Developing ProVis, a proteomic visualization tool for rapid visualization and analysis of complex proteomic datasets, to study DNA sensing against viral infections

Abstract

The application of proteomic approaches to study viral infection has provided significant insights into the viral replication cycle, host antiviral and immune activity, and viral mechanisms to inhibit host defenses. Using mass spectrometry, protein expression levels and protein-protein interactions during viral infections can be readily uncovered. The coupling of this information with biochemical assays can further provide insights on viral infections across space and time. However, the output of most proteomic search algorithms are inherently complex datasets containing thousands of proteins that can be difficult for both novice and experienced users to understand. Furthermore, these proteomics datasets are often obtained from experiments carried out in various conditions (e.g., infection types) and organisms, and cross-comparisons and data analysis can be time-consuming. To address this need, I developed ProVis, a proteomic visualization tool that integrates temporal proteomics data collected from different experimental contexts. With ProVis, users are able to easily search for proteins of interest and rapidly visualize temporal alterations in protein abundances. I applied ProVis to analyze the proteomes of cells infected by the doublestranded DNA virus herpes simplex virus 1 (HSV-1). First, to demonstrate the utility of this tool, I replicated the results from a previous publication on the proteome alterations in cells during infection by various HSV-1 strains. Next, to provide additional insight into the cellular mechanisms in place to combat viral infections, I applied ProVis with a new dataset investigating a class of anti-viral proteins called DNA sensors, which can detect viral DNA to initiate an anti-viral response. Among these is the interferon-inducible protein IFIX, which has recently been characterized as a sensor of foreign DNA in the nucleus. Given the limited research on IFIX as a nuclear DNA sensor, I performed a preliminary examination with ProVis of the temporal proteome alterations in IFIX-deficient cells, and I uncovered several interferon-induced proteins that are downregulated in the absence of IFIX and thus warrant further study. Overall, this thesis describes a new computational tool to analyze proteomics datasets and generate hypotheses for further experimentation.