A multi-omics approach reveals mechanisms of nanomaterial toxicity and structure–activity relationships in alveolar macrophages

Size-Dependent Cytotoxicity and Multi-Omic Changes Induced by Amorphous Silicon Nanoparticles in HepG2 Cells

(1) Background: Silica nanoparticles (SiO2 NPs) have a high potential for human exposure and tend to accumulate in the liver. This study aimed to explore the size-dependent cytotoxicity induced by SiO2 NPs and identify key molecular pathways at the in vitro level through proteomics, metabolomics, and a combination of multiple omics methods. (2) Methods: The human hepatoma cells (HepG2) cells were exposed to SiO2 NPs of three different sizes (60, 250, and 400 nm) at doses of 0, 12.5, 25, 50, 100, and 200 μg/mL for 24 h. (3) Results: Exposure to 60 nm SiO2 NPs induced more reduction in cell viability than the other two larger-scale particles. Changes in the metabolomic and proteomic profiles of HepG2 cells induced by SiO2 NPs were also size-dependent. The main pathways that were significantly affected in the 60 nm SiO2 NPs treatment group represented cholesterol metabolism in proteomics and central carbon metabolism in metabolomics. Moreover, common enrichment pathways between differential proteins and metabolites included protein digestion and absorption and vitamin digestion and absorption. (4) Conclusions: Exposure to SiO2 NPs could induce size-dependent cytotoxicity and changes in proteomics and metabolomics, probably mainly by interfering with energy metabolism pathways.

Progress in toxicogenomics to protect human health

Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.

Nanotoxicology: developments and new insights

The use of nanoparticles (NPs) in treatment of diseases have increased exponentially recently, giving rise to the science of nanomedicine. The safety of these NPs in humans has also led to the science of nanotoxicology. Due to a dearth of both readily available models and precise bio-dispersion characterization techniques, nanotoxicological research has obviously been constrained. However, the ensuing years were notable for the emergence of improved synthesis methods and characterization tools. Major advances have been made in linking certain physical variables, paralleling improvements in characterization size, shape, or coating factors to the resulting physiological reactions. Although significant progress has been a contribution to the development of nanotoxicology, however, it faces numerous difficulties and technical constraints distinct from those of conventional toxicological assessment as it attempts to improve the therapeutic effects of medicines. Determining thorough characterization standards, standardizing dosimetry, assessing the kinetics of ions dissolving and enhancing the accuracy of in vitro-in vivo correlation efficiency, also defining restrictions on exposure protection are some of the most important and pressing concerns. This article will explore the past advancement and potential prospects of nanotoxicology, standard models, emphasizing significant findings from earlier studies and examining current challenges, giving insight on the way forward.

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.

Towards characterization of cell culture conditions for reliable proteomic analysis: in vitro studies on A549, differentiated THP-1, and NR8383 cell lines

Proteomic investigations result in high dimensional datasets, but integration or comparison of different studies is hampered by high variances due to different experimental setups. In addition, cell culture conditions can have a huge impact on the outcome. This study systematically investigates the impact of experimental parameters on the proteomic profiles of commonly used cell lines-A549, differentiated THP-1 macrophage-like cells, and NR8383-for toxicity studies. The work focuses on analyzing the influence at the proteome level of cell culture setup involving different vessels, cell passage numbers, and post-differentiation harvesting time, aiming to improve the reliability of proteomic analyses for hazard assessment. Mass-spectrometry-based proteomics was utilized for accurate protein quantification by means of a label-free approach. Our results showed that significant proteome variations occur when cells are cultivated under different setups. Further analysis of these variations revealed their association to specific cellular pathways related to protein misfolding, oxidative stress, and proteasome activity. Conversely, the influence of cell passage numbers on the proteome is minor, suggesting a reliable range for conducting reproducible biological replicates. Notable, substantial proteome alterations occur over-time post-differentiation of dTHP-1 cells, particularly impacting pathways crucial for macrophage function. This finding is key for the interpretation of experimental results. These results highlight the need for standardized culture conditions in proteomic-based evaluations of treatment effects to ensure reliable results, a prerequisite for achieving regulatory acceptance of proteomics data.

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.

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.

A bibliometric analysis of the recent achievements in pulmonary safety of nanoparticles

Assessing research activity is an important step for planning future initiatives oriented toward filling the remaining gaps in a field. Therefore, the objective of the current study was to review recently published research on pulmonary toxicity caused by nanomaterials. However, here, instead of reviewing possible toxic effects and discussing their mode of action, the goal was to establish trends considering for example examined so far nanomaterials or used testing strategies. A total of 2316 related articles retrieved from the three most cited databases (PubMed Scopus, Web of Science), selected based on the title and abstract requirements, were used as the source of the review. Based on the bibliometric analysis, the nano-meter metal oxides, and carbon-based nanotubes were identified as the most frequently studied nanomaterials, while quantum dots, which might induce possible harmful effects, were not considered so far. The majority of testing of pulmonary safety is based on in vitro studies with observed growth of the contribution of novel testing strategies, such as 3D lung model, air-liquid interface system, or omic analysis.

Oxidation is an underappreciated post-translational modification in the regulation of immune responses associated with changes in phosphorylation

Although macrophages are known to be affected by their redox status, oxidation is not yet a well-recognized post-translational modification (PTM) in regulating macrophages and immune cells in general. While it has been described that the redox status of single cysteines in specific proteins is relevant for macrophage functions, global oxidation information is scarce. Hence, we globally assessed the impact of oxidation on macrophage activation using untargeted proteomics and PTM-omics. We exposed THP-1 macrophages to lipopolysaccharide (LPS) for 4 h and 24 h and applied a sequential iodoTMT labeling approach to get information on overall oxidation as well as reversible oxidation of cysteines. Thus, we identified 10452 oxidation sites, which were integratively analyzed with 5057 proteins and 7148 phosphorylation sites to investigate their co-occurance with other omics layers. Based on this integrative analysis, we found significant upregulation of several immune-related pathways, e.g. toll-like receptor 4 (TLR4) signaling, for which 19 proteins, 7 phosphorylation sites, and 39 oxidation sites were significantly affected, highlighting the relevance of oxidations in TLR4-induced macrophage activation. Co-regulation of oxidation and phosphorylation was observed, as evidenced by multiply modified proteins related to inflammatory pathways. Additionally, we observed time-dependent effects, with differences in the dynamics of oxidation sites compared to proteins and phosphorylation sites. Overall, this study highlights the importance of oxidation in regulating inflammatory processes and provides a method that can be readily applied to study the cellular redoxome globally.

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.

Di-(2-ethylhexyl) phthalate substitutes accelerate human adipogenesis through PPARγ activation and cause oxidative stress and impaired metabolic homeostasis in mature adipocytes

The obesity pandemic is presumed to be accelerated by endocrine disruptors such as phthalate-plasticizers, which interfere with adipose tissue function. With the restriction of the plasticizer di-(2-ethylhexyl)-phthalate (DEHP), the search for safe substitutes gained importance. Focusing on the master regulator of adipogenesis and adipose tissue functionality, the peroxisome proliferator-activated receptor gamma (PPARγ), we evaluated 20 alternative plasticizers as well as their metabolites for binding to and activation of PPARγ and assessed effects on adipocyte lipid accumulation. Among several compounds that showed interaction with PPARγ, the metabolites MINCH, MHINP, and OH-MPHP of the plasticizers DINCH, DINP, and DPHP exerted the highest adipogenic potential in human adipocytes. These metabolites and their parent plasticizers were further analyzed in human preadipocytes and mature adipocytes using cellular assays and global proteomics. In preadipocytes, the plasticizer metabolites significantly increased lipid accumulation, enhanced leptin and adipsin secretion, and upregulated adipogenesis-associated markers and pathways, in a similar pattern to the PPARγ agonist rosiglitazone. Proteomics of mature adipocytes revealed that both, the plasticizers and their metabolites, induced oxidative stress, disturbed lipid storage, impaired metabolic homeostasis, and led to proinflammatory and insulin resistance promoting adipokine secretion. In conclusion, the plasticizer metabolites enhanced preadipocyte differentiation, at least partly mediated by PPARγ activation and, together with their parent plasticizers, affected the functionality of mature adipocytes similar to reported effects of a high-fat diet. This highlights the need to further investigate the currently used plasticizer alternatives for potential associations with obesity and the metabolic syndrome.

Alternatives for the worse: Molecular insights into adverse effects of bisphenol a and substitutes during human adipocyte differentiation

Bisphenol A (BPA), which is used in a variety of consumer-related plastic products, was reported to cause adverse effects, including disruption of adipocyte differentiation, interference with obesity mechanisms, and impairment of insulin- and glucose homeostasis. Substitute compounds are increasingly emerging but are not sufficiently investigated.We aimed to investigate the mode of action of BPA and four of its substitutes during the differentiation of human preadipocytes to adipocytes and their molecular interaction with peroxisome proliferator-activated receptor γ (PPARγ), a pivotal regulator of adipogenesis.Binding and effective biological activation of PPARγ were investigated by surface plasmon resonance and reporter gene assay, respectively. Human preadipocytes were continuously exposed to BPA, BPS, BPB, BPF, BPAF, and the PPARγ-antagonist GW9662. After 12 days of differentiation, lipid production was quantified via Oil Red O staining, and global protein profiles were assessed using LC-MS/MS-based proteomics. All tested bisphenols bound to human PPARγ with similar efficacy as the natural ligand 15d-PGJ2in vitroand provoked an antagonistic effect on PPARγ in the reporter gene assay at non-cytotoxic concentrations. During the differentiation of human preadipocytes, all bisphenols decreased lipid production. Global proteomics displayed a down-regulation of adipogenesis and metabolic pathways, similar to GW9662. Interestingly, pro-inflammatory pathways were up-regulated, MCP1 release was increased, and adiponectin decreased. pAKT/AKT ratios revealed significantly reduced insulin sensitivity by BPA, BPB, and BPS upon insulin stimulation.Thus, our results show that not only BPA but also its substitutes disrupt crucial metabolic functions and insulin signaling in adipocytes under low, environmentally relevant concentrations. This effect, mediated through inhibition of PPARγ, may promote hypertrophy of adipose tissue and increase the risk of developing metabolic syndrome, including insulin resistance.

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.

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.

Machine learning-integrated omics for the risk and safety assessment of nanomaterials

With the advancement in nanotechnology, we are experiencing transformation in world order with deep insemination of nanoproducts from basic necessities to advanced electronics, health care products and medicines. Therefore, nanoproducts, however, can have negative side effects and must be strictly monitored to avoid negative outcomes. Future toxicity and safety challenges regarding nanomaterial incorporation into consumer products, including rapid addition of nanomaterials with diverse functionalities and attributes, highlight the limitations of traditional safety evaluation tools. Currently, artificial intelligence and machine learning algorithms are envisioned for enhancing and improving the nano-bio-interaction simulation and modeling, and they extend to the post-marketing surveillance of nanomaterials in the real world. Thus, hyphenation of machine learning with biology and nanomaterials could provide exclusive insights into the perturbations of delicate biological functions after integration with nanomaterials. In this review, we discuss the potential of combining integrative omics with machine learning in profiling nanomaterial safety and risk assessment and provide guidance for regulatory authorities as well.

Proteomics in systems toxicology

Proteins are the ultimate product of gene expression. As they hinge between gene transcription and phenotype, they offer a more realistic perspective of toxicopathic effects, responses and even susceptibility to insult than targeting genes and mRNAs while dodging some inter-individual variability that hinders measuring downstream endpoints like metabolites or enzyme activity. Toxicologists have long focused on proteins as biomarkers but the advent of proteomics shifted risk assessment from narrow single-endpoint analyses to whole-proteome screening, enabling deriving protein-centric adverse outcome pathways (AOPs), which are pivotal for the derivation of Systems Biology informally named Systems Toxicology. Especially if coupled pathology, the identification of molecular initiating events (MIEs) and AOPs allow predictive modeling of toxicological pathways, which now stands as the frontier for the next generation of toxicologists. Advances in mass spectrometry, bioinformatics, protein databases and top-down proteomics create new opportunities for mechanistic and effects-oriented research in all fields, from ecotoxicology to pharmacotoxicology.

Recent advances in development of nanomedicines for multiple sclerosis diagnosis

Multiple sclerosis (MS) is a neurodegenerative disease with a high morbidity and disease burden. It is characterized by the loss of the myelin sheath, resulting in the disruption of neuron electrical signal transmissions and sensory and motor ability deficits. The diagnosis of MS is crucial to its management, but the diagnostic sensitivity and specificity are always a challenge. To overcome this challenge, nanomedicines have recently been employed to aid the diagnosis of MS with an improved diagnostic efficacy. Advances in nanomedicine-based contrast agents in magnetic resonance imaging scanning of MS lesions, and nanomedicine-derived sensors for detecting biomarkers in the cerebrospinal fluid biopsy, or analyzing the composition of exhaled breath gas, have demonstrated the potential of using nanomedicines in the accurate diagnosis of MS. This review aims to provide an overview of recent advances in the application of nanomedicines for the diagnosis of MS and concludes with perspectives of using nanomedicines for the development of safe and effective MS diagnostic nanotools.

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.

Direct Observations of Silver Nanowire-Induced Frustrated Phagocytosis among NR8383 Lung Alveolar Macrophages

The interaction of long nanowires and living cells is directly related to nanowires' nanotoxicity and health impacts. Interactions of silver nanowires (AgNWs) and macrophage cell lines (NR8383) were investigated using laser scanning confocal microscopy and single cell compression (SCC). With high-resolution imaging and mechanics measurement of individual cells, AgNW-induced frustrated phagocytosis was clearly captured in conjunction with structural and property changes of cells. While frustrated phagocytosis is known for long microwires and long carbon nanotubes, this work reports first direct observations of frustrated phagocytosis of AgNWs among living cells in situ. In the case of partial penetration of AgNWs into NR8383 cells, confocal imaging revealed actin participation at the entry sites, whose behavior differs from microwire-induced frustrated phagocytosis. The impacts of frustrated phagocytosis on the cellular membrane and cytoskeleton were also quantified by measuring the mechanical properties using SCC. Taken collectively, this study reveals the structural and property characteristics of nanowire-induced frustrated phagocytosis, which deepens our understanding of nanowire-cell interactions and nanocytotoxicity.

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.

Physicochemical characterization and genotoxicity of the broad class of carbon nanotubes and nanofibers used or produced in U.S. facilities

BACKGROUND

Carbon nanotubes and nanofibers (CNT/F) have known toxicity but simultaneous comparative studies of the broad material class, especially those with a larger diameter, with computational analyses linking toxicity to their fundamental material characteristics was lacking. It was unclear if all CNT/F confer similar toxicity, in particular, genotoxicity. Nine CNT/F (MW #1-7 and CNF #1-2), commonly found in exposure assessment studies of U.S. facilities, were evaluated with reported diameters ranging from 6 to 150 nm. All materials were extensively characterized to include distributions of physical dimensions and prevalence of bundled agglomerates. Human bronchial epithelial cells were exposed to the nine CNT/F (0-24 μg/ml) to determine cell viability, inflammation, cellular oxidative stress, micronuclei formation, and DNA double-strand breakage. Computational modeling was used to understand various permutations of physicochemical characteristics and toxicity outcomes.

RESULTS

Analyses of the CNT/F physicochemical characteristics illustrate that using detailed distributions of physical dimensions provided a more consistent grouping of CNT/F compared to using particle dimension means alone. In fact, analysis of binning of nominal tube physical dimensions alone produced a similar grouping as all characterization parameters together. All materials induced epithelial cell toxicity and micronuclei formation within the dose range tested. Cellular oxidative stress, DNA double strand breaks, and micronuclei formation consistently clustered together and with larger physical CNT/F dimensions and agglomerate characteristics but were distinct from inflammatory protein changes. Larger nominal tube diameters, greater lengths, and bundled agglomerate characteristics were associated with greater severity of effect. The portion of tubes with greater nominal length and larger diameters within a sample was not the majority in number, meaning a smaller percentage of tubes with these characteristics was sufficient to increase toxicity. Many of the traditional physicochemical characteristics including surface area, density, impurities, and dustiness did not cluster with the toxicity outcomes.

CONCLUSION

Distributions of physical dimensions provided more consistent grouping of CNT/F with respect to toxicity outcomes compared to means only. All CNT/F induced some level of genotoxicity in human epithelial cells. The severity of toxicity was dependent on the sample containing a proportion of tubes with greater nominal lengths and diameters.

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.

Surface atomic arrangement of nanomaterials affects nanotoxicity

Understanding the roles of the properties of nanomaterials in biological interactions is a key issue in their safe applications, but the surface atomic arrangement, as an important property of engineered nanomaterials (ENMs), remains largely unknown. Herein, the interfacial interactions (affinity sites and intensity) between monolayer MoS₂ and zebrafish embryos mediated by 1 T phase surface atomic arrangement (octahedral coordination) and the 2H phase surface atomic arrangement (triangular prism coordination) MoS₂ nanosheets were studied. 1 T-MoS₂ first bound to phosphate and then proteins on the chorion, while the adhesion of 2H-MoS₂ occurred in the opposite order. The binding affinity of 2H-MoS₂ with embryos was higher than that of 1 T-MoS₂, and the former material changed the protein structure from β-sheets to turns and bends and random coils. Compared to 1 T-MoS₂, 2H-MoS₂ more readily entered embryos, which was facilitated by caveolae-mediated endocytosis, and caused higher developmental toxicity. Furthermore, metabolic pathways related to amino acid and protein biosynthesis and energy metabolism were affected by the nanomaterial surface atomic arrangements. The above results provide insights into the designs, applications and risk assessments of nanomaterials by the surface atomic arrangement regulation.

Influence of Size and Phase on the Biodegradation, Excretion, and Phytotoxicity Persistence of Single-Layer Molybdenum Disulfide

The increasing applications of single-layer molybdenum disulfide (SLMoS₂) pose great potential risks associated with environmental exposure. This study found that metallic-phase SLMoS₂ with nanoscale (N-1T-SLMoS₂, ∼400 nm) and microscale (M-1T-SLMoS₂, ∼3.6 μm) diameters at 10-25 mg/L induced significant algal growth inhibition (maximum 72.7 and 74.6%, respectively), plasmolysis, and oxidative damage, but these alterations were recoverable. Nevertheless, membrane permeability, chloroplast damage, and chlorophyll biosynthesis reduction were persistent. By contrast, the growth inhibition (maximum 55.3%) and adverse effects of nano-sized semiconductive-phase SLMoS₂ (N-2H-SLMoS₂, ∼400 nm) were weak and easily alleviated after 96 h of recovery. N-1T-SLMoS₂ (0.011 μg/h) and N-2H-SLMoS₂ (0.008 μg/h) were quickly biodegraded to soluble Mo compared with M-1T-SLMoS₂ (0.004 μg/h) and excreted by algae. Incomplete biodegradation of SLMoS₂ (26.8-43.9%) did not significantly mitigate its toxicity. Proteomics and metabolomics indicated that the downregulation of proteins (50.7-99.2%) related to antioxidants and photosynthesis and inhibition of carbon fixation and carbohydrate metabolism contributed to the persistent phytotoxicity. These findings highlight the roles and mechanisms of the size and phase in the persistent phytotoxicity of SLMoS₂, which has potential implications for risk assessment and environmental applications of nanomaterials.