NIAID Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

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Principal Investigator

Description

Last updated on 2023-05-05T16:36:07+00:00 by LN Anderson

PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" (U19AI106772) program project was a highly integrated and comprehensive systems biology research core, funded by the NIH from 2013-06-01 to 2018-05-31, investigating the complex host response to infection in a series of NIAID priority pathogens. Resulting project deliverables include an extensive and comprehensive systems biology data collection that serves to both enhance predictive modeling of infectious disease and identifying functional regulators of severe human virus pathogenicity for exploiting new developments and therapeutic interventions assisting the human host response to Category A, B, and C priority pathogens.

Impact

Omics lethal human virus (OMICS-LHV) sub-project research activities conducted at Pacific Northwest National Laboratory (PNNL) included the Proteomics, Metabolomics, and Lipidomics Core (PML) and the Computational Modeling Core (CMC), where performed proteomic, metabolomic, lipidomic, and transcriptomic data profiling leveraged world-class mass spectrometry (MS)-based capability platforms and state-of-the-art statistical and computational techniques in providing linked primary and secondary transformation viral experimental infection data.

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. Using a highly integrated and multidisciplinary approach, linked primary data and metadata supporting secondary normalization datasets, provide critical information necessary for research reproducibility and long-term preservation. Enabling on-demand data access for research community consumption and developer reuse, serves to support new mechanistic insights and discoveries into host-pathogen interactions for aiding future biohazard data preparedness efforts in emergency response to global health crises involving viral infection.

Reference Citation

Anderson, Lindsey N, Eisfeld, Amie J, Waters, Katrina M, Pacific Northwest National Laboratory DataHub: Scientific Data Repository, and Modeling Host Responses to Understand Severe Human Virus Infections Program Project. PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection. United States. 2023. PNNL DataHub (Web). DOI: 10.25584/1971764

Reusable Digital Research Data Lifecycle Downloads

    Processed raw measurement (secondary data) qualitative viral experimental dataset DOI downloads contain one or more statistically processed quantitative data file(s) and differential expression analyses leveraging unique high-resolution instrument capabilities. In addition, all metadata files (including experimental designs, dataset summary, and viral titer workbooks as supporting metadata) necessary to support, corroborate, and verify the legitimacy of the viral infection studies reported herein have been included at each experimental dataset DOI download for enhanced transparency and reproducibility. Omics-LHV dataset DOI download (listed below) contain comprehensive time sampled measurement data from proteomic (P), metabolomic (M), lipidomic (L), and/or transcriptomics (T) experimental study that each have a direct relationship to a primary sample data accession corresponding to the Gene Expression Omnibus (GEO) and/or MassIVE domain repository. Collection references below contain multi-Omic host response to Ebola virus (EBOV) infection, Influenza A virus (lAV) infection, West Nile virus (WNV) infection, Middle Eastern Respiratory Syndrome coronavirus (MERS-CoV) infection, and human interferon (IFN) treatment.

    Project Dataset Catalogs

    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 Ebola Virus Infection, a Processed Dataset DOI Catalog Experimental Collection. United States. 2021. PNNL DataHub (Web). DOI: 10.25584/LHVEBOV/1784282.
    2. 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 Influenza A Virus Infection, a Processed Dataset DOI Catalog Experimental Collection. United States. 2021. PNNL DataHub (Web). DOI: 10.25584/LHVFLU/1773428.
    3. 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 West Nile Virus Infection, a Processed Dataset DOI Catalog Experimental Collection. United States. 2021. PNNL DataHub (Web). DOI: 10.25584/LHVWNV/1784305.
    4. 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 Interferon-Stimulated Response to Virus Infection, a Processed Dataset DOI Catalog Experimental Collection. United States. 2021. PNNL DataHub (Web). DOI: 10.25584/LHVIFN/1786979.
    5. 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.

    Source Code

    1. Kelly G. Stratton & Lisa M. Bramer. (2018). pmartR: Quality Control and Statistics for Mass Spectrometry-Based Biological Data (0.10.0). Zenodo. DOI: 10.5281/zenodo.6108668. URL: https://github.com/pmartR/pmartR/tree/v1.0.0
    2. Matthew Monroe, Cameron Casey, Grant Fujimoto, Christopher Wilkins, Joon-Yong Lee, Cameron Giberson, & Michael Degan. (2022). LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data. DOI: 10.5281/zenodo.6459463. URL: https://github.com/PNNL-Comp-Mass-Spec/LIQUID

    Linked Open Primary Datasets

    Sequencing Raw Measurement Data (T) - 2,555 total primary datasets

    Primary transcriptome experimental data collections and associated metadata are openly available from the NCBI BioProject platform, corresponding to umbrella BioProject PRJNA274402 and SuperSeries: GSE65575, have been linked to primary publication data accessions where possible. 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) - 21,194 total primary datasets

    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. 

    Reusable FAIRsharing Project Standards

    Raw Measurement Data

    Mass Spectrometry

    Microarray

    Digital Research Data

    Processed Raw Measurement Data

    Source Code

    Analysis Tools

     

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

        Project status

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        English
        Datasets (45)
        Publications (20)
        People (10)

        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...

        Tom Metz is a Principal Investigator within the Integrative Omics group at PNNL and the Metabolomics Team Lead for a group of scientists that focuses on development and applications of high throughput metabolomics and lipidomics methods to various biological questions. He has worked to develop state...

        Biography Bobbie-Jo Webb-Robertson has 20 years of experience in the statistics and data science fields. She currently serves as the chief scientist of computational biology in the Biological Sciences Division at PNNL. Her research portfolio is largely related to the biomedical field and primarily...

        Research Interests Lipidomics (environment and human systems) Mass spectrometry

        Biography Kristin Burnum-Johnson is a senior scientist and team lead of the Biomolecular Pathways team at PNNL. Burnum-Johnson earned her PhD in Biochemistry from Vanderbilt University with Professor Richard M. Caprioli and then completed a postdoctoral fellowship at PNNL with Dr. Richard D. Smith...

        Biography Young-Mo Kim is a senior bioanalytical chemist at PNNL. He received his PhD from Pohang University of Science and Technology in the School of Environmental Science and Engineering, studying analysis of metabolites during the bacterial and fungal degradation of xenobiotic substrates using...

        Biography Carrie Nicora is a senior research scientist (chemist III) at PNNL, specializing in high-throughput scientific research sample management using modular automation techniques for processing a wide range of biological specimens for proteomic, metabolomic, and lipidomic analysis. She is an...

        Biography Dr. Smith's research interests span the development of advanced analytical methods and instrumentation, with particular emphasis on high-resolution separations and mass spectrometry, and their applications in biological and biomedical research. This has included creating and applying new...

        Biography Kelly is a senior data scientist in the Computational Biology group within the Biological Sciences Division at Pacific Northwest National Laboratory (PNNL). After earning a MS in Biostatistics from the University of Washington in 2012, she worked at a cancer research company for two years...

        Data Sources (4)
        Methods (1)
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        Software (2)