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 SiO2 NMs. Cellular responses were analyzed by global proteomics, targeted metabolomics and SH2 profiling. Results were integrated using Weighted Gene Correlation Network Analysis (WGCNA).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.

BackgroundOxidative stress, a commonly used paradigm to explain nanoparticle (NP)-induced toxicity, results from an imbalance between reactive oxygen species (ROS) generation and detoxification. As one consequence, protein carbonyl levels may become enhanced. Thus, the qualitative and quantitative description of protein carbonylation may be used to characterize how biological systems respond to oxidative stress induced by NPs.MethodsWe investigated a representative panel of 24 NPs including functionalized amorphous silica (6), zirconium dioxide (4), silver (4), titanium dioxide (3), zinc oxide (2), multiwalled carbon nanotubes (3), barium sulfate and boehmite. Surface reactivities of all NPs were studied in a cell-free system by electron spin resonance (ESR). NRK-52E cells were treated with all NPs, analyzed for viability (WST-1 assay) and intracellular ROS production (DCFDA assay). Carbonylated proteins were assessed by 1D and/or 2D immunoblotting and identified by matrix assisted laser desorption time-of-flight mass spectrometry (MALDI-TOF/TOF). In parallel, tissue homogenates from rat lungs intratracheally instilled with silver NPs were studied.ResultsEleven NPs induced elevated levels of carbonylated proteins. This was in good agreement with the surface reactivity of the NPs as obtained by ESR and the reduction in cell viability as assessed by WST-1 assay. By contrast, results obtained by DCFDA assay were deviating. Each NP induced an individual pattern of protein carbonyls on 2D immunoblots. Affected proteins comprised cytoskeletal components, proteins being involved in stress response, or cytoplasmic enzymes of central metabolic pathways such as glycolysis and gluconeogenesis. Furthermore, induction of carbonyls upon silver NP treatment was also verified in rat lung tissue homogenates.ConclusionsAnalysis of protein carbonylation is a versatile and sensitive method to describe NP-induced oxidative stress and, therefore, can be used to identify NPs of concern. Furthermore, detailed information about compromised proteins may aid in classifying NPs according to their mode of action.Electronic supplementary materialThe online version of this article (doi:10.1186/s12989-015-0108-2) contains supplementary material, which is available to authorized users.

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