Computational identification of hepatitis C virus associated microRNA-mRNA regulatory modules in human livers

<p>Abstract</p> <p>Background</p> <p>Hepatitis C virus (HCV) is a major cause of chronic liver disease by infecting over 170 million people worldwide. Recent studies have shown that microRNAs (miRNAs), a class of small non-coding regulatory RNAs, are involved in the regulation of HCV infection, but their functions have not been systematically studied. We propose an integrative strategy for identifying the miRNA-mRNA regulatory modules that are associated with HCV infection. This strategy combines paired expression profiles of miRNAs and mRNAs and computational target predictions. A miRNA-mRNA regulatory module consists of a set of miRNAs and their targets, in which the miRNAs are predicted to coordinately regulate the level of the target mRNA.</p> <p>Results</p> <p>We simultaneously profiled the expression of cellular miRNAs and mRNAs across 30 HCV positive or negative human liver biopsy samples using microarray technology. We constructed a miRNA-mRNA regulatory network, and using a graph theoretical approach, identified 38 miRNA-mRNA regulatory modules in the network that were associated with HCV infection. We evaluated the direct miRNA regulation of the mRNA levels of targets in regulatory modules using previously published miRNA transfection data. We analyzed the functional roles of individual modules at the systems level by integrating a large-scale protein interaction network. We found that various biological processes, including some HCV infection related canonical pathways, were regulated at the miRNA level during HCV infection.</p> <p>Conclusion</p> <p>Our regulatory modules provide a framework for future experimental analyses. This report demonstrates the utility of our approach to obtain new insights into post-transcriptional gene regulation at the miRNA level in complex human diseases.</p

Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury

ABSTRACT Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV.IMPORTANCESevere acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI

Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice

Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirroring that of the human population. Here we used mice from 44 influenza-infected pre-Collaborative Cross lines determined to have extreme phenotypes with regard to the host response to influenza A virus infection. Global transcriptome profiling identified 2671 transcripts that were significantly differentially expressed between mice that showed a severe (“high”) and mild (“low”) response to infection. Expression quantitative trait loci mapping was performed on those transcripts that were differentially expressed because of differences in host response phenotype to identify putative regulatory regions potentially controlling their expression. Twenty-one significant expression quantitative trait loci were identified, which allowed direct examination of genes associated with regulation of host response to infection. To perform initial validation of our findings, quantitative polymerase chain reaction was performed in the infected founder strains, and we were able to confirm or partially confirm more than 70% of those tested. In addition, we explored putative causal and reactive (downstream) relationships between the significantly regulated genes and others in the high or low response groups using structural equation modeling. By using systems approaches and a genetically diverse population, we were able to develop a novel framework for identifying the underlying biological subnetworks under host genetic control during influenza virus infection

Lethal Influenza Virus Infection in Macaques Is Associated with Early Dysregulation of Inflammatory Related Genes

The enormous toll on human life during the 1918–1919 Spanish influenza pandemic is a constant reminder of the potential lethality of influenza viruses. With the declaration by the World Health Organization of a new H1N1 influenza virus pandemic, and with continued human cases of highly pathogenic H5N1 avian influenza virus infection, a better understanding of the host response to highly pathogenic influenza viruses is essential. To this end, we compared pathology and global gene expression profiles in bronchial tissue from macaques infected with either the reconstructed 1918 pandemic virus or the highly pathogenic avian H5N1 virus A/Vietnam/1203/04. Severe pathology was observed in respiratory tissues from 1918 virus-infected animals as early as 12 hours after infection, and pathology steadily increased at later time points. Although tissues from animals infected with A/Vietnam/1203/04 also showed clear signs of pathology early on, less pathology was observed at later time points, and there was evidence of tissue repair. Global transcriptional profiles revealed that specific groups of genes associated with inflammation and cell death were up-regulated in bronchial tissues from animals infected with the 1918 virus but down-regulated in animals infected with A/Vietnam/1203/04. Importantly, the 1918 virus up-regulated key components of the inflammasome, NLRP3 and IL-1β, whereas these genes were down-regulated by A/Vietnam/1203/04 early after infection. TUNEL assays revealed that both viruses elicited an apoptotic response in lungs and bronchi, although the response occurred earlier during 1918 virus infection. Our findings suggest that the severity of disease in 1918 virus-infected macaques is a consequence of the early up-regulation of cell death and inflammatory related genes, in which additive or synergistic effects likely dictate the severity of tissue damage

Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross

Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC) recombinant inbred (RI) panel (the pre-CC population) to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules) that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL) mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza Mx1 gene. We sequenced the coding regions of Mx1 in the eight CC founder strains, and identified a novel Mx1 allele that showed reduced ability to inhibit viral replication, while maintaining protection from weight loss

Genomic Analysis Reveals Pre- and Postchallenge Differences in a Rhesus Macaque AIDS Vaccine Trial: Insights into Mechanisms of Vaccine Efficacy▿ †

We have employed global transcriptional profiling of whole blood to identify biologically relevant changes in cellular gene expression in response to alternative AIDS vaccine strategies with subsequent viral challenge in a rhesus macaque vaccine model. Samples were taken at day 0 (prechallenge), day 14 (peak viremia), and week 12 (set point) from animals immunized with replicating adenovirus type 5 host range (Ad5hr) recombinant viruses expressing human immunodeficiency virus HIVenv89.6P, simian immunodeficiency virus SIVgag239, or SIVnef239 alone or in combination with two intramuscular boosts with HIV89.6Pgp140ΔCFI protein (L. J. Patterson et al., Virology 374:322-337, 2008), and each treatment resulted in significant control of viremia following simian-human immunodeficiency virus SHIV89.6P challenge (six animals per group plus six controls). At day 0, 8 weeks after the last treatment, the microarray profiles revealed significant prechallenge differences between treatment groups; data from the best-protected animals led to identification of a network of genes related to B cell development and lymphocyte survival. At peak viremia, expression profiles of the immunized groups were extremely similar, and comparisons to control animals reflected immunological differences other than effector T cell functions. Suggested protective mechanisms for vaccinated animals included upregulation of interleukin-27, a cytokine known to inhibit lentivirus replication, and increased expression of complement components, which may synergize with vaccine-induced antibodies. Divergent expression profiles at set point for the immunized groups implied distinct immunological responses despite phenotypic similarities in viral load and CD4+ T cell levels. Data for the gp140-boosted group provided evidence for antibody-dependent, cell-mediated viral control, whereas animals immunized with only the replicating Ad5hr recombinants exhibited a different evolution of the B cell compartment even at 3 months postchallenge. This study demonstrates the sensitivity and discrimination of gene expression profiling of whole blood as an analytical tool in AIDS vaccine trials, providing unique insights into in vivo mechanisms and potential correlates of protection

Expression quantitative trait loci for extreme host response to influenza A in pre-collaborative cross mice

Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirroring that of the human population. Here we used mice from 44 influenza-infected pre-Collaborative Cross lines determined to have extreme phenotypes with regard to the host response to influenza A virus infection. Global transcriptome profiling identified 2671 transcripts that were significantly differentially expressed between mice that showed a severe ("high") and mild ("low") response to infection. Expression quantitative trait loci mapping was performed on those transcripts that were differentially expressed because of differences in host response phenotype to identify putative re

Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross

<div><p>Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC) recombinant inbred (RI) panel (the pre-CC population) to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules) that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL) mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza <i>Mx1</i> gene. We sequenced the coding regions of <i>Mx1</i> in the eight CC founder strains, and identified a novel <i>Mx1</i> allele that showed reduced ability to inhibit viral replication, while maintaining protection from weight loss.</p> </div