An in-depth multi-omics analysis in RLE-6TN rat alveolar epithelial cells allows for nanomaterial categorization

Bioinformatics and machine learning to support nanomaterial grouping

Nanomaterials (NMs) offer plenty of novel functionalities. Moreover, their physicochemical properties can be fine-tuned to meet the needs of specific applications, leading to virtually unlimited numbers of NM variants. Hence, efficient hazard and risk assessment strategies building on New Approach Methodologies (NAMs) become indispensable. Indeed, the design, the development and implementation of NAMs has been a major topic in a substantial number of research projects. One of the promising strategies that can help to deal with the high number of NMs variants is grouping and read-across. Based on demonstrated structural and physicochemical similarity, NMs can be grouped and assessed together. Within an established NM group, read-across may be performed to fill in data gaps for data-poor variants using existing data for NMs within the group. Establishing a group requires a sound justification, usually based on a grouping hypothesis that links specific physicochemical properties to well-defined hazard endpoints. However, for NMs these interrelationships are only beginning to be understood. The aim of this review is to demonstrate the power of bioinformatics with a specific focus on Machine Learning (ML) approaches to unravel the NM Modes-of-Action (MoA) and identify the properties that are relevant to specific hazards, in support of grouping strategies. This review emphasizes the following messages: 1) ML supports identification of the most relevant properties contributing to specific hazards; 2) ML supports analysis of large omics datasets and identification of MoA patterns in support of hypothesis formulation in grouping approaches; 3) omics approaches are useful for shifting away from consideration of single endpoints towards a more mechanistic understanding across multiple endpoints gained from one experiment; and 4) approaches from other fields of Artificial Intelligence (AI) like Natural Language Processing or image analysis may support automated extraction and interlinkage of information related to NM toxicity. Here, existing ML models for predicting NM toxicity and for analyzing omics data in support of NM grouping are reviewed. Various challenges related to building robust models in the field of nanotoxicology exist and are also discussed.

Advancing Nanomaterial Toxicology Screening Through Efficient and Cost-Effective Quantitative Proteomics

Proteomic investigations yield high-dimensional datasets, yet their application to large-scale toxicological assessments is hindered by reproducibility challenges due to fluctuating measurement conditions. To address these limitations, this study introduces an advanced tandem mass tag (TMT) labeling protocol. Although labeling approaches shorten data acquisition time by multiplexing samples compared to traditional label-free quantification (LFQ) methods in general, the associated costs may surge significantly with large sample sets, for example, in toxicological screenings. However, the introduced advanced protocol offers an efficient, cost-effective alternative, reducing TMT reagent usage (by a factor of ten) and requiring minimal biological material (1 µg), while demonstrating increased reproducibility compared to LFQ. To demonstrate its effectiveness, the advanced protocol is employed to assess the toxicity of nine benchmark nanomaterials (NMs) on A549 lung epithelial cells. While LFQ measurements identify 3300 proteins, they proved inadequate to reveal NM toxicity. Conversely, despite detecting 2600 proteins, the TMT protocol demonstrates superior sensitivity by uncovering alterations induced by NM treatment. In contrast to previous studies, the introduced advanced protocol allows simultaneous and straightforward assessment of multiple test substances, enabling prioritization, ranking, and grouping for hazard evaluation. Additionally, it fosters the development of New Approach Methodologies (NAMs), contributing to innovative methodologies in toxicological research.

Meta-Analysis of Integrated Proteomic and Transcriptomic Data Discerns Structure-Activity Relationship of Carbon Materials with Different Morphologies

The Fiber Pathogenicity Paradigm (FPP) establishes connections between fiber structure, durability, and disease-causing potential observed in materials like asbestos and synthetic fibers. While emerging nanofibers are anticipated to exhibit pathogenic traits according to the FPP, their nanoscale diameter limits rigidity, leading to tangling and loss of fiber characteristics. The absence of validated rigidity measurement methods complicates nanofiber toxicity assessment. By comprehensively analyzing 89 transcriptomics and 37 proteomics studies, this study aims to enhance carbon material toxicity understanding and proposes an alternative strategy to assess morphology-driven toxicity. Carbon materials are categorized as non-fibrous, high aspect ratio with shorter lengths, tangled, and rigid fibers. Mitsui-7 serves as a benchmark for pathogenic fibers. The meta-analysis reveals distinct cellular changes for each category, effectively distinguishing rigid fibers from other carbon materials. Subsequently, a robust random forest model is developed to predict morphology, unveiling the pathogenicity of previously deemed non-pathogenic NM-400 due to its secondary structures. This study fills a crucial gap in nanosafety by linking toxicological effects to material morphology, in particular regarding fibers. It demonstrates the significant impact of morphology on toxicological behavior and the necessity of integrating morphological considerations into regulatory frameworks.

Multiparametric in vitro genotoxicity assessment of different variants of amorphous silica nanomaterials in rat alveolar epithelial cells

The hazard posed to human health by inhaled amorphous silica nanomaterials (aSiO2 NM) remains uncertain. Herein, we assessed the cyto- and genotoxicity of aSiO2 NM variants covering different sizes (7, 15, and 40 nm) and surface modifications (unmodified, phosphonate-, amino- and trimethylsilyl-modified) on rat alveolar epithelial (RLE-6TN) cells. Cytotoxicity was evaluated at 24 h after exposure to the aSiO2 NM variants by the lactate dehydrogenase (LDH) release and WST-1 reduction assays, while genotoxicity was assessed using different endpoints: DNA damage (single- and double-strand breaks [SSB and DSB]) by the comet assay for all aSiO2 NM variants; cell cycle progression and γ-H2AX levels (DSB) by flow cytometry for those variants that presented higher cytotoxic and DNA damaging potential. The variants with higher surface area demonstrated a higher cytotoxic potential (SiO2_7, SiO2_15_Unmod, SiO2_15_Amino, and SiO2_15_Phospho). SiO2_40 was the only variant that induced significant DNA damage on RLE-6TN cells. On the other hand, all tested variants (SiO2_7, SiO2_15_Unmod, SiO2_15_Amino, and SiO2_40) significantly increased total γ-H2AX levels. At high concentrations (28 µg/cm2), a decrease in G0/G1 subpopulation was accompanied by a significant increase in S and G2/M sub-populations after exposure to all tested materials except for SiO2_40 which did not affect cell cycle progression. Based on the obtained data, the tested variants can be ranked for its genotoxic DNA damage potential as follows: SiO2_7 = SiO2_40 = SiO2_15_Unmod > SiO2_15_Amino. Our study supports the usefulness of multiparametric approaches to improve the understanding on NM mechanisms of action and hazard prediction.

The toxicity of nanoparticles and their interaction with cells: an in vitro metabolomic perspective

Nowadays, nanomaterials (NMs) are widely present in daily life due to their significant benefits, as demonstrated by their application in many fields such as biomedicine, engineering, food, cosmetics, sensing, and energy. However, the increasing production of NMs multiplies the chances of their release into the surrounding environment, making human exposure to NMs inevitable. Currently, nanotoxicology is a crucial field, which focuses on studying the toxicity of NMs. The toxicity or effects of nanoparticles (NPs) on the environment and humans can be preliminary assessed in vitro using cell models. However, the conventional cytotoxicity assays, such as the MTT assay, have some drawbacks including the possibility of interference with the studied NPs. Therefore, it is necessary to employ more advanced techniques that provide high throughput analysis and avoid interferences. In this case, metabolomics is one of the most powerful bioanalytical strategies to assess the toxicity of different materials. By measuring the metabolic change upon the introduction of a stimulus, this technique can reveal the molecular information of the toxicity induced by NPs. This provides the opportunity to design novel and efficient nanodrugs and minimizes the risks of NPs used in industry and other fields. Initially, this review summarizes the ways that NPs and cells interact and the NP parameters that play a role in this interaction, and then the assessment of these interactions using conventional assays and the challenges encountered are discussed. Subsequently, in the main part, we introduce the recent studies employing metabolomics for the assessment of these interactions in vitro.

Comparing species-different responses in pulmonary fibrosis research: Current understanding of in vitro lung cell models and nanomaterials

Pulmonary fibrosis (PF) is a chronic, irreversible lung disease that is typically fatal and characterized by an abnormal fibrotic response. As a result, vast areas of the lungs are gradually affected, and gas exchange is impaired, making it one of the world's leading causes of death. This can be attributed to a lack of understanding of the onset and progression of the disease, as well as a poor understanding of the mechanism of adverse responses to various factors, such as exposure to allergens, nanomaterials, environmental pollutants, etc. So far, the most frequently used preclinical evaluation paradigm for PF is still animal testing. Nonetheless, there is an urgent need to understand the factors that induce PF and find novel therapeutic targets for PF in humans. In this regard, robust and realistic in vitro fibrosis models are required to understand the mechanism of adverse responses. Over the years, several in vitro and ex vivo models have been developed with the goal of mimicking the biological barriers of the lung as closely as possible. This review summarizes recent progress towards the development of experimental models suitable for predicting fibrotic responses, with an emphasis on cell culture methods, nanomaterials, and a comparison of results from studies using cells from various species.

Multiomics reveal unique signatures of human epiploic adipose tissue related to systemic insulin resistance

OBJECTIVE

Human white adipose tissue (AT) is a metabolically active organ with distinct depot-specific functions. Despite their locations close to the gastrointestinal tract, mesenteric AT and epiploic AT (epiAT) have only scarcely been investigated. Here, we aim to characterise these ATs in-depth and estimate their contribution to alterations in whole-body metabolism.

DESIGN

Mesenteric, epiploic, omental and abdominal subcutaneous ATs were collected from 70 patients with obesity undergoing Roux-en-Y gastric bypass surgery. The metabolically well-characterised cohort included nine subjects with insulin sensitive (IS) obesity, whose AT samples were analysed in a multiomics approach, including methylome, transcriptome and proteome along with samples from subjects with insulin resistance (IR) matched for age, sex and body mass index (n=9). Findings implying differences between AT depots in these subgroups were validated in the entire cohort (n=70) by quantitative real-time PCR.

RESULTS

While mesenteric AT exhibited signatures similar to those found in the omental depot, epiAT was distinct from all other studied fat depots. Multiomics allowed clear discrimination between the IS and IR states in all tissues. The highest discriminatory power between IS and IR was seen in epiAT, where profound differences in the regulation of developmental, metabolic and inflammatory pathways were observed. Gene expression levels of key molecules involved in AT function, metabolic homeostasis and inflammation revealed significant depot-specific differences with epiAT showing the highest expression levels.

CONCLUSION

Multi-omics epiAT signatures reflect systemic IR and obesity subphenotypes distinct from other fat depots. Our data suggest a previously unrecognised role of human epiploic fat in the context of obesity, impaired insulin sensitivity and related diseases.

An inter-laboratory effort to harmonize the cell-delivered in vitro dose of aerosolized materials

Air-liquid interface (ALI) lung cell models cultured on permeable transwell inserts are increasingly used for respiratory hazard assessment requiring controlled aerosolization and deposition of any material on ALI cells. The approach presented herein aimed to assess the transwell insert-delivered dose of aerosolized materials using the VITROCELL® Cloud12 system, a commercially available aerosol-cell exposure system. An inter-laboratory comparison study was conducted with seven European partners having different levels of experience with the VITROCELL® Cloud12. A standard operating procedure (SOP) was developed and applied by all partners for aerosolized delivery of materials, i.e., a water-soluble molecular substance (fluorescence-spiked salt) and two poorly soluble particles, crystalline silica quartz (DQ₁₂) and titanium dioxide nanoparticles (TiO₂ NM-105). The material dose delivered to transwell inserts was quantified with spectrofluorometry (fluorescein) and with the quartz crystal microbalance (QCM) integrated in the VITROCELL® Cloud12 system. The shape and agglomeration state of the deposited particles were confirmed with transmission electron microscopy (TEM). Inter-laboratory comparison of the device-specific performance was conducted in two steps, first for molecular substances (fluorescein-spiked salt), and then for particles. Device- and/or handling-specific differences in aerosol deposition of VITROCELL® Cloud12 systems were characterized in terms of the so-called deposition factor (DF), which allows for prediction of the transwell insert-deposited particle dose from the particle concentration in the aerosolized suspension. Albeit DF varied between the different labs from 0.39 to 0.87 (mean (coefficient of variation (CV)): 0.64 (28%)), the QCM of each VITROCELL® Cloud 12 system accurately measured the respective transwell insert-deposited dose. Aerosolized delivery of DQ₁₂ and TiO₂ NM-105 particles showed good linearity (R² > 0.95) between particle concentration of the aerosolized suspension and QCM-determined insert-delivered particle dose. The VITROCELL® Cloud 12 performance for DQ₁₂ particles was identical to that for fluorescein-spiked salt, i.e., the ratio of measured and salt-predicted dose was 1.0 (29%). On the other hand, a ca. 2-fold reduced dose was observed for TiO₂ NM-105 (0.54 (41%)), which was likely due to partial retention of TiO₂ NM-105 agglomerates in the vibrating mesh nebulizer of the VITROCELL® Cloud12. This inter-laboratory comparison demonstrates that the QCM integrated in the VITROCELL® Cloud 12 is a reliable tool for dosimetry, which accounts for potential variations of the transwell insert-delivered dose due to device-, handling- and/or material-specific effects. With the detailed protocol presented herein, all seven partner laboratories were able to demonstrate dose-controlled aerosolization of material suspensions using the VITROCELL® Cloud12 exposure system at dose levels relevant for observing in vitro hazard responses. This is an important step towards regulatory approved implementation of ALI lung cell cultures for in vitro hazard assessment of aerosolized materials.

Surface Treatment With Hydrophobic Coating Reagents (Organosilanes) Strongly Reduces the Bioactivity of Synthetic Amorphous Silica in vitro

Synthetic amorphous silica (SAS) is industrially relevant material whose bioactivity in vitro is strongly diminished, for example, by protein binding to the particle surface. Here, we investigated the in vitro bioactivity of fourteen SAS (pyrogenic, precipitated, or colloidal), nine of which were surface-treated with organosilanes, using alveolar macrophages as a highly sensitive test system. Dispersion of the hydrophobic SAS required pre-wetting with ethanol and extensive ultrasonic treatment in the presence of 0.05% BSA (Protocol 1). Hydrophilic SAS was suspended by moderate ultrasonic treatment (Protocol 2) and also by Protocol 1. The suspensions were administered to NR8383 alveolar macrophages under serum-free conditions for 16 h, and the release of LDH, GLU, H2O2, and TNFα was measured in cell culture supernatants. While seven surface-treated hydrophobic SAS exhibited virtually no bioactivity, two materials (AEROSIL® R 504 and AEROSIL® R 816) had minimal effects on NR8383 cells. In contrast, non-treated SAS elicited considerable increases in LDH, GLU, and TNFα, while the release of H2O2 was low except for CAB-O-SIL® S17D Fumed Silica. Dispersing hydrophilic SAS with Protocol 1 gradually reduced the bioactivity but did not abolish it. The results show that hydrophobic coating reagents, which bind covalently to the SAS surface, abrogate the bioactivity of SAS even under serum-free in vitro conditions. The results may have implications for the hazard assessment of hydrophobic surface-treated SAS in the lung.

Evaluating the cytotoxicity and pathogenicity of multi-walled carbon nanotube through weighted gene co-expression network analysis: a nanotoxicogenomics study

Background

Multi-walled carbon nanotube (MWCNT) is one of the most momentous carbonaceous nanoparticles which is widely used for various applications such as electronics, vehicles, and therapeutics. However, their possible toxicity and adverse effects convert them into a major health threat for humans and animals.

Results

In this study, we employed weighted gene co-expression network analysis (WGCNA) to identify the co-expressed gene groups and dysregulated pathways due to the MWCNT exposure. For this purpose, three weighted gene co-expression networks for the microarray gene expression profiles of the mouse after 1, 6, and 12-month post-exposure to MWCNT were constructed. The module-trait analysis specified the significant modules related to different doses (1, 10, 40, and 80 µg) of MWCNT. Afterward, common genes between co-regulated and differentially expressed genes were determined. The further pathway analysis highlighted the enrichment of genes including Actb, Ube2b, Psme3, Ezh2, Alas2, S100a10, Ypel5, Rhoa, Rac1, Ube2l6, Prdx2, Ctsb, Bnip3l, Gp6, Myh9, Ube2k, Mbnl1, Kbtbd8, Riok3, Itgb1, Rap1a, and Atp5h in immune-, inflammation-, and protein metabolism-related pathways.

Conclusions

This study discloses the genotoxicity and cytotoxicity effects of various doses of MWCNT which also affect the metabolism system. The identified genes can serve as potential biomarkers and therapeutic candidates. However, further studies should be performed to validate them in human cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01031-3.

How can we justify grouping of nanoforms for hazard assessment? Concepts and tools to quantify similarity

The risk of each nanoform (NF) of the same substance cannot be assumed to be the same, as they may vary in their physicochemical characteristics, exposure and hazard. However, neither can we justify a need for more animal testing and resources to test every NF individually. To reduce the need to test all NFs, (regulatory) information requirements may be fulfilled by grouping approaches. For such grouping to be acceptable, it is important to demonstrate similarities in physicochemical properties, toxicokinetic behaviour, and (eco)toxicological behaviour. The GRACIOUS Framework supports the grouping of NFs, by identifying suitable grouping hypotheses that describe the key similarities between different NFs. The Framework then supports the user to gather the evidence required to test these hypotheses and to subsequently assess the similarity of the NFs within the proposed group. The evidence needed to support a hypothesis is gathered by an Integrated Approach to Testing and Assessment (IATA), designed as decision trees constructed of decision nodes. Each decision node asks the questions and provides the methods needed to obtain the most relevant information. This White paper outlines existing and novel methods to assess similarity of the data generated for each decision node, either via a pairwise analysis conducted property-by-property, or by assessing multiple decision nodes simultaneously via a multidimensional analysis. For the pairwise comparison conducted property-by-property we included in this White paper: The x-fold, Bayesian and Arsinh-OWA distance algorithms performed comparably in the scoring of similarity between NF pairs. The Euclidean distance was also useful, but only with proper data transformation. The x-fold method does not standardize data, and thus produces skewed histograms, but has the advantage that it can be implemented without programming knowhow. A range of multidimensional evaluations, using for example dendrogram clustering approaches, were also investigated. Multidimensional distance metrics were demonstrated to be difficult to use in a regulatory context, but from a scientific perspective were found to offer unexpected insights into the overall similarity of very different materials. In conclusion, for regulatory purposes, a property-by-property evaluation of the data matrix is recommended to substantiate grouping, while the multidimensional approaches are considered to be tools of discovery rather than regulatory methods.

Nanomaterials induce different levels of oxidative stress, depending on the used model system: Comparison of in vitro and in vivo effects

The immense diversity and constant development of nanomaterials (NMs) increase the need for a facilitated risk assessment, which requires knowledge of the modes of action (MoAs) of NMs. This necessitates a comprehensive data basis, which can be obtained using omics. Furthermore, the establishment of suitable in vitro test systems is essential to follow the 3R concept and to cope with the high number of NMs. In the present study, we aimed to compare NM effects in vitro and in vivo using a multi-omics approach. We applied an integrated data analysis strategy based on proteomics and metabolomics to four silica NMs and one titanium dioxide-based NM. For the in vitro investigations, rat alveolar epithelial cells (RLE-6TN) and rat alveolar macrophages (NR8383) were treated with different doses of NMs, and the results were compared with the effects on rat lungs after short-term inhalations and instillations. Since reactive oxygen species (ROS) production has been described as a critical biological effect of NMs, we focused on different levels of oxidative stress. Thus, we found opposite changes in proteins and metabolites related to the production of reduced glutathione in alveolar epithelial cells and alveolar macrophages, demonstrating that the MoAs of NMs depend on the model system used. Interestingly, in vivo, pathways related to inflammation were more affected than oxidative stress responses. Hence, the assignment of the observed effects to levels of oxidative stress was also different in vitro and in vivo. However, the overall classification of "active" and "passive" NMs was consistent in vitro and in vivo, suggesting that both cell lines tested are suitable for the assessment of NM toxicity. In summary, the results presented here highlight the need to carefully review model systems to decipher the extent to which they can replace in vivo assays.

Proteomic Characterization of the Cellular Effects of AhR Activation by Microbial Tryptophan Catabolites in Endotoxin-Activated Human Macrophages

Sensing microbial tryptophan catabolites by the aryl hydrocarbon receptor (AhR) plays a pivotal role in host-microbiome homeostasis by modulating the host immune response. Nevertheless, the involved cellular processes triggered by the metabolites are mainly unknown. Here, we analyzed proteomic changes in macrophages after treatment with the tryptophan metabolites indole-3-acetic acid (I3AA) or indole-3-aldehyde (IAld), as well as the prototypic exogenous AhR-ligand benzo(a)pyrene (BaP) in the absence and presence of lipopolysaccharide (LPS) to identify affected cellular processes and pathways. The AhR-ligands regulated metabolic and immunologic processes in dependency of LPS co-stimulation. All investigated ligands time-dependently enhanced fatty acid β-oxidation. Differences due to the combination with LPS were observed for all three ligands. Additionally, oxidative phosphorylation was significantly increased by IAld and I3AA in a time and LPS-dependent manner. Immunoregulatory processes were affected in distinct ways. While BaP and I3AA up-regulated IL-8 signaling, IL-6 signaling was decreased by IAld. BaP decreased the inflammasome pathway. Thus, AhR-ligand-dependent regulations were identified, which may modulate the response of macrophages to bacterial infections, but also the commensal microbiota through changes in immune cell signaling and metabolic pathways that may also alter functionality. These findings highlight the relevance of AhR for maintaining microbial homeostasis and, consequently, host health.

The Emerging Plasticizer Alternative DINCH and Its Metabolite MINCH Induce Oxidative Stress and Enhance Inflammatory Responses in Human THP-1 Macrophages

The use of the plasticizer bis(2-ethylhexyl)phthalate (DEHP) and other plasticizers in the manufacture of plastic products has been restricted due to adverse health outcomes such as obesity, metabolic syndrome, and asthma, for which inflammation has been described to be a driving factor. The emerging alternative plasticizer 1,2-cyclohexanedioic acid diisononyl ester (DINCH) still lacks information regarding its potential effects on the immune system. Here, we investigated the effects of DINCH and its naturally occurring metabolite monoisononylcyclohexane-1,2-dicarboxylic acid ester (MINCH) on the innate immune response. Human THP-1 macrophages were exposed to 10 nM–10 μM DINCH or MINCH for 4 h, 16 h, and 24 h. To decipher the underlying mechanism of action, we applied an untargeted proteomic approach that revealed xenobiotic-induced activation of immune-related pathways such as the nuclear factor κB (NF-κB) signaling pathway. Key drivers were associated with oxidative stress, mitochondrial dysfunction, DNA damage repair, apoptosis, and autophagy. We verified increased reactive oxygen species (ROS) leading to cellular damage, NF-κB activation, and subsequent TNF and IL-1β release, even at low nM concentrations. Taken together, DINCH and MINCH induced cellular stress and pro-inflammatory effects in macrophages, which may lead to adverse health effects.

Genotoxicity and Gene Expression in the Rat Lung Tissue following Instillation and Inhalation of Different Variants of Amorphous Silica Nanomaterials (aSiO2 NM)

Several reports on amorphous silica nanomaterial (aSiO2 NM) toxicity have been questioning their safety. Herein, we investigated the in vivo pulmonary toxicity of four variants of aSiO2 NM: SiO2_15_Unmod, SiO2_15_Amino, SiO2_7 and SiO2_40. We focused on alterations in lung DNA and protein integrity, and gene expression following single intratracheal instillation in rats. Additionally, a short-term inhalation study (STIS) was carried out for SiO2_7, using TiO2_NM105 as a benchmark NM. In the instillation study, a significant but slight increase in oxidative DNA damage in rats exposed to the highest instilled dose (0.36 mg/rat) of SiO2_15_Amino was observed in the recovery (R) group. Exposure to SiO2_7 or SiO2_40 markedly increased oxidative DNA lesions in rat lung cells of the exposure (E) group at every tested dose. This damage seems to be repaired, since no changes compared to controls were observed in the R groups. In STIS, a significant increase in DNA strand breaks of the lung cells exposed to 0.5 mg/m3 of SiO2_7 or 50 mg/m3 of TiO2_NM105 was observed in both groups. The detected gene expression changes suggest that oxidative stress and/or inflammation pathways are likely implicated in the induction of (oxidative) DNA damage. Overall, all tested aSiO2 NM were not associated with marked in vivo toxicity following instillation or STIS. The genotoxicity findings for SiO2_7 from instillation and STIS are concordant; however, changes in STIS animals were more permanent/difficult to revert.

A Multi-Omics Analysis of Mucosal-Associated-Invariant T Cells Reveals Key Drivers of Distinct Modes of Activation

The function of mucosal-associated invariant T (MAIT) cells highly depends on the mode of activation, either by recognition of bacterial metabolites via their T cell receptor (TCR) or in a TCR-independent manner via cytokines. The underlying molecular mechanisms are not entirely understood. To define the activation of MAIT cells on the molecular level, we applied a multi-omics approach with untargeted transcriptomics, proteomics and metabolomics. Transcriptomic analysis of E. coli- and TCR-activated MAIT cells showed a distinct transcriptional reprogramming, including altered pathways, transcription factors and effector molecules. We validated the consequences of this reprogramming on the phenotype by proteomics and metabolomics. Thus, and to distinguish between TCR-dependent and -independent activation, MAIT cells were stimulated with IL12/IL18, anti-CD3/CD28 or both. Only a combination of both led to full activation of MAIT cells, comparable to activation by E. coli. Using an integrated network-based approach, we identified key drivers of the distinct modes of activation, including cytokines and transcription factors, as well as negative feedback regulators like TWIST1 or LAG3. Taken together, we present novel insights into the biological function of MAIT cells, which may represent a basis for therapeutic approaches to target MAIT cells in pathological conditions.

An environmental ecocorona influences the formation and evolution of the biological corona on the surface of single-walled carbon nanotubes

Nanomaterials (NMs) taken up from the environment carry a complex ecocorona consisting of dissolved organic matter. An ecocorona is assumed to influence the interactions between NMs and endogenous biomolecules and consequently affects the formation of a biological corona (biocorona) and the biological fate of the NMs. This study shows that biomolecules in fish plasma attach immediately (within <5 min) to the surface of SWCNTs and the evolution of the biocorona is a size dependent phenomenon. Quantitative proteomics data revealed that the nanotube size also influences the plasma protein composition on the surface of SWCNTs. The presence of a pre-attached ecocorona on the surface of SWCNTs eliminated the influence of nanotube size on the formation and evolution of the biocorona. Over time, endogenous biomolecules from the plasma partially replaced the pre-attached ecocorona as measured using a fluorescently labelled ecocorona. The presence of an ecocorona offers a unique surface composition to each nanotube. This suggests that understanding the biological fate of NMs taken up from the environment by organisms to support the environmental risk assessment of NMs is a challenging task because each NM may have a unique surface composition in the body of an organism.

The gut bacterium Extibacter muris produces secondary bile acids and influences liver physiology in gnotobiotic mice

Extibacter muris is a newly described mouse gut bacterium which metabolizes cholic acid (CA) to deoxycholic acid (DCA) via 7α-dehydroxylation. Although bile acids influence metabolic and inflammatory responses, few in vivo models exist for studying their metabolism and impact on the host. Mice were colonized from birth with the simplified community Oligo-MM12 with or without E. muris. As the metabolism of bile acids is known to affect lipid homeostasis, mice were fed either a low- or high-fat diet for eight weeks before sampling and analyses targeting the gut and liver. Multiple Oligo-MM12 strains were capable of deconjugating primary bile acids in vitro. E. muris produced DCA from CA either as pure compound or in mouse bile. This production was inducible by CA in vitro. Ursodeoxycholic, chenodeoxycholic, and β-muricholic acid were not metabolized under the conditions tested. All gnotobiotic mice were stably colonized with E. muris, which showed higher relative abundances after HF diet feeding. The presence of E. muris had minor, diet-dependent effects on Oligo-MM12 communities. The secondary bile acids DCA and surprisingly LCA and their taurine conjugates were detected exclusively in E. muris-colonized mice. E. muris colonization did not influence body weight, white adipose tissue mass, liver histopathology, hepatic aspartate aminotransferase, or blood levels of cholesterol, insulin, and paralytic peptide (PP). However, proteomics revealed shifts in hepatic pathways involved in amino acid, glucose, lipid, energy, and drug metabolism in E. muris-colonized mice. Liver fatty acid composition was substantially altered by dietary fat but not by E. muris.In summary, E. muris stably colonized the gut of mice harboring a simplified community and produced secondary bile acids, which affected proteomes in the liver. This new gnotobiotic mouse model can now be used to study the pathophysiological role of secondary bile acids in vivo.

Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages

Insights into the modes of action (MoAs) of xenobiotics are of utmost importance for the definition of adverse outcome pathways (AOPs), which are essential for a mechanism-based risk assessment. A well-established strategy to reveal MoAs of xenobiotics is the use of omics. However, often an even more comprehensive approach is needed, which can be achieved using multi-omics. Since the immune system plays a central role in the defense against foreign substances and pathogens, with the innate immune system building a first barrier, we systematically reviewed multi-omics studies investigating the effects of xenobiotics on macrophages. Surprisingly, only nine publications were identified, combining proteomics with transcriptomics or metabolomics. We summarized pathways and single proteins, transcripts, or metabolites, which were described to be affected upon treatment with xenobiotics in the reviewed studies, thus revealing a broad range of effects. In summary, we show that macrophages are a relevant model system to investigate the toxicological effects induced by xenobiotics. Furthermore, the multi-omics approaches led to a more comprehensive overview compared to only one omics layer with slight advantages for combinations that complement each other directly, e.g., proteome and metabolome.

Comparison of quantitation methods in proteomics to define relevant toxicological information on AhR activation of HepG2 cells by BaP

The application of quantitative proteomics provides a new and promising tool for standardized toxicological research. However, choosing a suitable quantitative method still puzzles many researchers because the optimal method needs to be determined. In this study, we investigated the advantages and limitations of two of the most commonly used global quantitative proteomics methods, namely label-free quantitation (LFQ) and tandem mass tags (TMT). As a case study, we exposed hepatocytes (HepG2) to the environmental contaminant benzo[a]pyrene (BaP) using a concentration of 2 μM. Our results revealed that both methods yield a similar proteome coverage, in which for LFQ a wider range of fold changes was observed but with less significant p-values compared to TMT. We detected 37 and 47 significantly enriched pathways by LFQ and TMT, respectively, with 17 overlapping pathways. To define the minimally required effort in proteomics as a benchmark, we artificially reduced the LFQ, and TMT data sets stepwise and compared the pathway enrichment. Thereby, we found that fewer proteins are necessary for detecting significant enrichment of pathways in TMT compared to LFQ, which might be explained by the higher reproducibility of the TMT data that was observed. In summary, we showed that the TMT approach is the preferable one when investigating toxicological questions because it offers a high reproducibility and sufficient proteome coverage in a comparably short time.

Multiparametric Profiling of Engineered Nanomaterials: Unmasking the Surface Coating Effect

Despite considerable efforts, the properties that drive the cytotoxicity of engineered nanomaterials (ENMs) remain poorly understood. Here, the authors inverstigate a panel of 31 ENMs with different core chemistries and a variety of surface modifications using conventional in vitro assays coupled with omics-based approaches. Cytotoxicity screening and multiplex-based cytokine profiling reveals a good concordance between primary human monocyte-derived macrophages and the human monocyte-like cell line THP-1. Proteomics analysis following a low-dose exposure of cells suggests a nonspecific stress response to ENMs, while microarray-based profiling reveals significant changes in gene expression as a function of both surface modification and core chemistry. Pathway analysis highlights that the ENMs with cationic surfaces that are shown to elicit cytotoxicity downregulated DNA replication and cell cycle responses, while inflammatory responses are upregulated. These findings are validated using cell-based assays. Notably, certain small, PEGylated ENMs are found to be noncytotoxic yet they induce transcriptional responses reminiscent of viruses. In sum, using a multiparametric approach, it is shown that surface chemistry is a key determinant of cellular responses to ENMs. The data also reveal that cytotoxicity, determined by conventional in vitro assays, does not necessarily correlate with transcriptional effects of ENMs.

Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures

Biological organisms are constantly exposed to an immense repertoire of molecules that cover environmental or food-derived molecules and drugs, triggering a continuous flow of stimuli-dependent adaptations. The diversity of these chemicals as well as their concentrations contribute to the multiplicity of induced effects, including activation, stimulation, or inhibition of physiological processes and toxicity. Metabolism, as the foremost phenotype and manifestation of life, has proven to be immensely sensitive and highly adaptive to chemical stimuli. Therefore, studying the effect of endo- or xenobiotics over cellular metabolism delivers valuable knowledge to apprehend potential cellular activity of individual molecules and evaluate their acute or chronic benefits and toxicity. The development of modern metabolomics technologies such as mass spectrometry or nuclear magnetic resonance spectroscopy now offers unprecedented solutions for the rapid and efficient determination of metabolic profiles of cells and more complex biological systems. Combined with the availability of well-established cell culture techniques, these analytical methods appear perfectly suited to determine the biological activity and estimate the positive and negative effects of chemicals in a variety of cell types and models, even at hardly detectable concentrations. Metabolic phenotypes can be estimated from studying intracellular metabolites at homeostasis in vivo, while in vitro cell cultures provide additional access to metabolites exchanged with growth media. This article discusses analytical solutions available for metabolic phenotyping of cell culture metabolism as well as the general metabolomics workflow suitable for testing the biological activity of molecular compounds. We emphasize how metabolic profiling of cell supernatants and intracellular extracts can deliver valuable and complementary insights for evaluating the effects of xenobiotics on cellular metabolism. We note that the concepts and methods discussed primarily for xenobiotics exposure are widely applicable to drug testing in general, including endobiotics that cover active metabolites, nutrients, peptides and proteins, cytokines, hormones, vitamins, etc.

Mitochondrial Transfer by Human Mesenchymal Stromal Cells Ameliorates Hepatocyte Lipid Load in a Mouse Model of NASH

Mesenchymal stromal cell (MSC) transplantation ameliorated hepatic lipid load; tissue inflammation; and fibrosis in rodent animal models of non-alcoholic steatohepatitis (NASH) by as yet largely unknown mechanism(s). In a mouse model of NASH; we transplanted bone marrow-derived MSCs into the livers; which were analyzed one week thereafter. Combined metabolomic and proteomic data were applied to weighted gene correlation network analysis (WGCNA) and subsequent identification of key drivers. Livers were analyzed histologically and biochemically. The mechanisms of MSC action on hepatocyte lipid accumulation were studied in co-cultures of hepatocytes and MSCs by quantitative image analysis and immunocytochemistry. WGCNA and key driver analysis revealed that NASH caused the impairment of central carbon; amino acid; and lipid metabolism associated with mitochondrial and peroxisomal dysfunction; which was reversed by MSC treatment. MSC improved hepatic lipid metabolism and tissue homeostasis. In co-cultures of hepatocytes and MSCs; the decrease of lipid load was associated with the transfer of mitochondria from the MSCs to the hepatocytes via tunneling nanotubes (TNTs). Hence; MSCs may ameliorate lipid load and tissue perturbance by the donation of mitochondria to the hepatocytes. Thereby; they may provide oxidative capacity for lipid breakdown and thus promote recovery from NASH-induced metabolic impairment and tissue injury.

Toxicity of TiO2 Nanoparticles: Validation of Alternative Models

There are many studies concerning titanium dioxide (TiO₂) nanoparticles (NP) toxicity. Nevertheless, there are few publications comparing in vitro and in vivo exposure, and even less comparing air–liquid interface exposure (ALI) with other in vitro and in vivo exposures. The identification and validation of common markers under different exposure conditions are relevant for the development of smart and quick nanotoxicity tests. In this work, cell viability was assessed in vitro by WST-1 and LDH assays after the exposure of NR8383 cells to TiO₂ NP sample. To evaluate in vitro gene expression profile, NR8383 cells were exposed to TiO₂ NP during 4 h at 3 cm² of TiO₂ NP/cm² of cells or 19 μg/mL, in two settings—submerged cultures and ALI. For the in vivo study, Fischer 344 rats were exposed by inhalation to a nanostructured aerosol at a concentration of 10 mg/m³, 6 h/day, 5 days/week for 4 weeks. This was followed immediately by gene expression analysis. The results showed a low cytotoxic potential of TiO₂ NP on NR8383 cells. Despite the absence of toxicity at the doses studied, the different exposures to TiO₂ NP induce 18 common differentially expressed genes (DEG) which are involved in mitosis regulation, cell proliferation and apoptosis and inflammation transport of membrane proteins. Among these genes, we noticed the upregulation of Ccl4, Osm, Ccl7 and Bcl3 genes which could be suggested as early response biomarkers after exposure to TiO₂ NP. On the other hand, the comparison of the three models helped us to validate the alternative ones, namely submerged and ALI approaches.