Investigations of Viral RNA Replication in Living Cells.
Rutgers University Newark, Newark NJ
Investigators
Abstract
Intellectual Merit RNA viruses often induce massive morphological changes upon infecting their host cells, in particular by generating unconventional membrane-bound organelles that become viral replication factories. This project studies formation of this organelle and its relevance to viral replication in a model system of cellular infection by Coxsackievirus (a member of the picornavirus family that also includes polio virus). Earlier findings documented the sensitivity of picornavirus replication to the activity of the cellular small GTPase Arf, which is known to regulate organelle dynamics in the secretory pathway of eukaryotic cells. Hence, it is hypothesized that picornaviruses may selectively harness the nascent organelle building activities of the secretory pathway machinery (including Arf GTPases and their effectors) to build unconventional organelles that are optimal for viral replication. This study will rely on live-cell imaging methodologies to monitor the host-pathogen interaction. Fluorescence tagging of specific proteins will unravel the dynamics of replication organelle formation in infected cells. A new methodology, based on molecular beacons (i.e. nucleic acid probes that can detect viral RNA in living cells) will be developed to probe the dynamic interplay between viral RNA replication and the secretory pathway machinery. The combination of these two techniques is particularly well-suited to the study of the virus-cell interface because they can provide valuable spatio-temporal information without perturbing the dynamic events themselves, thereby allowing investigation of virus host events at the single-cell level. Ultimately, this project will glean information on the formation, organization and dynamics of replication organelles in individual cells. In particular, the roles of known components of the secretory pathway machinery in generating the viral RNA replication organelles will be investigated. A biological screen will be performed to identify as yet uncharacterized components of the secretory pathway whose expression regulates organelle formation and viral RNA replication. Determining the cellular components of these virus-specific organelles will shed light on how specific host activities contribute to the formation of an organelle that facilitates viral RNA replication. Moreover, characterizing the role of cellular components for the formation of unconventional organelles, such as those for viral replication, may provide important information about their respective roles in conventional organelle biogenesis taking place in eukaryotic cells. Finally the strategies developed in the project will provide a novel framework for others to explore the dynamics of host-pathogen interactions. Broader Impacts Live-cell imaging is a critical component of current research in the life sciences, providing unparalleled insights. However, the majority of biology majors and M.S./Ph.D. candidates do not have the opportunity to see the power of this approach much less gain experience with it. This project will provide opportunity for students to learn and apply to a complex biological phenomenon such as virus-host dynamics a variety of state of the art live-cell imaging methodologies, image processing/analysis techniques and quantitative data analysis and modeling. In addition, a live-cell imaging course has been created to introduce undergraduate and graduate students to the power of imaging methodologies towards tackling a wide range of cell physiology problems. The interdisciplinary nature of the project and its focus on organelle biogenesis and viral RNA dynamics has generated an excellent opportunity to forge collaborations with mathematicians and chemists from neighboring institutions in Newark, New Jersey. This project will generate new perspectives on and novel methods of inquiry into the fundamental biological problem of host-pathogen interactions.
View original record on NSF Award Search →