Core D: Bioinformatics and Modeling Core

CORE D: PROJECT SUMMARY/ABSTRACT The role of the Bioinformatics and Modeling Core is to process, analyze, and model the genome and proteome-level datasets produced in this project. This will be accomplished through two main objectives: (1) to design and provide tools to analyze experimental data, and (2) to integrate data into network models of host response and pathogenicity. Previously developed in-house tools, publicly available established relevant software packages, and new bioinformatics tools developed in the Projects will be integrated, automated, and then applied to data generated by the Projects, and made available to the larger research community through web-based interfaces. EBOV-relevant publicly available and locally produced data will be organized into databases that can be used by Program investigators and others to test hypotheses.

The following Specific Aims will be spearheaded by the Core in close collaboration with the project investigators. Aim 1. Characterize the transcriptional, posttranscriptional, and posttranslational mechanisms impacted by EBOV infection in cells and organisms. Tools aimed for revealing the host gene regulatory mechanisms impacted by EBOV infection will be developed and applied.

Differentially expressed, modified, and processed RNAs and genomic regulatory regions between infected and uninfected cells will be identified. Differential posttranslational protein modifications will also be identified. Specific altered regulatory mechanisms will be predicted using transcription factor, cofactor, epigenetic regulator, RNA binding protein, and microRNA enrichment analyses. The Core will systematically intersect the genomic locations of infection-modified loci and processed custom databases containing more than 20,000 human publicly available genome-wide databases to reveal molecular processes and factors affected by EBOV infection.

Aim 2. Model cell type-specific responses to EBOV in vitro and in vivo. The Core will build an integrative model of the mechanisms controlling EBOV pathogenesis by combining data generated the Projects. To this end, they will employ network-based data integration approaches using network propagation-based techniques.

In brief, modeling approaches will be applied to find correlates and associations between transcriptional, posttranscriptional, and posttranslational data to define host and viral factors that (1) reflect the activation states of the network; (2) control cell response to EBOV; and (3) can be tested for both diagnostics and therapies. Aim 3. Facilitate internal and external collaborations through metadata standardization, and interactive web and programmatic data interfaces. Streamlined computational pipelines will be built using best-standard engineering processes and release the code and data through web-based interfaces.

The Bioinformatics and Modeling Core will facilitate centralized data collection, exchange and analysis, and provide expertise by the members of the Core encompassing genetics, viral infection, functional genomics, gene regulation, proteomics, modeling, and bioinformatics.

Grant Number: 5P01AI150585-05
NIH Institute/Center: NIH
Principal Investigator: Alexander Bukreyev