Single-cell profiling of Ebola virus infection in vivo reveals viral and host transcriptional dynamics (InVivo scRNA-seq)
Ontology highlight
ABSTRACT:
ORGANISM(S): Macaca mulatta
PROVIDER: GSE158442 | GEO | 2020/09/23
REPOSITORIES: GEO
Similar Datasets
Project description:Ebola virus (EBOV) causes epidemics with high mortality, yet remains understudied due to the challenge of experimentation in high-containment and outbreak settings. Here, we used single-cell transcriptomics and CyTOF-based single-cell protein quantification to characterize peripheral immune cells during EBOV infection in rhesus monkeys. We obtained 100,000 transcriptomes and 15,000,000 protein profiles, providing insight into pathogenesis: e.g., immature, proliferative monocyte-lineage cells with reduced antigen presentation capacity replace conventional monocyte subsets, while lymphocytes upregulate apoptosis genes and decline in abundance. By quantifying intracellular viral RNA, we identify molecular determinants of tropism among circulating immune cells and examine temporal dynamics in viral and host gene expression. Within infected cells, EBOV down-regulates STAT1 mRNA and interferon signaling, and up-regulates putative pro-viral genes (e.g., DYNLL1 and HSPA5), nominating pathways the virus manipulates for its replication. This study sheds light on EBOV tropism, replication dynamics, and elicited immune response, and provides a framework for characterizing host-virus interactions under maximum containment.
2020-09-23 | GSE158440 | GEO
Project description:Ebola virus (EBOV) causes epidemics with high mortality, yet remains understudied due to the challenge of experimentation in high-containment and outbreak settings. Here, we used single-cell transcriptomics and CyTOF-based single-cell protein quantification to characterize peripheral immune cells during EBOV infection in rhesus monkeys. We obtained 100,000 transcriptomes and 15,000,000 protein profiles, providing insight into pathogenesis: e.g., immature, proliferative monocyte-lineage cells with reduced antigen presentation capacity replace conventional monocyte subsets, while lymphocytes upregulate apoptosis genes and decline in abundance. By quantifying intracellular viral RNA, we identify molecular determinants of tropism among circulating immune cells and examine temporal dynamics in viral and host gene expression. Within infected cells, EBOV down-regulates STAT1 mRNA and interferon signaling, and up-regulates putative pro-viral genes (e.g., DYNLL1 and HSPA5), nominating pathways the virus manipulates for its replication. This study sheds light on EBOV tropism, replication dynamics, and elicited immune response, and provides a framework for characterizing host-virus interactions under maximum containment.
2020-09-23 | GSE158390 | GEO
Project description:The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remain unclear. Here, we combine a multiomics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies.
2022-01-17 | PXD030785 | Pride
Project description:Highly pathogenic Zaire ebolavirus (EBOV) infection is associated with a dysregulated immune response and high levels of cytokines and chemokines are observed in fatal human cases. . In stark contrast Reston ebolavirus (RESTV) might be non-pathogenic for humans yet the underlying mechanisms determining pathogenicity for different Ebola viruses are not understood. In this study we investigate antiviral immune responses in EBOV- and RESTV- infected primary human monocyte-derived macrophages (MDM). We provide evidence that increased pathogenicity of the highly pathogenic EBOV is associated with a strong activation of host responses from infected MDM. The observed cytokine response after EBOV infection is strikingly similar to LPS-mediated immune signatures however EBOV caused significant induction of the interferon response in addition. In contrast we show that the low pathogenic RESTV fails to elicit significant immune responses in infected MDM. These results demonstrate a correlation of pathogenicity and excessive MDM activation for different Ebola virus species. Interaction of the viral glycoprotein (GP) with Toll-like receptor 4 (TLR4) leading to activation of NF_B signaling is responsible for this effect rather than differences in replication or blocking of immune signaling. We demonstrate that inhibition of TLR4 is able to abolish EBOV-GP mediated NF_B activation which might offer the possibility to develop targeted treatments for EBOV limiting the extreme immune response that seems to be detrimental to the host.
2016-12-31 | GSE84188 | GEO
Project description:The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remain unclear. Here, we combine a multiomics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies.
2022-01-17 | GSE193708 | GEO
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.
2024-09-02 | BIOMD0000000529 | BioModels
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.
2024-09-02 | BIOMD0000000528 | BioModels
Project description:Long non-coding RNAs (lncRNAs) are pivotal mediators of systemic immune response to viral infection yet most studies concerning their expression and functions upon immune stimulation are limited to in vitro bulk cell populations. This strongly constrains our understanding of how lncRNA expression varies at single-cell resolution, and whether differences with protein coding genes exist in their cell-type specific immune regulatory roles. Here, we perform the first in-depth characterization of lncRNA expression variation at single-cell resolution during Ebola virus (EBOV) infection in vivo. Using bulk RNA-sequencing from 119 samples and 12 tissue types, we significantly expand the current macaque lncRNA annotation. We then profile lncRNA expression variation in immune circulating single-cells during EBOV infection and find that lncRNAs’ expression in fewer cells is a major differentiating factor to their protein coding gene counterparts. Upon EBOV infection, lncRNAs present dynamic and mostly cell-type specific changes in their expression profiles especially in monocytes, the main cell type targeted by EBOV. Such changes are associated with gene regulatory modules related to important innate immune responses such as interferon response and purine metabolism. Within infected cells, several lncRNAs have correlated and anti-correlated expression with viral load, suggesting that expression of some of these lncRNAs might be directly hijacked by EBOV to attack host cells. This study provides novel insights on the roles that lncRNAs play in the host response to acute viral infection and paves the way for future lncRNA studies at single-cell resolution.
2023-04-26 | GSE191315 | GEO
Project description:Long non-coding RNAs (lncRNAs) are pivotal mediators of systemic immune response to viral infection yet most studies concerning their expression and functions upon immune stimulation are limited to in vitro bulk cell populations. This strongly constrains our understanding of how lncRNA expression varies at single-cell resolution, and whether differences with protein coding genes exist in their cell-type specific immune regulatory roles. Here, we perform the first in-depth characterization of lncRNA expression variation at single-cell resolution during Ebola virus (EBOV) infection in vivo. Using bulk RNA-sequencing from 119 samples and 12 tissue types, we significantly expand the current macaque lncRNA annotation. We then profile lncRNA expression variation in immune circulating single-cells during EBOV infection and find that lncRNAs’ expression in fewer cells is a major differentiating factor to their protein coding gene counterparts. Upon EBOV infection, lncRNAs present dynamic and mostly cell-type specific changes in their expression profiles especially in monocytes, the main cell type targeted by EBOV. Such changes are associated with gene regulatory modules related to important innate immune responses such as interferon response and purine metabolism. Within infected cells, several lncRNAs have correlated and anti-correlated expression with viral load, suggesting that expression of some of these lncRNAs might be directly hijacked by EBOV to attack host cells. This study provides novel insights on the roles that lncRNAs play in the host response to acute viral infection and paves the way for future lncRNA studies at single-cell resolution.
2023-04-26 | GSE191102 | GEO
Project description:Ebola virus (EBOV) critically depends on the viral polymerase to replicate and transcribe the viral RNA genome in the cytoplasm of host cells, where cellular factors can antagonize or facilitate the virus life cycle. Here we leveraged proximity proteomics and conducted an siRNA screen to define the functional interactome of EBOV polymerase. As proof-of-principle, we validated two cellular mRNA decay factors from 35 identified host factors: eukaryotic peptide chain release factor subunit 3a (eRF3a/GSPT1) and up-frameshift protein 1 (UPF1). Our data suggest that EBOV can subvert restrictions of cellular mRNA decay and repurpose both GSPT1 and UPF1 to promote viral replication. Treating EBOV-infected human hepatocytes with a drug candidate that targets GSPT1 for degradation significantly reduced viral RNA load and particle production. Our work demonstrates the utility of proximity proteomics to capture the functional host-interactome of the EBOV polymerase and to illuminate host-dependent regulations of viral RNA synthesis.
2022-02-17 | MSV000088859 | MassIVE