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Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism
BACKGROUND: Comparative 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 transcri...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4536893/ https://www.ncbi.nlm.nih.gov/pubmed/26272204 http://dx.doi.org/10.1186/s12865-015-0107-y |
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author | Thakar, Juilee Hartmann, Boris M. Marjanovic, Nada Sealfon, Stuart C. Kleinstein, Steven H. |
author_facet | Thakar, Juilee Hartmann, Boris M. Marjanovic, Nada Sealfon, Stuart C. Kleinstein, Steven H. |
author_sort | Thakar, Juilee |
collection | PubMed |
description | BACKGROUND: Comparative 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. RESULTS: Existing 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. CONCLUSIONS: Comparative 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12865-015-0107-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4536893 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45368932015-08-15 Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism Thakar, Juilee Hartmann, Boris M. Marjanovic, Nada Sealfon, Stuart C. Kleinstein, Steven H. BMC Immunol Research Article BACKGROUND: Comparative 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. RESULTS: Existing 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. CONCLUSIONS: Comparative 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12865-015-0107-y) contains supplementary material, which is available to authorized users. BioMed Central 2015-08-14 /pmc/articles/PMC4536893/ /pubmed/26272204 http://dx.doi.org/10.1186/s12865-015-0107-y Text en © Thakar et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Thakar, Juilee Hartmann, Boris M. Marjanovic, Nada Sealfon, Stuart C. Kleinstein, Steven H. Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism |
title | Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism |
title_full | Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism |
title_fullStr | Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism |
title_full_unstemmed | Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism |
title_short | Comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism |
title_sort | comparative analysis of anti-viral transcriptomics reveals novel effects of influenza immune antagonism |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4536893/ https://www.ncbi.nlm.nih.gov/pubmed/26272204 http://dx.doi.org/10.1186/s12865-015-0107-y |
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