Experimental and mathematical insights on the competition between poliovirus and a defective interfering genome

AbstractDuring replication, RNA virus populations accumulate genome alterations, such as mutations and deletions. The interactions between individual variants within the population can determine the fitness of the virus and, thus, the outcome of infection. We developed an ordinary differential equation model to infer the effect of the interaction between defective interfering (DI) replicons and wild-type (WT) poliovirus. We measure production of RNA and viral particles during a single infection cycle, and use these data to infer model parameters. We find that DI replicates faster than WT, but an equilibrium is established when both WT and DI compete for resources needed for RNA replication and genome encapsidation. In the presence of DI, the concentration of WT virions at cell lysis is suppressed by the factor of 5. Multiple generations within a single cell infection provide opportunities for significant inhibition of WT replication by competition with the faster replicating DI genomes.

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Experimental and mathematical insights on the interactions between poliovirus and a defective interfering genome

10.1101/2021.01.11.426198 ◽

2021 ◽

Author(s):

Yuta Shirogane ◽

Elsa Rousseau ◽

Jakub Voznica ◽

Yinghong Xiao ◽

Weiheng Su ◽

...

Keyword(s):

Rna Viruses ◽

Equation Model ◽

Model Parameters ◽

Experimental Measurements ◽

Genome Replication ◽

Virus Population ◽

Wild Type ◽

Ordinary Differential Equation Model ◽

Differential Equation Model ◽

Genome Encapsidation

1AbstractDuring replication, RNA viruses accumulate genome alterations, such as mutations and deletions. The interactions between individual variants can determine the fitness of the virus population and, thus, the outcome of infection. To investigate the effects of defective interfering genomes (DI) on wild-type (WT) poliovirus replication, we developed an ordinary differential equation model. We experimentally determined virus and DI replication during co-infection, and use these data to infer model parameters. Our model predicts, and our experimental measurements confirm, that DI replication and encapsidation are the most important determinants for the outcome of the competition. WT replication inversely correlates with DI replication. Our model predicts that genome replication and effective DI genome encapsidation are critical to effectively inhibit WT production, but an equilibrium can be established which enables WT to replicate, albeit to reduce levels.

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Experimental and mathematical insights on the interactions between poliovirus and a defective interfering genome

PLoS Pathogens ◽

10.1371/journal.ppat.1009277 ◽

2021 ◽

Vol 17 (9) ◽

pp. e1009277

Author(s):

Yuta Shirogane ◽

Elsa Rousseau ◽

Jakub Voznica ◽

Yinghong Xiao ◽

Weiheng Su ◽

...

Keyword(s):

Rna Viruses ◽

Equation Model ◽

Critical Parameters ◽

Model Parameters ◽

Experimental Measurements ◽

Genome Replication ◽

Virus Population ◽

Wild Type ◽

Ordinary Differential Equation Model ◽

Differential Equation Model

During replication, RNA viruses accumulate genome alterations, such as mutations and deletions. The interactions between individual variants can determine the fitness of the virus population and, thus, the outcome of infection. To investigate the effects of defective interfering genomes (DI) on wild-type (WT) poliovirus replication, we developed an ordinary differential equation model, which enables exploring the parameter space of the WT and DI competition. We also experimentally examined virus and DI replication kinetics during co-infection, and used these data to infer model parameters. Our model identifies, and our experimental measurements confirm, that the efficiencies of DI genome replication and encapsidation are two most critical parameters determining the outcome of WT replication. However, an equilibrium can be established which enables WT to replicate, albeit to reduced levels.

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Evaluation of the Number of Visits to Chinese Medical Institutions Using a Logistic Differential Equation Model

Complexity ◽

10.1155/2021/7943651 ◽

2021 ◽

Vol 2021 ◽

pp. 1-16

Author(s):

Xiaoxia Zhao ◽

Wei Li ◽

Yanyang Wang ◽

Lihong Jiang

Keyword(s):

Differential Equation ◽

Equilibrium Point ◽

Equilibrium Points ◽

Equation Model ◽

Positive Equilibrium ◽

Model Parameters ◽

Unknown Parameters ◽

Differential Equation Model ◽

Number Of Visits ◽

Positive Equilibrium Point

In this study, we established a two-dimensional logistic differential equation model to study the number of visits in Chinese PHCIs and hospitals based on the behavior of patients. We determine the model's equilibrium points and analyze their stability and then use China medical services data to fit the unknown parameters of the model. Finally, the sensitivity of model parameters is evaluated to determine the parameters that are susceptible to influence the system. The results indicate that the system corresponds to the zero-equilibrium point, the boundary equilibrium point, and the positive equilibrium point under different parameter conditions. We found that, in order to substantially increase visits to PHCIs, efforts should be made to improve PHCI comprehensive capacity and maximum service capacity.

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A Bayes Regularized Ordinary Differential Equation Model for the Inference of Gene Regulatory Networks

Handbook of Research on Computational Methodologies in Gene Regulatory Networks ◽

10.4018/978-1-60566-685-3.ch006 ◽

2010 ◽

pp. 139-168

Author(s):

Nicole Radde ◽

Lars Kaderali

Keyword(s):

Differential Equation ◽

Ordinary Differential Equation ◽

Regulatory Networks ◽

Quantitative Description ◽

Simulated Data ◽

Equation Model ◽

Model Parameters ◽

Ordinary Differential Equation Model ◽

Differential Equation Model ◽

Stochastic Framework

Differential equation models provide a detailed, quantitative description of transcription regulatory networks. However, due to the large number of model parameters, they are usually applicable to small networks only, with at most a few dozen genes. Moreover, they are not well suited to deal with noisy data. In this chapter, we show how to circumvent these limitations by integrating an ordinary differential equation model into a stochastic framework. The resulting model is then embedded into a Bayesian learning approach. We integrate the-biologically motivated-expectation of sparse connectivity in the network into the inference process using a specifically defined prior distribution on model parameters. The approach is evaluated on simulated data and a dataset of the transcriptional network governing the yeast cell cycle.

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Identification of a baculovirus polyhedron formation mutant with a novel phenotype

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100166440 ◽

1996 ◽

Vol 54 ◽

pp. 796-797

Author(s):

James M. Slavicek ◽

Melissa J. Mercer ◽

Mary Ellen Kelly

Keyword(s):

Viral Gene ◽

Gene Products ◽

Type Number ◽

Infection Cycle ◽

Wild Type ◽

Protein Matrix ◽

Insect Midgut ◽

Viral Particles ◽

Budded Virus ◽

Viral Form

Nucleopolyhedroviruses (NPV, family Baculoviridae) produce two morphological forms, a budded virus form and a viral form that is occluded into a paracrystalline protein matrix. This structure is termed a polyhedron and is composed primarily of the protein polyhedrin. Insects are infected by NPVs after ingestion of the polyhedron and release of the occluded virions through dissolution of the polyhedron in the alkaline environment of the insect midgut. Early after infection the budded virus form is produced. It buds through the plasma membrane and then infects other cells. Later in the infection cycle the occluded form of the virus is generated (reviewed by Blissard and Rohrmann, 1990).The processes of polyhedron formation and virion occlusion are likely to involve a number of viral gene products. However, only two genes, the polyhedrin gene and 25K FP gene, have been identified to date that are necessary for the wild type number of polyhedra to be formed and viral particles occluded.

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A fractional differential equation model for the COVID-19 transmission by using the Caputo–Fabrizio derivative

Advances in Difference Equations ◽

10.1186/s13662-020-02762-2 ◽

2020 ◽

Vol 2020 (1) ◽

Cited By ~ 22

Author(s):

Dumitru Baleanu ◽

Hakimeh Mohammadi ◽

Shahram Rezapour

Keyword(s):

Differential Equation ◽

Fractional Differential Equation ◽

Equation Model ◽

Differential Equation Model ◽

Fractional Differential

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Explicit tight frames for simulating a new system of fractional nonlinear partial differential equation model of Alzheimer disease

Results in Physics ◽

10.1016/j.rinp.2020.103809 ◽

2021 ◽

Vol 21 ◽

pp. 103809

Author(s):

Mutaz Mohammad ◽

Alexander Trounev

Keyword(s):

Differential Equation ◽

Partial Differential Equation ◽

Alzheimer Disease ◽

Nonlinear Partial Differential Equation ◽

Equation Model ◽

Tight Frames ◽

Differential Equation Model ◽

Partial Differential ◽

Partial Differential Equation Model ◽

New System

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Chronic alcohol exposure inhibits biotin uptake by pancreatic acinar cells: possible involvement of epigenetic mechanisms

AJP Gastrointestinal and Liver Physiology ◽

10.1152/ajpgi.00278.2014 ◽

2014 ◽

Vol 307 (9) ◽

pp. G941-G949 ◽

Cited By ~ 8

Author(s):

Padmanabhan Srinivasan ◽

Rubina Kapadia ◽

Arundhati Biswas ◽

Hamid M. Said

Keyword(s):

Transgenic Mice ◽

Chronic Exposure ◽

Methylation Status ◽

Acinar Cells ◽

Alcohol Exposure ◽

Significant Inhibition ◽

Pancreatic Acinar Cells ◽

Chronic Alcohol ◽

Wild Type ◽

Chronic Alcohol Exposure

Chronic exposure to alcohol affects different physiological aspects of pancreatic acinar cells (PAC), but its effect on the uptake process of biotin is not known. We addressed this issue using mouse-derived pancreatic acinar 266-6 cells chronically exposed to alcohol and wild-type and transgenic mice (carrying the human SLC5A6 5′-promoter) fed alcohol chronically. First we established that biotin uptake by PAC is Na+ dependent and carrier mediated and involves sodium-dependent multivitamin transporter (SMVT). Chronic exposure of 266-6 cells to alcohol led to a significant inhibition in biotin uptake, expression of SMVT protein, and mRNA as well as in the activity of the SLC5A6 promoter. Similarly, chronic alcohol feeding of wild-type and transgenic mice carrying the SLC5A6 promoter led to a significant inhibition in biotin uptake by PAC, as well as in the expression of SMVT protein and mRNA and the activity of the SLC5A6 promoters expressed in the transgenic mice. We also found that chronic alcohol feeding of mice is associated with a significant increase in the methylation status of CpG islands predicted to be in the mouse Slc5a6 promoters and a decrease in the level of expression of transcription factor KLF-4, which plays an important role in regulating SLC5A6 promoter activity. These results demonstrate, for the first time, that chronic alcohol exposure negatively impacts biotin uptake in PAC and that this effect is exerted (at least in part) at the level of transcription of the SLC5A6 gene and may involve epigenetic/molecular mechanisms.

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