Last updated on 2023-01-30T00:09:57+00:00 by LN Anderson
Omics-LHV Profiling of Host Response to MERS-CoV Virus Infection
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 are 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 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.
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.
Project Page Citation
Anderson, Lindsey, 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 Secondary Digital Data Download DOIs
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 [NCBITAXON:1335626] 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)
Secondary Transformation Omics Data
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.
- MCL001 DataHub DOI: 10.25584/LHVMCL001/1661931
- MCL002 DataHub DOI: 10.25584/LHVMCL002/1661933
- MCL003 DataHub DOI: 10.25584/LHVMCL003/1661945
- MFB001 DataHub DOI: 10.25584/LHVMFB001/1661935
- MFB002 DataHub DOI: 10.25584/LHVMFB002/1661936
- MFB003 DataHub DOI: 10.25584/LHVMFB003/1661937
- MHAE001 DataHub DOI: 10.25584/LHVMHAE001/1661938
- MHAE002 DataHub DOI: 10.25584/LHVMHAE002/1661939
- MHAE003 DataHub DOI: 10.25584/LHVMHAE003/1661940
- MM001 DataHub DOI: 10.25584/LHVMM001/1661941
- MMVE001 DataHub DOI: 10.25584/LHVMMVE001/1661942
- MMVE002 DataHub DOI: 10.25584/LHVMMVE002/1661943
- MMVE003 DataHub DOI: 10.25584/LHVMMVE003/1661944
Linked Open Primary Data Accessions
Primary Sequencing Raw Measurement Data (T)
The Gene Expression Omnibus (GEO) is a public domain community data repository, supported by the NIH, promoting the free exchange of MIAME-compliant gene expression profile and array-based data. Primary transcriptome (Agilent and Affymetrix microarray) experimental data collections (txt and txt.gz) and associated metadata are openly available from NCBI under the following BioProject accessions, linked to primary publication data accessions where possible.
Primary Mass Spectrometry Raw Measurement Data (PML)
The Mass Spectrometry Interactive Virtual Environment (MassIVE) is a public domain community data repository promoting the free exchange of mass spectrometry data. Primary mass spectrometry proteome, metabolome, and lipidome data (raw and mzML) along with corresponding parameter files (xml), 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.
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.
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).
Last updated on 2023-01-30T00:09:57+00:00 by LN Anderson