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GABA-A receptor antagonists increase firing, bursting and synchrony of spontaneous activity in neuronal networks grown on microelectrode arrays: a step towards chemical "fingerprinting"
Citation:
Johnson, A., J. Turner, C. M. MACK, L. BURGOON, AND TIM SHAFER. GABA-A receptor antagonists increase firing, bursting and synchrony of spontaneous activity in neuronal networks grown on microelectrode arrays: a step towards chemical "fingerprinting". Presented at Society of Toxicology (SOT) Annual Meeting, RTP, DC, March 06 - 10, 2011.
Impact/Purpose:
This approach will improve the predictive nature of MEA data from uncharacterized chemicals by providing mode of action information.
Description:
Assessment of effects on spontaneous network activity in neurons grown on MEAs is a proposed method to screen chemicals for potential neurotoxicity. In addition, differential effects on network activity (chemical "fingerprints") could be used to classify chemical modes of action. To test this, we examined effects of 4 GABA-A antagonists (bicuculline (BIC), lindane, picrotoxin (PTX), RDX) on network activity in neocortical neurons and compared them to verapamil (VER; Ca2 + channel antagonist), fluoxetine (FLU; 5HT3 reuptake inhibitor) and muscimol (MUS; GABA-A agonist). Concentration-response relationships for effects on network spike rates were determined using MEAs, followed by analysis of bursting patterns and firing synchrony using Neuroexplorer and custom written software, respectively. GABA-A receptor antagonists increased network activity (EC50 (uM): BIC, 0.41; lindane, 1.9; PTX, 15.2; RDX, 12.3), while the other compounds decreased it (IC50 (uM): VER 6.9; FLU, 5.4; MUS, 0.4). GABAA receptor antagonists, but not other compounds, also altered #bursts/min, burst duration, and %spikes in bursts. GABA-A receptor antagonists increased synchrony of firing (EC50 (uM): PTX 0.045; RDX, 8; lindane, 0.15). By contrast, MUS (IC50 = 7.7 nM), VER(IC50 = 1.0 uM), FLU (IC50 =1.5 uM) decreased synchrony. While additional chemical classes need to be evaluated, these data confirm that MEAs are useful to screen chemicals for neuroactivity and indicate that analysis of chemical effects on spike rates, burst parameters and synchrony may be useful to develop chemical fingerprints. This approach will improve the predictive nature of MEA data from uncharacterized chemicals by providing mode of action information. This abstract does not reflect Agency policy