Ontology highlight
ABSTRACT:
PROVIDER: PRJNA301942 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Host-virus transcriptome dynamics determined from RNA-sequencing
| PRJNA302091 | ENA
Project description:Host-virus transcriptome dynamics determined from microarray analyses
| PRJNA268696 | ENA
Project description:Dengue and Zika viral infections affect millions of people annually and can be complicated by hemorrhage or neurological manifestations, respectively. However, a thorough understanding of the host response to these viruses is lacking, partly because conventional approaches ignore heterogeneity in virus abundance across cells. We present viscRNA-Seq (virus-inclusive single cell RNA-Seq), an approach to probe the host transcriptome together with intracellular viral RNA at the single cell level. We applied viscRNA-Seq to monitor dengue and Zika virus infection in cultured cells and discovered extreme heterogeneity in virus abundance. We exploited this variation to identify host factors that show complex dynamics and a high degree of specificity for either virus, including proteins involved in the endoplasmic reticulum translocon, signal peptide processing, and membrane trafficking. We validated the viscRNA-Seq hits and discovered novel proviral and antiviral factors. viscRNA-Seq is a powerful approach to assess the genome-wide virus-host dynamics at single cell level.
2018-02-27 | GSE110496 | GEO
Project description:The worldwide spread of severe acute respiratory syndrome-related coronavirus-2 (SARS- CoV-2) caused an urgent need for an in-depth understanding of virus-host interactions. Here, we dissected the dynamics of virus replication and the host cell transcriptional response to SARS-CoV-2 infection at a systems level by combining time-resolved RNA sequencing with mathematical modeling. We observed an immediate transcriptional activation of inflammatory pathways linked to the anti-viral response followed by increased expression of genes involved in ribosome and mitochondria function, thus hinting at rapid alterations in protein production and cellular energy supply. At later stages, metabolic processes, in particular those related to xenobiotic metabolism, were downregulated. To gain a deeper understanding of the underlying transcriptional dynamics, we developed an ODE model of SARS-CoV-2 infection and replication. Mathematical modeling of SARS-CoV-2 replication suggested a strong inhibitory effect of SARS-CoV-2 proteins on the anti-viral response and a large excess of virus transcripts over the translation capacity. Our study provides insights into the sequence of SARS-CoV-2 virus-host interactions and facilitates the identification of druggable host pathways supporting virus replication.
2022-11-10 | GSE217504 | GEO
Project description:Virus and host factors contribute to cell-to-cell variation in viral infection and determine the outcome of the overall infection. However, the extent of the variability at the single cell level and how it impacts virus-host interactions at a systems level are not well understood. To characterize the dynamics of viral transcription and host responses, we used single-cell RNA sequencing to quantify at multiple time points the host and viral transcriptomes of human A549 cells and primary bronchial epithelial cells infected with influenza A virus. We observed substantial variability of viral transcription between cells, including the accumulation of defective viral genomes (DVGs) that impact viral replication. We show a correlation between DVGs and viral-induced variation of the host transcriptional program and an association between differential induction of innate immune response genes and attenuated viral transcription in subpopulations of cells. These observations at the single cell level improve our understanding of the complex virus-host interplay during influenza infection.
2019-12-10 | GSE118773 | GEO
Project description:Here we compare transcriptome dynamics in human lung carcinoma cells A549 infected with Influenza virus A/Port Chalmers/1/73 (H3N2) at two different virus to host cell ratios: multiplicity of infection (MOI) 1 and 5. Our goal was to outline the activation profiles of two main host pro-survival mechanisms, autophagy and mTORC2, co-opted by the virus to effectively complete the replication cycle, amplify, and release of infectious particles. We found that at high virus load MOI5 autophagy, a stress response mechanisms that postpones mammalian cell death, was activated and inhibited within 1 hour of infection. Autophagy downregulation was quickly followed by the activation of genes regulating mTORC2, a secondary cell survival mechanism promoting low capacity of cellular metabolism by inhibition of mTORC1, a main regulator of protein synthesis activating ribosomal elongation factors. At lower MOI (1) autophagy activation followed the virus replication cycle. We found that ULK1 gene expression was gradually upregulated upon Influenza virus A infection at MOI1 together with the activation of key regulators of mTORC1. Such results was not expected since mTORC1 inhibits autophagy activation pathway on post-transcription level through phosphorylation of ULK1.
2020-11-29 | GSE162295 | GEO
Project description:Genome-Wide Expression Dynamics of a Marine Virus and its Host during Lytic Infection
| PRJNA101423 | ENA
Project description:We previously reported widespread differential expression of long non-protein-coding RNAs (ncRNAs) in response to virus infection. Here, we expanded the study through small RNA transcriptome sequencing analysis of the host response to both severe acute respiratory syndrome coronavirus (SARS-CoV) and influenza virus infections across four founder mouse strains of the Collaborative Cross, a recombinant inbred mouse resource for mapping complex traits. We observed differential expression of over 200 small RNAs of diverse classes during infection. A majority of identified microRNAs (miRNAs) showed divergent changes in expression across mouse strains with respect to SARS-CoV and influenza virus infections and responded differently to a highly pathogenic reconstructed 1918 virus compared to a minimally pathogenic seasonal influenza virus isolate. Novel insights into miRNA expression changes, including the association with pathogenic outcomes and large differences between in vivo and in vitro experimental systems, were further elucidated by a survey of selected miRNAs across diverse virus infections. The small RNAs identified also included many non-miRNA small RNAs, such as small nucleolar RNAs (snoRNAs), in addition to nonannotated small RNAs. An integrative sequencing analysis of both small RNAs and long transcripts from the same samples showed that the results revealing differential expression of miRNAs during infection were largely due to transcriptional regulation and that the predicted miRNA-mRNA network could modulate global host responses to virus infection in a combinatorial fashion. These findings represent the first integrated sequencing analysis of the response of host small RNAs to virus infection and show that small RNAs are an integrated component of complex networks involved in regulating the host response to infection. IMPORTANCE: Most studies examining the host transcriptional response to infection focus only on protein-coding genes. However, mammalian genomes transcribe many short and long non-protein-coding RNAs (ncRNAs). With the advent of deepsequencing technologies, systematic transcriptome analysis of the host response, including analysis of ncRNAs of different sizes, is now possible. Using this approach, we recently discovered widespread differential expression of host long (>200 nucleotide[nt]) ncRNAs in response to virus infection. Here, the samples described in the previous report were again used, but we sequenced another fraction of the transcriptome to study very short (about 20 to 30 nt) ncRNAs. We demonstrated that virus infection also altered expression of many short ncRNAs of diverse classes. Putting the results of the two studies together, we show that small RNAs may also play an important role in regulating the host response to virus infection.
2012-03-31 | GSE36971 | GEO
Project description:For the assessment of host response dynamics to SARS-CoV and SARS-CoV-2 infections in human airway epithelial cells at ambient temperature corresponding to the upper or lower respiratory tract. We performed a temporal transcriptome analysis on human airway epithelial cell (hAEC) cultures infected with SARS-CoV and SARS-CoV-2, as well as uninfected hAEC cultures, incubated either at 33°C or 37°C. hAEC cultures were harvested at 24, 48 72, 96 hpi and processed for Bulk RNA Barcoding and sequencing (BRB-seq), which allows a rapid and sensitive genome-wide transcriptomic analysis in a highly multiplexed manner. Transcriptome data was obtained from a total of 7 biological donors for pairwise comparisons of SARS-CoV or SARS-CoV-2 virus-infected to unexposed hAEC cultures at respective time points and temperatures.
2020-11-27 | E-MTAB-9781 | biostudies-arrayexpress
Project description:We assess the viral and host transcriptome during CCMV BAC virus infection
2021-06-01 | GSE171149 | GEO