Functional Toxicogenomics: Mechanism-Centered Toxicology

Traditional toxicity testing using animal models is slow, low capacity, expensive and assesses a limited number of endpoints. Such approaches are inadequate to deal with the increasingly large number of compounds found in the environment for which there are no toxicity data. Mechanism-centered high-throughput testing represents an alternative approach to meet this pressing need but is limited by our current understanding of toxicity pathways. Functional toxicogenomics, the global study of the biological function of genes on the modulation of the toxic effect of a compound, can play an important role in identifying the essential cellular components and pathways involved in toxicity response. The combination of the identification of fundamental toxicity pathways and mechanism-centered targeted assays represents an integrated approach to advance molecular toxicology to meet the challenges of toxicity testing in the 21st century

Functional toxicology: tools to advance the future of toxicity testing

The increased presence of chemical contaminants in the environment is an undeniable concern to human health and ecosystems. Historically, by relying heavily upon costly and laborious animal-based toxicity assays, the field of toxicology has often neglected examinations of the cellular and molecular mechanisms of toxicity for the majority of compounds – information that, if available, would strengthen risk assessment analyses. Functional toxicology, where cells or organisms with gene deletions or depleted proteins are used to assess genetic requirements for chemical tolerance, can advance the field of toxicity testing by contributing data regarding chemical mechanisms of toxicity. Functional toxicology can be accomplished using available genetic tools in yeasts, other fungi and bacteria, and eukaryotes of increased complexity, including zebrafish, fruit flies, rodents, and human cell lines. Underscored is the value of using less complex systems such as yeasts to direct further studies in more complex systems such as human cell lines. Functional techniques can yield (1) novel insights into chemical toxicity; (2) pathways and mechanisms deserving of further study; and (3) candidate human toxicant susceptibility or resistance genes

Regulatory Motif Finding by Logic Regression

Multiple transcription factors coordinately control transcriptional regulation of genes in eukaryotes. Although multiple computational methods consider the identification of individual transcription factor binding sites (TFBSs), very few focus on the interactions between these sites. We consider finding transcription factor binding sites and their context specific interactions using microarray gene expression data. We devise a hybrid approach called LogicMotif composed of a TFBS identification method combined with the new regression methodology logic regression of Ruczinski et al. (2003). LogicMotif has two steps: First potential binding sites are identified from transcription control regions of genes of interest. Various available methods can be used in this first step when the genes of interest can be divided into groups such as up and down regulated. For this step, we also develop a simple univariate regression and extension method MFURE to extract candidate TFBSs from a large number of genes in the availability of microarray gene expression data. MFURE provides an alternative method for this step when partitioning of the genes into disjoint groups is not preferred. This first step aims to identify individual sites within gene groups of interest or sites that are correlated with the gene expression outcome. In the second step, logic regression is used to build a predictive model of outcome of interest (either gene expression or up and down regulation) using these potential sites. This two-fold approach creates a rich diverse set of potential binding sites in the first step and builds regression or classification models in the second step using logic regression that is particularly good at identifying complex interactions. LogicMotif is applied to two publicly available data sets. A genome-wide gene expression data set of Saccharomyces cerevisiae is used for validation. The regression models obtained are interpretable and the biological implications are in agreement with the known resuts. This analysis suggests that LogicMotif provides biologically more reasonable regression models than previous analysis of this data set with standard linear regression methods. Another data set of Saccharomyces cerevisiae illustrates the use of LogicMotif in classification questions by building a model that discriminates between up and down regulated genes in iron copper deficiency. LogicMotif identified an inductive and two repressor motifs in this data set. The inductive motif matches the binding site of the transcription factor Aft1p that has a key role in regulation of the uptake process. One of the novel repressor sites is highly present in transcription control regions of FeS genes. This site could represent a TFBS for an unknown transcription factor involved in repression of genes encoding FeS proteins in iron deficiency. We established the stability of the method to the type of outcome variable by using both continuous and binary outcome variables for this data set. Our results indicate that logic regression used in combination with cluster/group operating binding site identification methods or with our proposed method MFURE is a powerful and flexible alternative to linear regression based motif finding methods

A comparison between whole transcript and 3' RNA sequencing methods using Kapa and Lexogen library preparation methods.

Background3' RNA sequencing provides an alternative to whole transcript analysis. However, we do not know a priori the relative advantage of each method. Thus, a comprehensive comparison between the whole transcript and the 3' method is needed to determine their relative merits. To this end, we used two commercially available library preparation kits, the KAPA Stranded mRNA-Seq kit (traditional method) and the Lexogen QuantSeq 3' mRNA-Seq kit (3' method), to prepare libraries from mouse liver RNA. We then sequenced and analyzed the libraries to determine the advantages and disadvantages of these two approaches.ResultsWe found that the traditional whole transcript method and the 3' RNA-Seq method had similar levels of reproducibility. As expected, the whole transcript method assigned more reads to longer transcripts, while the 3' method assigned roughly equal numbers of reads to transcripts regardless of their lengths. We found that the 3' RNA-Seq method detected more short transcripts than the whole transcript method. With regard to differential expression analysis, we found that the whole transcript method detected more differentially expressed genes, regardless of the level of sequencing depth.ConclusionsThe 3' RNA-Seq method was better able to detect short transcripts, while the whole transcript RNA-Seq was able to detect more differentially expressed genes. Thus, both approaches have relative advantages and should be selected based on the goals of the experiment

Short versus long silver nanowires: a comparison of in vivo pulmonary effects post instillation.

BackgroundSilver nanowires (Ag NWs) are increasingly being used to produce touchscreens for smart phones and computers. When applied in a thin film over a plastic substrate, Ag NWs create a transparent, highly-conductive network of fibers enabling the touch interface between consumers and their electronics. Large-scale application methods utilize techniques whereby Ag NW suspensions are deposited onto substrates via droplets. Aerosolized droplets increase risk of occupational Ag NW exposure. Currently, there are few published studies on Ag NW exposure-related health effects. Concerns have risen about the potential for greater toxicity from exposure to high-aspect ratio nanomaterials compared to their non-fibrous counterparts. This study examines whether Ag NWs of varying lengths affect biological responses and silver distribution within the lungs at different time-points.MethodsTwo different sizes of Ag NWs (2 μm [S-Ag NWs] and 20 μm [L-Ag NWs]) were tested. Male, Sprague-Dawley rats were intratracheally instilled with Ag NWs (0, 0.1, 0.5, or 1.0 mg/kg). Broncho-alveolar lavage fluid (BALF) and lung tissues were obtained at 1, 7, and 21 days post exposure for analysis of BAL total cells, cell differentials, and total protein as well as tissue pathology and silver distribution.Results and conclusionsThe two highest doses produced significant increases in BAL endpoints. At Day 1, Ag NWs increased total cells, inflammatory polymorphonuclear cells (PMNs), and total protein. PMNs persisted for both Ag NW types at Day 7, though not significantly so, and by Day 21, PMNs appeared in line with sham control values. Striking histopathological features associated with Ag NWs included 1) a strong influx of eosinophils at Days 1 and 7; and 2) formation of Langhans and foreign body giant cells at Days 7 and 21. Epithelial sloughing in the terminal bronchioles (TB) and cellular exudate in alveolar regions were also common. By Day 21, Ag NWs were primarily enclosed in granulomas or surrounded by numerous macrophages in the TB-alveolar duct junction. These findings suggest short and long Ag NWs produce pulmonary toxicity; thus, further research into exposure-related health effects and possible exposure scenarios are necessary to ensure human safety as Ag NW demand increases

A Systems Biology Approach Reveals a Calcium-Dependent Mechanism for Basal Toxicity in Daphnia magna.

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Environmental Science & Technology, copyright © American Chemical Society after peer review and technical editing by the publisher.The expanding diversity and ever increasing amounts of man-made chemicals discharged to the environment pose largely unknown hazards to ecosystem and human health. The concept of adverse outcome pathways (AOPs) emerged as a comprehensive framework for risk assessment. However, the limited mechanistic information available for most chemicals and a lack of biological pathway annotation in many species represent significant challenges to effective implementation of this approach. Here, a systems level, multistep modeling strategy demonstrates how to integrate information on chemical structure with mechanistic insight from genomic studies, and phenotypic effects to define a putative adverse outcome pathway. Results indicated that transcriptional changes indicative of intracellular calcium mobilization were significantly overrepresented in Daphnia magna (DM) exposed to sublethal doses of presumed narcotic chemicals with log Kow ≥ 1.8. Treatment of DM with a calcium ATPase pump inhibitor substantially recapitulated the common transcriptional changes. We hypothesize that calcium mobilization is a potential key molecular initiating event in DM basal (narcosis) toxicity. Heart beat rate analysis and metabolome analysis indicated sublethal effects consistent with perturbations of calcium preceding overt acute toxicity. Together, the results indicate that altered calcium homeostasis may be a key early event in basal toxicity or narcosis induced by lipophilic compounds

CAPRG: Sequence Assembling Pipeline for Next Generation Sequencing of Non-Model Organisms

Our goal is to introduce and describe the utility of a new pipeline “Contigs Assembly Pipeline using Reference Genome” (CAPRG), which has been developed to assemble “long sequence reads” for non-model organisms by leveraging a reference genome of a closely related phylogenetic relative. To facilitate this effort, we utilized two avian transcriptomic datasets generated using ROCHE/454 technology as test cases for CAPRG assembly. We compared the results of CAPRG assembly using a reference genome with the results of existing methods that utilize de novo strategies such as VELVET, PAVE, and MIRA by employing parameter space comparisons (intra-assembling comparison). CAPRG performed as well or better than the existing assembly methods based on various benchmarks for “gene-hunting.” Further, CAPRG completed the assemblies in a fraction of the time required by the existing assembly algorithms. Additional advantages of CAPRG included reduced contig inflation resulting in lower computational resources for annotation, and functional identification for contigs that may be categorized as “unknowns” by de novo methods. In addition to providing evaluation of CAPRG performance, we observed that the different assembly (inter-assembly) results could be integrated to enhance the putative gene coverage for any transcriptomics study

Novel insights into iron metabolism by integrating deletome and transcriptome analysis in an iron deficiency model of the yeast Saccharomyces cerevisiae

<p>Abstract</p> <p>Background</p> <p>Iron-deficiency anemia is the most prevalent form of anemia world-wide. The yeast <it>Saccharomyces cerevisiae </it>has been used as a model of cellular iron deficiency, in part because many of its cellular pathways are conserved. To better understand how cells respond to changes in iron availability, we profiled the yeast genome with a parallel analysis of homozygous deletion mutants to identify essential components and cellular processes required for optimal growth under iron-limited conditions. To complement this analysis, we compared those genes identified as important for fitness to those that were differentially-expressed in the same conditions. The resulting analysis provides a global perspective on the cellular processes involved in iron metabolism.</p> <p>Results</p> <p>Using functional profiling, we identified several genes known to be involved in high affinity iron uptake, in addition to novel genes that may play a role in iron metabolism. Our results provide support for the primary involvement in iron homeostasis of vacuolar and endosomal compartments, as well as vesicular transport to and from these compartments. We also observed an unexpected importance of the peroxisome for growth in iron-limited media. Although these components were essential for growth in low-iron conditions, most of them were not differentially-expressed. Genes with altered expression in iron deficiency were mainly associated with iron uptake and transport mechanisms, with little overlap with those that were functionally required. To better understand this relationship, we used expression-profiling of selected mutants that exhibited slow growth in iron-deficient conditions, and as a result, obtained additional insight into the roles of <it>CTI6</it>, <it>DAP1</it>, <it>MRS4 </it>and <it>YHR045W </it>in iron metabolism.</p> <p>Conclusion</p> <p>Comparison between functional and gene expression data in iron deficiency highlighted the complementary utility of these two approaches to identify important functional components. This should be taken into consideration when designing and analyzing data from these type of studies. We used this and other published data to develop a molecular interaction network of iron metabolism in yeast.</p