Omics Lethal Human Viruses Project Profiling of the Host Response to MERS-CoV Infection, Processed Experimental Dataset Catalog

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Description

Last updated on 2024-02-11T22:41:43+00:00 by LN Anderson

Omics-LHV Profiling of Host Response to MERS-CoV Virus Infection

Background

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 and even fatal infections in humans where lethal host-associated mechanisms are not clearly defined. 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. This project was comprised of a multidisciplinary team of researchers with expertise in virology, host genetics, advanced high-throughput technologies, computational modeling, and data management integration strategies for quantifying the host immune response to cellular trafficking activities identified in primary host tissues and cell lines.

Impact

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 lifecycle datasets and project metadata. The knowledge gained from this work is expected to provide a strong foundation in facilitating a better understanding and treatment of Middle East Respiratory Syndrome coronavirus infections in humans for development of improved strategies for intervening with lethal virus disease, and unveiling mechanisms from highly collaborative state-of-the-art systems biology methodologies and unique data capture capabilities.

Viral Project Reference Citation

  1. Anderson, Lindsey N, Eisfeld, Amie J, Waters, Katrina M, and Modeling Host Responses to Understand Severe Human Virus Infections Program Project. PNNL DataHub Omics-LHV Project Profiling of the Host Response to Middle Eastern Respiratory Syndrome coronavirus Infection, a Processed Dataset DOI Catalog Experimental Collection. United States. 2021. PNNL DataHub (Web). DOI: 10.25584/LHVMERS/1813911

Accessible Digital Data DOI Downloads

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 (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 experimental infection study.

  • (P) Protein quantification by liquid chromatography mass spectrometry (LC-MS)
  • (M) Metabolite quantification by gas chromatography mass spectrometry (GC-MS)
  • (L) Lipid quantification by liquid chromatography mass spectrometry (LC-MS)
  • (T) Expression profiling by array (mRNA) and/or Non-coding RNA profiling by array (miRNA)

Multi-omic Dataset Collections

Note: MCL004 and MCL005 provide primary metadata only and do not contain processed data downloads. DOIs represent metadata documentation archival and serve to support raw measurement data located at the primary data repository.

  1. MCL001 DataHub DOI: 10.25584/LHVMCL001/1661931 (T)
  2. MCL002 DataHub DOI: 10.25584/LHVMCL002/1661933 (PML)
  3. MCL003 DataHub DOI: 10.25584/LHVMCL003/1661945 (PML)
  4. MCL004 DataHub DOI: 10.25584/LHVMCL004/1661946 (experimental metadata only)
  5. MCL005 DataHub DOI: 10.25584/LHVMCL004/1661947 (experimental metadata only)
  6. MFB001 DataHub DOI: 10.25584/LHVMFB001/1661935 (PMLT)
  7. MFB002 DataHub DOI: 10.25584/LHVMFB002/1661936 (PMLT)
  8. MFB003 DataHub DOI: 10.25584/LHVMFB003/1661937 (PMLT)
  9. MHAE001 DataHub DOI: 10.25584/LHVMHAE001/1661938 (PMLT)
  10. MHAE002 DataHub DOI: 10.25584/LHVMHAE002/1661939 (PMLT)
  11. MHAE003 DataHub DOI: 10.25584/LHVMHAE003/1661940 (PMLT)
  12. MM001 DataHub DOI: 10.25584/LHVMM001/1661941 (PMLT)
  13. MMVE001 DataHub DOI: 10.25584/LHVMMVE001/1661942 (PMLT)
  14. MMVE002 DataHub DOI: 10.25584/LHVMMVE002/1661943 (PMLT)
  15. MMVE003 DataHub DOI: 10.25584/LHVMMVE003/1661944 (PMLT)

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 [NCBITAXON:10090; BTO:0000763]. BTO ontology identifiers were assigned under release version 2021-10-26.

Linked Primary Data Repository Standards

Sequencing Raw Measurement Data (T) - NCBi BioProject Repository (10.25504/FAIRsharing.aqhv1y), GEO Repository (10.25504/FAIRsharing.5hc8vt)

Primary transcriptome experimental data collections and associated metadata are openly available from the NCBI BioProject platform, and have been linked to primary publication data accessions where possible. Dataset series have been deposited at the Gene Expression Omnibus (GEO), a public domain community data repository supported by the NIH, for promoting the free exchange of MIAME-compliant gene expression profile and array-based data for reuse and discovery. 

Mass Spectrometry Raw Measurement Data (PML) - MassIVE Repository (10.25504/FAIRsharing.LYsiMd)

Primary mass spectrometry proteome, metabolome, and lipidome experimental data and corresponding parameter files, including those used for accurate mass and time (AMT) tag database generation, are openly available for download at the MassIVE data repository under the following accessions. The Mass Spectrometry Interactive Virtual Environment (MassIVE) is a public domain community data repository promoting the free exchange of mass spectrometry data for reuse and discovery.

 

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.

Data Licensing

CC BY 4.0 (dataset DOI downloads), CC0 1.0 (PNNL DataHub policy default)

    Project status

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    English
    Datasets (15)
    Publications (3)
    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...

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    Methods (1)
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