How receptor diffusion influences gradient sensing

Nguyen, Huyen; Dayan, Peter; Goodhill, Geoffrey J.

doi:10.1098/rsif.2014.1097

Cited by 11 publications

(6 citation statements)

References 35 publications

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“…The first concept is that receptors along the surface of the membrane change position. This is important since the spatial distribution of receptors can influence the movement that a neuron has in response to the extracellular ligands (Nguyen et al 2014(Nguyen et al , 2015. We hypothesize that the spatial distribution of UNC-40 can influence the manner though which force is applied to the membrane and thereby affect the outward movement of the membrane.…”

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confidence: 99%

A Statistically-Oriented Asymmetric Localization (SOAL) Model for Neuronal Outgrowth Patterning by Caenorhabditis elegans UNC-5 (UNC5) and UNC-40 (DCC) Netrin Receptors

et al. 2018

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Neurons extend processes that vary in number, length, and direction of "outgrowth". Extracellular cues help determine outgrowth patterns. In , neurons respond to the extracellular UNC-6 (netrin) cue via UNC-40 (DCC) and UNC-5 (UNC5) receptors. Previously, we presented evidence that UNC-40 asymmetric localization at the plasma membrane is self-organizing, and that UNC-40 can localize and mediate outgrowth at randomly selected sites. Here, we provide further evidence for a statistically-oriented asymmetric localization (SOAL) model in which UNC-5 receptor activity affects patterns of axon outgrowth by regulating UNC-40 asymmetric localization. According to the SOAL model, the direction of outgrowth activity fluctuates across the membrane over time. Random walk modeling predicts that increasing the degree to which the direction of outgrowth fluctuates will decrease the outward displacement of the membrane. By differentially affecting the degree to which the direction of outgrowth activity fluctuates over time, extracellular cues can produce different rates of outgrowth along the surface and create patterns of "extension". Consistent with the SOAL model, we show that mutations alter UNC-40 asymmetric localization, increase the degree to which the direction of outgrowth fluctuates, and reduce the extent of outgrowth in multiple directions relative to the source of UNC-6 These results are inconsistent with current models, which predict that UNC-5 mediates a "repulsive" response to UNC-6 Genetic interactions suggest that UNC-5 acts through the UNC-53 (NAV2) cytoplasmic protein to regulate UNC-40 asymmetric localization in response to both the UNC-6 and EGL-20 (Wnt) extracellular cues.

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confidence: 99%

A Statistically-Oriented Asymmetric Localization (SOAL) Model for Neuronal Outgrowth Patterning by Caenorhabditis elegans UNC-5 (UNC5) and UNC-40 (DCC) Netrin Receptors

et al. 2018

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“…An incomplete set of examples include cooperative sensing by multiple ligand-receptor sensors [8,9], multiple ligand sensing by single sensor [10,11], ligand-receptor networks [12][13][14], etc. Additionally, Markovian signal detection [15], effect of receptor diffusion [16], etc have also been considered in the study of ligand-receptor accuracy.…”

Section: Introductionmentioning

confidence: 99%

Multiplexing and its upper bound in biological sensory receptors

Asawari¹,

Min²,

Lu³

2022

Preprint

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Biological sensory receptors provide perfect examples of microscopic scale information transduction in the presence of non-negligible thermal fluctuations. For example, studies of ligand-receptor reveal that accurate concentration sensing is achieved by integrating out noise in the sensor's stochastic trajectories. However, we argue that the stochastic trajectory is not always an adversary -it could allow a single sensor to perform multiplexing (or muxing) by simultaneously transducing multiple environmental variables (e.g., concentration, temperature, and flow speed) to the downstream sensory network. This work develops a general theory of stochastic sensory muxing and a theoretical upper bound of muxing. The theory is demonstrated and verified by an exactly solvable Markov dynamics model, where an arbitrary sensor can achieve the upper bound of muxing without optimizing parameters. The theory is further demonstrated by a realistic Langevin dynamics simulation of a ligand receptor within a bath of ligands. Simulations verify that even a binary state ligand receptor with short-term memory can simultaneously sense two out of three independent environmental variables -ligand concentration, temperature, and media's flow speed. Both models demonstrate that the upper bound for muxing is tight. This theory provides insights on designing novel microscopic sensors that are capable of muxing in realistic and complex environments.

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“…First, successive measurements need to be made with a sufficient time interval in between to ensure that the measurements are statistically independent from each other, thus enabling the concentration of molecules to be obtained accurately through averaging [9], [10]. Second, bionanomachine receptors that measure the concentration of molecules in the environment behave stochastically; they bind to and unbind from molecules probabilistically [11], they perform random walks over the surface of or within a bio-nanomachine [12], and they are internalized and recycled upon binding to molecules [13]. Due to these receptor behaviors, it may not be possible for bio-nanomachines to measure the concentration of molecules continuously.…”

Section: Introductionmentioning

confidence: 99%

Mobile Molecular Communication Through Multiple Measurements of the Concentration of Molecules

Okaie

Nakano

2020

IEEE Access

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Multiple measurements of the concentration of molecules serve as a useful technique to enable bio-nanomachines to reliably extract information encoded in the concentration of molecules. In this paper, we develop mathematical models to examine the impact of multiple measurements of the concentration of molecules on the performance of mobile molecular communication taking into account the constrains associated with the systems. In this scenario, a mobile transmitter bio-nanomachine releases a pre-defined number of molecules and a mobile receiver bio-nanomachine receives information by measuring the concentration of these molecules on multiple occasions. Numerical results obtained using the models show that multiple measurements of the concentration of molecules serve as an effective means to improve mobile molecular communication performance. INDEX TERMS Molecular communication, multiple measurements, demodulation, mobile molecular communication, bio-nanomachine VOLUME 4, 2016 This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.

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How receptor diffusion influences gradient sensing

Cited by 11 publications

References 35 publications

A Statistically-Oriented Asymmetric Localization (SOAL) Model for Neuronal Outgrowth Patterning by Caenorhabditis elegans UNC-5 (UNC5) and UNC-40 (DCC) Netrin Receptors

A Statistically-Oriented Asymmetric Localization (SOAL) Model for Neuronal Outgrowth Patterning by Caenorhabditis elegans UNC-5 (UNC5) and UNC-40 (DCC) Netrin Receptors

Multiplexing and its upper bound in biological sensory receptors

Mobile Molecular Communication Through Multiple Measurements of the Concentration of Molecules

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