Next Article in Journal
Nanoscale Characterization of Surface Plasmon-Coupled Photoluminescence Enhancement in Pseudo Micro Blue LEDs Using Near-Field Scanning Optical Microscopy
Next Article in Special Issue
Transcriptomics in Toxicogenomics, Part II: Preprocessing and Differential Expression Analysis for High Quality Data
Previous Article in Journal
Fe-Cu Doped Multiwalled Carbon Nanotubes for Fenton-like Degradation of Paracetamol Under Mild Conditions
Previous Article in Special Issue
Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment
Open AccessReview

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

1
Faculty of Medicine and Health Technology, Tampere University, 33200 Tampere, Finland
2
BioMediTech Institute, Tampere University, 33200 Tampere, Finland
3
Institute of Biotechnology, University of Helsinki, 00790 Helsinki, Finland
4
Institute of Environmental Medicine, Karolinska Institutet, 17177 Stockholm, Sweden
5
Division of Toxicology, Misvik Biology, 20520 Turku, Finland
6
School of Chemical Engineering, National Technical University of Athens, 15780 Athens, Greece
7
Center for Next Generation Cytometry, Hanyang University, Seoul 04763, Korea
8
Department of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea
9
Institute of Next Generation Material Design, Hanyang University, Seoul 04763, Korea
10
QSAR Lab Ltd., Aleja Grunwaldzka 190/102, 80-266 Gdansk, Poland
11
Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
12
National Institute for Occupational Health, Johannesburg 2000, South Africa
13
Nanoinformatics Department, NovaMechanics Ltd., Nicosia 1065, Cyprus
14
Haematology and Molecular Medicine Department, School of Pathology, University of the Witwatersrand, Johannesburg 2000, South Africa
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Nanomaterials 2020, 10(4), 750; https://doi.org/10.3390/nano10040750
Received: 10 March 2020 / Revised: 2 April 2020 / Accepted: 3 April 2020 / Published: 15 April 2020
(This article belongs to the Special Issue From Nanoinformatics to Nanomaterials Risk Assessment and Governance)
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 (Findable, Accessible, Interoperable, and Reusable) principles. In this review, we summarize the 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. View Full-Text
Keywords: transcriptomics; toxicogenomics (TGx); high throughput; microarrays; sequencing; experimental design; engineered nanomaterials (ENM); toxicology; alternative risk assessment transcriptomics; toxicogenomics (TGx); high throughput; microarrays; sequencing; experimental design; engineered nanomaterials (ENM); toxicology; alternative risk assessment
Show Figures

Graphical abstract

MDPI and ACS Style

Kinaret, P.A.S.; Serra, A.; Federico, A.; Kohonen, P.; Nymark, P.; Liampa, I.; Ha, M.K.; Choi, J.-S.; Jagiello, K.; Sanabria, N.; Melagraki, G.; Cattelani, L.; Fratello, M.; Sarimveis, H.; Afantitis, A.; Yoon, T.-H.; Gulumian, M.; Grafström, R.; Puzyn, T.; Greco, D. Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects. Nanomaterials 2020, 10, 750.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop