17 research outputs found
Beyond the Bench: What Skills are Needed for Next-Gen Developmental and Reproductive Toxicology?
Presented at the Teratology Society Annual Meeting<br
Channel Interactions and Robust Inference for Ratiometric βâLactamase Assay Data: A Tox21 Library Analysis
Ratiometric
β-lactamase (BLA) reporters are widely used to
study transcriptional responses in a high-throughput screening (HTS)
format. Typically, a ratio readout (background/target fluorescence)
is used for toxicity assessment and structureâactivity modeling
efforts from BLA HTS data. This ratio readout may be confounded by
channel-specific artifacts. To maximize the utility of BLA HTS data,
we analyzed the relationship between individual channels and ratio
readouts after fitting 10,000 chemical titration series screened in
seven BLA stressâresponse assays from the Tox21 initiative.
Similar to previous observations, we found that activity classifications
based on BLA ratio readout alone are confounded by interference patterns
for up to 85% (50% on average) of active chemicals. Most Tox21 analyses
adjust for this issue by evaluating target and ratio readout direction.
In addition, we found that the potency and efficacy estimates derived
from the ratio readouts may not represent the target channel effects
and thus complicates chemical activity comparison. From these analyses,
we recommend a simpler approach using a direct evaluation of the target
and background channels as well as the respective noise levels when
using BLA data for toxicity assessment. This approach eliminates the
channel interference issues and allows for straightforward chemical
assessment and comparisons
Correction to âOrganophosphate Ester Flame Retardants: Are They a Regrettable Substitution for Polybrominated Diphenyl Ethers?â
Correction to
âOrganophosphate Ester Flame
Retardants: Are They a Regrettable Substitution for Polybrominated
Diphenyl Ethers?
An Intuitive Approach for Predicting Potential Human Health Risk with the Tox21 10k Library
In vitroâin vivo extrapolation
(IVIVE) analyses translating
high-throughput screening (HTS) data to human relevance have been
limited. This study represents the first report applying IVIVE approaches
and exposure comparisons using the entirety of the Tox21 federal collaboration
chemical screening data, incorporating assay response efficacy and
quality of concentrationâresponse fits, and providing quantitative
anchoring to first address the likelihood of human in vivo interactions
with Tox21 compounds. This likelihood was assessed using a maximum
blood concentration to in vitro response ratio approach (<i>C</i><sub>max</sub>/AC<sub>50</sub>), analogous to decision-making methods
for clinical drugâdrug interactions. Fraction unbound in plasma
(<i>f</i><sub>up</sub>) and intrinsic hepatic clearance
(CL<sub>int</sub>) parameters were estimated in silico and incorporated
in a three-compartment toxicokinetic (TK) model to first predict <i>C</i><sub>max</sub> for in vivo corroboration using therapeutic
scenarios. Toward lower exposure scenarios, 36 compounds of 3925 unique
chemicals with curated activity in the HTS data using high-quality
doseâresponse model fits and âĽ40% efficacy gave âpossibleâ
human in vivo interaction likelihoods lower than median human exposures
predicted in the United States Environmental Protection Agencyâs
ExpoCast program. A publicly available web application has been designed
to provide all Tox21âToxCast dose-likelihood predictions. Overall,
this approach provides an intuitive framework to relate in vitro toxicology
data rapidly and quantitatively to exposures using either in vitro
or in silico derived TK parameters and can be thought of as an important
step toward estimating plausible biological interactions in a high-throughput
risk-assessment framework
Profiling 976 ToxCast Chemicals across 331 Enzymatic and Receptor Signaling Assays
Understanding potential health risks
is a significant challenge
due to the large numbers of diverse chemicals with poorly characterized
exposures and mechanisms of toxicities. The present study analyzes
976 chemicals (including failed pharmaceuticals, alternative plasticizers,
food additives, and pesticides) in Phases I and II of the U.S. EPAâs
ToxCast project across 331 cell-free enzymatic and ligand-binding
high-throughput screening (HTS) assays. Half-maximal activity concentrations
(AC50) were identified for 729 chemicals in 256 assays (7,135 chemicalâassay
pairs). Some of the most commonly affected assays were CYPs (CYP2C9
and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and
dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and
dithiocarbamate fungicides showed promiscuous but distinctly different
patterns of activity, whereas many of the pharmaceutical compounds
showed promiscuous activity across GPCRs. Literature analysis confirmed
>50% of the activities for the most potent chemicalâassay
pairs
(54) but also revealed 10 missed interactions. Twenty-two chemicals
with known estrogenic activity were correctly identified for the majority
(77%), missing only the weaker interactions. In many cases, novel
findings for previously unreported chemicalâtarget combinations
clustered with known chemicalâtarget interactions. Results
from this large inventory of chemicalâbiological interactions
can inform read-across methods as well as link potential targets to
molecular initiating events in adverse outcome pathways for diverse
toxicities
Profiling 976 ToxCast Chemicals across 331 Enzymatic and Receptor Signaling Assays
Understanding potential health risks
is a significant challenge
due to the large numbers of diverse chemicals with poorly characterized
exposures and mechanisms of toxicities. The present study analyzes
976 chemicals (including failed pharmaceuticals, alternative plasticizers,
food additives, and pesticides) in Phases I and II of the U.S. EPAâs
ToxCast project across 331 cell-free enzymatic and ligand-binding
high-throughput screening (HTS) assays. Half-maximal activity concentrations
(AC50) were identified for 729 chemicals in 256 assays (7,135 chemicalâassay
pairs). Some of the most commonly affected assays were CYPs (CYP2C9
and CYP2C19), transporters (mitochondrial TSPO, norepinephrine, and
dopaminergic), and GPCRs (aminergic). Heavy metals, surfactants, and
dithiocarbamate fungicides showed promiscuous but distinctly different
patterns of activity, whereas many of the pharmaceutical compounds
showed promiscuous activity across GPCRs. Literature analysis confirmed
>50% of the activities for the most potent chemicalâassay
pairs
(54) but also revealed 10 missed interactions. Twenty-two chemicals
with known estrogenic activity were correctly identified for the majority
(77%), missing only the weaker interactions. In many cases, novel
findings for previously unreported chemicalâtarget combinations
clustered with known chemicalâtarget interactions. Results
from this large inventory of chemicalâbiological interactions
can inform read-across methods as well as link potential targets to
molecular initiating events in adverse outcome pathways for diverse
toxicities
Predictive Endocrine Testing in the 21st Century Using <i>in Vitro</i> Assays of Estrogen Receptor Signaling Responses
Thousands
of environmental chemicals are subject to regulatory review for their
potential to be endocrine disruptors (ED). <i>In vitro</i> high-throughput screening (HTS) assays have emerged as a potential
tool for prioritizing chemicals for ED-related whole-animal tests.
In this study, 1814 chemicals including pesticide active and inert
ingredients, industrial chemicals, food additives, and pharmaceuticals
were evaluated in a panel of 13 <i>in vitro</i> HTS assays.
The panel of <i>in vitro</i> assays interrogated multiple
end points related to estrogen receptor (ER) signaling, namely binding,
agonist, antagonist, and cell growth responses. The results from the <i>in vitro</i> assays were used to create an ER Interaction Score.
For 36 reference chemicals, an ER Interaction Score >0 showed 100%
sensitivity and 87.5% specificity for classifying potential ER activity.
The magnitude of the ER Interaction Score was significantly related
to the potency classification of the reference chemicals (<i>p</i> < 0.0001). ERι/ERβ selectivity was also
evaluated, but relatively few chemicals showed significant selectivity
for a specific isoform. When applied to a broader set of chemicals
with <i>in vivo</i> uterotrophic data, the ER Interaction
Scores showed 91% sensitivity and 65% specificity. Overall, this study
provides a novel method for combining <i>in vitro</i> concentration
response data from multiple assays and, when applied to a large set
of ER data, accurately predicted estrogenic responses and demonstrated
its utility for chemical prioritization
A hybrid gene selection approach to create the S1500+ targeted gene sets for use in high-throughput transcriptomics
<div><p>Changes in gene expression can help reveal the mechanisms of disease processes and the mode of action for toxicities and adverse effects on cellular responses induced by exposures to chemicals, drugs and environment agents. The U.S. Tox21 Federal collaboration, which currently quantifies the biological effects of nearly 10,000 chemicals via quantitative high-throughput screening(qHTS) in <i>in vitro</i> model systems, is now making an effort to incorporate gene expression profiling into the existing battery of assays. Whole transcriptome analyses performed on large numbers of samples using microarrays or RNA-Seq is currently cost-prohibitive. Accordingly, the Tox21 Program is pursuing a high-throughput transcriptomics (HTT) method that focuses on the targeted detection of gene expression for a carefully selected subset of the transcriptome that potentially can reduce the cost by a factor of 10-fold, allowing for the analysis of larger numbers of samples. To identify the optimal transcriptome subset, genes were sought that are (1) representative of the highly diverse biological space, (2) capable of serving as a proxy for expression changes in unmeasured genes, and (3) sufficient to provide coverage of well described biological pathways. A hybrid method for gene selection is presented herein that combines data-driven and knowledge-driven concepts into one cohesive method. Our approach is modular, applicable to any species, and facilitates a robust, quantitative evaluation of performance. In particular, we were able to perform gene selection such that the resulting set of âsentinel genesâ adequately represents all known canonical pathways from Molecular Signature Database (MSigDB v4.0) and can be used to infer expression changes for the remainder of the transcriptome. The resulting computational model allowed us to choose a purely data-driven subset of 1500 sentinel genes, referred to as the S1500 set, which was then augmented using a knowledge-driven selection of additional genes to create the final S1500+ gene set. Our results indicate that the sentinel genes selected can be used to accurately predict pathway perturbations and biological relationships for samples under study.</p></div
Real-Time Growth Kinetics Measuring Hormone Mimicry for ToxCast Chemicals in Tâ47D Human Ductal Carcinoma Cells
High-throughput
screening (HTS) assays capable of profiling thousands of environmentally
relevant chemicals for <i>in vitro</i> biological activity
provide useful information on the potential for disrupting endocrine
pathways. Disruption of the estrogen signaling pathway has been implicated
in a variety of adverse health effects including impaired development,
reproduction, and carcinogenesis. The estrogen-responsive human mammary
ductal carcinoma cell line T-47D was exposed to 1815 ToxCast chemicals
comprising pesticides, industrial chemicals, pharmaceuticals, personal
care products, cosmetics, food ingredients, and other chemicals with
known or suspected human exposure potential. Cell growth kinetics
were evaluated using real-time cell electronic sensing. T-47D cells
were exposed to eight concentrations (0.006â100 ÎźM),
and measurements of cellular impedance were repeatedly recorded for
105 h. Chemical effects were evaluated based on potency (concentration
at which response occurs) and efficacy (extent of response). A linear
growth response was observed in response to prototypical estrogen
receptor agonists (17β-estradiol, genistein, bisphenol A, nonylphenol,
and 4-<i>tert</i>-octylphenol). Several compounds, including
bisphenol A and genistein, induced cell growth comparable in efficacy
to that of 17β-estradiol, but with decreased potency. Progestins,
androgens, and corticosteroids invoked a biphasic growth response
indicative of changes in cell number or cell morphology. Results from
this cell growth assay were compared with results from additional
estrogen receptor (ER) binding and transactivation assays. Chemicals
detected as active in both the cell growth and ER receptor binding
assays demonstrated potencies highly correlated with two ER transactivation
assays (<i>r</i> = 0.72; <i>r</i> = 0.70). While
ER binding assays detected chemicals that were highly potent or efficacious
in the T-47D cell growth and transactivation assays, the binding assays
lacked sensitivity in detecting weakly active compounds. In conclusion,
this cell-based assay rapidly detects chemical effects on T-47D growth
and shows potential, in combination with other HTS assays, to detect
environmentally relevant chemicals with potential estrogenic activity
Real-Time Growth Kinetics Measuring Hormone Mimicry for ToxCast Chemicals in Tâ47D Human Ductal Carcinoma Cells
High-throughput
screening (HTS) assays capable of profiling thousands of environmentally
relevant chemicals for <i>in vitro</i> biological activity
provide useful information on the potential for disrupting endocrine
pathways. Disruption of the estrogen signaling pathway has been implicated
in a variety of adverse health effects including impaired development,
reproduction, and carcinogenesis. The estrogen-responsive human mammary
ductal carcinoma cell line T-47D was exposed to 1815 ToxCast chemicals
comprising pesticides, industrial chemicals, pharmaceuticals, personal
care products, cosmetics, food ingredients, and other chemicals with
known or suspected human exposure potential. Cell growth kinetics
were evaluated using real-time cell electronic sensing. T-47D cells
were exposed to eight concentrations (0.006â100 ÎźM),
and measurements of cellular impedance were repeatedly recorded for
105 h. Chemical effects were evaluated based on potency (concentration
at which response occurs) and efficacy (extent of response). A linear
growth response was observed in response to prototypical estrogen
receptor agonists (17β-estradiol, genistein, bisphenol A, nonylphenol,
and 4-<i>tert</i>-octylphenol). Several compounds, including
bisphenol A and genistein, induced cell growth comparable in efficacy
to that of 17β-estradiol, but with decreased potency. Progestins,
androgens, and corticosteroids invoked a biphasic growth response
indicative of changes in cell number or cell morphology. Results from
this cell growth assay were compared with results from additional
estrogen receptor (ER) binding and transactivation assays. Chemicals
detected as active in both the cell growth and ER receptor binding
assays demonstrated potencies highly correlated with two ER transactivation
assays (<i>r</i> = 0.72; <i>r</i> = 0.70). While
ER binding assays detected chemicals that were highly potent or efficacious
in the T-47D cell growth and transactivation assays, the binding assays
lacked sensitivity in detecting weakly active compounds. In conclusion,
this cell-based assay rapidly detects chemical effects on T-47D growth
and shows potential, in combination with other HTS assays, to detect
environmentally relevant chemicals with potential estrogenic activity