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Screening for Chemical Effects on Neuronal Proliferation and Neurite Outgrowth Using High-Content/High-Throughput Microscopy
Citation:
BREIER, J. M., N. RADIO, K. A. HOUCK, D. J. DIX, W. R. MUNDY, AND TIM J. SHAFER. Screening for Chemical Effects on Neuronal Proliferation and Neurite Outgrowth Using High-Content/High-Throughput Microscopy. Presented at Society of Toxicology Annual Meeting, Baltimore, MD, March 15 - 19, 2009.
Impact/Purpose:
These results demonstrate that these cell models can be used to screen large numbers of chemicals for the endpoints of proliferation, NOG, and viability using a high-content/high-throughput platform. These data are now being incorporated into the larger ToxCast dataset, and being evaluated for the ability to predict in vivo chemical toxicities.
Description:
The need to develop novel screening methods for developmental neurotoxicity in order to alleviate the demands of cost, time, and animals required for in vivo toxicity studies is well recognized. Accordingly, the U.S. EPA launched the ToxCast research program in 2007 to develop cost-effective approaches for prioritizing the toxicity testing of large numbers of chemicals in a short period of time. In ToxCast, data from hundreds of high-throughput assays are being used to develop computational models forecasting potential in vivo toxicity. As part of this effort, we have screened the 320 phase I chemicals of ToxCast (primarily pesticide actives) using high-content microscopic analysis of two cell lines, the immortalized human neural progenitor cell line ReNcell CX, and the PC12 sub-clone NS-1. Chemical effects on cell proliferation and viability were evaluated in ReNcell CX cells, while effects on neurite outgrowth (NOG) and viability were assessed using NS-1 cells. Using a high-content screening platform, chemical effects (40 µM; 24 hr) on ReNcell CX cell proliferation and viability were assessed by BrdU incorporation and propidium iodide exclusion, respectively. Similarly, NS-1 cells were assessed for chemical-induced changes (40 µM; 96 hr) in NOG and viability by βIII-tubulin staining and ATP quantification assays, respectively. Significant chemical effects on any endpoint were defined as changes greater than three-fold the standard deviation for negative control values. In ReNcell CX cells, 112 chemicals inhibited proliferation, 62 decreased viability, and 49 chemicals decreased both proliferation and viability. NOG in NS-1 cells was enhanced by 4 chemicals, but inhibited by 29 chemicals. NS-1 cell viability was decreased by 43 chemicals, and all chemicals that inhibited NOG also inhibited viability. It is noteworthy that 28 chemicals inhibited cell viability in both cell types, and that 20 chemicals produced significant effects on all four endpoints (proliferation in ReNcell CX cells, NOG in NS-1 cells, viability in both cell types). These results demonstrate that these cell models can be used to screen large numbers of chemicals for the endpoints of proliferation, NOG, and viability using a high-content/high-throughput platform. These data are now being incorporated into the larger ToxCast dataset, and being evaluated for the ability to predict in vivo chemical toxicities.