Gene expression signature-based screening identifies new broadly effective influenza a antivirals

Human norovirus cultivation systems and their use in antiviral research

Human norovirus (HuNoV) is a major cause of acute gastroenteritis and foodborne diseases, affecting all age groups. Despite its clinical needs, no approved antiviral therapies are available. Since the discovery of HuNoV in 1972, studies on anti-norovirals, mechanism of HuNoV infection, viral inactivation, etc., have been hampered by the lack of a robust laboratory-based cultivation system for HuNoV. A recent breakthrough in the development of HuNoV cultivation systems has opened opportunities for researchers to investigate HuNoV biology in the context of de novo HuNoV infections. A tissue stem cell-derived human intestinal organoid/enteroid (HIO) culture system is one of those that supports HuNoV replication reproducibly and, to our knowledge, is most widely distributed to laboratories worldwide to study HuNoV and develop therapeutic strategies. This review summarizes recently developed HuNoV cultivation systems, including HIO, and their use in antiviral studies.

Proteome-Based Investigation Identified Potential Drug Repurposable Small Molecules Against Monkeypox Disease

Monkeypox Virus (MPXV), the causative agent of Monkeypox (MPX) disease, is an emerging zoonotic pathogen spreading in different endemic and non-endemic nations and creating outbreaks. MPX treatment mainly includes Cidofovir and Tecovirimat but they have several side effects and solely depending on these drugs may promote the emergence of drug-resistant variants. Hence, new drugs are required to control the spread of the disease. In this study, we explored the MPXV proteome to suggest repurposable drugs. DrugBank screening revealed drugs such as Brinzolamide, Dorzolamide, Methazolamide, Zidovudine, Gemcitabine, Hydroxyurea, Fludarabine, and Tecovirimat as controls. Structural analogs of these compounds were extracted from ChEMBL Database. After Molecular docking and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET)-based screening, we identified Zidovudine (binding affinity-5.9 kcal/mol) and a Harmala alkaloid (2S,4R)-4-(9H-Pyrido[3,4-b]indol-1-yl)-1,2,4-butanetriol (binding affinity - 6.6 kcal/mol) against L2R receptor (Thymidine Kinase). Moreover, Fludarabine (binding affinity - 6.4 kcal/mol) and 5'-Dehydroadenosine (binding affinity - 6.4 kcal/mol) can strongly interact with the I4L receptor (Ribonucleotide reductase large subunit R1). Molecular Dynamics (MD) simulations suggest all of these compounds can change the C-alpha backbone, residue mobility, compactness, and solvent accessible surface area of L2R and I4L. Our results strongly suggest that these drug repurposing small molecules are worth exploring in vivo and in vitro for clinical applications.

Standardization of an antiviral pipeline for human norovirus in human intestinal enteroids demonstrates nitazoxanide has no to weak antiviral activity

Human noroviruses (HuNoVs) are the leading cause of acute gastroenteritis. In immunocompetent hosts, symptoms usually resolve within 3 days; however, in immunocompromised persons, HuNoV infection can become persistent, debilitating, and sometimes life-threatening. There are no licensed therapeutics for HuNoV due to a near half-century delay in its cultivation. Treatment for chronic HuNoV infection in immunosuppressed patients anecdotally includes nitazoxanide, a broad-spectrum antimicrobial licensed for treatment of parasite-induced gastroenteritis. Despite its off-label use for chronic HuNoV infection, nitazoxanide has not been clearly demonstrated to be an effective treatment. In this study, we standardized a pipeline for antiviral testing using multiple human small intestinal enteroid lines representing different intestinal segments and evaluated whether nitazoxanide inhibits replication of five HuNoV strains in vitro. Nitazoxanide did not exhibit high selective antiviral activity against any HuNoV strain tested, indicating it is not an effective antiviral for HuNoV infection. Human intestinal enteroids are further demonstrated as a model to serve as a preclinical platform to test antivirals against HuNoVs to treat gastrointestinal disease. Abstr.

Bioinformatics and System Biology Approach to Reveal the Interaction Network and the Therapeutic Implications for Non-Small Cell Lung Cancer Patients With COVID-19

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the leading cause of coronavirus disease-2019 (COVID-19), is an emerging global health crisis. Lung cancer patients are at a higher risk of COVID-19 infection. With the increasing number of non-small-cell lung cancer (NSCLC) patients with COVID-19, there is an urgent need of efficacious drugs for the treatment of COVID-19/NSCLC.

Methods: Based on a comprehensive bioinformatic and systemic biological analysis, this study investigated COVID-19/NSCLC interactional hub genes, detected common pathways and molecular biomarkers, and predicted potential agents for COVID-19 and NSCLC.

Results: A total of 122 COVID-19/NSCLC interactional genes and 21 interactional hub genes were identified. The enrichment analysis indicated that COVID-19 and NSCLC shared common signaling pathways, including cell cycle, viral carcinogenesis, and p53 signaling pathway. In total, 10 important transcription factors (TFs) and 44 microRNAs (miRNAs) participated in regulations of 21 interactional hub genes. In addition, 23 potential candidates were predicted for the treatment of COVID-19 and NSCLC.

Conclusion: This study increased our understanding of pathophysiology and screened potential drugs for COVID-19 and NSCLC.

Preclinical and clinical developments for combination treatment of influenza

Antiviral drugs are an important measure of control for influenza in the population, particularly for those that are severely ill or hospitalised. The neuraminidase inhibitor (NAI) class of drugs, including oseltamivir, have been the standard of care (SOC) for severe influenza illness for many years. The approval of drugs with novel mechanisms of action, such as baloxavir marboxil, is important and broadens potential treatment options for combination therapy. The use of antiviral treatments in combination for influenza is of interest; one potential benefit of this treatment strategy is that the combination of drugs with different mechanisms of action may lower the selection of resistance due to treatment. In addition, combination therapy may become an important treatment option to improve patient outcomes in those with severe illness due to influenza or those that are immunocompromised. Clinical trials increasingly evaluate drug combinations in a range of patient cohorts. Here, we summarise preclinical and clinical advances in combination therapy for the treatment of influenza with reference to immunocompromised animal models and clinical data in hospitalised patient cohorts where available. There is a wide array of drug categories in development that have also been tested in combination. Therefore, in this review, we have included polymerase inhibitors, monoclonal antibodies (mAbs), host-targeted therapies, and adjunctive therapies. Combination treatment regimens should be carefully evaluated to determine whether they provide an added benefit relative to effectiveness of monotherapy and in a variety of patient cohorts, particularly, if there is a greater chance of an adverse outcome. Safe and effective treatment of influenza is important not only for seasonal influenza infection, but also if a pandemic strain was to emerge.

Identification of potentially anti-COVID-19 active drugs using the connectivity MAP

Drug repurposing can be an interesting strategy for an emergency response to the severe acute respiratory syndrome-coronavirus-2, (SARS-COV-2), the causing agent of the coronavirus disease-19 (COVID-19) pandemic. For this, we applied the Connectivity Map (CMap) bioinformatic resource to identify drugs that generate, in the CMap database, gene expression profiles (GEP) that negatively correlate with a SARS-COV-2 GEP, anticipating that these drugs could antagonize the deleterious effects of the virus at cell, tissue or organism levels. We identified several anti-cancer compounds that target MDM2 in the p53 pathway or signaling proteins: Ras, PKBβ, Nitric Oxide synthase, Rho kinase, all involved in the transmission of proliferative and growth signals. We hypothesized that these drugs could interfere with the high rate of biomass synthesis in infected cells, a feature shared with cancer cells. Other compounds including etomoxir, triacsin-c, PTB1-IN-3, are known to modulate lipid metabolism or to favor catabolic reactions by activating AMPK. Four different anti-inflammatory molecules, including dexamethasone, fluorometholone and cytosporone-b, targeting the glucocorticoid receptor, cyclooxygenase, or NUR77 also came out of the analysis. These results represent a first step in the characterization of potential repositioning strategies to treat SARS-COV-2.

Paradoxical Pro-angiogenic Effect of Low-Dose Ellipticine Identified by In Silico Drug Repurposing

Inadequate vessel maintenance or growth causes ischemia in diseases such as myocardial infarction, stroke, and neurodegenerative disorders. Therefore, developing an effective strategy to salvage ischemic tissues using a novel compound is urgent. Drug repurposing has become a widely used method that can make drug discovery more efficient and less expensive. Additionally, computational virtual screening tools make drug discovery faster and more accurate. This study found a novel drug candidate for pro-angiogenesis by in silico virtual screening. Using Gene Expression Omnibus (GEO) microarray datasets related to angiogenesis studies, differentially expressed genes were identified and characteristic direction signatures extracted from GEO2EnrichR were used as input data on L1000CDS² to screen pro-angiogenic molecules. After a thorough review of the candidates, a list of compounds structurally similar to TWS-119 was generated using ChemMine Tools and its clustering toolbox. ChemMine Tools and ChemminR structural similarity search tools for small-molecule analysis and clustering were used for second screening. A molecular docking simulation was conducted using AutoDock v.4 to evaluate the physicochemical effect of secondary-screened chemicals. A cell viability or toxicity test was performed to determine the proper dose of the final candidate, ellipticine. As a result, we found ellipticine, which has pro-angiogenic effects, using virtual computational methods. The noncytotoxic concentration of ellipticine was 156.25 nM. The phosphorylation of glycogen synthase kinase-3β was decreased, whereas the β-catenin expression was increased in human endothelial cells treated with ellipticine. We concluded that ellipticine at sublethal dosage could be successfully repositioned as a pro-angiogenic substance by in silico virtual screening.

A systems-level study reveals host-targeted repurposable drugs against SARS-CoV-2 infection

Understanding the mechanism of SARS-CoV-2 infection and identifying potential therapeutics are global imperatives. Using a quantitative systems pharmacology approach, we identified a set of repurposable and investigational drugs as potential therapeutics against COVID-19. These were deduced from the gene expression signature of SARS-CoV-2-infected A549 cells screened against Connectivity Map and prioritized by network proximity analysis with respect to disease modules in the viral-host interactome. We also identified immuno-modulating compounds aiming at suppressing hyperinflammatory responses in severe COVID-19 patients, based on the transcriptome of ACE2-overexpressing A549 cells. Experiments with Vero-E6 cells infected by SARS-CoV-2, as well as independent syncytia formation assays for probing ACE2/SARS-CoV-2 spike protein-mediated cell fusion using HEK293T and Calu-3 cells, showed that several predicted compounds had inhibitory activities. Among them, salmeterol, rottlerin, and mTOR inhibitors exhibited antiviral activities in Vero-E6 cells; imipramine, linsitinib, hexylresorcinol, ezetimibe, and brompheniramine impaired viral entry. These novel findings provide new paths for broadening the repertoire of compounds pursued as therapeutics against COVID-19.

The Crossroads between Host Copper Metabolism and Influenza Infection

Three main approaches are used to combat severe viral respiratory infections. The first is preemptive vaccination that blocks infection. Weakened or dead viral particles, as well as genetic constructs carrying viral proteins or information about them, are used as an antigen. However, the viral genome is very evolutionary labile and changes continuously. Second, chemical agents are used during infection and inhibit the function of a number of viral proteins. However, these drugs lose their effectiveness because the virus can rapidly acquire resistance to them. The third is the search for points in the host metabolism the effect on which would suppress the replication of the virus but would not have a significant effect on the metabolism of the host. Here, we consider the possibility of using the copper metabolic system as a target to reduce the severity of influenza infection. This is facilitated by the fact that, in mammals, copper status can be rapidly reduced by silver nanoparticles and restored after their cancellation.

A Panel of Broad-Spectrum Antivirals in Topical Ophthalmic Medications from the Drug Repurposing Approach during and after the Coronavirus Disease 2019 Era

The coronavirus disease 2019 (COVID-19) represents a global concern of public health caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its clinical manifestations are characterized by a heterogeneous group of symptoms and pictures (ranging from asymptomatic to lethal courses). The prevalence of conjunctivitis in patients with COVID-19 is at present controversial. Although it has been reported that only 0.9% developed signs of conjunctivitis, other report indicates that up to 31.6% of hospitalized patients had conjunctivitis. Considering the widespread use of topical ophthalmic medications (e.g., eye drops) by the general population, for various reasons (e.g., artificial tears, anti-glaucoma medications, topical antibiotics, etc.), the existence of their side effects as antiviral action should be investigated in-depth because it could possibly explain the aforementioned controversial data and represent a potential antiviral treatment for SARS-CoV-2 replication/diffusion on the ocular surface. Here, we discuss and elucidate the antiviral side effect of many eye drops and ophthalmic ointments commonly used for others purposes, thus showing that these secondary effects (not to be confused with the 'adverse effects') might be of primary importance in a number of viral infections (e.g., those for which there is no validated treatment protocol), according to a drug repurposing approach. Some active ingredients or excipients described here have activity against other types of viruses, thus suggesting potential broad-spectrum applications.

Potentially repurposable drugs for COVID-19 identified from SARS-CoV-2 Host Protein Interactome

We previously presented the protein-protein interaction network - the 'HoP' or the host protein interactome - of 332 host proteins that were identified to interact with 27 nCoV19 viral proteins by Gordon et al. Here, we studied drugs targeting the proteins in this interactome to identify whether any of them may potentially be repurposable against SARS-CoV-2. We studied each of the drugs using the BaseSpace Correlation Engine and identified those that induce gene expression profiles negatively correlated with SARS-associated expression profile. This analysis resulted in 20 drugs whose differential gene expression (drug versus normal) had an anti-correlation with differential expression for SARS (viral infection versus normal). These included drugs that were already being tested for their clinical activity against SARS-CoV-2, those with proven activity against SARS-CoV/MERS-CoV, broad-spectrum antiviral drugs, and those identified/prioritized by other computational re-purposing studies. In summary, our integrated computational analysis of the HoP interactome in conjunction with drug-induced transcriptomic data resulted in drugs that may be repurposable for COVID-19.

Characterization of cellular transcriptomic signatures induced by different respiratory viruses in human reconstituted airway epithelia

Acute respiratory infections, a large part being of viral origin, constitute a major public health issue. To propose alternative and/or new therapeutic approaches, it is necessary to increase our knowledge about the interactions between respiratory viruses and their primary cellular targets using the most biologically relevant experimental models. In this study, we used RNAseq to characterize and compare the transcriptomic signature of infection induced by different major respiratory viruses (Influenza viruses, hRSV and hMPV) in a model of reconstituted human airway epithelia. Our results confirm the importance of several cellular pathways commonly or specifically induced by these respiratory viruses, such as the innate immune response or antiviral defense. A very interesting common feature revealed by the global virogenomic signature shared between hRSV, hMPV and influenza viruses is the global downregulation of cilium-related gene expression, in good agreement with experimental evaluation of mucociliary clearance. Beyond providing new information about respiratory virus/host interactions, our study also underlines the interest of using biologically relevant experimental models to study human respiratory viruses.

GSMA: an approach to identify robust global and test Gene Signatures using Meta-Analysis

MOTIVATION

Recent advances in biomedical research have made massive amount of transcriptomic data available in public repositories from different sources. Due to the heterogeneity present in the individual experiments, identifying reproducible biomarkers for a given disease from multiple independent studies has become a major challenge. The widely used meta-analysis approaches, such as Fisher's method, Stouffer's method, minP and maxP, have at least two major limitations: (i) they are sensitive to outliers, and (ii) they perform only one statistical test for each individual study, and hence do not fully utilize the potential sample size to gain statistical power.

RESULTS

Here, we propose a gene-level meta-analysis framework that overcomes these limitations and identifies a gene signature that is reliable and reproducible across multiple independent studies of a given disease. The approach provides a comprehensive global signature that can be used to understand the underlying biological phenomena, and a smaller test signature that can be used to classify future samples of a given disease. We demonstrate the utility of the framework by constructing disease signatures for influenza and Alzheimer's disease using nine datasets including 1108 individuals. These signatures are then validated on 12 independent datasets including 912 individuals. The results indicate that the proposed approach performs better than the majority of the existing meta-analysis approaches in terms of both sensitivity as well as specificity. The proposed signatures could be further used in diagnosis, prognosis and identification of therapeutic targets.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Connectivity Mapping: Methods and Applications

Connectivity mapping resources consist of signatures representing changes in cellular state following systematic small-molecule, disease, gene, or other form of perturbations. Such resources enable the characterization of signatures from novel perturbations based on similarity; provide a global view of the space of many themed perturbations; and allow the ability to predict cellular, tissue, and organismal phenotypes for perturbagens. A signature search engine enables hypothesis generation by finding connections between query signatures and the database of signatures. This framework has been used to identify connections between small molecules and their targets, to discover cell-specific responses to perturbations and ways to reverse disease expression states with small molecules, and to predict small-molecule mimickers for existing drugs. This review provides a historical perspective and the current state of connectivity mapping resources with a focus on both methodology and community implementations.

Systems pharmacology-based integration of human and mouse data for drug repurposing to treat thoracic aneurysms

Marfan syndrome (MFS) is associated with mutations in fibrillin-1 that predispose afflicted individuals to progressive thoracic aortic aneurysm (TAA) leading to dissection and rupture of the vessel wall. Here we combined computational and experimental approaches to identify and test FDA-approved drugs that may slow or even halt aneurysm progression. Computational analyses of transcriptomic data derived from the aortas of MFS patients and MFS mice (Fbn1mgR/mgR mice) predicted that subcellular pathways associated with reduced muscle contractility are key TAA determinants that could be targeted with the GABAB receptor agonist baclofen. Systemic administration of baclofen to Fbn1mgR/mgR mice validated our computational prediction by mitigating arterial disease progression at the cellular and physiological levels. Interestingly, baclofen improved muscle contraction-related subcellular pathways by upregulating a different set of genes than those downregulated in the aorta of vehicle-treated Fbn1mgR/mgR mice. Distinct transcriptomic profiles were also associated with drug-treated MFS and wild-type mice. Thus, systems pharmacology approaches that compare patient- and mouse-derived transcriptomic data for subcellular pathway-based drug repurposing represent an effective strategy to identify potential new treatments of human diseases.

Drug Repurposing Approaches for the Treatment of Influenza Viral Infection: Reviving Old Drugs to Fight Against a Long-Lived Enemy

Influenza viruses still constitute a real public health problem today. To cope with the emergence of new circulating strains, but also the emergence of resistant strains to classic antivirals, it is necessary to develop new antiviral approaches. This review summarizes the state-of-the-art of current antiviral options against influenza infection, with a particular focus on the recent advances of anti-influenza drug repurposing strategies and their potential therapeutic, regulatory and economic benefits. The review will illustrate the multiple ways to reposition molecules for the treatment of influenza, from adventitious discovery to in silico-based screening. These novel antiviral molecules, many of which targeting the host cell, in combination with conventional antiviral agents targeting the virus, will ideally enter the clinics and reinforce the therapeutic arsenal to combat influenza virus infections.

Drug repurposing for antimicrobial discovery

Antimicrobial resistance continues to be a public threat on a global scale. The ongoing need to develop new antimicrobial drugs that are effective against multi-drug-resistant pathogens has spurred the research community to invest in various drug discovery strategies, one of which is drug repurposing-the process of finding new uses for existing drugs. While still nascent in the antimicrobial field, the approach is gaining traction in both the public and private sector. While the approach has particular promise in fast-tracking compounds into clinical studies, it nevertheless has substantial obstacles to success. This Review covers the art of repurposing existing drugs for antimicrobial purposes. We discuss enabling screening platforms for antimicrobial discovery and present encouraging findings of novel antimicrobial therapeutic strategies. Also covered are general advantages of repurposing over de novo drug development and challenges of the strategy, including scientific, intellectual property and regulatory issues.

Repurposing of Drugs as Novel Influenza Inhibitors From Clinical Gene Expression Infection Signatures

Influenza virus infections remain a major and recurrent public health burden. The intrinsic ever-evolving nature of this virus, the suboptimal efficacy of current influenza inactivated vaccines, as well as the emergence of resistance against a limited antiviral arsenal, highlight the critical need for novel therapeutic approaches. In this context, the aim of this study was to develop and validate an innovative strategy for drug repurposing as host-targeted inhibitors of influenza viruses and the rapid evaluation of the most promising candidates in Phase II clinical trials. We exploited in vivo global transcriptomic signatures of infection directly obtained from a patient cohort to determine a shortlist of already marketed drugs with newly identified, host-targeted inhibitory properties against influenza virus. The antiviral potential of selected repurposing candidates was further evaluated in vitro, in vivo, and ex vivo. Our strategy allowed the selection of a shortlist of 35 high potential candidates out of a rationalized computational screening of 1,309 FDA-approved bioactive molecules, 31 of which were validated for their significant in vitro antiviral activity. Our in vivo and ex vivo results highlight diltiazem, a calcium channel blocker currently used in the treatment of hypertension, as a promising option for the treatment of influenza infections. Additionally, transcriptomic signature analysis further revealed the so far undescribed capacity of diltiazem to modulate the expression of specific genes related to the host antiviral response and cholesterol metabolism. Finally, combination treatment with diltiazem and virus-targeted oseltamivir neuraminidase inhibitor further increased antiviral efficacy, prompting rapid authorization for the initiation of a Phase II clinical trial. This original, host-targeted, drug repurposing strategy constitutes an effective and highly reactive process for the rapid identification of novel anti-infectious drugs, with potential major implications for the management of antimicrobial resistance and the rapid response to future epidemic or pandemic (re)emerging diseases for which we are still disarmed.

LINCS L1000 dataset-based repositioning of CGP-60474 as a highly potent anti-endotoxemic agent

Sepsis is one of the most common clinical syndromes that causes death and disability. Although many studies have developed drugs for sepsis treatment, none have decreased the mortality rate. The aim of this study was to identify a novel treatment option for sepsis using the library of integrated network-based cellular signatures (LINCS) L1000 perturbation dataset based on an in vitro and in vivo sepsis model. Sepsis-related microarray studies of early-stage inflammatory processes in patients and innate immune cells were collected from the Gene Expression Omnibus (GEO) data repository and used for candidate drug selection based on the LINCS L1000 perturbation dataset. The anti-inflammatory effects of the selected candidate drugs were analyzed using activated macrophage cell lines. CGP-60474, an inhibitor of cyclin-dependent kinase, was the most potent drug. It alleviated tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in activated macrophages by downregulating the NF-κB activity, and it reduced the mortality rate in LPS induced endotoxemia mice. This study shows that CGP-60474 could be a potential therapeutic candidate to attenuate the endotoxemic process. Additionally, the virtual screening strategy using the LINCS L1000 perturbation dataset could be a cost and time effective tool in the early stages of drug development.

A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria

Background

Nearly half of the world’s population (3.2 billion people) were at risk of malaria in 2015, and resistance to current therapies is a major concern. While the standard of care includes drug combinations, there is a pressing need to identify new combinations that can bypass current resistance mechanisms. In the work presented here, a combined transcriptional drug repositioning/discovery and machine learning approach is proposed.

Methods

The integrated approach utilizes gene expression data from patient-derived samples, in combination with large-scale anti-malarial combination screening data, to predict synergistic compound combinations for three Plasmodium falciparum strains (3D7, DD2 and HB3). Both single compounds and combinations predicted to be active were prospectively tested in experiment.

Results

One of the predicted single agents, apicidin, was active with the AC50 values of 74.9, 84.1 and 74.9 nM in 3D7, DD2 and HB3 P. falciparum strains while its maximal safe plasma concentration in human is 547.6 ± 136.6 nM. Apicidin at the safe dose of 500 nM kills on average 97% of the parasite. The synergy prediction algorithm exhibited overall precision and recall of 83.5 and 65.1% for mild-to-strong, 48.8 and 75.5% for moderate-to-strong and 12.0 and 62.7% for strong synergies. Some of the prospectively predicted combinations, such as tacrolimus-hydroxyzine and raloxifene-thioridazine, exhibited significant synergy across the three P. falciparum strains included in the study.

Conclusions

Systematic approaches can play an important role in accelerating discovering novel combinational therapies for malaria as it enables selecting novel synergistic compound pairs in a more informed and cost-effective manner.

Electronic supplementary material

The online version of this article (10.1186/s12936-018-2294-5) contains supplementary material, which is available to authorized users.

Meta- and cross-species analyses of insulin resistance based on gene expression datasets in human white adipose tissues

Ample evidence indicates that insulin resistance (IR) is closely related to white adipose tissue (WAT), but the underlying mechanisms of IR pathogenesis are still unclear. Using 352 microarray datasets from seven independent studies, we identified a meta-signature which comprised of 1,413 genes. Our meta-signature was also enriched in overall WAT in in vitro and in vivo IR models. Only 12 core enrichment genes were consistently enriched across all IR models. Among the meta-signature, we identified a drug signature made up of 211 genes with expression levels that were co-regulated by thiazolidinediones and metformin using cross-species analysis. To confirm the clinical relevance of our drug signature, we found that the expression levels of 195 genes in the drug signature were significantly correlated with both homeostasis model assessment 2-IR score and body mass index. Finally, 18 genes from the drug signature were identified by protein-protein interaction network cluster. Four core enrichment genes were included in 18 genes and the expression levels of selected 8 genes were validated by quantitative PCR. These findings suggest that our signatures provide a robust set of genetic markers which can be used to provide a starting point for developing potential therapeutic targets in improving IR in WAT.

Iminosugars: Promising therapeutics for influenza infection

Influenza virus causes three to five million severe respiratory infections per year in seasonal epidemics, and sporadic pandemics, three of which occurred in the twentieth century and are a continuing global threat. Currently licensed antivirals exclusively target the viral neuraminidase or M2 ion channel, and emerging drug resistance necessitates the development of novel therapeutics. It is believed that a host-targeted strategy may combat the development of antiviral drug resistance. To this end, a class of molecules known as iminosugars, hydroxylated carbohydrate mimics with the endocyclic oxygen atom replaced by a nitrogen atom, are being investigated for their broad-spectrum antiviral potential. The influenza virus glycoproteins, hemagglutinin and neuraminidase, are susceptible to inhibition of endoplasmic reticulum α-glucosidases by certain iminosugars, leading to reduced virion production or infectivity, demonstrated by in vitro and in vivo studies. In some experiments, viral strain-specific effects are observed. Iminosugars may also inhibit other host and virus targets with antiviral consequences. While investigations of anti-influenza iminosugar activities have been conducted since the 1980s, recent successes of nojirimycin derivatives have re-invigorated investigation of the therapeutic potential of iminosugars as orally available, low cytotoxicity, effective anti-influenza drugs.

Benchmarking selected computational gene network growing tools in context of virus-host interactions

Several available online tools provide network growing functions where an algorithm utilizing different data sources suggests additional genes/proteins that should connect an input gene set into functionally meaningful networks. Using the well-studied system of influenza host interactions, we compare the network growing function of two free tools GeneMANIA and STRING and the commercial IPA for their performance of recovering known influenza A virus host factors previously identified from siRNA screens. The result showed that given small (~30 genes) or medium (~150 genes) input sets all three network growing tools detect significantly more known host factors than random human genes with STRING overall performing strongest. Extending the networks with all the three tools significantly improved the detection of GO biological processes of known host factors compared to not growing networks. Interestingly, the rate of identification of true host factors using computational network growing is equal or better to doing another experimental siRNA screening study which could also be true and applied to other biological pathways/processes.

Bioinformatics in translational drug discovery

Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse 'big data' that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications.

Systems-based approach to examine the cytokine responses in primary mouse lung macrophages infected with low pathogenic avian Influenza virus circulating in South East Asia

Background

Influenza A virus (IAV) is a major public health concern, being responsible for the death of approximately half a million people each year. Zoonotic transmissions of the virus from swine and avian origin have occurred in the past, and can potentially lead to the emgergence of new IAV stains in future pandemics. Pulmonary macrophages have been implicated in disease severity in the lower airway, and understanding the host response of macrophages infected with avian influenza viruses should provide new therapeutic strategies.

Results

We used a systems-based approach to investigate the transcriptome response of primary murine lung macrophages (PMФ) infected with the mouse-adapted H1N1/WSN virus and low pathogenic avian influenza (LPAI) viruses H5N2 and H5N3. The results showed that the LPAI viruses H5N2 and H5N3 can infect PMФ with similar efficiency to the H1N1/WSN virus. While all viruses induced antiviral responses, the H5N3 virus infection resulted in higher expression levels of cytokines and chemokines associated with inflammatory responses.

Conclusions

The LPAI H5N2 and H5N3 viruses are able to infect murine lung macrophages. However, the H5N3 virus was associated with increased expression of pro-inflammatory mediators. Although the H5N3 virus it is capable of inducing high levels of cytokines that are associated with inflammation, this property is distinct from its inability to efficiently replicate in a mammalian host.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3803-6) contains supplementary material, which is available to authorized users.

Comprendre le poumon agressé. Actes du séminaire de recherche translationnelle de la Société de Réanimation de Langue Française (6 décembre 2016)

Le séminaire de recherche translationnelle 2016 organisé par la Société de Réanimation de Langue Française s’est focalisé sur les mécanismes de réponse à l’agression et de réparation pulmonaire. Le poumon représente une interface essentielle entre l’hôte et son environnement et est à ce titre soumis à des agressions constantes et multiples. La réanimation s’est en grande partie construite autour de la prise en charge de la défaillance respiratoire. Au-delà du traitement étiologique et du support ventilatoire, se pose la problématique récurrente du développement de thérapeutiques adjuvantes à visée immunomodulatrice. Le développement de telles thérapeutiques innovantes est conditionné par les avancées dans la compréhension de la physiopathologie de l’agression pulmonaire aiguë, ainsi que par la validation au lit du patient d’outils d’évaluation permettant de quantifier l’effet des interventions thérapeutiques.

Avian influenza viruses that cause highly virulent infections in humans exhibit distinct replicative properties in contrast to human H1N1 viruses

Avian influenza viruses present an emerging epidemiological concern as some strains of H5N1 avian influenza can cause severe infections in humans with lethality rates of up to 60%. These have been in circulation since 1997 and recently a novel H7N9-subtyped virus has been causing epizootics in China with lethality rates around 20%. To better understand the replication kinetics of these viruses, we combined several extensive viral kinetics experiments with mathematical modelling of in vitro infections in human A549 cells. We extracted fundamental replication parameters revealing that, while both the H5N1 and H7N9 viruses replicate faster and to higher titers than two low-pathogenicity H1N1 strains, they accomplish this via different mechanisms. While the H7N9 virions exhibit a faster rate of infection, the H5N1 virions are produced at a higher rate. Of the two H1N1 strains studied, the 2009 pandemic H1N1 strain exhibits the longest eclipse phase, possibly indicative of a less effective neuraminidase activity, but causes infection more rapidly than the seasonal strain. This explains, in part, the pandemic strain’s generally slower growth kinetics and permissiveness to accept mutations causing neuraminidase inhibitor resistance without significant loss in fitness. Our results highlight differential growth properties of H1N1, H5N1 and H7N9 influenza viruses.

[Modulation of transcriptomic signature of the infected host: a new therapeutic strategy for the management of severe viral infections? Example of the flu]

Ces dernières décennies ont été marquées par l’émergence ou la réémergence de virus responsables d’épidémies ou de pandémies plus ou moins sévères. Les stratégies préventives sont prises à défaut, et l’arsenal antiviral curatif est limité d’autant plus que les résistances virales peuvent apparaître rapidement. Par ailleurs, le développement de nouvelles molécules nécessite un délai incompatible avec la réponse rapide nécessaire lors d’une épidémie d’envergure ou d’une pandémie. C’est la raison pour laquelle de nouvelles approches thérapeutiques sont nécessaires. Un concept novateur est le repositionnement de molécules déjà sur le marché en exploitant leur capacité à inverser la réponse transcriptomique cellulaire de l’hôte infecté. En identifiant des molécules qui visent l’hôte et non le virus, cette stratégie permet d’avoir un large spectre d’action et d’être potentiellement actif sur de nouveaux variants. La mise en place de cette stratégie nécessite de caractériser les réponses cellulaires spécifiques de l’infection virale d’intérêt, de cribler in silico des molécules candidates, de les tester sur modèles cellulaires et animaux, avant d’envisager des essais cliniques chez l’homme. Nous présenterons cette démarche en prenant pour exemple l’infection grippale.

Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia

High-throughput omics have proven invaluable in studying human disease, and yet day-to-day clinical practice still relies on physiological, non-omic markers. The metabolic syndrome, for example, is diagnosed and monitored by blood and urine indices such as blood cholesterol levels. Nevertheless, the association between the molecular and the physiological manifestations of the disease, especially in response to treatment, has not been investigated in a systematic manner. To this end, we studied a mouse model of diet-induced dyslipidemia and atherosclerosis that was subject to various drug treatments relevant to the disease in question. Both physiological data and gene expression data (from the liver and white adipose) were analyzed and compared. We find that treatments that restore gene expression patterns to their norm are associated with the successful restoration of physiological markers to their baselines. This holds in a tissue-specific manner—treatments that reverse the transcriptomic signatures of the disease in a particular tissue are associated with positive physiological effects in that tissue. Further, treatments that introduce large non-restorative gene expression alterations are associated with unfavorable physiological outcomes. These results provide a sound basis to in silico methods that rely on omic metrics for drug repurposing and drug discovery by searching for compounds that reverse a disease's omic signatures. Moreover, they highlight the need to develop drugs that restore the global cellular state to its healthy norm rather than rectify particular disease phenotypes.

Open drug discovery for the Zika virus

The Zika virus (ZIKV) outbreak in the Americas has caused global concern that we may be on the brink of a healthcare crisis. The lack of research on ZIKV in the over 60 years that we have known about it has left us with little in the way of starting points for drug discovery. Our response can build on previous efforts with virus outbreaks and lean heavily on work done on other flaviviruses such as dengue virus. We provide some suggestions of what might be possible and propose an open drug discovery effort that mobilizes global science efforts and provides leadership, which thus far has been lacking. We also provide a listing of potential resources and molecules that could be prioritized for testing as in vitro assays for ZIKV are developed. We propose also that in order to incentivize drug discovery, a neglected disease priority review voucher should be available to those who successfully develop an FDA approved treatment. Learning from the response to the ZIKV, the approaches to drug discovery used and the success and failures will be critical for future infectious disease outbreaks.

Identification of Influenza A/H7N9 virus infection-related human genes based on shortest paths in a virus-human protein interaction network

The recently emerging Influenza A/H7N9 virus is reported to be able to infect humans and cause mortality. However, viral and host factors associated with the infection are poorly understood. It is suggested by the "guilt by association" rule that interacting proteins share the same or similar functions and hence may be involved in the same pathway. In this study, we developed a computational method to identify Influenza A/H7N9 virus infection-related human genes based on this rule from the shortest paths in a virus-human protein interaction network. Finally, we screened out the most significant 20 human genes, which could be the potential infection related genes, providing guidelines for further experimental validation. Analysis of the 20 genes showed that they were enriched in protein binding, saccharide or polysaccharide metabolism related pathways and oxidative phosphorylation pathways. We also compared the results with those from human rhinovirus (HRV) and respiratory syncytial virus (RSV) by the same method. It was indicated that saccharide or polysaccharide metabolism related pathways might be especially associated with the H7N9 infection. These results could shed some light on the understanding of the virus infection mechanism, providing basis for future experimental biology studies and for the development of effective strategies for H7N9 clinical therapies.

Interferon-β and mycophenolic acid are potent inhibitors of Middle East respiratory syndrome coronavirus in cell-based assays

The Middle East respiratory syndrome coronavirus (MERS-CoV) presents a novel emerging threat to public health worldwide. Several treatments for infected individuals have been suggested including IFN, ribavirin and passive immunotherapy with convalescent plasma. Administration of IFN-α2b and ribavirin has improved outcomes of MERS-CoV infection in rhesus macaques when administered within 8 h post-challenge. However, detailed and systematic evidence on the activity of other clinically available drugs is limited. Here we compared the susceptibility of MERS-CoV with different IFN products (IFN-α2b, IFN-γ, IFN-universal, IFN-α2a and IFN-β), as well as with two antivirals, ribavirin and mycophenolic acid (MPA), against MERS-CoV (Hu/Jordan-N3/2012) in vitro. Of all the IFNs tested, IFN-β showed the strongst inhibition of MERS-CoV in vitro, with an IC₅₀ of 1.37 U ml(-1), 41 times lower than the previously reported IC₅₀ (56.08 U ml(-1)) of IFN-α2b. IFN-β inhibition was confirmed in the virus yield reduction assay, with an IC90 of 38.8 U ml(-1). Ribavirin did not inhibit viral replication in vitro at a dose that would be applicable to current treatment protocols in humans. In contrast, MPA showed strong inhibition, with an IC₅₀ of 2.87 µM. This drug has not been previously tested against MERS-CoV and may provide an alternative to ribavirin for treatment of MERS-CoV. In conclusion, IFN-β, MPA or a combination of the two may be beneficial in the treatment of MERS-CoV or as a post-exposure intervention in high-risk patients with known exposures to MERS-CoV.

Transcriptomic characterization of the novel avian-origin influenza A (H7N9) virus: specific host response and responses intermediate between avian (H5N1 and H7N7) and human (H3N2) viruses and implications for treatment options

A novel avian-origin H7N9 influenza A virus (IAV) emerged in China in 2013, causing mild to lethal human respiratory infections. H7N9 originated with multiple reassortment events between avian viruses and carries genetic markers of human adaptation. Determining whether H7N9 induces a host response closer to that with human or avian IAV is important in order to better characterize this emerging virus. Here we compared the human lung epithelial cell response to infection with A/Anhui/01/13 (H7N9) or highly pathogenic avian-origin H5N1, H7N7, or human seasonal H3N2 IAV. The transcriptomic response to H7N9 was highly specific to this strain but was more similar to the response to human H3N2 than to that to other avian IAVs. H7N9 and H3N2 both elicited responses related to eicosanoid signaling and chromatin modification, whereas H7N9 specifically induced genes regulating the cell cycle and transcription. Among avian IAVs, the response to H7N9 was closest to that elicited by H5N1 virus. Host responses common to H7N9 and the other avian viruses included the lack of induction of the antigen presentation pathway and reduced proinflammatory cytokine induction compared to that with H3N2. Repression of these responses could have an important impact on the immunogenicity and virulence of H7N9 in humans. Finally, using a genome-based drug repurposing approach, we identified several drugs predicted to regulate the host response to H7N9 that may act as potential antivirals, including several kinase inhibitors, as well as FDA-approved drugs, such as troglitazone and minocycline. Importantly, we validated that minocycline inhibited H7N9 replication in vitro, suggesting that our computational approach holds promise for identifying novel antivirals.

IMPORTANCE

Whether H7N9 will be the next pandemic influenza virus or will persist and sporadically infect humans from its avian reservoir, similar to H5N1, is not known yet. High-throughput profiling of the host response to infection allows rapid characterization of virus-host interactions and generates many hypotheses that will accelerate understanding and responsiveness to this potential threat. We show that the cellular response to H7N9 virus is closer to that induced by H3N2 than to that induced by H5N1, reflecting the potential of this new virus for adaptation to humans. Importantly, dissecting the host response to H7N9 may guide host-directed antiviral development.

Moving H5N1 studies into the era of systems biology

The dynamics of H5N1 influenza virus pathogenesis are multifaceted and can be seen as an emergent property that cannot be comprehended without looking at the system as a whole. In past years, most of the high-throughput studies on H5N1-host interactions have focused on the host transcriptomic response, at the cellular or the lung tissue level. These studies pointed out that the dynamics and magnitude of the innate immune response and immune cell infiltration is critical to H5N1 pathogenesis. However, viral-host interactions are multidimensional and advances in technologies are creating new possibilities to systematically measure additional levels of 'omic data (e.g. proteomic, metabolomic, and RNA profiling) at each temporal and spatial scale (from the single cell to the organism) of the host response. Natural host genetic variation represents another dimension of the host response that determines pathogenesis. Systems biology models of H5N1 disease aim at understanding and predicting pathogenesis through integration of these different dimensions by using intensive computational modeling. In this review, we describe the importance of 'omic studies for providing a more comprehensive view of infection and mathematical models that are being developed to integrate these data. This review provides a roadmap for what needs to be done in the future and what computational strategies should be used to build a global model of H5N1 pathogenesis. It is time for systems biology of H5N1 pathogenesis to take center stage as the field moves toward a more comprehensive view of virus-host interactions.

Drug repurposing: a better approach for infectious disease drug discovery?

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Infectious disease investigators need to embrace new drug repurposing approaches.

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Key components include public databases and predictive computational methods.

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This approach could significantly reduce cost and time for drug development.

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Support for large scale drug and disease phenotype screening is essential.

The advent of publicly available databases containing system-wide phenotypic data of the host response to both drugs and pathogens, in conjunction with bioinformatics and computational methods now allows for in silico predictions of FDA-approved drugs as treatments against infection diseases. This systems biology approach captures the complexity of both the pathogen and drug host response in the form of expression patterns or molecular interaction networks without having to understand the underlying mechanisms of action. These drug repurposing techniques have been successful in identifying new drug candidates for several types of cancers and were recently used to identify potential therapeutics against influenza, the newly discovered Middle Eastern Respiratory Syndrome coronavirus and several parasitic diseases. These new approaches have the potential to significantly reduce both the time and cost for infectious diseases drug discovery.

Antiviral and anti-inflammatory activity of arbidol hydrochloride in influenza A (H1N1) virus infection

AIM

To investigate the effects of arbidol hydrochloride (ARB), a widely used antiviral agent, on the inflammation induced by influenza virus.

METHODS

MDCK cells were infected with seasonal influenza A/FM/1/47 (H1N1) or pandemic influenza A/Hubei/71/2009 (H1N1). In vitro cytotoxicity and antiviral activity of ARB was determined using MTT assay. BALB/c mice were infected with A/FM/1/47 (H1N1). Four hours later the mice were administered ARB (45, 90, and 180 mg·kg(-1)·d(-1)) or the neuraminidase inhibitor oseltamivir (22.5 mg·kg(-1)·d(-1)) via oral gavage once a day for 5 d. Body-weight, median survival time, viral titer, and lung index of the mice were measured. The levels of inflammatory cytokines were examined using real-time RT-PCR and ELISA.

RESULTS

Both H1N1 stains were equally sensitive to ARB as tested in vitro. In the infected mice, ARB (90 and 180 mg·kg(-1)·d(-1)) significantly decreased the mortality, alleviated virus-induced lung lesions and viral titers. Furthermore, ARB suppressed the levels of IL-1β, IL-6, IL-12, and TNF-α, and elevated the level of IL-10 in the bronchoalveolar lavage fluids and lung tissues. However, ARB did not significantly affect the levels of IFN-α and IFN-γ, but reduced the level of IFN-β1 in lung tissues at 5 dpi. In peritoneal macrophages challenged with A/FM/1/47 (H1N1) or poly I:C, ARB (20 μmol/L) suppressed the levels of IL-1β, IL-6, IL-12, and TNF-α, and elevated the level of IL-10. Oseltamivir produced comparable alleviation of virus-induced lung lesions with more reduction in the viral titers, but less effective modulation of the inflammatory cytokines.

CONCLUSION

ARB efficiently inhibits both H1N1 stains and diminishes both viral replication and acute inflammation through modulating the expression of inflammatory cytokines.

Systems virology: host-directed approaches to viral pathogenesis and drug targeting

Systems biology approaches are required to advance our understanding of virus–host interactions, how these interactions cause disease and, ultimately, how to improve diagnostics, therapeutics and vaccines.

Over the past decade, the field of systems virology has evolved from using first-generation microarrays to the integration of multidimensional data sets. This has resulted in significant findings, including the identification of gene expression signatures that are predictive of viral pathogenesis and vaccine efficacy, insights into how viruses disrupt cellular metabolism, and the mapping of virus–host interactomes.

To fulfil its initial promise of revolutionizing our understanding of virus–host interactions, the field of systems virology must move beyond just the listing of molecules that are differentially expressed following viral infection; it must now look to define the relationships between key host molecules and their interactions with viral components.

Several key computational challenges must be addressed in order to move into this new phase of systems virology, including consideration of nonlinear relationships such as the dynamics of the system, the integration of multidimensional data sets and the identification of causal relationships.

Virologists, computer scientists and mathematicians must combine their skills and expertise in applying systems approaches to untangle the complex question of how viruses kill.

Katze and colleagues provide an overview of the evolution of systems virology and the insights obtained from using such methodologies to study virus–host interactions. Combining systems, mathematical and computational approaches with traditional virology research will offer a better understanding of how viruses cause disease and will help in the development of therapeutics.

High-throughput molecular profiling and computational biology are changing the face of virology, providing a new appreciation of the importance of the host in viral pathogenesis and offering unprecedented opportunities for better diagnostics, therapeutics and vaccines. Here, we provide a snapshot of the evolution of systems virology, from global gene expression profiling and signatures of disease outcome, to geometry-based computational methods that promise to yield novel therapeutic targets, personalized medicine and a deeper understanding of how viruses cause disease. To realize these goals, pipettes and Petri dishes need to join forces with the powers of mathematics and computational biology.

Cell host response to infection with novel human coronavirus EMC predicts potential antivirals and important differences with SARS coronavirus

A novel human coronavirus (HCoV-EMC) was recently identified in the Middle East as the causative agent of a severe acute respiratory syndrome (SARS) resembling the illness caused by SARS coronavirus (SARS-CoV). Although derived from the CoV family, the two viruses are genetically distinct and do not use the same receptor. Here, we investigated whether HCoV-EMC and SARS-CoV induce similar or distinct host responses after infection of a human lung epithelial cell line. HCoV-EMC was able to replicate as efficiently as SARS-CoV in Calu-3 cells and similarly induced minimal transcriptomic changes before 12 h postinfection. Later in infection, HCoV-EMC induced a massive dysregulation of the host transcriptome, to a much greater extent than SARS-CoV. Both viruses induced a similar activation of pattern recognition receptors and the interleukin 17 (IL-17) pathway, but HCoV-EMC specifically down-regulated the expression of several genes within the antigen presentation pathway, including both type I and II major histocompatibility complex (MHC) genes. This could have an important impact on the ability of the host to mount an adaptive host response. A unique set of 207 genes was dysregulated early and permanently throughout infection with HCoV-EMC, and was used in a computational screen to predict potential antiviral compounds, including kinase inhibitors and glucocorticoids. Overall, HCoV-EMC and SARS-CoV elicit distinct host gene expression responses, which might impact in vivo pathogenesis and could orient therapeutic strategies against that emergent virus.

IMPORTANCE

Identification of a novel coronavirus causing fatal respiratory infection in humans raises concerns about a possible widespread outbreak of severe respiratory infection similar to the one caused by SARS-CoV. Using a human lung epithelial cell line and global transcriptomic profiling, we identified differences in the host response between HCoV-EMC and SARS-CoV. This enables rapid assessment of viral properties and the ability to anticipate possible differences in human clinical responses to HCoV-EMC and SARS-CoV. We used this information to predict potential effective drugs against HCoV-EMC, a method that could be more generally used to identify candidate therapeutics in future disease outbreaks. These data will help to generate hypotheses and make rapid advancements in characterizing this new virus.

Host microRNA molecular signatures associated with human H1N1 and H3N2 influenza A viruses reveal an unanticipated antiviral activity for miR-146a

While post-transcriptional regulation of gene expression by microRNAs (miRNAs) has been shown to be involved in influenza virus replication cycle, only a few studies have further investigated this aspect in a human cellular model infected with human influenza viruses. In this study, we performed miRNA global profiling in human lung epithelial cells (A549) infected by two different subtypes of human influenza A viruses (H1N1 and H3N2). We identified a common miRNA signature in response to infection by the two different strains, highlighting a pool of five miRNAs commonly deregulated, which are known to be involved in the innate immune response or apoptosis. Among the five miRNA hits, the only upregulated miRNA in response to influenza infection corresponded to miR-146a. Based on a previously published gene expression dataset, we extracted inversely correlated miR-146a target genes and determined their first-level interactants. This functional analysis revealed eight distinct biological processes strongly associated with these interactants: Toll-like receptor pathway, innate immune response, cytokine production and apoptosis. To better understand the biological significance of miR-146a upregulation, using a reporter assay and a specific anti-miR-146a inhibitor, we confirmed that infection increased the endogenous miR-146a promoter activity and that inhibition of miR-146a significantly increased viral propagation. Altogether, our results suggest a functional role of miR-146a in the outcome of influenza infection, at the crossroads of several biological processes.

Newer influenza antivirals, biotherapeutics and combinations

This summary provides an overview of investigational antiviral agents for influenza and of future directions for development of influenza therapeutics. While progress in developing clinically useful antiviral agents for influenza has been generally slow, especially with respect to seriously ill and high-risk patients, important clinical studies of intravenous neuraminidase inhibitors, antibodies and drug combinations are currently in progress. The current decade offers the promise of developing small molecular weight inhibitors with novel mechanisms of action, including host-directed therapies, new biotherapeutics and drug combinations, that should provide more effective antiviral therapies and help mitigate the problem of antiviral resistance. Immunomodulatory interventions also offer promise but need to be based on better understanding of influenza pathogenesis, particularly in seriously ill patients. The development of combination interventions, immunomodulators and host-directed therapies presents unique clinical trial design and regulatory hurdles that remain to be addressed.

18S rRNA is a reliable normalisation gene for real time PCR based on influenza virus infected cells

BACKGROUND

One requisite of quantitative reverse transcription PCR (qRT-PCR) is to normalise the data with an internal reference gene that is invariant regardless of treatment, such as virus infection. Several studies have found variability in the expression of commonly used housekeeping genes, such as beta-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), under different experimental settings. However, ACTB and GAPDH remain widely used in the studies of host gene response to virus infections, including influenza viruses. To date no detailed study has been described that compares the suitability of commonly used housekeeping genes in influenza virus infections. The present study evaluated several commonly used housekeeping genes [ACTB, GAPDH, 18S ribosomal RNA (18S rRNA), ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide (ATP5B) and ATP synthase, H+ transporting, mitochondrial Fo complex, subunit C1 (subunit 9) (ATP5G1)] to identify the most stably expressed gene in human, pig, chicken and duck cells infected with a range of influenza A virus subtypes.

RESULTS

The relative expression stability of commonly used housekeeping genes were determined in primary human bronchial epithelial cells (HBECs), pig tracheal epithelial cells (PTECs), and chicken and duck primary lung-derived cells infected with five influenza A virus subtypes. Analysis of qRT-PCR data from virus and mock infected cells using NormFinder and BestKeeper software programmes found that 18S rRNA was the most stable gene in HBECs, PTECs and avian lung cells.

CONCLUSIONS

Based on the presented data from cell culture models (HBECs, PTECs, chicken and duck lung cells) infected with a range of influenza viruses, we found that 18S rRNA is the most stable reference gene for normalising qRT-PCR data. Expression levels of the other housekeeping genes evaluated in this study (including ACTB and GPADH) were highly affected by influenza virus infection and hence are not reliable as reference genes for RNA normalisation.

Inhibition of rotavirus infection in cultured cells by N-acetyl-cysteine, PPARγ agonists and NSAIDs

Although the current rotavirus vaccines have shown good tolerance and significant efficacy, it would be useful to develop alternative or complementary strategies aimed at preventing or treating acute diarrhoeal disease caused by this viral agent. A variety of antiviral strategies other than vaccines have been assayed for rotavirus infection management. The recently demonstrated sensitivity of rotavirus infectivity to thiol/disulfide reagents prompted assays for screening drugs that potentially affect cellular redox reactions. MA104 or Caco-2 cells were inoculated with the rotavirus strains RRV, Wa, Wi or M69 and then incubated with different concentrations of drugs belonging to a selected group of 60 drugs that are currently used in humans for purposes other than rotavirus infection treatment. Eighteen of these drugs were able to inhibit rotavirus infectivity to different extents. A more systematic evaluation was performed with drugs that could be used in children such as N-acetylcysteine and ascorbic acid, in addition to ibuprofen, pioglitazone and rosiglitazone, all of which affecting cellular pathways potentially needed by the rotavirus infection process. Evidence is provided here that rotavirus infectivity is significantly inhibited by NAC in different cell-culture systems. These findings suggest that NAC has the potential to be used as a therapeutic tool for treatment and prevention of rotavirus disease in children.

The influenza fingerprints: NS1 and M1 proteins contribute to specific host cell ultrastructure signatures upon infection by different influenza A viruses

Influenza A are nuclear replicating viruses which hijack host machineries in order to achieve optimal infection. Numerous functional virus-host interactions have now been characterized, but little information has been gathered concerning their link to the virally induced remodeling of the host cellular architecture. In this study, we infected cells with several human and avian influenza viruses and we have analyzed their ultrastructural modifications by using electron and confocal microscopy. We discovered that infections lead to a major and systematic disruption of nucleoli and the formation of a large number of diverse viral structures showing specificity that depended on the subtype origin and genomic composition of viruses. We identified NS1 and M1 proteins as the main actors in the remodeling of the host ultra-structure and our results suggest that each influenza A virus strain could be associated with a specific cellular fingerprint, possibly correlated to the functional properties of their viral components.

Influenza A viruses control expression of proviral human p53 isoforms p53β and Delta133p53α

Previous studies have described the role of p53 isoforms, including p53β and Δ133p53α, in the modulation of the activity of full-length p53, which regulates cell fate. In the context of influenza virus infection, an interplay between influenza viruses and p53 has been described, with p53 being involved in the antiviral response. However, the role of physiological p53 isoforms has never been explored in this context. Here, we demonstrate that p53 isoforms play a role in influenza A virus infection by using silencing and transient expression strategies in human lung epithelial cells. In addition, with the help of a panel of different influenza viruses from different subtypes, we also show that infection differentially regulates the expressions of p53β and Δ133p53α. Altogether, our results highlight the role of p53 isoforms in the viral cycle of influenza A viruses, with p53β and Δ133p53α acting as regulators of viral production in a p53-dependent manner.

A chemical genetic approach identifies piperazine antipsychotics as promoters of CNS neurite growth on inhibitory substrates

Injury to the central nervous system (CNS) can result in lifelong loss of function due in part to the regenerative failure of CNS neurons. Inhibitory proteins derived from myelin and the astroglial scar are major barriers for the successful regeneration of injured CNS neurons. Previously, we described the identification of a novel compound, F05, which promotes neurite growth from neurons challenged with inhibitory substrates in vitro, and promotes axonal regeneration in vivo (Usher et al., 2010). To identify additional regeneration-promoting compounds, we used F05-induced gene expression profiles to query the Broad Institute Connectivity Map, a gene expression database of cells treated with >1300 compounds. Despite no shared chemical similarity, F05-induced changes in gene expression were remarkably similar to those seen with a group of piperazine phenothiazine antipsychotics (PhAPs). In contrast to antipsychotics of other structural classes, PhAPs promoted neurite growth of CNS neurons challenged with two different glial derived inhibitory substrates. Our pharmacological studies suggest a mechanism whereby PhAPs promote growth through antagonism of calmodulin signaling, independent of dopamine receptor antagonism. These findings shed light on mechanisms underlying neurite-inhibitory signaling, and suggest that clinically approved antipsychotic compounds may be repurposed for use in CNS injured patients.

Overview of chemical genomics and proteomics

Chemical genetics, genomics, and proteomics have been in existence as distinct offshoots of chemical biology for about 20 years. This review provides a brief definition of each, followed by some examples of how each technology is being used to advance basic research and drug discovery.

Systematic approaches towards the development of host-directed antiviral therapeutics

Since the onset of antiviral therapy, viral resistance has compromised the clinical value of small-molecule drugs targeting pathogen components. As intracellular parasites, viruses complete their life cycle by hijacking a multitude of host-factors. Aiming at the latter rather than the pathogen directly, host-directed antiviral therapy has emerged as a concept to counteract evolution of viral resistance and develop broad-spectrum drug classes. This approach is propelled by bioinformatics analysis of genome-wide screens that greatly enhance insights into the complex network of host-pathogen interactions and generate a shortlist of potential gene targets from a multitude of candidates, thus setting the stage for a new era of rational identification of drug targets for host-directed antiviral therapies. With particular emphasis on human immunodeficiency virus and influenza virus, two major human pathogens, we review screens employed to elucidate host-pathogen interactions and discuss the state of database ontology approaches applicable to defining a therapeutic endpoint. The value of this strategy for drug discovery is evaluated, and perspectives for bioinformatics-driven hit identification are outlined.

Cellular transcriptional profiling in human lung epithelial cells infected by different subtypes of influenza A viruses reveals an overall down-regulation of the host p53 pathway

Background

Influenza viruses can modulate and hijack several cellular signalling pathways to efficiently support their replication. We recently investigated and compared the cellular gene expression profiles of human lung A549 cells infected by five different subtypes of human and avian influenza viruses (Josset et al. Plos One 2010). Using these transcriptomic data, we have focused our analysis on the modulation of the p53 pathway in response to influenza infection.

Results

Our results were supported by both RT-qPCR and western blot analyses and reveal multiple alterations of the p53 pathway during infection. A down-regulation of mRNA expression was observed for the main regulators of p53 protein stability during infection by the complete set of viruses tested, and a significant decrease in p53 mRNA expression was also observed in H5N1 infected cells. In addition, several p53 target genes were also down-regulated by these influenza viruses and the expression of their product reduced.

Conclusions

Our data reveal that influenza viruses cause an overall down-regulation of the host p53 pathway and highlight this pathway and p53 protein itself as important viral targets in the altering of apoptotic processes and in cell-cycle regulation.