Role of Relaxation Time Scale in Noisy Signal Transduction

Maity, Alok Kumar; Chaudhury, Pinaki; Banik, Suman Kumar

doi:10.1371/journal.pone.0123242

Cited by 14 publications

(29 citation statements)

References 81 publications

(235 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…that of protein population, leading to a greater extrinsic noise generated at the signaling level. Hence one can say that protein species cannot sense the rapid population fluctuations of the signal [11].…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Information processing in a simple one-step cascade

et al. 2018

Self Cite

View full text Add to dashboard Cite

Using the formalism of information theory, we analyze the mechanism of information transduction in a simple one-step signaling cascade S→X representing the gene regulatory network.Approximating the signaling channel to be Gaussian, we describe the dynamics using Langevin equations. Upon discretization, we calculate the associated second moments for linear and nonlinear regulation of the output by the input, which follows the birth-death process. While mutual information between the input and the output characterizes the channel capacity, the Fano factor of the output gives a clear idea of how internal and external fluctuations assemble at the output level. To quantify the contribution of the present state of the input to predict the future output, transfer entropy is computed. We find that higher amount of transfer entropy is accompanied by the greater magnitude of external fluctuations (quantified by the Fano factor of the output) propagation from the input to the output. We notice that low input population characterized by the number of signaling molecules S, which fluctuates in a relatively slower fashion compared to its downstream (target) species X, is maximally able to predict (as quantified by transfer entropy) the future state of the output. Our computations also reveal that with increased linear nature of the input-output interaction, all three metrics of mutual information, Fano factor and, transfer entropy achieve relatively larger magnitudes. *

show abstract

Section: Resultsmentioning

confidence: 99%

“…We now write the explicit forms of the functions f s (s) and f x (s, x) keeping in mind the nature of the biochemical interaction. For linear interaction, we have [11]…”

Section: A Analytical Calculationsmentioning

confidence: 99%

Information processing in a simple one-step cascade

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…information and hinder otherwise 34,[57][58][59] . Now, we re-express the preceding statement as a guiding principle to analyze information flow in the motif under investigation.…”

Section: B Common Source Of Input Fluctuations Generates Effective Rmentioning

confidence: 99%

Interplay of synergy and redundancy in diamond motif

Biswas

Banik

2018

Chaos: An Interdisciplinary Journal of Nonlinear Science

Self Cite

View full text Add to dashboard Cite

The formalism of partial information decomposition provides a number of independent components which altogether constitute the total information provided by the source variable(s) about the target variable(s). These non-overlapping terms are recognized as unique information, synergistic information and, redundant information. The metric of net synergy conceived as the difference between synergistic and redundant information, is capable of detecting effective synergy, effective redundancy and, information independence among stochastic variables. The net synergy can be quantified using appropriate combinations of different Shannon mutual information terms. The utilization of the net synergy in network motifs with the nodes representing different biochemical species, involved in information sharing, uncovers rich store for exciting results. In the current study, we use this formalism to obtain a comprehensive understanding of the relative information processing mechanism in a diamond motif and two of its sub-motifs namely bifurcation and integration motif embedded within the diamond motif. The emerging patterns of effective synergy and effective redundancy and their contribution towards ensuring high fidelity information transmission are duly compared in the submotifs. Investigation on the metric of net synergy in independent bifurcation and integration motifs are also executed. In all of these computations, the crucial roles played by various systemic time scales, activation coefficients and signal integration mechanisms at the output of the network topologies are especially emphasized. Following this plan of action, we become confident that the origin of effective synergy and effective redundancy can be architecturally justified by decomposing a diamond motif into bifurcation and integration motif. According to our conjecture, the presence of common source of fluctuations creates effective redundancy. Our calculations reveal effective redundancy empowers signal fidelity. Moreover, to achieve this, input signaling species avoids strong interaction with downstream intermediates. This strategy is capable of making the diamond motif noise-tolerant. Apart from the topological features, our study also puts forward the active contribution of additive and multiplicative signal integration mechanisms to nurture effective redundancy and effective synergy.

show abstract

“…An input signal can reliably flow downstream if relaxation rate (or degradation rate) of a cascade protein is higher than that of its upstream cascade proteins [35]. For red line, we consider higher degradation rate for x p2 and x p3 (y p2 and y p3 ) compared to x p1 (y p1 ).…”

Section: Two Variable Mutual Informationmentioning

confidence: 99%

“…The fluctuations associated with at least one of the species participating in each of the second-order reaction are Poissonian and uncorrelated with the fluctuations of other species. Also, LNA remains valid for faster activation and deactivation (or synthesis and degradation) rates of the corresponding components compared to the coarse-grained (steady state) time scale [30][31][32][33][34][35][36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Information Theoretical Study of Cross-Talk Mediated Signal Transduction in MAPK Pathways

Maity

Chaudhury

Banik

2017

Entropy

Self Cite

View full text Add to dashboard Cite

Abstract:Biochemical networks having similar functional pathways are often correlated due to cross-talk among the homologous proteins in the different networks. Using a stochastic framework, we address the functional significance of the cross-talk between two pathways. A theoretical analysis on generic MAPK pathways reveals cross-talk is responsible for developing coordinated fluctuations between the pathways. The extent of correlation evaluated in terms of the information theoretic measure provides directionality to net information propagation. Stochastic time series suggest that the cross-talk generates synchronisation in a cell. In addition, the cross-interaction develops correlation between two different phosphorylated kinases expressed in each of the cells in a population of genetically identical cells. Depending on the number of inputs and outputs, we identify signal integration and signal bifurcation motif that arise due to inter-pathway connectivity in the composite network. Analysis using partial information decomposition, an extended formalism of multivariate information calculation, also quantifies the net synergy in the information propagation through the branched pathways. Under this formalism, signature of synergy or redundancy is observed due to the architectural difference in the branched pathways.

show abstract

Role of Relaxation Time Scale in Noisy Signal Transduction

Cited by 14 publications

References 81 publications

Information processing in a simple one-step cascade

Information processing in a simple one-step cascade

Interplay of synergy and redundancy in diamond motif

Information Theoretical Study of Cross-Talk Mediated Signal Transduction in MAPK Pathways

Contact Info

Product

Resources

About