A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America
Open accessAbstract
Although metagenomics has been previously employed for pathogen discovery, its cost and complexity have prevented its use as a practical front-line diagnostic for unknown infectious diseases. Here we demonstrate the utility of two metagenomics-based strategies, a pan-viral microarray (Virochip) and deep sequencing, for the identification and characterization of 2009 pandemic H1N1 influenza A virus. Using nasopharyngeal swabs collected during the earliest stages of the pandemic in Mexico, Canada, and the United States (n = 17), the Virochip was able to detect a novel virus most closely related to swine influenza viruses without a priori information. Deep sequencing yielded reads corresponding to 2009 H1N1 influenza in each sample (percentage of aligned sequences corresponding to 2009 H1N1 ranging from 0.0011% to 10.9%), with up to 97% coverage of the influenza genome in one sample. Detection of 2009 H1N1 by deep sequencing was possible even at titers near the limits of detection for specific RT-PCR, and the percentage of sequence reads was linearly correlated with virus titer. Deep sequencing also provided insights into the upper respiratory microbiota and host gene expression in response to 2009 H1N1 infection. An unbiased analysis combining sequence data from all 17 outbreak samples revealed that 90% of the 2009 H1N1 genome could be assembled de novo without the use of any reference sequence, including assembly of several near full-length genomic segments. These results indicate that a streamlined metagenomics detection strategy can potentially replace the multiple conventional diagnostic tests required to investigate an outbreak of a novel pathogen, and provide a blueprint for comprehensive diagnosis of unexplained acute illnesses or outbreaks in clinical and public health settings.
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These studies demonstrated that there was considerable inter-subject variability, highlighting the need for longitudinal studies to decipher changes following viral infection.
“However, these studies demonstrated that there was considerable inter-subject variability, highlighting the need for longitudinal studies to decipher changes following viral infection.”
From Respiratory viral infection-induced microbiome alterations and secondary bacterial pneumonia. (2018) · cites this paper as [110]
Another group found that Moraxella and Enterobacter spp. (which are classified as Proteobacteria) were the most highly represented bacteria in nasopharyngeal samples obtained from patients with pandemic H1N1 influenza.
“These findings are supported by another group who found that Moraxella and Enterobacter spp. (which are classified as Proteobacteria) were the most highly represented bacteria in nasopharyngeal samples obtained from patients with pandemic H1N1 influenza (110).”
From Respiratory viral infection-induced microbiome alterations and secondary bacterial pneumonia. (2018) · cites this paper as [110]
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- Authors
- Greninger, A. L., Chen, E. C., Sittler, T., Scheinerman, A., Roubinian, N., Yu, G., Kim, E., Pillai, D. R., Guyard, C., Mazzulli, T., Isa, P., Arias, C. F., Hackett, J., Schochetman, G., Miller, S., Tang, P., & Chiu, C. Y.
- Affiliations
- University of California, San Francisco (US)
- University of British Columbia (CA)
- University of Toronto (CA)
- Mount Sinai Hospital (CA)
- Universidad Nacional Autónoma de México (MX)
- Corresponding author
- Chiu, Charles Y.
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-10-18
- Volume
- 5
- Issue
- 10
- Pages
- e13381
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC2956640
- OpenAlex
- W2078626331
- Cited by
- 193
- References
- 54
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 8 · 2023: 6 · 2022: 5 · 2021: 9 · 2020: 7 · 2019: 12 · 2018: 15 · 2017: 16 · 2016: 11 · 2015: 16 · 2014: 19 · 2013: 27 · 2012: 23
- FWCI
- 14.43
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Greater South Information System
- Funders
- Kleine-Levin Syndrome Foundation
- California Department of Public Health
- Amazon Web Services
- National Institutes of Health
- University of California, San Francisco
- Abbott Diagnostics
- National Institute of General Medical Sciences (T32GM007618)
- National Institute of Allergy and Infectious Diseases (K08AI074913)
- Topics
- Health Sciences › Medicine › Epidemiology › Influenza Virus Research Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Health Sciences › Medicine › Epidemiology › Respiratory viral infections research
- Keywords
- 2009 H1N1 influenza A virus, pandemic influenza, metagenomics, deep sequencing, swine influenza virus, host gene expression, de novo genome assembly, viral titer, outbreak diagnosis, North America
- MeSH terms
- Humans, Influenza, Human, North America, Polymorphism, Single Nucleotide, Gene Expression Profiling, Genomics, Influenza A Virus, H1N1 Subtype
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