Grant Gucinski, Hayes Lab, PhD Defense

Speaker

Grant Gucinski, Hayes Lab

Date and Location

Monday June 12, 2017 10:00am to 11:00am
MSI Auditorium

Abstract

Title: "Delivery and Activity of Contact-Dependent Growth Inhibition Nuclease Toxins"

Abstract: Bacteria exist in diverse environments where they are in constant competition for resources, driving the evolution of various strategies to promote their own survival and proliferation. One such strategy is contact-dependent growth inhibition (CDI), a form of bacterial competition mediated by the CdiB/CdiA family of two-partner secretion proteins. CDI+ bacteria utilize CdiB to export CdiA, a long filamentous protein which extends from the cell surface where they can interact with neighboring bacteria. Upon recognition of target bacteria, CdiA delivers a toxin derived from its C-terminus (CdiA-CT) that results in growth inhibition. CDI+ bacteria also produce an immunity protein, CdiI, which binds the CdiA-CT and neutralizes its activity. CdiA-CT sequences are highly variable amongst bacteria, reflecting a multitude of different toxins that may be deployed in competition.

The study of CDI is still in its infancy, and many questions remain. Accordingly, this presentation will address recent developments in our understanding of CDI. First, we will present data suggestive of a model for toxin transport into target bacteria. CdiA-CTs are often composed of two domains with distinct functions. While the very C-terminal domain typically possesses toxic nuclease activity, the N-terminal domain appears to facilitate binding to specific inner membrane proteins and subsequent translocation into the cytoplasm. Next, we will present the crystal structure of a novel CDI tRNase toxin in complex with its cognate immunity protein and elongation factor Tu (EF-Tu). Furthermore, we demonstrate that this toxin has a unique ribonuclease activity that requires not only EF-Tu, but also EF-Ts. As such, we suggest that the utilization of target-cell factors is a particularly advantageous strategy for the evolution of robust CDI systems.