1
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Eisfeld AJ, Anderson LN, Fan S, Walters KB, Halfmann PJ, Westhoff Smith D, Thackray LB, Tan Q, Sims AC, Menachery VD, Schäfer A, Sheahan TP, Cockrell AS, Stratton KG, Webb-Robertson BJM, Kyle JE, Burnum-Johnson KE, Kim YM, Nicora CD, Peralta Z, N'jai AU, Sahr F, van Bakel H, Diamond MS, Baric RS, Metz TO, Smith RD, Kawaoka Y, Waters KM. A compendium of multi-omics data illuminating host responses to lethal human virus infections. Sci Data 2024; 11:328. [PMID: 38565538 PMCID: PMC10987564 DOI: 10.1038/s41597-024-03124-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 03/04/2024] [Indexed: 04/04/2024] Open
Abstract
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.
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Affiliation(s)
- Amie J Eisfeld
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA.
| | - Lindsey N Anderson
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Shufang Fan
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Coronavirus and Other Respiratory Viruses Laboratory Branch (CRVLB), Coronavirus and Other Respiratory Viruses Division (CORVD), National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, GA, 30329, USA
| | - Kevin B Walters
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD, 21702, USA
| | - Peter J Halfmann
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Danielle Westhoff Smith
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Surgery, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Larissa B Thackray
- Department of Medicine, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Qing Tan
- Department of Medicine, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Amy C Sims
- Department of Epidemiology, University of North Carolina at Chapel Hill, North Carolina, 27599, USA
- Nuclear, Chemistry, and Biosciences Division; National Security Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Vineet D Menachery
- Department of Epidemiology, University of North Carolina at Chapel Hill, North Carolina, 27599, USA
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, 77555, USA
| | - Alexandra Schäfer
- Department of Epidemiology, University of North Carolina at Chapel Hill, North Carolina, 27599, USA
| | - Timothy P Sheahan
- Department of Epidemiology, University of North Carolina at Chapel Hill, North Carolina, 27599, USA
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Adam S Cockrell
- Department of Epidemiology, University of North Carolina at Chapel Hill, North Carolina, 27599, USA
- Solid Biosciences, Charlston, MA, 02139, USA
| | - Kelly G Stratton
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Bobbie-Jo M Webb-Robertson
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Jennifer E Kyle
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Kristin E Burnum-Johnson
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Young-Mo Kim
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Carrie D Nicora
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Zuleyma Peralta
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY, 10029, USA
- Partillion Bioscience, Los Angeles, CA, 90064, USA
| | - Alhaji U N'jai
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Biological Sciences, Fourah Bay College, Freetown, Sierra Leone
- Department of Microbiology, College of Medicine and Allied Health Sciences, University of Sierra Leone, Freetown, Sierra Leone
- Department of Medical Education, California University of Science and Medicine, Colton, CA, 92324, USA
| | - Foday Sahr
- Department of Microbiology, College of Medicine and Health Sciences, University of Sierra Leone, Freetown, Sierra Leone
| | - Harm van Bakel
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY, 10029, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York City, NY, 10029, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York City, NY, 10029, USA
| | - Michael S Diamond
- Department of Medicine, Washington University School of Medicine, Saint Louis, MO, 63110, USA
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Ralph S Baric
- Department of Epidemiology, University of North Carolina at Chapel Hill, North Carolina, 27599, USA
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Thomas O Metz
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Richard D Smith
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Yoshihiro Kawaoka
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, 108-8639, Tokyo, Japan
- The Research Center for Global Viral Diseases, National Center for Global Health and Medicine Research Institute, Tokyo, 108-8639, Japan
| | - Katrina M Waters
- Biological Sciences Division, Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
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2
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Mitchell HD, Eisfeld AJ, Stratton KG, Heller NC, Bramer LM, Wen J, McDermott JE, Gralinski LE, Sims AC, Le MQ, Baric RS, Kawaoka Y, Waters KM. The Role of EGFR in Influenza Pathogenicity: Multiple Network-Based Approaches to Identify a Key Regulator of Non-lethal Infections. Front Cell Dev Biol 2019; 7:200. [PMID: 31616667 PMCID: PMC6763731 DOI: 10.3389/fcell.2019.00200] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 09/05/2019] [Indexed: 12/14/2022] Open
Abstract
Despite high sequence similarity between pandemic and seasonal influenza viruses, there is extreme variation in host pathogenicity from one viral strain to the next. Identifying the underlying mechanisms of variability in pathogenicity is a critical task for understanding influenza virus infection and effective management of highly pathogenic influenza virus disease. We applied a network-based modeling approach to identify critical functions related to influenza virus pathogenicity using large transcriptomic and proteomic datasets from mice infected with six influenza virus strains or mutants. Our analysis revealed two pathogenicity-related gene expression clusters; these results were corroborated by matching proteomics data. We also identified parallel downstream processes that were altered during influenza pathogenesis. We found that network bottlenecks (nodes that bridge different network regions) were highly enriched in pathogenicity-related genes, while network hubs (highly connected network nodes) were significantly depleted in these genes. We confirmed that this trend persisted in a distinct virus: Severe Acute Respiratory Syndrome Coronavirus (SARS). The role of epidermal growth factor receptor (EGFR) in influenza pathogenesis, one of the bottleneck regulators with corroborating signals across transcript and protein expression data, was tested and validated in additional mouse infection experiments. We demonstrate that EGFR is important during influenza infection, but the role it plays changes for lethal versus non-lethal infections. Our results show that by using association networks, bottleneck genes that lack hub characteristics can be used to predict a gene's involvement in influenza virus pathogenicity. We also demonstrate the utility of employing multiple network approaches for analyzing host response data from viral infections.
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Affiliation(s)
- Hugh D Mitchell
- Pacific Northwest National Laboratory, Richland, WA, United States
| | - Amie J Eisfeld
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - Kelly G Stratton
- Pacific Northwest National Laboratory, Richland, WA, United States
| | - Natalie C Heller
- Pacific Northwest National Laboratory, Richland, WA, United States
| | - Lisa M Bramer
- Pacific Northwest National Laboratory, Richland, WA, United States
| | - Ji Wen
- Pacific Northwest National Laboratory, Richland, WA, United States
| | | | - Lisa E Gralinski
- Department of Microbiology and Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Amy C Sims
- Department of Microbiology and Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Mai Q Le
- National Institute of Hygiene and Epidemiology, Hanoi, Vietnam
| | - Ralph S Baric
- Department of Microbiology and Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Yoshihiro Kawaoka
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, United States.,Division of Virology, Department of Microbiology and Immunology, Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan.,International Research Center for Infectious Diseases, Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Katrina M Waters
- Pacific Northwest National Laboratory, Richland, WA, United States
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Eisfeld AJ, Gasper DJ, Suresh M, Kawaoka Y. C57BL/6J and C57BL/6NJ Mice Are Differentially Susceptible to Inflammation-Associated Disease Caused by Influenza A Virus. Front Microbiol 2019; 9:3307. [PMID: 30713529 PMCID: PMC6346684 DOI: 10.3389/fmicb.2018.03307] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 12/19/2018] [Indexed: 01/01/2023] Open
Abstract
Influenza viruses cause seasonal epidemics and sporadic pandemics, and are a major burden on human health. To develop better countermeasures and improve influenza disease outcomes, a clearer understanding of influenza pathogenesis is necessary. Host genetic factors have emerged as potential regulators of human influenza disease susceptibility, and in the mouse model, genetic background has been clearly linked to influenza pathogenicity. Here, we show that C57BL/6J mice are significantly more susceptible to disease caused by a 2009 pandemic H1N1 virus, an H7N9 virus, and a highly pathogenic H5N1 influenza virus compared to the closely related substrain, C57BL/6NJ. Mechanistically, influenza virus infection in C57BL/6J mice results in earlier presentation of edema, increased immune cell infiltration, higher levels of inflammatory cytokines, greater tissue damage, and delayed activation of regenerative processes in infected lung tissues compared to C57BL/6NJ mice. These differences are not dependent on virus replication levels. Six genes with known coding region differences between C57BL/6J and C57BL/6NJ strains exhibit increased transcript levels in influenza virus-infected mouse lungs, suggesting potential contributions to regulation of disease susceptibility. This work uncovers a previously unappreciated difference in disease susceptibility between the closely related C57BL/6J and C57BL/6NJ mice, which may be exploited in future studies to identify host factors and/or specific genetic elements that regulate host-dependent inflammatory mechanisms involved in influenza virus pathogenicity.
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Affiliation(s)
- Amie J Eisfeld
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - David J Gasper
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - M Suresh
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, United States
| | - Yoshihiro Kawaoka
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, United States.,Division of Virology, Department of Microbiology and Immunology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.,International Research Center for Infectious Diseases, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
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4
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Influenza-Omics and the Host Response: Recent Advances and Future Prospects. Pathogens 2017; 6:pathogens6020025. [PMID: 28604586 PMCID: PMC5488659 DOI: 10.3390/pathogens6020025] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Revised: 06/07/2017] [Accepted: 06/08/2017] [Indexed: 12/23/2022] Open
Abstract
Influenza A viruses (IAV) continually evolve and have the capacity to cause global pandemics. Because IAV represents an ongoing threat, identifying novel therapies and host innate immune factors that contribute to IAV pathogenesis is of considerable interest. This review summarizes the relevant literature as it relates to global host responses to influenza infection at both the proteome and transcriptome level. The various-omics infection systems that include but are not limited to ferrets, mice, pigs, and even the controlled infection of humans are reviewed. Discussion focuses on recent advances, remaining challenges, and knowledge gaps as it relates to influenza-omics infection outcomes.
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5
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Wani SA, Sahu AR, Saxena S, Hussain S, Pandey A, Kanchan S, Sahoo AP, Mishra B, Tiwari AK, Mishra BP, Gandham RK, Singh RK. Systems biology approach: Panacea for unravelling host-virus interactions and dynamics of vaccine induced immune response. GENE REPORTS 2016; 5:23-29. [PMID: 32289096 PMCID: PMC7104209 DOI: 10.1016/j.genrep.2016.08.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 06/24/2016] [Accepted: 08/01/2016] [Indexed: 12/18/2022]
Abstract
Systems biology is an interdisciplinary research field in life sciences, which involves a comprehensive and quantitative analysis of the interactions between all of the components of biological systems over time. For the past 50 years the discipline of virology has overly focused on the pathogen itself. However, we now know that the host response is equally or more important in defining the eventual pathological outcome of infection. Systems biology has in recent years been increasingly recognised for its importance to infectious disease research. Host-virus interactions can be better understood by taking into account the dynamical molecular networks that constitute a biological system. To decipher the pathobiological mechanisms of any disease requires a deep knowledge of how multiple and concurrent signal-transduction pathways operate and are deregulated. Hence the intricacies of signalling pathways can be dissected only by system level approaches. Deciphering the host virus interactions through system biology approach reviewed High throughput techniques to understand the host pathogen interactions examined Shift from virus-centric perspective to spectrum of virus-host interactions Modeling of host-virus cross talk
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Affiliation(s)
- Sajad Ahmad Wani
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Amit Ranjan Sahu
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Shikha Saxena
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Shahid Hussain
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Aruna Pandey
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Sonam Kanchan
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Aditya Prasad Sahoo
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Bina Mishra
- Division of Biological Products, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Ashok Kumar Tiwari
- Division of Biological Standardization, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Bishnu Prasad Mishra
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Ravi Kumar Gandham
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
| | - Raj Kumar Singh
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar 243122, India
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6
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Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens. PLoS Comput Biol 2016; 12:e1005013. [PMID: 27403523 PMCID: PMC4942116 DOI: 10.1371/journal.pcbi.1005013] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Accepted: 06/06/2016] [Indexed: 12/17/2022] Open
Abstract
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. An important challenge in infectious disease research is to understand how the human immune system responds to different types of pathogenic infections. An important component of mounting proper response is the transcriptional regulatory network that specifies the context-specific gene expression program in the host cell. However, our understanding of this regulatory network and how it drives context-specific transcriptional programs is incomplete. To address this gap, we performed a network-based analysis of host response to influenza viruses that integrated high-throughput mRNA- and protein measurements and protein-protein interaction networks to identify virus and pathogenicity-specific modules and their upstream physical regulatory programs. We inferred regulatory networks for human cell line and mouse host systems, which recapitulated several known regulators and pathways of the immune response and viral life cycle. We used the networks to study time point and strain-specific subnetworks and to prioritize important regulators of host response. We predicted several novel regulators, both at the mRNA and protein levels, and experimentally verified their role in the virus life cycle based on their ability to significantly impact viral replication.
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Niu Z, Chasman D, Eisfeld AJ, Kawaoka Y, Roy S. Multi-task consensus clustering of genome-wide transcriptomes from related biological conditions. Bioinformatics 2016; 32:1509-17. [PMID: 26801959 DOI: 10.1093/bioinformatics/btw007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Accepted: 01/04/2016] [Indexed: 12/27/2022] Open
Abstract
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.
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Affiliation(s)
- Zhen Niu
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Deborah Chasman
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Amie J Eisfeld
- Influenza Research Institute, Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, 53711, USA
| | - Yoshihiro Kawaoka
- Influenza Research Institute, Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, 53711, USA Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Sushmita Roy
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53792, USA
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8
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Abstract
The preceding chapters describe essential aspects of viral pathogenesis, including virus–cell interactions; viral spread within a host; and intrinsic, innate, and adaptive immune responses. This chapter extends the theme and addresses diverse patterns of viral infections that are determined by both the virus and the host. Thus, virulence or susceptibility depends upon the specific virus–host combination. This is particularly true in the case of persistent infections, which involve a delicate balance between virus and host. We will focus first on virus virulence and host susceptibility, and then turn to the complex variables that govern persistent infections. Chapters 4–6, on innate, adaptive, and aberrant immunity, and Chapters 11–15, on systems biology approaches, also provide important insights into the patterns of infection.
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9
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Korth MJ, Law GL. Systems Virology. VIRAL PATHOGENESIS 2016. [PMCID: PMC7149947 DOI: 10.1016/b978-0-12-800964-2.00011-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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10
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Park SJ, Kumar M, Kwon HI, Seong RK, Han K, Song JM, Kim CJ, Choi YK, Shin OS. Dynamic changes in host gene expression associated with H5N8 avian influenza virus infection in mice. Sci Rep 2015; 5:16512. [PMID: 26576844 PMCID: PMC4649622 DOI: 10.1038/srep16512] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Accepted: 10/12/2015] [Indexed: 11/10/2022] Open
Abstract
Emerging outbreaks of newly found, highly pathogenic avian influenza (HPAI) A(H5N8) viruses have been reported globally. Previous studies have indicated that H5N8 pathogenicity in mice is relatively moderate compared with H5N1 pathogenicity. However, detailed mechanisms underlying avian influenza pathogenicity are still undetermined. We used a high-throughput RNA-seq method to analyse host and pathogen transcriptomes in the lungs of mice infected with A/MD/Korea/W452/2014 (H5N8) and A/EM/Korea/W149/2006 (H5N1) viruses. Sequenced numbers of viral transcripts and expression levels of host immune-related genes at 1 day post infection (dpi) were higher in H5N8-infected than H5N1-infected mice. Dual sequencing of viral transcripts revealed that in contrast to the observations at 1 dpi, higher number of H5N1 genes than H5N8 genes was sequenced at 3 and 7 dpi, which is consistent with higher viral titres and virulence observed in infected lungs in vivo. Ingenuity pathway analysis revealed a more significant upregulation of death receptor signalling, driven by H5N1 than with H5N8 infection at 3 and 7 dpi. Early induction of immune response-related genes may elicit protection in H5N8-infected mice, which correlates with moderate pathogenicity in vivo. Collectively, our data provide new insight into the underlying mechanisms of the differential pathogenicity of avian influenza viruses.
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Affiliation(s)
- Su-Jin Park
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju 361-763, Republic of Korea
| | - Mukesh Kumar
- Department of Tropical Medicine, Medical Microbiology and Pharmacology, Pacific Center for Emerging Infectious Diseases Research, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, 96822, USA
| | - Hyeok-il Kwon
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju 361-763, Republic of Korea
| | - Rak-Kyun Seong
- Department of Biomedical Sciences, College of Medicine, Korea University Guro Hospital, Seoul, 152-703, Republic of Korea
| | - Kyudong Han
- Department of Nanobiomedical Science, Dankook University, Cheonan, 330-714 Republic of Korea
| | - Jae-min Song
- Department of Global Medical Science, Sungshin Women's University, Seoul, 136-742 Republic of Korea
| | - Chul-Joong Kim
- College of Veterinary Medicine, Chungnam National University, Daejeon, 305-764 Republic of Korea
| | - Young-Ki Choi
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju 361-763, Republic of Korea
| | - Ok Sarah Shin
- Department of Biomedical Sciences, College of Medicine, Korea University Guro Hospital, Seoul, 152-703, Republic of Korea.,Department of Microbiology, College of Medicine, Korea University, Seoul, 136-701 Republic of Korea
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11
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Luczo JM, Stambas J, Durr PA, Michalski WP, Bingham J. Molecular pathogenesis of H5 highly pathogenic avian influenza: the role of the haemagglutinin cleavage site motif. Rev Med Virol 2015; 25:406-30. [PMID: 26467906 PMCID: PMC5057330 DOI: 10.1002/rmv.1846] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2014] [Revised: 06/09/2015] [Accepted: 06/11/2015] [Indexed: 11/22/2022]
Abstract
The emergence of H5N1 highly pathogenic avian influenza has caused a heavy socio‐economic burden through culling of poultry to minimise human and livestock infection. Although human infections with H5N1 have to date been limited, concerns for the pandemic potential of this zoonotic virus have been greatly intensified following experimental evidence of aerosol transmission of H5N1 viruses in a mammalian infection model. In this review, we discuss the dominance of the haemagglutinin cleavage site motif as a pathogenicity determinant, the host‐pathogen molecular interactions driving cleavage activation, reverse genetics manipulations and identification of residues key to haemagglutinin cleavage site functionality and the mechanisms of cell and tissue damage during H5N1 infection. We specifically focus on the disease in chickens, as it is in this species that high pathogenicity frequently evolves and from which transmission to the human population occurs. With >75% of emerging infectious diseases being of zoonotic origin, it is necessary to understand pathogenesis in the primary host to explain spillover events into the human population. © 2015 The Authors. Reviews in Medical Virology published by John Wiley & Sons Ltd.
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Affiliation(s)
- Jasmina M Luczo
- Australian Animal Health Laboratory, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Geelong, Victoria, Australia.,School of Medicine, Deakin University, Geelong, Victoria, Australia
| | - John Stambas
- School of Medicine, Deakin University, Geelong, Victoria, Australia
| | - Peter A Durr
- Australian Animal Health Laboratory, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Geelong, Victoria, Australia
| | - Wojtek P Michalski
- Australian Animal Health Laboratory, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Geelong, Victoria, Australia
| | - John Bingham
- Australian Animal Health Laboratory, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Geelong, Victoria, Australia
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12
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Menachery VD, Gralinski LE, Baric RS, Ferris MT. New Metrics for Evaluating Viral Respiratory Pathogenesis. PLoS One 2015; 10:e0131451. [PMID: 26115403 PMCID: PMC4482571 DOI: 10.1371/journal.pone.0131451] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 06/02/2015] [Indexed: 12/14/2022] Open
Abstract
Viral pathogenesis studies in mice have relied on markers of severe systemic disease, rather than clinically relevant measures, to evaluate respiratory virus infection; thus confounding connections to human disease. Here, whole-body plethysmography was used to directly measure changes in pulmonary function during two respiratory viral infections. This methodology closely tracked with traditional pathogenesis metrics, distinguished both virus- and dose-specific responses, and identified long-term respiratory changes following both SARS-CoV and Influenza A Virus infection. Together, the work highlights the utility of examining respiratory function following infection in order to fully understand viral pathogenesis.
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Affiliation(s)
- Vineet D. Menachery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Lisa E. Gralinski
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Ralph S. Baric
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
| | - Martin T. Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America
- * E-mail:
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13
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Shoemaker JE, Fukuyama S, Eisfeld AJ, Zhao D, Kawakami E, Sakabe S, Maemura T, Gorai T, Katsura H, Muramoto Y, Watanabe S, Watanabe T, Fuji K, Matsuoka Y, Kitano H, Kawaoka Y. An Ultrasensitive Mechanism Regulates Influenza Virus-Induced Inflammation. PLoS Pathog 2015; 11:e1004856. [PMID: 26046528 PMCID: PMC4457877 DOI: 10.1371/journal.ppat.1004856] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2014] [Accepted: 04/06/2015] [Indexed: 12/25/2022] Open
Abstract
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.
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Affiliation(s)
- Jason E. Shoemaker
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Satoshi Fukuyama
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Amie J. Eisfeld
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Dongming Zhao
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Eiryo Kawakami
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Laboratory for Disease Systems Modeling, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Saori Sakabe
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Department of Emerging Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan
| | - Tadashi Maemura
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Takeo Gorai
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Hiroaki Katsura
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Yukiko Muramoto
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Shinji Watanabe
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Laboratory of Veterinary Microbiology, Department of Veterinary Sciences, University of Miyazaki, Miyazaki, Japan
| | - Tokiko Watanabe
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Ken Fuji
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Yukiko Matsuoka
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- The Systems Biology Institute, Tokyo, Japan
| | - Hiroaki Kitano
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Laboratory for Disease Systems Modeling, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- The Systems Biology Institute, Tokyo, Japan
- Okinawa Institute of Science and Technology, Okinawa, Japan
| | - Yoshihiro Kawaoka
- ERATO Infection-induced Host Responses Project, Japan Science and Technology Agency, Saitama, Japan
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Department of Special Pathogens, International Research Center for Infectious Diseases, Institute of Medical Science, University of Tokyo, Tokyo, Japan
- * E-mail:
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14
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Aevermann BD, Pickett BE, Kumar S, Klem EB, Agnihothram S, Askovich PS, Bankhead A, Bolles M, Carter V, Chang J, Clauss TRW, Dash P, Diercks AH, Eisfeld AJ, Ellis A, Fan S, Ferris MT, Gralinski LE, Green RR, Gritsenko MA, Hatta M, Heegel RA, Jacobs JM, Jeng S, Josset L, Kaiser SM, Kelly S, Law GL, Li C, Li J, Long C, Luna ML, Matzke M, McDermott J, Menachery V, Metz TO, Mitchell H, Monroe ME, Navarro G, Neumann G, Podyminogin RL, Purvine SO, Rosenberger CM, Sanders CJ, Schepmoes AA, Shukla AK, Sims A, Sova P, Tam VC, Tchitchek N, Thomas PG, Tilton SC, Totura A, Wang J, Webb-Robertson BJ, Wen J, Weiss JM, Yang F, Yount B, Zhang Q, McWeeney S, Smith RD, Waters KM, Kawaoka Y, Baric R, Aderem A, Katze MG, Scheuermann RH. A comprehensive collection of systems biology data characterizing the host response to viral infection. Sci Data 2014; 1:140033. [PMID: 25977790 PMCID: PMC4410982 DOI: 10.1038/sdata.2014.33] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2014] [Accepted: 08/15/2014] [Indexed: 12/13/2022] Open
Abstract
The Systems Biology for Infectious Diseases Research program was established by
the U.S. National Institute of Allergy and Infectious Diseases to investigate
host-pathogen interactions at a systems level. This program generated 47
transcriptomic and proteomic datasets from 30 studies that investigate
in vivo and in vitro host responses to
viral infections. Human pathogens in the Orthomyxoviridae and
Coronaviridae families, especially pandemic H1N1 and avian
H5N1 influenza A viruses and severe acute respiratory syndrome coronavirus
(SARS-CoV), were investigated. Study validation was demonstrated via
experimental quality control measures and meta-analysis of independent
experiments performed under similar conditions. Primary assay results are
archived at the GEO and PeptideAtlas public repositories, while processed
statistical results together with standardized metadata are publically available
at the Influenza Research Database (www.fludb.org) and the Virus Pathogen
Resource (www.viprbrc.org). By comparing data from mutant versus wild-type
virus and host strains, RNA versus protein differential expression, and
infection with genetically similar strains, these data can be used to further
investigate genetic and physiological determinants of host responses to viral
infection.
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Affiliation(s)
| | | | - Sanjeev Kumar
- Northrop Grumman Information Systems, Health IT , Rockville, MD 20850, USA
| | - Edward B Klem
- Northrop Grumman Information Systems, Health IT , Rockville, MD 20850, USA
| | - Sudhakar Agnihothram
- Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599-7400, USA
| | | | - Armand Bankhead
- Oregon Clinical & Translational Research Institute , Portland, Oregon 97239-3098, USA ; Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University , Portland, Oregon 97239-3098, USA
| | - Meagen Bolles
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599-7290, USA
| | - Victoria Carter
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Jean Chang
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Therese R W Clauss
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Pradyot Dash
- Department of Immunology, St. Jude Children's Research Hospital , Memphis, TN 38105-3678, USA
| | - Alan H Diercks
- Seattle Biomedical Research Institute , Seattle, WA 98109, USA
| | - Amie J Eisfeld
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison , Madison, WI 53706, USA
| | - Amy Ellis
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison , Madison, WI 53706, USA
| | - Shufang Fan
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison , Madison, WI 53706, USA
| | - Martin T Ferris
- Department of Genetics, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599-7264, USA
| | - Lisa E Gralinski
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599-7290, USA
| | - Richard R Green
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Marina A Gritsenko
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Masato Hatta
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison , Madison, WI 53706, USA
| | - Robert A Heegel
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Jon M Jacobs
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Sophia Jeng
- Oregon Clinical & Translational Research Institute , Portland, Oregon 97239-3098, USA
| | - Laurence Josset
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Shari M Kaiser
- Seattle Biomedical Research Institute , Seattle, WA 98109, USA
| | - Sara Kelly
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - G Lynn Law
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Chengjun Li
- Division of Animal influenza, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences , Harbin, Heilongjiang Province 150001, China
| | - Jiangning Li
- Seattle Biomedical Research Institute , Seattle, WA 98109, USA
| | - Casey Long
- Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599-7400, USA
| | - Maria L Luna
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Melissa Matzke
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Jason McDermott
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Vineet Menachery
- Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599-7400, USA
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Hugh Mitchell
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Matthew E Monroe
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Garnet Navarro
- Seattle Biomedical Research Institute , Seattle, WA 98109, USA
| | - Gabriele Neumann
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison , Madison, WI 53706, USA
| | | | - Samuel O Purvine
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory , Richland, WA 99354, USA
| | | | - Catherine J Sanders
- Department of Immunology, St. Jude Children's Research Hospital , Memphis, TN 38105-3678, USA
| | - Athena A Schepmoes
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Anil K Shukla
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Amy Sims
- Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599-7400, USA
| | - Pavel Sova
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Vincent C Tam
- Seattle Biomedical Research Institute , Seattle, WA 98109, USA
| | - Nicolas Tchitchek
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital , Memphis, TN 38105-3678, USA
| | - Susan C Tilton
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Allison Totura
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599-7290, USA
| | - Jing Wang
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | | | - Ji Wen
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Jeffrey M Weiss
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA
| | - Feng Yang
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Boyd Yount
- Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599-7400, USA
| | - Qibin Zhang
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Shannon McWeeney
- Oregon Clinical & Translational Research Institute , Portland, Oregon 97239-3098, USA ; Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health Sciences University , Portland, Oregon 97239-3098, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Katrina M Waters
- Biological Sciences Division, Pacific Northwest National Laboratory , Richland, WA 99352, USA
| | - Yoshihiro Kawaoka
- School of Veterinary Medicine, Department of Pathobiological Sciences, Influenza Research Institute, University of Wisconsin-Madison , Madison, WI 53706, USA
| | - Ralph Baric
- Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC 27599-7400, USA ; Department of Microbiology and Immunology, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599-7290, USA
| | - Alan Aderem
- Seattle Biomedical Research Institute , Seattle, WA 98109, USA
| | - Michael G Katze
- Department of Microbiology, University of Washington , Seattle, WA 98195, USA ; Washington National Primate Research Center, University of Washington , Seattle, WA 98195, USA
| | - Richard H Scheuermann
- J. Craig Venter Institute , La Jolla, CA 92037, USA ; Department of Pathology, University of California , San Diego, CA 92093, USA
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15
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H7N9 and other pathogenic avian influenza viruses elicit a three-pronged transcriptomic signature that is reminiscent of 1918 influenza virus and is associated with lethal outcome in mice. J Virol 2014; 88:10556-68. [PMID: 24991006 DOI: 10.1128/jvi.00570-14] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
UNLABELLED Modulating the host response is a promising approach to treating influenza, caused by a virus whose pathogenesis is determined in part by the reaction it elicits within the host. Though the pathogenicity of emerging H7N9 influenza virus in several animal models has been reported, these studies have not included a detailed characterization of the host response following infection. Therefore, we characterized the transcriptomic response of BALB/c mice infected with H7N9 (A/Anhui/01/2013) virus and compared it to the responses induced by H5N1 (A/Vietnam/1203/2004), H7N7 (A/Netherlands/219/2003), and pandemic 2009 H1N1 (A/Mexico/4482/2009) influenza viruses. We found that responses to the H7 subtype viruses were intermediate to those elicited by H5N1 and pdm09H1N1 early in infection but that they evolved to resemble the H5N1 response as infection progressed. H5N1, H7N7, and H7N9 viruses were pathogenic in mice, and this pathogenicity correlated with increased transcription of cytokine response genes and decreased transcription of lipid metabolism and coagulation signaling genes. This three-pronged transcriptomic signature was observed in mice infected with pathogenic H1N1 strains such as the 1918 virus, indicating that it may be predictive of pathogenicity across multiple influenza virus strains. Finally, we used host transcriptomic profiling to computationally predict drugs that reverse the host response to H7N9 infection, and we identified six FDA-approved drugs that could potentially be repurposed to treat H7N9 and other pathogenic influenza viruses. IMPORTANCE Emerging avian influenza viruses are of global concern because the human population is immunologically naive to them. Current influenza drugs target viral molecules, but the high mutation rate of influenza viruses eventually leads to the development of antiviral resistance. As the host evolves far more slowly than the virus, and influenza pathogenesis is determined in part by the host response, targeting the host response is a promising approach to treating influenza. Here we characterize the host transcriptomic response to emerging H7N9 influenza virus and compare it with the responses to H7N7, H5N1, and pdm09H1N1. All three avian viruses were pathogenic in mice and elicited a transcriptomic signature that also occurs in response to the legendary 1918 influenza virus. Our work identifies host responses that could be targeted to treat severe H7N9 influenza and identifies six FDA-approved drugs that could potentially be repurposed as H7N9 influenza therapeutics.
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16
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Josset L, Tchitchek N, Gralinski LE, Ferris MT, Eisfeld AJ, Green RR, Thomas MJ, Tisoncik-Go J, Schroth GP, Kawaoka Y, Pardo-Manuel de Villena F, Baric RS, Heise MT, Peng X, Katze MG. 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. RNA Biol 2014; 11:875-90. [PMID: 24922324 PMCID: PMC4179962 DOI: 10.4161/rna.29442] [Citation(s) in RCA: 81] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2014] [Revised: 05/28/2014] [Accepted: 06/03/2014] [Indexed: 11/19/2022] Open
Abstract
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).
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Affiliation(s)
- Laurence Josset
- Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
| | - Nicolas Tchitchek
- Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
| | - Lisa E Gralinski
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
- Department of Epidemiology; University of North Carolina-Chapel Hill; Chapel Hill, NC USA
| | - Martin T Ferris
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
- Department of Genetics; University of North Carolina-Chapel Hill; Chapel Hill, NC USA
| | - Amie J Eisfeld
- Department of Pathobiological Sciences; Influenza Research Institute; University of Wisconsin-Madison; Madison, WI USA
| | - Richard R Green
- Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
| | - Matthew J Thomas
- Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
| | - Jennifer Tisoncik-Go
- Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
| | | | - Yoshihiro Kawaoka
- Department of Pathobiological Sciences; Influenza Research Institute; University of Wisconsin-Madison; Madison, WI USA
| | | | - Ralph S Baric
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
- Department of Epidemiology; University of North Carolina-Chapel Hill; Chapel Hill, NC USA
| | - Mark T Heise
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
- Department of Genetics; University of North Carolina-Chapel Hill; Chapel Hill, NC USA
| | - Xinxia Peng
- Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
| | - Michael G Katze
- Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA
- Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA
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17
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Systems biology and systems genetics - novel innovative approaches to study host-pathogen interactions during influenza infection. Curr Opin Virol 2014; 6:47-54. [PMID: 24769047 DOI: 10.1016/j.coviro.2014.03.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Revised: 03/04/2014] [Accepted: 03/14/2014] [Indexed: 11/19/2022]
Abstract
Influenza represents a serious threat to public health with thousands of deaths each year. A deeper understanding of the host-pathogen interactions is urgently needed to evaluate individual and population risks for severe influenza disease and to identify new therapeutic targets. Here, we review recent progress in large scale omics technologies, systems genetics as well as new mathematical and computational developments that are now in place to apply a systems biology approach for a comprehensive description of the multidimensional host response to influenza infection. In addition, we describe how results from experimental animal models can be translated to humans, and we discuss some of the future challenges ahead.
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18
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Josset L, Tisoncik-Go J, Katze MG. Moving H5N1 studies into the era of systems biology. Virus Res 2013; 178:151-67. [PMID: 23499671 PMCID: PMC3834220 DOI: 10.1016/j.virusres.2013.02.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2012] [Accepted: 02/24/2013] [Indexed: 12/20/2022]
Abstract
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.
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Affiliation(s)
- Laurence Josset
- Department of Microbiology, School of Medicine, University of Washington, Seattle, WA 98195, United States
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