: Defining toxicological tipping points with microelectrode array recordings of developing neural networks
Citation:
Frank, C., J. Brown, K. Wallace, W. Mundy, I. Shah, AND Tim Shafer. : Defining toxicological tipping points with microelectrode array recordings of developing neural networks. 2017 Society of Toxicology Annual Meeting, Baltimore, MD, March 12 - 16, 2017.
Impact/Purpose:
This abstract describes the determination of tipping points from data on chemical alterations of neural network development. This could be useful for prioritization of compounds for DNT screening
Description:
Current guideline studies for developmental neurotoxicology (DNT) hazard are resource and time intensive, and therefore have only been conducted for a limited set of compounds. The EPA is developing more efficient methods to screen and prioritize the thousands of chemicals with undefined DNT hazard. Recognizing the major end product of neurodevelopment is connected neural networks capable of complex communication, we have developed an assay for network function based on microelectrode array recordings of developing cortical neuron networks. By 12 days in vitro, isolated rat cortical neurons establish mature networks, enabling examination of chemical effects on network formation and maintenance across this timeframe. We exposed developing networks to a library of 70 compounds across a range of concentrations (typically 0.03 – 30 µM) and measured 16 different network parameters for 4 timepoints. We developed two complimentary methods to quantify compound potency in producing adverse network effects. First, an area-under-the-curve metric applied to network parameters over time simplified concentration-response modeling while capturing developmental delay effects, and allowed for estimation of concentration where 50% of network activity is lost (EC50) for each parameter. Second, to integrate data across network parameters and model network adaptive response to exposure, we calculated the total scalar perturbation at each timepoint. This allowed for estimation of system velocities indicating whether a given concentration causes network failure or allows for recovery. For example, exposure to 1 µm haloperidol permitted system recovery by day 12, but concentrations of 3 µM and above did not. Critical concentrations (i.e, “tipping points”) that mark the point at which toxicity begins to overwhelm the system were defined from the system velocities of 35 compounds. Comparison of these network formation tipping points to network and cell viability EC50 estimates suggested tipping points are often more sensitive than individual network parameters and capture selective effects. Integrated tipping points for functional neural networks are therefore an attractive new metric for prioritizing compounds for DNT hazard. These data fill a critical gap in current DNT hazard screening approaches by prioritizing neural network disruptors with a scalable assay. (This abstract does not represent EPA policy)