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The interaction between proteins and RNA has gained increased attention as a key regulatory mechanism of RNA translation beyond conventional postulated mechanisms. It is also involved in various pathologies, including cancer and neurodegenerative disorders. In this thesis, the interactions between the RNA-binding protein Musashi-1 (MSI1) and both linear and hairpin-like RNA strands have been investigated using time-resolved and structural technologies, such as SPR biosensors, LigandTracer, and NMR.

Initially, the interactions of the two RNA recognition motifs (RRM1 and RRM2) in MSI1 were characterized separately. Both motifs exhibited high affinity for the UAG motif, with no significant difference between linear and hairpin-like RNA. These interactions followed a 1:1 binding mechanism, with relatively fast, but well-defined association and dissociation rate constants. Next, the interaction of the N-terminal region of MSI1, containing both RRMs, was analyzed, revealing a bivalent binding mechanism. Commercial software was not suitable for distinguishing the fast monovalent and slow bivalent interactions. Therefore, a novel method was developed to quantify kinetic rate constants and binding affinities.

To explore the determinants for the specificity of the interaction, RNA mutants and protein variants were designed to shift RRM2 recognition from the UAG to the CAG motifs. Comprehensive characterization confirmed the impact of these mutations and RNA structural modifications on the interaction.

Additionally, to examine MSI1 regulatory role in synthetic biology, a post-transcriptionally controlled circuit was engineered in E. coli using MSI1 binding to RNA strands. This system, developed on solid media, utilized sfGFP fluorescence as a reporter. Data analysis using the Gompertz growth model correlated well with previously published data on bacteria in suspension. The regulatory effect of oleic acid, a potential MSI1 allosteric inhibitor, was confirmed using this assay. Similarly, MSI1 inhibition effects were assessed in HCT-116 colorectal cancer cells, revealing that both oleic acid and luteolin impacted cell proliferation and CD44v6 receptor expression.

In conclusion, this work has resulted in novel methods and insights for studying and understanding the kinetics and mechanisms of protein-RNA interactions.

Reporter systems are widely used to study biomolecular interactions and processes in vivo, representing one of the basic tools used to characterize synthetic regulatory circuits. Here, we developed a method that enables the monitoring of RNA–protein interactions through a reporter system in bacteria with high temporal resolution. For this, we used a Real-Time Protein Expression Assay (RT-PEA) technology for real-time monitoring of a fluorescent reporter protein, while having bacteria growing on solid media. Experimental results were analyzed by fitting a three-variable Gompertz growth model. To validate the method, the interactions between a set of RNA sequences and the RNA-binding protein (RBP) Musashi-1 (MSI1) were evaluated, as well as the allosteric modulation of the interaction by a small molecule (oleic acid). This new approach proved to be suitable to quantitatively characterize RNA–RBP interactions, thereby expanding the toolbox to study molecular interactions in living bacteria, including allosteric modulation, with special relevance for systems that are not suitable to be studied in liquid media.

We report here an experimental-computational study of hydrated TiO2 anatase nanoparticles interacting with glycine, where we obtain quantitative agreement of the measured adsorption free energies. Ab initio simulations are performed within the tight binding and density functional theory in combination with enhanced free-energy sampling techniques, which exploit the thermodynamic integration of the unbiased mean forces collected on-the-fly along the molecular dynamics trajectories. The experiments adopt a new and efficient setup for electrochemical impedance spectroscopy measurements based on portable screen-printed gold electrodes, which allows fast and in situ signal assessment. The measured adsorption free energy is -30 kJ/mol (both from experiment and calculation), with preferential interaction of the charged NH3+ group which strongly adsorbs on the TiO2 bridging oxygens. This highlights the importance of the terminal amino groups in the adsorption mechanism of amino acids on hydrated metal oxides. The excellent agreement between computation and experiment for this amino acid opens the doors to the exploration of the interaction free energies for other moderately complex bionano systems.

The RNA recognition motif (RRM) is the most common RNA-binding protein domain identified in nature. However, RRM-containing proteins are only prevalent in eukaryotic phyla, in which they play central regulatory roles. Here, we engineered an orthogonal post-transcriptional control system of gene expression in the bacterium Escherichia coli with the mammalian RNA-binding protein Musashi-1, which is a stem cell marker with neurodevelopmental role that contains two canonical RRMs. In the circuit, Musashi-1 is regulated transcriptionally and works as an allosteric translation repressor thanks to a specific interaction with the N-terminal coding region of a messenger RNA and its structural plasticity to respond to fatty acids. We fully characterized the genetic system at the population and single-cell levels showing a significant fold change in reporter expression, and the underlying molecular mechanism by assessing the in vitro binding kinetics and in vivo functionality of a series of RNA mutants. The dynamic response of the system was well recapitulated by a bottom-up mathematical model. Moreover, we applied the post-transcriptional mechanism engineered with Musashi-1 to specifically regulate a gene within an operon, implement combinatorial regulation, and reduce protein expression noise. This work illustrates how RRM-based regulation can be adapted to simple organisms, thereby adding a new regulatory layer in prokaryotes for translation control.

The kinetics of the interaction between Musashi-1 (MSI1) and RNA have been characterized using surface plasmon resonance biosensor analysis. Truncated variants of human MSI1 encompassing the two homologous RNA recognition motifs (RRM1 and RRM2) in tandem (aa 1-200), and the two RRMs in isolation (aa 1-103 and aa 104-200, respectively) were produced. The proteins were injected over sensor surfaces with immobilized RNA, varying in sequence and length, and with one or two RRM binding motifs. The interactions of the individual RRMs with all RNA variants were well described by a 1:1 interaction model. The interaction between the MSI1 variant encompassing both RRM motifs was bivalent and rapid for all RNA variants. Due to difficulties in fitting this complex data using standard procedures, we devised a new method to quantify the interactions. It revealed that two RRMs in tandem resulted in a significantly longer residence time than a single RRM. It also showed that RNA with double UAG binding motifs and potential hairpin structures forms less stable bivalent complexes with MSI1 than the single UAG motif containing linear RNA. Substituting the UAG binding motif with a CAG sequence resulted in a reduction of the affinity of the individual RRMs, but for MSI1, this reduction was strongly enhanced, demonstrating the importance of bivalency for specificity. This study has provided new insights into the interaction between MSI1 and RNA and an understanding of how individual domains contribute to the overall interaction. It provides an explanation for why many RNA-binding proteins contain dual RRMs.

RNA Recognition Motifs (RRMs) are essential post-transcriptional regulators of gene expression in eukaryotic cells. The Human Musashi-1 (MSI-1) is an RNA-binding protein that recognizes (G/A)U1-3AGU and UAG sequences in diverse RNAs through two RRMs and regulates the fate of target RNA.

Here, we combined structural biology and computational approaches to analyse the binding of the RRM domains of human MSI-1 with single-stranded and structured RNAs ligands. We used our recently developed computational tool RRMScorer to design a set of mutants of the MSI-1 protein to bind novel RNA sequences to alter the binding selectivity. The in-silico predictions of the designed protein-RNA interactions are assessed by NMR and SPR. These experiments also are used to study the competition of the two RRM domains of MSI-1 for the same binding site within linear and harpin RNA. Our experimental results confirm the in-silico designed interactions, thus opening the way for the development of new biomolecules for in vitro and in vivo studies and downstream applications.