scholarly journals Mathematical Model for the Intracellular Kinetics of Influenza a Virus Replication in Vitro

2021 ◽  
Author(s):  
Diana Schwendener Forkel
Keyword(s):  
Influenza A Virus ◽  
Virus Replication ◽  
Influenza A ◽  
Infection Process ◽  
Treatment Modalities ◽  
Viral Production ◽  
A Cell ◽  
Basic Biology ◽  
Kinetics Of

In the last twenty years, mathematical modelling (MM) has been notably used to capture the infection kinetics of many infectious diseases as it allows insights into the basic biology, infection kinetics, and the mechanisms and efficacy of treatment modalities. MMs of influenza A virus (IAV) infection usually represent the process of virus replication within a cell as a ‘black box’ term for viral production. The simplification is appropriate when we are not interested in the microscopic details of infection. Recently though, MMs have begun to account for the kinetics of intracellular IAV replication. Herein, we examine the MM by Heldt et al., which is able to capture kinetics of IAV infection. It however, does so by adjusting parameters of the MM to various events in the infection process. We developed a robust, yet concise, MM for the intracellular kinetics of influenza A virus infection in vitro with a consistent set of parameters. We use attachment, fusion and RNA data gathered from literature sources to validate our simplified MM and match known infection kinetics consistent throughout infection.

scholarly journals Mathematical Model for the Intracellular Kinetics of Influenza a Virus Replication in Vitro

2021 ◽  
Author(s):  
Diana Schwendener Forkel
Keyword(s):  
Influenza A Virus ◽  
Virus Replication ◽  
Influenza A ◽  
Infection Process ◽  
Treatment Modalities ◽  
Viral Production ◽  
A Cell ◽  
Basic Biology ◽  
Kinetics Of

In the last twenty years, mathematical modelling (MM) has been notably used to capture the infection kinetics of many infectious diseases as it allows insights into the basic biology, infection kinetics, and the mechanisms and efficacy of treatment modalities. MMs of influenza A virus (IAV) infection usually represent the process of virus replication within a cell as a ‘black box’ term for viral production. The simplification is appropriate when we are not interested in the microscopic details of infection. Recently though, MMs have begun to account for the kinetics of intracellular IAV replication. Herein, we examine the MM by Heldt et al., which is able to capture kinetics of IAV infection. It however, does so by adjusting parameters of the MM to various events in the infection process. We developed a robust, yet concise, MM for the intracellular kinetics of influenza A virus infection in vitro with a consistent set of parameters. We use attachment, fusion and RNA data gathered from literature sources to validate our simplified MM and match known infection kinetics consistent throughout infection.

scholarly journals Pretreatment of Epithelial Cells with Live Streptococcus pneumoniae Has No Detectable Effect on Influenza A Virus Replication In Vitro

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e90066 ◽  
Author(s):  
Kang Ouyang ◽  
Shireen A. Woodiga ◽  
Varun Dwivedi ◽  
Carolyn M. Buckwalter ◽  
Anirudh K. Singh ◽  
...  
Keyword(s):  
Streptococcus Pneumoniae ◽  
Epithelial Cells ◽  
Influenza A Virus ◽  
Virus Replication ◽  
Influenza A ◽  
Detectable Effect

scholarly journals Mathematical models of Influenza A. virus infections in vitro: Invesigating defective interfering particles and virus release

2021 ◽  
Author(s):  
Laura Liao
Keyword(s):  
Mathematical Models ◽  
Influenza A Virus ◽  
Release Rate ◽  
Influenza A ◽  
Quantitative Methods ◽  
Virus Release ◽  
Virus Infections ◽  
Defective Interfering Particles ◽  
A Cell

In this work, two studies were performed where mathematical models (MM) were used to re-examine and refine quantitative methods based on in vitro assays of influenza A virus infections. In the first study, we investigated the standard experimental method for counting defective interfering particles (DIPs) based on the reduction in standard virus (STV) yield (Bellett & Cooper, 1959). We found the method is valid for counting DIPs provided that: (1) a STV-infected cell’s co-infection window is approximately half its eclipse phase (it blocks infection by other virions before it begins producing progeny virions); (2) a cell co-infected by STV and DIP produces less than 1 STV per 1,000 DIPs; and (3) a high MOI of STV stock (>4 plaque-forming units/cell) is added to perform the assay. Prior work makes no mention of these criteria such that the counting method has been applied incorrectly in several publications discussed herein. We determined influenza A virus meets these criteria, making the method suitable for counting influenza A DIPs. In the second study, we compared a MM with an explicit representation of viral release to a simple MM without explicit release, and investigated whether parameter estimation and the estimation of neuraminidase inhibitor (NAI) efficacy were affected by the use of a simple MM. Since the release rate of influenza A virus is not well-known, a broad range of release rates were considered. If the virus release rate is greater than ∼0.1 h−1, the simple MM provides accurate estimates of infection parameters, but underestimates NAI efficacy, which could lead to underdosing and the emergence of NAI resistance. In contrast, when release is slower than ∼0.1 h−1, the simple MM accurately estimates NAI efficacy, but it can significantly overestimate the infectious lifespan (i.e., the time a cell remains infectious and producing free virus), and it will significantly underestimate the total virus yield and thus the likelihood of resistance emergence. We discuss the properties of, and a possible lower bound for, the influenza A virus release rate. Overall, MMs are a valuable tool in the exploration of the known unknowns (i.e., DIPs, virus release) of influenza A virus infection.

scholarly journals Mathematical models of Influenza A. virus infections in vitro: Invesigating defective interfering particles and virus release

2021 ◽  
Author(s):  
Laura Liao
Keyword(s):  
Mathematical Models ◽  
Influenza A Virus ◽  
Release Rate ◽  
Influenza A ◽  
Quantitative Methods ◽  
Virus Release ◽  
Virus Infections ◽  
Defective Interfering Particles ◽  
A Cell

In this work, two studies were performed where mathematical models (MM) were used to re-examine and refine quantitative methods based on in vitro assays of influenza A virus infections. In the first study, we investigated the standard experimental method for counting defective interfering particles (DIPs) based on the reduction in standard virus (STV) yield (Bellett & Cooper, 1959). We found the method is valid for counting DIPs provided that: (1) a STV-infected cell’s co-infection window is approximately half its eclipse phase (it blocks infection by other virions before it begins producing progeny virions); (2) a cell co-infected by STV and DIP produces less than 1 STV per 1,000 DIPs; and (3) a high MOI of STV stock (>4 plaque-forming units/cell) is added to perform the assay. Prior work makes no mention of these criteria such that the counting method has been applied incorrectly in several publications discussed herein. We determined influenza A virus meets these criteria, making the method suitable for counting influenza A DIPs. In the second study, we compared a MM with an explicit representation of viral release to a simple MM without explicit release, and investigated whether parameter estimation and the estimation of neuraminidase inhibitor (NAI) efficacy were affected by the use of a simple MM. Since the release rate of influenza A virus is not well-known, a broad range of release rates were considered. If the virus release rate is greater than ∼0.1 h−1, the simple MM provides accurate estimates of infection parameters, but underestimates NAI efficacy, which could lead to underdosing and the emergence of NAI resistance. In contrast, when release is slower than ∼0.1 h−1, the simple MM accurately estimates NAI efficacy, but it can significantly overestimate the infectious lifespan (i.e., the time a cell remains infectious and producing free virus), and it will significantly underestimate the total virus yield and thus the likelihood of resistance emergence. We discuss the properties of, and a possible lower bound for, the influenza A virus release rate. Overall, MMs are a valuable tool in the exploration of the known unknowns (i.e., DIPs, virus release) of influenza A virus infection.

scholarly journals p-STAT1 regulates the influenza A virus replication and inflammatory response in vitro and vivo

Virology ◽  
2019 ◽  
Vol 537 ◽  
pp. 110-120 ◽  
Author(s):  
Shouping Zhang ◽  
Caiyun Huo ◽  
Jin Xiao ◽  
Tao Fan ◽  
Shumei Zou ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Influenza A Virus ◽  
Virus Replication ◽  
Influenza A

scholarly journals In Vitro System for Modeling Influenza A Virus Resistance under Drug Pressure

2010 ◽  
Vol 54 (8) ◽  
pp. 3442-3450 ◽  
Author(s):  
Ashley N. Brown ◽  
James J. McSharry ◽  
Qingmei Weng ◽  
Elizabeth M. Driebe ◽  
David M. Engelthaler ◽  
...  
Keyword(s):  
Influenza Virus ◽  
Influenza A Virus ◽  
Virus Replication ◽  
Influenza A ◽  
Mdck Cells ◽  
Influenza Virus Infection ◽  
Infection Model ◽  
Virus Infections ◽  
Drug Pressure

ABSTRACT One of the biggest challenges in the effort to treat and contain influenza A virus infections is the emergence of resistance during treatment. It is well documented that resistance to amantadine arises rapidly during the course of treatment due to mutations in the gene coding for the M2 protein. To address this problem, it is critical to develop experimental systems that can accurately model the selection of resistance under drug pressure as seen in humans. We used the hollow-fiber infection model (HFIM) system to examine the effect of amantadine on the replication of influenza virus, A/Albany/1/98 (H3N2), grown in MDCK cells. At 24 and 48 h postinfection, virus replication was inhibited in a dose-dependent fashion. At 72 and 96 h postinfection, virus replication was no longer inhibited, suggesting the emergence of amantadine-resistant virus. Sequencing of the M2 gene revealed that mutations appeared at between 48 and 72 h of drug treatment and that the mutations were identical to those identified in the clinic for amantadine-resistant viruses (e.g., V27A, A30T, and S31N). Interestingly, we found that the type of mutation was strongly affected by the dose of the drug. The data suggest that the HFIM is a good model for influenza virus infection and resistance generation in humans. The HFIM has the advantage of being a highly controlled system where multiplicity parameters can be directly and accurately controlled and measured.

scholarly journals Glucosyl Hesperidin Prevents Influenza A Virus Replication in Vitro by Inhibition of Viral Sialidase

2009 ◽  
Vol 32 (7) ◽  
pp. 1188-1192 ◽  
Author(s):  
Repon Kumer Saha ◽  
Tadanobu Takahashi ◽  
Takashi Suzuki
Keyword(s):  
Influenza A Virus ◽  
Virus Replication ◽  
Influenza A

scholarly journals Engineered Small-Molecule Control of Influenza A Virus Replication

2018 ◽  
Vol 93 (1) ◽  
Author(s):  
Elizabeth J. Fay ◽  
Stephanie L. Aron ◽  
Ian A. Stone ◽  
Barbara M. Waring ◽  
Richard K. Plemper ◽  
...  
Keyword(s):  
Influenza A Virus ◽  
Virus Replication ◽  
Small Molecule ◽  
Human Population ◽  
Influenza A ◽  
Health Concern ◽  
Highly Pathogenic ◽  
Significant Safety

ABSTRACT Influenza A virus (IAV) remains a global health concern despite the availability of a seasonal vaccine. It is difficult to predict which strains will circulate during influenza season, and therefore, it is extremely challenging to test novel vaccines in the human population. To overcome this obstacle, new vaccines must be tested in challenge studies. This approach poses significant safety problems, since current pharmacological interventions for IAV are poorly efficacious. New methods are needed to enhance the safety of these challenge studies. In this study, we have generated a virus expressing a small-molecule-assisted shutoff (SMASh) tag as a safety switch for IAV replication. The addition of the SMASh tag to an essential IAV protein allows for small-molecule-mediated inhibition of replication. Treatment with this drug controls the replication of a SMASh-tagged virus in vitro and in vivo. This model for restriction of viral replication has potential for broad applications in vaccine studies, virotherapy, and basic virus research. IMPORTANCE Influenza A virus (IAV) causes significant morbidity and mortality annually worldwide, despite the availability of new formulations of the vaccine each season. There is a critical need to develop more-efficacious vaccines. However, testing novel vaccines in the human population in controlled studies is difficult due to the limited availability and efficacy of intervention strategies should the vaccine fail. There are also significant safety concerns for work with highly pathogenic IAV strains in the laboratory. Therefore, novel strategies are needed to improve the safety of vaccine studies and of research on highly pathogenic IAV. In this study, we developed an IAV strain engineered to contain a small-molecule-mediated safety switch. This tag, when attached to an essential viral protein, allows for the regulation of IAV replication in vitro and in vivo. This strategy provides a platform for the regulation of virus replication without targeting viral proteins directly.

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