Influenza A virus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA939935 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR23732246.fastq.gz | Fastqsanger.gz | |||
| SRR23732247.fastq.gz | Fastqsanger.gz | |||
| SRR23732248.fastq.gz | Fastqsanger.gz | |||
| SRR23732249.fastq.gz | Fastqsanger.gz | |||
| SRR23732250.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 28 |
Similar Datasets
Project description:Influenza A virus SPLASH samples
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Project description:Disruption of influenza virus packaging signals results in various misassembled genome complexes
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Project description:Influenza A packaging mutants
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Project description:Transcription and co-transcriptional pre-mRNA splicing are kinetically coupled as shown by the widespread effects of transcription speed on alternative splicing. The molecular basis for kinetic coupling is incompletely understood, but one potential mechanism is through elongation rate dependent alternative folding pathways of the nascent pre-mRNA. To search for RNA structures in nascent pre-mRNA, we modified SPLASH (1) (Sequencing of Psoralen Crosslinked, Ligated And Selected Hybrids) for use with Chromatin Associated RNA. We applied this new method called CAR-SPLASH to cells expressing WT and slow mutant pol II and identified >3000 intragenic RNA structures of which >400 are proximal to splice sites. ASO disruption of several structures identified by CAR-SPLASH that sequester splice sites changed alternative splicing outcomes in vivo. We identified three examples of novel regulatory elements we designate “RNA kinetic switches”. ASO disruption of these structures modified alternative splicing of NISCH Exon 18 GAK Exon 7 and MEGF8 Exon 24 in a way that depended on the rate of transcription elongation. These results demonstrate that individual RNA structures can mediate kinetic coupling between transcription and pre-mRNA splicing and that nascent RNA structures can serve as targets for splice modifying ASO’s.
2025-09-14 | GSE288524 | GEO
Project description:Transcription and co-transcriptional pre-mRNA splicing are kinetically coupled as shown by the widespread effects of transcription speed on alternative splicing. The molecular basis for kinetic coupling is incompletely understood, but one potential mechanism is through elongation rate dependent alternative folding pathways of the nascent pre-mRNA. To search for RNA structures in nascent pre-mRNA, we modified SPLASH (1) (Sequencing of Psoralen Crosslinked, Ligated And Selected Hybrids) for use with Chromatin Associated RNA. We applied this new method called CAR-SPLASH to cells expressing WT and slow mutant pol II and identified >3000 intragenic RNA structures of which >400 are proximal to splice sites. ASO disruption of several structures identified by CAR-SPLASH that sequester splice sites changed alternative splicing outcomes in vivo. We identified three examples of novel regulatory elements we designate “RNA kinetic switches”. ASO disruption of these structures modified alternative splicing of NISCH Exon 18 GAK Exon 7 and MEGF8 Exon 24 in a way that depended on the rate of transcription elongation. These results demonstrate that individual RNA structures can mediate kinetic coupling between transcription and pre-mRNA splicing and that nascent RNA structures can serve as targets for splice modifying ASO’s.
2025-09-14 | GSE288523 | GEO
Project description:Identification of RNA motif for segmented genome packaging of influenza virus
| PRJDB4090 | ENA
Project description:Due to the RNA nature of their genomes, influenza viruses have to utilize many RNA-binding proteins (RBPs) of both viral and host origin, for their replication. To uncover the comprehensive vRNA-host protein interactions, we performed affinity purification coupled with mass spectrometry (AP-MS) analysis of influenza vRNA complexes. The eight vRNA segments of H7N9 were transcribed and individually labeled with biotin in vitro and incubated with IAV virus-infected THP-1 cells, and vRNA complexes were enriched streptavidin magnetic beads and analyzed by mass spectrometry
2021-03-25 | PXD020723 | Pride
Project description:Influenza A Virus Interactions with Epithelial Cells
| PRJNA297517 | ENA
Project description:Epidemics of influenza virus are of great challenges to the public concern. The lung inflammation and injury caused by excessive inflammatory cell infiltration into the lungs and overproduction of inflammatory mediators are major consequences during influenza virus infection. Neutrophils are vital for anti-microbial defense. However, the roles of neutrophils during viral infections are less clear. Furthermore, the molecular regulation of neutrophil fate and function at the viral infected sites is largely elusive. We found that BCL6 deficiency in neutrophils, but not in monocytes nor lung macrophages, attenuated host inflammation and morbidity following influenza infection. Mechanistically, BCL6 bound to the neutrophil gene loci involved in cellular apoptosis specifically at the site of infection. As such, BCL6 disruption resulted in increased expression of apoptotic genes in neutrophils in the respiratory tract, but not in the circulation nor bone marrow. Consequently, BCL6 deficiency promoted tissue neutrophil apoptosis. Our results have revealed a previously unappreciated role of BCL6 in modulating neutrophil apoptosis at the site of infection for the regulation of host disease development following viral infection.
2019-06-24 | GSE126622 | GEO
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
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2024-09-02 | BIOMD0000000463 | BioModels