Using ToxCast™ Data to Reconstruct Dynamic Cell State Trajectories and Estimate Toxicological Points of Departure

Abstract

Background: High-content imaging (HCI) allows simultaneous measurement of multiple cellular phenotypic changes and is an important tool for evaluating the biological activity of chemicals.

Objectives: Our goal was to analyze dynamic cellular changes using HCI to identify the "tipping point" at which the cells did not show recovery towards a normal phenotypic state.

Methods: HCI was used to evaluate the effects of 967 chemicals (in concentrations ranging from 0.4 to 200 μM) on HepG2 cells over a 72-hr exposure period. The HCI end points included p53, c-Jun, histone H2A.x, α-tubulin, histone H3, alpha tubulin, mitochondrial membrane potential, mitochondrial mass, cell cycle arrest, nuclear size, and cell number. A computational model was developed to interpret HCI responses as cell-state trajectories.

Results: Analysis of cell-state trajectories showed that 336 chemicals produced tipping points and that HepG2 cells were resilient to the effects of 334 chemicals up to the highest concentration (200 μM) and duration (72 hr) tested. Tipping points were identified as concentration-dependent transitions in system recovery, and the corresponding critical concentrations were generally between 5 and 15 times (25th and 75th percentiles, respectively) lower than the concentration that produced any significant effect on HepG2 cells. The remaining 297 chemicals require more data before they can be placed in either of these categories.

Conclusions: These findings show the utility of HCI data for reconstructing cell state trajectories and provide insight into the adaptation and resilience of in vitro cellular systems based on tipping points. Cellular tipping points could be used to define a point of departure for risk-based prioritization of environmental chemicals.

Citation: Shah I, Setzer RW, Jack J, Houck KA, Judson RS, Knudsen TB, Liu J, Martin MT, Reif DM, Richard AM, Thomas RS, Crofton KM, Dix DJ, Kavlock RJ. 2016. Using ToxCast™ data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure. Environ Health Perspect 124:910-919; http://dx.doi.org/10.1289/ehp.1409029.

Figure 1

Hypothetical dynamic system perturbations as trajectories and calculation of tipping points. (A) The green curve depicts a hypothetical trajectory across observations at time t (X^t) shown on the basis of two endpoints (x_i and x_j). (B) The perturbation velocity (V) is calculated as the derivative of the scalar perturbation (|X |) with respect to time (shown in green). (C) Three different types of trajectories are shown using |X |: trajectories that describe the normal behavior of the system (shown in green); adaptive trajectories, which include some perturbation of the system state followed by recovery (shown in orange); and adverse trajectories that show initial adaptive responses followed by lack of recovery at later times (shown in red). (D) The relationship between the velocity, concentration, and time is given by a continuous surface, V = f(c,t). (E) The rate of change of velocity with respect to concentration is given by ∂_cV = ∂V/∂c = ∂² X/∂t∂c. (F) Solving ∂_cV = 0 gives the critical concentration, C_cr.

Figure 2

Concentration and time-dependent perturbations produced by chemicals. From top to bottom, each row of heat maps shows the perturbations produced by increasing concentrations of (A) octanoic acid, (B) dimethyl terephthalate, (C) chlorpyrifos-methyl, (D) butachlor, (E) dicofol, and (F) oxadiazon. Each heat map shows the end points (columns), time in hours (rows), and perturbations (colors) produced by each concentration (title). The end points include p53 activity, stress kinase (SK), oxidative stress (OS), microtubules (Mt), mitochondrial mass (MM), mitochondrial membrane potential (MMP), mitotic arrest (MA), cell cycle arrest (CCA), nuclear size (NS), and cell number (CN). The colors signify no effect (yellow), increase (red), and decrease (blue), and the magnitude of the changes is indicated by the color bar in the lower right corner.

Figure 3

Magnitude of perturbations for trajectories produced by fixed treatment concentrations of different chemicals. Each graph shows scalar perturbations (y-axis) over time (x-axis) for multiple doses of a chemical. The colors signify treatment concentrations ranging from low (blue) to high (red).

Figure 4

Trajectory analysis and critical concentrations of different chemicals at 72 hr. The y-axis of each graph shows the scalar system perturbation (X = green), velocity (V = blue) and derivative of velocity with respect to concentration (∂_cV = red), and uncertainty analysis of ∂_cV (light red). The x-axis of each graph shows the treatment concentration of the chemical (μM). Dimethyl terephthalate, sodium ʟ-ascorbate, octanoic acid, chlorpyrifos-methyl, fludioxonil, and tetramethrin produced trends in ∂_cV consistent with system recovery. Butachlor, oxadiazon, pioglitazone, farglitazar, troglitazone, and thiram elicited trajectories with tipping points. Captan, mercuric chloride, and fluazinam produced complex trends in ∂_cV that could be indicative of experimental noise.

Figure 5

Critical concentrations (C_cr) for 340 chemicals at 72 hr. Chemicals are sorted by C_cr in descending order from top to bottom (y-axis), and each row shows the C_cr, the lowest effect concentration (LEC), the scalar perturbation (|X|), and the velocity (V). (A) C_cr s (μM) are indicated by points along the x-axis; the uncertainty is indicated by the gray line, the minimum LECs are green points, and select chemicals are labeled. (B) LEC (μM) across p53, SK (stress kinase), OS (oxidative stress), Mt (microtubules), MM (mitochondrial mass), mitochondrial membrane potential (MMP), mitotic arrest (MA), cell cycle arrest (CCA), nuclear size (NS), and cell number (CN). The LEC value is represented as no effect (pink), through saturation (red), as shown in the color bar on the right. (C) |X| as a heat map across concentrations (μM), where magnitude is represented by color saturation (values shown in color bar on the right). (D) V as a heat map across concentrations (μM) where V > 0 (reds), V < 0 (blues), and V = 0 (white).