ArticleParticle and fibre toxicology2019
An in-depth multi-omics analysis in RLE-6TN rat alveolar epithelial cells allows for nanomaterial categorization.
Article in Particle and fibre toxicology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Meta-Analysis of Integrated Proteomic and Transcriptomic Data Discerns Structure-Activity Relationship of Carbon Materials with Different Morphologies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Pooled it
- Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages.International journal of molecular sciences · 2020Pooled it
- Size-Dependent Cytotoxicity and Multi-Omic Changes Induced by Amorphous Silicon Nanoparticles in HepG2 Cells.Toxics · 2025Article
- Advancing Nanomaterial Toxicology Screening Through Efficient and Cost-Effective Quantitative Proteomics.Small methods · 2024Article
- The toxicity of nanoparticles and their interaction with cells: anNanoscale advances · 2023Review
- Article
- Evaluating the cytotoxicity and pathogenicity of multi-walled carbon nanotube through weighted gene co-expression network analysis: a nanotoxicogenomics study.BMC genomic data · 2022Article
- Surface Treatment With Hydrophobic Coating Reagents (Organosilanes) Strongly Reduces the Bioactivity of Synthetic Amorphous SilicaFrontiers in public health · 2022Article
- Proteomic Characterization of the Cellular Effects of AhR Activation by Microbial Tryptophan Catabolites in Endotoxin-Activated Human Macrophages.International journal of environmental research and public health · 2021Article
- Article
- Genotoxicity and Gene Expression in the Rat Lung Tissue following Instillation and Inhalation of Different Variants of Amorphous Silica Nanomaterials (aSiONanomaterials (Basel, Switzerland) · 2021Article
- A Multi-Omics Analysis of Mucosal-Associated-Invariant T Cells Reveals Key Drivers of Distinct Modes of Activation.Frontiers in immunology · 2021Article
- Multiparametric Profiling of Engineered Nanomaterials: Unmasking the Surface Coating Effect.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020Article
- Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures.International journal of molecular sciences · 2020Review
- Mitochondrial Transfer by Human Mesenchymal Stromal Cells Ameliorates Hepatocyte Lipid Load in a Mouse Model of NASH.Biomedicines · 2020Article
- Toxicity of TiOInternational journal of molecular sciences · 2020Article
- The gut bacteriumGut microbesArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNanomaterials (NMs) can be fine-tuned in their properties resulting in a high number of variants, each requiring a thorough safety assessment. Grouping and categorization approaches that would reduce the amount of testing are in principle existing for NMs but are still mostly conceptual. One drawback is the limited mechanistic understanding of NM toxicity. Thus, we conducted a multi-omics in vitro study in RLE-6TN rat alveolar epithelial cells involving 12 NMs covering different materials and including a systematic variation of particle size, surface charge and hydrophobicity for SiO
resultsCluster analyses involving all data sets separated Graphene Oxide, TiO2_NM105, SiO2_40 and Phthalocyanine Blue from the other NMs as their cellular responses showed a high degree of similarities, although apical in vivo results may differ. SiO2_7 behaved differently but still induced significant changes. In contrast, the remaining NMs were more similar to untreated controls. WGCNA revealed correlations of specific physico-chemical properties such as agglomerate size and redox potential to cellular responses. A key driver analysis could identify biomolecules being highly correlated to the observed effects, which might be representative biomarker candidates. Key drivers in our study were mainly related to oxidative stress responses and apoptosis.
conclusionsOur multi-omics approach involving proteomics, metabolomics and SH2 profiling proved useful to obtain insights into NMs Mode of Actions. Integrating results allowed for a more robust NM categorization. Moreover, key physico-chemical properties strongly correlating with NM toxicity were identified. Finally, we suggest several key drivers of toxicity that bear the potential to improve future testing and assessment approaches.
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Registered trials
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