학술논문

Using ToxCast™ Data to Reconstruct Dynamic Cell State Trajectories and Estimate Toxicological Points of Departure.
Document Type
Article
Source
Environmental Health Perspectives. Jul2016, Vol. 124 Issue 7, p910-919. 10p. 5 Graphs.
Subject
*PROTEIN analysis
*CELL analysis
*ACIDS
*CELL culture
*CELL cycle
*CONFIDENCE intervals
*DIGITAL diagnostic imaging
*DIMETHYL sulfoxide
*HAZARDOUS substances
*ORGANIC compounds
*PACLITAXEL
*PESTICIDES
*STAINS & staining (Microscopy)
*TIME
*TOXICITY testing
*PHENOTYPES
*BIOINFORMATICS
*DATA analysis software
*DESCRIPTIVE statistics
*FLUORESCENT dyes
*IN vitro studies
Language
ISSN
0091-6765
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. [ABSTRACT FROM AUTHOR]