Characterization of a new SARS-CoV-2 variant that emerged in Brazil.

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a key role in viral infectivity. It is also the major antigen stimulating the host's protective immune response, specifically, the production of neutralizing antibodies. Recently, a new variant of SARS-CoV-2 possessing multiple mutations in the S protein, designated P.1, emerged in Brazil. Here, we characterized a P.1 variant isolated in Japan by using Syrian hamsters, a well-established small animal model for the study of SARS-CoV-2 disease (COVID-19). In hamsters, the variant showed replicative abilities and pathogenicity similar to those of early and contemporary strains (i.e., SARS-CoV-2 bearing aspartic acid [D] or glycine [G] at position 614 of the S protein). Sera and/or plasma from convalescent patients and BNT162b2 messenger RNA vaccinees showed comparable neutralization titers across the P.1 variant, S-614D, and S-614G strains. In contrast, the S-614D and S-614G strains were less well recognized than the P.1 variant by serum from a P.1-infected patient. Prior infection with S-614D or S-614G strains efficiently prevented the replication of the P.1 variant in the lower respiratory tract of hamsters upon reinfection. In addition, passive transfer of neutralizing antibodies to hamsters infected with the P.1 variant or the S-614G strain led to reduced virus replication in the lower respiratory tract. However, the effect was less pronounced against the P.1 variant than the S-614G strain. These findings suggest that the P.1 variant may be somewhat antigenically different from the early and contemporary strains of SARS-CoV-2.

Hypergraph models of biological networks to identify genes critical to pathogenic viral response.

BACKGROUND: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. RESULTS: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. CONCLUSIONS: Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses.

MERS-CoV and H5N1 influenza virus antagonize antigen presentation by altering the epigenetic landscape.

Convergent evolution dictates that diverse groups of viruses will target both similar and distinct host pathways to manipulate the immune response and improve infection. In this study, we sought to leverage this uneven viral antagonism to identify critical host factors that govern disease outcome. Utilizing a systems-based approach, we examined differential regulation of IFN-γ-dependent genes following infection with robust respiratory viruses including influenza viruses [A/influenza/Vietnam/1203/2004 (H5N1-VN1203) and A/influenza/California/04/2009 (H1N1-CA04)] and coronaviruses [severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV)]. Categorizing by function, we observed down-regulation of gene expression associated with antigen presentation following both H5N1-VN1203 and MERS-CoV infection. Further examination revealed global down-regulation of antigen-presentation gene expression, which was confirmed by proteomics for both H5N1-VN1203 and MERS-CoV infection. Importantly, epigenetic analysis suggested that DNA methylation, rather than histone modification, plays a crucial role in MERS-CoV-mediated antagonism of antigen-presentation gene expression; in contrast, H5N1-VN1203 likely utilizes a combination of epigenetic mechanisms to target antigen presentation. Together, the results indicate a common mechanism utilized by H5N1-VN1203 and MERS-CoV to modulate antigen presentation and the host adaptive immune response.

Characterization of H7N9 influenza A viruses isolated from humans.

Avian influenza A viruses rarely infect humans; however, when human infection and subsequent human-to-human transmission occurs, worldwide outbreaks (pandemics) can result. The recent sporadic infections of humans in China with a previously unrecognized avian influenza A virus of the H7N9 subtype (A(H7N9)) have caused concern owing to the appreciable case fatality rate associated with these infections (more than 25%), potential instances of human-to-human transmission, and the lack of pre-existing immunity among humans to viruses of this subtype. Here we characterize two early human A(H7N9) isolates, A/Anhui/1/2013 (H7N9) and A/Shanghai/1/2013 (H7N9); hereafter referred to as Anhui/1 and Shanghai/1, respectively. In mice, Anhui/1 and Shanghai/1 were more pathogenic than a control avian H7N9 virus (A/duck/Gunma/466/2011 (H7N9); Dk/GM466) and a representative pandemic 2009 H1N1 virus (A/California/4/2009 (H1N1pdm09); CA04). Anhui/1, Shanghai/1 and Dk/GM466 replicated well in the nasal turbinates of ferrets. In nonhuman primates, Anhui/1 and Dk/GM466 replicated efficiently in the upper and lower respiratory tracts, whereas the replicative ability of conventional human influenza viruses is typically restricted to the upper respiratory tract of infected primates. By contrast, Anhui/1 did not replicate well in miniature pigs after intranasal inoculation. Critically, Anhui/1 transmitted through respiratory droplets in one of three pairs of ferrets. Glycan arrays showed that Anhui/1, Shanghai/1 and A/Hangzhou/1/2013 (H7N9) (a third human A(H7N9) virus tested in this assay) bind to human virus-type receptors, a property that may be critical for virus transmissibility in ferrets. Anhui/1 was found to be less sensitive in mice to neuraminidase inhibitors than a pandemic H1N1 2009 virus, although both viruses were equally susceptible to an experimental antiviral polymerase inhibitor. The robust replicative ability in mice, ferrets and nonhuman primates and the limited transmissibility in ferrets of Anhui/1 suggest that A(H7N9) viruses have pandemic potential.

Multi-task consensus clustering of genome-wide transcriptomes from related biological conditions.

MOTIVATION: Identifying the shared and pathogen-specific components of host transcriptional regulatory programs is important for understanding the principles of regulation of immune response. Recent efforts in systems biology studies of infectious diseases have resulted in a large collection of datasets measuring host transcriptional response to various pathogens. Computational methods to identify and compare gene expression modules across different infections offer a powerful way to identify strain-specific and shared components of the regulatory program. An important challenge is to identify statistically robust gene expression modules as well as to reliably detect genes that change their module memberships between infections. RESULTS: We present MULCCH (MULti-task spectral Consensus Clustering for Hierarchically related tasks), a consensus extension of a multi-task clustering algorithm to infer high-confidence strain-specific host response modules under infections from multiple virus strains. On simulated data, MULCCH more accurately identifies genes exhibiting pathogen-specific patterns compared to non-consensus and nonmulti-task clustering approaches. Application of MULCCH to mammalian transcriptional response to a panel of influenza viruses showed that our method identifies clusters with greater coherence compared to non-consensus methods. Further, MULCCH derived clusters are enriched for several immune system-related processes and regulators. In summary, MULCCH provides a reliable module-based approach to identify molecular pathways and gene sets characterizing commonality and specificity of host response to viruses of different pathogenicities. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://bitbucket.org/roygroup/mulcch CONTACT: sroy@biostat.wisc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An Ultrasensitive Mechanism Regulates Influenza Virus-Induced Inflammation.

Influenza viruses present major challenges to public health, evident by the 2009 influenza pandemic. Highly pathogenic influenza virus infections generally coincide with early, high levels of inflammatory cytokines that some studies have suggested may be regulated in a strain-dependent manner. However, a comprehensive characterization of the complex dynamics of the inflammatory response induced by virulent influenza strains is lacking. Here, we applied gene co-expression and nonlinear regression analysis to time-course, microarray data developed from influenza-infected mouse lung to create mathematical models of the host inflammatory response. We found that the dynamics of inflammation-associated gene expression are regulated by an ultrasensitive-like mechanism in which low levels of virus induce minimal gene expression but expression is strongly induced once a threshold virus titer is exceeded. Cytokine assays confirmed that the production of several key inflammatory cytokines, such as interleukin 6 and monocyte chemotactic protein 1, exhibit ultrasensitive behavior. A systematic exploration of the pathways regulating the inflammatory-associated gene response suggests that the molecular origins of this ultrasensitive response mechanism lie within the branch of the Toll-like receptor pathway that regulates STAT1 phosphorylation. This study provides the first evidence of an ultrasensitive mechanism regulating influenza virus-induced inflammation in whole lungs and provides insight into how different virus strains can induce distinct temporal inflammation response profiles. The approach developed here should facilitate the construction of gene regulatory models of other infectious diseases.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens.

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.

MPLEx: a method for simultaneous pathogen inactivation and extraction of samples for multi-omics profiling.

The continued emergence and spread of infectious agents is of great concern, and systems biology approaches to infectious disease research can advance our understanding of host-pathogen relationships and facilitate the development of new therapies and vaccines. Molecular characterization of infectious samples outside of appropriate biosafety containment can take place only subsequent to pathogen inactivation. Herein, we describe a modified Folch extraction using chloroform/methanol that facilitates the molecular characterization of infectious samples by enabling simultaneous pathogen inactivation and extraction of proteins, metabolites, and lipids for subsequent mass spectrometry-based multi-omics measurements. This single-sample metabolite, protein and lipid extraction (MPLEx) method resulted in complete inactivation of clinically important bacterial and viral pathogens with exposed lipid membranes, including Yersinia pestis, Salmonella Typhimurium, and Campylobacter jejuni in pure culture, and Yersinia pestis, Campylobacter jejuni, and West Nile, MERS-CoV, Ebola, and influenza H7N9 viruses in infection studies. In addition, >99% inactivation, which increased with solvent exposure time, was also observed for pathogens without exposed lipid membranes including community-associated methicillin-resistant Staphylococcus aureus, Clostridium difficile spores and vegetative cells, and adenovirus type 5. The overall pipeline of inactivation and subsequent proteomic, metabolomic, and lipidomic analyses was evaluated using a human epithelial lung cell line infected with wild-type and mutant influenza H7N9 viruses, thereby demonstrating that MPLEx yields biomaterial of sufficient quality for subsequent multi-omics analyses. Based on these experimental results, we believe that MPLEx will facilitate systems biology studies of infectious samples by enabling simultaneous pathogen inactivation and multi-omics measurements from a single specimen with high success for pathogens with exposed lipid membranes.

Ebola Virus Stability Under Hospital and Environmental Conditions.

The West African outbreak of Ebola virus (EBOV) is largely contained, but sporadic new cases continue to emerge. To assess the potential contribution of fomites to human infections with EBOV, we tested EBOV stability in human blood spotted onto Sierra Leonean banknotes and in syringe needles under hospital and environmental conditions. Under some of these conditions, EBOV remained infectious for >30 days, indicating that EBOV-contaminated items may pose a serious risk to humans.

Adding protein context to the human protein-protein interaction network to reveal meaningful interactions.

Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs), which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays) or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer's disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the annotated human PPI network via a web frontend that allows the construction of context-specific networks in several ways.

Annotation of long non-coding RNAs expressed in collaborative cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts.

The outcome of respiratory virus infection is determined by a complex interplay of viral and host factors. Some potentially important host factors for the antiviral response, whose functions remain largely unexplored, are long non-coding RNAs (lncRNAs). Here we systematically inferred the regulatory functions of host lncRNAs in response to influenza A virus and severe acute respiratory syndrome coronavirus (SARS-CoV) based on their similarity in expression with genes of known function. We performed total RNA-Seq on viral-infected lungs from eight mouse strains, yielding a large data set of transcriptional responses. Overall 5,329 lncRNAs were differentially expressed after infection. Most of the lncRNAs were co-expressed with coding genes in modules enriched in genes associated with lung homeostasis pathways or immune response processes. Each lncRNA was further individually annotated using a rank-based method, enabling us to associate 5,295 lncRNAs to at least one gene set and to predict their potential cis effects. We validated the lncRNAs predicted to be interferon-stimulated by profiling mouse responses after interferon-α treatment. Altogether, these results provide a broad categorization of potential lncRNA functions and identify subsets of lncRNAs with likely key roles in respiratory virus pathogenesis. These data are fully accessible through the MOuse NOn-Code Lung interactive database (MONOCLdb).

A compendium of multi-omics data illuminating host responses to lethal human virus infections.

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

The TLR4-TRIF pathway protects against H5N1 influenza virus infection.

Prestimulation of the TLR4 pathway with lipopolysaccharide (LPS) protects mice from lethal infection with H5N1 influenza virus. Here, we reveal that the TLR4-TRIF pathway is required for this protective effect by using mice whose TLR4-related molecules were knocked out. Microarray analysis of primary mouse lung culture cells that were LPS pretreated and infected with an H5N1 virus indicated that TLR3 mRNA was upregulated. Primary lung culture cells of TLR3 knockout mice showed no response to LPS pretreatment against H5N1 virus infection, suggesting that TLR3 is also involved in the preventive effect of LPS. Our data suggest that the TLR4-TRIF axis has an important role in stimulating protective innate immunity against H5N1 influenza A virus infection and that TLR3 signaling is involved in this pathway.

Integrated clinical, pathologic, virologic, and transcriptomic analysis of H5N1 influenza virus-induced viral pneumonia in the rhesus macaque.

Viral pneumonia has been frequently reported during early stages of influenza virus pandemics and in many human cases of highly pathogenic avian influenza (HPAI) H5N1 virus infection. To better understand the pathogenesis of this disease, we produced nonlethal viral pneumonia in rhesus macaques by using an HPAI H5N1 virus (A/Anhui/2/2005; referred to as Anhui/2). Infected macaques were monitored for 14 days, and tissue samples were collected at 6 time points for virologic, histopathologic, and transcriptomic analyses. Anhui/2 efficiently replicated in the lung from 12 h to 3 days postinfection (p.i.) and caused temporal but severe pneumonia that began to resolve by day 14. Lung transcriptional changes were first observed at 6 h, and increased expression of vascular permeability regulators and neutrophil chemoattractants correlated with increased serum leakage and neutrophil infiltration in situ. Additional inflammatory, antiviral, and apoptotic genes were upregulated from 12 h, concurrent with viral antigen detection and increasing immune cell populations. A shift toward upregulation of acquired immunity was apparent after day 6. Expression levels of established immune cell molecular markers revealed remarkable similarity with pathological findings, indicating early and robust neutrophil infiltration, a slight delay in macrophage accumulation, and abundant late populations of T lymphocytes. We also characterized the putative mechanisms regulating a unique, pneumonia-associated biphasic fever pattern. Thus, this study is the first to use a comprehensive and integrative approach to delineate specific molecular mechanisms regulating influenza virus-induced pneumonia in nonhuman primates, an important first step toward better management of human influenza virus disease.

Multi-omics of NET formation and correlations with CNDP1, PSPB, and L-cystine levels in severe and mild COVID-19 infections.

The detailed mechanisms of COVID-19 infection pathology remain poorly understood. To improve our understanding of SARS-CoV-2 pathology, we performed a multi-omics and correlative analysis of an immunologically naïve SARS-CoV-2 clinical cohort from blood plasma of uninfected controls, mild, and severe infections. Consistent with previous observations, severe patient populations showed an elevation of pulmonary surfactant levels. Intriguingly, mild patients showed a statistically significant elevation in the carnosine dipeptidase modifying enzyme (CNDP1). Mild and severe patient populations showed a strong elevation in the metabolite L-cystine (oxidized form of the amino acid cysteine) and enzymes with roles in glutathione metabolism. Neutrophil extracellular traps (NETs) were observed in both mild and severe populations, and NET formation was higher in severe vs. mild samples. Our correlative analysis suggests a potential protective role for CNDP1 in suppressing PSPB release from the pulmonary space whereas NET formation correlates with increased PSPB levels and disease severity. In our discussion we put forward a possible model where NET formation drives pulmonary occlusions and CNDP1 promotes antioxidation, pleiotropic immune responses, and vasodilation by accelerating histamine synthesis.

Human immunodeficiency virus rev-binding protein is essential for influenza a virus replication and promotes genome trafficking in late-stage infection.

Influenza A virus uses cellular protein transport systems (e.g., CRM1-mediated nuclear export and Rab11-dependent recycling endosomes) for genome trafficking from the nucleus to the plasma membrane, where new virions are assembled. However, the detailed mechanisms of these events have not been completely resolved, and additional cellular factors are probably required. Here, we investigated the role of the cellular human immunodeficiency virus (HIV) Rev-binding protein (HRB), which interacts with influenza virus nuclear export protein (NEP), during the influenza virus life cycle. By using small interfering RNAs (siRNAs) and overexpression of a dominant negative HRB protein fragment, we show that cells lacking functional HRB have significantly reduced production of influenza virus progeny and that this defect results from impaired viral ribonucleoprotein (vRNP) delivery to the plasma membrane in late-stage infection. Since HRB colocalizes with influenza vRNPs early after their delivery to the cytoplasm, it may mediate a connection between the nucleocytoplasmic transport machinery and the endosomal system, thus facilitating the transfer of vRNPs from nuclear export to cytoplasmic trafficking complexes. We also found an association between NEP and HRB in the perinuclear region, suggesting that NEP may contribute to this process. Our results identify HRB as a second endosomal factor with a crucial role in influenza virus genome trafficking, suggest cooperation between unique endosomal compartments in the late steps of the influenza virus life cycle, and provide a common link between the cytoplasmic trafficking mechanisms of influenza virus and HIV.

RAB11A is essential for transport of the influenza virus genome to the plasma membrane.

Influenza A virus assembly is a complex process that requires the intersection of pathways involved in transporting viral glycoproteins, the matrix protein, and viral genomes, incorporated in the viral ribonucleoprotein (vRNP) complex, to plasma membrane sites of virion formation. Among these virion components, the mechanism of vRNP delivery is the most incompletely understood. Here, we reveal a functional relationship between the cellular Rab11 GTPase isoform, RAB11A, and vRNPs and show that RAB11A is indispensable for proper vRNP transport to the plasma membrane. Using an immunofluorescence-based assay with a monoclonal antibody that recognizes nucleoprotein in the form of vRNP, we demonstrate association between RAB11A and vRNPs at all stages of vRNP cytoplasmic transport. Abrogation of RAB11A expression through small interfering RNA (siRNA) treatment or disruption of RAB11A function by overexpression of dominant negative or constitutively active proteins caused aberrant vRNP intracellular accumulation, retention in the perinuclear region, and lack of accumulation at the plasma membrane. Complex formation between RAB11A and vRNPs was further established biochemically. Our results uncover a critical host factor with an essential contribution to influenza virus genome delivery and reveal a potential role for RAB11A in the transport of ribonucleoprotein cargo.

Host regulatory network response to infection with highly pathogenic H5N1 avian influenza virus.

During the last decade, more than half of humans infected with highly pathogenic avian influenza (HPAI) H5N1 viruses have died, yet virus-induced host signaling has yet to be clearly elucidated. Airway epithelia are known to produce inflammatory mediators that contribute to HPAI H5N1-mediated pathogenicity, but a comprehensive analysis of the host response in this cell type is lacking. Here, we leveraged a system approach to identify and statistically validate signaling subnetworks that define the dynamic transcriptional response of human bronchial epithelial cells after infection with influenza A/Vietnam/1203/2004 (H5N1, VN1203). Importantly, we validated a subset of transcripts from one subnetwork in both Calu-3 cells and mice. A more detailed examination of two subnetworks involved in the immune response and keratinization processes revealed potential novel mediators of HPAI H5N1 pathogenesis and host response signaling. Finally, we show how these results compare to those for a less virulent strain of influenza virus. Using emergent network properties, we provide fresh insight into the host response to HPAI H5N1 virus infection and identify novel avenues for perturbation studies and potential therapeutic interventions for fatal HPAI H5N1 disease.

Toll-like receptor pre-stimulation protects mice against lethal infection with highly pathogenic influenza viruses.

Since the beginning of the 20th century, humans have experienced four influenza pandemics, including the devastating 1918 'Spanish influenza'. Moreover, H5N1 highly pathogenic avian influenza (HPAI) viruses are currently spreading worldwide, although they are not yet efficiently transmitted among humans. While the threat of a global pandemic involving a highly pathogenic influenza virus strain looms large, our mechanisms to address such a catastrophe remain limited. Here, we show that pre-stimulation of Toll-like receptors (TLRs) 2 and 4 increased resistance against influenza viruses known to induce high pathogenicity in animal models. Our data emphasize the complexity of the host response against different influenza viruses, and suggest that TLR agonists might be utilized to protect against lethality associated with highly pathogenic influenza virus infection in humans.