Evaluation of chemical compounds that inhibit neurite outgrowth using GFP-labeled iPSC-derived human neurons

Abstract

Due to the increasing number of drugs and untested environmental compounds introduced into commercial use, there is recognition for a need to develop reliable and efficient screening methods to identify compounds that may adversely impact the nervous system. One process that has been implicated in neurodevelopment is neurite outgrowth; the disruption of which can result in adverse outcomes that persist later in life. Here, we developed a green fluorescent protein (GFP) labeled neurite outgrowth assay in a high-content, high-throughput format using induced pluripotent stem cell (iPSC) derived human spinal motor neurons and cortical glutamatergic neurons. The assay was optimized for use in a 1536-well plate format. Then, we used this assay to screen a set of 84 unique compounds that have previously been screened in other neurite outgrowth assays. This library consists of known developmental neurotoxicants, environmental compounds with unknown toxicity, and negative controls. Neurons were cultured for 40 h and then treated with compounds at 11 concentrations ranging from 1.56 nM to 92 μM for 24 and 48 h. Effects of compounds on neurite outgrowth were evaluated by quantifying total neurite length, number of segments, and maximum neurite length per cell. Among the 84 tested compounds, neurite outgrowth in cortical neurons and motor neurons were selectively inhibited by 36 and 31 compounds, respectively. Colchicine, rotenone, and methyl mercuric (II) chloride inhibited neurite outgrowth in both cortical and motor neurons. It is interesting to note that some compounds like parathion and bisphenol AF had inhibitory effects on neurite outgrowth specifically in the cortical neurons, while other compounds, such as 2,2',4,4'-tetrabromodiphenyl ether and caffeine, inhibited neurite outgrowth in motor neurons. The data gathered from these studies show that GFP-labeled iPSC-derived human neurons are a promising tool for identifying and prioritizing compounds with developmental neurotoxicity potential for further hazard characterization.

Keywords: Developmental neurotoxicity; High-content imaging; High-throughput screening; Neurite outgrowth.

Fig.1.

High-content assay development on iPSC-derived motor and cortical neurons. The cells extend neurites rapidly after plating in a 1536-well plate for 24 hours. Cell number and neurite morphology was also measured using automated image analysis. Input images was separated into component color channels to identify cell body and number of segments. Scale bar: 100 μm.

Fig. 2.

Concentration-response curves and representative images of the neurons in response to rotenone treatment. Motor neurons and cortical neurons labeled with GFP were cultured in 1536-well format and treated with varying concentrations of rotenone for 24 and 48 hours, respectively. There were dose curves in 1536-well using both motor neurons and cortical neurons (A). Blue circles (24 hours) and squares (48 hours) in the curves represent the number of objects listed on the right axis. Black circles (24 hours) and squares (48 hours) represent the total neurite length listed on the left axis for reference of neurite outgrowth. The unit of neurite length is expressed as pixel. The neurite growth was inhibited using rotenone treatment (0.36, 2.88 and 5.76 μM) for 24 and 48 hours, and DMSO was used as the negative control (B). The images were acquired using Operetta High-Content Imaging System with a 20× Plan Fluor objective (Nikon). Excitation: 488 nm; emission: 530 nm. Each value represents the mean ± SD of three independent experiments. Scale bar: 100 μm.

Fig. 3.

Comparison of endpoints in the neurite outgrowth assay. Scatter plots showed IC_50S for three neurite outgrowth endpoints for the 84 compounds using cortical neurons after 48-hour treatment. Pearson correlation values are shown between (A) Total neurite length and Number of segments; (B) Total neurite length and Maximum neurite length; (C) Number of segments and Maximum neurite length.

Fig. 4.

Heat map of the 49 compounds in the neurite outgrowth assays. The motor and cortical neurons labeled with GFP were incubated with 11 concentration of compounds for 24 and 48 hours, respectively. The values were c total neurite length. The compound activity is colored according to potency (IC₅₀) and efficacy. Inactive compounds are colored grey.

Fig. 5.

Concentration response curves for several selective neurite outgrowth inhibitors in motor and cortical neurons. Total neurite length (TNL) and viable cells (VC) were determined at 11 concentrations to identify hits. A compound is considered a selective neurite inhibitor if there is a statistically significant difference between the IC₅₀ values of total neurite length and cell viability (t-test, p<0.05). Colchicine, and methyl mercuric (II) chloride were selective neurite outgrowth inhibitors both in motor neurons (A) and cortical neurons (B). Each value represents the mean ± SD of three independent experiments.

Fig. 6.

Cross comparison of test data for the NTP collection. Neurite outgrowth inhibition data using GFP-labeled cortical neurons and motor neurons are shown in parallel with other two published data sets (Delp et al., 2018; Ryan et al., 2016). In our study, the positive compounds were defined by either active in 24- or 48-hour treatment. Selective neurite outgrowth inhibitors are defined as compounds where there is a statistically significant difference between the IC₅₀ values of total neurite length and cell viability (t-test, p<0.05). Selective inhibitors were defined as ones having a high ratio (≥ 3.16) between BMC s (benchmark concentrations) for viability and neurite area (Ryan et al., 2016). Selective inhibitors were defined by an IC₅₀ (viability/neurite area) ratio for NeuriTox test (≥4) and PeriTox test (≥3) (Delp et al., 2018). The effect of the compound is indicated as specific neurotoxicity (green), cytotoxic effect (red) or no effect (white). Compounds with * are known DNT as classified in the previous studies (Aschner et al., 2017; Mundy et al., 2015).