The roles of catecholamines (dopamine, DA, norepinephrine, NE and epinephrine, EP) in neurological diseases are important in understanding brain function. Fast scan cyclic voltammetry, a conventional electrochemical technique used in such investigations in vivo, suffers from high background current and is either limited or unable to quantitate individual catecholamines in their mixtures. Redox cycling, however, can differentiate between catecholamines based on their propensity to survive diffusion from oxidative (generator) electrodes to and produce an electrochemical response at neighboring reductive (collector) electrodes¹ at arrays of two or more closely-spaced sets of the microelectrodes. This process repeats for many rounds until the analyte is lost through diffusion into bulk solution or through homogeneous chemical reactions.

At the generator electrode, the catecholamine undergoes a two-electron oxidation (E), producing an o-quinone (OQ) that can be re-reduced at the collector electrode back to the original catecholamine. However, the OQ can undergo an intramolecular cyclization process (C^’) to form the leucoaminochrome (LAC), which is electroinactive under our conditions. The apparent intramolecular cyclization rate constants (k) for the three catecholamines are different² (at pH= 7.4 in phosphate buffer, k_EP~89 k_NE, k_EP~700 k_DA, and k_NE~7.5 k_DA), which provide opportunity for differentiation by spatial distribution based on survival of the OQ form produced at the generator from the following chemistry C.³ Additionally, another OQ can undergo a bimolecular reaction (C’) with the LAC, reducing back to the original catecholamine, while LAC oxidizes to an aminochrome (AC), which is also electroinactive, and especially impacts the spatial distribution of OQ in mixtures of different catecholamines. The number of times that the catecholamine and OQ species go back and forth between generators and collectors defines the magnitude of the signal amplification, which leads to the ability to quantify the catecholamines and determine their detection limits.

Fabrication of probes with suitable dimensions is paramount to measuring catecholamines in vivo. The probe shank for feasible catecholamine measurements should be less than 100 µm wide to minimize tissue damage and about 6 mm long to reach the areas of interest in a rat’s brain.⁴ The devices previously made in our laboratory with which we demonstrated differentiation of catecholamines by redox cycling,⁵ do not have proper dimensions for insertion into the brain without causing substantial tissue damage. Although other research groups have fabricated and implanted neural probes with multiple electrodes^6-9, none to our knowledge have the requisite dimensions, geometry, and number of electrodes suitable for both redox cycling and tissue insertion.

 We will report the next steps we have taken to improve the design of electrodes to achieve desirable sensitivity and limits of detection and to fabricate the electrodes on probes with suitable dimensions. Using an equation proposed by Aoki et al.,¹⁰ we predict that a reversible diffusion-controlled current at an electrode at an array of nine interdigitated microband electrodes, each 100 µm long with our existing dimensions of 4 µm width and 4 µm separation, is about 24 pA for 0.4 µM DA. This current is suitable for quantitative measurements. By decreasing electrode width and gap (e.g. to 1 µm each), and by increasing the number of electrodes on the probe (e.g. 40), detection limits on the order of a tens of nM for a single catecholamine species by redox cycling should be possible. Integrating such designs with the approach to differentiate catecholamines in their mixtures and subsequent impact on detection limits will be discussed. Probe substrates are being constructed from polymer films that are subsequently lifted off a silicon substrate. The challenges associated with the use of SU-8 as the polymer material and new directions using other polymers such as polyimide and parylene will be examined.

 

References

1. Aggarwal et al., Analytical and Bioanalytical Chemistry 2013, 405 (11), 3859-3869.

2. Ciolkowski et al., Journal of analytical Chemistry 1994, 66 (21), 3611-3617.

3. Hu et al., Journal of Analytical Chemistry 2015, 87 (4), 2029-2032.

4. Wightman et al., Analytical Chemistry 1988, 60 (13), 769A-779A.

5. Hu et al., Analytical Chemistry 2016.

6. Yoon et al., J. Nanotechnol. Eng. Med. 2010, 1 (1), 011004/1-011004/8.

7. Chen et al., Biosens. Bioelectron. 2009, 24 (7), 1911-1917.

8. Cheung et al., J. Microelectromech. Syst. 2003, 12 (2), 179-184.

9. Metallo et al., J Neurosci Methods 2011, 195 (2), 176-84.

10. Aoki, K., J. Electroanal. Chem. 1988, 256, 269-282.