Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog
Abstract
Middle East Respiratory Syndrome coronavirus (MERS-CoV) is classified as a Category C priority pathogen (Coronaviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), and is known to cause severe respiratory disease with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen 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 (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV [NCBITAXON:1335626] experimental infection study. Host sample types include human lungmore »
- Authors:
-
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Univ. of Wisconsin, Madison, WI (United States). School of Veterinary Medicine. Pathology Department
- Publication Date:
- Other Number(s):
- LHVMERS
MCL001;MCL002;MCL003;MCL004;MCL005;MDC001;MFB001;MFB002;MFB003;MHAE001;MHAE002;MHAE003;MM001;MMVE001;MMVE002;MMVE003
- DOE Contract Number:
- AC05-76RL01830
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC); National Institute of Allergy and Infectious Diseases (NIAID)
- Collaborations:
- Modeling Host Responses to Understand Severe Human Virus Infections Program Project
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES
- Keywords:
- Virology [edam.topic:0781]; Immune Response [GO:0006955]; Human virus [NCIT:C14317]; MERS-CoV [NCBITAXON:1335626]; Time Sampled Measurement Datasets [IAO:0000584]; Mass spectrometry data [edam.data:2536]; MassIVE dataset identifier [MS:1002487]; Gene expression profile data [edam.data:0928]; BioProject Accession Number [NCIT:C175890]; Omics [edam.topic:3391]; Multi-omics [edam.topic:4021]; data transformation [SIO:000594]; differential expression analysis [SWO:7000018]; Dataset Collection [schema:DataCatalog]
- OSTI Identifier:
- 1813911
- DOI:
- https://doi.org/10.25584/LHVMERS/1813911
Citation Formats
Anderson, Lindsey N., Eisfeld, Amie J., and Waters, Katrina M. Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog. United States: N. p., 2021.
Web. doi:10.25584/LHVMERS/1813911.
Anderson, Lindsey N., Eisfeld, Amie J., & Waters, Katrina M. Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog. United States. doi:https://doi.org/10.25584/LHVMERS/1813911
Anderson, Lindsey N., Eisfeld, Amie J., and Waters, Katrina M. 2021.
"Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog". United States. doi:https://doi.org/10.25584/LHVMERS/1813911. https://www.osti.gov/servlets/purl/1813911. Pub date:Mon Jan 18 00:00:00 EST 2021
@article{osti_1813911,
title = {Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog},
author = {Anderson, Lindsey N. and Eisfeld, Amie J. and Waters, Katrina M.},
abstractNote = {Middle East Respiratory Syndrome coronavirus (MERS-CoV) is classified as a Category C priority pathogen (Coronaviridae) by the National Institute of Allergy and Infectious Diseases (NIAID), and is known to cause severe respiratory disease with high mortality rates in humans. Lethal host-pathogen invasion mechanisms and the cellular intricacies behind these fatal infections still remain unclear. The NIAID Modeling Host Responses to Understand Severe Human Virus Infections Research Program project (2013-2018) aimed to develop an improved comprehensive understanding of the host response to a suite of viruses causing lethal infections leveraging a systems biology approach. Herein, PNNL sub-projects provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open-access to viral Omics datasets and project lifecycle metadata. Secondary host-pathogen 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 (P), metabolomics (M), lipidomics (L), and transcriptomics (T) dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific MERS-CoV [NCBITAXON:1335626] experimental infection study. Host sample types include human lung adenocarcinoma cells ["Calu-3", BTO:0002750], human bronchial epithelial cells ["Calu-3 clone 2B4"; BTO:0002022], primary human fibroblasts ["FB"; BTO:0000452], primary human airway epithelial cells ["HAE"; BTO:0005571], human microvascular endothelial cells ["HMVE"; BTO:0003123], and whole mouse lung [BTO:0000763] tissue collections.},
doi = {10.25584/LHVMERS/1813911},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 18 00:00:00 EST 2021},
month = {Mon Jan 18 00:00:00 EST 2021}
}