the color plot at the peak oxidation potential for H2O2 to assess chemical dynamics (Figure 2A, red). Figure 2B provides a series of voltammograms for lactate concentrations ranging from 75 µM to 1000 µM. A calibration curve is shown in Figure 2C. The linear portion of this curve encompasses physiological brain lactate concentrations (0 to 1000 µM),1 with a sensitivity of 22 ± 1 nA·mM-1 (Figure 2D, r2 = 0.98; n=15). The limit of detection, 8 ACS Paragon Plus Environment

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defined as three times the standard deviation of the noise, was 7.0 ± 0.7 µM. Response time, defined as the time required for the signal to rise from 10% to 90% of its maximum value, was determined to be 1.6 ± 0.1 sec (n = 3) for the detection of a 2 sec bolus of 500 µM lactate.

Figure 2. Sensitivity to lactate. (a) Left, representative color plot collected in the detection of 250 µM lactate using a LaOx-modified microelectrode coupled with FSCV. The H2O2 CV (inset), taken at the white dashed line, verifies the presence of lactate. Right, current vs time trace (red) was extracted from the color plot at 1.2 V, the peak oxidation potential for H2O2. (b) A series of representative CVs collected for bolus injections (75 µM to 1000 µM) of lactate. (c) Calibration plot (n = 15 electrodes). (d) Expanded view of the linear range.

Microbiosensor Stability Chemical dynamics are often monitored in vivo over a time course of at least 3 - 4 hrs, requiring a sensor to respond predictably for precise quantification over the course of the entire experiment. To validate biosensor stability, 500 µM lactate was detected every 15 min over 4 hrs (n = 4). Peak oxidation currents were normalized to that recorded for a given electrode in response to the first injection. One-way ANOVA revealed there was no significant change in current response across time (Figure 3A, F(3,51)=0.82, p=0.66). Figure 3B displays 9 ACS Paragon Plus Environment


representative color plots collected for the first (left) and last (right) injection of lactate on a single microbiosensor. These results directly demonstrate microbiosensor stability over the course of at least 4 hrs.

Figure 3. Lactate microbiosensor stability. (a) Normalized current collected in response to repeated bolus injections of lactate (500 µM) over 4 hrs. (b) Representative color plots containing voltammetric data collected on the same electrode for the first injection (left) and the last injection (right). CVs for enzymatically generated H2O2 were extracted at the vertical dashed lines for identification of lactate (inset).

Selectivity In a complex environment such as the brain, selective detection of the molecule of interest is a primary concern. In order to assess selectivity, ‘null’ electrodes were fabricated in a manner identical to the lactate microbiosensors, except the chitosan mixture was void of LaOx. The electrochemical performance of the ‘null’ and ‘active’ microbiosensors was directly compared. Figure 4A-F depicts representative color plots collected on null (left) and active (right) lactate microbiosensors in response to lactate (lac, 500 µM), DA (1000 nM) and H2O2 (50 µM). Voltammograms (inset) were extracted at the time indicated by the white vertical lines for 10 ACS Paragon Plus Environment

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analyte identification. Glucose (1.6 mM) and ascorbic acid (50 µM) were also assessed, however color plots for these analytes are not shown because there was no measured response. Quantitative comparison of the complete data set is shown in Figure 4G. Two-way ANOVA revealed a significant main effect of current between electrode types (null, black and active, red; F(1, 33)=78.72, p

Carbon-Fiber Microbiosensor for Monitoring Rapid Lactate

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