Signal Destruction Tunes the Zone of Activation in Spatially Distributed Signaling Networks

Silva, Kalinga Pavan; Chellamuthu, Prithiviraj; Boedicker, James

doi:10.1016/j.bpj.2017.01.010

Cited by 16 publications

(30 citation statements)

References 57 publications

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“…Senders increase the expression of the GFP reporter gene in response to an increase in the concentration of a diffusible signaling molecule, here acyl-homoserine lactones (AHL). The response function of GFP production is non-linear, exhibiting a sharp increase in cellular fluorescence when the amount of signal exceeds a threshold concentration [26,32]. Degrader cells are a strain of E. coli constitutively expressing the lactonase enzyme AiiA [27].…”

Section: A Experimental Setupmentioning

confidence: 99%

“…Degrader cells are a strain of E. coli constitutively expressing the lactonase enzyme AiiA [27]. AiiA remains inside the degrader cells and degrades AHL quorum sensing signals that diffuse into the cell, including the 3-oxo-C6-HSL produced by the sender cells [26,33].…”

Section: A Experimental Setupmentioning

confidence: 99%

“…We developed a model that captured the dynamics of signal exchange and cell growth. The growth of the cells is modeled with a logistic growth equation [9,26],…”

Section: A Reaction-diffusion Modelmentioning

confidence: 99%

“…Quorum sensing (QS) regulates several collective, group-level behaviors, including pathogenesis [21,22], biofilm formation [23], antibiotic production [1,24,25], and bioluminescence [20]. Empirical evidence suggests that these behaviors can span large distances [9,20,26] .…”

Section: Introductionmentioning

confidence: 99%

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Disruption of microbial communication yields a two-dimensional percolation transition

et al. 2019

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Bacteria communicate with each other to coordinate macro-scale behaviors including pathogenesis, biofilm formation and antibiotic production. Empirical evidence suggests that bacteria are capable of communicating at length scales far exceeding the size of individual cells. Several mechanisms of signal interference have been observed in nature, and how interference influences macro-scale activity within microbial populations is unclear. Here we examined the exchange of quorum sensing signals to coordinate microbial activity over long distances in the presence of a variable amount of interference through a neighboring signal-degrading strain. As the level of interference increased, communication over large distances was disrupted and at a critical amount of interference, large-scale communication was suppressed. We explored this transition in experiments and reaction-diffusion models, and confirmed that this transition is a 2D percolation transition. These results demonstrate the utility of applying physical models to emergence in complex biological networks to probe robustness and universal quantitative features.

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Section: A Experimental Setupmentioning

confidence: 99%

Section: A Experimental Setupmentioning

confidence: 99%

“…We developed a model that captured the dynamics of signal exchange and cell growth. The growth of the cells is modeled with a logistic growth equation [9,26],…”

Section: A Reaction-diffusion Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Disruption of microbial communication yields a two-dimensional percolation transition

et al. 2019

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“…We also extend the formalism to solve signal transduction in a cascade, which serves as a model for a variety of biological networks. The formalism is general and is applicable to arbitrary networks with feedback, time delay and special variations [26]. Our work exploits standard methods in physics, illustrating the usefulness of a field theoretic formulation at the interface of communication theory and biology.…”

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confidence: 99%

Optimal information transfer in enzymatic networks: A field theoretic formulation

2017

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Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach in order to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus (Phys. Rev. X., 4, 041017 (2014)). We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudo intermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudo intermediate. Surprisingly, in these examples the minimum error computed using simulations that take non-linearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters.Inclusion of second order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in networks of arbitrary complexity.

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Spiral Wave Propagation in Communities with Spatially Correlated Heterogeneity

Zhai

Larkin

Süel

et al. 2020

Biophysical Journal

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Many multicellular communities propagate signals in a directed manner via excitable waves. Cellto-cell heterogeneity is a ubiquitous feature of multicellular communities, but the effects of heterogeneity on wave propagation are still unclear. Here we use a minimal FitHugh-Nagumo-type model to investigate excitable wave propagation in a two-dimensional heterogeneous community. The model shows three dynamic regimes in which waves either propagate directionally, die out, or spiral indefinitely, and we characterize how these regimes depend on the heterogeneity parameters. We find that in some parameter regimes, spatial correlations in the heterogeneity enhance directional propagation and suppress spiraling. However, in other regimes, spatial correlations promote spiraling, a surprising feature that we explain by demonstrating that these spirals form by a second, distinct mechanism. Finally, we characterize the dependence of the spiral period on the degree of heterogeneity in the system by using techniques from percolation theory. Our results reveal that the spatial structure of cell-to-cell heterogeneity can have important consequences for signal propagation in cellular communities.

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Signal Destruction Tunes the Zone of Activation in Spatially Distributed Signaling Networks

Cited by 16 publications

References 57 publications

Disruption of microbial communication yields a two-dimensional percolation transition

Disruption of microbial communication yields a two-dimensional percolation transition

Optimal information transfer in enzymatic networks: A field theoretic formulation

Spiral Wave Propagation in Communities with Spatially Correlated Heterogeneity

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