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MicroRNA as a potential vector for the propagation of robustness in protein expression and oscillatory dynamics within a ceRNA network.

ABSTRACT: microRNAs (miRNAs) are small noncoding RNAs that are important post-transcriptional regulators of gene expression. miRNAs can induce thresholds in protein synthesis. Such thresholds in protein output can be also achieved by oligomerization of transcription factors (TF) for the control of gene expression. First, we propose a minimal model for protein expression regulated by miRNA and by oligomerization of TF. We show that miRNA and oligomerization of TF generate a buffer, which increases the robustness of protein output towards molecular noise as well as towards random variation of kinetics parameters. Next, we extend the model by considering that the same miRNA can bind to multiple messenger RNAs, which accounts for the dynamics of a minimal competing endogenous RNAs (ceRNAs) network. The model shows that, through common miRNA regulation, TF can control the expression of all proteins formed by the ceRNA network, even if it drives the expression of only one gene in the network. The model further suggests that the threshold in protein synthesis mediated by the oligomerization of TF can be propagated to the other genes, which can increase the robustness of the expression of all genes in such ceRNA network. Furthermore, we show that a miRNA could increase the time delay of a "Goodwin-like" oscillator model, which may favor the occurrence of oscillations of large amplitude. This result predicts important roles of miRNAs in the control of the molecular mechanisms leading to the emergence of biological rhythms. Moreover, a model for the latter oscillator embedded in a ceRNA network indicates that the oscillatory behavior can be propagated, via the shared miRNA, to all proteins formed by such ceRNA network. Thus, by means of computational models, we show that miRNAs could act as vectors allowing the propagation of robustness in protein synthesis as well as oscillatory behaviors within ceRNA networks.

SUBMITTER: Gerard C

PROVIDER: S-EPMC3871652 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The nonsinusoidal waveform is emerging as an important feature of neuronal oscillations. However, the role of single-cycle shape dynamics in rapidly unfolding brain activity remains unclear. Here, we develop an analytical framework that isolates oscillatory signals from time series using masked empirical mode decomposition to quantify dynamical changes in the shape of individual cycles (along with amplitude, frequency, and phase) with instantaneous frequency. We show how phase-alignment, a process of projecting cycles into a regularly sampled phase grid space, makes it possible to compare cycles of different durations and shapes. "Normalized shapes" can then be constructed with high temporal detail while accounting for differences in both duration and amplitude. We find that the instantaneous frequency tracks nonsinusoidal shapes in both simulated and real data. Notably, in local field potential recordings of mouse hippocampal CA1, we find that theta oscillations have a stereotyped slow-descending slope in the cycle-wise average yet exhibit high variability on a cycle-by-cycle basis. We show how principal component analysis allows identification of motifs of theta cycle waveform that have distinct associations to cycle amplitude, cycle duration, and animal movement speed. By allowing investigation into oscillation shape at high temporal resolution, this analytical framework will open new lines of inquiry into how neuronal oscillations support moment-by-moment information processing and integration in brain networks.NEW & NOTEWORTHY We propose a novel analysis approach quantifying nonsinusoidal waveform shape. The approach isolates oscillations with empirical mode decomposition before waveform shape is quantified using phase-aligned instantaneous frequency. This characterizes the full shape profile of individual cycles while accounting for between-cycle differences in duration, amplitude, and timing. We validated in simulations before applying to identify a range of data-driven nonsinusoidal shape motifs in hippocampal theta oscillations.

Project description:BackgroundPreeclampsia (PE), one of hypertension-related disorders of pregnancy, is a common cause of maternal death worldwide. This study aimed to identify a circRNA-miRNA-mRNA-associated ceRNA network and related pathways in PE.Material and methodsWe downloaded 3 microarray datasets from the Gene Expression Omnibus database, obtained 163 differentially expressed circRNAs (dif-circRNAs) (61 upregulated and 102 downregulated), 39 differentially expressed microRNAs (dif-miRNAs) (22 upregulated and 17 downregulated), and 271 differentially expressed mRNAs (dif-mRNAs) (168 upregulated and 103 downregulated) from placenta tissues of PE. Functional enrichment analysis and protein-protein interaction (PPI) network with module analysis of dif-mRNAs were performed. The regulatory relationship between dif-miRNAs and dif-mRNAs/circRNAs was predicted via related databases. A circRNA-miRNA-mRNA regulatory network was constructed.ResultsA total of 53 pairs were obtained, including 13 circRNAs (10 upregulated and 3 downregulated), 9 miRNAs (3 upregulated and 6 downregulated) and 31 mRNAs (22 upregulated and 9 downregulated). GNB5 and IL2RB were obtained. KEGG enrichment analysis showed that both of them were closely related with the PI3K-Akt signalling pathway. Therefore, ceRNAs might affect the PI3K-Akt signalling pathway via the upregulation of GNB5 by binding to miR-1248 in PE. Meanwhile, hsa_circ_0052661 might upregulate IL2RB by binding miR-4303 to play a role in PE in the same way.ConclusionGNB5 and IL2RB might be key genes involved in the PI3K-Akt signalling pathway in PE, and hsa_circ_0087208, hsa_circ_0035443, hsa_circ_0067557 and hsa_circ_0052661 might regulate these key genes in PE by binding miR-1248 or miR-4303.Key messagesThere is still a lack of predictive and diagnostic factors for preeclampsia, which is a common cause of maternal death worldwide.This study identified a novel circRNA-associated ceRNA network and related pathways in preeclampsia.GNB5 and IL2RB might be key genes in their related circRNA-associated ceRNA network, and probably take an important role in preeclampsia via PI3K-Akt signalling pathway, which made them to be potential markers of preeclampsia.

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MicroRNA as a potential vector for the propagation of robustness in protein expression and oscillatory dynamics within a ceRNA network.

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