Generation of High-Resolution Chromatin Configuration and Epigenomics Datasets to Decipher Host-Pathogen Interactions
Authors:
Christina R. Steadman1* ([email protected]), V. Venu1, S. Adikari1, E. Small1, Cullen Roth1, J. Brown2, J. Kubicek-Sutherland1, P. Freimuth3, Shawn R. Starkenburg1 (PI)
Institutions:
1Los Alamos National Laboratory; 2University of Arizona; 3Brookhaven National Laboratory
Abstract
The ability to counter biological threats is limited given the lack of knowledge of host resilience mechanisms in the face of pervasive pathogens. Research suggests that epigenetic mechanisms and associated chromatin structure regulate the functionality of the genome and play profound roles in host-pathogen interactions. As such, this team hypothesizes that these processes vary between resilient versus susceptible hosts, potentially providing specific signatures (patterns) of infectivity. Further, these signatures may be attributed to classes of pathogens allowing for early detection and mitigation. Yet, the paucity of epigenomics and chromatin structural datasets from systematically tested pathogen exposures precludes identifying these proposed signatures for surveillance and diagnostics in novel species.
As such, this project’s goal is to develop an experimental workflow to generate large omics datasets to characterize and survey early onset molecular signatures of infection, with particular focus on viruses. The workflow is designed to utilize representative molecules for various classes of viruses in the same primary cell culture system (mammalian and plant) to generate single cell sequencing assessments for deep learning and exascale computing analysis. The team’s initial assessments demonstrate the relationship between specific local (epigenetic) and global (genomic) structures and their variability in response to infection, providing novel signatures.