The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Pathogenic Influenza Viruses and Coronaviruses Utilize Similar and Contrasting Approaches To Control Interferon-Stimulated Gene Responses
Open accessAbstract
The broad range and diversity of interferon-stimulated genes (ISGs) function to induce an antiviral state within the host, impeding viral pathogenesis. While successful respiratory viruses overcome individual ISG effectors, analysis of the global ISG response and subsequent viral antagonism has yet to be examined. Employing models of the human airway, transcriptomics and proteomics datasets were used to compare ISG response patterns following highly pathogenic H5N1 avian influenza (HPAI) A virus, 2009 pandemic H1N1, severe acute respiratory syndrome coronavirus (SARS-CoV), and Middle East respiratory syndrome CoV (MERS-CoV) infection. The results illustrated distinct approaches utilized by each virus to antagonize the global ISG response. In addition, the data revealed that highly virulent HPAI virus and MERS-CoV induce repressive histone modifications, which downregulate expression of ISG subsets. Notably, influenza A virus NS1 appears to play a central role in this histone-mediated downregulation in highly pathogenic influenza strains. Together, the work demonstrates the existence of unique and common viral strategies for controlling the global ISG response and provides a novel avenue for viral antagonism via altered histone modifications. IMPORTANCE This work combines systems biology and experimental validation to identify and confirm strategies used by viruses to control the immune response. Using a novel screening approach, specific comparison between highly pathogenic influenza viruses and coronaviruses revealed similarities and differences in strategies to control the interferon and innate immune response. These findings were subsequently confirmed and explored, revealing both a common pathway of antagonism via type I interferon (IFN) delay as well as a novel avenue for control by altered histone modification. Together, the data highlight how comparative systems biology analysis can be combined with experimental validation to derive novel insights into viral pathogenesis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Chromatin modifications and their function
Kouzarides, T. (2007) · Cell · doi:10.1016/j.cell.2007.02.005 · Cited by 10,883
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845
Linking DNA methylation and histone modification: patterns and paradigms
Cedar, H., & Bergman, Y. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2540 · Cited by 2,267 · cited 1×
“While histone modification has been shown to play a role in a variety of host processes, including cell development (37), host metabolism (38), and ISG induction (36), these findings represent additional evidence that pathogens can exploit the same repression processes to modulate and control the host IFN response (39…”
BackgroundViruses and interferon: a fight for supremacy
Katze, M. G., He, Y., & Gale, M. (2002) · Nature Reviews Immunology · doi:10.1038/nri888 · Cited by 1,419
Self-citationGeneration of influenza A viruses entirely from cloned cDNAs
Neumann, G., Watanabe, T., Ito, H., Watanabe, S., Goto, H., Gao, P., Hughes, M., Perez, D. R., Donis, R., Hoffmann, E., et al. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.16.9345 · Cited by 1,278
Self-citationThe multifunctional NS1 protein of influenza A viruses
Hale, B. G., Randall, R. E., Ortín, J., & Jackson, D. (2008) · Journal of General Virology · doi:10.1099/vir.0.2008/004606-0 · Cited by 1,079
Influence of Metabolism on Epigenetics and Disease
Kaelin, W. G., & McKnight, S. L. (2013) · Cell · doi:10.1016/j.cell.2013.03.004 · Cited by 920
van Boheemen, S., de Graaf, M., Lauber, C., Bestebroer, T. M., Raj, V. S., Zaki, A. M., Osterhaus, A. D. M. E., Haagmans, B. L., Gorbalenya, A. E., Snijder, E. J., et al. (2012) · mBio · doi:10.1128/mbio.00473-12 · Cited by 914
Erasing the methyl mark: histone demethylases at the center of cellular differentiation and disease
Cloos, P. A. C., Christensen, J., Agger, K., & Helin, K. (2008) · Genes & Development · doi:10.1101/gad.1652908 · Cited by 669
Control of Inducible Gene Expression by Signal-Dependent Transcriptional Elongation
Hargreaves, D. C., Horng, T., & Medzhitov, R. (2009) · Cell · doi:10.1016/j.cell.2009.05.047 · Cited by 644
Cited by
Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19
Blanco-Melo, D., Nilsson-Payant, B. E., Liu, W.-C., Uhl, S., Hoagland, D., Møller, R., Jordan, T. X., Oishi, K., Panis, M., Sachs, D., et al. (2020) · Cell · doi:10.1016/j.cell.2020.04.026 · Cited by 4,222
SARS and MERS: recent insights into emerging coronaviruses
de Wit, E., van Doremalen, N., Falzarano, D., & Munster, V. J. (2016) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2016.81 · Cited by 3,510
SARS-CoV-2 Reverse Genetics Reveals a Variable Infection Gradient in the Respiratory Tract
Hou, Y. J., Okuda, K., Edwards, C. E., Martinez, D. R., Asakura, T., Dinnon, K. H., Kato, T., Lee, R. E., Yount, B. L., Mascenik, T. M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.042 · Cited by 1,488
Self-citationWhy does COVID-19 disproportionately affect older people?
Mueller, A. L., McNamara, M. S., & Sinclair, D. A. (2020) · Aging · doi:10.18632/aging.103344 · Cited by 1,128
Cytokine Storm in COVID-19: The Current Evidence and Treatment Strategies
Tang, Y., Liu, J., Zhang, D., Xu, Z., Ji, J., & Wen, C. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.01708 · Cited by 1,094
Metadata
- Authors
- Menachery, V. D., Eisfeld, A. J., Schäfer, A., Josset, L., Sims, A. C., Proll, S., Fan, S., Li, C., Neumann, G., Tilton, S. C., Chang, J., Gralinski, L. E., Long, C., Green, R., Williams, C. M., Weiss, J., Matzke, M. M., Webb-Robertson, B.-J., Schepmoes, A. A., Shukla, A. K., Metz, T. O., Smith, R. D., Waters, K. M., Katze, M. G., Kawaoka, Y., & Baric, R. S.
- Venue
- mBio
- Publisher
- American Society for Microbiology
- Published
- 2014-07
- Volume
- 5
- Issue
- 3
- Pages
- e01174-14
- ISSN
- 2150-7511 (ISSN-L)
- 2161-2129
- OpenAlex
- W2103208261
- Cited by
- 305
- References
- 53
- FWCI
- 5.71
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Pathogenic Influenza Viruses and Coronaviruses Utilize Similar and Contrasting Approaches To Control Interferon-Stimulated Gene Responses. https://app.cochat.ai/papers/10.1128/mbio.01174-14
- The paper
- Menachery, V. D., Eisfeld, A. J., Schäfer, A., Josset, L., Sims, A. C., Proll, S., Fan, S., Li, C., Neumann, G., Tilton, S. C., Chang, J., Gralinski, L. E., Long, C., Green, R., Williams, C. M., Weiss, J., Matzke, M. M., Webb-Robertson, B.-J., Schepmoes, A. A., . . . Baric, R. S. (2014). Pathogenic Influenza Viruses and Coronaviruses Utilize Similar and Contrasting Approaches To Control Interferon-Stimulated Gene Responses. mBio. https://doi.org/10.1128/mbio.01174-14
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.