scholarly journals Extrinsic Noise Suppression in Micro RNA mediated Incoherent Feedforward Loops

2018 ◽  
Author(s):  
Alberto Carignano ◽  
Sumit Mukherjee ◽  
Abhyudai Singh ◽  
Georg Seelig
Keyword(s):  
Mammalian Cells ◽  
Micro Rna ◽  
Network Motifs ◽  
Extrinsic Noise ◽  
Feed Forward ◽  
Feed Forward Loop ◽  
Noise Rejection ◽  
Feed Forward Network ◽  
Translational Inhibition ◽  
Special Case

AbstractMicroRNA mediated incoherent feed forward loops (IFFLs) are recurrent network motifs in mammalian cells and have been a topic of study for their noise rejection and buffering properties. Previous work showed that IFFLs can adapt to varying promoter activity and are less prone to noise than similar circuits without the feed forward loop. Furthermore, it has been shown that microRNAs are better at rejecting extrinsic noise than intrinsic noise. This work studies the biological mechanisms that lead to extrinsic noise rejection for microRNA mediated feed forward network motifs. Specifically, we compare the effects of microRNA-induced mRNA degradation and translational inhibition on extrinsic noise rejection, and identify the parameter regimes where noise is most efficiently rejected. In the case of static extrinsic noise, we find that translational inhibition can expand the regime of extrinsic noise rejection. We then analyze rejection of dynamic extrinsic noise in the case of a single-gene feed forward loop (sgFFL), a special case of the IFFL motif where the microRNA and target mRNA are co-expressed. For this special case, we demonstrate that depending on the time-scale of fluctuations in the extrinsic variable compared to the mRNA and microRNA decay rates, the feed forward loop can both buffer or amplify fluctuations in gene product copy numbers.

scholarly journals Organisation of feed-forward loop motifs reveals architectural principles in natural and engineered networks

2017 ◽  
Author(s):  
Thomas E. Gorochowski ◽  
Claire S. Grierson ◽  
Mario di Bernardo
Keyword(s):  
Escherichia Coli ◽  
Functional Analysis ◽  
Broad Spectrum ◽  
Building Blocks ◽  
Networked Systems ◽  
Network Motifs ◽  
Feed Forward ◽  
Feed Forward Loop ◽  
Architectural Principles ◽  
Important Nodes

AbstractNetwork motifs are significantly expressed sub-graphs that have been proposed as building blocks for natural and engineered networks. Detailed functional analysis has been performed for many types of motif in isolation, but less is known about how motifs work together to perform complex tasks. To address this issue we measure the aggregation of network motifs via methods that extract precisely how these structures are connected. Applying this approach to a broad spectrum of networked systems and focusing on the widespread feed-forward loop motif, we uncover striking differences in motif organisation. The types of connection are often highly constrained, differ between domains, and clearly capture architectural principles. We show how this information can be used to effectively predict functionally important nodes in the metabolic network ofEscherichia coli. Our findings have implications for understanding how networked systems are constructed from motif parts and elucidates constraints that guide their evolution.

scholarly journals Large deviations for a feed-forward network

2011 ◽  
Vol 43 (02) ◽  
pp. 545-571 ◽  
Author(s):  
Leila Setayeshgar ◽  
Hui Wang
Keyword(s):  
Large Deviation ◽  
Sample Path ◽  
Service Discipline ◽  
Single Server ◽  
Feed Forward ◽  
Exponential Decay Rate ◽  
Feed Forward Network ◽  
Multiple Levels ◽  
Overflow Probabilities ◽  
Special Case

We consider a feed-forward network with a single-server station serving jobs with multiple levels of priority. The service discipline is preemptive in that the server always serves a job with the current highest level of priority. For this system with discontinuous dynamics, we establish the sample path large deviation principle using a weak convergence argument. In the special case where jobs have two different levels of priority, we also explicitly identify the exponential decay rate of the total population overflow probabilities by examining the geometry of the zero-level sets of the system Hamiltonians.

scholarly journals Vibrational resonance in feed-forward-loop neuronal network motifs

2015 ◽  
Vol 16 (S1) ◽  
Author(s):  
Ali Calim ◽  
Ugur Ileri ◽  
Muhammet Uzuntarla ◽  
Mahmut Ozer
Keyword(s):  
Neuronal Network ◽  
Network Motifs ◽  
Vibrational Resonance ◽  
Feed Forward ◽  
Feed Forward Loop

scholarly journals On Information Extraction and Decoding Mechanisms Improved by Noisy Amplification in Signaling Pathways

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Aaron Vazquez-Jimenez ◽  
Jesus Rodriguez-Gonzalez
Keyword(s):  
Information Transmission ◽  
Signaling Pathways ◽  
Channel Capacity ◽  
Cellular Response ◽  
Detailed Comparison ◽  
Erk Pathway ◽  
Extrinsic Noise ◽  
Positive Dependence ◽  
Feed Forward ◽  
Feed Forward Loop

Abstract The cells need to process information about extracellular stimuli. They encode, transmit and decode the information to elicit an appropriate response. Studies aimed at understanding how such information is decoded in the signaling pathways to generate a specific cellular response have become essential. Eukaryotic cells decode information through two different mechanisms: the feed-forward loop and the promoter affinity. Here, we investigate how these two mechanisms improve information transmission. A detailed comparison is made between the stochastic model of the MAPK/ERK pathway and a stochastic minimal decoding model. The maximal amount of transmittable information was computed. The results suggest that the decoding mechanism of the MAPK/ERK pathway improve the channel capacity because it behaves as a noisy amplifier. We show a positive dependence between the noisy amplification and the amount of information extracted. Additionally, we show that the extrinsic noise can be tuned to improve information transmission. This investigation has revealed that the feed-forward loop and the promoter affinity motifs extract information thanks to processes of amplification and noise addition. Moreover, the channel capacity is enhanced when both decoding mechanisms are coupled. Altogether, these findings suggest novel characteristics in how decoding mechanisms improve information transmission.

scholarly journals Large deviations for a feed-forward network

2011 ◽  
Vol 43 (2) ◽  
pp. 545-571 ◽  
Author(s):  
Leila Setayeshgar ◽  
Hui Wang
Keyword(s):  
Large Deviation ◽  
Sample Path ◽  
Service Discipline ◽  
Single Server ◽  
Feed Forward ◽  
Exponential Decay Rate ◽  
Feed Forward Network ◽  
Multiple Levels ◽  
Overflow Probabilities ◽  
Special Case

We consider a feed-forward network with a single-server station serving jobs with multiple levels of priority. The service discipline is preemptive in that the server always serves a job with the current highest level of priority. For this system with discontinuous dynamics, we establish the sample path large deviation principle using a weak convergence argument. In the special case where jobs have two different levels of priority, we also explicitly identify the exponential decay rate of the total population overflow probabilities by examining the geometry of the zero-level sets of the system Hamiltonians.

scholarly journals Cell-Free Characterization of Coherent Feed-Forward Loop-Based Synthetic Genetic Circuits

2021 ◽  
Author(s):  
Pascal A. Pieters ◽  
Bryan L. Nathalia ◽  
Ardjan J. van der Linden ◽  
Peng Yin ◽  
Jongmin Kim ◽  
...  
Keyword(s):  
Genetic Circuits ◽  
Feed Forward ◽  
Feed Forward Loop
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