All cellular functions require that proteins group together in different combinations, forming complexes with highly specialized functions. Yet, conventional approaches for studying such complexes have significant limitations. For example, because some complexes come apart easily, they are invisible to many standard experimental approaches. In addition, some proteins can alter their shape to interact with different partner proteins. To address some of the limitations of conventional approaches to study protein complexes, a new method called DEEPN will be refined that uses modern cutting-edge DNA sequencing technology to help identify protein interactions. DEEPN will be applied to the study of an important family of proteins that change their shape in response to biological stimuli. These studies will have high scientific impact since they will define new connections between proteins and their functions. This project will simplify and streamline this new methodological approach so that it is easy, effective and economical for other scientific investigators of varying levels of expertise (including undergraduate researchers) to perform. In addition, a number of interdisciplinary research and educational activities for undergraduates will be developed.
The DEEPN strategy (Dynamic Enrichment for Evaluation of Protein Networks) was developed as a robust method for simultaneous discovery of dozens of protein interactions with statistical certainty. DEEPN uses newly available next-generation, high-throughput DNA sequencing approaches to computationally determine protein interactions. This technique will be used to comprehensively describe the protein complexes that involve members of an important family of proteins that regulate many cell functions, the Ras superfamily. These proteins are among those that undergo a shape change that influences their function, and DEEPN will be used to follow specifically how such changes affect the composition of protein complexes. The scientific merit of this work is that it will bring new mechanistic insights into how members of the Ras superfamily of proteins collectively contribute to almost all aspects of cellular function. The impact of this study will be broad because it will: 1) streamline methods and develop new computational tools that will allow other investigators to apply the DEEPN approach to the study of other important cellular functions, and 2) integrate aspects of the DEEPN approach into a laboratory class, exposing upper-level undergraduate students to how molecular biology and computational bioinformatics can be combined for modern state-of-the-art cell biology research.
