Unbiased approach for the identification of molecular mechanisms sensitive to chemical exposures

Toxicogenomic analysis of physiologically important metals: An integrated in silico approach

Biologically important metals regulate cellular homeostasis in living systems. Anthropogenic exposure to these metals can cause adverse effects, including an increased incidence of diseases in humans such as cancer, lung, and cardiovascular defects. However, the effects of metals and the common genes/signaling pathways involved in metal toxicity have not been elucidated. Hence, the present study used toxicogenomic data mining with the comparative toxicogenomics database to explore the impact of these metals. The metals were categorized into transition, alkali, and alkali earth. The common genes were identified and subjected to functional enrichment analysis. Further, gene-gene and protein-protein interactions were assessed. Also, the top ten transcription factors and miRNAs that regulate the genes were identified. The phenotypes and diseases that have increased incidence upon alterations of these genes were detected. Overall, we were able to identify IL1B and SOD2 as the common genes, along with the AGE-RAGE signaling pathway in diabetic complications as the common pathway altered. Enriched genes and pathways specific to each metal category were also found. Further, we identified heart failure as the major diseases that have increased the incidence of these metals' exposure. In conclusion, exposure to essential metals might cause adverse effects via inflammation and oxidative stress.

In silico, in vitro and in vivo studies: Dibutyl phthalate promotes prostate cancer cell proliferation by activating Forkhead Box M1 and remission after Natura-α pretreatment

Dibutyl phthalate (DBP) is widely used in perfumes, cosmetics, shampoos and medical devices. It is ubiquitous in the environment and greatly endangers people's health. Several studies have reported that being exposed to it can promote the development of lung cancer, breast cancer, hepatoma, and multiple myeloma. However, there are still few studies on the specific molecular mechanism and prevention methods of DBP promoting the progression of prostate cancer. This study, in silico, in vitro and in vivo, aims to explore the promoting effect of DBP on prostate cancer cell proliferation. In silico analysis, we obtained a set of DBP interactive genes by utilizing TCGA, CTD and GEO database. These genes are mainly enriched in cell cycle regulatory pathways and they have high degree of homogeneity. We found that these genes shared one transcription factor - Forkhead Box M1 (FOXM1) by performing Chip-X Enrichment Analysis (Version 3.0). FOXM1, once called the 2010 Molecule of the Year, aberrantly expressed in up to 20 kinds of tumors. In vitro experiments, we used DBP at concentrations of 10^-8 M and 5 * 10^-7 M to treat C4-2 and PC3 cells for 6 days, respectively. Cell viability was promoted significantly. When Natura-α was added in the background of above-mentioned concentration of DBP, this effect was significantly inhibited. In addition, we also found that DBP can interfering with the efficacy of enzalutamide therapy. The introduction of Natura-α can also reverse this phenomenon. In vivo, subcutaneous tumor formation experiments in nude mice, 800 mg/kg/day DBP can promote the growth of prostate cancer. This phenomenon was suppressed when Natura-α (100 mg/kg/day) was added. Based on the results of the above three levels, we confirmed that DBP can target FOXM1 to promote prostate cancer cell proliferation. Natura-α can reverse its cancer-promoting effect. This study provides new insights into the impact of DBP on prostate cancer.

Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures

Chemical exposures from diverse sources merge on a limited number of molecular pathways described as toxicity pathways. Changes in the same set of molecular pathways in different cell and tissue types may generate seemingly unrelated health conditions. Today, no approaches are available to predict in an unbiased way sensitivities of different disease states and their combinations to multi-chemical exposures across the exposome. We propose an inductive in-silico workflow where sensitivities of genes to chemical exposures are identified based on the overlap of existing genomic datasets, and data on sensitivities of individual genes is further used to sequentially derive predictions on sensitivities of molecular pathways, disease states, and groups of disease states (syndromes). Our analysis predicts that conditions representing the most significant public health problems are among the most sensitive to cumulative chemical exposures. These conditions include six leading types of cancer in the world (prostatic, breast, stomach, lung, colorectal neoplasms, and hepatocellular carcinoma), obesity, type 2 diabetes, non-alcoholic fatty liver disease, autistic disorder, Alzheimer's disease, hypertension, heart failure, brain and myocardial ischemia, and myocardial infarction. Overall, our predictions suggest that environmental risk factors may be underestimated for the most significant public health problems.

Network Toxicology Guided Mechanism Study on the Association between Thyroid Function and Exposures to Polychlorinated Biphenyls Mixture

Polychlorinated biphenyls (PCBs) are persistent and highly toxic pollutants, which can accumulate in organisms and produce toxic effects, especially damaging the function of thyroid hormones. So far, the molecular mechanism of PCBs mixture and their metabolites interfering with thyroid hormones has not been studied thoroughly except for individual compounds. In this study, PubMed, Web of Science, and STITCH databases were used to search PCBs and their corresponding target proteins. The intersection of PCBs and thyroid hormone dysfunction target proteins was obtained from GeneCards. The “compounds-targets-pathways” network was constructed by Cytoscape software. And KEGG and Go analyses were performed for key targets. Finally, molecular docking was used to verify the binding effect. Four major active components, five key targets, and 10 kernel pathways were successfully screened by constructing the network. Functional enrichment analysis showed that the interference was mediated by cancer, proteoglycans, PI3K-Akt, thyroid hormone, and FoxO signaling pathways. The molecular docking results showed that the binding energies were less than -5 kcal·mol-1. PCBs and their metabolites may act on the key targets of MAPK3, MAPK1, RXRA, PIK3R1, and TP53. The toxic effect of sulfated and methyl sulfone PCBs is greater. The method of screening targets based on the simultaneous action of multiple PCBs can provide a reference for other research. The targets were not found in previous metabolite toxicity studies. It also provides a bridge for the toxic effects and experimental research of PCBs and their metabolites in the future.

Network-based integrated analysis for toxic effects of high-concentration formaldehyde inhalation exposure through the toxicogenomic approach

Formaldehyde is a colorless, pungent, highly reactive, and toxic environmental pollutant used in various industries and products. Inhaled formaldehyde is a human and animal carcinogen that causes genotoxicity, such as reactive oxygen species formation and DNA damage. This study aimed to identify the toxic effects of inhaled formaldehyde through an integrated toxicogenomic approach utilizing database information. Microarray datasets (GSE7002 and GSE23179) were collected from the Gene Expression Omnibus database, and differentially expressed genes were identified. The network analyses led to the construction of the respiratory system-related biological network associated with formaldehyde exposure, and six upregulated hub genes (AREG, CXCL2, HMOX1, PLAUR, PTGS2, and TIMP1) were identified. The expression levels of these genes were verified via qRT-PCR in 3D reconstructed human airway tissues exposed to aerosolized formaldehyde. Furthermore, NRARP was newly found as a potential gene associated with the respiratory and carcinogenic effects of formaldehyde by comparison with human in vivo and in vitro formaldehyde-exposure data. This study improves the understanding of the toxic mechanism of formaldehyde and suggests a more applicable analytic pipeline for predicting the toxic effects of inhaled toxicants.

Simple method for cutoff point identification in descriptive high-throughput biological studies

Background

Rapid development of high-throughput omics technologies generates an increasing interest in algorithms for cutoff point identification. Existing cutoff methods and tools identify cutoff points based on an association of continuous variables with another variable, such as phenotype, disease state, or treatment group. These approaches are not applicable for descriptive studies in which continuous variables are reported without known association with any biologically meaningful variables.

Results

The most common shape of the ranked distribution of continuous variables in high-throughput descriptive studies corresponds to a biphasic curve, where the first phase includes a big number of variables with values slowly growing with rank and the second phase includes a smaller number of variables rapidly growing with rank. This study describes an easy algorithm to identify the boundary between these phases to be used as a cutoff point.

Discussion

The major assumption of that approach is that a small number of variables with high values dominate the biological system and determine its major processes and functions. This approach was tested on three different datasets: human genes and their expression values in the human cerebral cortex, mammalian genes and their values of sensitivity to chemical exposures, and human proteins and their expression values in the human heart. In every case, the described cutoff identification method produced shortlists of variables (genes, proteins) highly relevant for dominant functions/pathways of the analyzed biological systems.

Conclusions

The described method for cutoff identification may be used to prioritize variables in descriptive omics studies for a focused functional analysis, in situations where other methods of dichotomization of data are inaccessible.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08427-6.

Membrane polarization in non-neuronal cells as a potential mechanism of metabolic disruption by depolarizing insecticides

A significant rise in the incidence of obesity and type 2 diabetes has occurred worldwide in the last two decades. Concurrently, a growing body of evidence suggests a connection between exposure to environmental pollutants, particularly insecticides, and the development of obesity and type 2 diabetes. This review summarizes key evidence of (1) the presence of different types of neuronal receptors - target sites for neurotoxic insecticides - in non-neuronal cells, (2) the activation of these receptors in non-neuronal cells by membrane-depolarizing insecticides, and (3) changes in metabolic functions, including lipid and glucose accumulation, associated with changes in membrane potential. Based on these findings, we propose that changes in membrane potential (V_mem) by certain insecticides serve as a novel regulator of lipid and glucose metabolism in non-excitable cells associated with obesity and type 2 diabetes.

Integrating in silico with in vivo approach to investigate phthalate and bisphenol A mixture-linked asthma development: Positive probiotic intervention

The aim of this study was to explore the mechanisms of bis(2- ethylhexyl) phthalate (DEHP), dibutyl phthalate (DBP) and bisphenol A (BPA) mixture-induced asthma development and test probiotic as a potential positive intervention. Comparative Toxicogenomics Database (CTD) and ToppGene Suite were used as the main tools for in silico analysis. In vivo 28-day experiment was conducted on rats - seven groups (n = 6): (1) Control: corn oil, (2) P: probiotic (8.78 * 10⁸ CFU/kg/day); (3) DEHP: 50 mg/kg b.w./day, (4) DBP: 50 mg/kg b.w./day, (5) BPA: 25 mg/kg b.w./day; (6) MIX: DEHP + DBP + BPA; (7) MIX + P. Lungs, thymus and kidneys were extracted and prepared for redox status and essential metals analysis. By conducting additional in vitro experiment, probiotic phthalate and BPA binding ability was explored. There were 24 DEHP, DBP and BPA asthma-related genes, indicating the three most probable mechanisms - apoptosis, inflammation and oxidative stress. In vivo experiment confirmed that significant changes in redox status/essential metal parameters were either prominent, or only present in the MIX group, indicating possible additive effects. In vitro experiment confirmed the ability of the multy-strain probiotic to bind DEHP/DBP/BPA mixture, while probiotic administration ameliorated mixture-induced changes in rat tissue.

Chemical Exposures Affect Innate Immune Response to SARS-CoV-2

Severe outcomes of COVID-19 are associated with pathological response of the immune system to the SARS-CoV-2 infection. Emerging evidence suggests that an interaction may exist between COVID-19 pathogenesis and a broad range of xenobiotics, resulting in significant increases in death rates in highly exposed populations. Therefore, a better understanding of the molecular basis of the interaction between SARS-CoV-2 infection and chemical exposures may open opportunities for better preventive and therapeutic interventions. We attempted to gain mechanistic knowledge on the interaction between SARS-CoV-2 infection and chemical exposures using an in silico approach, where we identified genes and molecular pathways affected by both chemical exposures and SARS-CoV-2 in human immune cells (T-cells, B-cells, NK-cells, dendritic, and monocyte cells). Our findings demonstrate for the first time that overlapping molecular mechanisms affected by a broad range of chemical exposures and COVID-19 are linked to IFN type I/II signaling pathways and the process of antigen presentation. Based on our data, we also predict that exposures to various chemical compounds will predominantly impact the population of monocytes during the response against COVID-19.

DNA Damage and Expression Profile of Genes Associated with Nephrotoxicity Induced by Butralin and Ameliorating Effect of Arabic Gum in Female Rats

Nephrotoxicity induced by exposure to environmental pollution, including herbicides, is becoming a global problem. Natural products are the prime alternative scientific research as they express better medicinal activity and minor side effects compared with a variety of synthetic drugs. This study was performed to evaluate the nephroprotective proficiency of Arabic gum against butralin-induced nephrotoxicity. Adult female rats were supplemented with Arabic gum (4.3 g/kg b.wt) and/or butralin (312 mg/L) in drinking water for 30 days. The results found that markers of serum kidney function, oxidative stress biomarkers, DNA damage, and expression of kidney specific genes (Acsm2, Ace, and Ace2) as well as histopathological examination in treated rats were conducted. Butralin-treated rats showed a rise in serum creatinine (41%), BUN (47.3%), and MDA (140.9%) as well as decrease in activity of the antioxidant markers (CAT (-21%); GPx (-70.7%); and TAC (43.2%)) in comparison with the control group. In addition, butralin treatment increased the DNA damage (221%); altered the expression levels of Acsm2, Ace, and Ace2 (-51.6%, 141.6%, and 143% respectively); and elevated histopathological lesions in the kidney tissues. Pretreatment of Arabic gum prevented butralin-prompted degenerative changes of kidney tissues. The results suggested that the protective effect provided by Arabic gum on renal tissues exposed to the herbicide butralin could be attributed to enhancement of antioxidants and increase the free radical scavenging activity in vivo.

Probiotic reduced the impact of phthalates and bisphenol A mixture on type 2 diabetes mellitus development: Merging bioinformatics with in vivo analysis

Linkage between bis(2-ethylhexyl) phthalate (DEHP), dibutyl phthalate (DBP), and bisphenol A (BPA) co-exposure and type 2 diabetes mellitus (T2DM), as well as ability of multi-strained probiotic to reduce DEHP, DBP and BPA mixture-induced oxidative damage in rat pancreas were investigated. The Comparative Toxicogenomics Database, Cytoscape software and ToppGene Suite were used for data-mining. Animals were sorted into seven groups (n = 6): (1) Control group: corn oil, (2) P: probiotic: Saccharomyces boulardii + Lactobacillus rhamnosus + Lactobacillus plantarum LP 6595 + Lactobacillus plantarum HEAL9; (3) DEHP: 50 mg/kg b.w./day, (4) DBP: 50 mg/kg b.w./day, (5) BPA: 25 mg/kg b.w./day, and (6) MIX: 50 mg/kg b.w./day DEHP + 50 mg/kg b.w/day DBP + 25 mg/kg b.w./day BPA; (7) MIX + P. Rats were sacrificed after 28 days of oral exposure. In silico investigation highlighted 44 DEHP, DBP and BPA mutual genes linked to the T2DM, while apoptosis and oxidative stress were highlighted as the main mechanisms of DEHP, DBP and BPA mixture-linked T2DM. In vivo experiment confirmed the presence of significant changes in redox status parameters (TOS, SOD and SH groups) only in the MIX group, indicating possible additive effects, while probiotic ameliorated mixture-induced redox status changes in rat pancreatic tissue.

Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures

A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria: data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expression analysis. Genes not present in genomes of all three species were filtered out. The resulting dataset included 591,084 chemical-gene interaction. All chemical compounds in the database were annotated for their major uses. For every gene in the database number of chemical-gene interactions was calculated and used as a metric of gene sensitivity to a variety of chemical exposures. The lists of genes with corresponding numbers of chemical-gene interactions were used in gene-set enrichment analysis (GSEA) to identify potential sensitivity to chemical exposures of molecular pathways in Hallmark, KEGG and Reactome collections. Thus, data presented here represent unbiased and searchable datasets of sensitivity of genes and molecular pathways to a broad range of chemical exposures. As such the data can be used for a diverse range of toxicological and regulatory applications. Approach for the identification of molecular mechanisms sensitive to chemical exposures may inform regulatory toxicology about best toxicity testing strategies. Analysis of sensitivity of genes and molecular pathways to chemical exposures based on these datasets was published in Chemosphere (Suvorov et al., 2021) [1].