Cell-to-cell variation in defective virus expression and effect on host response during influenza virus infection
Ontology highlight
ABSTRACT:
ORGANISM(S): Canis lupus familiaris Homo sapiens Influenza A virus (A/Puerto Rico/8/1934(H1N1))
PROVIDER: GSE118773 | GEO | 2019/12/10
REPOSITORIES: GEO
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Project description:While a common symptom of influenza and coronavirus disease 2019 (COVID-19) is fever, its physiological role on host resistance to viral infection remains less clear. Here, we demonstrate that exposure of mice to the high ambient temperature of 36 °C increase host resistance to viral pathogens including influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). High heat-exposed mice increase basal body temperature over 38 °C to enable more bile acids production in a gut microbiota-dependent manner. The gut microbiota-derived deoxycholic acid (DCA) and its plasma membrane-bound receptor Takeda G-protein-coupled receptor 5 (TGR5) signaling increase host resistance to influenza virus infection by suppressing virus replication and neutrophil-dependent tissue damage. Furthermore, the DCA and its nuclear farnesoid X receptor (FXR) agonist protect Syrian hamster from lethal SARS-CoV-2 infection. Moreover, we demonstrate that certain bile acids are reduced in the plasma of COVID-19 patients who developed moderate I/II disease compared with minor illness group. These findings uncover an unexpected mechanism by which virus-induced high fever increases host resistance to influenza virus and SARS-CoV-2 in a gut microbiota-dependent manner.
2023-02-14 | ST002479 | MetabolomicsWorkbench
Project description:While a common symptom of influenza and coronavirus disease 2019 (COVID-19) is fever, its physiological role on host resistance to viral infection remains less clear. Here, we demonstrate that exposure of mice to the high ambient temperature of 36 °C increase host resistance to viral pathogens including influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). High heat-exposed mice increase basal body temperature over 38 °C to enable more bile acids production in a gut microbiota-dependent manner. The gut microbiota-derived deoxycholic acid (DCA) and its plasma membrane-bound receptor Takeda G-protein-coupled receptor 5 (TGR5) signaling increase host resistance to influenza virus infection by suppressing virus replication and neutrophil-dependent tissue damage. Furthermore, the DCA and its nuclear farnesoid X receptor (FXR) agonist protect Syrian hamster from lethal SARS-CoV-2 infection. Moreover, we demonstrate that certain bile acids are reduced in the plasma of COVID-19 patients who developed moderate I/II disease compared with minor illness group. These findings uncover an unexpected mechanism by which virus-induced high fever increases host resistance to influenza virus and SARS-CoV-2 in a gut microbiota-dependent manner.
2023-01-24 | ST002476 | MetabolomicsWorkbench
Project description:Heldt2012 - Influenza Virus Replication
The model describes the life cycle of influenza A virus in a mammalian cell including the following steps: attachment of parental virions to the cell membrane, receptor-mediated endocytosis, fusion of the virus envelope with the endosomal membrane, nuclear import of vRNPs, viral transcription and replication, translation of the structural viral proteins, nuclear export of progeny vRNPs and budding of new virions. It also explicitly accounts for the stabilization of cRNA by viral polymerases and NP and the inhibition of vRNP activity by M1 protein binding. In short, the model focuses on the molecular mechanism that controls viral transcription and replication.
This model is described in the article:
Modeling the intracellular dynamics of influenza virus replication to understand the control of viral RNA synthesis.
Heldt FS, Frensing T, Reichl U.
J Virol.
Abstract:
Influenza viruses transcribe and replicate their negative-sense RNA genome inside the nucleus of host cells via three viral RNA species. In the course of an infection, these RNAs show distinct dynamics, suggesting that differential regulation takes place. To investigate this regulation in a systematic way, we developed a mathematical model of influenza virus infection at the level of a single mammalian cell. It accounts for key steps of the viral life cycle, from virus entry to progeny virion release, while focusing in particular on the molecular mechanisms that control viral transcription and replication. We therefore explicitly consider the nuclear export of viral genome copies (vRNPs) and a recent hypothesis proposing that replicative intermediates (cRNA) are stabilized by the viral polymerase complex and the nucleoprotein (NP). Together, both mechanisms allow the model to capture a variety of published data sets at an unprecedented level of detail. Our findings provide theoretical support for an early regulation of replication by cRNA stabilization. However, they also suggest that the matrix protein 1 (M1) controls viral RNA levels in the late phase of infection as part of its role during the nuclear export of viral genome copies. Moreover, simulations show an accumulation of viral proteins and RNA toward the end of infection, indicating that transport processes or budding limits virion release. Thus, our mathematical model provides an ideal platform for a systematic and quantitative evaluation of influenza virus replication and its complex regulation.
With the current parameter set, the model reproduces an infection at a multiplicity of infection (MOI) of 10. Figure 2A of the paper is reproduced here, with parameters kDegRnp and kSynP changed to zeros.
Initial conditions and parameter changes that were used to obtain specific figures in the article can be found in Table A2.
The model has the correct value for kAttLo as 4.55e-04. The value of this parameter mentioned as 4.55e-02 in Table 1 of the paper is incorrect. This is checked with the author.
This model is hosted on BioModels Database
and identified
by: MODEL1307270000
.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication
for more information.
2013-08-07 | BIOMD0000000463 | BioModels
Project description:Viral infection perturbs host cells and can be used to uncover host regulatory mechanisms controlling both cell response and homeostasis. Here, using cell biological, biochemical and genetic tools, we reveal that influenza virus infection induces global transcriptional defects at the 3’-end of active host genes and RNA polymerase II (RNAPII) run-through into extragenic regions. This effect induces the biogenesis of aberrant RNAs (3’-extensions and host gene fusions) which ultimately causes global transcriptional downregulation of physiological transcripts, an effect that impacts antiviral response and virulence. We show that this phenomenon occurs with multiple strains of influenza virus and it is dependent on influenza NS1 protein expression. Mechanistically, pervasive RNAPII run-through can be modulated by SUMOylation of an intrinsically disordered region (IDR) of the NS1 expressed by the 1918 pandemic influenza virus. SUMOylation increases NS1 partitioning in nuclear granules and interference with the host transcriptional apparatus which result in augmentation of termination defects and a concomitant increase in global host gene shut off. Our data identify a general strategy used by influenza virus to suppress host gene expression and indicate that polymorphisms in IDRs of viral proteins, along with human genetic variation in enzymes that metabolize post-translational modifications, can determine the outcome of an infection. We thus propose that analysis of strain-specific determinant of pathogenesis can shed light on the molecular basis of virulence.
2018-09-05 | GSE103604 | GEO
Project description:Viral infection can dramatically alter a cell's transcriptome. However, these changes have mostly been studied by bulk measurements on many cells. Here we use single-cell mRNA sequencing to examine the transcriptional consequences of influenza virus infection. We find extremely wide cell-to-cell variation in production of viral gene transcripts -- viral transcripts compose less than a percent of total mRNA in many infected cells, but a few cells derive over half their mRNA from virus. Some infected cells fail to express at least one viral gene, and this gene absence partially explains variation in viral transcriptional load. Despite variation in total viral load, the relative abundances of viral mRNAs are fairly consistent across infected cells. Activation of innate immune pathways is rare, but some cellular genes co-vary in abundance with the amount of viral mRNA. Overall, our results highlight the complexity of viral infection at the level of single cells.
2017-12-14 | GSE108041 | GEO
Project description:Viral infection outcomes are governed by the complex and dynamic interplay between the infecting virus population and the host response. It is increasingly clear that both viral and host cell populations are highly heterogeneous, but little is known about how this heterogeneity influences infection dynamics or viral pathogenicity. To dissect the interactions between influenza A virus (IAV) and host cell heterogeneity, we examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV virion. We observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at the single cell level. We show that human H1N1 and H3N2 strains differ significantly in patterns of both viral and host anti-viral gene transcriptional heterogeneity at the single cell level. Our analyses also reveal that semi-infectious particles that fail to express the viral NS can play a dominant role in triggering the innate anti-viral response to infection. Altogether, these data reveal how patterns of viral population heterogeneity can serve as a major determinant of antiviral gene activation.
2020-06-18 | GSE143167 | GEO
Project description:Fribourg2014 - Dynamics of viral antagonism and innate immune response (H1N1 influenza A virus - Cal/09)
The dynamics of the interplay between the viral antagonism and the innate immune response has been studied using modelling approaches. The responses of human monocyte-derived dendritic cells infected by two influenza A H1N1 strains (the pandemic swine-origin A/California/4/2009 (Cal/09) and the seasonal A/New Caledonia/20/1999 (NC/99)) that have different clinical outcomes have been modelled. From the time course gene expression measurements of a set of selected genes, the dynamic features of viral antagonism and innate immune response are extracted. It is found that the strength and the time scale of action of viral antagonism is significantly different between the two viruses. This model describes the viral infection by seasonal Cal/09.
This model is described in the article:
Model of influenza A virus infection: Dynamics of viral antagonism and innate immune response.
Fribourg M, Hartmann B, Schmolke M, Marjanovic N, Albrecht RA, García-Sastre A, Sealfon SC, Jayaprakash C, Hayot F.
J Theor Biol. 2014 Mar 2;351C:47-57.
Abstract:
Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses.
This model is hosted on BioModels Database and identified
by: MODEL1403310002.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication for more information.
2014-04-03 | BIOMD0000000528 | BioModels
Project description:Fribourg2014 - Dynamics of viral antagonism and innate immune response (H1N1 influenza A virus - NC/99)
The dynamics of the interplay between the viral antagonism and the innate immune response has been studied using modelling approaches. The responses of human monocyte-derived dendritic cells infected by two influenza A H1N1 strains (the pandemic swine-origin A/California/4/2009 (Cal/09) and the seasonal A/New Caledonia/20/1999 (NC/99)) that have different clinical outcomes have been modelled. From the time course gene expression measurements of a set of selected genes, the dynamic features of viral antagonism and innate immune response are extracted. It is found that the strength and the time scale of action of viral antagonism is significantly different between the two viruses. This model describes the viral infection by seasonal NC/99.
This model is described in the article:
Model of influenza A virus infection: Dynamics of viral antagonism and innate immune response.
Fribourg M, Hartmann B, Schmolke M, Marjanovic N, Albrecht RA, García-Sastre A, Sealfon SC, Jayaprakash C, Hayot F.
J Theor Biol. 2014 Mar 2;351C:47-57.
Abstract:
Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses.
This model is hosted on BioModels Database and identified
by: MODEL1403310001.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication for more information.
2014-04-03 | BIOMD0000000529 | BioModels
Project description:Infection with a single influenza A virus (IAV) is only rarely sufficient to initiate productive infection. Here, we exploit both single cell approaches and whole-animal systems to show that the extent of IAV reliance on multiple infection varies with virus strain and host species. Influenza A/guinea fowl/HK/WF10/99 (H9N2) [GFHK99] virus exhibits strong dependence on collective interactions in mammalian systems. This reliance focuses viral progeny production within coinfected cells and therefore results in frequent genetic exchange through reassortment. In contrast, GFHK99 virus has greatly reduced dependence on multiple infection in avian systems, indicating a role for host factors in viral collective interactions. Genetic mapping implicated the viral polymerase as a major driver of multiple infection dependence. Mechanistically, quantification of incomplete viral genomes showed that their complementation only partly accounts for the observed reliance on coinfection. Indeed, even when all polymerase components are detected in single cell mRNA sequencing, robust polymerase activity of GFHK99 virus in mammalian cells is reliant on multiple infection. In sum, IAV collective interactions not only augment reassortment, but can also overcome species-specific barriers to infection. These findings underscore the importance of virus-virus interactions in IAV infection, evolution and emergence. We used a single-cell sequencing platform (10x Genomics) to elucidate the differential infection rate of an avian influenza A virus on an avian cell line (DF1) and a mammalian (MDCK) cell line. Our work on IAV reassortment has raised new questions about the fundamental strategies that drive influenza virus evolution. Our data indicate that a large majority of influenza virus genomesare incomplete within cells, comprising less than the eight complete segments normally found in a replication competent infectious viral particle. This led us to ask: what underlying mechanisms give rise to incomplete genomes? What constitute an infectious unit? What are the implications for viral diversification, evolution and spread. By addressing these questions, we will advance he field by deepening our understanding how viral infections are initiated and propagated.
2020-06-16 | GSE135553 | GEO
Project description:Influenza A virus, with the limited coding capacity of 10 to 14 proteins, requires the host cellular machinery for many aspects of its life cycle. Knowledge of these host cell requirements not only reveals molecular pathways exploited by the virus or triggered by the immune system, but also provides further targets for antiviral drug development. To uncover novel pathways and key targets of influenza infection, we assembled a large amount of data from 12 cell-based gene-expression studies of influenza infection for an integrative network analysis. We systematically identified differentially expressed genes and gene co-expression networks induced by influenza infection. We revealed the dedicator of cytokinesis 5 (DOCK5) played potentially an important role for influenza virus replication. CRISPR/Cas9 knockout of DOCK5 reduced influenza virus replication, indicating that DOCK5 is a key regulator for the viral life cycle. DOCK5’s targets determined by the DOCK5 knockout experiments strongly validated the predicted gene signatures and networks. This study systematically uncovered and validated fundamental patterns of molecular responses, intrinsic structures of gene co-regulation, and novel key targets in influenza virus infection.
2018-02-14 | GSE104168 | GEO