PRedicting Emergence Of Virulent Entities By Novel Technologies (PREVENT) Symposium - Session 2, Molecular Level Theme
Van Valen, David
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Paul Turner - Plenary Talk TITLE: "Predicting Evolution of Virus Emergence". Pathogen emergence occurs in many ways, but an overarching goal is to generally predict which pathogens are poised to emerge in the future. From an evolutionary-process perspective, this problem can be addressed by studying four interrelated topics that dictate success (or not) of pathogen emergence: evolvability, adaptability, constraint, and extinction. This talk emphasizes the power of experimental evolution to elucidate rules of pathogen emergence, especially in rapidly-evolving viruses. Also, the talk stresses why molecular biology and genomics can reveal crucial mechanistic details of experimental evolution, and why bridges to disciplines such as data/computer science and the participation of a diverse workforce are vital for studying emergence.Marc Riedel - Presentation TITLE: "Computationally Predicting and Characterizing the Immune Response to Viral Infections". Whether an individual mounts a strong response to SARS-Cov-2 or not depends, at least in part, on their genes. Specific genes code for the proteins on the surface of our cells that present viral protein fragments to the immune system. Killer T cells recognize these fragments and kill the infected cells. The immune response to COVID-19 hinges on whether the viral protein fragments bind into a groove in these cell-surface proteins -- like a key into a lock. The molecular biology is well understood. Whether a protein fragment binds or not is a question of 3D structure and simple atomic force calculations. The full proteome of the SARS-CoV-2 virus was published in March. However, no one has attempted to solve this problem for COVID-19 (or any other virus) because of the scale of the computation required. The conventional approach is to simulate at the atomic level: the trajectories of all atoms in the system are determined by numerically solving Newton's equations of motion. Simulating a single binding event takes *days* of super-computing time. There are 21,000 variants of the relevant genes in the population, each coding for slightly different 3D structures of the cell-surface proteins. There are about 38,000 viral protein fragments from SARS-CoV-2. So the scale of the problem is to perform about 798 million such simulations. We think that we can manage it. In joint work with the Mayo Clinic, we are develop custom software for this specific molecular problem, and we will deploy it at scale on cloud-computing infrastructure. With a targeted approach, we believe that we can turn 1 billion days of supercomputing time into 1 million minutes of cloud-computing time, which is manageable in terms of cost and complexity. Given reasonable cloud resources, the computation can complete in approximately one month. Note that if we develop this ability, it will be transformative for COVID-19. The knowledge of which viral protein fragments are good targets for the immune system will enable vaccine development. If successful, the same computational infrastructure could be deployed in the future for other viruses. It could also be transformative in other contexts, for instance for treatments of cancer via immunotherapy as well as for the treatment of autoimmune diseases.David Van Valen - Presentation TITLE: "Uncovering Host-Virus Interactions With Imaging-Based Reverse Genetics". Advances in imaging and genomics have increased our ability to capture information in the form of images. Concurrent advances in machine learning have made it easier to extract quantitative information from biological imaging data. Combined, these advances have positioned images to be a universal data type for biology. In this talk, I discuss how these trends in technology can potentially accelerate our understanding of host-virus interactions. Using the latency decision in bacteriophage lambda as a model system, I show how imaging-based reverse genetics can reveal the host-virus interactions that underlie complex aspects of the viral life cycle. I also describe a new technology for performing similar imaging-based studies of mammalian viruses.