MFB: Defining a molecular grammar for ribonucleoprotein particle trafficking

RNA molecules are actively transported in many tissues of our body, including muscle, brain, skin, digestive tract, heart, among others. This process is important to maximize efficiency of protein production and to provide spatial and temporal control of various biological processes. It is well known that molecular motors (kinesins) carry RNAs in cells by interacting with RNA binding proteins. There are 45 kinesin motors, hundreds of RNA binding proteins, and thousands of RNAs – and due to this complexity, we lack basic understanding of a specificity code that directs an RNA to the appropriate location(s) at the requisite time. This project seeks to elucidate any underlying specificity code that could then be leveraged for biotechnological applications. Objective 1 is to elucidate an association code between kinesins and RNA binding proteins, and Objective 2 is to integrate this knowledge with RNA targets. Success of this project will broadly benefit society by 1) opening up a new field of study, 2) providing training and outreach opportunities to students and postdocs, as well as other scientists involved in this work, and 3) providing a repository of data and knowledge that will be publicly shared via web servers and analytical pipelines. RNA sequences and structures interact with specific RNA binding proteins (RBPs); together, these interactions influence biogenesis of ribonucleoprotein particles (RNPs) and their cellular functions. It is known that trafficking of RNAs depends on kinesin motors in various tissues. Although the human genome encodes 45 kinesin motors, hundreds of RBPs, and thousands of localized mRNAs, only a handful of RBPs have been linked to specific kinesin motors. A broader specificity code for kinesin-RBP-RNA associations awaits discovery. The project will employ high-throughput molecular and cellular assays to 1) identify kinesin-RBP interactions and 2) determine a grammar for how RNA sequences recruit their RBP & kinesin partners, ultimately controlling RNP trafficking. For the former goal, an innovative centrosome recruitment assay will be scaled up by applying high-throughput automated imaging and computational analyses. For the latter goal, proximity ligation approaches, synthetic RNA libraries, and machine learning will be used to define and test principles of RNA localization in a variety of cell and tissue contexts. The project outcomes are expected to deliver a predictive understanding of key mechanisms that drive RNA transport. This project is supported by the Division of Molecular and Cellular Biosciences in the Biological Sciences Directorate and by the Division of Chemistry in the Mathematical and Physical Sciences Directorate. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.