Congratulations to Dr. O'Donnell for recieving the NSF CAREER grant for Regulation of Cargo Selection and Ubiquitination by Protein Trafficking Adaptors!

This is a 5 year grant with funding of $1,052,291.

Below are some pictures of the champaign celebration and the summary of the grant.

Cells must make correct ‘decisions’ to control protein activity, levels and localization to survive. For example, cell surface proteins such as nutrient transporters and hormone receptors–referred to hereafter as ‘cargo’–are removed and destroyed when not needed. How is the decision made to relocalize these proteins?

Trafficking adaptors selectively bind to and facilitate relocalization of cargo proteins. Importantly, trafficking adaptors recruit a ubiquitin ligase that adds a ubiquitin (Ub) peptide to protein cargo, which acts as a signal to direct protein trafficking and degradation. This model for trafficking adaptor function is deceptively simple, as many questions remain unanswered. How does trafficking adaptor-ubiquitin ligase association alter cargo ubiquitination and trafficking? How is the adaptor modified to regulate cargo trafficking? And, how do these adaptors achieve selective cargo recognition? Answers to these questions are critical as defective trafficking adaptor function has catastrophic consequences for the cell.

The α-arrestins, conserved from yeast to humans and related to the well-characterized and clinically important mammalian β-arrestins, are a recently described class of trafficking adaptor, that play a critical role in selective protein trafficking. While we have yet to appreciate the breadth of α-arrestin function, in yeast they interact with the Ub ligase Rsp5 to regulate the trafficking fate of cargo proteins. Here the PI proposes to: 1) Define how disruption of the α-arrestin-Rsp5 interface impairs the Ub ligase efficiency of Rsp5; 2) Determine how ubiquitination regulates α-arrestin-mediated trafficking and determine how Rsp5 activity is restricted to permit α-arrestin mono-ubiquitination; and 3) Comprehensively identify α-arrestin cargo proteins and define motifs that dictate α-arrestin-cargo interaction using a robust, new computational approach that employs evolutionary signatures to infer functional relationships.