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Multi-omics evaluation of SARS-CoV-2 infected mouse lungs reveals dynamics of host responses

ABSTRACT: Multi-omics evaluation of SARS-CoV-2 infected mouse lungs reveals dynamics of host responses

PROVIDER: PRJNA805187 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17972654_1.fastq.gz	Fastqsanger.gz
	SRR17972654_2.fastq.gz	Fastqsanger.gz
	SRR17972655_1.fastq.gz	Fastqsanger.gz
	SRR17972655_2.fastq.gz	Fastqsanger.gz
	SRR17972656_1.fastq.gz	Fastqsanger.gz

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Multi-omics evaluation of SARS-CoV-2 infected mouse lungs reveals dynamics of host responses

Project description:Lung tissues from a mouse model sensitized to SARS-CoV-2 infection were serially collected at different time points for evaluation of transcriptome, proteome and phosphoproteome. We showed the ebb and flow of several host responses in the lung across viral infection. The signaling pathways and kinases regulating networks were alternated at different phases of infection. Our study not only revealed the dynamics of lung pathophysiology and their underlying molecular mechanisms during SARS-CoV-2 infection, but also highlighted some molecules and signaling pathways that might guide future investigations on COVID-19 therapies.

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Multi-omics evaluation of SARS-CoV-2 infected mouse lungs reveals dynamics of host responses

Project description:The outbreak of Coronavirus disease 2019 (COVID-19) throughout the world has caused millions of death, while the dynamics of host responses and the underlying regulation mechanisms during SARS-CoV-2 infection are not well depicted. Lung tissues from a mouse model sensitized to SARS-CoV-2 infection were serially collected at different time points for evaluation of transcriptome, proteome and phosphoproteome. We showed the ebb and flow of several host responses in the lung across viral infection. The signaling pathways and kinases regulating networks were alternated at different phases of infection. Our study not only revealed the dynamics of lung pathophysiology and their underlying molecular mechanisms during SARS-CoV-2 infection, but also highlighted some molecules and signaling pathways that might guide future investigations on COVID-19 therapies.

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Multi-omics evaluation of SARS-CoV-2 infected mouse lungs reveals dynamics of host responses.

Project description:The outbreak of Coronavirus disease 2019 (COVID-19) throughout the world has caused millions of death, while the dynamics of host responses and the underlying regulation mechanisms during SARS-CoV-2 infection are not well depicted. Lung tissues from a mouse model sensitized to SARS-CoV-2 infection were serially collected at different time points for evaluation of transcriptome, proteome, and phosphoproteome. We showed the ebb and flow of several host responses in the lung across the viral infection. The signaling pathways and kinases regulating networks were alternated at different phases of infection. This multiplex evaluation also revealed that many kinases of the CDK and MAPK family were interactive and served as functional hubs in mediating the signal transduction during SARS-CoV-2 infection. Our study not only revealed the dynamics of lung pathophysiology and their underlying molecular mechanisms during SARS-CoV-2 infection, but also highlighted some molecules and signaling pathways that might guide future investigations on COVID-19 therapies.

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Project description:To better understand the biological pathways by which UV inactivated SARS-CoV-induced pulmonary eosinophilia occurs, we examined global transcriptional changes in macrophages from the lungs of mouse. Female BALB/c mice were used at 21 weeks of age. Mice were subcutaneously immunized with UV inactivated SARS-CoV (UV-V) or UV-V and Toll like receptor (TLR) ligands at 6 and 1 weeks prior to mouse-adapted SARS-CoV (n=6 per group). Mice were intranasally challenged with 1E+6 TCID50 in 30M-NM-<L. MEM was challenged in six mice as control infection. Mice were sacrificed and collected lungs at 1 days after challenge, then CD11b positive cells were isolated from the lungs of these mice. These cells were used for the analysis of microarray.

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