From Endogenous to Synthetic microRNA-Mediated Regulatory Circuits: An Overview

MicroRNAs are short non-coding RNAs that are evolutionarily conserved and are pivotal post-transcriptional mediators of gene regulation. Together with transcription factors and epigenetic regulators, they form a highly interconnected network whose building blocks can be classified depending on the number of molecular species involved and the type of interactions amongst them. Depending on their topology, these molecular circuits may carry out specific functions that years of studies have related to the processing of gene expression noise. In this review, we first present the different over-represented network motifs involving microRNAs and their specific role in implementing relevant biological functions, reviewing both theoretical and experimental studies. We then illustrate the recent advances in synthetic biology, such as the construction of artificially synthesised circuits, which provide a controlled tool to test experimentally the possible microRNA regulatory tasks and constitute a starting point for clinical applications

Gene autoregulation via intronic microRNAs and its functions

Background: MicroRNAs, post-transcriptional repressors of gene expression, play a pivotal role in gene regulatory networks. They are involved in core cellular processes and their dysregulation is associated to a broad range of human diseases. This paper focus on a minimal microRNA-mediated regulatory circuit, in which a protein-coding gene (host gene) is targeted by a microRNA located inside one of its introns. Results: Autoregulation via intronic microRNAs is widespread in the human regulatory network, as confirmed by our bioinformatic analysis, and can perform several regulatory tasks despite its simple topology. Our analysis, based on analytical calculations and simulations, indicates that this circuitry alters the dynamics of the host gene expression, can induce complex responses implementing adaptation and Weber's law, and efficiently filters fluctuations propagating from the upstream network to the host gene. A fine-tuning of the circuit parameters can optimize each of these functions. Interestingly, they are all related to gene expression homeostasis, in agreement with the increasing evidence suggesting a role of microRNA regulation in conferring robustness to biological processes. In addition to model analysis, we present a list of bioinformatically predicted candidate circuits in human for future experimental tests. Conclusions: The results presented here suggest a potentially relevant functional role for negative self-regulation via intronic microRNAs, in particular as a homeostatic control mechanism of gene expression. Moreover, the map of circuit functions in terms of experimentally measurable parameters, resulting from our analysis, can be a useful guideline for possible applications in synthetic biology.Comment: 29 pages and 7 figures in the main text, 18 pages of Supporting Informatio

microRNA-mediated noise processing in cells: A fight or a game?

In the past decades, microRNAs (miRNA) have much attracted the attention of researchers at the interface between life and theoretical sciences for their involvement in post-transcriptional regulation and related diseases. Thanks to the always more sophisticated experimental techniques, the role of miRNAs as “noise processing units” has been further elucidated and two main ways of miRNA noise-control have emerged by combinations of theoretical and experimental studies. While on one side miRNAs were thought to buffer gene expression noise, it has recently been suggested that miRNAs could also increase the cell-to-cell variability of their targets. In this Mini Review, we focus on the role of miRNAs in molecular noise processing and on the advantages as well as current limitations of theoretical modelling

Dynamics of p53 and Cancer

Cancer is a multifactorial disease in which cell types lost their capability to regulate growth, proliferation, and cell death pathways, causing the uncontrolled proliferation of tumor cells. Cell death pathway is supported by the operation of the p53–Mdm2-negative feedback loop that has a central role to prevent the development of tumor cells. Under severe DNA damage, this loop takes the control of the apoptotic pathway and activates Bax, which, in turn, activates the caspase cascade to produce the death of the injured cell. However, events like Mdm2 overexpression or the suppression of caspase-9 gene can block the transmission of the death signal to the caspase cascade allowing the survival of the mutated cell. In this chapter, a mathematical model that explores the effect of Mdm2 overexpression and the suppression of caspase-9 on the control of death by the p53–Mdm2 loop is presented. From the model, two strategies for tumor cell survival are indentified, showing how mutations that affect the death pathway allow the survival of transformed cells. The model suggests that the combination of different simultaneous treatments against these mutations can be a suitable strategy against cancer

Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs

Non-conding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting e.g. the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.Comment: review article, 29 pages, 7 figure

MicroRNAs as a selective channel of communication between competing RNAs: a steady-state theory

It has recently been suggested that the competition for a finite pool of microRNAs (miRNA) gives rise to effective interactions among their common targets (competing endogenous RNAs or ceRNAs) that could prove to be crucial for post-transcriptional regulation (PTR). We have studied a minimal model of PTR where the emergence and the nature of such interactions can be characterized in detail at steady state. Sensitivity analysis shows that binding free energies and repression mechanisms are the key ingredients for the cross-talk between ceRNAs to arise. Interactions emerge in specific ranges of repression values, can be symmetrical (one ceRNA influences another and vice-versa) or asymmetrical (one ceRNA influences another but not the reverse) and may be highly selective, while possibly limited by noise. In addition, we show that non-trivial correlations among ceRNAs can emerge in experimental readouts due to transcriptional fluctuations even in absence of miRNA-mediated cross-talk.Comment: 15 pages, 10 figures, to appear in Biophys

MYC dosage compensation is mediated by miRNA-transcription factor interactions in aneuploid cancer

We hypothesize that dosage compensation of critical genes arises from systems- level properties for cancer cells to withstand the negative effects of aneuploidy. We identified several candidate genes in cancer multiomics data and developed a biocomputational platform to construct a mathematical model of their interac- tion network with micro-RNAs and transcription factors, where the property of dosage compensation emerged for MYC and was dependent on the kinetic pa- rameters of its feedback interactions with three micro-RNAs. These circuits were experimentally validated using a genetic tug-of-war technique to overex- press an exogenous MYC, leading to overexpression of the three microRNAs involved and downregulation of endogenous MYC. In addition, MYC overexpres- sion or inhibition of its compensating miRNAs led to dosage-dependent cytotoxicity in MYC-amplified colon cancer cells. Finally, we identified negative correlation of MYC dosage compensation with patient survival in TCGA breast cancer patients, highlighting the potential of this mechanism to prevent aneu- ploid cancer progression.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Enfermedades Tropicales (CIET)UCR::Vicerrectoría de Investigación::Sistema de Estudios de Posgrado::Salud::Maestría Académica en Bioinformática y Biología de SistemasUCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ciencias de la Computación e InformáticaUCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ingeniería EléctricaUCR::Vicerrectoría de Docenci

Computational design and designability of gene regulatory networks

Nuestro conocimiento de las interacciones moleculares nos ha conducido hoy hacia una perspectiva ingenieril, donde diseños e implementaciones de sistemas artificiales de regulación intentan proporcionar instrucciones fundamentales para la reprogramación celular. Nosotros aquí abordamos el diseño de redes de genes como una forma de profundizar en la comprensión de las regulaciones naturales. También abordamos el problema de la diseñabilidad dada una genoteca de elementos compatibles. Con este fin, aplicamos métodos heuríticos de optimización que implementan rutinas para resolver problemas inversos, así como herramientas de análisis matemático para estudiar la dinámica de la expresión genética. Debido a que la ingeniería de redes de transcripción se ha basado principalmente en el ensamblaje de unos pocos elementos regulatorios usando principios de diseño racional, desarrollamos un marco de diseño computacional para explotar este enfoque. Modelos asociados a genotecas fueron examinados para descubrir el espacio genotípico asociado a un cierto fenotipo. Además, desarrollamos un procedimiento completamente automatizado para diseñar moleculas de ARN no codificante con capacidad regulatoria, basándonos en un modelo fisicoquímico y aprovechando la regulación alostérica. Los circuitos de ARN resultantes implementaban un mecanismo de control post-transcripcional para la expresión de proteínas que podía ser combinado con elementos transcripcionales. También aplicamos los métodos heurísticos para analizar la diseñabilidad de rutas metabólicas. Ciertamente, los métodos de diseño computacional pueden al mismo tiempo aprender de los mecanismos naturales con el fin de explotar sus principios fundamentales. Así, los estudios de estos sistemas nos permiten profundizar en la ingeniería genética. De relevancia, el control integral y las regulaciones incoherentes son estrategias generales que los organismos emplean y que aquí analizamos.Rodrigo Tarrega, G. (2011). Computational design and designability of gene regulatory networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1417

Signaling pathways have an inherent need for noise to acquire information

Background All living systems acquire information about their environment. At the cellular level, they do so through signaling pathways. Such pathways rely on reversible binding interactions between molecules that detect and transmit the presence of an extracellular cue or signal to the cell’s interior. These interactions are inherently stochastic and thus noisy. On the one hand, noise can cause a signaling pathway to produce the same response for different stimuli, which reduces the amount of information a pathway acquires. On the other hand, in processes such as stochastic resonance, noise can improve the detection of weak stimuli and thus the acquisition of information. It is not clear whether the kinetic parameters that determine a pathway’s operation cause noise to reduce or increase the acquisition of information. Results We analyze how the kinetic properties of the reversible binding interactions used by signaling pathways affect the relationship between noise, the response to a signal, and information acquisition. Our results show that, under a wide range of biologically sensible parameter values, a noisy dynamic of reversible binding interactions is necessary to produce distinct responses to different stimuli. As a consequence, noise is indispensable for the acquisition of information in signaling pathways. Conclusions Our observations go beyond previous work by showing that noise plays a positive role in signaling pathways, demonstrating that noise is essential when such pathways acquire information. Results We analyze how the kinetic properties of the reversible binding interactions used by signaling pathways affect the relationship between noise, the response to a signal, and information acquisition. Our results show that, under a wide range of biologically sensible parameter values, a noisy dynamic of reversible binding interactions is necessary to produce distinct responses to different stimuli. As a consequence, noise is indispensable for the acquisition of information in signaling pathways. Conclusions Our observations go beyond previous work by showing that noise plays a positive role in signaling pathways, demonstrating that noise is essential when such pathways acquire information