Omics-Lethal Human Viruses, Influenza A Experiment ICL102

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Description

Influenza A virus Experiment ICL102

The purpose of this experiment was to evaluate the human host cellular response to wild-type Influenza A/Anhui/1/2013 (H7N9; "AH1-WT") virus and mutant viruses NS1-L103F/I106M ("AH1-F/M") and partially ferret-adapted ("AH1-691") infection. Sample data was obtained from human lung adenocarcinoma cells (Calu-3) and processed for mRNA, miRNA, proteomics, lipidomics, and metabolomics expression analysis.

Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics each dataset download has a direct relationship to a primary sample submission corresponding to a specific Influenza A virus infection.

Accessible Secondary Digital Data Downloads

Transcriptomics

  1. Expression profiling by array (mRNA) 
  2. Non-coding RNA profiling by array (miRNA)

Proteomics, Metabolomics, Lipidomics

  1. Protein quantification by liquid chromatography mass spectrometry (LC-MS)
  2. Metabolite quantification by gas chromatography mass spectrometry (GC-MS)
  3. Lipid quantification by liquid chromatography mass spectrometry (LC-MS)

Download Citation

Anderson, Lindsey, Eisfeld, Amie J, Waters, Katrina M, and Modeling Host Responses to Understand Severe Human Virus Infections Program Project. Omics-Lethal Human Viruses, Influenza A Experiment ICL102. United States. 2021. PNNL DataHub (Web). DOI: 10.25584/LHVICL102/1661912

Linked Primary Data Accessions

BioProject Accession:  PRJNA284341

GEO Dataset Accession: GSE69026 (mRNA transcriptome response), GSE69027 (miRNA transcriptome response)*

MassIVE Accession:  MSV000079164 (proteome response), MSV000079386 (lipidome response), MSV000079156 (metabolome response)

*Raw measurement data has primary data publication PMID: 34051754

 

Acknowledgment of Federal Funding

The data described here was funded in whole or in part by the National Institute of Allergy and Infectious Diseases, of the National Institutes of Health under award number U19AI106772 and is a contribution of the "Modeling Host Responses to Understand Severe Human Virus Infections" Project at Pacific Northwest National Laboratory. Data generated by the Omics-LHV Core for proteomics, metabolomics, and lipidomics analyses for were performed at Pacific Northwest National Laboratory in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy’s (DOE) Office, operating under the Battelle Memorial Institute for the DOE under contract number DE-AC05-76RLO1830. 

Citation Policy

In efforts to enable discovery, reproducibility, and reuse of NIH-funded project dataset citations, we ask that all reuse of project data and metadata download materials acknowledge all primary and secondary dataset citations where applicable and direct corresponding journal articles (Grant U19AI106772) where allowable in accordance with best practices outlined by the FORCE11 Joint Declaration of Data Citation Principles in alignment with NIH acknowledgement requirements (NOT-OD-21-013).

Data Licensing

CC BY-SA 4.0 (secondary dataset download DOIs), CC0 1.0 (project metadata and PNNL DataHub policy default)

Last updated on 2023-01-30T00:09:57+00:00 by LN Anderson

 

English
Projects (2)
Omics Lethal Human Viruses Project Profiling of the Host Response to Influenza A Virus Infection, Processed Experimental Dataset Catalog
NIAID Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collections
Publications (1)
Hypergraph models of biological networks to identify genes critical to pathogenic viral response
People (2)

Lindsey Anderson’s research has been dedicated to the identification and characterization of novel, targeted and non-targeted, functional metabolic interactions using a high-throughput systems biology and computational biology approach. Her expertise in functional metabolism and multidisciplinary...

Dr. Katrina Waters is the division director for Biological Sciences at the Pacific Northwest National Laboratory. Waters has a Ph.D. in biochemistry and more than 15 years of experience in microarray and proteomics data analysis. Her research interests are focused on the integration of genomics...

Data Sources (3)
Methods (1)
Institutions (3)
Software (1)