10.5061/DRYAD.R2280GBB7
Deisenroth, Chad
0000-0002-0276-9716
Environmental Protection Agency
DeGroot, Danica
Environmental Protection Agency
Zurlinden, Todd
Environmental Protection Agency
Eicher, Andrew
Environmental Protection Agency
McCord, James
0000-0002-1780-4916
Environmental Protection Agency
Lee, Mi-Young
Unilever (United Kingdom)
Carmichael, Paul
Unilever (United Kingdom)
Thomas, Russell
Environmental Protection Agency
The Alginate Immobilization of Metabolic Enzymes (AIME) platform retrofits
an estrogen receptor transactivation assay with metabolic competence
Dryad
dataset
2020
Environmental Protection Agency
https://ror.org/03tns0030
Unilever (United Kingdom)
https://ror.org/05n8ah907
2020-09-10T00:00:00Z
2020-09-10T00:00:00Z
en
6758807 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
The U.S. EPA Endocrine Disruptor Screening Program utilizes data across
the ToxCast/Tox21 high-throughput screening (HTS) programs to evaluate the
biological effects of potential endocrine active substances (EAS). A
potential limitation to the use of in vitro assay data in regulatory
decision-making is the lack of coverage for xenobiotic metabolic
processes. Both hepatic- and peripheral-tissue metabolism can yield
metabolites that exhibit greater activity than the parent compound
(bioactivation) or are inactive (bioinactivation) for a given biological
target. Interpretation of biological effect data for both putative EAS, as
well as other chemicals, screened in HTS assays may benefit from the
addition of xenobiotic metabolic capabilities to decrease the uncertainty
in predicting potential hazards to human health. The objective of this
study was to develop an approach to retrofit existing HTS assays with
hepatic metabolism. The Alginate Immobilization of Metabolic Enzymes
(AIME) platform encapsulates hepatic S9 fractions in alginate microspheres
attached to 96-well peg lids. Functional characterization across a panel
of reference substrates for phase I cytochrome P450 enzymes revealed
substrate depletion with expected metabolite accumulation. Performance of
the AIME method in the VM7Luc estrogen receptor (ER) transactivation assay
was evaluated across 15 reference chemicals and 48 test chemicals that
yield metabolites previously identified as ER active or inactive. The
results demonstrate the utility of applying the AIME method for
identification of false positive and false negative target assay effects,
reprioritization of hazard based on metabolism-dependent bioactivity, and
enhanced in vivo concordance with the rodent uterotrophic bioassay.
Integration of the AIME metabolism method may prove useful for future
biochemical and cell-based HTS applications.