scholarly journals Maximized redundant and synergistic information transfers predict the rise in the output gene expression noise in a generic class of coherent type-1 feed-forward loop networks

2021 ◽  
Author(s):  
Md Sorique Aziz Momin ◽  
Ayan Biswas
Keyword(s):  
Gene Expression ◽  
Gene Product ◽  
Partial Information ◽  
Feed Forward ◽  
Gene Expression Noise ◽  
Feed Forward Loop ◽  
Output Noise ◽  
Generic Class ◽  
Information Transfers

AbstractWe apply the partial information decomposition principle to a generic coherent type-1 feed-forward loop (C1-FFL) motif with tunable direct and indirect transcriptional regulations of the output gene product and quantify the redundant, synergistic, and unique information transfers from the regulators to their target output species. Our results which are obtained within the small-noise regime of a Gaussian framework reveal that the redundant and synergistic information transfers are antagonistically related to the output noise. Most importantly, these two information flavors are maximized prior to the minimization and subsequent growth of the output noise. Therefore, we hypothesize that the dynamic information redundancy and synergy maxima may possibly be utilized as efficient statistical predictors to forecast the increasing trend of the fluctuations associated with the output gene expression dynamics in the C1-FFL class of network motifs. Our core analytical finding is supported by exact stochastic simulation data and furthermore validated for a diversified repertoire of biologically plausible parameters. Since, the output gene product serves essential physiological purposes in the cell, a predictive estimate of its noise level is supposed to be of considerable biophysical utility.

scholarly journals MUTE Directly Orchestrates Cell State Switch and the Single Symmetric Division to Create Stomata

2018 ◽  
Author(s):  
Soon-Ki Han ◽  
Xingyun Qi ◽  
Kei Sugihara ◽  
Jonathan H. Dang ◽  
Takaho A. Endo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cell Division ◽  
List Type ◽  
Transcriptional Repressors ◽  
Potent Inducer ◽  
Feed Forward ◽  
Feed Forward Loop ◽  
Symmetric Division ◽  
Cell Cycle Genes

SUMMARYPrecise cell division control is critical for developmental patterning. For the differentiation of a functional stoma, a cellular valve for efficient gas exchange, the single symmetric division of an immediate precursor is absolutely essential. Yet, the mechanism governing the single division event remains unclear. Here we report the complete inventories of gene expression by the Arabidopsis bHLH protein MUTE, a potent inducer of stomatal differentiation. MUTE switches the gene expression program initiated by its sister bHLH, SPEECHLESS. MUTE directly induces a suite of cell-cycle genes, including CYCD5;1, and their transcriptional repressors, FAMA and FOUR LIPS. The architecture of the regulatory network initiated by MUTE represents an Incoherent Type 1 Feed-Forward Loop. Our mathematical modeling and experimental perturbations support a notion that MUTE orchestrates a transcriptional cascade leading to the tightly-restricted, robust pulse of cell-cycle gene expression, thereby ensuring the single cell division to create functional stomata.HighlightsComplete inventories of gene expression in stomatal differentiation state are elucidatedMUTE switches stomatal patterning program initiated by its sister bHLH, SPEECHLESSMUTE directly induces cell-cycle genes and their direct transcriptional repressorsIncoherent feed-forward loop by MUTE ensures the single division of a stomatal precursor

scholarly journals The cost of sensitive response and accurate adaptation in networks with an incoherent type-1 feed-forward loop

2013 ◽  
Vol 10 (87) ◽  
pp. 20130489 ◽  
Author(s):  
Ganhui Lan ◽  
Yuhai Tu
Keyword(s):  
Energy Dissipation ◽  
Enzymatic Reaction ◽  
Reaction Network ◽  
Initial Response ◽  
Energy Dissipation Rate ◽  
Feed Forward ◽  
Feed Forward Loop ◽  
Energy Dissipated ◽  
Speed Accuracy

The incoherent type-1 feed-forward loop (I1-FFL) is ubiquitous in biological regulatory circuits. Although much is known about the functions of the I1-FFL motif, the energy cost incurred in the network and how it affects the performance of the network have not been investigated. Here, we study a generic I1-FFL enzymatic reaction network modelled after the GEF–GAP–Ras pathway responsible for chemosensory adaptation in eukaryotic cells. Our analysis shows that the I1-FFL network always operates out of equilibrium. Continuous energy dissipation is necessary to drive an internal phosphorylation–dephosphorylation cycle that is crucial in achieving strong short-time response and accurate long-time adaptation. In particular, we show quantitatively that the energy dissipated in the I1-FFL network is used (i) to increase the system's initial response to the input signals; (ii) to enhance the adaptation accuracy at steady state; and (iii) to expand the range of such accurate adaptation. Moreover, we find that the energy dissipation rate, the catalytic speed and the maximum adaptation accuracy in the I1-FFL network satisfy the same energy–speed–accuracy relationship as in the negative-feedback-loop (NFL) networks. Because the I1-FFL and NFL are the only two basic network motifs that enable accurate adaptation, our results suggest that a universal cost–performance trade-off principle may underlie all cellular adaptation processes independent of the detailed biochemical circuit architecture.

SUMOylation and c-Myc Form Feed-Forward Loop Via miR-34b/c Targeted Gene Expression Program

2017 ◽  
Vol 17 (1) ◽  
pp. e122
Author(s):  
Yuan Chen ◽  
Yi-Jia Li ◽  
Li Du ◽  
Grace Aldana-Masangkay ◽  
Xiuli Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Program ◽  
Feed Forward ◽  
Feed Forward Loop ◽  
Targeted Gene Expression ◽  
Expression Program

scholarly journals A system for gene expression noise control in yeast

2018 ◽  
Author(s):  
Max Mundt ◽  
Alexander Anders ◽  
Seán Murray ◽  
Victor Sourjik
Keyword(s):  
Gene Expression ◽  
Noise Control ◽  
Stochastic Variation ◽  
Gene Expression Noise ◽  
Protein Levels ◽  
Expression Noise ◽  
Degradation Rates ◽  
Output Noise ◽  
Complex Regulatory Network ◽  
Synthesis And Degradation

AbstractGene expression noise arises from stochastic variation in the synthesis and degradation of mRNA and protein molecules and creates differences in protein numbers across populations of genetically identical cells. Such variability can lead to imprecision and reduced performance of both native and synthetic networks. In principle, gene expression noise can be controlled through the rates of transcription, translation and degradation, such that different combinations of those rates lead to the same protein concentrations but at different noise levels. Here, we present a “noise tuner” which allows orthogonal control over the transcription and the mRNA degradation rates by two different inducer molecules. Combining experiments with theoretical analysis, we show that in this system the noise is largely determined by the transcription rate whereas mean expression can be independently adjusted by mRNA stability. This noise tuner enables twofold changes in gene expression noise over a fivefold range of mean protein levels. We demonstrated the efficacy of the noise tuner in a complex regulatory network by varying gene expression noise in the mating pathway of Saccharomyces cerevisiae, which allowed us to control the output noise and the mutual information transduced through the pathway. The noise tuner thus represents an effective tool of gene expression noise control, both to interrogate noise sensitivity of natural networks and enhance performance of synthetic circuits.

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