A Feedback Loop Couples Musashi-1 Activity to Omega-9 Fatty Acid Biosynthesis: A Dissertation

All living creatures change their gene expression program in response to nutrient availability and metabolic demands. Nutrients and metabolites can directly control transcription and activate second-­‐messenger systems. In bacteria, metabolites also affect post-­‐transcriptional regulatory mechanisms, but there are only a few isolated examples of this regulation in eukaryotes. Here, I present evidence that RNA-­‐binding by the stem cell translation regulator Musashi-­‐1 (MSI1) is allosterically inhibited by 18-­‐22 carbon ω-­‐9 monounsaturated fatty acids. The fatty acid binds to the N-­‐terminal RNA Recognition Motif (RRM) and induces a conformational change that prevents RNA association. Musashi proteins are critical for development of the brain, blood, and epithelium. I identify stearoyl-­‐CoA desaturase-­‐1 as a MSI1 target, revealing a feedback loop between ω-­‐9 fatty acid biosynthesis and MSI1 activity. To my knowledge, this is the first example of an RNA-­‐binding protein directly regulated by fatty acid. This finding may represent one of the first examples of a potentially broad network connecting metabolism with post-­‐transcriptional regulation

Allosteric inhibition of a stem cell RNA-binding protein by an intermediary metabolite

Gene expression and metabolism are coupled at numerous levels. Cells must sense and respond to nutrients in their environment, and specialized cells must synthesize metabolic products required for their function. Pluripotent stem cells have the ability to differentiate into a wide variety of specialized cells. How metabolic state contributes to stem cell differentiation is not understood. In this study, we show that RNA-binding by the stem cell translation regulator Musashi-1 (MSI1) is allosterically inhibited by 18-22 carbon omega-9 monounsaturated fatty acids. The fatty acid binds to the N-terminal RNA Recognition Motif (RRM) and induces a conformational change that prevents RNA association. Musashi proteins are critical for development of the brain, blood, and epithelium. We identify stearoyl-CoA desaturase-1 as a MSI1 target, revealing a feedback loop between omega-9 fatty acid biosynthesis and MSI1 activity. We propose that other RRM proteins could act as metabolite sensors to couple gene expression changes to physiological state

Quaking Regulates Hnrnpa1 Expression through Its 3′ UTR in Oligodendrocyte Precursor Cells

In mice, Quaking (Qk) is required for myelin formation; in humans, it has been associated with psychiatric disease. QK regulates the stability, subcellular localization, and alternative splicing of several myelin-related transcripts, yet little is known about how QK governs these activities. Here, we show that QK enhances Hnrnpa1 mRNA stability by binding a conserved 3′ UTR sequence with high affinity and specificity. A single nucleotide mutation in the binding site eliminates QK-dependent regulation, as does reduction of QK by RNAi. Analysis of exon expression across the transcriptome reveals that QK and hnRNP A1 regulate an overlapping subset of transcripts. Thus, a simple interpretation is that QK regulates a large set of oligodendrocyte precursor genes indirectly by increasing the intracellular concentration of hnRNP A1. Together, the data show that hnRNP A1 is an important QK target that contributes to its control of myelin gene expression

Metabolite sensing in eukaryotic mRNA biology

All living creatures change their gene expression program in response to nutrient availability and metabolic demands. Nutrients and metabolites can directly control transcription and activate second-messenger systems. More recent studies reveal that metabolites also affect post-transcriptional regulatory mechanisms. Here, we review the increasing number of connections between metabolism and post-transcriptional regulation in eukaryotic organisms. First, we present evidence that riboswitches, a common mechanism of metabolite sensing in bacteria, also function in eukaryotes. Next, we review an example of a double stranded RNA modifying enzyme that directly interacts with a metabolite, suggesting a link between RNA editing and metabolic state. Finally, we discuss work that shows some metabolic enzymes bind directly to RNA to affect mRNA stability or translation efficiency. These examples were discovered through gene-specific genetic, biochemical, and structural studies. A directed systems level approach will be necessary to determine whether they are anomalies of evolution or pioneer discoveries in what may be a broadly connected network of metabolism and post-transcriptional regulation. WIREs RNA 2013. doi: 10.1002/wrna.1167 For further resources related to this article, please visit the WIREs website

Quantitative approaches to monitor protein–nucleic acid interactions using fluorescent probes

Sequence-specific recognition of nucleic acids by proteins is required for nearly every aspect of gene expression. Quantitative binding experiments are a useful tool to measure the ability of a protein to distinguish between multiple sequences. Here, we describe the use of fluorophore-labeled oligonucleotide probes to quantitatively monitor protein/nucleic acid interactions. We review two complementary experimental methods, fluorescence polarization and fluorescence electrophoretic mobility shift assays, that enable the quantitative measurement of binding affinity. We also present two strategies for post-synthetic end-labeling of DNA or RNA oligonucleotides with fluorescent dyes. The approaches discussed here are efficient and sensitive, providing a safe and accessible alternative to the more commonly used radio-isotopic methods

A conserved three-nucleotide core motif defines Musashi RNA binding specificity

Musashi (MSI) family proteins control cell proliferation and differentiation in many biological systems. They are overexpressed in tumors of several origins, and their expression level correlates with poor prognosis. MSI proteins control gene expression by binding RNA and regulating its translation. They contain two RNA recognition motif (RRM) domains, which recognize a defined sequence element. The relative contribution of each nucleotide to the binding affinity and specificity is unknown. We analyzed the binding specificity of three MSI family RRM domains using a quantitative fluorescence anisotropy assay. We found that the core element driving recognition is the sequence UAG. Nucleotides outside of this motif have a limited contribution to binding free energy. For mouse MSI1, recognition is determined by the first of the two RRM domains. The second RRM adds affinity but does not contribute to binding specificity. In contrast, the recognition element for Drosophila MSI is more extensive than the mouse homolog, suggesting functional divergence. The short nature of the binding determinant suggests that protein-RNA affinity alone is insufficient to drive target selection by MSI family proteins