Ribonucleoprotein dynamics connects mRNA networks with drug mechanisms

Abstract

Mol Syst Biol. 5: 289 Beyond transcription, gene expression is potently controlled through processes that affect pre‐mRNA splicing and maturation, as well as mRNA transport, turnover, storage, and translation. These events are tightly regulated by two main classes of trans ‐binding factors, RNA‐binding proteins (RBPs) and non‐coding RNAs (ncRNAs) (Moore, 2005; Mattick and Makunin, 2006). RBPs bind to target transcripts and influence virtually all facets of post‐transcriptional gene expression; ncRNAs, particularly microRNAs (miRNAs), mainly lower the translation and stability of target mRNAs (Keene, 2007; Bartel, 2009). As mRNAs transit through the cell, their association with RBPs and miRNAs determines their recruitment to cellular sites such as processing bodies (PBs), stress granules (SGs), polysomes, the exosome, and the RNA‐induced silencing complex (RISC), each specialized in distinct aspects of mRNA metabolism (Filipowicz et al , 2008). In this manner, ribonucleoprotein (RNP) interactions directly affect the types, location, and abundance of expressed proteins. In a report published in Molecular Systems Biology , Mukherjee et al (2009) use quantitative RNA dynamics to present a fundamentally new approach to study global RNP networks. The study bridges two key and reciprocal concepts in post‐transcriptional gene regulation. The first is that each individual mRNA is capable of associating with numerous RBPs. Several studies have shown that RBPs can interact combinatorially on a single mRNA and thereby alter its post‐transcriptional fate and ultimately the levels of expressed protein; for example, an RBP can compete or cooperate with another RBP for binding to a shared target mRNA, while miRNAs can promote or prevent the action of RBPs on a given mRNA (e.g., Lal et al , 2004; George and …