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Using ToxCast data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure.

Metadata Updated: May 2, 2021

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.

This dataset is associated with the following publication: Shah , I., W. Setzer , J. Jack, K. Houck , R. Judson , T. Knudsen , J. Liu, M. Martin , D. Reif, A.M. Richard , R.S. Thomas , K. Crofton , D.J. Dix , and R.J. Kavlock. (Envir. Health Perspect.) Using ToxCast data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 1-33, (2015).

Access & Use Information

Public: This dataset is intended for public access and use. License: See this page for license information.

Downloads & Resources

References

https://doi.org/10.1289/ehp.1409029

Dates

Metadata Created Date November 12, 2020
Metadata Updated Date May 2, 2021

Metadata Source

Harvested from EPA ScienceHub

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date May 2, 2021
Publisher U.S. EPA Office of Research and Development (ORD)
Maintainer
Identifier A-dncw-386
Data Last Modified 2016-07-01
Public Access Level public
Bureau Code 020:00
Schema Version https://project-open-data.cio.gov/v1.1/schema
Harvest Object Id 944a6ae7-4eb4-446a-9faa-887319bfb52f
Harvest Source Id 04b59eaf-ae53-4066-93db-80f2ed0df446
Harvest Source Title EPA ScienceHub
License https://pasteur.epa.gov/license/sciencehub-license.html
Program Code 020:095
Publisher Hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
Related Documents https://doi.org/10.1289/ehp.1409029
Source Datajson Identifier True
Source Hash bdb8602e29f009dde16c46aa68c4b54cfa128ccf
Source Schema Version 1.1

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