TCDD dysregulation of lncRNA expression, liver zonation and intercellular communication across the liver lobule.

The persistent environmental aryl hydrocarbon receptor agonist and hepatotoxin TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin) induces hepatic lipid accumulation (steatosis), inflammation (steatohepatitis) and fibrosis. Thousands of liver-expressed, nuclear-localized lncRNAs with regulatory potential have been identified; however, their roles in TCDD-induced hepatoxicity and liver disease are unknown. We analyzed single nucleus (sn)RNA-seq data from control and subchronic (4 wk) TCDD-exposed mouse liver to determine liver cell-type specificity, zonation and differential expression profiles for thousands of lncRNAs. TCDD dysregulated >4000 of these lncRNAs in one or more liver cell types, including 684 lncRNAs specifically dysregulated in liver non-parenchymal cells. Trajectory inference analysis revealed major disruption by TCDD of hepatocyte zonation, affecting >800 genes, including 121 lncRNAs, with strong enrichment for lipid metabolism genes. TCDD also dysregulated expression of >200 transcription factors, including 19 Nuclear Receptors, most notably in hepatocytes and Kupffer cells. TCDD-induced changes in cell-cell communication patterns included marked decreases in EGF signaling from hepatocytes to non-parenchymal cells and increases in extracellular matrix-receptor interactions central to liver fibrosis. Gene regulatory networks constructed from the snRNA-seq data identified TCDD-exposed liver network-essential lncRNA regulators linked to functions such as fatty acid metabolic process, peroxisome and xenobiotic metabolism. Networks were validated by the striking enrichments that predicted regulatory lncRNAs showed for specific biological pathways. These findings highlight the power of snRNA-seq to discover functional roles for many xenobiotic-responsive lncRNAs in both hepatocytes and liver non-parenchymal cells and to elucidate novel aspects of foreign chemical-induced hepatotoxicity and liver disease, including dysregulation of intercellular communication within the liver lobule.

Dysregulation of murine long noncoding single-cell transcriptome in nonalcoholic steatohepatitis and liver fibrosis.

LncRNAs comprise a heterogeneous class of RNA-encoding genes typified by low expression, nuclear enrichment, high tissue-specificity, and functional diversity, but the vast majority remain uncharacterized. Here, we assembled the mouse liver noncoding transcriptome from >2000 bulk RNA-seq samples and discovered 48,261 liver-expressed lncRNAs, a majority novel. Using these lncRNAs as a single-cell transcriptomic reference set, we elucidated lncRNA dysregulation in mouse models of high fat diet-induced nonalcoholic steatohepatitis and carbon tetrachloride-induced liver fibrosis. Trajectory inference analysis revealed lncRNA zonation patterns across the liver lobule in each major liver cell population. Perturbations in lncRNA expression and zonation were common in several disease-associated liver cell types, including nonalcoholic steatohepatitis-associated macrophages, a hallmark of fatty liver disease progression, and collagen-producing myofibroblasts, a central feature of liver fibrosis. Single-cell-based gene regulatory network analysis using bigSCale2 linked individual lncRNAs to specific biological pathways, and network-essential regulatory lncRNAs with disease-associated functions were identified by their high network centrality metrics. For a subset of these lncRNAs, promoter sequences of the network-defined lncRNA target genes were significantly enriched for lncRNA triplex formation, providing independent mechanistic support for the lncRNA-target gene linkages predicted by the gene regulatory networks. These findings elucidate liver lncRNA cell-type specificities, spatial zonation patterns, associated regulatory networks, and temporal patterns of dysregulation during hepatic disease progression. A subset of the liver disease-associated regulatory lncRNAs identified have human orthologs and are promising candidates for biomarkers and therapeutic targets.

TCDD dysregulation of lncRNA expression, liver zonation and intercellular communication across the liver lobule.

The persistent environmental aryl hydrocarbon receptor agonist and hepatotoxin TCDD (2,3,7,8-tetrachlorodibenzo- p -dioxin) induces hepatic lipid accumulation (steatosis), inflammation (steatohepatitis) and fibrosis. Thousands of liver-expressed, nuclear-localized lncRNAs with regulatory potential have been identified; however, their roles in TCDD-induced hepatoxicity and liver disease are unknown. We analyzed single nucleus (sn)RNA-seq data from control and chronic TCDD-exposed mouse liver to determine liver cell-type specificity, zonation and differential expression profiles for thousands of IncRNAs. TCDD dysregulated >4,000 of these lncRNAs in one or more liver cell types, including 684 lncRNAs specifically dysregulated in liver non-parenchymal cells. Trajectory inference analysis revealed major disruption by TCDD of hepatocyte zonation, affecting >800 genes, including 121 IncRNAs, with strong enrichment for lipid metabolism genes. TCDD also dysregulated expression of >200 transcription factors, including 19 Nuclear Receptors, most notably in hepatocytes and Kupffer cells. TCDD-induced changes in cellâ€"cell communication patterns included marked decreases in EGF signaling from hepatocytes to non-parenchymal cells and increases in extracellular matrix-receptor interactions central to liver fibrosis. Gene regulatory networks constructed from the snRNA-seq data identified TCDD-exposed liver network-essential lncRNA regulators linked to functions such as fatty acid metabolic process, peroxisome and xenobiotic metabolic. Networks were validated by the striking enrichments that predicted regulatory IncRNAs showed for specific biological pathways. These findings highlight the power of snRNA-seq to discover functional roles for many xenobiotic-responsive lncRNAs in both hepatocytes and liver non-parenchymal cells and to elucidate novel aspects of foreign chemical-induced hepatotoxicity and liver disease, including dysregulation of intercellular communication within the liver lobule.

Long non-coding RNA G23Rik attenuates fasting-induced lipid accumulation in mouse liver.

Peroxisome proliferator-activated receptor α (PPARα) is a key mediator of lipid metabolism and metabolic stress in the liver. A recent study revealed that PPARα-dependent long non-coding RNAs (lncRNAs) play an important role in modulating metabolic stress and inflammation in the livers of fasted mice. Here hepatic lncRNA 3930402G23Rik (G23Rik) was found to have active peroxisome proliferator response elements (PPREs) within its promoter and is directly regulated by PPARα. Although G23Rik RNA was expressed to varying degrees in several tissues, the PPARα-dependent regulation of this lncRNA was only observed in the liver. Pharmacological activation of PPARα induced PPARα recruitment at the G23Rik promoter and a pronounced increase in hepatic G23Rik lncRNA expression. A G23Rik-null mouse line was developed to further characterize the function of this lncRNA in the liver. G23Rik-null mice were more susceptible to hepatic lipid accumulation in response to acute fasting. Histological analysis further revealed a pronounced buildup of lipid droplets and a significant increase in neutral triglycerides and lipids as indicated by enhanced oil red O staining of liver sections. Hepatic cholesterol, non-esterified fatty acid, and triglyceride levels were significantly elevated in G23Rik-null mice and associated with induction of the lipid-metabolism related gene Cd36. These findings provide evidence for a lncRNA dependent mechanism by which PPARα attenuates hepatic lipid accumulation in response to metabolic stress through lncRNA G23Rik induction.

Interplay Between GH-regulated, Sex-biased Liver Transcriptome and Hepatic Zonation Revealed by Single-Nucleus RNA Sequencing.

The zonation of liver metabolic processes is well-characterized; however, little is known about the cell type-specificity and zonation of sexually dimorphic gene expression or its growth hormone (GH)-dependent transcriptional regulators. We address these issues using single-nucleus RNA-sequencing of 32 000 nuclei representing 9 major liver cell types. Nuclei were extracted from livers from adult male and female mice; from males infused with GH continuously, mimicking the female plasma GH pattern; and from mice exposed to TCPOBOP, a xenobiotic agonist ligand of the nuclear receptor CAR that perturbs sex-biased gene expression. Analysis of these rich transcriptomic datasets revealed the following: 1) expression of sex-biased genes and their GH-dependent transcriptional regulators is primarily restricted to hepatocytes and is not a feature of liver nonparenchymal cells; 2) many sex-biased transcripts show sex-dependent zonation within the liver lobule; 3) gene expression is substantially feminized both in periportal and pericentral hepatocytes when male mice are infused with GH continuously; 4) sequencing nuclei increases the sensitivity for detecting thousands of nuclear-enriched long-noncoding RNAs (lncRNAs) and enables determination of their liver cell type-specificity, sex-bias and hepatocyte zonation profiles; 5) the periportal to pericentral hepatocyte cell ratio is significantly higher in male than female liver; and 6) TCPOBOP exposure disrupts both sex-specific gene expression and hepatocyte zonation within the liver lobule. These findings highlight the complex interconnections between hepatic sexual dimorphism and zonation at the single-cell level and reveal how endogenous hormones and foreign chemical exposure can alter these interactions across the liver lobule with large effects both on protein-coding genes and lncRNAs.

Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to PPARA agonism and fasting.

Exploring the molecular mechanisms that prevent inflammation during caloric restriction may yield promising therapeutic targets. During fasting, activation of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα) promotes the utilization of lipids as an energy source. Herein, we show that ligand activation of PPARα directly upregulates the long non-coding RNA gene Gm15441 through PPARα binding sites within its promoter. Gm15441 expression suppresses its antisense transcript, encoding thioredoxin interacting protein (TXNIP). This, in turn, decreases TXNIP-stimulated NLR family pyrin domain containing 3 (NLRP3) inflammasome activation, caspase-1 (CASP1) cleavage, and proinflammatory interleukin 1ß (IL1B) maturation. Gm15441-null mice were developed and shown to be more susceptible to NLRP3 inflammasome activation and to exhibit elevated CASP1 and IL1B cleavage in response to PPARα agonism and fasting. These findings provide evidence for a mechanism by which PPARα attenuates hepatic inflammasome activation in response to metabolic stress through induction of lncRNA Gm15441.

Widespread Dysregulation of Long Noncoding Genes Associated With Fatty Acid Metabolism, Cell Division, and Immune Response Gene Networks in Xenobiotic-exposed Rat Liver.

Xenobiotic exposure dysregulates hundreds of protein-coding genes in mammalian liver, impacting many physiological processes and inducing diverse toxicological responses. Little is known about xenobiotic effects on long noncoding RNAs (lncRNAs), many of which have important regulatory functions. Here, we present a computational framework to discover liver-expressed, xenobiotic-responsive lncRNAs (xeno-lncs) with strong functional, gene regulatory potential and elucidate the impact of xenobiotic exposure on their gene regulatory networks. We assembled the long noncoding transcriptome of xenobiotic-exposed rat liver using RNA-seq datasets from male rats treated with 27 individual chemicals, representing 7 mechanisms of action (MOAs). Ortholog analysis was combined with coexpression data and causal inference methods to infer lncRNA function and deduce gene regulatory networks, including causal effects of lncRNAs on protein-coding gene expression and biological pathways. We discovered > 1400 liver-expressed xeno-lncs, many with human and/or mouse orthologs. Xenobiotics representing different MOAs often regulated common xeno-lnc targets: 123 xeno-lncs were dysregulated by ≥ 10 chemicals, and 5 xeno-lncs responded to ≥ 20 of the 27 chemicals investigated; 81 other xeno-lncs served as MOA-selective markers of xenobiotic exposure. Xeno-lnc-protein-coding gene coexpression regulatory network analysis identified xeno-lncs closely associated with exposure-induced perturbations of hepatic fatty acid metabolism, cell division, or immune response pathways, and with apoptosis or cirrhosis. We also identified hub and bottleneck lncRNAs, which are expected to be key regulators of gene expression. This work elucidates extensive networks of xeno-lnc-protein-coding gene interactions and provides a framework for understanding the widespread transcriptome-altering actions of foreign chemicals in a key-responsive mammalian tissue.

Pipeliner: A Nextflow-Based Framework for the Definition of Sequencing Data Processing Pipelines.

The advent of high-throughput sequencing technologies has led to the need for flexible and user-friendly data preprocessing platforms. The Pipeliner framework provides an out-of-the-box solution for processing various types of sequencing data. It combines the Nextflow scripting language and Anaconda package manager to generate modular computational workflows. We have used Pipeliner to create several pipelines for sequencing data processing including bulk RNA-sequencing (RNA-seq), single-cell RNA-seq, as well as digital gene expression data. This report highlights the design methodology behind Pipeliner that enables the development of highly flexible and reproducible pipelines that are easy to extend and maintain on multiple computing environments. We also provide a quick start user guide demonstrating how to setup and execute available pipelines with toy datasets.

Identifying enriched drug fragments as possible candidates for metabolic engineering.

BACKGROUND: Fragment-based approaches have now become an important component of the drug discovery process. At the same time, pharmaceutical chemists are more often turning to the natural world and its extremely large and diverse collection of natural compounds to discover new leads that can potentially be turned into drugs. In this study we introduce and discuss a computational pipeline to automatically extract statistically overrepresented chemical fragments in therapeutic classes, and search for similar fragments in a large database of natural products. By systematically identifying enriched fragments in therapeutic groups, we are able to extract and focus on few fragments that are likely to be active or structurally important. RESULTS: We show that several therapeutic classes (including antibacterial, antineoplastic, and drugs active on the cardiovascular system, among others) have enriched fragments that are also found in many natural compounds. Further, our method is able to detect fragments shared by a drug and a natural product even when the global similarity between the two molecules is generally low. CONCLUSIONS: A further development of this computational pipeline is to help predict putative therapeutic activities of natural compounds, and to help identify novel leads for drug discovery.