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. 2024 Jun 5;14(6):295.
doi: 10.3390/bios14060295.

Novel Multiparametric Bioelectronic Measurement System for Monitoring Virus-Induced Alterations in Functional Neuronal Networks

Heinz-Georg Jahnke  1 , Verena Te Kamp  2 , Christoph Prönnecke  1 , Sabine Schmidt  1 , Ronny Azendorf  1 , Barbara Klupp  2 , Andrea A Robitzki  3 , Stefan Finke  2
Affiliations

Novel Multiparametric Bioelectronic Measurement System for Monitoring Virus-Induced Alterations in Functional Neuronal Networks

Heinz-Georg Jahnke et al. Biosensors (Basel). .

Abstract

Development and optimisation of bioelectronic monitoring techniques like microelectrode array-based field potential measurement and impedance spectroscopy for the functional, label-free and non-invasive monitoring of in vitro neuronal networks is widely investigated in the field of biosensors. Thus, these techniques were individually used to demonstrate the capabilities of, e.g., detecting compound-induced toxicity in neuronal culture models. In contrast, extended application for investigating the effects of central nervous system infecting viruses are rarely described. In this context, we wanted to analyse the effect of herpesviruses on functional neuronal networks. Therefore, we developed a unique hybrid bioelectronic monitoring platform that allows for performing field potential monitoring and impedance spectroscopy on the same microelectrode. In the first step, a neuronal culture model based on primary hippocampal cells from neonatal rats was established with reproducible and stable synchronised electrophysiological network activity after 21 days of cultivation on microelectrode arrays. For a proof of concept, the pseudorabies model virus PrV Kaplan-ΔgG-GFP was applied and the effect on the neuronal networks was monitored by impedance spectroscopy and field potential measurement for 72 h in a multiparametric mode. Analysis of several bioelectronic parameters revealed a virus concentration-dependent degeneration of the neuronal network within 24-48 h, with a significant early change in electrophysiological activity, subsequently leading to a loss of activity and network synchronicity. In conclusion, we successfully developed a microelectrode array-based hybrid bioelectronic measurement platform for quantitative monitoring of pathologic effects of a herpesvirus on electrophysiological active neuronal networks.

Keywords: field potential monitoring; impedance spectroscopy; microelectrode arrays; primary hippocampal neurons; pseudorabies virus model.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Description of hybrid measurement system. (A) Scheme of combined field potential and impedance spectroscopy measurement on the same microelectrode. (B) Scheme of field potential circuit pathway and high-precision impedance spectroscopy pathway based on channel multiplexing. Connection of both pathways on the measurement electrode is realised by a low noise switch. (C) Scheme and photo of whole measurement setup. (D) Measurement signals (field potential baseline and cell signal represented by relative impedance) of directly connected (without switch) measurement pathways and pathways connected over low noise switches.
Figure 2
Figure 2
Microelectrode size optimisation and bioelectronic characterisation of primary hippocampal cultures. (A) Images of used microelectrode arrays with 54 measurement electrodes and a shared reference/counter-electrode with a bonded 8.2 mm × 8.2 mm culture chamber. (B) Noise (standard deviation) analysis for field potential base signal of microelectrodes with different diameter (n = 18 electrodes, mean ± sd). (C) Representative field potential signal of electrophysiological active rat hippocampal culture (day 21) at different time scales, demonstrating different signal patterns (single spikes and spike clusters called bursts). High-resolution single spikes are shown as an overlay of 30 spikes from a single electrode. (D) Basic characterisation of electrophysiological activity for defining quality criteria of used cultures in experiments. Dashed lines represent minimum and maximum criteria (n = 28, mean ± sd). (E) Maximum relative impedance (cell signal) for only an impedance reference frontend in comparison to the novel hybrid frontend (n = 8, mean ± sd).
Figure 3
Figure 3
Virus-induced morphological degeneration of the neuronal network. (A) Transmitted light (TL) and fluorescence (GFP) microscopic images of neuronal cultures on an exemplarily MEA incubated with 1 MOI virus at discrete time points. White arrows mark initial areas of morphological dissolution/degeneration of the cell layer (scale bar = 200 µm). (B) Determined cellular contribution to impedance magnitude spectra (relative impedance) at selected time points (n = 6, mean ± sem). (C) Relative impedance spectra-derived maximum cell signal (relative impedance maximum) traces of control, 0.1 MOI and 1 MOI virus normalised to time point 0 h (left) as well as statistical analysis of values normalised to control for selected time points (right). (n = 6, mean ± sem, * p < 0.05, ** p < 0.01, *** p < 0.001).
Figure 4
Figure 4
Virus effects on the electrophysiological activity of the neural network. (A) Time traces of discrete electrophysiological parameters for control, 0.1 MOI and 1 MOI that are normalised to time point 0 h (left) and statistical analysis of values normalised to control (right) for selected timepoints (n = 6, mean ± sem, * p < 0.05, ** p < 0.01, *** p < 0.001). (B) Immunocytochemical characterisation of neuronal cultures on MEAs after end of experiment (time point 72 h) with neuronal marker neurofilament 200 (red), astrocyte marker GFAP (green) and DAPI nuclei stain (blue) (scale bar 100 µm).
Figure 5
Figure 5
Analysis of neuronal network synchronicity. (A) Exemplary field potential traces of neighbouring electrodes with partially (green boxes) and completely (red boxes) synchronised spikes. (B) Spatial allocation of spike traces (blue vertical lines in square boxes, box wide corresponds to time window of two seconds) for active electrodes marked as coloured squares (colour code represents spike count per minute with a minimum threshold for activity of 5). Exemplarily selected time points for 1 MOI virus. (C) Time traces of spike synchronicity for control, 0.1 MOI and 1 MOI that are normalised to time point 0 h (left) and statistical analysis of values normalised to control (right) for selected time points (n = 6, mean ± sem, ** p < 0.01, *** p < 0.001).
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