Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects

Abstract

The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms' responses to environmental, chemical, and physical agents by observing the molecular alterations in more detail. Toxicogenomics integrates classical toxicology with omics assays, thus allowing the characterization of the mechanism of action (MOA) of chemical compounds, novel small molecules, and engineered nanomaterials (ENMs). Lack of standardization in data generation and analysis currently hampers the full exploitation of toxicogenomics-based evidence in risk assessment. To fill this gap, TGx methods need to take into account appropriate experimental design and possible pitfalls in the transcriptomic analyses as well as data generation and sharing that adhere to the FAIR Nanomaterials 2020, 10, 750 2 of 23 recent advancements in the design and analysis of DNA microarray, RNA sequencing (RNA-Seq), and single-cell RNA-Seq (scRNA-Seq) data. We provide guidelines on exposure time, dose and complex endpoint selection, sample quality considerations and sample randomization. Furthermore, we summarize publicly available data resources and highlight applications of TGx data to understand and predict chemical toxicity potential. Additionally, we discuss the efforts to implement TGx into regulatory decision making to promote alternative methods for risk assessment and to support the 3R (reduction, refinement, and replacement) concept. This review is the first part of a three-article series on Transcriptomics in Toxicogenomics. These initial considerations on Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects, are the starting point for further rigorous and reliable data preprocessing and modeling, described in the second and third part of the review series.

Advances in De Novo Drug Design: From Conventional to Machine Learning Methods

“…Toxicogenomics is the field of study that links the safety assessment of chemicals to the underlying biological mechanisms [ 136 , 137 ]. One important aspect tackled by toxicogenomics is the characterization of the mechanism-of-action (MOA) of a compound, represented as the set of all molecular alterations induced by the exposure of an organism (human) to it.…”

Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials

“…Rigorous risk assessment is needed to ensure the safety of ENMs. Toxicogenomics (TGx) has emerged as a complementary approach to traditional toxicology with the potential to facilitate faster and cheaper hazard assessment of ENMs 1,2 . The large-scale profiling of exposure-induced molecular alterations sets the stage for mechanistic toxicology and expedites the development of predictive models.…”

“…Our manually curated transcriptomics data collection with supporting ENM descriptions will have a high impact on the nanosafety community and can aid the development of new methodologies for nanomaterial safety assessment 2,8,30,33,43 .…”

Nextcast: A software suite to analyse and model toxicogenomics data

“…Traditional risk assessment strategies provide little understanding of the underlying molecular mechanisms leading to toxic outcomes [1] . It relies on molecular profiling technologies such as genomics, proteomics, and metabolomics to draw comprehensive conclusions on the possible toxicity of a chemical or substance [2] , [3] , [4] . Toxicogenomics has the potential to widen our understanding of the cascade of events and biological responses to exposure beyond the traditional toxicity endpoints.…”