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ALTEX: Alternatives to Animal Experimentation
Article . 2021 . Peer-reviewed
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A high-throughput and highly automated genotoxicity screening assay

Authors: Renxiang, Chen; Yun-Tien, Lin; Albert J, Fornace; Heng-Hong, Li;

A high-throughput and highly automated genotoxicity screening assay

Abstract

The increasing number of compounds under development and chemicals in commerce that require safety assessments pose a serious challenge for regulatory agencies worldwide. In vitro screening using toxicogenomic biomarkers has been proposed as a first-tier screen in chemical assessment and has been endorsed internationally. We previously developed, evaluated, and validated an in vitro transcriptomic biomarker responsive to DNA damage-inducing (DDI) agents, namely TGx-DDI, for genotoxicity testing in human cells and demonstrated the feasibility of using TGx-DDI in a medium-throughput, cell-based genotoxicity testing system by implementing this biomarker with the Nanostring nCounter system. In this current study, we took advantage of Nanostring nCounter Plexset technology to develop a highly auto­mated, multiplexed, and high-throughput genotoxicity testing assay, designated the TGx-DDI Plexset assay, which can increase the screening efficiency eight-fold compared to standard nCounter technology while decreasing the hands-on time. We demonstrate the high-throughput capability of this assay by eliminating concentration determination and RNA extraction steps without compromising the specificity and sensitivity of TGx-DDI. Thus, we propose that this simple, highly automated, multiplexed high-throughput pipeline can be widely used in chemical screening and assessment.

Keywords

Genetic Markers, Mutagenicity Tests, Gene Expression Profiling, Humans, Cell Line, DNA Damage, Mutagens

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
gold