Center for Viral Systems Biology (CViSB)

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Project Summary - Center for Viral Systems Biology (CViSB) The COVID-19 pandemic is a stark reminder of the threat posed by infectious diseases, but other priority pathogens, such as Lassa and Ebola viruses, continue to pose significant challenges in endemic areas. Infection with Lassa, Ebola, and SARS-CoV-2 viruses can lead to diverse acute and long-term outcomes, ranging from mild or asymptomatic disease to long-term sequelae or death. When we established the Center for Viral Systems Biology (CViSB, cvisb.org) in 2018, we set a main goal of answering why. With a focus on Ebola, Lassa, and via a scope expansion, COVID-19, we have achieved this goal by identifying clinical, immunological, genetic, and virus molecular factors that determine the outcome of disease. In this renewal application, we will move beyond standard systems biology data generation and analysis and use a reverse translational approach to expand on our prior work with a focus on both fundamental research and translational application. Our central hypothesis remains that complex networks of viral and human factors, including distinct clinical, immunological, genetic, virological, and physiological attributes play key roles in determining the outcome and spread of Lassa, Ebola, and COVID-19. Our overall goal is to identify these molecular networks and provide a deep system-level understanding of the virus, host, and environmental drivers of disease severity and spread to discover predictive markers of human disease. We will successfully achieve this goal by applying ‘omics’ technologies, wearables, and high-throughput experimental approaches to unique patient, vaccinee, and survivor cohorts in West Africa and the United States. Built around two interconnected projects and four cores, we will complete the following major goals: (1) we will integrate complex systems immunology, host genetic, physiological, clinical, and metabolic datasets to perform predictive modeling and define biosignatures that describe the risk, severity, and outcome of Lassa, Ebola, and COVID-19 using cohorts in West Africa and the United States. (2) We will integrate large-scale host-virus genomic datasets with population data and high-throughput experimental approaches to build multivariate network analyses and dynamic growth models to elucidate the molecular epidemiology, functional evolution, adaptive immunity, and host-pathogen dynamics of Lassa virus, Ebola virus, and SARS-CoV-2. (3) We will expand and develop high-throughput experimental methods, open-source software, machine learning tools, and web-based platforms to analyze and visualize large-scale datasets that enable real-time interrogation and interpretation of complex host-pathogen-environment network structures and dynamics. (4) We will continue to develop and maintain robust databases and application programming interfaces for open-source CViSB generated systems biology datasets and perform outreach and training to promote the use of systems biology to study infectious diseases.