1
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Adams SK, Ducharme GE, Loveday EK. All the single cells: if you like it then you should put some virus on it. J Virol 2024:e0127323. [PMID: 38904395 DOI: 10.1128/jvi.01273-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2024] Open
Abstract
Across a rich 70-year history, single-cell virology has revealed the impact of host and pathogen heterogeneity during virus infections. Recent technological innovations have enabled higher-resolution analyses of cellular and viral heterogeneity. Furthermore, single-cell analysis has revealed extreme phenotypes and provided additional insights into host-pathogen dynamics. Using a single-cell approach to explore fundamental virology questions, contemporary researchers have contributed to a revival of interest in single-cell virology with increased insights and enthusiasm.
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Affiliation(s)
- Sophia K Adams
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana, USA
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA
| | - Grace E Ducharme
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA
- Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana, USA
| | - Emma K Loveday
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA
- Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana, USA
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2
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Zinnecker T, Badri N, Araujo D, Thiele K, Reichl U, Genzel Y. From single-cell cloning to high-yield influenza virus production - implementing advanced technologies in vaccine process development. Eng Life Sci 2024; 24:2300245. [PMID: 38584687 PMCID: PMC10991716 DOI: 10.1002/elsc.202300245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 01/16/2024] [Accepted: 02/05/2024] [Indexed: 04/09/2024] Open
Abstract
Innovations in viral vaccine manufacturing are crucial for pandemic preparedness and to meet ever-rising global demands. For influenza, however, production still mainly relies on technologies established decades ago. Although modern production shifts from egg-based towards cell culture technologies, the full potential has not yet been fully exploited. Here, we evaluate whether implementation of state-of-the-art technologies for cell culture-based recombinant protein production are capable to challenge outdated approaches in viral vaccine process development. For this, a fully automated single-cell cloning strategy was established to generate monoclonal suspension Madin-Darby canine kidney (MDCK) cells. Among selected cell clones, we could observe distinct metabolic and growth characteristics, with C59 reaching a maximum viable cell concentration of 17.3 × 106 cells/mL and low doubling times in batch mode. Screening for virus production using a panel of human vaccine-relevant influenza A and B viruses in an ambr15 system revealed high titers with yields competing or even outperforming available MDCK cell lines. With C113, we achieved cell-specific virus yields of up to 25,000 virions/cell, making this cell clone highly attractive for vaccine production. Finally, we confirmed process performance at a 50-fold higher working volume. In summary, we present a scalable and powerful approach for accelerated development of high-yield influenza virus production in chemically defined medium starting from a single cell.
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Affiliation(s)
- Tilia Zinnecker
- Max Planck Institute for Dynamics of Complex Technical SystemsMagdeburgGermany
| | | | - Diogo Araujo
- Sartorius Stedim Biotech S.A.Aubagne CedexFrance
| | | | - Udo Reichl
- Max Planck Institute for Dynamics of Complex Technical SystemsMagdeburgGermany
- Bioprocess EngineeringOtto‐von‐Guericke UniversityMagdeburgGermany
| | - Yvonne Genzel
- Max Planck Institute for Dynamics of Complex Technical SystemsMagdeburgGermany
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3
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Fredrikson JP, Domanico LF, Pratt SL, Loveday EK, Taylor MP, Chang CB. Single-cell herpes simplex virus type 1 infection of neurons using drop-based microfluidics reveals heterogeneous replication kinetics. SCIENCE ADVANCES 2024; 10:eadk9185. [PMID: 38416818 PMCID: PMC10901367 DOI: 10.1126/sciadv.adk9185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 01/25/2024] [Indexed: 03/01/2024]
Abstract
Single-cell analyses of viral infections reveal heterogeneity that is not detected by traditional population-level studies. This study applies drop-based microfluidics to investigate the dynamics of herpes simplex virus type 1 (HSV-1) infection of neurons at the single-cell level. We used micrometer-scale Matrigel beads, termed microgels, to culture individual murine superior cervical ganglia (SCG) neurons or epithelial cells. Microgel-cultured cells are encapsulated in individual media-in-oil droplets with a dual-fluorescent reporter HSV-1, enabling real-time observation of viral gene expression and replication. Infection within drops revealed that the kinetics of initial viral gene expression and replication were dependent on the inoculating dose. Notably, increasing inoculating doses led to earlier onset of viral gene expression and more frequent productive viral replication. These observations provide crucial insights into the complexity of HSV-1 infection in neurons and emphasize the importance of studying single-cell outcomes of viral infection. These techniques for cell culture and infection in drops provide a foundation for future virology and neurobiology investigations.
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Affiliation(s)
- Jacob P. Fredrikson
- Department of Chemical and Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
| | - Luke F. Domanico
- Department of Microbiology and Cell Biology, Montana State University, P.O. Box 173520, Bozeman, MT 59717, USA
| | - Shawna L. Pratt
- Department of Chemical and Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
| | - Emma K. Loveday
- Department of Chemical and Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
| | - Matthew P. Taylor
- Department of Microbiology and Cell Biology, Montana State University, P.O. Box 173520, Bozeman, MT 59717, USA
| | - Connie B. Chang
- Department of Chemical and Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, USA
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4
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Quirouette C, Cresta D, Li J, Wilkie KP, Liang H, Beauchemin CAA. The effect of random virus failure following cell entry on infection outcome and the success of antiviral therapy. Sci Rep 2023; 13:17243. [PMID: 37821517 PMCID: PMC10567758 DOI: 10.1038/s41598-023-44180-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 10/04/2023] [Indexed: 10/13/2023] Open
Abstract
A virus infection can be initiated with very few or even a single infectious virion, and as such can become extinct, i.e. stochastically fail to take hold or spread significantly. There are many ways that a fully competent infectious virion, having successfully entered a cell, can fail to cause a productive infection, i.e. one that yields infectious virus progeny. Though many stochastic models (SMs) have been developed and used to estimate a virus infection's establishment probability, these typically neglect infection failure post virus entry. The SM presented herein introduces parameter [Formula: see text] which corresponds to the probability that a virion's entry into a cell will result in a productive cell infection. We derive an expression for the likelihood of infection establishment in this new SM, and find that prophylactic therapy with an antiviral reducing [Formula: see text] is at least as good or better at decreasing the establishment probability, compared to antivirals reducing the rates of virus production or virus entry into cells, irrespective of the SM parameters. We investigate the difference in the fraction of cells consumed by so-called extinct versus established virus infections, and find that this distinction becomes biologically meaningless as the probability of establishment approaches zero. We explain why the release of virions continuously over an infectious cell's lifespan, rather than as a single burst at the end of the cell's lifespan, does not result in an increased risk of infection extinction. We show, instead, that the number of virus released, not the timing of the release, affects infection establishment and associated critical antiviral efficacy.
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Affiliation(s)
| | - Daniel Cresta
- Department of Physics, Toronto Metropolitan University, Toronto, Canada
| | - Jizhou Li
- Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS), RIKEN, Wako, Japan
| | - Kathleen P Wilkie
- Department of Mathematics, Toronto Metropolitan University, Toronto, Canada
| | - Haozhao Liang
- Nishina Center for Accelerator-Based Science (RNC), RIKEN, Wako, Japan
- Department of Physics, University of Tokyo, Tokyo, Japan
| | - Catherine A A Beauchemin
- Department of Physics, Toronto Metropolitan University, Toronto, Canada.
- Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS), RIKEN, Wako, Japan.
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5
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Eberhardt N, Noval MG, Kaur R, Amadori L, Gildea M, Sajja S, Das D, Cilhoroz B, Stewart O, Fernandez DM, Shamailova R, Guillen AV, Jangra S, Schotsaert M, Newman JD, Faries P, Maldonado T, Rockman C, Rapkiewicz A, Stapleford KA, Narula N, Moore KJ, Giannarelli C. SARS-CoV-2 infection triggers pro-atherogenic inflammatory responses in human coronary vessels. NATURE CARDIOVASCULAR RESEARCH 2023; 2:899-916. [PMID: 38076343 PMCID: PMC10702930 DOI: 10.1038/s44161-023-00336-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 08/23/2023] [Indexed: 12/19/2023]
Abstract
Patients with coronavirus disease 2019 (COVID-19) present increased risk for ischemic cardiovascular complications up to 1 year after infection. Although the systemic inflammatory response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection likely contributes to this increased cardiovascular risk, whether SARS-CoV-2 directly infects the coronary vasculature and attendant atherosclerotic plaques remains unknown. Here we report that SARS-CoV-2 viral RNA is detectable and replicates in coronary lesions taken at autopsy from severe COVID-19 cases. SARS-CoV-2 targeted plaque macrophages and exhibited a stronger tropism for arterial lesions than adjacent perivascular fat, correlating with macrophage infiltration levels. SARS-CoV-2 entry was increased in cholesterol-loaded primary macrophages and dependent, in part, on neuropilin-1. SARS-CoV-2 induced a robust inflammatory response in cultured macrophages and human atherosclerotic vascular explants with secretion of cytokines known to trigger cardiovascular events. Our data establish that SARS-CoV-2 infects coronary vessels, inducing plaque inflammation that could trigger acute cardiovascular complications and increase the long-term cardiovascular risk.
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Affiliation(s)
- Natalia Eberhardt
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Maria Gabriela Noval
- Department of Microbiology, New York University School of Medicine, New York, NY, USA
| | - Ravneet Kaur
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Letizia Amadori
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Michael Gildea
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Swathy Sajja
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Dayasagar Das
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Burak Cilhoroz
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - O’Jay Stewart
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dawn M. Fernandez
- Department of Medicine, Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Roza Shamailova
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Andrea Vasquez Guillen
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Sonia Jangra
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael Schotsaert
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jonathan D. Newman
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Peter Faries
- Department of Surgery, Vascular Division, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Maldonado
- Department of Surgery, Vascular Division, New York University Langone Health, New York, NY, USA
| | - Caron Rockman
- Department of Surgery, Vascular Division, New York University Langone Health, New York, NY, USA
| | - Amy Rapkiewicz
- Department of Pathology, NYU Winthrop Hospital, Long Island School of Medicine, New York, NY, USA
| | - Kenneth A. Stapleford
- Department of Microbiology, New York University School of Medicine, New York, NY, USA
| | - Navneet Narula
- Department of Pathology, New York University School of Medicine, New York, NY, USA
| | - Kathryn J. Moore
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
| | - Chiara Giannarelli
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
- Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pathology, New York University School of Medicine, New York, NY, USA
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6
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Liang Q, Yang J, Fan WTL, Lo WC. Patch formation driven by stochastic effects of interaction between viruses and defective interfering particles. PLoS Comput Biol 2023; 19:e1011513. [PMID: 37782667 PMCID: PMC10569632 DOI: 10.1371/journal.pcbi.1011513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 10/12/2023] [Accepted: 09/12/2023] [Indexed: 10/04/2023] Open
Abstract
Defective interfering particles (DIPs) are virus-like particles that occur naturally during virus infections. These particles are defective, lacking essential genetic materials for replication, but they can interact with the wild-type virus and potentially be used as therapeutic agents. However, the effect of DIPs on infection spread is still unclear due to complicated stochastic effects and nonlinear spatial dynamics. In this work, we develop a model with a new hybrid method to study the spatial-temporal dynamics of viruses and DIPs co-infections within hosts. We present two different scenarios of virus production and compare the results from deterministic and stochastic models to demonstrate how the stochastic effect is involved in the spatial dynamics of virus transmission. We compare the spread features of the virus in simulations and experiments, including the formation and the speed of virus spread and the emergence of stochastic patchy patterns of virus distribution. Our simulations simultaneously capture observed spatial spread features in the experimental data, including the spread rate of the virus and its patchiness. The results demonstrate that DIPs can slow down the growth of virus particles and make the spread of the virus more patchy.
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Affiliation(s)
- Qiantong Liang
- Department of Mathematics, City University of Hong Kong, Hong Kong, China
| | - Johnny Yang
- Department of Mathematics, Indiana University, Bloomington, Indiana, United States of America
| | - Wai-Tong Louis Fan
- Department of Mathematics, Indiana University, Bloomington, Indiana, United States of America
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Wing-Cheong Lo
- Department of Mathematics, City University of Hong Kong, Hong Kong, China
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7
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Fredrikson JP, Domanico LF, Pratt SL, Loveday EK, Taylor MP, Chang CB. Single-cell Herpes Simplex Virus type-1 infection of neurons using drop-based microfluidics reveals heterogeneous replication kinetics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.18.558333. [PMID: 37790515 PMCID: PMC10542126 DOI: 10.1101/2023.09.18.558333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Single-cell analyses of viral infections often reveal heterogeneity that is not detected by traditional population-level studies. This study applies drop-based microfluidics to investigate the dynamics of HSV-1 infection of neurons at the single-cell level. We used micron-scale Matrigel beads, termed microgels, to culture individual murine Superior Cervical ganglia (SCG) neurons or epithelial cells. Microgel-cultured cells are subsequently enclosed in individual media-in-oil droplets with a dual fluorescent-reporter HSV-1, enabling real-time observation of viral gene expression and replication. Infection within drops revealed that the kinetics of initial viral gene expression and replication were dependent on the inoculating dose. Notably, increasing inoculating doses led to earlier onset of viral gene expression and more frequent productive viral replication. These observations provide crucial insights into the complexity of HSV-1 infection in neurons and emphasize the importance of studying single-cell outcomes of viral infection. The innovative techniques presented here for cell culture and infection in drops provide a foundation for future virology and neurobiology investigations.
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Affiliation(s)
- Jacob P. Fredrikson
- Department of Chemical & Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
| | - Luke F. Domanico
- Department of Microbiology & Cell Biology, Montana State University, P.O. Box 173520, Bozeman, MT 59717, USA
| | - Shawna L. Pratt
- Department of Chemical & Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
| | - Emma K. Loveday
- Department of Chemical & Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
| | - Matthew P. Taylor
- Department of Microbiology & Cell Biology, Montana State University, P.O. Box 173520, Bozeman, MT 59717, USA
| | - Connie B. Chang
- Department of Chemical & Biological Engineering, Montana State University, P.O. Box 173920, Bozeman, MT 59717, USA
- Center for Biofilm Engineering, Montana State University, 366 Barnard Hall, Bozeman, MT 59717, USA
- Department of Physiology & Biomedical Engineering, Mayo Clinic, 200 First St. SW, Rochester, MN 55905, USA
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8
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Bacsik DJ, Dadonaite B, Butler A, Greaney AJ, Heaton NS, Bloom JD. Influenza virus transcription and progeny production are poorly correlated in single cells. eLife 2023; 12:RP86852. [PMID: 37675839 PMCID: PMC10484525 DOI: 10.7554/elife.86852] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023] Open
Abstract
The ultimate success of a viral infection at the cellular level is determined by the number of progeny virions produced. However, most single-cell studies of infection quantify the expression of viral transcripts and proteins, rather than the amount of progeny virions released from infected cells. Here, we overcome this limitation by simultaneously measuring transcription and progeny production from single influenza virus-infected cells by embedding nucleotide barcodes in the viral genome. We find that viral transcription and progeny production are poorly correlated in single cells. The cells that transcribe the most viral mRNA do not produce the most viral progeny and often represent aberrant infections that fail to express the influenza NS gene. However, only some of the discrepancy between transcription and progeny production can be explained by viral gene absence or mutations: there is also a wide range of progeny production among cells infected by complete unmutated virions. Overall, our results show that viral transcription is a relatively poor predictor of an infected cell's contribution to the progeny population.
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Affiliation(s)
- David J Bacsik
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
- Department of Genome Sciences & Medical Scientist Training Program, University of WashingtonSeattleUnited States
| | - Bernadeta Dadonaite
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
| | - Andrew Butler
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
| | - Allison J Greaney
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
- Department of Genome Sciences & Medical Scientist Training Program, University of WashingtonSeattleUnited States
| | - Nicholas S Heaton
- Department of Molecular Genetics and Microbiology, Duke University School of MedicineDurhamUnited States
- Duke Human Vaccine Institute, Duke University School of MedicineDurhamUnited States
| | - Jesse D Bloom
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
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9
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Reffsin S, Miller J, Ayyanathan K, Dunagin MC, Jain N, Schultz DC, Cherry S, Raj A. Single cell susceptibility to SARS-CoV-2 infection is driven by variable cell states. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.06.547955. [PMID: 37461472 PMCID: PMC10350037 DOI: 10.1101/2023.07.06.547955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
The ability of a virus to infect a cell type is at least in part determined by the presence of host factors required for the viral life cycle. However, even within cell types that express known factors needed for infection, not every cell is equally susceptible, suggesting that our knowledge of the full spectrum of factors that promote infection is incomplete. Profiling the most susceptible subsets of cells within a population may reveal additional factors that promote infection. However, because viral infection dramatically alters the state of the cell, new approaches are needed to reveal the state of these cells prior to infection with virus. Here, we used single-cell clone tracing to retrospectively identify and characterize lung epithelial cells that are highly susceptible to infection with SARS-CoV-2. The transcriptional state of these highly susceptible cells includes markers of retinoic acid signaling and epithelial differentiation. Loss of candidate factors identified by our approach revealed that many of these factors play roles in viral entry. Moreover, a subset of these factors exert control over the infectable cell state itself, regulating the expression of key factors associated with viral infection and entry. Analysis of patient samples revealed the heterogeneous expression of these factors across both cells and patients in vivo. Further, the expression of these factors is upregulated in particular inflammatory pathologies. Altogether, our results show that the variable expression of intrinsic cell states is a major determinant of whether a cell can be infected by SARS-CoV-2.
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Affiliation(s)
- Sam Reffsin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Jesse Miller
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kasirajan Ayyanathan
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Margaret C. Dunagin
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
| | - Naveen Jain
- Genetics and Epigenetics, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David C. Schultz
- Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA, USA
| | - Sara Cherry
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, PA, USA
- Department of Microbiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Arjun Raj
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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10
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Cable J, Sun J, Cheon IS, Vaughan AE, Castro IA, Stein SR, López CB, Gostic KM, Openshaw PJM, Ellebedy AH, Wack A, Hutchinson E, Thomas MM, Langlois RA, Lingwood D, Baker SF, Folkins M, Foxman EF, Ward AB, Schwemmle M, Russell AB, Chiu C, Ganti K, Subbarao K, Sheahan TP, Penaloza-MacMaster P, Eddens T. Respiratory viruses: New frontiers-a Keystone Symposia report. Ann N Y Acad Sci 2023; 1522:60-73. [PMID: 36722473 PMCID: PMC10580159 DOI: 10.1111/nyas.14958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Respiratory viruses are a common cause of morbidity and mortality around the world. Viruses like influenza, RSV, and most recently SARS-CoV-2 can rapidly spread through a population, causing acute infection and, in vulnerable populations, severe or chronic disease. Developing effective treatment and prevention strategies often becomes a race against ever-evolving viruses that develop resistance, leaving therapy efficacy either short-lived or relevant for specific viral strains. On June 29 to July 2, 2022, researchers met for the Keystone symposium "Respiratory Viruses: New Frontiers." Researchers presented new insights into viral biology and virus-host interactions to understand the mechanisms of disease and identify novel treatment and prevention approaches that are effective, durable, and broad.
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Affiliation(s)
| | - Jie Sun
- Division of Pulmonary and Critical Medicine, Department of Medicine; Department of Immunology; and Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
- Carter Immunology Center and Division of Infectious Disease and International Health, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - In Su Cheon
- Division of Pulmonary and Critical Medicine, Department of Medicine; Department of Immunology; and Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
- Carter Immunology Center and Division of Infectious Disease and International Health, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - Andrew E Vaughan
- University of Pennsylvania School of Veterinary Medicine, Biomedical Sciences, Philadelphia, Pennsylvania, USA
| | - Italo A Castro
- Virology Research Center, Ribeirao Preto Medical School, University of São Paulo - USP, São Paulo, Brazil
| | - Sydney R Stein
- Emerging Pathogens Section, Critical Care Medicine Department, Clinical Center and Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA
| | - Carolina B López
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Molecular Microbiology and Center for Women Infectious Disease Research, Washington University School of Medicine, St Louis, Missouri, USA
| | - Katelyn M Gostic
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, USA
| | | | - Ali H Ellebedy
- Department of Pathology and Immunology; The Andrew M. and Jane M. Bursky Center for Human Immunology & Immunotherapy Programs; and Center for Vaccines and Immunity to Microbial Pathogens, Washington University School of Medicine, St Louis, Missouri, USA
| | - Andreas Wack
- Immunoregulation Laboratory, The Francis Crick Institute, London, UK
| | | | | | - Ryan A Langlois
- Center for Immunology and Department of Microbiology and Immunology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Daniel Lingwood
- The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology, and Harvard University, Cambridge, Massachusetts, USA
| | - Steven F Baker
- Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA
| | - Melanie Folkins
- Department of Medical Microbiology and Immunology, University of Alberta, Edmonton, Alberta, Canada
| | - Ellen F Foxman
- Department of Laboratory Medicine and Department of Immunology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Andrew B Ward
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California, USA
| | - Martin Schwemmle
- Institute of Virology, Freiburg University Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Alistair B Russell
- Division of Biological Sciences, University of California, San Diego, La Jolla, California, USA
| | - Christopher Chiu
- Department of Infectious Disease, Imperial College London, London, UK
| | - Ketaki Ganti
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Kanta Subbarao
- Department of Microbiology and Immunology, WHO Collaborating Centre for Reference and Research on Influenza at the Peter Doherty Institute for Infection and Immunity, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Timothy P Sheahan
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Pablo Penaloza-MacMaster
- Department of Microbiology-Immunology, School of Medicine, Northwestern University Feinberg, Chicago, Illinois, USA
| | - Taylor Eddens
- Pediatric Scientist Development Program, University of Pittsburgh Medical Center (UPMC) Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
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11
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Canova CT, Inguva PK, Braatz RD. Mechanistic modeling of viral particle production. Biotechnol Bioeng 2023; 120:629-641. [PMID: 36461898 DOI: 10.1002/bit.28296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 11/29/2022] [Accepted: 11/30/2022] [Indexed: 12/05/2022]
Abstract
Viral systems such as wild-type viruses, viral vectors, and virus-like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial-scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild-type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in-silico testing of novel process operating strategies and/or advanced process control.
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Affiliation(s)
- Christopher T Canova
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Pavan K Inguva
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Richard D Braatz
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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12
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Kannoly S, Oken G, Shadan J, Musheyev D, Singh K, Singh A, Dennehy JJ. Single-Cell Approach Reveals Intercellular Heterogeneity in Phage-Producing Capacities. Microbiol Spectr 2023; 11:e0266321. [PMID: 36541779 PMCID: PMC9927085 DOI: 10.1128/spectrum.02663-21] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Bacteriophage burst size is the average number of phage virions released from infected bacterial cells, and its magnitude depends on the duration of an intracellular progeny accumulation phase. Burst size is often measured at the population level, not the single-cell level, and consequently, statistical moments are not commonly available. In this study, we estimated the bacteriophage lambda (λ) single-cell burst size mean and variance following different intracellular accumulation period durations by employing Escherichia coli lysogens bearing lysis-deficient λ prophages. Single lysogens can be isolated and chemically lysed at desired times following prophage induction to quantify progeny intracellular accumulation within individual cells. Our data showed that λ phage burst size initially increased exponentially with increased lysis time (i.e., period between induction and chemical lysis) and then saturated at longer lysis times. We also demonstrated that cell-to-cell variation, or "noise," in lysis timing did not contribute significantly to burst size noise. The burst size noise remained constant with increasing mean burst size. The most likely explanation for the experimentally observed constant burst size noise was that cell-to-cell differences in burst size originated from intercellular heterogeneity in cellular capacities to produce phages. The mean burst size measured at different lysis times was positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicated that there are other factors in addition to cell size that determine this cellular capacity. IMPORTANCE Phages produce offspring by hijacking a cell's replicative machinery. Previously, it was noted that the variation in the number of phages produced by single infected cells far exceeded cell size variation. It was hypothesized that this variation is a consequence of variation in the timing of host cell lysis. Here, we show that cell-to-cell variation in lysis timing does not significantly contribute to the burst size variation. We suggest that the constant burst size variation across different host lysis times results from cell-to-cell differences in capacity to produce phages. We found that the mean burst size measured at different lysis times was positively correlated to cell volume, which may determine the cellular phage production capacity. However, experiments controlling for cell size indicated that there are other factors in addition to cell size that determine this cellular capacity.
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Affiliation(s)
- Sherin Kannoly
- Biology Department, Queens College of The City University of New York, New York, New York, USA
| | - Gabriella Oken
- Biology Department, Queens College of The City University of New York, New York, New York, USA
| | - Jonathan Shadan
- Biology Department, Queens College of The City University of New York, New York, New York, USA
| | - David Musheyev
- Biology Department, Queens College of The City University of New York, New York, New York, USA
| | - Kevin Singh
- Biology Department, Queens College of The City University of New York, New York, New York, USA
| | - Abhyudai Singh
- Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware, USA
| | - John J. Dennehy
- Biology Department, Queens College of The City University of New York, New York, New York, USA
- The Graduate Center of The City University of New York, New York, New York, USA
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13
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Pu F, Wang R, Yang X, Hu X, Wang J, Zhang L, Zhao Y, Zhang D, Liu Z, Liu J. Nucleotide and codon usage biases involved in the evolution of African swine fever virus: A comparative genomics analysis. J Basic Microbiol 2023; 63:499-518. [PMID: 36782108 DOI: 10.1002/jobm.202200624] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/05/2023] [Accepted: 01/21/2023] [Indexed: 02/15/2023]
Abstract
Since African swine fever virus (ASFV) replication is closely related to its host's machinery, codon usage of viral genome can be subject to selection pressures. A better understanding of codon usage can give new insights into viral evolution. We implemented information entropy and revealed that the nucleotide usage pattern of ASFV is significantly associated with viral isolation factors (region and time), especially the usages of thymine and cytosine. Despite the domination of adenine and thymine in the viral genome, we found that mutation pressure alters the overall codon usage pattern of ASFV, followed by selective forces from natural selection. Moreover, the nucleotide skew index at the gene level indicates that nucleotide usages influencing synonymous codon bias of ASFV are significantly correlated with viral protein hydropathy. Finally, evolutionary plasticity is proved to contribute to the weakness in synonymous codons with A- or T-end serving as optimal codons of ASFV, suggesting that fine-tuning translation selection plays a role in synonymous codon usages of ASFV for adapting host. Taken together, ASFV is subject to evolutionary dynamics on nucleotide selections and synonymous codon usage, and our detailed analysis offers deeper insights into the genetic characteristics of this newly emerging virus around the world.
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Affiliation(s)
- Feiyang Pu
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Rui Wang
- Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Xuanye Yang
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Xinyan Hu
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Jinqian Wang
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Lijuan Zhang
- College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Yongqing Zhao
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Derong Zhang
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Zewen Liu
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
| | - Junlin Liu
- Biomedical Research Center, Northwest Minzu University, Lanzhou, China.,College of Life Science and Engineering, Northwest Minzu University, Lanzhou, Gansu, China
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14
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Loveday EK, Sanchez HS, Thomas MM, Chang CB. Single-Cell Infection of Influenza A Virus Using Drop-Based Microfluidics. Microbiol Spectr 2022; 10:e0099322. [PMID: 36125315 PMCID: PMC9603537 DOI: 10.1128/spectrum.00993-22] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 08/22/2022] [Indexed: 12/30/2022] Open
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.
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Affiliation(s)
- Emma Kate Loveday
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA
- Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana, USA
| | - Humberto S. Sanchez
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA
- Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana, USA
| | - Mallory M. Thomas
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA
- Microbiology and Cell Biology, Montana State University, Bozeman, Montana, USA
| | - Connie B. Chang
- Center for Biofilm Engineering, Montana State University, Bozeman, Montana, USA
- Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana, USA
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
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15
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Pires De Souza GA, Le Bideau M, Boschi C, Wurtz N, Colson P, Aherfi S, Devaux C, La Scola B. Choosing a cellular model to study SARS-CoV-2. Front Cell Infect Microbiol 2022; 12:1003608. [PMID: 36339347 PMCID: PMC9634005 DOI: 10.3389/fcimb.2022.1003608] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 10/03/2022] [Indexed: 08/04/2023] Open
Abstract
As new pathogens emerge, new challenges must be faced. This is no different in infectious disease research, where identifying the best tools available in laboratories to conduct an investigation can, at least initially, be particularly complicated. However, in the context of an emerging virus, such as SARS-CoV-2, which was recently detected in China and has become a global threat to healthcare systems, developing models of infection and pathogenesis is urgently required. Cell-based approaches are crucial to understanding coronavirus infection biology, growth kinetics, and tropism. Usually, laboratory cell lines are the first line in experimental models to study viral pathogenicity and perform assays aimed at screening antiviral compounds which are efficient at blocking the replication of emerging viruses, saving time and resources, reducing the use of experimental animals. However, determining the ideal cell type can be challenging, especially when several researchers have to adapt their studies to specific requirements. This review strives to guide scientists who are venturing into studying SARS-CoV-2 and help them choose the right cellular models. It revisits basic concepts of virology and presents the currently available in vitro models, their advantages and disadvantages, and the known consequences of each choice.
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Affiliation(s)
- Gabriel Augusto Pires De Souza
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
| | - Marion Le Bideau
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
| | - Céline Boschi
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
| | - Nathalie Wurtz
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
| | - Philippe Colson
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
| | - Sarah Aherfi
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
| | - Christian Devaux
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
- Department of Biological Sciences (INSB), Centre National de la Recherche Scientifique, Marseille, France
| | - Bernard La Scola
- Microbes, Evolution, Phylogeny and Infection (MEPHI), UM63, Institut de Recherche pour le Développement (IRD), Assistance Publique - Hôpitaux de Marseille (AP-HM), Aix-Marseille Université, Marseille, France
- Institut Hospitalo-Universitaire Méditerranée Infection, Marseille, France
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16
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Kelly JN, Laloli L, V’kovski P, Holwerda M, Portmann J, Thiel V, Dijkman R. Comprehensive single cell analysis of pandemic influenza A virus infection in the human airways uncovers cell-type specific host transcriptional signatures relevant for disease progression and pathogenesis. Front Immunol 2022; 13:978824. [PMID: 36268025 PMCID: PMC9576848 DOI: 10.3389/fimmu.2022.978824] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 09/01/2022] [Indexed: 12/04/2022] Open
Abstract
The respiratory epithelium constitutes the first line of defense against invading respiratory pathogens, such as the 2009 pandemic strain of influenza A virus (IAV, H1N1pdm09), and plays a crucial role in the host antiviral response to infection. Despite its importance, however, it remains unknown how individual cell types within the respiratory epithelium respond to IAV infection or how the latter may influence IAV disease progression and pathogenesis. Here, we used single cell RNA sequencing (scRNA-seq) to dissect the host response to IAV infection in its natural target cells. scRNA-seq was performed on human airway epithelial cell (hAEC) cultures infected with either wild-type pandemic IAV (WT) or with a mutant version of IAV (NS1R38A) that induced a robust innate immune response. We then characterized both the host and viral transcriptomes of more than 19,000 single cells across the 5 major cell types populating the human respiratory epithelium. For all cell types, we observed a wide spectrum of viral burden among single infected cells and a disparate host response between infected and bystander populations. Interestingly, we also identified multiple key differences in the host response to IAV among individual cell types, including high levels of pro-inflammatory cytokines and chemokines in secretory and basal cells and an important role for luminal cells in sensing and restricting incoming virus. Multiple infected cell types were shown to upregulate interferons (IFN), with type III IFNs clearly dominating the antiviral response. Transcriptional changes in genes related to cell differentiation, cell migration, and tissue repair were also identified. Strikingly, we also detected a shift in viral host cell tropism from non-ciliated cells to ciliated cells at later stages of infection and observed major changes in the cellular composition. Microscopic analysis of both WT and NS1R38A virus-infected hAECs at various stages of IAV infection revealed that the transcriptional changes we observed at 18 hpi were likely driving the downstream histopathological alterations in the airway epithelium. To our knowledge, this is the first study to provide a comprehensive analysis of the cell type-specific host antiviral response to influenza virus infection in its natural target cells – namely, the human respiratory epithelium.
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Affiliation(s)
- Jenna N. Kelly
- Institute of Virology and Immunology, Bern, Switzerland
- Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Laura Laloli
- Institute of Virology and Immunology, Bern, Switzerland
- Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Philip V’kovski
- Institute of Virology and Immunology, Bern, Switzerland
- Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Melle Holwerda
- Institute of Virology and Immunology, Bern, Switzerland
- Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Jasmine Portmann
- Institute of Virology and Immunology, Bern, Switzerland
- Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Volker Thiel
- Institute of Virology and Immunology, Bern, Switzerland
- Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
- European Virus Bioinformatics Center (EVBC), Jena, Germany
| | - Ronald Dijkman
- Institute of Virology and Immunology, Bern, Switzerland
- Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
- European Virus Bioinformatics Center (EVBC), Jena, Germany
- *Correspondence: Ronald Dijkman,
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17
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Shartouny JR, Lee CY, Delima GK, Lowen AC. Beneficial effects of cellular coinfection resolve inefficiency in influenza A virus transcription. PLoS Pathog 2022; 18:e1010865. [PMID: 36121893 PMCID: PMC9521904 DOI: 10.1371/journal.ppat.1010865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 09/29/2022] [Accepted: 09/08/2022] [Indexed: 11/22/2022] Open
Abstract
For diverse viruses, cellular infection with single vs. multiple virions can yield distinct biological outcomes. We previously found that influenza A/guinea fowl/Hong Kong/WF10/99 (H9N2) virus (GFHK99) displays a particularly high reliance on multiple infection in mammalian cells. Here, we sought to uncover the viral processes underlying this phenotype. We found that the need for multiple infection maps to amino acid 26K of the viral PA protein. PA 26K suppresses endonuclease activity and viral transcription, specifically within cells infected at low multiplicity. In the context of the higher functioning PA 26E, inhibition of PA using baloxavir acid augments reliance on multiple infection. Together, these data suggest a model in which sub-optimal activity of the GFHK99 endonuclease results in inefficient priming of viral transcription, an insufficiency which can be overcome with the introduction of additional viral ribonucleoprotein templates to the cell. More broadly, the finding that deficiency in a core viral function is ameliorated through multiple infection suggests that the fitness effects of many viral mutations are likely to be modulated by multiplicity of infection, such that the shape of fitness landscapes varies with viral densities.
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Affiliation(s)
- Jessica R. Shartouny
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia, United States of America
- Emory Center of Excellence for Influenza Research and Response (Emory-CEIRR), Atlanta, Georgia, United States of America
| | - Chung-Young Lee
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia, United States of America
- Emory Center of Excellence for Influenza Research and Response (Emory-CEIRR), Atlanta, Georgia, United States of America
| | - Gabrielle K. Delima
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia, United States of America
- Emory Center of Excellence for Influenza Research and Response (Emory-CEIRR), Atlanta, Georgia, United States of America
| | - Anice C. Lowen
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia, United States of America
- Emory Center of Excellence for Influenza Research and Response (Emory-CEIRR), Atlanta, Georgia, United States of America
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18
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Allman B, Koelle K, Weissman D. Heterogeneity in viral populations increases the rate of deleterious mutation accumulation. Genetics 2022; 222:6673144. [PMID: 35993909 PMCID: PMC9526070 DOI: 10.1093/genetics/iyac127] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/11/2022] [Indexed: 11/13/2022] Open
Abstract
RNA viruses have high mutation rates, with the majority of mutations being deleterious. We examine patterns of deleterious mutation accumulation over multiple rounds of viral replication, with a focus on how cellular coinfection and heterogeneity in viral output affect these patterns. Specifically, using agent-based intercellular simulations we find, in agreement with previous studies, that coinfection of cells by viruses relaxes the strength of purifying selection, and thereby increases the rate of deleterious mutation accumulation. We further find that cellular heterogeneity in viral output exacerbates the rate of deleterious mutation accumulation, regardless of whether this heterogeneity in viral output is stochastic or is due to variation in cellular multiplicity of infection. These results highlight the need to consider the unique life histories of viruses and their population structure to better understand observed patterns of viral evolution.
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Affiliation(s)
- Brent Allman
- Graduate Program in Population Biology, Ecology, and Evolution, Emory University, Atlanta, Georgia 30322, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, Georgia 30322, USA
| | - Daniel Weissman
- Department of Biology, Emory University, Atlanta, Georgia 30322, USA.,Department of Physics, Emory University, Atlanta, Georgia 30322, USA
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19
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Segredo-Otero E, Sanjuán R. Cooperative Virus-Virus Interactions: An Evolutionary Perspective. BIODESIGN RESEARCH 2022; 2022:9819272. [PMID: 37850129 PMCID: PMC10521650 DOI: 10.34133/2022/9819272] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/21/2022] [Indexed: 10/19/2023] Open
Abstract
Despite extensive evidence of virus-virus interactions, not much is known about their biological significance. Importantly, virus-virus interactions could have evolved as a form of cooperation or simply be a by-product of other processes. Here, we review and discuss different types of virus-virus interactions from the point of view of social evolution, which provides a well-established framework for interpreting the fitness costs and benefits of such traits. We also classify interactions according to their mechanisms of action and speculate on their evolutionary implications. As in any other biological system, the evolutionary stability of viral cooperation critically requires cheaters to be excluded from cooperative interactions. We discuss how cheater viruses exploit cooperative traits and how viral populations are able to counteract this maladaptive process.
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Affiliation(s)
- Ernesto Segredo-Otero
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas-Universitat de València, C/ Catedrático Agustín Escardino 9, 46980 Paterna, València, Spain
| | - Rafael Sanjuán
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas-Universitat de València, C/ Catedrático Agustín Escardino 9, 46980 Paterna, València, Spain
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20
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Zitzmann C, Dächert C, Schmid B, van der Schaar H, van Hemert M, Perelson AS, van Kuppeveld FJ, Bartenschlager R, Binder M, Kaderali L. Mathematical modeling of plus-strand RNA virus replication to identify broad-spectrum antiviral treatment strategies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.07.25.501353. [PMID: 35923314 PMCID: PMC9347285 DOI: 10.1101/2022.07.25.501353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Plus-strand RNA viruses are the largest group of viruses. Many are human pathogens that inflict a socio-economic burden. Interestingly, plus-strand RNA viruses share remarkable similarities in their replication. A hallmark of plus-strand RNA viruses is the remodeling of intracellular membranes to establish replication organelles (so-called "replication factories"), which provide a protected environment for the replicase complex, consisting of the viral genome and proteins necessary for viral RNA synthesis. In the current study, we investigate pan-viral similarities and virus-specific differences in the life cycle of this highly relevant group of viruses. We first measured the kinetics of viral RNA, viral protein, and infectious virus particle production of hepatitis C virus (HCV), dengue virus (DENV), and coxsackievirus B3 (CVB3) in the immuno-compromised Huh7 cell line and thus without perturbations by an intrinsic immune response. Based on these measurements, we developed a detailed mathematical model of the replication of HCV, DENV, and CVB3 and show that only small virus-specific changes in the model were necessary to describe the in vitro dynamics of the different viruses. Our model correctly predicted virus-specific mechanisms such as host cell translation shut off and different kinetics of replication organelles. Further, our model suggests that the ability to suppress or shut down host cell mRNA translation may be a key factor for in vitro replication efficiency which may determine acute self-limited or chronic infection. We further analyzed potential broad-spectrum antiviral treatment options in silico and found that targeting viral RNA translation, especially polyprotein cleavage, and viral RNA synthesis may be the most promising drug targets for all plus-strand RNA viruses. Moreover, we found that targeting only the formation of replicase complexes did not stop the viral replication in vitro early in infection, while inhibiting intracellular trafficking processes may even lead to amplified viral growth. Author summary Plus-strand RNA viruses comprise a large group of related and medically relevant viruses. The current global pandemic of COVID-19 caused by the SARS-coronavirus-2 as well as the constant spread of diseases such as dengue and chikungunya fever show the necessity of a comprehensive and precise analysis of plus-strand RNA virus infections. Plus-strand RNA viruses share similarities in their life cycle. To understand their within-host replication strategies, we developed a mathematical model that studies pan-viral similarities and virus-specific differences of three plus-strand RNA viruses, namely hepatitis C, dengue, and coxsackievirus. By fitting our model to in vitro data, we found that only small virus-specific variations in the model were required to describe the dynamics of all three viruses. Furthermore, our model predicted that ribosomes involved in viral RNA translation seem to be a key player in plus-strand RNA replication efficiency, which may determine acute or chronic infection outcome. Furthermore, our in-silico drug treatment analysis suggests that targeting viral proteases involved in polyprotein cleavage, in combination with viral RNA replication, may represent promising drug targets with broad-spectrum antiviral activity.
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Affiliation(s)
- Carolin Zitzmann
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Christopher Dächert
- Research Group “Dynamics of Early Viral Infection and the Innate Antiviral Response”, Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bianca Schmid
- Dept of Infectious Diseases, Molecular Virology, Heidelberg University, Heidelberg, Germany
| | - Hilde van der Schaar
- Division of infectious Diseases and Immunology, Virology Section, Dept of Biomolecular Health Sciences, Utrecht University, Utrecht, The Netherlands
| | - Martijn van Hemert
- Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Alan S. Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Frank J.M. van Kuppeveld
- Division of infectious Diseases and Immunology, Virology Section, Dept of Biomolecular Health Sciences, Utrecht University, Utrecht, The Netherlands
| | - Ralf Bartenschlager
- Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Dept of Infectious Diseases, Molecular Virology, Heidelberg University, Heidelberg, Germany
- German Center for Infection Research (DZIF), Heidelberg partner site, Heidelberg, Germany
| | - Marco Binder
- Research Group “Dynamics of Early Viral Infection and the Innate Antiviral Response”, Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lars Kaderali
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
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21
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Abstract
Microfluidics has enabled a new era of cellular and molecular assays due to the small length scales, parallelization, and the modularity of various analysis and actuation functions. Droplet microfluidics, in particular, has been instrumental in providing new tools for biology with its ability to quickly and reproducibly generate drops that act as individual reactors. A notable beneficiary of this technology has been single-cell RNA sequencing, which has revealed new heterogeneities and interactions for the fundamental unit of life. However, viruses far surpass the diversity of cellular life, affect the dynamics of all ecosystems, and are a chronic source of global health crises. Despite their impact on the world, high-throughput and high-resolution viral profiling has been difficult, with conventional methods being limited to population-level averaging, large sample volumes, and few cultivable hosts. Consequently, most viruses have not been identified and studied. Droplet microfluidics holds the potential to address many of these limitations and offers new levels of sensitivity and throughput for virology. This Feature highlights recent efforts that have applied droplet microfluidics to the detection and study of viruses, including for diagnostics, virus-host interactions, and cell-independent virus assays. In combination with traditional virology methods, droplet microfluidics should prove a potent tool toward achieving a better understanding of the most abundant biological species on Earth.
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Affiliation(s)
- Wenyang Jing
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Hee-Sun Han
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Urbana, Illinois 61801, United States
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22
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Abstract
Vertebrate immune systems suppress viral infection using both innate restriction factors and adaptive immunity. Viruses mutate to escape these defenses, driving hosts to counterevolve to regain fitness. This cycle recurs repeatedly, resulting in an evolutionary arms race whose outcome depends on the pace and likelihood of adaptation by host and viral genes. Although viruses evolve faster than their vertebrate hosts, their proteins are subject to numerous functional constraints that impact the probability of adaptation. These constraints are globally defined by evolutionary landscapes, which describe the fitness and adaptive potential of all possible mutations. We review deep mutational scanning experiments mapping the evolutionary landscapes of both host and viral proteins engaged in arms races. For restriction factors and some broadly neutralizing antibodies, landscapes favor the host, which may help to level the evolutionary playing field against rapidly evolving viruses. We discuss the biophysical underpinnings of these landscapes and their therapeutic implications.
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Affiliation(s)
- Jeannette L Tenthorey
- Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA; , ,
| | - Michael Emerman
- Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA; , , .,Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Harmit S Malik
- Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA; , , .,Howard Hughes Medical Institute, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
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23
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Küchler J, Püttker S, Lahmann P, Genzel Y, Kupke S, Benndorf D, Reichl U. Absolute quantification of viral proteins during single-round replication of MDCK suspension cells. J Proteomics 2022; 259:104544. [PMID: 35240312 DOI: 10.1016/j.jprot.2022.104544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 02/15/2022] [Accepted: 02/20/2022] [Indexed: 11/17/2022]
Abstract
Madin-Darby canine kidney (MDCK) cells are widely used in basic research and for the propagation of influenza A viruses (IAV) for vaccine production. To identify targets for antiviral therapies and to optimize vaccine manufacturing, a detailed understanding of the viral life cycle is important. This includes the characterization of virus entry, the synthesis of the various viral RNAs and proteins, the transfer of viral compounds in the cell and virus budding. In case quantitative information is available, the analysis can be complemented by mathematical modelling approaches. While comprehensive studies focusing on IAV entry as well as viral mRNA, vRNA and cRNA accumulation in the nucleus of cells have been performed, quantitative data regarding IAV protein synthesis and accumulation was mostly lacking. In this study, we present a mass spectrometry (MS)-based method to evaluate whether an absolute quantification of viral proteins is possible for single-round replication in suspension MDCK cells. Using influenza A/PR/8/34 (H1N1, RKI) as a model strain at a multiplicity of infection of ten, defined amounts of isotopically labelled peptides of synthetic origin of four IAV proteins (hemagglutinin, neuraminidase, nucleoprotein, matrix protein 1) were added as an internal standard before tryptic digestion of samples for absolute quantification (AQUA). The first intracellular protein detected was NP at 1 h post infection (hpi). A maximum extracellular concentration of 7.7E+12 copies/mL was achieved. This was followed by hemagglutinin (3 hpi, maximum 4.1E+12 copies/mL at 13 hpi), matrix protein 1 (5 hpi, maximum 2.2E+12 copies/mL at 13 hpi) and neuraminidase (5 hpi, 6.0E+11 copies/mL at 13 hpi). In sum, for the first time absolute IAV protein copy numbers were quantified by a MS-based method for infected MDCK cells providing important insights into viral protein dynamics during single-round virus replication. SIGNIFICANCE: Influenza A virus is a significant human pathogen worldwide. To improve therapies against influenza and overcome bottlenecks in vaccine production in cell culture, it is critical to gain a detailed understanding of the viral life cycle. In addition to qPCR-based models, this study will examine the dynamics of influenza virus proteins during infection of producer cells to gain initial insights into changes in absolute copy numbers.
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Affiliation(s)
- Jan Küchler
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
| | - Sebastian Püttker
- Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Patrick Lahmann
- Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Yvonne Genzel
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Sascha Kupke
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
| | - Dirk Benndorf
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany; Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Udo Reichl
- Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany; Bioprocess Engineering, Otto von Guericke University Magdeburg, Magdeburg, Germany
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24
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Viral Aggregation: The Knowns and Unknowns. Viruses 2022; 14:v14020438. [PMID: 35216031 PMCID: PMC8879382 DOI: 10.3390/v14020438] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 01/31/2022] [Accepted: 02/14/2022] [Indexed: 11/21/2022] Open
Abstract
Viral aggregation is a complex and pervasive phenomenon affecting many viral families. An increasing number of studies have indicated that it can modulate critical parameters surrounding viral infections, and yet its role in viral infectivity, pathogenesis, and evolution is just beginning to be appreciated. Aggregation likely promotes viral infection by increasing the cellular multiplicity of infection (MOI), which can help overcome stochastic failures of viral infection and genetic defects and subsequently modulate their fitness, virulence, and host responses. Conversely, aggregation can limit the dispersal of viral particles and hinder the early stages of establishing a successful infection. The cost–benefit of viral aggregation seems to vary not only depending on the viral species and aggregating factors but also on the spatiotemporal context of the viral life cycle. Here, we review the knowns of viral aggregation by focusing on studies with direct observations of viral aggregation and mechanistic studies of the aggregation process. Next, we chart the unknowns and discuss the biological implications of viral aggregation in their infection cycle. We conclude with a perspective on harnessing the therapeutic potential of this phenomenon and highlight several challenging questions that warrant further research for this field to advance.
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25
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Sensitivity of SARS-CoV-2 Life Cycle to IFN Effects and ACE2 Binding Unveiled with a Stochastic Model. Viruses 2022; 14:v14020403. [PMID: 35215996 PMCID: PMC8875829 DOI: 10.3390/v14020403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/27/2022] [Accepted: 02/04/2022] [Indexed: 02/01/2023] Open
Abstract
Mathematical modelling of infection processes in cells is of fundamental interest. It helps to understand the SARS-CoV-2 dynamics in detail and can be useful to define the vulnerability steps targeted by antiviral treatments. We previously developed a deterministic mathematical model of the SARS-CoV-2 life cycle in a single cell. Despite answering many questions, it certainly cannot accurately account for the stochastic nature of an infection process caused by natural fluctuation in reaction kinetics and the small abundance of participating components in a single cell. In the present work, this deterministic model is transformed into a stochastic one based on a Markov Chain Monte Carlo (MCMC) method. This model is employed to compute statistical characteristics of the SARS-CoV-2 life cycle including the probability for a non-degenerate infection process. Varying parameters of the model enables us to unveil the inhibitory effects of IFN and the effects of the ACE2 binding affinity. The simulation results show that the type I IFN response has a very strong effect on inhibition of the total viral progeny whereas the effect of a 10-fold variation of the binding rate to ACE2 turns out to be negligible for the probability of infection and viral production.
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26
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Bhat T, Cao A, Yin J. Virus-like Particles: Measures and Biological Functions. Viruses 2022; 14:383. [PMID: 35215979 PMCID: PMC8877645 DOI: 10.3390/v14020383] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 02/10/2022] [Accepted: 02/10/2022] [Indexed: 12/25/2022] Open
Abstract
Virus-like particles resemble infectious virus particles in size, shape, and molecular composition; however, they fail to productively infect host cells. Historically, the presence of virus-like particles has been inferred from total particle counts by microscopy, and infectious particle counts or plaque-forming-units (PFUs) by plaque assay; the resulting ratio of particles-to-PFUs is often greater than one, easily 10 or 100, indicating that most particles are non-infectious. Despite their inability to hijack cells for their reproduction, virus-like particles and the defective genomes they carry can exhibit a broad range of behaviors: interference with normal virus growth during co-infections, cell killing, and activation or inhibition of innate immune signaling. In addition, some virus-like particles become productive as their multiplicities of infection increase, a sign of cooperation between particles. Here, we review established and emerging methods to count virus-like particles and characterize their biological functions. We take a critical look at evidence for defective interfering virus genomes in natural and clinical isolates, and we review their potential as antiviral therapeutics. In short, we highlight an urgent need to better understand how virus-like genomes and particles interact with intact functional viruses during co-infection of their hosts, and their impacts on the transmission, severity, and persistence of virus-associated diseases.
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Affiliation(s)
| | | | - John Yin
- Department of Chemical and Biological Engineering, Wisconsin Institute for Discovery, University of Wisconsin-Madison, 330 N. Orchard Street, Madison, WI 53715, USA; (T.B.); (A.C.)
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27
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Jang HB, Chittick L, Li YF, Zablocki O, Sanderson CM, Carrillo A, van den Engh G, Sullivan MB. Viral tag and grow: a scalable approach to capture and characterize infectious virus-host pairs. ISME COMMUNICATIONS 2022; 2:12. [PMID: 37938680 PMCID: PMC9723727 DOI: 10.1038/s43705-022-00093-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 01/06/2022] [Accepted: 01/13/2022] [Indexed: 04/27/2023]
Abstract
Viral metagenomics (viromics) has reshaped our understanding of DNA viral diversity, ecology, and evolution across Earth's ecosystems. However, viromics now needs approaches to link newly discovered viruses to their host cells and characterize them at scale. This study adapts one such method, sequencing-enabled viral tagging (VT), to establish "Viral Tag and Grow" (VT + Grow) to rapidly capture and characterize viruses that infect a cultivated target bacterium, Pseudoalteromonas. First, baseline cytometric and microscopy data improved understanding of how infection conditions and host physiology impact populations in VT flow cytograms. Next, we extensively evaluated "and grow" capability to assess where VT signals reflect adsorption alone or wholly successful infections that lead to lysis. Third, we applied VT + Grow to a clonal virus stock, which, coupled to traditional plaque assays, revealed significant variability in burst size-findings that hint at a viral "individuality" parallel to the microbial phenotypic heterogeneity literature. Finally, we established a live protocol for public comment and improvement via protocols.io to maximally empower the research community. Together these efforts provide a robust foundation for VT researchers, and establish VT + Grow as a promising scalable technology to capture and characterize viruses from mixed community source samples that infect cultivable bacteria.
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Affiliation(s)
- Ho Bin Jang
- Department of Microbiology, The Ohio State University, Columbus, OH, USA
| | - Lauren Chittick
- Department of Microbiology, The Ohio State University, Columbus, OH, USA
| | - Yueh-Fen Li
- Department of Microbiology, The Ohio State University, Columbus, OH, USA
| | - Olivier Zablocki
- Department of Microbiology, The Ohio State University, Columbus, OH, USA
| | | | - Alfonso Carrillo
- Department of Microbiology, The Ohio State University, Columbus, OH, USA
| | | | - Matthew B Sullivan
- Department of Microbiology, The Ohio State University, Columbus, OH, USA.
- Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, OH, USA.
- Center of Microbiome Science, The Ohio State University, Columbus, OH, USA.
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28
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Heterogeneity of Early Host Response to Infection with Four Low-Pathogenic H7 Viruses with a Different Evolutionary History in the Field. Viruses 2021; 13:v13112323. [PMID: 34835129 PMCID: PMC8620788 DOI: 10.3390/v13112323] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 11/12/2021] [Accepted: 11/17/2021] [Indexed: 12/15/2022] Open
Abstract
Once low-pathogenic avian influenza viruses (LPAIVs) of the H5 and H7 subtypes from wild birds enter into poultry species, there is the possibility of them mutating into highly pathogenic avian influenza viruses (HPAIVs), resulting in severe epizootics with up to 100% mortality. This mutation from a LPAIV to HPAIV strain is the main cause of an AIV’s major economic impact on poultry production. Although AIVs are inextricably linked to their hosts in their evolutionary history, the contribution of host-related factors in the emergence of HPAI viruses has only been marginally explored so far. In this study, transcriptomic sequencing of tracheal tissue from chickens infected with four distinct LP H7 viruses, characterized by a different history of pathogenicity evolution in the field, was implemented. Despite the inoculation of a normalized infectious dose of viruses belonging to the same subtype (H7) and pathotype (LPAI), the use of animals of the same age, sex and species as well as the identification of a comparable viral load in the target samples, the analyses revealed a heterogeneity in the gene expression profile in response to infection with each of the H7 viruses administered.
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29
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Silva JMF, Nagata T, Melo FL, Elena SF. Heterogeneity in the Response of Different Subtypes of Drosophila melanogaster Midgut Cells to Viral Infections. Viruses 2021; 13:2284. [PMID: 34835089 PMCID: PMC8623525 DOI: 10.3390/v13112284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/05/2021] [Accepted: 11/13/2021] [Indexed: 11/29/2022] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) offers the possibility to monitor both host and pathogens transcriptomes at the cellular level. Here, public scRNA-seq datasets from Drosophila melanogaster midgut cells were used to compare the differences in replication strategy and cellular responses between two fly picorna-like viruses, Thika virus (TV) and D. melanogaster Nora virus (DMelNV). TV exhibited lower levels of viral RNA accumulation but infected a higher number of cells compared to DMelNV. In both cases, viral RNA accumulation varied according to cell subtype. The cellular heat shock response to TV and DMelNV infection was cell-subtype- and virus-specific. Disruption of bottleneck genes at later stages of infection in the systemic response, as well as of translation-related genes in the cellular response to DMelNV in two cell subtypes, may affect the virus replication.
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Affiliation(s)
- João M. F. Silva
- Departamento de Biologia Celular, Universidade de Brasília, Brasília 70910-900, Brazil; (J.M.F.S.); (T.N.); (F.L.M.)
- Instituto de Biología Integrativa de Sistemas (I2SysBio), CSIC-Universitat de València, 46980 Paterna, València, Spain
| | - Tatsuya Nagata
- Departamento de Biologia Celular, Universidade de Brasília, Brasília 70910-900, Brazil; (J.M.F.S.); (T.N.); (F.L.M.)
| | - Fernando L. Melo
- Departamento de Biologia Celular, Universidade de Brasília, Brasília 70910-900, Brazil; (J.M.F.S.); (T.N.); (F.L.M.)
| | - Santiago F. Elena
- Instituto de Biología Integrativa de Sistemas (I2SysBio), CSIC-Universitat de València, 46980 Paterna, València, Spain
- The Santa Fe Institute, Santa Fe, NM 87501, USA
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30
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Single-Cell Genomics: Enabling the Functional Elucidation of Infectious Diseases in Multi-Cell Genomes. Pathogens 2021; 10:pathogens10111467. [PMID: 34832622 PMCID: PMC8624509 DOI: 10.3390/pathogens10111467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/06/2021] [Accepted: 09/09/2021] [Indexed: 11/16/2022] Open
Abstract
Since the time when detection of gene expression in single cells by microarrays to the Next Generation Sequencing (NGS) enabled Single Cell Genomics (SCG), it has played a pivotal role to understand and elucidate the functional role of cellular heterogeneity. Along this journey to becoming a key player in the capture of the individuality of cells, SCG overcame many milestones, including scale, speed, sensitivity and sample costs (4S). There have been many important experimental and computational innovations in the efficient analysis and interpretation of SCG data. The increasing role of AI in SCG data analysis has further enhanced its applicability in building models for clinical intervention. Furthermore, SCG has been instrumental in the delineation of the role of cellular heterogeneity in specific diseases, including cancer and infectious diseases. The understanding of the role of differential immune responses in driving coronavirus disease-2019 (COVID-19) disease severity and clinical outcomes has been greatly aided by SCG. With many variants of concern (VOC) in sight, it would be of great importance to further understand the immune response specificity vis-a-vis the immune cell repertoire, the identification of novel cell types, and antibody response. Given the potential of SCG to play an integral part in the multi-omics approach to the study of the host-pathogen interaction and its outcomes, our review attempts to highlight its strengths, its implications for infectious disease biology, and its current limitations. We conclude that the application of SCG would be a critical step towards future pandemic preparedness.
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31
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Chhajer H, Rizvi VA, Roy R. Life cycle process dependencies of positive-sense RNA viruses suggest strategies for inhibiting productive cellular infection. J R Soc Interface 2021; 18:20210401. [PMID: 34753308 PMCID: PMC8580453 DOI: 10.1098/rsif.2021.0401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/18/2021] [Indexed: 12/25/2022] Open
Abstract
Life cycle processes of positive-strand (+)RNA viruses are broadly conserved across families, yet they employ different strategies to grow in the cell. Using a generalized dynamical model for intracellular (+)RNA virus growth, we decipher these life cycle determinants and their dependencies for several viruses and parse the effects of viral mutations, drugs and host cell permissivity. We show that poliovirus employs rapid replication and virus assembly, whereas the Japanese encephalitis virus leverages its higher rate of translation and efficient cellular reorganization compared to the hepatitis C virus. Stochastic simulations demonstrate infection extinction if all seeding (inoculating) viral RNA degrade before establishing robust replication critical for infection. The probability of this productive cellular infection, 'cellular infectivity', is affected by virus-host processes and defined by early life cycle events and viral seeding. An increase in cytoplasmic RNA degradation and delay in vesicular compartment formation reduces infectivity, more so when combined. Synergy among these parameters in limiting (+)RNA virus infection as predicted by our model suggests new avenues for inhibiting infections by targeting the early life cycle bottlenecks.
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Affiliation(s)
- Harsh Chhajer
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
| | - Vaseef A. Rizvi
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, Karnataka, India
| | - Rahul Roy
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
- Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
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32
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Dengue virus is sensitive to inhibition prior to productive replication. Cell Rep 2021; 37:109801. [PMID: 34644578 DOI: 10.1016/j.celrep.2021.109801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 06/23/2021] [Accepted: 09/15/2021] [Indexed: 11/21/2022] Open
Abstract
Uncovering vulnerable steps in the life cycle of viruses supports the rational design of antiviral treatments. However, information on viral replication dynamics obtained from traditional bulk assays with host cell populations is inherently limited as the data represent averages over a multitude of unsynchronized replication cycles. Here, we use time-lapse imaging of virus replication in thousands of single cells, combined with computational inference, to identify rate-limiting steps for dengue virus (DENV), a widespread human pathogen. Comparing wild-type DENV with a vaccine candidate mutant, we show that the viral spread in the mutant is greatly attenuated by delayed onset of productive replication, whereas wild-type and mutant virus have identical replication rates. Single-cell analysis done after applying the broad-spectrum antiviral drug, ribavirin, at clinically relevant concentrations revealed the same mechanism of attenuating viral spread. We conclude that the initial steps of infection, rather than the rate of established replication, are quantitatively limiting DENV spread.
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33
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Koca C, Civas M, Sahin SM, Ergonul O, Akan OB. Molecular Communication Theoretical Modeling and Analysis of SARS-CoV2 Transmission in Human Respiratory System. IEEE TRANSACTIONS ON MOLECULAR, BIOLOGICAL, AND MULTI-SCALE COMMUNICATIONS 2021; 7:153-164. [PMID: 35782716 PMCID: PMC8544952 DOI: 10.1109/tmbmc.2021.3071748] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 12/28/2020] [Accepted: 03/15/2021] [Indexed: 12/20/2022]
Abstract
Severe Acute Respiratory Syndrome-CoronaVirus 2 (SARS-CoV2) caused the ongoing pandemic. This pandemic devastated the world by killing more than a million people, as of October 2020. It is imperative to understand the transmission dynamics of SARS-CoV2 so that novel and interdisciplinary prevention, diagnostic, and therapeutic techniques could be developed. In this work, we model and analyze the transmission of SARS-CoV2 through the human respiratory tract from a molecular communication perspective. We consider that virus diffusion occurs in the mucus layer so that the shape of the tract does not have a significant effect on the transmission. Hence, this model reduces the inherent complexity of the human respiratory system. We further provide the impulse response of SARS-CoV2-ACE2 receptor binding event to determine the proportion of the virus population reaching different regions of the respiratory tract. Our findings confirm the results in the experimental literature on higher mucus flow rate causing virus migration to the lower respiratory tract. These results are especially important to understand the effect of SARS-CoV2 on the different human populations at different ages who have different mucus flow rates and ACE2 receptor concentrations in the different regions of the respiratory tract.
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Affiliation(s)
- Caglar Koca
- Internet of Everything Group, Electrical Engineering DivisionDepartment of EngineeringUniversity of CambridgeCambridgeCB2 1PZU.K.
| | - Meltem Civas
- Next-Generation and Wireless Communications LaboratoryDepartment of Electrical and Electronics EngineeringKoç University34450IstanbulTurkey
| | | | - Onder Ergonul
- School of MedicineDepartment of Infectious Diseases and Clinical MicrobiologyKoç University34450IstanbulTurkey
- Research Centre for Infectious DiseasesKoç University34450IstanbulTurkey
| | - Ozgur B. Akan
- Research Centre for Infectious DiseasesKoç University34450IstanbulTurkey
- Next-Generation and Wireless Communications LaboratoryCollege of Engineering, Koç University34450IstanbulTurkey
- Internet of Everything GroupDepartment of EngineeringUniversity of CambridgeCambridgeCB2 1PZU.K.
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34
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Grebennikov D, Kholodareva E, Sazonov I, Karsonova A, Meyerhans A, Bocharov G. Intracellular Life Cycle Kinetics of SARS-CoV-2 Predicted Using Mathematical Modelling. Viruses 2021; 13:1735. [PMID: 34578317 PMCID: PMC8473439 DOI: 10.3390/v13091735] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 12/15/2022] Open
Abstract
SARS-CoV-2 infection represents a global threat to human health. Various approaches were employed to reveal the pathogenetic mechanisms of COVID-19. Mathematical and computational modelling is a powerful tool to describe and analyze the infection dynamics in relation to a plethora of processes contributing to the observed disease phenotypes. In our study here, we formulate and calibrate a deterministic model of the SARS-CoV-2 life cycle. It provides a kinetic description of the major replication stages of SARS-CoV-2. Sensitivity analysis of the net viral progeny with respect to model parameters enables the identification of the life cycle stages that have the strongest impact on viral replication. These three most influential parameters are (i) degradation rate of positive sense vRNAs in cytoplasm (negative effect), (ii) threshold number of non-structural proteins enhancing vRNA transcription (negative effect), and (iii) translation rate of non-structural proteins (positive effect). The results of our analysis could be used for guiding the search for antiviral drug targets to combat SARS-CoV-2 infection.
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Affiliation(s)
- Dmitry Grebennikov
- Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), 119333 Moscow, Russia;
- Moscow Center for Fundamental and Applied Mathematics at INM RAS, 119333 Moscow, Russia
- World-Class Research Center “Digital Biodesign and Personalized Healthcare”, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - Ekaterina Kholodareva
- Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), 119333 Moscow, Russia;
- Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, 141701 Moscow Oblast, Russia
| | - Igor Sazonov
- College of Engineering, Swansea University, Bay Campus, Fabian Way, Swansea SA1 8EN, UK;
| | - Antonina Karsonova
- Department of Clinical Immunology and Allergology, Sechenov First Moscow State Medical University, 119991 Moscow, Russia;
| | - Andreas Meyerhans
- Infection Biology Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain;
- ICREA, Pg. Lluis Companys 23, 08010 Barcelona, Spain
| | - Gennady Bocharov
- Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), 119333 Moscow, Russia;
- Moscow Center for Fundamental and Applied Mathematics at INM RAS, 119333 Moscow, Russia
- Institute of Computer Science and Mathematical Modelling, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
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35
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Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell. MATHEMATICS 2021. [DOI: 10.3390/math9172025] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Replication of Human Immunodeficiency Virus type 1 (HIV) in infected CD4+ T cells represents a key driver of HIV infection. The HIV life cycle is characterised by the heterogeneity of infected cells with respect to multiplicity of infection and the variability in viral progeny. This heterogeneity can result from the phenotypic diversity of infected cells as well as from random effects and fluctuations in the kinetics of biochemical reactions underlying the virus replication cycle. To quantify the contribution of stochastic effects to the variability of HIV life cycle kinetics, we propose a high-resolution mathematical model formulated as a Markov chain jump process. The model is applied to generate the statistical characteristics of the (i) cell infection multiplicity, (ii) cooperative nature of viral replication, and (iii) variability in virus secretion by phenotypically identical cells. We show that the infection with a fixed number of viruses per CD4+ T cell leads to some heterogeneity of infected cells with respect to the number of integrated proviral genomes. The bottleneck factors in the virus production are identified, including the Gag-Pol proteins. Sensitivity analysis enables ranking of the model parameters with respect to the strength of their impact on the size of viral progeny. The first three globally influential parameters are the transport of genomic mRNA to membrane, the tolerance of transcription activation to Tat-mediated regulation, and the degradation of free and mature virions. These can be considered as potential therapeutical targets.
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36
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Sotoudegan MS, Arnold JJ, Cameron CE. Single-cell analysis for the study of viral inhibitors. Enzymes 2021; 49:195-213. [PMID: 34696832 DOI: 10.1016/bs.enz.2021.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Stochastic outcomes of viral infections are attributed in large part to multiple layers of intrinsic and extrinsic heterogeneity that exist within a population of cells and viruses. Traditional methods in virology often lack the ability to demonstrate cell-to-cell variability in response to the invasion of viruses, and to decipher the sources of heterogeneities that are reflected in the variable infection dynamics. To overcome this challenge, the field of single-cell virology emerged less than a decade ago, enabling researchers to reveal the behavior of single, isolated, infected cells that has been masked in population-based assays. The use of microfluidics in single-cell virology, in particular, has resulted in the development of high-throughput devices that are capable of capturing, isolating, and monitoring single infected cells over the duration of an infection. Results from the studies of viral infection dynamics presented in this chapter indicate how single-cell data provide a more accurate prediction of the start time, replication rate, duration, and yield of infection when compared to population-based data. Additionally, single-cell analysis reveals striking differences between genetically distinct viruses that are almost indistinguishable in population methods. Importantly, both the efficacy and distinct mechanisms of action of antiviral compounds can be elucidated by using single-cell analysis.
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Affiliation(s)
- Mohamad S Sotoudegan
- Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, NC, United States
| | - Jamie J Arnold
- Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, NC, United States
| | - Craig E Cameron
- Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, NC, United States.
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37
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Suomalainen M, Greber UF. Virus Infection Variability by Single-Cell Profiling. Viruses 2021; 13:1568. [PMID: 34452433 PMCID: PMC8402812 DOI: 10.3390/v13081568] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 07/30/2021] [Accepted: 08/05/2021] [Indexed: 12/15/2022] Open
Abstract
Cell-to-cell variability of infection has long been known, yet it has remained one of the least understood phenomena in infection research. It impacts on disease onset and development, yet only recently underlying mechanisms have been studied in clonal cell cultures by single-virion immunofluorescence microscopy and flow cytometry. In this review, we showcase how single-cell RNA sequencing (scRNA-seq), single-molecule RNA-fluorescence in situ hybridization (FISH), and copper(I)-catalyzed azide-alkyne cycloaddition (click) with alkynyl-tagged viral genomes dissect infection variability in human and mouse cells. We show how the combined use of scRNA-FISH and click-chemistry reveals highly variable onsets of adenoviral gene expression, and how single live cell plaques reveal lytic and nonlytic adenovirus transmissions. The review highlights how scRNA-seq profiling and scRNA-FISH of coxsackie, influenza, dengue, zika, and herpes simplex virus infections uncover transcriptional variability, and how the host interferon response tunes influenza and sendai virus infections. We introduce the concept of "cell state" in infection variability, and conclude with advances by single-cell simultaneous measurements of chromatin accessibility and mRNA counts at high-throughput. Such technology will further dissect the sequence of events in virus infection and pathology, and better characterize the genetic and genomic stability of viruses, cell autonomous innate immune responses, and mechanisms of tissue injury.
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Affiliation(s)
- Maarit Suomalainen
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Urs F. Greber
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
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38
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Leander RN, Wu Y, Ding W, Nelson DE, Sinkala Z. A model of the innate immune response to SARS-CoV-2 in the alveolar epithelium. ROYAL SOCIETY OPEN SCIENCE 2021; 8:210090. [PMID: 34430043 PMCID: PMC8355678 DOI: 10.1098/rsos.210090] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 07/19/2021] [Indexed: 05/15/2023]
Abstract
We present a differential equation model of the innate immune response to SARS-CoV-2 within the alveolar epithelium. Critical determinants of the viral dynamics and host response, including type I and type II alveolar epithelial cells, interferons, chemokines, toxins and innate immune cells, are included. We estimate model parameters, compute the within-host basic reproductive number, and study the impacts of therapies, prophylactics, and host/pathogen variability on the course of the infection. Model simulations indicate that the innate immune response suppresses the infection and enables the alveolar epithelium to partially recover. While very robust antiviral therapy controls the infection and enables the epithelium to heal, moderate therapy is of limited benefit. Meanwhile interferon therapy is predicted to reduce viral load but exacerbate tissue damage. The deleterious effects of interferon therapy are especially apparent late in the infection. Individual variation in ACE2 expression, epithelial cell interferon production, and SARS-CoV-2 spike protein binding affinity are predicted to significantly impact prognosis.
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Affiliation(s)
- R. N. Leander
- Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro 37132-0002, USA
| | - Y. Wu
- Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro 37132-0002, USA
| | - W. Ding
- Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro 37132-0002, USA
| | - D. E. Nelson
- Department of Biology, Middle Tennessee State University, Murfreesboro 37132-0002, USA
| | - Z. Sinkala
- Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro 37132-0002, USA
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39
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Abstract
Despite their simplicity, viruses exhibit certain types of social interactions. Situations in which a given virus achieves higher fitness in combination with other members of the viral population have been described at the level of transmission, replication, suppression of host immune responses, and host killing, enabling the evolution of viral cooperation. Although cellular coinfection with multiple viral particles is the typical playground for these interactions, cooperation between viruses infecting different cells is also established through cellular and viral-encoded communication systems. In general, the stability of cooperation is compromised by cheater genotypes, as best exemplified by defective interfering particles. As predicted by social evolution theory, cheater invasion can be avoided when cooperators interact preferentially with other cooperators, a situation that is promoted in spatially structured populations. Processes such as transmission bottlenecks, organ compartmentalization, localized spread of infection foci, superinfection exclusion, and even discrete intracellular replication centers promote multilevel spatial structuring in viruses. Expected final online publication date for the Annual Review of Virology, Volume 8 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Rafael Sanjuán
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas and Universitat de València, 46980 Paterna, València, Spain;
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40
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Gregg RW, Shabnam F, Shoemaker JE. Agent-based modeling reveals benefits of heterogeneous and stochastic cell populations during cGAS-mediated IFNβ production. Bioinformatics 2021; 37:1428-1434. [PMID: 33196784 DOI: 10.1093/bioinformatics/btaa969] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 10/13/2020] [Accepted: 11/04/2020] [Indexed: 01/25/2023] Open
Abstract
MOTIVATION The cGAS pathway is a component of the innate immune system responsible for the detection of pathogenic DNA and upregulation of interferon beta (IFNβ). Experimental evidence shows that IFNβ signaling occurs in highly heterogeneous cells and is stochastic in nature; however, the benefits of these attributes remain unclear. To investigate how stochasticity and heterogeneity affect IFNβ production, an agent-based model is developed to simulate both DNA transfection and viral infection. RESULTS We show that heterogeneity can enhance IFNβ responses during infection. Furthermore, by varying the degree of IFNβ stochasticity, we find that only a percentage of cells (20-30%) need to respond during infection. Going beyond this range provides no additional protection against cell death or reduction of viral load. Overall, these simulations suggest that heterogeneity and stochasticity are important for moderating immune potency while minimizing cell death during infection. AVAILABILITY AND IMPLEMENTATION Model repository is available at: https://github.com/ImmuSystems-Lab/AgentBasedModel-cGASPathway. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Robert W Gregg
- Department of Chemical and Petroleum Engineering, 15260, Pittsburgh, PA 15260, USA
| | - Fathima Shabnam
- Department of Chemical and Petroleum Engineering, 15260, Pittsburgh, PA 15260, USA
| | - Jason E Shoemaker
- Department of Chemical and Petroleum Engineering, 15260, Pittsburgh, PA 15260, USA.,McGowan Institute for Regenerative Medicine, 15219, Pittsburgh, PA 15260, USA.,Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
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41
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Duarte P, Riveros-Perez E. Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors. Ann Med Surg (Lond) 2021; 66:102437. [PMID: 34094532 PMCID: PMC8168336 DOI: 10.1016/j.amsu.2021.102437] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 05/21/2021] [Accepted: 05/23/2021] [Indexed: 12/23/2022] Open
Abstract
The incidence curve of coronavirus disease 19 (COVID-19) shows cyclical patterns over time. We examine the cyclical properties of the incidence curves in various countries and use principal components analysis to shed light on the underlying dynamics that are common to all countries. We find that the cyclical series of 37 countries can be summarized in four principal components which explain over 90% of the variation. We also discuss the influence of complex interactions between biological viral natural history and socio-political reactions and measures adopted by different countries on the cyclical patterns exhibited by COVID-19 around the globe.
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Affiliation(s)
- Pablo Duarte
- Flossbach von Storch Research Institute, Germany
| | - Efrain Riveros-Perez
- Medical College of Georgia, Department of Anesthesiology and Perioperative Medicine, USA
- Outcomes Research Consortium. Cleveland Clinic, USA
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42
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Modeling poliovirus replication dynamics from live time-lapse single-cell imaging data. Sci Rep 2021; 11:9622. [PMID: 33953215 PMCID: PMC8100109 DOI: 10.1038/s41598-021-87694-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 03/15/2021] [Indexed: 02/03/2023] Open
Abstract
Viruses experience selective pressure on the timing and order of events during infection to maximize the number of viable offspring they produce. Additionally, they may experience variability in cellular environments encountered, as individual eukaryotic cells can display variation in gene expression among cells. This leads to a dynamic phenotypic landscape that viruses must face to replicate. To examine replication dynamics displayed by viruses faced with this variable landscape, we have developed a method for fitting a stochastic mechanistic model of viral infection to time-lapse imaging data from high-throughput single-cell poliovirus infection experiments. The model's mechanistic parameters provide estimates of several aspects associated with the virus's intracellular dynamics. We examine distributions of parameter estimates and assess their variability to gain insight into the root causes of variability in viral growth dynamics. We also fit our model to experiments performed under various drug treatments and examine which parameters differ under these conditions. We find that parameters associated with translation and early stage viral replication processes are essential for the model to capture experimentally observed dynamics. In aggregate, our results suggest that differences in viral growth data generated under different treatments can largely be captured by steps that occur early in the replication process.
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43
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Singer ZS, Ambrose PM, Danino T, Rice CM. Quantitative measurements of early alphaviral replication dynamics in single cells reveals the basis for superinfection exclusion. Cell Syst 2021; 12:210-219.e3. [PMID: 33515490 PMCID: PMC9143976 DOI: 10.1016/j.cels.2020.12.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 09/10/2020] [Accepted: 12/30/2020] [Indexed: 12/20/2022]
Abstract
While decades of research have elucidated many steps of the alphavirus lifecycle, the earliest replication dynamics have remained unclear. This missing time window has obscured early replicase strand-synthesis behavior and prevented elucidation of how the first events of infection might influence subsequent viral competition. Using quantitative live-cell and single-molecule imaging, we observed the initial replicase activity and its strand preferences in situ and measured the trajectory of replication over time. Under this quantitative framework, we investigated viral competition, where one alphavirus is able to exclude superinfection by a second homologous virus. We show that this appears as an indirect phenotypic consequence of a bidirectional competition between the two species, coupled with the rapid onset of viral replication and a limited total cellular carrying capacity. Together, these results emphasize the utility of analyzing viral kinetics within single cells.
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Affiliation(s)
- Zakary S Singer
- Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA; Laboratory of Virology and Infectious Disease, The Rockefeller University, New York, NY 10065, USA
| | - Pradeep M Ambrose
- Laboratory of Virology and Infectious Disease, The Rockefeller University, New York, NY 10065, USA; Department of Physiology, Biophysics, and Systems Biology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Tal Danino
- Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA; Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY 10027, USA; Data Science Institute, Columbia University, New York, NY 10027, USA.
| | - Charles M Rice
- Laboratory of Virology and Infectious Disease, The Rockefeller University, New York, NY 10065, USA.
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44
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Loveday EK, Zath GK, Bikos DA, Jay ZJ, Chang CB. Screening of Additive Formulations Enables Off-Chip Drop Reverse Transcription Quantitative Polymerase Chain Reaction of Single Influenza A Virus Genomes. Anal Chem 2021; 93:4365-4373. [PMID: 33635052 PMCID: PMC10016143 DOI: 10.1021/acs.analchem.0c03455] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
The miniaturization of polymerase chain reaction (PCR) using drop-based microfluidics allows for amplification of single nucleic acids in aqueous picoliter-sized drops. Accurate data collection during PCR requires that drops remain stable to coalescence during thermocycling and drop contents are retained. Following systematic testing of known PCR additives, we identified an optimized formulation of 1% w/v Tween-20, 0.8 μg/μL bovine serum albumin, 1 M betaine in the aqueous phase, and 3 wt % (w/w) of the polyethylene glycol-perfluoropolyether2 surfactant in the oil phase of 50 μm diameter drops that maintains drop stability and prevents dye transport. This formulation enables a method we call off-chip drop reverse transcription quantitative PCR (OCD RT-qPCR) in which drops are thermocycled in a qPCR machine and sampled at various cycle numbers "off-chip", or outside of a microfluidic chip. qPCR amplification curves constructed from hundreds of individual drops using OCD RT-qPCR and imaged using epifluorescence microscopy correlate with amplification curves of ≈300,000 drops thermocycled using a qPCR machine. To demonstrate the utility of OCD RT-qPCR, influenza A virus (IAV) RNA was detected down to a single viral genome copy per drop, or 0.320 cpd. This work was extended to perform multiplexed detection of IAV M gene RNA and cellular β-actin DNA in drops, and direct amplification of IAV genomes from infected cells without a separate RNA extraction step. The optimized additive formulation and the OCD-qPCR method allow for drop-based RT-qPCR without complex devices and demonstrate the ability to quantify individual or rare nucleic acid species within drops with minimal processing.
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Affiliation(s)
- Emma Kate Loveday
- Center for Biofilm Engineering and the Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana 59717, United States
| | - Geoffrey K Zath
- Center for Biofilm Engineering and the Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana 59717, United States
| | - Dimitri A Bikos
- Center for Biofilm Engineering and the Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana 59717, United States
| | - Zackary J Jay
- Department of Chemistry and Biochemistry, Montana State University, Bozeman, Montana 59717, United States
| | - Connie B Chang
- Center for Biofilm Engineering and the Department of Chemical and Biological Engineering, Montana State University, Bozeman, Montana 59717, United States
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45
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Hortsch SK, Kremling A. Stochastic Models for Studying the Role of Cellular Noise and Heterogeneity. SYSTEMS MEDICINE 2021. [DOI: 10.1016/b978-0-12-801238-3.11466-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
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46
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Andreu-Moreno I, Bou JV, Sanjuán R. Cooperative nature of viral replication. SCIENCE ADVANCES 2020; 6:6/49/eabd4942. [PMID: 33277258 PMCID: PMC7821885 DOI: 10.1126/sciadv.abd4942] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 10/21/2020] [Indexed: 06/12/2023]
Abstract
The ability of viruses to infect their hosts depends on rapid dissemination following transmission. The notion that viral particles function as independent propagules has been challenged by recent observations suggesting that viral aggregates show enhanced infectivity and faster spread. However, these observations remain poorly understood. Here, we show that viral replication is a cooperative process, such that entry of multiple viral genome copies into the same cell disproportionately increases short-term viral progeny production. This cooperativity arises from the positive feedback established between replication templates and virus-encoded products involved in replication and should be a general feature of viruses. We develop a simple model that captures this effect, verify that cooperativity also emerges in more complex models for specific human viruses, validate our predictions experimentally using different mammalian viruses, and discuss the implications of cooperative replication for viral fitness.
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Affiliation(s)
- Iván Andreu-Moreno
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas-Universitat de València, C/ Catedrático Agustín Escardino 9, 46980 Paterna, València, Spain
| | - Juan-Vicente Bou
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas-Universitat de València, C/ Catedrático Agustín Escardino 9, 46980 Paterna, València, Spain
| | - Rafael Sanjuán
- Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Científicas-Universitat de València, C/ Catedrático Agustín Escardino 9, 46980 Paterna, València, Spain.
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47
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Suomalainen M, Prasad V, Kannan A, Greber UF. Cell-to-cell and genome-to-genome variability of adenovirus transcription tuned by the cell cycle. J Cell Sci 2020; 134:jcs252544. [PMID: 32917739 DOI: 10.1242/jcs.252544] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 08/27/2020] [Indexed: 12/11/2022] Open
Abstract
In clonal cultures, not all cells are equally susceptible to virus infection, and the mechanisms underlying this are poorly understood. Here, we developed image-based single-cell measurements to scrutinize the heterogeneity of adenovirus (AdV) infection. AdV delivers, transcribes and replicates a linear double-stranded DNA genome in the nucleus. We measured the abundance of viral transcripts using single-molecule RNA fluorescence in situ hybridization (FISH) and the incoming 5-ethynyl-2'-deoxycytidine (EdC)-tagged viral genomes using a copper(I)-catalyzed azide-alkyne cycloaddition (click) reaction. Surprisingly, expression of the immediate early gene E1A only moderately correlated with the number of viral genomes in the cell nucleus. Intranuclear genome-to-genome heterogeneity was found at the level of viral transcription and, in accordance, individual genomes exhibited heterogeneous replication activity. By analyzing the cell cycle state, we found that G1 cells exhibited the highest E1A gene expression and displayed increased correlation between E1A gene expression and viral genome copy numbers. The combined image-based single-molecule procedures described here are ideally suited to explore the cell-to-cell variability in viral gene expression in a range of different settings, including the innate immune response.
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Affiliation(s)
- Maarit Suomalainen
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Vibhu Prasad
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Abhilash Kannan
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
| | - Urs F Greber
- Department of Molecular Life Sciences, University of Zurich, 8057 Zurich, Switzerland
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48
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Brzostek J, Fatin A, Chua WH, Tan HY, Dick T, Gascoigne NRJ. Single Cell Analysis of Drug Susceptibility of Mycobacterium Abscessus During Macrophage Infection. Antibiotics (Basel) 2020; 9:antibiotics9100711. [PMID: 33080864 PMCID: PMC7650608 DOI: 10.3390/antibiotics9100711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 10/15/2020] [Accepted: 10/16/2020] [Indexed: 11/16/2022] Open
Abstract
Mycobacterium abscessus is an emerging health risk to immunocompromised individuals and to people with pre-existing pulmonary conditions. As M. abscessus possesses multiple mechanisms of drug resistance, treatments of M. abscessus are of poor efficacy. Therefore, there is an urgent need for new therapeutic strategies targeting M. abscessus. We describe an experimental system for screening of compounds for their antimicrobial activity against intracellular M. abscessus using flow cytometry and imaging flow cytometry. The assay allows simultaneous analysis of multiple parameters, such as proportion of infected host cells, bacterial load per host cell from the infected population, and host cell viability. We verified the suitability of this method using two antibiotics with known activity against M. abscessus: clarithromycin and amikacin. Our analysis revealed a high degree of infection heterogeneity, which correlated with host cell size. A higher proportion of the larger host cells is infected with M. abscessus as compared to smaller host cells, and infected larger cells have higher intracellular bacterial burden than infected smaller cells. Clarithromycin treatment has a more pronounced effect on smaller host cells than on bigger host cells, suggesting that heterogeneity within the host cell population has an effect on antibiotic susceptibility of intracellular bacteria.
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Affiliation(s)
- Joanna Brzostek
- Department of Microbiology and Immunology, Yong Loo Lin School of Medcine, National University of Singapore, 5 Science Drive 2, Singapore 117545, Singapore; (A.F.); (W.H.C.); (H.Y.T.); (T.D.)
- Correspondence: (J.B.); (N.R.J.G.)
| | - Amierah Fatin
- Department of Microbiology and Immunology, Yong Loo Lin School of Medcine, National University of Singapore, 5 Science Drive 2, Singapore 117545, Singapore; (A.F.); (W.H.C.); (H.Y.T.); (T.D.)
| | - Wen Hui Chua
- Department of Microbiology and Immunology, Yong Loo Lin School of Medcine, National University of Singapore, 5 Science Drive 2, Singapore 117545, Singapore; (A.F.); (W.H.C.); (H.Y.T.); (T.D.)
| | - Hui Yi Tan
- Department of Microbiology and Immunology, Yong Loo Lin School of Medcine, National University of Singapore, 5 Science Drive 2, Singapore 117545, Singapore; (A.F.); (W.H.C.); (H.Y.T.); (T.D.)
| | - Thomas Dick
- Department of Microbiology and Immunology, Yong Loo Lin School of Medcine, National University of Singapore, 5 Science Drive 2, Singapore 117545, Singapore; (A.F.); (W.H.C.); (H.Y.T.); (T.D.)
- Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, NJ 07110, USA
- Department of Medical Sciences, Hackensack Meridian School of Medicine at Seton Hall University, Nutley, NJ 07110, USA
| | - Nicholas R. J. Gascoigne
- Department of Microbiology and Immunology, Yong Loo Lin School of Medcine, National University of Singapore, 5 Science Drive 2, Singapore 117545, Singapore; (A.F.); (W.H.C.); (H.Y.T.); (T.D.)
- Immunology Programme, Life Sciences Institute, National University of Singapore, Singapore 117545, Singapore
- Correspondence: (J.B.); (N.R.J.G.)
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Martin BE, Harris JD, Sun J, Koelle K, Brooke CB. Cellular co-infection can modulate the efficiency of influenza A virus production and shape the interferon response. PLoS Pathog 2020; 16:e1008974. [PMID: 33064776 PMCID: PMC7592918 DOI: 10.1371/journal.ppat.1008974] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 10/28/2020] [Accepted: 09/10/2020] [Indexed: 12/19/2022] Open
Abstract
During viral infection, the numbers of virions infecting individual cells can vary significantly over time and space. The functional consequences of this variation in cellular multiplicity of infection (MOI) remain poorly understood. Here, we rigorously quantify the phenotypic consequences of cellular MOI during influenza A virus (IAV) infection over a single round of replication in terms of cell death rates, viral output kinetics, interferon and antiviral effector gene transcription, and superinfection potential. By statistically fitting mathematical models to our data, we precisely define specific functional forms that quantitatively describe the modulation of these phenotypes by MOI at the single cell level. To determine the generality of these functional forms, we compare two distinct cell lines (MDCK cells and A549 cells), both infected with the H1N1 strain A/Puerto Rico/8/1934 (PR8). We find that a model assuming that infected cell death rates are independent of cellular MOI best fits the experimental data in both cell lines. We further observe that a model in which the rate and efficiency of virus production increase with cellular co-infection best fits our observations in MDCK cells, but not in A549 cells. In A549 cells, we also find that induction of type III interferon, but not type I interferon, is highly dependent on cellular MOI, especially at early timepoints. This finding identifies a role for cellular co-infection in shaping the innate immune response to IAV infection. Finally, we show that higher cellular MOI is associated with more potent superinfection exclusion, thus limiting the total number of virions capable of infecting a cell. Overall, this study suggests that the extent of cellular co-infection by influenza viruses may be a critical determinant of both viral production kinetics and cellular infection outcomes in a host cell type-dependent manner. During influenza A virus (IAV) infection, the number of virions to enter individual cells can be highly variable. Cellular co-infection appears to be common and plays an essential role in facilitating reassortment for IAV, yet little is known about how cellular co-infection influences infection outcomes at the cellular level. Here, we combine quantitative in vitro infection experiments with statistical model fitting to precisely define the phenotypic consequences of cellular co-infection in two cell lines. We reveal that cellular co-infection can increase and accelerate the efficiency of IAV production in a cell line-dependent fashion, identifying it as a potential determinant of viral replication kinetics. We also show that induction of type III, but not type I, interferon is highly dependent upon the number of virions that infect a given cell, implicating cellular co-infection as an important determinant of the host innate immune response to infection. Altogether, our findings show that cellular co-infection plays a crucial role in determining infection outcome. The integration of experimental and statistical modeling approaches detailed here represents a significant advance in the quantitative study of influenza virus infection and should aid ongoing efforts focused on the construction of mathematical models of IAV infection.
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Affiliation(s)
- Brigitte E. Martin
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Jeremy D. Harris
- Department of Biology, Emory University, Atlanta, GA, United States of America
| | - Jiayi Sun
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, GA, United States of America
- * E-mail: (KK); (CB)
| | - Christopher B. Brooke
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, United States of America
- * E-mail: (KK); (CB)
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Jones JE, Le Sage V, Lakdawala SS. Viral and host heterogeneity and their effects on the viral life cycle. Nat Rev Microbiol 2020; 19:272-282. [PMID: 33024309 PMCID: PMC7537587 DOI: 10.1038/s41579-020-00449-9] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/03/2020] [Indexed: 02/08/2023]
Abstract
Traditionally, the viral replication cycle is envisioned as a single, well-defined loop with four major steps: attachment and entry into a target cell, replication of the viral genome, maturation of viral proteins and genome packaging into infectious progeny, and egress and dissemination to the next target cell. However, for many viruses, a growing body of evidence points towards extreme heterogeneity in each of these steps. In this Review, we reassess the major steps of the viral replication cycle by highlighting recent advances that show considerable variability during viral infection. First, we discuss heterogeneity in entry receptors, followed by a discussion on error-prone and low-fidelity polymerases and their impact on viral diversity. Next, we cover the implications of heterogeneity in genome packaging and assembly on virion morphology. Last, we explore alternative egress mechanisms, including tunnelling nanotubes and host microvesicles. In summary, we discuss the implications of viral phenotypic, morphological and genetic heterogeneity on pathogenesis and medicine. This Review highlights common themes and unique features that give nuance to the viral replication cycle.
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Affiliation(s)
- Jennifer E Jones
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Valerie Le Sage
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Seema S Lakdawala
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. .,Center for Vaccine Research, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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