Single-Cell Recording Of Vesicle Release From Human Neuroblastoma Cells Using 1024-Ch Monolithic Cmos Bioelectronics

Keywords

Amperometric sensors; Bioelectric phenomena; biological cells; biomedical transducers; biosensors; cell signaling; electrochemical devices

Abstract

Human neuroblastoma cells, SH-SY5Y, are often used as a neuronal model to study Parkinson's disease and dopamine release in the substantia nigra, a midbrain region that plays an important role in motor control. Using amperometric single-cell recordings of single vesicle release events, we can study molecular manipulations of dopamine release and gain a better understanding of the mechanisms of neurological diseases. However, single-cell analysis of neurotransmitter release using traditional techniques yields results with very low throughput. In this paper, we will discuss a monolithically-integrated CMOS sensor array that has the low-noise performance, fine temporal resolution, and 1024 parallel channels to observe dopamine release from many single cells with single-vesicle resolution. The measured noise levels of our transimpedance amplifier are 415, 622, and 1083 fARMS, at sampling rates of 10, 20, and 30 kS/s, respectively, without additional filtering. Post-CMOS processing is used to monolithically integrate 1024 on-chip gold electrodes, with an individual electrode size of 15 μm × 15 μm, directly on 1024 transimpedance amplifiers in the CMOS device. SU-8 traps are fabricated on individual electrodes to allow single cells to be interrogated and to reject multicellular clumps. Dopamine secretions from 76 cells are simultaneously recorded by loading the CMOS device with SH-SY5Y cells. In the 42-s measurement, a total of 7147 single vesicle release events are monitored. The study shows the CMOS device's capability of recording vesicle secretion at a single-cell level, with 1024 parallel channels, to provide detailed information on the dynamics of dopamine release at a single-vesicle resolution.

Publication Date

12-1-2018

Publication Title

IEEE Transactions on Biomedical Circuits and Systems

Volume

12

Issue

6

Number of Pages

1345-1355

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/TBCAS.2018.2861220

Socpus ID

85050733596 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85050733596

This document is currently not available here.

Share

COinS