CAREER: Complexity From Simplicity: Multi-scale Computational Deciphering of the Viral Life Cycle

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117- 2).

Viruses like Ebola and SARS-CoV-2 spread and cause disease through the combined action of multiple viral proteins working together. Limiting viral reproduction in patients will require a holistic view of how all of these proteins work together in one infected cell and across many cells in our bodies. This project will use a combination of experimental data and computer simulations to understand and predict the complex interactions that drive Ebola virus infection.

Such an understanding will allow the identification of any weak points in this protein network that can be targeted with new drugs. The project will also develop new research tools to advance the use of computer simulations to accelerate viral research. The educational objectives of the project will complement the research objectives by training the next generation of scientists (from high school to graduate student level) to readily combine computational and experimental research methods.

Together, the research and educational objectives will enable a comprehensive understanding of Ebola virus biology, integrated computational/experimental research tools, and a scientific workforce that can take advantage of computational technology to advance public health.

The overall objective of this proposal is to identify interconnected subcellular and inter-cellular mechanisms that drive viral replication and spread within a host, using Ebola virus as a model system. Mechanistic computational models are powerful tools that generate virtual versions of real biological systems, to enable analysis of complex systems-level dynamics.

In this project, mechanistic computational models, closely integrated with experimental data, will be used to identify key mechanisms in Ebola virus reproduction. New multi-dimensional analyses will be developed to elucidate coupled mechanisms, and computational predictions will be tested experimentally. Research objectives will quantify: 1) the impact of individual protein dynamics on viral production at the subcellular level using systems of ordinary differential equations; 2) the spatio-temporal impact of inter-cellular processes on cell-to-cell viral spread and proliferation using agent-based models; and 3) the combined impact of subcellular and inter-cellular mechanisms on viral replication across scales using multi-scale simulations.

These simulations will be calibrated to and validated against experimental data from the Ebola virus minigenome system that allows careful isolation of individual viral proteins and steps in the viral life-cycle (e.g. transcription and assembly). The research objectives will support educational objectives at the intersection of biology and computation.

The educational objectives will: integrate quantitative methods into existing biology curricula in an accessible and sustainable way; and advance interdisciplinary training in undergraduate biomedical engineering students. These objectives will be accomplished through a multi-tiered educational approach that connects students and teachers within, and between, high-school, undergraduate and graduate levels.

The project will develop: 1) quantitative learning modules for biology courses; 2) international interdisciplinary undergraduate courses; and 3) interdisciplinary research training for graduate students.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.