In vitro screening for population variability in toxicity of pesticide-containing mixtures

Population-based human in vitro models offer exceptional opportunities for evaluating the potential hazard and mode of action of chemicals, as well as variability in responses to toxic insults among individuals. This study was designed to test the hypothesis that comparative population genomics with efficient in vitro experimental design can be used for evaluation of the potential for hazard, mode of action, and the extent of population variability in responses to chemical mixtures. We selected 146 lymphoblast cell lines from 4 ancestrally and geographically diverse human populations based on the availability of genome sequence and basal RNA-seq data. Cells were exposed to two pesticide mixtures – an environmental surface water sample comprised primarily of organochlorine pesticides and a laboratory-prepared mixture of 36 currently used pesticides – in concentration response and evaluated for cytotoxicity. On average, the two mixtures exhibited a similar range of in vitro cytotoxicity and showed considerable inter-individual variability across screened cell lines. However, when in vitroto-in vivo extrapolation (IVIVE) coupled with reverse dosimetry was employed to convert the in vitro cytotoxic concentrations to oral equivalent doses and compared to the upper bound of predicted human exposure, we found that a nominally more cytotoxic chlorinated pesticide mixture is expected to have greater margin of safety (more than 5 orders of magnitude) as compared to the current use pesticide mixture (less than 2 orders of magnitude) due primarily to differences in exposure predictions. Multivariate genome-wide association mapping revealed an association between the toxicity of current use pesticide mixture and a polymorphism in rs1947825 in C17orf54. We conclude that a combination of in vitro human population-based cytotoxicity screening followed by dosimetric adjustment and comparative population genomics analyses enables quantitative evaluation of human health hazard from complex environmental mixtures. Additionally, such an approach yields testable hypotheses regarding potential toxicity mechanisms

An Empirical Bayes Approach for Multiple Tissue eQTL Analysis

Expression quantitative trait loci (eQTL) analyses, which identify genetic markers associated with the expression of a gene, are an important tool in the understanding of diseases in human and other populations. While most eQTL studies to date consider the connection between genetic variation and expression in a single tissue, complex, multi-tissue data sets are now being generated by the GTEx initiative. These data sets have the potential to improve the findings of single tissue analyses by borrowing strength across tissues, and the potential to elucidate the genotypic basis of differences between tissues. In this paper we introduce and study a multivariate hierarchical Bayesian model (MT-eQTL) for multi-tissue eQTL analysis. MT-eQTL directly models the vector of correlations between expression and genotype across tissues. It explicitly captures patterns of variation in the presence or absence of eQTLs, as well as the heterogeneity of effect sizes across tissues. Moreover, the model is applicable to complex designs in which the set of donors can (i) vary from tissue to tissue, and (ii) exhibit incomplete overlap between tissues. The MT-eQTL model is marginally consistent, in the sense that the model for a subset of tissues can be obtained from the full model via marginalization. Fitting of the MT-eQTL model is carried out via empirical Bayes, using an approximate EM algorithm. Inferences concerning eQTL detection and the configuration of eQTLs across tissues are derived from adaptive thresholding of local false discovery rates, and maximum a-posteriori estimation, respectively. We investigate the MT-eQTL model through a simulation study, and rigorously establish the FDR control of the local FDR testing procedure under mild assumptions appropriate for dependent data.Comment: accepted by Biostatistic

Effect of mineral fertilizer encapsulated with zeolite and polyethylene terephthalate on the soil microbiota, pH and plant germination

Environmental risks caused by the use of traditional mineral fertilizers require new agro-technical solutions, which are encapsulated long-acting fertilizers. The use of the capsule allows to reduce the concentration of mineral compounds in the fertilizer and to minimize the adverse effects of the chemical compounds contained in it on the environment. Encapsulated fertilizers provide more efficient absorption of mineral nutrition by plants, allowing to synchronize the release of elements in accordance with the needs of the plant. The use of natural materials as fertilizer shells is faced with the problem of their low solubility and cost, and the use of synthetic coatings with the problems of their biodegradation in the environment. The development of new environmentally friendly materials for long-acting fertilizer capsules is a challenge for modern society. In this context, a universal mineral fertilizer coated with a coating of natural zeolite sorbent and diethylene glycol (DEG) modified polyethyl terephthalate (PET) is promising. We analyzed the influence of fertilizer on the kinetics of soil pH change, the dynamics of the total microbial count and the increase in the number of microorganisms and the germination of Hordeum sativum and Lolium perenne. The application of fertilizer for 28 days of the experiment led to decrease in soil pH by 0.3. In the presence of encapsulated fertilizer the germination of ryegrass seeds was 3.51 times higher, and ones of barley 4.14 times higher than without fertilizer. The fertilizer provided a prolonged release of minerals, which had a positive effect on the germination of barley and ryegrass plants, stimulated plant growth and increased the total number of microorganisms in the soil as an important indicator of the efficiency of agricultural technology

Role of epigenetic aberrations in the development and progression of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most lethal and prevalent cancers in humans. The molecular mechanisms leading to the development of HCC are extremely complicated and consist of prominent genetic, genomic, and epigenetic alterations. This review summarizes the current knowledge of the role of epigenetic aberrations, including changes in DNA methylation, histone modifications, and expression of microRNAs in the pathogenesis of HCC. It also emphasizes that identification of the underlying epigenetic alterations that drive cell transformation and promote development and progression of HCC is crucially important for understanding mechanisms of hepatocarcinogenesis, its detection, therapeutic intervention, and prevention

Mechanisms of HCV-induced liver cancer: What did we learn from in vitro and animal studies?

Hepatitis C virus (HCV) is a cause of liver diseases that range from steatohepatitis, to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The challenge of understanding the pathogenesis of HCV-associated liver cancer is difficult as most standard animal models used in biomedical research are not permissive to HCV infection. Herein, we provide an overview of a number of creative in vivo, mostly in the mouse, and in vitro models that have been developed to advance our understanding of the molecular and cellular effects of HCV on the liver, specifically with their relevance to HCC

Systems biology and functional genomics approaches for the identification of cellular responses to drug toxicity

Extensive growth in the field of molecular biology in recent decades has led to the development of new and powerful experimental and computational tools that enable the analysis of complex biological responses to chemical exposure on both a functional and structural genetic level. The ability to profile global responses on a transcriptional level has become a valuable resource in the science of toxicology and attempts are currently being made to further understand toxicity mechanisms by incorporating metabolomics and proteomics approaches. In addition, recent progress in understanding the extent of the genetic diversity within and between species allows us to take a fresh look at research on genetic polymorphisms which may influence an individual’s susceptibility to toxicity. While new technologies have the potential to make a sizeable impact on our understanding of the mechanisms of toxicity, considerable challenges remain to be addressed, especially with regards to the regulatory acceptance and successful integration of omics data. This review highlights recent advancements in the application of functional and structural genomics techniques to chemical hazard identification and characterization, and to the understanding of the inter-individual differences in susceptibility to adverse drug reactions

In vitro models for liver toxicity testing

Over the years, various liver-derived in vitro model systems have been developed to enable investigation of the potential adverse effects of chemicals and drugs. Liver tissue slices, isolated microsomes, perfused liver, immortalized cell lines, and primary hepatocytes have been used extensively. Immortalized cell lines and primary isolated liver cells are currently the most widely used in vitro models for liver toxicity testing. Limited throughput, loss of viability, and decreases in liver-specific functionality and gene expression are common shortcomings of these models. Recent developments in the field of in vitro hepatotoxicity include three-dimensional tissue constructs and bioartificial livers, co-cultures of various cell types with hepatocytes, and differentiation of stem cells into hepatic lineage-like cells. In an attempt to provide a more physiological environment for cultured liver cells, some of the novel cell culture systems incorporate fluid flow, micro-circulation, and other forms of organotypic microenvironments. Co-cultures aim to preserve liver-specific morphology and functionality beyond those provided by cultures of pure parenchymal cells. Stem cells, both embryonic- and adult tissue-derived, may provide a limitless supply of hepatocytes from multiple individuals to improve reproducibility and enable testing of the individual-specific toxicity. This review describes various traditional and novel in vitro liver models and provides a perspective on the challenges and opportunities afforded by each individual test system.National Institutes of Health (U.S.) (P42 ES005948)National Institutes of Health (U.S.) (R01 ES01524

Prediction of binding affinity and efficacy of thyroid hormone receptor ligands using QSAR and structure-based modeling methods

The thyroid hormone receptor (THR) is an important member of the nuclear receptor family that can be activated by endocrine disrupting chemicals (EDC). Quantitative Structure-Activity Relationship (QSAR) models have been developed to facilitate the prioritization of THR-mediated EDC for the experimental validation. The largest database of binding affinities available at the time of the study for ligand binding domain (LBD) of THRβ was assembled to generate both continuous and classification QSAR models with an external accuracy of R2=0.55 and CCR=0.76, respectively. In addition, for the first time a QSAR model was developed to predict binding affinities of antagonists inhibiting the interaction of coactivators with the AF-2 domain of THRβ (R2=0.70). Furthermore, molecular docking studies were performed for a set of THRβ ligands (57 agonists and 15 antagonists of LBD, 210 antagonists of the AF-2 domain, supplemented by putative decoys/non-binders) using several THRβ structures retrieved from the Protein Data Bank. We found that two agonist-bound THRβ conformations could effectively discriminate their corresponding ligands from presumed non-binders. Moreover, one of the agonist conformations could discriminate agonists from antagonists. Finally, we have conducted virtual screening of a chemical library compiled by the EPA as part of the Tox21 program to identify potential THRβ-mediated EDCs using both QSAR models and docking. We concluded that the library is unlikely to have any EDC that would bind to the THRβ. Models developed in this study can be employed either to identify environmental chemicals interacting with the THR or, conversely, to eliminate the THR-mediated mechanism of action for chemicals of concern