title: Probing the Limits to MicroRNA-Mediated Control of Gene Expression.
abstract: According to the 'ceRNA hypothesis', microRNAs (miRNAs) may act as mediators of an effective positive interaction between long coding or non-coding RNA molecules, carrying significant potential implications for a variety of biological processes. Here, inspired by recent work providing a quantitative description of small regulatory elements as information-conveying channels, we characterize the effectiveness of miRNA-mediated regulation in terms of the optimal information flow achievable between modulator (transcription factors) and target nodes (long RNAs). Our findings show that, while a sufficiently large degree of target derepression is needed to activate miRNA-mediated transmission, (a) in case of differential mechanisms of complex processing and/or transcriptional capabilities, regulation by a post-transcriptional miRNA-channel can outperform that achieved through direct transcriptional control; moreover, (b) in the presence of large populations of weakly interacting miRNA molecules the extra noise coming from titration disappears, allowing the miRNA-channel to process information as effectively as the direct channel. These observations establish the limits of miRNA-mediated post-transcriptional cross-talk and suggest that, besides providing a degree of noise buffering, this type of control may be effectively employed in cells both as a failsafe mechanism and as a preferential fine tuner of gene expression, pointing to the specific situations in which each of these functionalities is maximized.
authors.affiliation: Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.|Soft and Living Matter Lab, Institute of Nanotechnology (CNR-NANOTEC), Consiglio Nazionale delle Ricerche, Rome, Italy.
authors.forename: Araks
authors.initials: A
authors.lastname: Martirosyan
authors.affiliation: Sorbonne Universités, UPMC, Institut de Calcul et de la Simulation, Paris, France.|Sorbonne Universités, UPMC, UMR 7238, Computational and Quantitative Biology, Paris, France.|CNRS, UMR 7238, Computational and Quantitative Biology, Paris, France.
authors.forename: Matteo
authors.initials: M
authors.lastname: Figliuzzi
authors.affiliation: Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.|INFN, Sezione di Roma 1, Rome, Italy.
authors.forename: Enzo
authors.initials: E
authors.lastname: Marinari
authors.affiliation: Dipartimento di Fisica, Sapienza Università di Roma, Rome, Italy.|Soft and Living Matter Lab, Institute of Nanotechnology (CNR-NANOTEC), Consiglio Nazionale delle Ricerche, Rome, Italy.|Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Rome, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: De Martino
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics*; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism; D008957:Models, Genetic; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
chemical_list: D035683:MicroRNAs; D014157:Transcription Factors
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