No Mere MiRs♦
Ontology highlight
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PROVIDER: S-EPMC2662091 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a "module" in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN) by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what actually constitutes a "module". In a self-consistent manner, proteins are grouped into "functional roles" if they interact in similar ways with other proteins according to their functional roles. Such grouping may well result in cohesive modules again, but only if the network structure actually supports this. We applied our method to the PIN from the Human Protein Reference Database (HPRD) and found that a representation of the network in terms of cohesive modules, at least on a global scale, does not optimally represent the network's structure because it focuses on finding independent groups of proteins. In contrast, a decomposition into functional roles is able to depict the structure much better as it also takes into account the interdependencies between roles and even allows groupings based on the absence of interactions between proteins in the same functional role. This, for example, is the case for transmembrane proteins, which could never be recognized as a cohesive group of nodes in a PIN. When mapping experimental methods onto the groups, we identified profound differences in the coverage suggesting that our method is able to capture experimental bias in the data, too. For example yeast-two-hybrid data were highly overrepresented in one particular group. Thus, there is more structure in protein-interaction networks than cohesive modules alone and we believe this finding can significantly improve automated function prediction algorithms.
| S-EPMC2813263 | biostudies-literature
Project description:MicroRNAs (miRNAs), small RNA molecules that post-transcriptionally regulate mRNA expression, are crucial in diverse developmental and physiological programs and their misregulation can lead to disease. Chemically modified oligonucleotides have been developed to modulate miRNA activity for therapeutic intervention in disease settings, but their mechanism of action has not been fully elucidated. Here we show that the miRNA inhibitors (anti-miRs) physically associate with Argonaute proteins in the context of the cognate target miRNA in vitro and in vivo. The association is mediated by the seed region of the miRNA and is sensitive to the placement of chemical modifications. Furthermore, the targeted miRNAs are stable and continue to be associated with Argonaute. Our results suggest that anti-miRs specifically associate with Argonaute-bound miRNAs, preventing association with target mRNAs, which leads to subsequent stabilization and thus increased expression of the targeted mRNAs.
| S-EPMC4084633 | biostudies-literature