A new Transcriptional Effect Level Index (TELI) for toxicogenomics-based toxicity assessment

Face mask derived micro(nano)plastics and organic compounds potentially induce threat to aquatic ecosystem security revealed by toxicogenomics-based assay

Micro(nano)plastics widely detected in aquatic environments have caused serious threat to water quality security. However, as a potential important source of micro(nano)plastics in surface water during the COVID-19 pandemic, the ecological risks of face mask waste to aquatic environments remain poorly understood. Herein, we comprehensively characterized the micro(nano)plastics and organic compounds released from four daily used face masks in aqueous environments and further evaluated their potential impacts on aquatic ecosystem safety by quantitative genotoxicity assay. Results from spectroscopy and high-resolution mass spectrum showed that plastic microfibers/particles (∼11%-83%) and leachable organic compounds (∼15%-87%) were dominantly emitted pollutants, which were significantly higher than nanoplastics (< ∼5%) based on mass of carbon. Additionally, a toxicogenomics approach using green fluorescence protein-fused whole-cell array revealed that membrane stress was the primary response upon the exposure to micro(nano)plastics, whereas the emitted organic chemicals were mainly responsible for DNA damage involving most of the DNA repair pathways (e.g., base/nucleotide excision repair, mismatch repair, double-strand break repair), implying their severe threat to membrane structure and DNA replication of microorganisms. Therefore, the persistent release of discarded face masks derived pollutants might exacerbate water quality and even adversely affect aquatic microbial functions. These findings would contribute to unraveling the potential effects of face mask waste on aquatic ecosystem security and highlight the necessity for more developed management regulations in face mask disposal.

Acute impact of salinity and C/N ratio on the formation and properties of soluble microbial products from activated sludge

The present study investigated the shock of NaCl and C/N ratio on properties of soluble microbial products (SMPs), focusing on their sized fractions. The results indicated that the NaCl stress increased the content of biopolymers, humic substances, building blocks, and LMW substances in SMPs, while the addition of 40 g NaCl L^-1 significantly changed their relative abundance in SMPs. The acute impact of both N-rich and N-deficient conditions accelerated the secretion of SMPs, but the characteristics of LMW substances differed. Meanwhile, the bio-utilization of SMPs has been enhanced with the increase of NaCl dosage but decreased with the increase of the C/N ratio. The mass balance of sized fractions in SMPs + EPS could be set up when NaCl dosage <10 g/L and C/N ratio >5, which indicates the hydrolysis of sized fractions in EPS mainly compensated for their increase/reduction in SMPs. Besides, the results of the toxic assessment indicated that the oxidative damage caused by the NaCl shock was an important factor affecting the property of SMPs, and the abnormal expression of DNA transcription cannot be neglected for bacteria metabolisms with the change of C/N ratio.

The toxicity assessment of 14 biocides for industrial circulating cooling water system by damage/repair pathway profiling analysis

The toxicity of 14 biocides commonly used in circulating cooling water systems were evaluated. Results showed that biocide exposure can induce complex damage/repair pathways, including DNA, oxidative, protein, general, and membrane stress. All damages enhanced with increasing concentrations. Among them, MTC exhibited toxicity at concentrations as low as 1.00×10^-17mg/L, and TELI_total reached 1.60. We derived molecular toxicity endpoints based on dose-response curves to compare the normalized toxicity of biocides. Total-TELI_1.5 exhibited that THPS, MTC, and DBNPA have the lowest toxic exposure concentrations, which are 2.180×10^-27, 1.015×10^-14, and 3.523×10^-6 mg/L. TBTC, MTC, and 2,4-DCP had the highest Total-TELI_max values, which are 861.70, 526.30, and 248.30. Moreover, there was a high correlation (R²=0.43~0.97) between biocides' molecular structure and toxicity. And, biocide exposure combinations were found to increase toxicity pathways and enhance toxic effects, with a similar toxicity mechanism observed as in single-component exposure.

UV-induced microplastics (MPs) aging leads to comprehensive toxicity

Herein, the toxicity of 4 MPs and additives released from MPs during UV-aging was quantitatively evaluated by the transcriptional effect level index (TELI) based on E. coli whole-cell microarray assay, and MPs-antibiotics complex pollutants. Results showed that MPs and these additives had high toxicity potential, the maximum TELI was 5.68/6.85 for polystyrene (PS)/bis(2-ethylhexyl) phthalate (DEHP). There were many similar toxic pathways between MPs and additives, indicating that part of the toxicity risk of MPs was caused by the release of additives. MPs were compounded with antibiotics, the toxicity value changed significantly. The TELI values of amoxicillin (AMX) + polyvinyl chloride (PVC) and ciprofloxacin (CIP) + PVC were as high as 12.30 and 14.58 (P < 0.05). Three antibiotics all decreased the toxicity of PS and had little effect on polypropylene (PP) and polyethylene (PE). The combined toxicity mechanism of MPs and antibiotics was very complicated, and the results could be divided into four types: MPs (PVC/PE + CIP), antibiotics (PVC + TC, PS + AMX/ tetracycline (TC)/CIP, PE + TC), both (PP + AMX/TC/CIP), or brand-new mechanisms (PVC + AMX).

Variation of the toxicity caused by key contaminants in industrial wastewater along the treatment train of Fenton-activated sludge-advanced oxidation processes

Industrial wastewater contains a mixture of refractory and hazardous pollutants that have comprehensive toxic effects. We investigated the treatment of a long-chain industrial wastewater treatment train containing Fenton, biological anoxic/oxic (AO), and heterogeneous ozone catalytic oxidation (HOCO) processes, and evaluated their detoxification effect based on the analysis of the genic toxicity of some key contaminants. The results showed that although the effluent met the discharge standard in terms of traditional quality parameters, the long-chain treatment process could not effectively detoxify the industrial wastewater. The analysis results of summer samples showed that the Fenton process increased the total toxicity and genotoxicity of the organics, concerned metals, and non-volatile pollutants, whereas the A/O process increased the toxicity of the organics and non-volatile pollutants, and the HOCO process led to higher toxicity caused by metals and non-volatile pollutants. The outputs of the winter samples indicated that the Fenton process reduced the total toxicity and genotoxicity caused by non-volatile pollutants but increased that of the organics and concerned metals. The effect of the A/O process on the effluent toxicity in winter was the same as that in summer, whereas the HOCO process increased the total toxicity and genotoxicity of the metals in winter samples. Correlation analysis showed that various toxicity stresses were significantly correlated with the variation of these key pollutants in wastewater. Our results could provide a reference for the optimization of industrial wastewater treatment plants (IWTPs) by selecting more suitable treatment procedures to reduce the toxicity of different contaminants.

In vitro toxicity assessment of haloacetamides via a toxicogenomics assay

It is important to study the stress effects and mechanisms of haloacetamide (HAcAm) disinfection byproducts to reveal their health hazards. In this context, toxicological g was applied to evaluate the effects of four HAcAms, revealing the status of gene expression on Escherichia coli in different stress response types (oxidative, protein, membrane, general, DNA). This study revealed that the main toxic action modes of these HAcAms were general and membrane stresses by high-resolution, real-time gene expression profiling combined with clustering analysis. The results of time-gene evaluation showed that the presence of chloroacetamide (CAcAm) and bromoacetamide (BAcAm) generated more reactive oxygen species, thus activating oxidative stress. Trichloroacetamide (tCAcAm) induced altered expression of glutathione marker genes and membrane stress-related genes, and iodoacetamide (IAcAm) caused severe DNA damage by damaging DNA strands and individual nucleotides mainly through damage to nucleic acids and bases. Furthermore, quantitative structure-activity relationship (QSAR) modelling results indicated that the biological activities of HAcAms were related to their quantum chemical and topological properties.

Integration of leave-one-out method and real-time live cell reporter array system to assess the toxicity of mixtures

The ever-increasing number of chemicals and complex mixtures demands a time-saving and cost-effective platform for environmental risk assessment. However, there is limit promising tool for evaluating the contribution of each component to the total toxicity effects of the mixture. Here, four widely distributed environmental pollutants with different mode-of-actions, i.e., cadmium chloride (Cd), nitrofurazone (NFZ), triclosan (TCS), and tris(2-chloroethyl) phosphate (TCEP), were selected as components of artificial mixture. Integration of leave-one-out method and high-dimensional live cell array system was used to explore relative contribution of each component from the mixture. A quaternary mixture (All_4_chems) and four ternary mixtures (Leave_Cd, Leave_NFZ, Leave_TCS and Leave_TCEP) were investigated by Escherichia coli (E. coli) live cell array system with 90 environmental stress genes modified by green fluorescent protein (GFP) expressing reporter vectors. E. coli cytotoxicity tests demonstrated that TCS has antagonism effect with other three chemicals (Cd, NFZ and TCEP), while it was additive effect in other three binary combinations. A total of 26, 23, 13, 31 and 23 genes were significantly altered with fold-change greater than 2 over the 4 h exposure by All_4_chems, Leave_Cd, Leave_NFZ, Leave_TCS and Leave_TCEP, respectively. Clustering analysis based on time-series gene expression patterns and transcriptional effect level index (TELI) showed that Leave_TCEP has similar profiles with All_4_chems, demonstrating TCEP has the least contribution among four components to the quaternary mixture. Leave_NFZ has the least number of significantly altered genes, implying NFZ has the largest toxicity effect contribution to the quaternary mixture. The relative contribution in different pathways indicated that Cd has the most contribution to the mixture in redox stress, while TCS has the least contribution in DNA stress pathway. Collectively, our results demonstrated the utility of high-dimensional toxicogenomics data and leave-one-out method in prioritizing the relative contribution of each component in mixture.

Performance Optimization and Toxicity Effects of the Electrochemical Oxidation of Octogen

Octogen (HMX) is widely used as a high explosive and constituent in plastic explosives, nuclear devices, and rocket fuel. The direct discharge of wastewater generated during HMX production threatens the environment. In this study, we used the electrochemical oxidation (EO) method with a PbO2-based anode to treat HMX wastewater and investigated its degradation performance, mechanism, and toxicity evolution under different conditions. The results showed that HMX treated by EO could achieve a removal efficiency of 81.2% within 180 min at a current density of 70 mA/cm2, Na2SO4 concentration of 0.25 mol/L, interelectrode distance of 1.0 cm, and pH of 5.0. The degradation followed pseudo-first-order kinetics (R2 > 0.93). The degradation pathways of HMX in the EO system have been proposed, including cathode reduction and indirect oxidation by •OH radicals. The molecular toxicity level (expressed as the transcriptional effect level index) of HMX wastewater first increased to 1.81 and then decreased to a non-toxic level during the degradation process. Protein and oxidative stress were the dominant stress categories, possibly because of the intermediates that evolved during HMX degradation. This study provides new insights into the electrochemical degradation mechanisms and molecular-level toxicity evolution during HMX degradation. It also serves as initial evidence for the potential of the EO-enabled method as an alternative for explosive wastewater treatment with high removal performance, low cost, and low environmental impact.

Comparing the toxicity of iodinated X-ray contrast media on eukaryote- and prokaryote-based quantified microarray assays

This study compared the toxicity mechanisms of four X-ray-based iodinated contrast media (ICM) on Escherichia coli (E. coli) and yeast microarray assays, aiming to determine the diverse toxicity mechanisms among different exposed organisms and the relationship between toxicity and their physical and chemical characteristics. The conventional phenotypic endpoint cytotoxicity and the change in reactive oxygen species (ROS) level were employed in conjunction with toxicogenomics to quantify changes in the gene/protein biomarker level in the regulation of different damage/repair pathways. The results showed that molecular toxicity endpoints, named transcriptional effect level index (TELI) and protein effect level index (PELI) for E. coli and yeast, respectively, correlated well with the phenotypic endpoints. Temporal altered gene/protein expression profiles revealed dynamic and complex damage/toxic mechanisms. In particular, compared with E. coli cells, yeast cells exposed to ICM exhibited significantly higher stress intensity and diverse stress types, resulting in stress or damage to the organism. The toxic mechanisms of ICM are concentration/property-dependent and relevant to the cellular structure and defense systems in prokaryotes and eukaryotes. In particular, the toxicity of ionic ICM is higher than that of non-ionic ICM, and eukaryotes are more susceptible than prokaryotes to ICM exposure.

Lanthanum and cerium disrupt similar biological pathways and interact synergistically in Triticum aestivum as revealed by metabolomic profiling and quantitative modeling

The industrial and agricultural applications of rare earth elements (REEs) lead to considerable REE emissions into environment. Yet, little is known about the molecular-level effects and interactions of REEs in terrestrial plants. Herein, the individual and joint effects of La and Ce in Triticum aestivum were investigated using mass spectrometry-based metabolomics. Metabolic effect level index (MELI) was utilized as a readable endpoint for quantifying mixture interactions. Exposure to single La/Ce at environmentally relevant levels induced significant dose-dependent metabolic changes. The highly overlap of differential metabolites and perturbed pathways of La and Ce suggested their similar mode of action. Exposure to La-Ce mixtures did not induce additional metabolic pathway perturbation. Specifically, metabolism of amino sugar and nucleotide sugar, starch and sucrose, fructose and mannose, glycerophospholipid and purine were disrupted for both single and binary exposures. These results, together with physiological indicators, point to REE-induced oxidative stress, energy expenditure, DNA damage and membrane disturbance. The MELI calculations showed that La and Ce interacted synergistically at the overall metabolic level, which could be causally linked to synergistic interaction at the individual level (root elongation). This work proved metabolomics could be an important and effective strategy for interpreting toxicity and interactions of REE mixtures.

Multi-omics analysis to reveal disorders of cell metabolism and integrin signaling pathways induced by PM2.5

Atmospheric fine particle pollution is known to cause many adverse health effects. However, the potential mechanisms of PM_2.5-induced cytotoxicity still needs further understanding. Herein, we integrated cytotoxicity, component profiling, metabolomics and proteomics data to deeply explain the biological responses of human bronchial epithelial cells exposed to PM_2.5. We observed that PM_2.5 caused cell cycle arrest, calcium influx, cell damage and further induced cell apoptosis. The contents of heavy metals and 4-6 rings PAHs in PM_2.5 were positively correlated with intracellular ROS, indicating that they might be the important components to induce the above cytotoxicity. Integrated metabolomics and proteomics analysis revealed the significant alterations of many metabolic processes, such as glycolysis, the citric acid cycle, amino acid metabolism and lipid metabolism. Notably, we found that PM_2.5 inhibited the integrin signaling pathway, including down-regulating the protein expression of integrins and the phosphorylation of downstream signaling kinases, which might ultimately affect cell cycle progression, cell metabolism and apoptosis. This study provided a comprehensive data resource for the deep understanding of biological toxicity mechanisms caused by atmospheric fine particles in human lung-bronchial epithelium cells.

Machine learning-based biomarkers identification from toxicogenomics - Bridging to regulatory relevant phenotypic endpoints

One of the major challenges in realization and implementations of the Tox21 vision is the urgent need to establish quantitative link between in-vitro assay molecular endpoint and in-vivo regulatory-relevant phenotypic toxicity endpoint. Current toxicomics approach still mostly rely on large number of redundant markers without pre-selection or ranking, therefore, selection of relevant biomarkers with minimal redundancy would reduce the number of markers to be monitored and reduce the cost, time, and complexity of the toxicity screening and risk monitoring. Here, we demonstrated that, using time series toxicomics in-vitro assay along with machine learning-based feature selection (maximum relevance and minimum redundancy (MRMR)) and classification method (support vector machine (SVM)), an "optimal" number of biomarkers with minimum redundancy can be identified for prediction of phenotypic toxicity endpoints with good accuracy. We included two case studies for in-vivo carcinogenicity and Ames genotoxicity prediction, using 20 selected chemicals including model genotoxic chemicals and negative controls, respectively. The results suggested that, employing the adverse outcome pathway (AOP) concept, molecular endpoints based on a relatively small number of properly selected biomarker-ensemble involved in the conserved DNA-damage and repair pathways among eukaryotes, were able to predict both Ames genotoxicity endpoints and in-vivo carcinogenicity in rats. A prediction accuracy of 76% with AUC = 0.81 was achieved while predicting in-vivo carcinogenicity with the top-ranked five biomarkers. For Ames genotoxicity prediction, the top-ranked five biomarkers were able to achieve prediction accuracy of 70% with AUC = 0.75. However, the specific biomarkers identified as the top-ranked five biomarkers are different for the two different phenotypic genotoxicity assays. The top-ranked biomarkers for the in-vivo carcinogenicity prediction mainly focused on double strand break repair and DNA recombination, whereas the selected top-ranked biomarkers for Ames genotoxicity prediction are associated with base- and nucleotide-excision repair The method developed in this study will help to fill in the knowledge gap in phenotypic anchoring and predictive toxicology, and contribute to the progress in the implementation of tox 21 vision for environmental and health applications.

Effects of a sulfated glycosaminoglycan from Sepia esculenta ink on transcriptional and metabolic profiles of Saccharomyces cerevisiae

Four fractions of water-extracted Sepia esculenta ink polysaccharides (SIP) were separated by dicthylaminoethy (DEAE) cellulose chromatography. The eluted fraction with the highest yield was characterized as a sulfate-rich glycosaminoglycan named SIP-IV. According to the analysis of laser scattering and refractive index signals, SIP-IV was determined to be 14.4 kDa and spherical molecular conformation in salt solution. SIP-IV is composed of fucose, galactosamine, glucosamine, mannose and glucuronic acid with a molar ratio of 5.1:7.3:3.8:1:4.4, which is obviously different from reported SIPs. SIP-IV promoted yeast proliferation and intercellular antioxidant level. Based on multi-omics strategy, data of transcriptome analysis suggested that growth promotion of SIP-IV on Saccharomyces cerevisiae might be attributed to regulation of Rho protein signal transduction, nuclear autophagy and nitrogen utilization. Combined with the metabolome results, SIP-IV also re-profiled metabolism of amino acids and phospholipids in yeast cells.

Multi-omics based strategy for toxicity analysis of acrylamide in Saccharomyces cerevisiae model

Although the toxicity of acrylamide (ACR) has been extensively investigated in different experimental models, its perturbations to multiple nodes of the cellular signaling network have not been systematically associated. In this study, changes at different omics layers in ACR exposed Saccharomyces cerevisiae cells were monitored using a multi-omics strategy. The results of the analysis highlighted the impairment of oxidative-reductive balance, energy metabolism, lipid metabolism, nucleotide metabolism, and ribosome function in yeast cells. Response to acute ACR damage, glutathione synthesis was upregulated, the process of protein degradation was accelerated, and the autophagy flux was initiated. Meanwhile, yeast upregulates gene expression levels of enzymes in carbohydrate metabolism and speeds up the oxidation process of fatty acids to compensate for energy depletion. Importantly, the multi-omics strategy captures features that have rarely been addressed in previous studies on the toxicology of ACR, including blocked de novo nucleotide synthesis, decreased levels of metabolic enzyme cofactors thiamine and D-biotin, increased intracellular concentrations of neurotoxic N-methyl d-aspartic acid and l-glutamic acid, and release of death mediators ceramide. The ACR perturbation network constructed in this work and the discovery of new damage features provide a theoretical basis for subsequent point-to-point toxicological studies.

Effects of emerging pollutants on the occurrence and transfer of antibiotic resistance genes: A review

The emergence and spread of antibiotic resistance genes (ARGs) have become major concerns for both public health and environmental ecosystems. Emerging pollutants (EPs) that accumulate in environmental compartments also pose a potential risk for the enrichment of ARGs in indigenous microorganisms. This paper presents a comprehensive review of the effects and intrinsic mechanisms of EPs, including microplastics, engineered nanomaterials, disinfection byproducts, pharmaceuticals, and personal care products, on the occurrence and dissemination of ARGs. State-of-the-art methods for identifying culture-independent ARG-host interactions and monitoring horizontal gene transfer (HGT) processes in real-time are first reviewed. The contributions of EPs to the abundance and diversity of ARGs are then summarized. Finally, we discussed the underlying mechanisms related to the regulation of HGT, increased mutagenesis, and the evolution of microbial communities. Further details of three HGT (i.e., conjugation, transformation, and transduction) frequency patterns in response to various EPs are also examined. This review contemplates and reassesses the risks of ARG evolution posed by the manufacture and application of EPs.

Dependence of Graphene Oxide (GO) Toxicity on Oxidation Level, Elemental Composition, and Size

The mass production of graphene oxide (GO) unavoidably elevates the chance of human exposure, as well as the possibility of release into the environment with high stability, raising public concern as to its potential toxicological risks and the implications for humans and ecosystems. Therefore, a thorough assessment of GO toxicity, including its potential reliance on key physicochemical factors, which is lacking in the literature, is of high significance and importance. In this study, GO toxicity, and its dependence on oxidation level, elemental composition, and size, were comprehensively assessed. A newly established quantitative toxicogenomic-based toxicity testing approach, combined with conventional phenotypic bioassays, were employed. The toxicogenomic assay utilized a GFP-fused yeast reporter library covering key cellular toxicity pathways. The results reveal that, indeed, the elemental composition and size do exert impacts on GO toxicity, while the oxidation level exhibits no significant effects. The UV-treated GO, with significantly higher carbon-carbon groups and carboxyl groups, showed a higher toxicity level, especially in the protein and chemical stress categories. With the decrease in size, the toxicity level of the sonicated GOs tended to increase. It is proposed that the covering and subsequent internalization of GO sheets might be the main mode of action in yeast cells.

Comparative and mechanistic toxicity assessment of structure-dependent toxicity of carbon-based nanomaterials

The wide application of carbon-based nanomaterials (CNMs) has resulted in the ubiquity of CNMs in the natural environment and they potentially impose adverse consequences on ecosystems and human health. In this study, we comprehensively evaluated and compared potential toxicological effects and mechanisms of seven CNMs in three representative types (carbon blacks, graphene nanoplatelets, and fullerenes), to elucidate the correlation between their physicochemical/structural properties and toxicity. We employed a recently-developed quantitative toxicogenomics-based toxicity testing system with GFP-fused yeast reporter library targeting main cellular stress response pathways, as well as conventional phenotype-based bioassays. The results revealed that DNA damage, oxidative stress, and protein stress were the major mechanisms of action for all the CNMs at sub-cytotoxic concentration levels. The molecular toxicity nature were concentration-dependent, and they exhibited both similarity within the same structural group and distinctiveness among different CNMs, evidencing the structure-driven toxicity of CNMs. The toxic potential based on toxicogenomics molecular endpoints revealed the remarkable impact of size and structure on the toxicity. Furthermore, the phenotypic endpoints derived from conventional phenotype-based bioassays correlated with quantitative molecular endpoints derived from the toxicogenomics assay, suggesting that the selected protein biomarkers captured the main cellular effects that are associated with phenotypic adverse outcomes.

Molecular mechanisms of zooplanktonic toxicity in the okadaic acid-producing dinoflagellate Prorocentrum lima

Prorocentrum lima is a dinoflagellate that forms hazardous blooms and produces okadaic acid (OA), leading to adverse environmental consequences associated with the declines of zooplankton populations. However, little is known about the toxic effects and molecular mechanisms of P. lima or OA on zooplankton. Here, their toxic effects were investigated using the brine shrimp Artemia salina. Acute exposure of A. salina to P. lima resulted in lethality at concentrations 100-fold lower than densities observed during blooms. The first comprehensive results from global transcriptomic and metabolomic analyses in A. salina showed up-regulated mRNA expression of antioxidant enzymes and reduced non-enzyme antioxidants, indicating general detoxification responses to oxidative stress after exposure to P. lima. The significantly up-regulated mRNA expression of proteasome, spliceosome, and ribosome, as well as the increased fatty acid oxidation and oxidative phosphorylation suggested the proteolysis of damaged proteins and induction of energy expenditure. Exposure to OA increased catabolism of chitin, which may further disrupt the molting and reproduction activities of A. salina. Our data shed new insights on the molecular responses and toxicity mechanisms of A. salina to P. lima or OA. The simple zooplankton model integrated with omic methods provides a sensitive assessment approach for studying hazardous algae.

Integration of transcriptomics and metabolomics reveals anlotinib-induced cytotoxicity in colon cancer cells

BACKGROUND

Mounting evidences suggested that anlotinib exhibits effective anti-tumor activity in various cancer types, such as lung cancer, glioblastoma and medullary thyroid cancer. However, its function in colon cancer remains to be further revealed.

METHODS

Colon cancer cells (HCT-116) were treated with or without anlotinib. Transcript and metabolite data were generated through RNA sequencing and liquid chromatography-tandem mass spectrometry, respectively. The integrated analysis transcriptomics and metabolomics was conducted using R programs and online tools, including ClusterProfiler R program, GSEA, Prognoscan and Cytoscape.

RESULTS

We found that differentially expressed genes (DEGs) were mainly involved in metabolic pathways and ribosome pathway. Structural maintenance of chromosome 3 (SMC3), Topoisomerase II alpha (TOP2A) and Glycogen phosphorylase B (PYGB) are the most significant DEGs which bring poor clinical prognosis in colon cancer. The analysis of metabolomics presented that most of the differentially accumulated metabolites (DAMs) were amino acids, such as L-glutamine, DL-serine and aspartic acid. The joint analysis of DEGs and DAMs showed that they were mainly involved in protein digestion and absorption, ABC transporters, central carbon metabolism, choline metabolism and Gap junction. Anlotinib affected protein synthesis and energy supporting of colon cancer cells by regulating amino acid metabolism.

CONCLUSIONS

Anlotinib has a significant effect on colon cancer in both transcriptome and metabolome. Our research will provide possible targets for colon cancer treatment using anlotinib.

TiO2 Nanoparticles Caused DNA Damage in Lung and Extra-Pulmonary Organs Through ROS-Activated FOXO3a Signaling Pathway After Intratracheal Administration in Rats

Introduction

Because of the increased production and application of manufactured Nano-TiO₂ in the past several years, it is important to investigate its potential hazards. TiO₂ is classified by IARC as a possible human carcinogen; however, the potential mechanism of carcinogenesis has not been studied clearly. The present study aimed to investigate the mechanism of DNA damage in rat lung and extra-pulmonary organs caused by TiO₂nanoparticles.

Methods

In the present study, SD rats were exposed to Nano-TiO₂ by intratracheal injection at a dose of 0, 0.2, or 1 g/kg body weight. The titanium levels in tissues were detected by ICP-MS. Western blot was used to detect the protein expression levels. The DNA damage and oxidative stress were detected by comet assay and ROS, MDA, SOD, and GSH-Px levels, respectively.

Results

The titanium levels of the 1 g/kg group on day-3 and day-7 were significantly increased in liver and kidney as well as significantly decreased in lung compared to day-1. ROS and MDA levels were statistically increased, whereas SOD and GSH-Px levels were statistically decreased in tissues of rats in dose-dependent manners after Nano-TiO₂ treatment. PI3K, p-AKT/AKT, and p-FOXO3a/FOXO3a in lung, liver, and kidney activated in dose-dependent manners. The levels of DNA damage in liver, kidney, and lung in each Nano-TiO₂ treatment group were significantly increased and could not recover within 7 days. GADD45α, ChK2, and XRCC1 in liver, kidney, and lung of rats exposed to Nano-TiO₂ statistically increased, which triggered DNA repair.

Conclusion

This work demonstrated that Ti could deposit in lung and enter extra-pulmonary organs of rats and cause oxidative stress, then trigger DNA damage through activating the PI3K-AKT-FOXO3a pathway and then promoting GADD45α, ChK2, and XRCC1 to process the DNA repair.

Impact of heavy metals on the formation and properties of solvable microbiological products released from activated sludge in biological wastewater treatment

This study investigated the acute impact of heavy metals on activated sludge with respect to the amount properties of biopolymers and other solvable microbiological products (SMPs) released from the sludge. Ten heavy metals were selected for the evaluation. Under the experimental conditions, exposing activated sludge to different metals led to an increase in SMPs, with a more significant increase in nitrogenous organics than in carbonaceous ones, where Hg²⁺, Ag⁺, Cu²⁺, and Cr⁶⁺ led to the highest increase in SMP species, while Cd²⁺, Ni²⁺, Mn²⁺, Pb²⁺, and Co²⁺ caused limited increase in the middle and small SMP molecules, and Zn²⁺ and Cr³⁺ resulted in a decrease in SMP content. To probe the molecular impact of heavy metals and the association between cellular stress and SMP formation, the toxicity of heavy metals was evaluated using a toxicogenomics assay. Based on a correlation analysis between the increase in SMP and the molecular toxicity index-transcriptional effect level index (TELI) of different genes under corresponding stress conditions, eight genes demonstrated a strong correlation with SMP properties and were pre-assumed to have the most significant influence on the increment in SMPs. We further validated the correlation equation established to predict SMP production based on the molecular disturbance of the eight key biomarkers, using arsenic As³⁺ and vanadium V⁵⁺ as tests, and by quantifying the amount of SMPs released from the activated sludge under the influence of these metals using a TELI-derived equation. In addition, the heavy metals that generated greater amounts of reactive oxygen species also caused larger increases in SMPs.

Preservatives accelerate the horizontal transfer of plasmid-mediated antimicrobial resistance genes via differential mechanisms

Increasing concentrations of preservatives have been detected in environments due to the overuse and misuse of preservatives in food and personal care products. Recent studies have relied heavily on the toxicity, biodegradability, and fate of preservatives in the environment. However, the biological effects of preservatives on antimicrobial resistance, which poses great threats to public health worldwide, are largely unknown. This study investigated three preservatives for their ability and mechanisms of promoting horizontal transfer of antimicrobial resistance genes (ARGs). The results demonstrated that these preservatives (sodium nitrite, sodium benzoate, and triclocarbon), under daily-use concentrations, led to concentration-dependent increases in conjugative transfer by 1.24-2.63, 6.79-7.05, and 2.17-4.31 folds compared with the control group. Even these three preservatives had different patterns on generating intracellular reactive oxidative species (ROS) and reactive nitrogen species (RNS), all of them could stimulate radical-induced RpoS regulon and SOS response, increase cell membrane permeability, and regulate conjugative transfer-related genes, subsequently promoting horizontal transfer of ARGs. The present results expanded the understanding of biological effects induced by preservatives, and provided mechanistic insight into the preservatives-induced resistance. This study also opens an intriguing question on the roles of emerging contaminants including preservatives in the emerging and spread of ARGs in various environments.

Transcriptomic responses of Artemia salina exposed to an environmentally relevant dose of Alexandrium minutum cells or Gonyautoxin2/3

Toxicities of the marine algae Alexandrium minutum and its excreted gonyautoxins (GTXs) to the marine crustacean Artemia salina were investigated. Mortality was observed for neither larvae nor adult A. salina exposed to A. minutum at a density of 5000 cells/mL or 0.5 μM GTX2/3. After exposure, the full transcriptome of adult A. salina was assembled and functionally annotated. A total of 599,286 transcripts were obtained, which were clustered into 515,196 unigenes. Results of the transcriptional effect level index revealed that direct exposure to the toxic algae A. minutum caused greater alterations in the transcriptome than did exposure to the extracellular product GTX2/3. Mechanisms of effects were different between exposure of A. salina to A. minutum cells or GTX2/3. Exposure to A. minutum modulated formation of the ribonucleoprotein complex and metabolism of amino acids and lipids in A. salina. Exposure to GTX2/3 exposure inhibited expression of genes related to metabolism of chitin, which might result in disruption of molting process or disturbed sheath morphogenesis. Overall, effects on transcription observed in this study represent the first report based on application of next generation sequencing techniques to investigate the transcriptomic response of A. salina exposed to an environmentally realistic level of A. minutum or GTX2/3.

Chemometric Evaluation of the Link between Acute Toxicity, Health Issues and Physicochemical Properties of Silver Nanoparticles

The present study’s objective is to focus on some developments in the field of statistical models of a complex system, like nanoparticles responses in the environmental media. An important problem that still needs to be studied and interpreted is the relations between physicochemical parameters of the nanoparticles like primary size, primary hydrophobic diameter, zeta potential, etc. with respective toxicity values. It holds true especially for silver nanoparticle systems due to their known bactericidal effect and wide distribution in practice. The present study deals with the data for physicochemical and toxicity parameters of 94 different silver nanoparticle systems in order to reveal specific relations between physicochemical properties and acute toxicity readings using multivariate statistical methods. Searching for these specific relationships between physicochemical parameters and toxicity responses is the novel element in the present study. This has focused our study toward developing a model that describes the relationship between physicochemical properties and toxicity of silver NPs based on a dataset gathered from the literature. It is shown that the systems studied could be divided into four patterns (clusters) of similarity depending not only on the physicochemical indicators related to particles size but also by their acute toxicity. The acute toxicity is strongly correlated to the zeta potential of the particles if the whole data set is considered.

The response of Escherichia coli to the alkylating agents chloroacetaldehyde and styrene oxide

DNA damage is ubiquitous and can arise from endogenous or exogenous sources. DNA-damaging alkylating agents are present in environmental toxicants as well as in cancer chemotherapy drugs and are a constant threat, which can lead to mutations or cell death. All organisms have multiple DNA repair and DNA damage tolerance pathways to resist the potentially negative effects of exposure to alkylating agents. In bacteria, many of the genes in these pathways are regulated as part of the SOS reponse or the adaptive response. In this work, we probed the cellular responses to the alkylating agents chloroacetaldehyde (CAA), which is a metabolite of 1,2-dichloroethane used to produce polyvinyl chloride, and styrene oxide (SO), a major metabolite of styrene used in the production of polystyrene and other polymers. Vinyl chloride and styrene are produced on an industrial scale of billions of kilograms annually and thus have a high potential for environmental exposure. To identify stress response genes in E. coli that are responsible for tolerance to the reactive metabolites CAA and SO, we used libraries of transcriptional reporters and gene deletion strains. In response to both alkylating agents, genes associated with several different stress pathways were upregulated, including protein, membrane, and oxidative stress, as well as DNA damage. E. coli strains lacking genes involved in base excision repair and nucleotide excision repair were sensitive to SO, whereas strains lacking recA and the SOS gene ybfE were sensitive to both alkylating agents tested. This work indicates the varied systems involved in cellular responses to alkylating agents, and highlights the specific DNA repair genes involved in the responses.

Arsenic Reduces Gene Expression Response to Changing Salinity in Killifish

Toxicogenomic approaches can detect and classify adverse interactions between environmental toxicants and other environmental stressors but require more complex experimental designs and analytical approaches. Here we use novel toxicogenomic techniques to analyze the effect of arsenic exposure in wild killifish populations acclimating to changing salinity. Fish from three populations were acclimated to full strength seawater and transferred to fresh water for 1 or 24 h. Linear models of gene expression in gill tissue identified 31 genes that responded to osmotic shock at 1 h and 178 genes that responded at 24 h. Arsenic exposure (100 μg/L) diminished the responses (reaction norms) of these genes by 22% at 1 h ( p = 1.0 × 10^-6) and by 10% at 24 h ( p = 3.0 × 10^-10). Arsenic also significantly reduced gene coregulation in gene regulatory networks ( p = 0.002, paired Levene's test), and interactions between arsenic and salinity acclimation were uniformly antagonistic at the biological pathway level ( p < 0.05, binomial test). Arsenic's systematic interference with gene expression reaction norms was validated in a mouse multistressor experiment, demonstrating the ability of these toxicogenomic approaches to identify biologically relevant adverse interactions between environmental toxicants and other environmental stressors.

Genotoxicity Assessment of Drinking Water Disinfection Byproducts by DNA Damage and Repair Pathway Profiling Analysis

Genotoxicity is considered a major concern for drinking water disinfection byproducts (DBPs). Of over 700 DBPs identified to date, only a small number has been assessed with limited information for DBP genotoxicity mechanism(s). In this study, we evaluated genotoxicity of 20 regulated and unregulated DBPs applying a quantitative toxicogenomics approach. We used GFP-fused yeast strains that examine protein expression profiling of 38 proteins indicative of all known DNA damage and repair pathways. The toxicogenomics assay detected genotoxicity potential of these DBPs that is consistent with conventional genotoxicity assays end points. Furthermore, the high-resolution, real-time pathway activation and protein expression profiling, in combination with clustering analysis, revealed molecular level details in the genotoxicity mechanisms among different DBPs and enabled classification of DBPs based on their distinct DNA damage effects and repair mechanisms. Oxidative DNA damage and base alkylation were confirmed to be the main molecular mechanisms of DBP genotoxicity. Initial exploration of QSAR modeling using moleular genotoxicity end points (PELI) suggested that genotoxicity of DBPs in this study was correlated with topological and quantum chemical descriptors. This study presents a toxicogenomics-based assay for fast and efficient mechanistic genotoxicity screening and assessment of a large number of DBPs. The results help to fill in the knowledge gap in the understanding of the molecular mechanisms of DBP genotoxicity.

Multiple-endpoints gene alteration-based (MEGA) assay: A toxicogenomics approach for water quality assessment of wastewater effluents

Wastewater effluents contain a significant number of toxic contaminants, which, even at low concentrations, display a wide variety of toxic actions. In this study, we developed a multiple-endpoints gene alteration-based (MEGA) assay, a real-time PCR-based transcriptomic analysis, to assess the water quality of wastewater effluents for human health risk assessment and management. Twenty-one genes from the human hepatoblastoma cell line (HepG2), covering the basic health-relevant stress responses such as response to xenobiotics, genotoxicity, and cytotoxicity, were selected and incorporated into the MEGA assay. The genes related to the p53-mediated DNA damage response and cytochrome P450 were selected as markers for genotoxicity and response to xenobiotics, respectively. Additionally, the genes that were dose-dependently regulated by exposure to the wastewater effluents were chosen as markers for cytotoxicity. The alterations in the expression of an individual gene, induced by exposure to the wastewater effluents, were evaluated by real-time PCR and the results were validated by genotoxicity (e.g., comet assay) and cell-based cytotoxicity tests. In summary, the MEGA assay is a real-time PCR-based assay that targets cellular responses to contaminants present in wastewater effluents at the transcriptional level; it is rapid, cost-effective, and high-throughput and can thus complement any chemical analysis for water quality assessment and management.

Subinhibitory Concentrations of Disinfectants Promote the Horizontal Transfer of Multidrug Resistance Genes within and across Genera

The greater abundances of antibiotic resistance genes (ARGs) in point-of-use tap and reclaimed water than that in freshly treated water raise the question whether residual disinfectants in distribution systems facilitate the spread of ARGs. This study investigated three widely used disinfectants (free chlorine, chloramine, and hydrogen peroxide) on promoting ARGs transfer within Escherichia coli strains and across genera from Escherichia coli to Salmonella typhimurium. The results demonstrated that subinhibitory concentrations (lower than minimum inhibitory concentrations [MICs]) of these disinfectants, namely 0.1-1 mg/L Cl₂ for free chlorine, 0.1-1 mg/L Cl₂ for chloramine, and 0.24-3 mg/L H₂O₂, led to concentration-dependent increases in intragenera conjugative transfer by 3.4-6.4, 1.9-7.5, and 1.4-5.4 folds compared with controls, respectively. By comparison, the intergenera conjugative frequencies were slightly increased by approximately 1.4-2.3 folds compared with controls. However, exposure to disinfectants concentrations higher than MICs significantly suppressed conjugative transfer. This study provided evidence and insights into possible underlying mechanisms for enhanced conjugative transfer, which involved intracellular reactive oxygen species formation, SOS response, increased cell membrane permeability, and altered expressions of conjugation-relevant genes. The results suggest that certain oxidative chemicals, such as disinfectants, accelerate ARGs transfer and therefore justify motivations in evaluating disinfection alternatives for controlling antibiotic resistance. This study also triggers questions regarding the potential role of environmental chemicals in the global spread of antibiotic resistance.

A Quantitative Toxicogenomics Assay for High-throughput and Mechanistic Genotoxicity Assessment and Screening of Environmental Pollutants

The ecological and health concern of mutagenicity and carcinogenicity potentially associated with an overwhelmingly large and ever-increasing number of chemicals demands for cost-effective and feasible method for genotoxicity screening and risk assessment. This study proposed a genotoxicity assay using GFP-tagged yeast reporter strains, covering 38 selected protein biomarkers indicative of all the seven known DNA damage repair pathways. The assay was applied to assess four model genotoxic chemicals, eight environmental pollutants and four negative controls across six concentrations. Quantitative molecular genotoxicity end points were derived based on dose response modeling of a newly developed integrated molecular effect quantifier, Protein Effect Level Index (PELI). The molecular genotoxicity end points were consistent with multiple conventional in vitro genotoxicity assays, as well as with in vivo carcinogenicity assay results. Further more, the proposed genotoxicity end point PELI values quantitatively correlated with both comet assay in human cell and carcinogenicity potency assay in mice, providing promising evidence for linking the molecular disturbance measurements to adverse outcomes at a biological relevant level. In addition, the high-resolution DNA damaging repair pathway alternated protein expression profiles allowed for chemical clustering and classification. This toxicogenomics-based assay presents a promising alternative for fast, efficient and mechanistic genotoxicity screening and assessment of drugs, foods, and environmental contaminants.

Water Disinfection Byproducts Induce Antibiotic Resistance-Role of Environmental Pollutants in Resistance Phenomena

The spread of antibiotic resistance represents a global threat to public health, and has been traditionally attributed to extensive antibiotic uses in clinical and agricultural applications. As a result, researchers have mostly focused on clinically relevant high-level resistance enriched by antibiotics above the minimal inhibitory concentrations (MICs). Here, we report that two common water disinfection byproducts (chlorite and iodoacetic acid) had antibiotic-like effects that led to the evolution of resistant E. coli strains under both high (near MICs) and low (sub-MIC) exposure concentrations. The subinhibitory concentrations of DBPs selected strains with resistance higher than those evolved under above-MIC exposure concentrations. In addition, whole-genome analysis revealed distinct mutations in small sets of genes known to be involved in multiple drug and drug-specific resistance, as well as in genes not yet identified to play role in antibiotic resistance. The number and identities of genetic mutations were distinct for either the high versus low sub-MIC concentrations exposure scenarios. This study provides evidence and mechanistic insight into the sub-MIC selection of antibiotic resistance by antibiotic-like environmental pollutants such as disinfection byproducts in water, which may be important contributors to the spread of global antibiotic resistance. The results from this study open an intriguing and profound question on the roles of large amount and various environmental contaminants play in selecting and spreading the antibiotics resistance in the environment.

Microbial reporter gene assay as a diagnostic and early warning tool for the detection and characterization of toxic pollution in surface waters

Surface water samples constantly receive a vast mixture of micropollutants mainly originating from wastewater treatment plants (WWTPs). High-throughput live cell arrays provide a promising method for the characterization of the effects of chemicals and the associated molecular mechanisms. In the present study, this test system was evaluated for the first time for the characterization of a set of typical surface water extracts receiving effluent from WWTPs. The extracts containing complex mixtures of micropollutants were analyzed for the expression of 90 stress responsive genes in the Escherichia coli reporter gene assay. The most affected pathways and the genes most sensitive to surface water samples suggested prominent stress-responsive pathways for wastewater-impacted surface water, such as oxidative stress, DNA damage, and drug resistance. Samples strongly affecting particular pathways were identified by statistical analysis of gene expression. Transcription data were correlated with contamination data from chemical screening and percentages of wastewater in the samples. Samples with particular effects and outstanding chemical composition were analyzed. For these samples, hypotheses on the alteration of the transcription of genes involved in drug resistance and DNA repair attributable to the presence of pharmaceuticals were drawn.

High-throughput concentration-response analysis for omics datasets

Omics-based methods are increasingly used in current ecotoxicology. Therefore, a large number of observations for various toxic substances and organisms are available and may be used for identifying modes of action, adverse outcome pathways, or novel biomarkers. For these purposes, good statistical analysis of toxicogenomic data is vital. In contrast to established ecotoxicological techniques, concentration-response modeling is rarely used for large datasets. Instead, statistical hypothesis testing is prevalent, which provides only a limited scope for inference. The present study therefore applied automated concentration-response modeling for 3 different ecotoxicotranscriptomic and ecotoxicometabolomic datasets. The modeling process was performed by simultaneously applying 9 different regression models, representing distinct mechanistic, toxicological, and statistical ideas that result in different curve shapes. The best-fitting models were selected by using Akaike's information criterion. The linear and exponential models represented the best data description for more than 50% of responses. Models generating U-shaped curves were frequently selected for transcriptomic signals (30%), and sigmoid models were identified as best fit for many metabolomic signals (21%). Thus, selecting the models from an array of different types seems appropriate, because concentration-response functions may vary because of the observed response type, and they also depend on the compound, the organism, and the investigated concentration and exposure duration range. The application of concentration-response models can help to further tap the potential of omics data and is a necessary step for quantitative mixture effect assessment at the molecular response level.

Metabolic Effect Level Index Links Multivariate Metabolic Fingerprints to Ecotoxicological Effect Assessment

A major goal of ecotoxicology is the prediction of adverse outcomes for populations from sensitive and early physiological responses. A snapshot of the physiological state of an organism can be provided by metabolic fingerprints. However, to inform chemical risk assessment, multivariate metabolic fingerprints need to be converted to readable end points suitable for effect estimation and comparison. The concentration- and time-dependent responsiveness of metabolic fingerprints to the PS-II inhibitor isoproturon was investigated by use of a Myriophyllum spicatum bioassay. Hydrophilic and lipophilic leaf extracts were analyzed with gas chromatography-mass spectrometry (GC-MS) and preprocessed with XCMS. Metabolic changes were aggregated in the quantitative metabolic effect level index (MELI), allowing effect estimation from Hill-based concentration-response models. Hereby, the most sensitive response on the concentration scale was revealed by the hydrophilic MELI, followed by photosynthetic efficiency and, 1 order of magnitude higher, by the lipophilic MELI and shoot length change. In the hydrophilic MELI, 50% change compares to 30% inhibition of photosynthetic efficiency and 10% inhibition of dry weight change, indicating effect development on different response levels. In conclusion, aggregated metabolic fingerprints provide quantitative estimates and span a broad response spectrum, potentially valuable for establishing adverse outcome pathways of chemicals in environmental risk assessment.

Toxicity Assessment of 4-Methyl-1-cyclohexanemethanol and Its Metabolites in Response to a Recent Chemical Spill in West Virginia, USA

The large-scale chemical spill on January 9, 2014 from coal processing and cleaning storage tanks of Freedom Industries in Charleston affected the drinking water supply to 300,000 people in Charleston, West Virginia metropolitan, while the short-term and long-term health impacts remain largely unknown and need to be assessed and monitored. There is a lack of publically available toxicological information for the main contaminant 4-methyl-1-cyclohexanemethanol (4-MCHM). Particularly, little is known about 4-MCHM metabolites and their toxicity. This study reports timely and original results of the mechanistic toxicity assessment of 4-MCHM and its metabolites via a newly developed quantitative toxicogenomics approach, employing proteomics analysis in yeast cells and transcriptional analysis in human cells. These results suggested that, although 4-MCHM is considered only moderately toxic based on the previous limited acute toxicity evaluation, 4-MCHM metabolites were likely more toxic than 4-MCHM in both yeast and human cells, with different toxicity profiles and potential mechanisms. In the yeast library, 4-MCHM mainly induced chemical stress related to transmembrane transport and transporter activity, while 4-MCHM metabolites of S9 mainly induced oxidative stress related to antioxidant activity and oxidoreductase activity. With human A549 cells, 4-MCHM mainly induced DNA damage-related biomarkers, which indicates that 4-MCHM is related to genotoxicity due to its DNA damage effect on human cells and therefore warrants further chronic carcinogenesis evaluation.

Toxicity mechanisms identification via gene set enrichment analysis of time-series toxicogenomics data: impact of time and concentration

The advance in high-throughput "toxicogenomics" technologies, which allows for concurrent monitoring of cellular responses globally upon exposure to chemical toxicants, presents promises for next-generation toxicity assessment. It is recognized that cellular responses to toxicants have a highly dynamic nature, and exhibit both temporal complexity and dose-response shifts. Most current gene enrichment or pathway analysis lack the recognition of the inherent correlation within time series data, and may potentially miss important pathways or yield biased and inconsistent results that ignore dynamic patterns and time-sensitivity. In this study, we investigated the application of two score metrics for GSEA (gene set enrichment analysis) to rank the genes that consider the temporal gene expression profile. One applies a novel time series CPCA (common principal components analysis) to generate scores for genes based on their contributions to the common temporal variation among treatments for a given chemical at different concentrations. Another one employs an integrated altered gene expression quantifier-TELI (transcriptional effect level index) that integrates altered gene expression magnitude over the exposure time. By comparing the GSEA results using two different ranking metrics for examining the dynamic responses of reporter cells treated with various dose levels of three model toxicants, mitomycin C, hydrogen peroxide, and lead nitrate, the analysis identified and revealed different toxicity mechanisms of these chemicals that exhibit chemical-specific, as well as time-aware and dose-sensitive nature. The ability, advantages, and disadvantages of varying ranking metrics were discussed. These findings support the notion that toxicity bioassays should account for the cells' complex dynamic responses, thereby implying that both data acquisition and data analysis should look beyond simple traditional end point responses.

NanoE-Tox: New and in-depth database concerning ecotoxicity of nanomaterials

The increasing production and use of engineered nanomaterials (ENMs) inevitably results in their higher concentrations in the environment. This may lead to undesirable environmental effects and thus warrants risk assessment. The ecotoxicity testing of a wide variety of ENMs rapidly evolving in the market is costly but also ethically questionable when bioassays with vertebrates are conducted. Therefore, alternative methods, e.g., models for predicting toxicity mechanisms of ENMs based on their physico-chemical properties (e.g., quantitative (nano)structure-activity relationships, QSARs/QNARs), should be developed. While the development of such models relies on good-quality experimental toxicity data, most of the available data in the literature even for the same test species are highly variable. In order to map and analyse the state of the art of the existing nanoecotoxicological information suitable for QNARs, we created a database NanoE-Tox that is available as Supporting Information File 1. The database is based on existing literature on ecotoxicology of eight ENMs with different chemical composition: carbon nanotubes (CNTs), fullerenes, silver (Ag), titanium dioxide (TiO2), zinc oxide (ZnO), cerium dioxide (CeO2), copper oxide (CuO), and iron oxide (FeO x ; Fe2O3, Fe3O4). Altogether, NanoE-Tox database consolidates data from 224 articles and lists altogether 1,518 toxicity values (EC50/LC50/NOEC) with corresponding test conditions and physico-chemical parameters of the ENMs as well as reported toxicity mechanisms and uptake of ENMs in the organisms. 35% of the data in NanoE-Tox concerns ecotoxicity of Ag NPs, followed by TiO2 (22%), CeO2 (13%), and ZnO (10%). Most of the data originates from studies with crustaceans (26%), bacteria (17%), fish (13%), and algae (11%). Based on the median toxicity values of the most sensitive organism (data derived from three or more articles) the toxicity order was as follows: Ag > ZnO > CuO > CeO2 > CNTs > TiO2 > FeO x . We believe NanoE-Tox database contains valuable information for ENM environmental hazard estimation and development of models for predicting toxic potential of ENMs.

Comparative and mechanistic genotoxicity assessment of nanomaterials via a quantitative toxicogenomics approach across multiple species

This study reports a comparative and mechanistic genotoxicity assessment of four engineered nanomaterials (ENMs) across three species, including E. coli, yeast, and human cells, with the aim to reveal the distinct potential genotoxicity mechanisms among the different nanomaterials and their association with physiochemical features. Both the conventional phenotypic alkaline comet test and the newly developed quantitative toxicogenomics assay, that detects and quantifies molecular level changes in the regulation of six DNA damage repair pathways, were employed. The proposed molecular endpoints derived from the toxicogenomics assays, namely TELI (Transcriptional Effect Level Index) and PELI (Protein Effect Level Index), correlated well with the phenotypic DNA damage endpoints from comet tests, suggesting that the molecular genotoxicity assay is suitable for genotoxicity detection. Temporal altered gene or protein expression profiles revealed various potential DNA damage types and relevant genotoxic mechanisms induced by the tested ENMs. nTiO2_a induced a wide spectrum of DNA damage consistently across three species. Three carbon-based ENMs, namely carbon black, single wall carbon nanotube (SWCNT) and fullerene, exhibited distinct, species and ENM property-dependent DNA damage mechanisms. All carbon based ENMs induced relatively weak DNA damage repair response in E. coli, but more severe DNA double strand break in eukaryotes. The differences in cellular structure and defense systems among prokaryotic and eukaryotic species lead to distinct susceptibility and mechanisms for ENM uptake and, thus, varying DNA damages and repair responses. The observation suggested that eukaryotes, especially mammalian cells, are likely more susceptible to genotoxicity than prokaryotes in the ecosystem when exposed to these ENMs.

A quantitative toxicogenomics assay reveals the evolution and nature of toxicity during the transformation of environmental pollutants

The incomplete mineralization of contaminants of emerging concern (CECs) during the advanced oxidation processes can generate transformation products that exhibit toxicity comparable to or greater than that of the original contaminant. In this study, we demonstrated the application of a novel, fast, and cost-effective quantitative toxicogenomics-based approach for the evaluation of the evolution and nature of toxicity along the electro-Fenton oxidative degradation of three representative CECs whose oxidative degradation pathways have been relatively well studied, bisphenol A, triclosan, and ibuprofen. The evolution of toxicity as a result of the transformation of parent chemicals and production of intermediates during the course of degradation are monitored, and the quantitative toxicogenomics assay results revealed the dynamic toxicity changes and mechanisms, as well as their association with identified intermediates during the electro-Fenton oxidation process of the selected CECs. Although for the three CECs, a majority (>75%) of the parent compounds disappeared at the 15 min reaction time, the nearly complete elimination of toxicity required a minimal 30 min reaction time, and they seem to correspond to the disappearance of identified aromatic intermediates. Bisphenol A led to a wide range of stress responses, and some identified transformation products containing phenolic or quinone group, such as 1,4-benzoquinone and hydroquinone, likely contributed to the transit toxicity exhibited as DNA stress (genotoxicity) and membrane stress during the degradation. Triclosan is known to cause severe oxidative stress, and although the oxidative damage potential decreased concomitantly with the disappearance of triclosan after a 15 min reaction, the sustained toxicity associated with both membrane and protein stress was likely attributed at least partially to the production of 2,4-dichlorophenol that is known to cause the production of abnormal proteins and affect the cell membrane. Ibuprofen affects the cell transporter function and exhibited significantly high membrane stress related to both membrane structure and function. Oxidative degradation of ibuprofen led to a shift in its toxicity profile from mainly membrane stress to one that exhibited not only sustained membrane stress but also protein stress and DNA stress. The information-rich and high-resolution toxicogenomics results served as "fingerprints" that discerned and revealed the toxicity mechanism at the molecular level among the CECs and their oxidation transformation products. This study demonstrated that the quantitative toxicogenomics assay can serve as a useful tool for remediation technology efficacy assessment and provide guidance about process design and optimization for desired toxicity elimination and risk reduction.

Risk and toxicity assessments of heavy metals in sediments and fishes from the Yangtze River and Taihu Lake, China

Heavy metal pollution is one of the most serous environmental issues globally. To evaluate the metal pollution in Jiangsu Province of China, the total concentrations of heavy metals in sediments and fishes from the Yangtze River and Taihu Lake were analyzed. Ecological risk of sediments and human health risk of fish consumption were assessed respectively. Furthermore, toxicity of samples on expression of the stress responsive genes was evaluated using microbial live cell-array method. The results showed that the heavy metals concentrations in sediments from the Yangtze River were much higher than those in sediments from the Taihu Lake. However, the fishes from the Taihu Lake had higher concentrations of heavy metals than fishes from the Yangtze River. Ecological risk evaluation showed that the heavy metal contaminants in sediments from the Yangtze River posed higher risk of adverse ecological effects, while sediments from the study areas of Taihu Lake were relatively safe. Health risk assessment suggested that the heavy metals in fishes of both Yangtze River and Taihu Lake might have risk of adverse health effects to human. The toxicity assessment indicated that the heavy metals in these sediments and fishes showed transcriptional effects on the selected 21 stress responsive genes, which were involved in the pathways of DNA damage response, chemical stress, and perturbations of electron transport. Together, this field investigation combined with chemical analysis, risk assessment and toxicity bioassay would provide useful information on the heavy metal pollution in Jiangsu Province.

Differential reconstructed gene interaction networks for deriving toxicity threshold in chemical risk assessment

Background

Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) approach to connect pathway perturbation with toxicity threshold setting.

Methods

Our DNs approach consists of 6 steps: time-series gene expression data collection, identification of altered genes, gene interaction network reconstruction, differential edge inference, mapping of genes with differential edges to pathways, and establishment of causal relationships between chemical concentration and perturbed pathways. A one-sample Gaussian process model and a linear regression model were used to identify genes that exhibited significant profile changes across an entire time course and between treatments, respectively. Interaction networks of differentially expressed (DE) genes were reconstructed for different treatments using a state space model and then compared to infer differential edges/interactions. DE genes possessing differential edges were mapped to biological pathways in databases such as KEGG pathways.

Results

Using the DNs approach, we analyzed a time-series Escherichia coli live cell gene expression dataset consisting of 4 treatments (control, 10, 100, 1000 mg/L naphthenic acids, NAs) and 18 time points. Through comparison of reconstructed networks and construction of differential networks, 80 genes were identified as DE genes with a significant number of differential edges, and 22 KEGG pathways were altered in a concentration-dependent manner. Some of these pathways were perturbed to a degree as high as 70% even at the lowest exposure concentration, implying a high sensitivity of our DNs approach.

Conclusions

Findings from this proof-of-concept study suggest that our approach has a great potential in providing a novel and sensitive tool for threshold setting in chemical risk assessment. In future work, we plan to analyze more time-series datasets with a full spectrum of concentrations and sufficient replications per treatment. The pathway alteration-derived thresholds will also be compared with those derived from apical endpoints such as cell growth rate.

Mapping the biological oxidative damage of engineered nanomaterials

Novel engineered nanomaterials (ENMs) are being introduced into the market rapidly with little understanding of their potential toxicity. Each ENM is a complex combination of diverse sizes, surface chemistries, crystallinity, and metal impurities. Variability in physicochemical properties is poorly understood but is critically important in revealing adverse effects of ENMs. A need also exists for discovering broad relationships between variations in these physicochemical parameters and toxicological endpoints of interest. Biological oxidative damage (BOD) has been recognized as a key mechanism of nanotoxicity. An assortment of 138 ENMs representing major classes are evaluated for BOD elicited (net decrease in the antioxidant capacity of ENM-exposed human blood serum, as compare to unexposed serum) using the 'Ferric Reducing Ability of Serum' (FRAS) assay. This robust and high-throughput approach has the ability to determine the co-effects which multiple physicochemical characteristics impart on oxidative potential, and subsequently to identify and quantify the influence of individual factors. FRAS BOD approach demonstrated the potential for preliminary evaluation of potential toxicity of ENMs, mapping the within- and between-class variability of ENMs, ranking the potential toxicity by material class, and prioritizing the ENMs for further toxicity evaluation and risk assessment.

The influence of capsular extracellular polymeric substances on the interaction between TiO₂ nanoparticles and planktonic bacteria

The role of capsular extracellular polymeric substances (EPS) at the surface of planktonic microorganisms was investigated for possible toxicity mitigation from titanium dioxide (TiO₂) nanoparticles, using variable EPS producing wild-type and isogenic mutant strains of Pseudomonas aeruginosa. Membrane integrity assays revealed that increased capsular EPS reduced cell membrane damage. Acting as a barrier to the cell membrane, capsular EPS permitted attachment of nanoparticles to the cell, while simultaneously delaying cellular damage caused by the production of reactive oxygen species (ROS). Modulations in ROS production were monitored in situ; while changes in the chemical composition of the microorganisms before and after exposure were examined with Fourier transform infrared spectroscopy (FTIR). The addition of methanol, a known radical scavenger, was shown to vastly reduce ROS production and membrane integrity losses, while not affecting physical interactions of nanoparticles with the microorganism. The results support that EPS provides an attachment site for nanoparticles, but more importantly act as a barrier to cell membrane oxidation from ROS. These observations provide better understanding of the overall importance of ROS in TiO₂ microbial toxicity.

Analyzing high dimensional toxicogenomic data using consensus clustering

Rapid development of high-throughput toxicogenomics technologies has created new approaches to screen environmental samples for mechanistic toxicity assessment. However, challenges remain in the analysis, especially clustering of the resulting high-dimensional data. Because of the lack of commonly accepted validation methods, it is difficult to compare clustering results between studies or to identify the key experimental or data features that impact the clustering results. We applied consensus clustering (CC), an approach that clusters the input data repeatedly through iterative resampling, and identifies frequently occurring high-confidence clusters. We used CC to analyze a set of high dimensional transcriptomics data with temporal resolution, which were generated using our E. coli whole-cell array system for a diverse variety of toxicants at different dose concentrations. The CC analysis allowed us to evaluate the clustering results' robustness and sensitivity against a number of conditions that represent the common variations in high-throughput experiments, including noisy data, subsets of treatments, subsets of reporter genes, and subsets of time points. We demonstrated the value of utilizing rich time-series data and underscored the importance of careful selection of sampling times for a given experimental system. The results also indicated that temporal data compression using our proposed Transcriptional Effect Level Index (TELI) concept followed by CC largely conserved the cluster resolution. We also found that for our cellular stress response ensemble-based high-throughput transcriptomics assay platform, the size and composition of the reporter gene set are critical factors that affect the resulting coherency of clusters. Taken together, these results demonstrated that more robust consensus clustering such as CC may be valuable in analyzing high-dimensional toxicogenomic data sets.

Concentration-dependent effects of carbon nanoparticles in gram-negative bacteria determined by infrared spectroscopy with multivariate analysis

With increasing production of carbon nanoparticles (CNPs), environmental release of these entities becomes an ever-greater inevitability. However, many questions remain regarding their impact on soil microorganisms. This study examined the effects of long or short multiwalled carbon nanotubes (MWCNTs), C60 fullerene and fullerene soot in Gram-negative bacteria. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was applied to derive signature spectral fingerprints of effects. A concentration-dependent response in spectral alterations was observed for each nanoparticle type. Long or short MWCNTs and fullerene soot gave rise to similar alterations to lipids, Amide II and DNA. The extent of alteration varies with nanoparticle size, with smaller short MWCNTs resulting in greater toxicity than long MWCNTs. Fullerene soot was the least toxic. C60 results in the most distinct and largest overall alterations, notably in extensive protein alteration. This work demonstrates a novel approach for assaying and discriminating the effects of CNPs in target systems.

Mixture toxicity revisited from a toxicogenomic perspective

The advent of new genomic techniques has raised expectations that central questions of mixture toxicology such as for mechanisms of low dose interactions can now be answered. This review provides an overview on experimental studies from the past decade that address diagnostic and/or mechanistic questions regarding the combined effects of chemical mixtures using toxicogenomic techniques. From 2002 to 2011, 41 studies were published with a focus on mixture toxicity assessment. Primarily multiplexed quantification of gene transcripts was performed, though metabolomic and proteomic analysis of joint exposures have also been undertaken. It is now standard to explicitly state criteria for selecting concentrations and provide insight into data transformation and statistical treatment with respect to minimizing sources of undue variability. Bioinformatic analysis of toxicogenomic data, by contrast, is still a field with diverse and rapidly evolving tools. The reported combined effect assessments are discussed in the light of established toxicological dose-response and mixture toxicity models. Receptor-based assays seem to be the most advanced toward establishing quantitative relationships between exposure and biological responses. Often transcriptomic responses are discussed based on the presence or absence of signals, where the interpretation may remain ambiguous due to methodological problems. The majority of mixture studies design their studies to compare the recorded mixture outcome against responses for individual components only. This stands in stark contrast to our existing understanding of joint biological activity at the levels of chemical target interactions and apical combined effects. By joining established mixture effect models with toxicokinetic and -dynamic thinking, we suggest a conceptual framework that may help to overcome the current limitation of providing mainly anecdotal evidence on mixture effects. To achieve this we suggest (i) to design studies to establish quantitative relationships between dose and time dependency of responses and (ii) to adopt mixture toxicity models. Moreover, (iii) utilization of novel bioinformatic tools and (iv) stress response concepts could be productive to translate multiple responses into hypotheses on the relationships between general stress and specific toxicity reactions of organisms.

Genome-wide bacterial toxicity screening uncovers the mechanisms of toxicity of a cationic polystyrene nanomaterial

By exploiting a genome-wide collection of bacterial single-gene deletion mutants, we have studied the toxicological pathways of a 60-nm cationic (amino-functionalized) polystyrene nanomaterial (PS-NH(2)) in bacterial cells. The IC(50) of commercially available 60 nm PS-NH(2) was determined to be 158 μg/mL, the IC(5) is 108 μg/mL, and the IC(90) is 190 μg/mL for the parent E. coli strain of the gene deletion library. Over 4000 single nonessential gene deletion mutants of Escherichia coli were screened for the growth phenotype of each strain in the presence and absence of PS-NH(2). This revealed that genes clusters in the lipopolysaccharide biosynthetic pathway, outer membrane transport channels, ubiquinone biosynthetic pathways, flagellar movement, and DNA repair systems are all important to how this organism responds to cationic nanomaterials. These results, coupled with those from confirmatory assays described herein, suggest that the primary mechanisms of toxicity of the 60-nm PS-NH(2) nanomaterial in E. coli are destabilization of the outer membrane and production of reactive oxygen species. The methodology reported herein should prove generally useful for identifying pathways that are involved in how cells respond to a broad range of nanomaterials and for determining the mechanisms of cellular toxicity of different types of nanomaterials.