ArticleBMC immunology2015
Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism.
Article in BMC immunology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Beyond the abscess:Frontiers in cellular and infection microbiology · 2025Article
- Review
- A systems genomics approach uncovers molecular associates of RSV severity.PLoS computational biology · 2021Article
- Molecular characterization of atherosclerosis in HIV positive persons.Scientific reports · 2021Article
- Unbiased analysis of peripheral blood mononuclear cells reveals CD4 T cell response to RSV matrix protein.Vaccine: X · 2020Article
- Innate Immune Response to Influenza Virus at Single-Cell Resolution in Human Epithelial Cells Revealed Paracrine Induction of Interferon Lambda 1.Journal of virology · 2019Article
- Executable pathway analysis using ensemble discrete-state modeling for large-scale data.PLoS computational biology · 2019Article
- A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection.Statistical methods in medical research · 2018Article
- Common microRNA⁻mRNA Interactions in Different Newcastle Disease Virus-Infected Chicken Embryonic Visceral Tissues.International journal of molecular sciences · 2018Article
- Association of Dynamic Changes in the CD4 T-Cell Transcriptome With Disease Severity During Primary Respiratory Syncytial Virus Infection in Young Infants.The Journal of infectious diseases · 2017Article
- Frontline Science: c-Myc regulates P-selectin glycoprotein ligand-1 expression in monocytes during HIV-1 infection.Journal of leukocyte biology · 2017Article
- Meta-analysis of cell- specific transcriptomic data using fuzzy c-means clustering discovers versatile viral responsive genes.BMC bioinformatics · 2017Article
- Detection of Serum microRNAs From Department of Defense Serum Repository: Correlation With Cotinine, Cytokine, and Polycyclic Aromatic Hydrocarbon Levels.Journal of occupational and environmental medicine · 2016Article
- MicroRNAs as Novel Biomarkers of Deployment Status and Exposure to Polychlorinated Dibenzo-p-Dioxins/Dibenzofurans.Journal of occupational and environmental medicine · 2016Article
- Boolean Modeling of Cellular and Molecular Pathways Involved in Influenza Infection.Computational and mathematical methods in medicine · 2016Article
- Human Dendritic Cell Response Signatures Distinguish 1918, Pandemic, and Seasonal H1N1 Influenza Viruses.Journal of virology · 2015Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundComparative analysis of genome-wide expression profiles are increasingly being used to study virus-specific host interactions. In order to gain mechanistic insights, gene expression profiles can be combined with information on DNA-binding sites of transcription factors to detect transcription factor activity (by analysis of target gene sets) during viral infections. Here, we apply this approach to study mechanisms of immune antagonism elicited by Influenza A virus (New Caledonia/20/1999) by comparing the transcriptional response with the non-pathogenic Newcastle disease virus (NDV), which lacks human immune antagonism.
resultsExisting gene set approaches do not quantify activity in a way that can be statistically compared between responses. We thus developed a new method for Bayesian Estimation of Transcription factor Activity (BETA) that allows for such quantification and comparative analysis across multiple responses. BETA predicted decreased ISGF3 activity during influenza A infection of human dendritic cells (reflected in lower expression of Interferon Stimulated Genes, ISGs). This prediction was confirmed through a combination of mathematical modeling and experiments at different multiplicities of infection to show that ISGs were specifically blocked in infected cells. Suppression of the transcription factor SATB1 was also predicted as a novel effect of influenza-mediated immune antagonism, and validated experimentally.
conclusionsComparative analysis of genome-wide transcriptional profiles can reveal new effects of viral immune antagonism. We have developed a computational framework (BETA) that enables quantitative comparative analysis of transcription factor activities. This method will aid future studies to identify mechanistic differences in the host-pathogen interactions. Application of BETA to genome-wide transcriptional profiling data from human DCs identified SATB1 as a novel effect of influenza antagonism.
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