Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death.
Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae , Filoviridae , Flaviviridae , and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data transcriptomics, proteomics, metabolomics, and lipidomics were acquired by microarray, RNA sequencing, or mass spectrometry analyses.
For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository.
This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology. These viruses comprise some of the most lethal and debilitating pathogens known to humans, exhibit significant potential for emergence of new pandemic strains, and impose substantial public health and economic burdens on the world community. Host responses against all four viruses are thought to contribute to pathogenesis in severe and fatal cases 2 , 3.
Therefore, the overarching goal of the OMICS-LHV Systems Biology Center was to use global host response data to model virus infections and identify host-dependent mechanisms that regulate severe or fatal disease. Samples were obtained from human or mouse cells and tissues infected with different viruses, host responses were measured using multi-omics approaches, and data were statistically processed using provided in-house developed software.
