The first aim of this thesis is to examine relationships between microRNAs targeting gene networks, combining knowledge from microRNA prediction databases into our microRNA Data Integration Portal (mirDIP). Modeling the microRNA:transcript interactome – referred to as the micronome – to build microRNA interaction networks of signalling pathways, we find genes within signalling pathways to be co-targeted by common microRNAs suggesting an unexpected level of transcriptional control. We identify two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets, to be more studied and more involved in cancer signalling than their intrapathway counterparts. The second aim was to undertake a more focused view, analyzing the characteristics of microRNAs within the micronome itself beginning with a focus on the under-examined microRNA terminal loop across the micronome to determine if this region of the microRNA structure might contribute to microRNA functioning. We have identified 2 main classes of microRNAs based on loop structure – perfect and occluded, which show biological relevance. We found regulatory motifs within microRNA terminal loops and found a large number of Frequently Occurring Words (FOWs) significantly overrepresented across the micronome. Set analysis of in vitro secreted microRNAs, microRNA expression across a panel of normal tissues, and microRNAs shown to be secreted in lung cancer shows that specific microRNA loop motifs within these groups are significantly overreperesented – suggesting that microRNA terminal loops harbour sequences bearing microRNA processing and localization signals.

Post-transcriptional regulation is carried out by RNA-binding proteins (RBPs) that bind to specific RNA molecules and control their processing, localization, stability and degradation. Experimental studies have successfully identified RNA targets associated with specific RBPs. However, because the locations of the binding sites within the targets are unknown and because RBPs recognize both sequence and structure elements in their binding sites, identification of RBP binding preferences from these data remains challenging. The unifying theme of this thesis is to identify RBP binding preferences from experimental data. First, we propose a protocol to design a complex RNA pool that represents diverse sets of sequence and structure elements to be used in an in vitro assay to efficiently measure RBP binding preferences. This design has been implemented in the RNAcompete method, and applied genome-wide to human and Drosophila RBPs. We show that RNAcompete-derived motifs are consistent with established binding preferences. We developed two computational models to learn binding preferences of RBPs from large-scale data. Our first model, RNAcontext uses a novel representation of secondary structure to infer both sequence and structure preferences of RBPs, and is optimized for use with in vitro binding data on short RNA sequences. We show that including structure information improves the prediction accuracy significantly. Our second model, MaLaRKey, extends RNAcontext to fit motif models to sequences of arbitrary length, and to incorporate a richer set of structure features to better model in vivo RNA secondary structure. We demonstrate that MaLaRKey infers detailed binding models that accurately predict binding of full-length transcripts.

Cytochrome c oxidase (CcO), the terminal enzyme in the electron transport chain, couples proton pumping to the reduction of dioxygen into water. The coupling mechanism remains to be elucidated. Previous studies have identified several mutations within CcO's primary proton uptake pathway (the D-channel) that decouple proton pumping from redox activity. Here, I examine the molecular basis for decoupling in single and double mutants of highly conserved residues, D132 and N139, in order to gain insight into the coupling mechanism. In particular, I use molecular dynamics and free energy simulations of a new, unconstrained model of bacterial CcO embedded in a solvated lipid bilayer to investigate how such mutants affect functional hydration and ionic selectivity in the D-channel. Results support earlier mechanistic insights obtained in our laboratory from simplified molecular models and predict a new, testable hypothesis by which cations such as K+ may inhibit proton pumping in charged mutants of N139.

Doctor of Philosophy

Doctor of Philosophy

Diss. (sammanfattning) Göteborg : Göteborgs universitet, 2007. / Härtill 3 uppsatser.

Diss. (sammanfattning) Uppsala : Univ., 2007. / Härtill 5 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2002. / Härtill 5 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 6 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst., 2004. / Härtill 5 uppsatser.