Bioinformatic analysis reveals cRel as a regulator of a subset of interferon-stimulated genes

Role of the transcription factor Fli-1 on the CXCL10/CXCR3 Axis

The transcription factor Fli-1, a member of the ETS family of transcription factors, is implicated in the pathogenesis of lupus disease. Reduced Fli-1 expression in lupus mice leads to decreased renal Cxcl10 mRNA levels and renal infiltrating CXCR3+ T cells that parallels reduced renal inflammatory cell infiltration and renal damage. Inflammatory chemokine CXCL10 is critical for attracting inflammatory cells expressing the chemokine receptor CXCR3. The CXCL10/CXCR3 axis plays a role in the pathogenesis of various inflammatory diseases including lupus. Our data here demonstrate that renal CXCL10 protein levels are significantly lower in Fli-1 heterozygous MRL/lpr mice compared to wild-type MRL/lpr mice. Knockdown of Fli-1 significantly reduced CXCL10 secretion in mouse and human endothelial cells, and human mesangial cells, upon LPS or TNFα stimulation. The Fli-1 inhibitor, Camptothecin, significantly reduced CXCL10 production in human monocyte cells upon interferon stimulation. Four putative Ets binding sites in the Cxcl10 promoter showed significant enrichment for FLI-1; however, FLI-1 did not directly drive transcription from the human or mouse promoters, suggesting FLI-1 may regulate CXCL10 expression indirectly. Our results also suggest that the DNA binding domain of FLI-1 is necessary for regulation of human hCXCR3 promotor activity in human T cells and interactions with co-activators. Together, these results support a role for FLI-1 in modulating the CXCL10-CXCR3 axis by directly or indirectly regulating the expression of both genes to impact lupus disease development. Signaling pathways or drugs that reduce FLI-1 expression may offer novel approaches to lupus treatment.

The emerging roles of IFIT3 in antiviral innate immunity and cellular biology

The interferon-inducible protein with tetrapeptide repeats 3 (IFIT3) is one of the most important members in both the IFIT family and interferon-stimulated genes family. IFIT3 has typical features of the IFIT family in terms of gene and protein structures, and is able to be activated through the classical PRRs-IFN-JAK/STAT pathway. A variety of viruses can induce the expression of IFIT3, which in turn inhibits the replication of viruses, with the underlying mechanism showing its crucial role in antiviral innate immunity. Emerging studies have also identified that IFIT3 is involved in cellular biology changes, including cell proliferation, apoptosis, differentiation, and cancer development. In this review, we summarize the characteristics of IFIT3 with respect to molecular structure and regulatory pathways, highlighting the role of IFIT3 in antiviral innate immunity, as well as its diverse biological roles. We also discuss the potential of IFIT3 as a biomarker in disease diagnosis and therapy.

ISG15 induction is required during L1-mediated colon cancer progression and metastasis

Hyperactivation of Wnt/β-catenin target gene expression is a hallmark of colorectal cancer (CRC) development. We identified L1-CAM (L1) and Nr-CAM, members of the immunoglobulin family of nerve cell adhesion receptors, as target genes of the Wnt/β-catenin pathway in CRC cells. L1 overexpression in CRC cells enhances their motile and tumorigenic capacity and promotes liver metastasis. L1 is often localized at the invasive edge of CRC tissue. Using gene arrays and proteomic analyses we identified downstream signaling pathways and targets of L1-mediated signaling. Here, we found that the expression of interferon-stimulated gene 15 (ISG15) that operates much like ubiquitin (is conjugated to proteins by ISGylation), is elevated in the conditioned medium and in CRC cells overexpressing L1. Suppression of endogenous ISG15 levels in L1-expressing cells blocked the increased proliferative, motile, tumorigenic and liver metastatic capacities of CRC cells. ISG15 overexpression, on its own, could enhance these properties in CRC cells, but only to a much lower extent compared to L1. We show that NF-κB signaling is involved in the L1-mediated increase in ISG15, since blocking the NF-κB pathway abolished the induction of ISG15 by L1. Point mutations in the L1 ectodomain that interfere with its binding to L1 ligands, also inhibited the increase in ISG15. We detected high levels of ISG15 in human CRC tissue cells and in the adjacent stroma, but not in the normal mucosa. The results suggest that ISG15 is involved in L1-mediated CRC development and is a potential target for CRC therapy.

Strand-Specific Dual RNA Sequencing of Bronchial Epithelial Cells Infected with Influenza A/H3N2 Viruses Reveals Splicing of Gene Segment 6 and Novel Host-Virus Interactions

Host-influenza virus interplay at the transcript level has been extensively characterized in epithelial cells. Yet, there are no studies that simultaneously characterize human host and influenza A virus (IAV) genomes. We infected human bronchial epithelial BEAS-2B cells with two seasonal IAV/H3N2 strains, Brisbane/10/07 and Perth/16/09 (reference strains for past vaccine seasons) and the well-characterized laboratory strain Udorn/307/72. Strand-specific RNA sequencing (RNA-seq) of the infected BEAS-2B cells allowed for simultaneous analysis of host and viral transcriptomes, in addition to pathogen genomes, to reveal changes in mRNA expression and alternative splicing (AS). In general, patterns of global and immune gene expression induced by the three IAVs were mostly shared. However, AS of host transcripts and small nuclear RNAs differed between the seasonal and laboratory strains. Analysis of viral transcriptomes showed deletions of the polymerase components (defective interfering-like RNAs) within the genome. Surprisingly, we found that the neuraminidase gene undergoes AS and that the splicing event differs between seasonal and laboratory strains. Our findings reveal novel elements of the host-virus interaction and highlight the importance of RNA-seq in identifying molecular changes at the genome level that may contribute to shaping RNA-based innate immunity.IMPORTANCE The use of massively parallel RNA sequencing (RNA-seq) has revealed insights into human and pathogen genomes and their evolution. Dual RNA-seq allows simultaneous dissection of host and pathogen genomes and strand-specific RNA-seq provides information about the polarity of the RNA. This is important in the case of negative-strand RNA viruses like influenza virus, which generate positive (complementary and mRNA) and negative-strand RNAs (genome) that differ in their potential to trigger innate immunity. Here, we characterize interactions between human bronchial epithelial cells and three influenza A/H3N2 strains using strand-specific dual RNA-seq. We focused on this subtype because of its epidemiological importance in causing significant morbidity and mortality during influenza epidemics. We report novel elements that differ between seasonal and laboratory strains highlighting the complexity of the host-virus interplay at the RNA level.

IFN-γ extends the immune functions of Guanylate Binding Proteins to inflammasome-independent antibacterial activities during Francisella novicida infection

Guanylate binding proteins (GBPs) are interferon-inducible proteins involved in the cell-intrinsic immunity against numerous intracellular pathogens. The molecular mechanisms underlying the potent antibacterial activity of GBPs are still unclear. GBPs have been functionally linked to the NLRP3, the AIM2 and the caspase-11 inflammasomes. Two opposing models are currently proposed to explain the GBPs-inflammasome link: i) GBPs would target intracellular bacteria or bacteria-containing vacuoles to increase cytosolic PAMPs release ii) GBPs would directly facilitate inflammasome complex assembly. Using Francisella novicida infection, we investigated the functional interactions between GBPs and the inflammasome. GBPs, induced in a type I IFN-dependent manner, are required for the F. novicida-mediated AIM2-inflammasome pathway. Here, we demonstrate that GBPs action is not restricted to the AIM2 inflammasome, but controls in a hierarchical manner the activation of different inflammasomes complexes and apoptotic caspases. IFN-γ induces a quantitative switch in GBPs levels and redirects pyroptotic and apoptotic pathways under the control of GBPs. Furthermore, upon IFN-γ priming, F. novicida-infected macrophages restrict cytosolic bacterial replication in a GBP-dependent and inflammasome-independent manner. Finally, in a mouse model of tularemia, we demonstrate that the inflammasome and the GBPs are two key immune pathways functioning largely independently to control F. novicida infection. Altogether, our results indicate that GBPs are the master effectors of IFN-γ-mediated responses against F. novicida to control antibacterial immune responses in inflammasome-dependent and independent manners.

The cell-intrinsic immunity is defined as the mechanisms allowing a host cell infected by an intracellular pathogen to mount effective immune mechanisms to detect and eliminate pathogens without any help from other immune cells. In infected macrophages, the Guanylate Binding Proteins (GBPs) are immune proteins, induced at low levels in a cell autonomous manner by endogenous type I IFN or at high levels following IFN-γ production by innate and adaptive lymphocytes. The antibacterial activity of GBPs has been recently tightly linked to the inflammasomes. Inflammasomes are innate immune complexes leading to inflammatory caspases activation and death of the infected cell. Francisella novicida, a bacterium replicating in the macrophage cytosol, is closely related to F. tularensis, the agent of tularemia and is used as a model to study cytosolic immunity. GBPs contribute to F. novicida lysis within the host cytosol leading to DNA release and AIM2 inflammasome activation. In addition to their regulation of the AIM2 inflammasome, we identified that GBPs also control several other pyroptotic and apoptotic pathways activated in a hierarchical manner. Furthermore, we demonstrate that IFN-γ priming extends GBPs anti-microbial responses from the inflammasome-dependent control of cell death to an inflammasome-independent control of cytosolic bacterial replication. Our results, validated in a mouse model of tularemia, thus segregate the antimicrobial activities of inflammasomes and GBPs as well as highlight GBPs as the master effectors of IFN-γ-mediated cytosolic immunity.

Unphosphorylated STAT3 regulates the antiproliferative, antiviral, and gene-inducing actions of type I interferons

Type I interferon (IFNα/β) induces antiviral and antiproliferative responses in cells through the induction of IFN-stimulated genes (ISGs). Although the roles of IFN-activated STAT1 and STAT2 in the IFN response are well described, the function of STAT3 is poorly characterized. We investigated the role of STAT3 in the biological response to IFNα/β in mouse embryonic fibroblasts (MEFs) with a germ line deletion of STAT3. These STAT3 knockout (STAT3-KO) MEFs were reconstituted with STAT3 or the F705-STAT3 mutant (unphosphorylated STAT3) where the canonical Y705 tyrosine phosphorylation site was mutated. We show that both STAT3 and unphosphorylated STAT3 expression enhance the sensitivity of MEFs to the antiviral, antiproliferative and gene-inducing actions of IFN. By chromatin immunoprecipitation assays, unphosphorylated STAT3 appears to bind, albeit weakly, to select gene promoters to enhance their expression. These results suggest that unphosphorylated STAT3 plays an important role in the IFN response pathway.

The Contribution of Immune Infiltrates to Ototoxicity and Cochlear Hair Cell Loss

Cells of the immune system have been shown to infiltrate the cochlea after acoustic trauma or ototoxic drug treatment; however, the contribution of the immune system to hair cell loss in the inner ear is incompletely understood. Most studies have concentrated on the immediate innate response to hair cell damage using CD45 as a broad marker for all immune cells. More recent studies have used RNA sequencing, GeneChip arrays and quantitative PCR to analyze gene expression in the entire cochlea after auditory trauma, leading to a better understanding of the chemokines and cytokines that attract immune cells to the cochlea. Immune suppression by blocking cytokines or immune receptors has been proven to suppress hair cell damage. However, it is now understood that not all immune cells are detrimental to the cochlea. CX3CR1+ resident macrophages protect hair cells from damage mediated by infiltrating immune cells. Systemically, the immune response is associated with both protection and pathology, and it has been implicated in the regeneration of certain tissues after injury. This review focuses on the studies of immune cells in various models of hearing loss and highlights the steps that can be taken to elucidate the connection between the immune response and hearing loss. The interplay between the immune system and tissues that were previously thought to be immune privileged, such as the cochlea, is an emerging research field, to which additional studies of the immune component of the cochlear response to injury will make an important contribution.

Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens

Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes-such as transcriptional profiles-at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays.

Overexpression of IFN-induced protein with tetratricopeptide repeats 3 (IFIT3) in pancreatic cancer: cellular "pseudoinflammation" contributing to an aggressive phenotype

Inflammation contributes to important traits that cancer cells acquire during malignant progression. Gene array data recently identified upregulation of interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) in aggressive pancreatic cancer cells. IFIT3 belongs to the group of interferon stimulated genes (ISG), can be induced by several cellular stress stimuli and by its tetratricopeptide repeats interacts with a multitude of cellular proteins.

Upregulation of IFIT3 was confirmed in the aggressive pancreatic cancer cell line L3.6pl compared with its less aggressive cell line of origin, COLO357FG. Transgenic induction of IFIT3 expression in COLO357FG resulted in greater mass of orthotopic tumors and higher prevalence of metastases. Several important traits that mediate malignancy were altered by IFIT3: increased VEGF and IL-6 secretion, chemoresistance and decreased starvation-induced apoptosis. IFIT3 showed binding to JNK and STAT1, the latter being an important inducer of IFIT3 expression. Despite still being alterable by “classical” IFN or NFκB signaling, our findings indicate constitutive - possibly auto-regulated - upregulation of IFIT3 in L3.6pl without presence of an adequate inflammatory stimulus. The transcription factor SOX9, which is linked to regulation of hypoxia-related genes, was identified as a key mediator of upregulation of the oncogene IFIT3 and thereby sustaining a “pseudoinflammatory” cellular condition.

An interferon response gene signature is associated with the therapeutic response of hepatitis C patients

Infection with the hepatitis C virus (HCV) is a major cause of chronic liver diseases and hepatocellular carcinoma worldwide, and thus represents a significant public health problem. The type I interferon (IFN), IFNα, has been successful in treating HCV-infected patients, but current IFN-based treatment regimens for HCV have suboptimal efficacy, and relatively little is known about why IFN therapy eliminates the virus in some patients but not in others. Therefore, it is critical to understand the basic mechanisms that underlie the therapeutic resistance to IFN action in HCV-infected individuals, and there is an urgent need to identify those patients most likely to respond to IFN therapy for HCV. To characterize the response of HCV-infected patients to treatment with IFNα, the expression of an IFN-response gene signature comprised of IFN-stimulated genes and genes that play an important role in the innate immune response was examined in liver biopsies from HCV-infected patients enrolled in a clinical trial. In the present study we found that the expression of a subset of IFN-response genes was dysregulated in liver biopsy samples from nonresponsive hepatitis C patients as compared with virologic responders. Based on these findings, a statistical model was developed to help predict the response of patients to IFN therapy, and compared to results obtained to the IL28 mutation model, which is highly predictive of the response to IFN-based therapy in HCV-infected patients. We found that a model incorporating gene expression data can improve predictions of IFN responsiveness compared to IL28 mutation status alone.

Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications

Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

Interferon-inducible guanylate binding protein (GBP2) is associated with better prognosis in breast cancer and indicates an efficient T cell response

BACKGROUND

Recently, interferon-inducible guanylate binding protein (GBP2) has been discussed as a possible control factor in tumor development, which is controlled by p53, and inhibits NF-Kappa B and Rac protein as well as expression of matrix metalloproteinase 9. However, the potential role that GBP2 plays in tumor development and prognosis has not yet been studied.

METHODS

We analyzed whether GBP2 mRNA levels are associated with metastasis-free interval in 766 patients with node negative breast carcinomas who did not receive systemic chemotherapy. Furthermore, response to anthracycline-based chemotherapy was studied in 768 breast cancer patients.

RESULTS

High expression of GBP2 in breast carcinomas was associated with better prognosis in the univariate (P < 0.001, hazard ratio 0.763, 95 % CI 0.650-0.896) as well as in the multivariate Cox analysis (P = 0.008, hazard ratio 0.731, 95 % CI 0.580-0.920) adjusted to the established clinical factors age, pT stage, grading, hormone and ERBB2 receptor status. The association was particularly strong in subgroups with high proliferation and positive estrogen receptor status but did not reach significance in carcinomas with low expression of proliferation associated genes. Besides its prognostic capacity, GBP2 also predicted pathologically complete response to anthracycline-based chemotherapy (P = 0.0037, odds ratio 1.39, 95 % CI 1.11-1.74). Interestingly, GBP2 correlated with a recently established T cell signature, indicating tumor infiltration with T cells (R = 0.607, P < 0.001).

CONCLUSION

GBP2 is associated with better prognosis in fast proliferating tumors and probably represents a marker of an efficient T cell response.

A key role for NF-κB transcription factor c-Rel in T-lymphocyte-differentiation and effector functions

The transcription factors of the Rel/NF-κB family function as key regulators of innate and adoptive immunity. Tightly and temporally controlled activation of NF-κB-signalling pathways ensures prevention of harmful immune cell dysregulation, whereas a loss of control leads to pathological conditions such as severe inflammation, autoimmune disease, and inflammation-associated oncogenesis. Five family members have been identified in mammals: RelA (p65), c-Rel, RelB, and the precursor proteins NF-κB1 (p105) and NF-κB2 (p100), that are processed into p50 and p52, respectively. While RelA-containing dimers are present in most cell types, c-Rel complexes are predominately found in cells of hematopoietic origin. In T-cell lymphocytes, certain genes essential for immune function such as Il2 and Foxp3 are directly regulated by c-Rel. Additionally, c-Rel-dependent IL-12 and IL-23 transcription by macrophages and dendritic cells is crucial for T-cell differentiation and effector functions. Accordingly, c-Rel expression in T cells and antigen-presenting cells (APCs) controls a delicate balance between tolerance and immunity. This review gives a selective overview on recent progress in understanding of diverse roles of c-Rel in regulating adaptive immunity.

Latent Semantic Indexing of PubMed abstracts for identification of transcription factor candidates from microarray derived gene sets

Background

Identification of transcription factors (TFs) responsible for modulation of differentially expressed genes is a key step in deducing gene regulatory pathways. Most current methods identify TFs by searching for presence of DNA binding motifs in the promoter regions of co-regulated genes. However, this strategy may not always be useful as presence of a motif does not necessarily imply a regulatory role. Conversely, motif presence may not be required for a TF to regulate a set of genes. Therefore, it is imperative to include functional (biochemical and molecular) associations, such as those found in the biomedical literature, into algorithms for identification of putative regulatory TFs that might be explicitly or implicitly linked to the genes under investigation.

Results

In this study, we present a Latent Semantic Indexing (LSI) based text mining approach for identification and ranking of putative regulatory TFs from microarray derived differentially expressed genes (DEGs). Two LSI models were built using different term weighting schemes to devise pair-wise similarities between 21,027 mouse genes annotated in the Entrez Gene repository. Amongst these genes, 433 were designated TFs in the TRANSFAC database. The LSI derived TF-to-gene similarities were used to calculate TF literature enrichment p-values and rank the TFs for a given set of genes. We evaluated our approach using five different publicly available microarray datasets focusing on TFs Rel, Stat6, Ddit3, Stat5 and Nfic. In addition, for each of the datasets, we constructed gold standard TFs known to be functionally relevant to the study in question. Receiver Operating Characteristics (ROC) curves showed that the log-entropy LSI model outperformed the tf-normal LSI model and a benchmark co-occurrence based method for four out of five datasets, as well as motif searching approaches, in identifying putative TFs.

Conclusions

Our results suggest that our LSI based text mining approach can complement existing approaches used in systems biology research to decipher gene regulatory networks by providing putative lists of ranked TFs that might be explicitly or implicitly associated with sets of DEGs derived from microarray experiments. In addition, unlike motif searching approaches, LSI based approaches can reveal TFs that may indirectly regulate genes.

The differential disease regulome

Background

Transcription factors in disease-relevant pathways represent potential drug targets, by impacting a distinct set of pathways that may be modulated through gene regulation. The influence of transcription factors is typically studied on a per disease basis, and no current resources provide a global overview of the relations between transcription factors and disease. Furthermore, existing pipelines for related large-scale analysis are tailored for particular sources of input data, and there is a need for generic methodology for integrating complementary sources of genomic information.

Results

We here present a large-scale analysis of multiple diseases versus multiple transcription factors, with a global map of over-and under-representation of 446 transcription factors in 1010 diseases. This map, referred to as the differential disease regulome, provides a first global statistical overview of the complex interrelationships between diseases, genes and controlling elements. The map is visualized using the Google map engine, due to its very large size, and provides a range of detailed information in a dynamic presentation format.

The analysis is achieved through a novel methodology that performs a pairwise, genome-wide comparison on the cartesian product of two distinct sets of annotation tracks, e.g. all combinations of one disease and one TF.

The methodology was also used to extend with maps using alternative data sets related to transcription and disease, as well as data sets related to Gene Ontology classification and histone modifications. We provide a web-based interface that allows users to generate other custom maps, which could be based on precisely specified subsets of transcription factors and diseases, or, in general, on any categorical genome annotation tracks as they are improved or become available.

Conclusion

We have created a first resource that provides a global overview of the complex relations between transcription factors and disease. As the accuracy of the disease regulome depends mainly on the quality of the input data, forthcoming ChIP-seq based binding data for many TFs will provide improved maps. We further believe our approach to genome analysis could allow an advance from the current typical situation of one-time integrative efforts to reproducible and upgradable integrative analysis. The differential disease regulome and its associated methodology is available at http://hyperbrowser.uio.no.

Functional cohesion of gene sets determined by latent semantic indexing of PubMed abstracts

High-throughput genomic technologies enable researchers to identify genes that are co-regulated with respect to specific experimental conditions. Numerous statistical approaches have been developed to identify differentially expressed genes. Because each approach can produce distinct gene sets, it is difficult for biologists to determine which statistical approach yields biologically relevant gene sets and is appropriate for their study. To address this issue, we implemented Latent Semantic Indexing (LSI) to determine the functional coherence of gene sets. An LSI model was built using over 1 million Medline abstracts for over 20,000 mouse and human genes annotated in Entrez Gene. The gene-to-gene LSI-derived similarities were used to calculate a literature cohesion p-value (LPv) for a given gene set using a Fisher's exact test. We tested this method against genes in more than 6,000 functional pathways annotated in Gene Ontology (GO) and found that approximately 75% of gene sets in GO biological process category and 90% of the gene sets in GO molecular function and cellular component categories were functionally cohesive (LPv<0.05). These results indicate that the LPv methodology is both robust and accurate. Application of this method to previously published microarray datasets demonstrated that LPv can be helpful in selecting the appropriate feature extraction methods. To enable real-time calculation of LPv for mouse or human gene sets, we developed a web tool called Gene-set Cohesion Analysis Tool (GCAT). GCAT can complement other gene set enrichment approaches by determining the overall functional cohesion of data sets, taking into account both explicit and implicit gene interactions reported in the biomedical literature.

Human cytomegalovirus IE1 protein elicits a type II interferon-like host cell response that depends on activated STAT1 but not interferon-γ

Human cytomegalovirus (hCMV) is a highly prevalent pathogen that, upon primary infection, establishes life-long persistence in all infected individuals. Acute hCMV infections cause a variety of diseases in humans with developmental or acquired immune deficits. In addition, persistent hCMV infection may contribute to various chronic disease conditions even in immunologically normal people. The pathogenesis of hCMV disease has been frequently linked to inflammatory host immune responses triggered by virus-infected cells. Moreover, hCMV infection activates numerous host genes many of which encode pro-inflammatory proteins. However, little is known about the relative contributions of individual viral gene products to these changes in cellular transcription. We systematically analyzed the effects of the hCMV 72-kDa immediate-early 1 (IE1) protein, a major transcriptional activator and antagonist of type I interferon (IFN) signaling, on the human transcriptome. Following expression under conditions closely mimicking the situation during productive infection, IE1 elicits a global type II IFN-like host cell response. This response is dominated by the selective up-regulation of immune stimulatory genes normally controlled by IFN-γ and includes the synthesis and secretion of pro-inflammatory chemokines. IE1-mediated induction of IFN-stimulated genes strictly depends on tyrosine-phosphorylated signal transducer and activator of transcription 1 (STAT1) and correlates with the nuclear accumulation and sequence-specific binding of STAT1 to IFN-γ-responsive promoters. However, neither synthesis nor secretion of IFN-γ or other IFNs seems to be required for the IE1-dependent effects on cellular gene expression. Our results demonstrate that a single hCMV protein can trigger a pro-inflammatory host transcriptional response via an unexpected STAT1-dependent but IFN-independent mechanism and identify IE1 as a candidate determinant of hCMV pathogenicity.

Murine coronavirus delays expression of a subset of interferon-stimulated genes

The importance of the type I interferon (IFN-I) system in limiting coronavirus replication and dissemination has been unequivocally demonstrated by rapid lethality following infection of mice lacking the alpha/beta IFN (IFN-alpha/beta) receptor with mouse hepatitis virus (MHV), a murine coronavirus. Interestingly, MHV has a cell-type-dependent ability to resist the antiviral effects of IFN-alpha/beta. In primary bone-marrow-derived macrophages and mouse embryonic fibroblasts, MHV replication was significantly reduced by the IFN-alpha/beta-induced antiviral state, whereas IFN treatment of cell lines (L2 and 293T) has only minor effects on replication (K. M. Rose and S. R. Weiss, Viruses 1:689-712, 2009). Replication of other RNA viruses, including Theiler's murine encephalitis virus (TMEV), vesicular stomatitis virus (VSV), Sindbis virus, Newcastle disease virus (NDV), and Sendai virus (SeV), was significantly inhibited in L2 cells treated with IFN-alpha/beta, and MHV had the ability to rescue only SeV replication. We present evidence that MHV infection can delay interferon-stimulated gene (ISG) induction mediated by both SeV and IFN-beta but only when MHV infection precedes SeV or IFN-beta exposure. Curiously, we observed no block in the well-defined IFN-beta signaling pathway that leads to STAT1-STAT2 phosphorylation and translocation to the nucleus in cultures infected with MHV. This observation suggests that MHV must inhibit an alternative IFN-induced pathway that is essential for early induction of ISGs. The ability of MHV to delay SeV-mediated ISG production may partially involve limiting the ability of IFN regulatory factor 3 (IRF-3) to function as a transcription factor. Transcription from an IRF-3-responsive promoter was partially inhibited by MHV; however, IRF-3 was transported to the nucleus and bound DNA in MHV-infected cells superinfected with SeV.

Systemic lipopolysaccharide protects the brain from ischemic injury by reprogramming the response of the brain to stroke: a critical role for IRF3

Lipopolysaccharide (LPS) preconditioning provides neuroprotection against subsequent cerebral ischemic injury through activation of its receptor, Toll-like receptor 4 (TLR4). Paradoxically, TLR activation by endogenous ligands after ischemia worsens stroke damage. Here, we define a novel, protective role for TLRs after ischemia in the context of LPS preconditioning. Microarray analysis of brains collected 24 h after stroke revealed a unique set of upregulated genes in LPS-pretreated animals. Promoter analysis of the unique gene set identified an overrepresentation of type I interferon (IFN)-associated transcriptional regulatory elements. This finding suggested the presence of type I IFNs or interferon regulatory factors (IRFs), which upregulate interferon-stimulated genes. Upregulation of IFNbeta was confirmed by real-time reverse transcription-PCR. Direct administration of IFNbeta intracerebroventricularly at the time of stroke was sufficient for neuroprotection. TLR4 can induce both IFNbeta and interferon-stimulated genes through its adapter molecule Toll/interleukin receptor domain-containing adaptor-inducing IFNbeta (TRIF) and the IRF3 transcription factor. We show in oxygen glucose deprivation of cortical neurons, an in vitro model of stroke, that activation of TRIF after stroke reduces neuronal death. Furthermore, mice lacking IRF3 were not protected by LPS preconditioning in our in vivo model. Our studies constitute the first demonstration of the neuroprotective capacity of TRIF/IRF3 signaling and suggest that interferon-stimulated genes, whether induced by IFNbeta or by enhanced TLR signaling to IRF3, are a potent means of protecting the brain against ischemic damage.