skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


This content will become publicly available on July 1, 2025

Title: Influenza A viral burst size from thousands of infected single cells using droplet quantitative PCR (dqPCR)
An important aspect of how viruses spread and infect is the viral burst size, or the number of new viruses produced by each infected cell. Surprisingly, this value remains poorly characterized for influenza A virus (IAV), commonly known as the flu. In this study, we screened tens of thousands of cells using a microfluidic method called droplet quantitative PCR (dqPCR). The high-throughput capability of dqPCR enabled the measurement of a large population of infected cells producing progeny virus. By measuring the fully assembled and successfully released viruses from these infected cells, we discover that the viral burst sizes for both the seasonal H3N2 and the 2009 pandemic H1N1 strains vary significantly, with H3N2 ranging from 101to 104viruses per cell, and H1N1 ranging from 101to 103viruses per cell. Some infected cells produce average numbers of new viruses, while others generate extensive number of viruses. In fact, we find that only 10% of the single-cell infections are responsible for creating a significant portion of all the viruses. This small fraction produced approximately 60% of new viruses for H3N2 and 40% for H1N1. On average, each infected cell of the H3N2 flu strain produced 709 new viruses, whereas for H1N1, each infected cell produced 358 viruses. This novel method reveals insights into the flu virus and can lead to improved strategies for managing and preventing the spread of viruses.  more » « less
Award ID(s):
2328766 1753352
PAR ID:
10539976
Author(s) / Creator(s):
; ; ; ; ; ; ;
Editor(s):
Lowen, Anice C
Publisher / Repository:
PLOS Journals
Date Published:
Journal Name:
PLOS Pathogens
Volume:
20
Issue:
7
ISSN:
1553-7374
Page Range / eLocation ID:
e1012257
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, PLOS Computational Biology)
    Kosakovsky Pond, Sergei L. (Ed.)
    Respiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestations at the cell and tissue levels is vital to understanding the mechanisms of immunopathology and to developing strain-independent treatments. Here, we present a novel spatialized multicellular computational model of RNA virus infection and the type-I interferon-mediated antiviral response that it induces within lung epithelial cells. The model is built using the CompuCell3D multicellular simulation environment and is parameterized using data from influenza virus-infected cell cultures. Consistent with experimental observations, it exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. The model suggests that modifying the activity of signaling molecules in the JAK/STAT pathway or altering the ratio of the diffusion lengths of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of plaque growth arrest on diffusion lengths highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro measurement of these diffusion coefficients. Sensitivity analyses under conditions leading to continuous or arrested plaque growth found that plaque growth is more sensitive to variations of most parameters and more likely to have identifiable model parameters when conditions lead to plaque arrest. This result suggests that cytokine assay measurements may be most informative under conditions leading to arrested plaque growth. The model is easy to extend to include SARS-CoV-2-specific mechanisms or to use as a component in models linking epithelial cell signaling to systemic immune models. 
    more » « less
  2. ; (, Integrative Biology)
    null (Ed.)
    Abstract Although viruses in their natural habitats add up to less than 10% of the biomass, they contribute more than 90% of the genome sequences [1]. These viral sequences or ‘viromes’ encode viruses that populate the Earth’s oceans [2, 3] and terrestrial environments [4, 5], where their infections impact life across diverse ecological niches and scales [6, 7], including humans [8–10]. Most viruses have yet to be isolated and cultured [11–13], and surprisingly few efforts have explored what analysis of available data might reveal about their nature. Here, we compiled and analyzed seven decades of one-step growth and other data for viruses from six major families, including their infections of archaeal, bacterial and eukaryotic hosts [14–191]. We found that the use of host cell biomass for virus production was highest for archaea at 10%, followed by bacteria at 1% and eukarya at 0.01%, highlighting the degree to which viruses of archaea and bacteria exploit their host cells. For individual host cells, the yield of virus progeny spanned a relatively narrow range (10–1000 infectious particles per cell) compared with the million-fold difference in size between the smallest and largest cells. Furthermore, healthy and infected host cells were remarkably similar in the time they needed to multiply themselves or their virus progeny. Specifically, the doubling time of healthy cells and the delay time for virus release from infected cells were not only correlated (r = 0.71, p < 10−10, n = 101); they also spanned the same range from tens of minutes to about a week. These results have implications for better understanding the growth, spread and persistence of viruses in complex natural habitats that abound with diverse hosts, including humans and their associated microbes. 
    more » « less
  3. ; ; ; (, Microbiology Spectrum)
    Kolawole, Abimbola O. (Ed.)
    ABSTRACT Drop-based microfluidics has revolutionized single-cell studies and can be applied toward analyzing tens of thousands to millions of single cells and their products contained within picoliter-sized drops. Drop-based microfluidics can shed insight into single-cell virology, enabling higher-resolution analysis of cellular and viral heterogeneity during viral infection. In this work, individual A549, MDCK, and siat7e cells were infected with influenza A virus (IAV) and encapsulated into 100-μm-size drops. Initial studies of uninfected cells encapsulated in drops demonstrated high cell viability and drop stability. Cell viability of uninfected cells in the drops remained above 75%, and the average drop radii changed by less than 3% following cell encapsulation and incubation over 24 h. Infection parameters were analyzed over 24 h from individually infected cells in drops. The number of IAV viral genomes and infectious viruses released from A549 and MDCK cells in drops was not significantly different from bulk infection as measured by reverse transcriptase quantitative PCR (RT-qPCR) and plaque assay. The application of drop-based microfluidics in this work expands the capacity to propagate IAV viruses and perform high-throughput analyses of individually infected cells. IMPORTANCE Drop-based microfluidics is a cutting-edge tool in single-cell research. Here, we used drop-based microfluidics to encapsulate thousands of individual cells infected with influenza A virus within picoliter-sized drops. Drop stability, cell loading, and cell viability were quantified from three different cell lines that support influenza A virus propagation. Similar levels of viral progeny as determined by RT-qPCR and plaque assay were observed from encapsulated cells in drops compared to bulk culture. This approach enables the ability to propagate influenza A virus from encapsulated cells, allowing for future high-throughput analysis of single host cell interactions in isolated microenvironments over the course of the viral life cycle. 
    more » « less
  4. ; ; ; ; (, Biomedical Optics Express)
    Early virus identification is a key component of both patient treatment and epidemiological monitoring. In the case of influenza A virus infections, where the detection of subtypes associated with bird flu in humans could lead to a pandemic, rapid subtype-level identification is important. Surface-enhanced Raman spectroscopy coupled with machine learning can be used to rapidly detect and identify viruses in a label-free manner. As there is a range of available excitation wavelengths for performing Raman spectroscopy, we must choose the best one to permit discrimination between highly similar subtypes of a virus. We show that the spectra produced by influenza A subtypes H1N1 and H3N2 exhibit a higher degree of dissimilarity when using 785 nm excitation wavelength in comparison with 532 nm excitation wavelength. Furthermore, the cross-validated area under the curve (AUC) for identification was higher for the 785 nm excitation, reaching 0.95 as compared to 0.86 for 532 nm. Ultimately, this study suggests that exciting with a 785 nm wavelength is better able to differentiate two closely related influenza viruses and likely can extend to other closely related pathogens. 
    more » « less
  5. ; ; ; ; ; ; (, PLOS Pathogens)
    Pagán, Israel (Ed.)
    Viruses with single-stranded, positive-sense (+) RNA genomes incur high numbers of errors during replication, thereby creating diversified genome populations from which new, better adapted viral variants can emerge. However, a definitive error rate is known for a relatively few (+) RNA plant viruses, due to challenges to account for perturbations caused by natural selection and/or experimental set-ups. To address these challenges, we developed a new approach that exclusively profiled errors in the (-)-strand replication intermediates of turnip crinkle virus (TCV), in singly infected cells. A series of controls and safeguards were devised to ensure errors inherent to the experimental process were accounted for. This approach permitted the estimation of a TCV error rate of 8.47 X 10−5substitution per nucleotide site per cell infection. Importantly, the characteristic error distribution pattern among the 50 copies of 2,363-base-pair cDNA fragments predicted that nearly all TCV (-) strands were products of one replication cycle per cell. Furthermore, some of the errors probably elevated error frequencies by lowering the fidelity of TCV RNA-dependent RNA polymerase, and/or permitting occasional re-replication of progeny genomes. In summary, by profiling errors in TCV (-)-strand intermediates incurred during replication in single cells, this study provided strong support for a stamping machine mode of replication employed by a (+) RNA virus. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email