Grantee Research Project Results
2016 Progress Report: Human Stem Cell-Based Platform to Predict Selective Developmental Neurotoxicity
EPA Grant Number: R835552Title: Human Stem Cell-Based Platform to Predict Selective Developmental Neurotoxicity
Investigators: Terskikh, Alexey V. , Farhy, Chen
Current Investigators: Terskikh, Alexey V.
Institution: Sanford-Burnham Medical Research Institute
EPA Project Officer: Aja, Hayley
Project Period: September 1, 2013 through August 31, 2017
Project Period Covered by this Report: October 1, 2015 through September 30,2016
Project Amount: $800,000
RFA: Development and Use of Adverse Outcome Pathways that Predict Adverse Developmental Neurotoxicity (2012) RFA Text | Recipients Lists
Research Category: Chemical Safety for Sustainability , Human Health
Objective:
The goal of this project is to develop and implement a novel approach to assay developmental neurotoxicity of ToxCast chemicals using a human embryonic stem cell (hESC)-based model of neuronal development. We proposed to determine the cytotoxicity of 1,200 ToxCast compound library chemicals towards human fetal neural precursor cells (hfNPCs), human ESC-derived ventral neural precursor cells (vNPCs), and human ESC-derived dorsal neural precursor cells (dNPCs). The primary round of such screening has been accomplished during the third year (see detailed description below). In support of our original hypothesis, we have identified compounds with selective toxicity towards some, but not all types of NPCs. During the fourth (last) year, we will perform the in-depth followup studies to investigate the nature of the selectively/differentially toxic compounds and will get insights into molecular mechanism of action of those compounds. The objectives of this project are to:
Objective 1: Develop an HTS platform based on hESC-derived NPC to identify ToxCast phase I chemicals that selectively affect ventral or dorsal NPCs.
Objective 2: Adapt the human NPC-based assays to 384-well format and identify ToxCast phase II chemicals selectively affect ventral or dorsal NPCs.
Objective 3: Investigate the cellular and molecular mechanisms of action of active ToxCast chemicals.
Progress Summary:
In the past year, we have made the major progress towards these objectives, which remain as originally proposed. Following the modifications and improvements incorporated in our strategies in the previous years, we have screened 1,200 ToxCast compounds for their activity profile using dorsal NPCs and ventral NPCs. The screening has been performed in 384-well format using automatic cell cytometry acquisition algorithm supported by the IC200 instrument at SBP Medical Discovery Institute. Critically, we have confirmed our original hypothesis and identified over 100 compounds, which have differential levels of toxicity for different types of NPCs (fetal NPCs vs ventral NPCs vs dorsal NPCs). We are currently conducting the secondary followup concentration response screenings for the active compounds identified during the primary screen.
1. Nonlinear Regression Analysis of Cell Growth After Administration of ToxCast Compounds
Nonlinear regression analysis is widely used in toxicology to assess the effect of chemicals on cell growth and differentiation (1-3). To classify the effect of ToxCast compounds on the growth of NPCs, we first mathematically defined the growth of vehicle (DMSO) treated cells by curve fitting using non-linear regression. The growth of DMSO treated cells was found to match an exponential growth model. In this model, the fold growth at any time point can be determined from the equation: FoldGrowth = exp(k*T) - (k – a constant modulating the rate of growth; T - time). We calculated the value of k(DMSO) for each plate using the average fold growth for all DMSO treated wells in each plate. We then asked whether the growth of cells treated with each compound can be fitted to the same exponential growth curve as the DMSO (same k). Compounds not significantly different from control (p > 0.01) were classified as "Inert." Compounds that yield an exponential growth with k value significantly higher than control were classified as "Increased Proliferation." Compounds inducing growth that when fitted to this model yield negative k, were classified as "Toxic." Compounds inducing growth that when fitted to this model yield k significantly smaller than DMSO, were classified as "Decreased Proliferation." Following classification, we calculated the average growth of all compounds in each category. As expected, 72 hours of culturing with toxic compounds reduced the number of cells bellow the initial number. Growth of inert compounds resembled that of DMSO treated cells. Compounds increasing proliferation yielded an exponential growth curve with slightly higher rate of growth, especially at the last interval (48-72 hours). Compounds decreasing proliferation yielded an average curve showing decreased proliferation at all stages and in many cases resembling linear growth and even growth arrest. Representative examples from hfNPCs and average growth curves for all compounds in each category and for each NPC line are shown in Figure 1. In-depth analyses of the activity of compounds in each category (toxic, decreased proliferation, inert, increased proliferation), including compounds that have differential levels of toxicity for different types of NPCs, are presented below.
2. Principle Component Analysis (PCA) Plot Representation Delineates Compounds With Different Activities
Though we bin ToxCast compounds to four distinct growth effects (Inert, Increased, Decreased, Toxic), we expected these compounds will display a continuous gradient of growth modulation effects on NPCs. To visualize the various effects on NPCs growth, we calculated principal components using the average fold growth for each compound at each time point (0, 24, 48 and 72 hours). Plotting the first two components yielded a scatter plot in which each compound is represented by a single dot and compounds, which induce similar growth patterns that are close to each other. We then color-coded the various dots according to our non-linear regression analysis. As expected, this analysis showed convergence of "Inert" compounds and DMSO-treated cells. Compounds decreasing or increasing proliferation were found on the edges of the inert compounds "cloud" showing the expected gradient of effects on growth. Toxic compounds showed a larger distribution on the PCA plot, possibly indicating multiple modalities of toxicity (Figure 2).
Identification of Selectively (Differentially) Toxic Compounds
To identify selectively toxic compounds, all compounds displaying toxicity in at least one NPC line were categorized according to the cell lines showing toxicity. Twenty-one out of 68 (30.8%) compounds inducing toxicity were toxic to all three lines while 30 out of 68 (44.1%) were toxic to only a single NPC line. Due to the gradient effect of compounds on NPC growth, categorization is sometimes arbitrary. We, therefore, conducted PCA for all toxic compounds based solely on the growth curve in all cell lines (no categorization information). This analysis allows identification of Intermediate growth phenotypes that can be used to fine tune compound classification. For example, many compounds categorized as inducing toxicity in only ventral and dorsal NPCs are located in proximity to triple toxic compounds. Plotting the growth curve of all these compounds in all three NPC lines clearly shows two subsets of compounds from this category. In the first subset, compounds toxic in d/vNPCs show significant decrease of hfNPCs proliferation while the second subset of compounds seems to have little effect on the growth of hfNPCs (Figure 3).
Though efficiently summarizing compound categorization across lines and effects, the table on the left does not contain information about the effect of compounds in lines, which display differential effect on growth. For example: compounds categorized as toxic for both v/dNPCs can be categorized as decreasing proliferation or inert towards fNPCs. For this, we use pairwise comparison of each pair of NPC lines. These allow a further level of analysis and candidate identification by focusing for example on drugs, which cause toxicity in one line but are inert in another (Figure 4).
We are currently conducting secondary dose-dependency screenings with selectively/differentially toxic compounds. Once the compound identities are confirmed, we will investigate possible molecular mechanisms of their actions and plan the in vivo experiments in mice to investigate the effect of confirmed compounds on neural/brain development.
Future Activities:
In the coming year, we plan to conduct a secondary (dose-dependent) screen and to follow up on the effect of compounds with selective/differential toxicity towards various types of neural progenitors. In particular, we will calculate statistical associations between the results obtained in our study and the data from ToxCast and ToxRefDB. This work will be performed in close collaboration with Dr. Thomas Knudsen at EPA within the frame of cooperative agreement established during the second year of this project.
Supplemental Keywords:
Exposure, risk assessment, human health, bioavailability, metabolism, vulnerability, sensitive populations, dose-response, teratogenProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.