Multiscale modeling of virus replication and spread

Kumberger, Peter; Frey, Felix J.; Schwarz, Ulrich S.; Graw, Frederik

doi:10.1002/1873-3468.12095

Cited by 25 publications

(24 citation statements)

References 130 publications

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“…The copy number of GCRV-I remained stable or even decreased slightly from day 1 to day 7 post-infection, whereas GCRV-II showed a rapid increase in copy number at 5 days post-stimulation. High virulence, short latent period, and high mortality could accelerate the spread of virus [30]. Our results explained that why the GCRV isolated recently in China belonged to GCRV-II rather than GCRV-I [10–12].…”

Section: Discussionmentioning

confidence: 77%

Differences in responses of grass carp to different types of grass carp reovirus (GCRV) and the mechanism of hemorrhage revealed by transcriptome sequencing

Zhang

Pei

et al. 2017

BMC Genomics

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BackgroundGrass carp is an important farmed fish in China that is affected by serious disease, especially hemorrhagic disease caused by grass carp reovirus (GCRV). The mechanism underlying the hemorrhagic symptoms in infected fish remains to be elucidated. Although GCRV can be divided into three distinct subtypes, differences in the pathogenesis and host immune responses to the different subtypes are still unclear. The aim of this study was to provide a comprehensive insight into the grass carp response to different GCRV subtypes and to elucidate the mechanism underlying the hemorrhagic symptoms.ResultsFollowing infection of grass carp, GCRV-I was associated with a long latent period and low mortality (42.5%), while GCRV-II was associated with a short latent period and high mortality (81.4%). The relative copy number of GCRV-I remained consistent or decreased slightly throughout the first 7 days post-infection, whereas a marked increase in GCRV-II high copy number was detected at 5 days post-infection. Transcriptome sequencing revealed 211 differentially expressed genes (DEGs) in Group I (66 up-regulated, 145 down-regulated) and 670 (386 up-regulated, 284 down-regulated) in Group II. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed significant enrichment in the terms or pathways involved in immune responses and correlating with blood or platelets. Most of the DEGs in Group I were also present in Group II, although the expression profiles differed, with most DEGs showing mild changes in Group I, while marked changes were observed in Group II, especially the interferon-related genes. Many of the genes involved in the complement pathway and coagulation cascades were significantly up-regulated at 7 days post-infection in Group II, suggesting activation of these pathways.ConclusionGCRV-I is associated with low virulence and a long latent period prior to the induction of a mild host immune response, whereas GCRV-II is associated with high virulence, a short latent period and stimulates a strong and extensive host immune response. The complement and coagulation pathways are significantly activated at 7 days post-infection, leading to the endothelial cell and blood cell damage that result in hemorrhagic symptoms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3824-1) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 77%

Differences in responses of grass carp to different types of grass carp reovirus (GCRV) and the mechanism of hemorrhage revealed by transcriptome sequencing

Zhang

Pei

et al. 2017

BMC Genomics

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“…Deterministic mathematical models have been widely used to make sense of data on the innate immune response and virus replication and spread . These models also significantly contributed to identifying the key parameters regulating these processes.…”

Section: Mathematical Modeling Of the Interferon Responsementioning

confidence: 99%

“…Deterministic mathematical models have been widely used to make sense of data on the innate immune response and virus replication and spread. [37][38][39][40][41] These models also significantly contributed to identifying the key parameters regulating these processes. More recently, a thorough examination of the cell-to-cell heterogeneity in innate immune responses became possible by technological advances in live-cell imaging methods.…”

Section: Mathemati C Al Modeling Of the Interferon Re S P Ons Ementioning

confidence: 99%

Antiviral interferon response at single‐cell resolution

Talemi

Höfer

2018

Immunological Reviews

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Experimental studies of the innate immune response of mammalian cells to viruses reveal pervasive heterogeneity at the level of single cells. Interferons are induced only in a fraction of virus-infected cells; subsequently a fraction of cells exposed to interferons upregulate interferon-stimulated genes. Nevertheless, quantitative experiments and linked mathematical models show that the interferon response can be effective in curbing viral spread through two distinct mechanisms. First, paracrine interferon signals from scattered source cells can protect many uninfected cells, and the self-amplification of interferon production might serve to calibrate response amplitude to strength of viral infection. Second, models of the tug-of-war between viral replication and the innate interferon response imply a pivotal role of interferon action on already infected cells in curbing viral spread, through effectively lowering virus replication rate. This finding is in line with the observation that several pathogenic viruses selectively abrogate interferon action on infected cells. Thus, interferons may delay viral spread in acute infections by acting as sentinels, warning uninfected cells of imminent danger, or as negative feedback regulators of virus replication in infected cells. The timing of the interferon response relative to the onset of viral replication is critical for its effectiveness in curbing viral spread.

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“…The data on HCV focus expansion were best described by a model assuming a focus size-dependent growth rate. Finally, there exist few hybrid approaches that model the immune response in lymph nodes using an agent-based framework for cell dynamics and the spatiotemporal description of cytokines and antigens via reaction-diffusion equations [25–28]. A two-dimensional lattice approximation of the permissive organs is used.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Dynamics of Virus Infection Spreading in Tissues

et al. 2016

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Virus spreading in tissues is determined by virus transport, virus multiplication in host cells and the virus-induced immune response. Cytotoxic T cells remove infected cells with a rate determined by the infection level. The intensity of the immune response has a bell-shaped dependence on the concentration of virus, i.e., it increases at low and decays at high infection levels. A combination of these effects and a time delay in the immune response determine the development of virus infection in tissues like spleen or lymph nodes. The mathematical model described in this work consists of reaction-diffusion equations with a delay. It shows that the different regimes of infection spreading like the establishment of a low level infection, a high level infection or a transition between both are determined by the initial virus load and by the intensity of the immune response. The dynamics of the model solutions include simple and composed waves, and periodic and aperiodic oscillations. The results of analytical and numerical studies of the model provide a systematic basis for a quantitative understanding and interpretation of the determinants of the infection process in target organs and tissues from the image-derived data as well as of the spatiotemporal mechanisms of viral disease pathogenesis, and have direct implications for a biopsy-based medical testing of the chronic infection processes caused by viruses, e.g. HIV, HCV and HBV.

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Multiscale modeling of virus replication and spread

Cited by 25 publications

References 130 publications

Differences in responses of grass carp to different types of grass carp reovirus (GCRV) and the mechanism of hemorrhage revealed by transcriptome sequencing

Differences in responses of grass carp to different types of grass carp reovirus (GCRV) and the mechanism of hemorrhage revealed by transcriptome sequencing

Antiviral interferon response at single‐cell resolution

Spatiotemporal Dynamics of Virus Infection Spreading in Tissues

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