Insights into Repeated Renal Injury Using RNA-Seq with Two New RPTEC Cell Lines.

Renal proximal tubule epithelial cells (RPTECs) are a primary site for kidney injury. We created two RPTEC lines from CD-1 mice immortalized with hTERT (human telomerase reverse transcriptase) or SV40 LgT antigen (Simian Virus 40 Large T antigen). Our hypothesis was that low-level, repeated exposure to subcytotoxic levels of 0.25-2.5 µM cisplatin (CisPt) or 12.5-100 µM aflatoxin B1 (AFB1) would activate distinctive genes and pathways in these two differently immortalized cell lines. RNA-seq showed only LgT cells responded to AFB1 with 1139 differentially expressed genes (DEGs) at 72 h. The data suggested that AFB1 had direct nephrotoxic properties on the LgT cells. However, both the cell lines responded to 2.5 µM CisPt from 3 to 96 h expressing 2000-5000 total DEGs. For CisPt, the findings indicated a coordinated transcriptional program of injury signals and repair from the expression of immune receptors with cytokine and chemokine secretion for leukocyte recruitment; robust expression of synaptic and substrate adhesion molecules (SAMs) facilitating the expression of neural and hormonal receptors, ion channels/transporters, and trophic factors; and the expression of nephrogenesis transcription factors. Pathway analysis supported the concept of a renal repair transcriptome. In summary, these cell lines provide in vitro models for the improved understanding of repeated renal injury and repair mechanisms. High-throughput screening against toxicant libraries should provide a wider perspective of their capabilities in nephrotoxicity.

Whole exome and transcript profiling of liver following aflatoxin B1 exposure in rats.

We recently developed a rat whole exome sequencing (WES) panel and used it to evaluate early somatic mutations in archival liver tissues from F344/N rats exposed to the hepatocarcinogen, Aflatoxin B1 (AFB1), a widely studied, potent mutagen and hepatocarcinogen associated with hepatocellular carcinoma (HCC). Rats were exposed to 1-ppm AFB1 in feed for 14, 90, and 90 days plus a recovery 60-day, non-exposure period (150-day) timepoint. Isolated liver DNA was exome sequenced. We identified 172 sequence variants across all timepoints, of which 101 were non-synonymous variants. Well-annotated genes carried a diverse set of 29 non-synonymous mutations at 14 days, increasing to 39 mutations at 90 days and then decreasing to 33 mutations following the 60-day recovery. Gene Set Enrichment Analysis conducted on previously reported, available RNA expression data of the same exome sequenced archival samples identified altered transcripts in pathways associated with malignant transformation. These included HALLMARK gene sets associated with cell proliferation (MYC Targets Version 1 and Version 2, E2F targets), cell cycle (G2M checkpoint, mitotic spindle), cell death (apoptosis), and DNA damage (DNA repair, UV response Up, Reactive oxygen species) pathways. DriverNet Impact analysis integrated exome-seq and expression data to reveal somatic mutations in Mcm8, Bdp1, and Cct6a that may drive cancer formation. Connectivity with transcript expression changes identified these genes as the top-ranked candidate driver genes associated with hepatocellular transformation. In conclusion, exome sequencing revealed early somatic mutations that may play a role in cancer cell transformation that are translatable to aflatoxin-induced HCC.

Chronic PFOA exposure in vitro causes acquisition of multiple tumor cell characteristics in rat liver cells.

Perfluorooctanoic acid (PFOA) is tumorigenic in rats and mice and potentially tumorigenic in humans. Here, we studied long-term PFOA exposure with an in vitro transformation model using the rat liver epithelial cell, TRL 1215. Cells were cultured in 10 µM (T10), 50 µM (T50) and 100 µM (T100) PFOA for 38 weeks and compared to passage-matched control cells. T100 cells showed morphological changes, loss of cell contact inhibition, formation of multinucleated giant and spindle-shaped cells. T10, T50, and T100 cells showed increased LC50 values 20%, 29% to 35% above control with acute PFOA treatment, indicating a resistance to PFOA toxicity. PFOA-treated cells showed increases in Matrix metalloproteinase-9 secretion, cell migration, and developed more and larger colonies in soft agar. Microarray data showed Myc pathway activation at T50 and T100, associating Myc upregulation with PFOA-induced morphological transformation. Western blot confirmed that PFOA produced significant increases in c-MYC protein expression in a time- and concentration-related manner. Tumor invasion indicators MMP-2 and MMP-9, cell cycle regulator cyclin D1, and oxidative stress protein GST were all significantly overexpressed in T100 cells. Taken together, chronic in vitro PFOA exposure produced multiple cell characteristics of malignant progression and differential gene expression changes suggestive of rat liver cell transformation.

Single nucleotide polymorphism patterns associated with a cancer resistant phenotype.

BACKGROUND AND AIMS: In this study ten mouse strains representing ~90% of genetic diversity in laboratory mice (B6C3F1/J, C57BL/6J, C3H/HeJ, A/J, NOD.B1oSnH2/J, NZO/HILtJ, 129S1/SvImJ, WSB/EiJ, PWK/PhJ, CAST/EiJ) were examined to identify the mouse strain with the lowest incidence of cancer. The unique single polymorphisms (SNPs) associated with this low cancer incidence are reported. METHODS: Evaluations of cancer incidence in the 10 mouse strains were based on gross and microscopic diagnosis of tumors. Single nucleotide polymorphisms (SNPs) in the coding regions of the genome were derived from the respective mouse strains located in the Sanger mouse sequencing database and the B6C3F1/N genome from the National Toxicology Program (NTP). RESULTS: The WSB strain had an overall lower incidence of both benign and malignant tumors compared to the other mouse strains. At 2 years, the incidence of total malignant tumors (Poly-3 incidence rate) ranged from 2% (WSB) to 92% (C3H) in males, and 14% (WSB) to 93% (NZO) in females, and the total incidence of benign and malignant tumor incidence ranged from 13% (WSB) to 99% (C3H) in males and 25% (WSB) to 96% (NOD) in females. Single nucleotide polymorphism (SNP) patterns were examined in the following strains: B6C3F1/N, C57BL/6J, C3H/HeJ, 129S1/SvImJ, A/J, NZO/HILtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ. We identified 7519 SNPs (involving 5751 Ensembl transcripts of 3453 Ensembl Genes) that resulted in a unique amino acid change in the coding region of the WSB strain. CONCLUSIONS: The inherited genetic patterns in the WSB cancer-resistant mouse strain occurred in genes involved in multiple cell functions including mitochondria, metabolic, immune, and membrane-related cell functions. The unique SNP patterns in a cancer resistant mouse strain provides insights for understanding and developing strategies for cancer prevention.

Deep Learning Image Analysis of High-Throughput Toxicology Assay Images.

High-throughput chemical screening approaches often employ microscopy to capture photomicrographs from multi-well cell culture plates, generating thousands of images that require time-consuming human analysis. To automate this subjective and time-consuming manual process, we have developed a method that uses deep learning to automatically classify digital assay images. We have trained a convolutional neural network (CNN) to perform binary and multi-class classification. The binary classifier binned assay images into healthy (comparable to untreated controls) and altered (not comparable to untreated-control) classes with >98% accuracy; the multi-class classifier assigned "Healthy," "Intermediate" and "Altered" labels to assay images with >95% accuracy. Our dataset comprised high-resolution assay images from primary human hepatocytes and undifferentiated (proliferating) and differentiated 2D cultures of HepaRG cells. In this study we have focused on testing and fine-tuning various CNN architectures, including ResNet 34, 50 and 101. To visualize regions in the images that the CNN model used for classification, we employed Class Activation Maps (CAM). This allowed us to better understand the inner workings of the neural network and led to additional optimizations of the algorithm. The results indicate a strong correspondence between dosage and classifier-predicted scores, suggesting that these scores might be useful in further characterizing benchmark dose. Together, these results clearly demonstrate that deep-learning based automated image classification of cell morphology changes upon chemical-induced stress can yield highly accurate and reproducible assessments of cytotoxicity across a variety of cell types.

Utility of Extrapolating Human S1500+ Genes to the Whole Transcriptome: Tunicamycin Case Study.

The TempO-Seq S1500+ platform(s), now available for human, mouse, rat, and zebrafish, measures a discrete number of genes that are representative of biological and pathway co-regulation across the entire genome in a given species. While measurement of these genes alone provides a direct assessment of gene expression activity, extrapolating expression values to the whole transcriptome (~26 000 genes in humans) can estimate measurements of non-measured genes of interest and increases the power of pathway analysis algorithms by using a larger background gene expression space. Here, we use data from primary hepatocytes of 54 donors that were treated with the endoplasmic reticulum (ER) stress inducer tunicamycin and then measured on the human S1500+ platform containing ~3000 representative genes. Measurements for the S1500+ genes were then used to extrapolate expression values for the remaining human transcriptome. As a case study of the improved downstream analysis achieved by extrapolation, the "measured only" and "whole transcriptome" (measured + extrapolated) gene sets were compared. Extrapolation increased the number of significant genes by 49%, bringing to the forefront many that are known to be associated with tunicamycin exposure. The extrapolation procedure also correctly identified established tunicamycin-related functional pathways reflected by coordinated changes in interrelated genes while maintaining the sample variability observed from the "measured only" genes. Extrapolation improved the gene- and pathway-level biological interpretations for a variety of downstream applications, including differential expression analysis, gene set enrichment pathway analysis, DAVID keyword analysis, Ingenuity Pathway Analysis, and NextBio correlated compound analysis. The extrapolated data highlight the role of metabolism/metabolic pathways, the ER, immune response, and the unfolded protein response, each of which are key activities associated with tunicamycin exposure that were unrepresented or underrepresented in one or more of the analyses of the original "measured only" dataset. Furthermore, the inclusion of the extrapolated genes raised "tunicamycin" from third to first upstream regulator in Ingenuity Pathway Analysis and from sixth to second most correlated compound in NextBio analysis. Therefore, our case study suggests an approach to extend and enhance data from the S1500+ platform for improved insight into biological mechanisms and functional outcomes of diseases, drugs, and other perturbations.

Quantitative Proteomic Profiling of Mitochondrial Toxicants in a Human Cardiomyocyte Cell Line.

Mitochondria are essential cellular organelles that participate in important cellular processes, including bioenergetics, metabolism, and signaling. Recent functional and proteomic studies have revealed the remarkable complexity of mitochondrial protein organization. Mitochondrial protein machineries with diverse functions such as protein translocation, respiration, metabolite transport, protein quality control and the control of membrane architecture interact with each other in dynamic networks. The goal of this study was to identify protein expression changes in a human cardiomyocyte cell line treated with several mitochondrial toxicants which inhibit mitochondrial membrane potential (MMP) and mitochondrial respiration. AC16 human cardiomyocyte cells were treated with carbonyl cyanide p-(trifluoromethoxy)phenylhydrazone (FCCP), dinoterb, picoxystrobin, pinacyanol, and triclocarban for 18 h around the IC50 values generated from MMP assay. The samples were harvested and labeled with tandem mass tags with different mass isotopes. Peptide assignment was performed in Proteome Discoverer. Each dataset was analyzed in Ingenuity Pathway Analysis (IPA). In the proteomic profile, these compounds showed dysregulation of a group of mitochondrial proteins (e.g., NDUA, NDUB, BCS1, CYB5B, and SDHF2), as well as proteins involved in lipid metabolism (e.g., CPT, MECR, and LPGAT1), cytoskeleton protein changes (e.g., CROCC, LAMC3, FBLN1, and FMN2) and stress response (e.g., IKBKG, IKBB, SYVN1, SOD2, and CPIN1). Proteomic data from the current study provides key insights into chemical induced cellular pathway dysregulation, supporting the use of proteomic profiling as a sensitive method to further explore molecular functions and disease pathogenesis upon exposure to environmental chemicals.

KRAS-retroviral fusion transcripts and gene amplification in arsenic-transformed, human prostate CAsE-PE cancer cells.

CAsE-PE cells are an arsenic-transformed, human prostate epithelial line containing oncogenic mutations in KRAS compared to immortalized, normal KRAS parent cells, RWPE-1. We previously reported increased copy number of mutated KRAS in CAsE-PE cells, suggesting gene amplification. Here, KRAS flanking genomic and transcriptomic regions were sequenced in CAsE-PE cells for insight into KRAS amplification. Comparison of DNA-Seq and RNA-Seq showed increased reads from background aligning to all KRAS exons in CAsE-PE cells, while a uniform DNA-Seq read distribution occurred in RWPE-1 cells with normal transcript expression. We searched for KRAS fusions in DNA and RNA sequencing data finding a portion of reads aligning to KRAS and viral sequence. After generation of cDNA from total RNA, short and long KRAS probes were generated to hybridize cDNA and KRAS enriched fragments were PacBio sequenced. More KRAS reads were captured from CAsE-PE cDNA versus RWPE-1 by each probe set. Only CAsE-PE cDNA showed KRAS viral fusion transcripts, primarily mapping to LTR and endogenous retrovirus sequences on either 5'- or 3'-ends of KRAS. Most KRAS viral fusion transcripts contained 4 to 6 exons but some PacBio sequences were in unusual orientations, suggesting viral insertions within the gene body. Additionally, conditioned media was extracted for potential retroviral particles. RNA-Seq of culture media isolates identified KRAS retroviral fusion transcripts in CAsE-PE media only. Truncated KRAS transcripts suggested multiple retroviral integration sites occurred within the KRAS gene producing KRAS retroviral fusions of various lengths. Findings suggest activation of endogenous retroviruses in arsenic carcinogenesis should be explored.

SWIFT-Active Screener: Accelerated document screening through active learning and integrated recall estimation.

BACKGROUND: In the screening phase of systematic review, researchers use detailed inclusion/exclusion criteria to decide whether each article in a set of candidate articles is relevant to the research question under consideration. A typical review may require screening thousands or tens of thousands of articles in and can utilize hundreds of person-hours of labor. METHODS: Here we introduce SWIFT-Active Screener, a web-based, collaborative systematic review software application, designed to reduce the overall screening burden required during this resource-intensive phase of the review process. To prioritize articles for review, SWIFT-Active Screener uses active learning, a type of machine learning that incorporates user feedback during screening. Meanwhile, a negative binomial model is employed to estimate the number of relevant articles remaining in the unscreened document list. Using a simulation involving 26 diverse systematic review datasets that were previously screened by reviewers, we evaluated both the document prioritization and recall estimation methods. RESULTS: On average, 95% of the relevant articles were identified after screening only 40% of the total reference list. In the 5 document sets with 5,000 or more references, 95% recall was achieved after screening only 34% of the available references, on average. Furthermore, the recall estimator we have proposed provides a useful, conservative estimate of the percentage of relevant documents identified during the screening process. CONCLUSION: SWIFT-Active Screener can result in significant time savings compared to traditional screening and the savings are increased for larger project sizes. Moreover, the integration of explicit recall estimation during screening solves an important challenge faced by all machine learning systems for document screening: when to stop screening a prioritized reference list. The software is currently available in the form of a multi-user, collaborative, online web application.

Identifying Compounds with Genotoxicity Potential Using Tox21 High-Throughput Screening Assays.

Genotoxicity is a critical component of a comprehensive toxicological profile. The Tox21 Program used five quantitative high-throughput screening (qHTS) assays measuring some aspect of DNA damage/repair to provide information on the genotoxic potential of over 10 000 compounds. Included were assays detecting activation of p53, increases in the DNA repair protein ATAD5, phosphorylation of H2AX, and enhanced cytotoxicity in DT40 cells deficient in DNA-repair proteins REV3 or KU70/RAD54. Each assay measures a distinct component of the DNA damage response signaling network; >70% of active compounds were detected in only one of the five assays. When qHTS results were compared with results from three standard genotoxicity assays (bacterial mutation, in vitro chromosomal aberration, and in vivo micronucleus), a maximum of 40% of known, direct-acting genotoxicants were active in one or more of the qHTS genotoxicity assays, indicating low sensitivity. This suggests that these qHTS assays cannot in their current form be used to replace traditional genotoxicity assays. However, despite the low sensitivity, ranking chemicals by potency of response in the qHTS assays revealed an enrichment for genotoxicants up to 12-fold compared with random selection, when allowing a 1% false positive rate. This finding indicates these qHTS assays can be used to prioritize chemicals for further investigation, allowing resources to focus on compounds most likely to induce genotoxic effects. To refine this prioritization process, models for predicting the genotoxicity potential of chemicals that were active in Tox21 genotoxicity assays were constructed using all Tox21 assay data, yielding a prediction accuracy up to 0.83. Data from qHTS assays related to stress-response pathway signaling (including genotoxicity) were the most informative for model construction. By using the results from qHTS genotoxicity assays, predictions from models based on qHTS data, and predictions from commercial bacterial mutagenicity QSAR models, we prioritized Tox21 chemicals for genotoxicity characterization.

Development of a Zebrafish S1500+ Sentinel Gene Set for High-Throughput Transcriptomics.

Sentinel gene sets have been developed with the purpose of maximizing the information from targeted transcriptomic platforms. We recently described the development of an S1500+ sentinel gene set, which was built for the human transcriptome, utilizing a data- and knowledge-driven hybrid approach to select a small subset of genes that optimally capture transcriptional diversity, correlation with other genes based on large-scale expression profiling, and known pathway annotation within the human genome. While this detailed bioinformatics approach for gene selection can in principle be applied to other species, the reliability of the resulting gene set depends on availability of a large body of transcriptomics data. For the model organism zebrafish, we aimed to create a similar sentinel gene set (Zf S1500+ gene set); however, there is insufficient standardized expression data in the public domain to train the gene correlation model. Therefore, our strategy was to use human-zebrafish ortholog mapping of the human S1500+ genes and nominations from experts in the zebrafish scientific community. In this study, we present the bioinformatics curation and refinement process to produce the final Zf S1500+ gene set, explore whole transcriptome extrapolation using this gene set, and assess pathway-level inference. This gene set will add value to targeted high-throughput transcriptomics in zebrafish for toxicogenomic screening and other research domains.

Next generation sequencing data for use in risk assessment.

Next generation sequencing (NGS) represents several powerful platforms that have revolutionized RNA and DNA analysis. The parallel sequencing of millions of DNA molecules can provide mechanistic insights into toxicology and provide new avenues for biomarker discovery with growing relevance for risk assessment. The evolution of NGS technologies has improved over the last decade with increased sensitivity and accuracy to foster new biomarker assays from tissue, blood and other biofluids. NGS sequencing technologies can identify transcriptional changes and genomic targets with base pair precision in response to chemical exposure. Further, there are several exciting movements within the toxicology community that incorporate NGS platforms into new strategies for more rapid toxicological characterizations. These include the Tox21 in vitro high throughput transcriptomic screening program, development of organotypic spheroids, alternative animal models, mining archival tissues, liquid biopsy and epigenomics. This review will describe NGS-based technologies, demonstrate how they can be used as tools for target discovery in tissue and blood, and suggest how they might be applied for risk assessment.

Arsenite malignantly transforms human prostate epithelial cells in vitro by gene amplification of mutated KRAS.

Inorganic arsenic is an environmental human carcinogen of several organs including the urinary tract. RWPE-1 cells are immortalized, non-tumorigenic, human prostate epithelia that become malignantly transformed into the CAsE-PE line after continuous in vitro exposure to 5µM arsenite over a period of months. For insight into in vitro arsenite transformation, we performed RNA-seq for differential gene expression and targeted sequencing of KRAS. We report >7,000 differentially expressed transcripts in CAsE-PE cells compared to RWPE-1 cells at >2-fold change, q<0.05 by RNA-seq. Notably, KRAS expression was highly elevated in CAsE-PE cells, with pathway analysis supporting increased cell proliferation, cell motility, survival and cancer pathways. Targeted DNA sequencing of KRAS revealed a mutant specific allelic imbalance, 'MASI', frequently found in primary clinical tumors. We found high expression of a mutated KRAS transcript carrying oncogenic mutations at codons 12 and 59 and many silent mutations, accompanied by lower expression of a wild-type allele. Parallel cultures of RWPE-1 cells retained a wild-type KRAS genotype. Copy number analysis and sequencing showed amplification of the mutant KRAS allele. KRAS is expressed as two splice variants, KRAS4a and KRAS4b, where variant 4b is more prevalent in normal cells compared to greater levels of variant 4a seen in tumor cells. 454 Roche sequencing measured KRAS variants in each cell type. We found KRAS4a as the predominant transcript variant in CAsE-PE cells compared to KRAS4b, the variant expressed primarily in RWPE-1 cells and in normal prostate, early passage, primary epithelial cells. Overall, gene expression data were consistent with KRAS-driven proliferation pathways found in spontaneous tumors and malignantly transformed cell lines. Arsenite is recognized as an important environmental carcinogen, but it is not a direct mutagen. Further investigations into this in vitro transformation model will focus on genomic events that cause arsenite-mediated mutation and overexpression of KRAS in CAsE-PE cells.

Identification of Compounds That Inhibit Estrogen-Related Receptor Alpha Signaling Using High-Throughput Screening Assays.

The nuclear receptor, estrogen-related receptor alpha (ERRα; NR3B1), plays a pivotal role in energy homeostasis. Its expression fluctuates with the demands of energy production in various tissues. When paired with the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), the PGC/ERR pathway regulates a host of genes that participate in metabolic signaling networks and in mitochondrial oxidative respiration. Unregulated overexpression of ERRα is found in many cancer cells, implicating a role in cancer progression and other metabolism-related diseases. Using high throughput screening assays, we screened the Tox21 10K compound library in stably transfected HEK293 cells containing either the ERRα-reporter or the reporter plus PGC-1α expression plasmid. We identified two groups of antagonists that were potent inhibitors of ERRα activity and/or the PGC/ERR pathway: nine antineoplastic agents and thirteen pesticides. Results were confirmed using gene expression studies. These findings suggest a novel mechanism of action on bioenergetics for five of the nine antineoplastic drugs. Nine of the thirteen pesticides, which have not been investigated previously for ERRα disrupting activity, were classified as such. In conclusion, we demonstrated that high-throughput screening assays can be used to reveal new biological properties of therapeutic and environmental chemicals, broadening our understanding of their modes of action.

DNA methylation in mice is influenced by genetics as well as sex and life experience.

DNA methylation is an essential epigenetic process in mammals, intimately involved in gene regulation. Here we address the extent to which genetics, sex, and pregnancy influence genomic DNA methylation by intercrossing 2 inbred mouse strains, C57BL/6N and C3H/HeN, and analyzing DNA methylation in parents and offspring using whole-genome bisulfite sequencing. Differential methylation across genotype is detected at thousands of loci and is preserved on parental alleles in offspring. In comparison of autosomal DNA methylation patterns across sex, hundreds of differentially methylated regions are detected. Comparison of animals with different histories of pregnancy within our study reveals a CpG methylation pattern that is restricted to female animals that had borne offspring. Collectively, our results demonstrate the stability of CpG methylation across generations, clarify the interplay of epigenetics with genetics and sex, and suggest that CpG methylation may serve as an epigenetic record of life events in somatic tissues at loci whose expression is linked to the relevant biology.

BMDExpress 2: enhanced transcriptomic dose-response analysis workflow.

SUMMARY: A new version (version 2) of the genomic dose-response analysis software, BMDExpress, has been created. The software addresses the increasing use of transcriptomic dose-response data in toxicology, drug design, risk assessment and translational research. In this new version, we have implemented additional statistical filtering options (e.g. Williams' trend test), curve fitting models, Linux and Macintosh compatibility and support for additional transcriptomic platforms with up-to-date gene annotations. Furthermore, we have implemented extensive data visualizations, on-the-fly data filtering, and a batch-wise analysis workflow. We have also significantly re-engineered the code base to reflect contemporary software engineering practices and streamline future development. The first version of BMDExpress was developed in 2007 to meet an unmet demand for easy-to-use transcriptomic dose-response analysis software. Since its original release, however, transcriptomic platforms, technologies, pathway annotations and quantitative methods for data analysis have undergone a large change necessitating a significant re-development of BMDExpress. To that end, as of 2016, the National Toxicology Program assumed stewardship of BMDExpress. The result is a modernized and updated BMDExpress 2 that addresses the needs of the growing toxicogenomics user community. AVAILABILITY AND IMPLEMENTATION: BMDExpress 2 is available at https://github.com/auerbachs/BMDExpress-2/releases. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Leucine-rich repeats and calponin homology containing 4 (Lrch4) regulates the innate immune response.

Toll-like receptors (TLRs) are pathogen-recognition receptors that trigger the innate immune response. Recent reports have identified accessory proteins that provide essential support to TLR function through ligand delivery and receptor trafficking. Herein, we introduce leucine-rich repeats (LRRs) and calponin homology containing 4 (Lrch4) as a novel TLR accessory protein. Lrch4 is a membrane protein with nine LRRs in its predicted ectodomain. It is widely expressed across murine tissues and has two expression variants that are both regulated by lipopolysaccharide (LPS). Predictive modeling indicates that Lrch4 LRRs conform to the horseshoe-shaped structure typical of LRRs in pathogen-recognition receptors and that the best structural match in the protein database is to the variable lymphocyte receptor of the jawless vertebrate hagfish. Silencing Lrch4 attenuates cytokine induction by LPS and multiple other TLR ligands and dampens the in vivo innate immune response. Lrch4 promotes proper docking of LPS in lipid raft membrane microdomains. We provide evidence that this is through regulation of lipid rafts as Lrch4 silencing reduces cell surface gangliosides, a metric of raft abundance, as well as expression and surface display of CD14, a raft-resident LPS co-receptor. Taken together, we identify Lrch4 as a broad-spanning regulator of the innate immune response and a potential molecular target in inflammatory disease.

Exome Sequencing of Fresh-frozen or Formalin-fixed Paraffin-embedded B6C3F1/N Mouse Hepatocellular Carcinomas Arising Either Spontaneously or due to Chronic Chemical Exposure.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide; however, the mutational properties of HCC-associated carcinogens remain largely uncharacterized. We hypothesized that mechanisms underlying chemical-induced HCC can be characterized by evaluating the mutational spectra of these tumors. To test this hypothesis, we performed exome sequencing of B6C3F1/N HCCs that arose either spontaneously in vehicle controls ( n = 3) or due to chronic exposure to gingko biloba extract (GBE; n = 4) or methyleugenol (MEG; n = 3). Most archived tumor samples are available as formalin-fixed paraffin-embedded (FFPE) blocks, rather than fresh-frozen (FF) samples; hence, exome sequencing from paired FF and FFPE samples was compared. FF and FFPE samples showed 63% to 70% mutation concordance. Multiple known (e.g., Ctnnb1T41A, BrafV637E) and novel (e.g., Erbb4C559S, Card10A700V, and Klf11P358L) mutations in cancer-related genes were identified. The overall mutational burden was greater for MEG than for GBE or spontaneous HCC samples. To characterize the mutagenic mechanisms, we analyzed the mutational spectra in the HCCs according to their trinucleotide motifs. The MEG tumors clustered closest to Catalogue of Somatic Mutations in Cancer signatures 4 and 24, which are, respectively, associated with benzo(a)pyrene- and aflatoxin-induced HCCs in humans. These results establish a novel approach for classifying liver carcinogens and understanding the mechanisms of hepatocellular carcinogenesis.

Dosage compensation and DNA methylation landscape of the X chromosome in mouse liver.

DNA methylation plays a key role in X-chromosome inactivation (XCI), a process that achieves dosage compensation for X-encoded gene products between mammalian female and male cells. However, differential sex chromosome dosage complicates genome-wide epigenomic assessments, and the X chromosome is frequently excluded from female-to-male comparative analyses. Using the X chromosome in the sexually dimorphic mouse liver as a model, we provide a general framework for comparing base-resolution DNA methylation patterns across samples that have different chromosome numbers and ask at a systematic level if predictions by historical analyses of X-linked DNA methylation hold true at a base-resolution chromosome-wide level. We demonstrate that sex-specific methylation patterns on the X chromosome largely reflect the effects of XCI. While our observations concur with longstanding observations of XCI at promoter-proximal CpG islands, we provide evidence that sex-specific DNA methylation differences are not limited to CpG island boundaries. Moreover, these data support a model in which maintenance of CpG islands in the inactive state does not require complete regional methylation. Further, we validate an intragenic non-CpG methylation signature in genes escaping XCI in mouse liver. Our analyses provide insight into underlying methylation patterns that should be considered when assessing sex differences in genome-wide methylation analyses.

Whole exome sequencing in the rat.

BACKGROUND: The rat genome was sequenced in 2004 with the aim to improve human health altered by disease and environmental influences through gene discovery and animal model validation. Here, we report development and testing of a probe set for whole exome sequencing (WES) to detect sequence variants in exons and UTRs of the rat genome. Using an in-silico approach, we designed probes targeting the rat exome and compared captured mutations in cancer-related genes from four chemically induced rat tumor cell lines (C6, FAT7, DSL-6A/C1, NBTII) to validated cancer genes in the human database, Catalogue of Somatic Mutations in Cancer (COSMIC) as well as normal rat DNA. Paired, fresh frozen (FF) and formalin-fixed, paraffin-embedded (FFPE) liver tissue from naive rats were sequenced to confirm known dbSNP variants and identify any additional variants. RESULTS: Informatics analysis of available gene annotation from rat RGSC6.0/rn6 RefSeq and Ensembl transcripts provided 223,636 unique exons representing a total of 26,365 unique genes and untranslated regions. Using this annotation and the Rn6 reference genome, an in-silico probe design generated 826,878 probe sequences of which 94.2% were uniquely aligned to the rat genome without mismatches. Further informatics analysis revealed 25,249 genes (95.8%) covered by at least one probe and 23,603 genes (93.5%) had every exon covered by one or more probes. We report high performance metrics from exome sequencing of our probe set and Sanger validation of annotated, highly relevant, cancer gene mutations as cataloged in the human COSMIC database, in addition to several exonic variants in cancer-related genes. CONCLUSIONS: An in-silico probe set was designed to enrich the rat exome from isolated DNA. The platform was tested on rat tumor cell lines and normal FF and FFPE liver tissue. The method effectively captured target exome regions in the test DNA samples with exceptional sensitivity and specificity to obtain reliable sequencing data representing variants that are likely chemically induced somatic mutations. Genomic discovery conducted by means of high throughput WES queries should benefit investigators in discovering rat genomic variants in disease etiology and in furthering human translational research.