The influence of receptor positioning on chemotactic information

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

doi:10.1016/j.jtbi.2014.06.022

Cited by 9 publications

(5 citation statements)

References 20 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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“…Although DFRO was originally posed as a difference in receptor occupancy between extreme points on a cell (Wang et al, 2004), this is an oversimplified interpretation, as cells transduce signals from receptors all over their surfaces, not just extremes. Moreover, the orientation of a cell and the distribution of its receptors affect how reliably the cell perceives the gradient (Nguyen et al, 2014). For these reasons, rather than conceptually representing cell response in terms of FRO at extreme points on a cell, we use DFRO because it is an effective way to account for chemoattractant concentration and gradient slopes in interpreting experimental data.…”

Section: Methodsmentioning

confidence: 99%

Determining whether observed eukaryotic cell migration indicates chemotactic responsiveness or random chemokinetic motion

Szatmary

Nossal

2017

Journal of Theoretical Biology

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Chemotaxis, the motion of cells directed by a gradient of chemoattractant molecules, guides cells in immune response, development, wound healing, and cancer. Unfortunately, this process is difficult to distinguish from chemokinesis, i.e., stimulated random cell motion. Chemotaxis is frequently inferred by determining how many cells cross a boundary in a chemotaxis assay, for example how many cells crawl into a chemoattractant-infused filter, or how many cells enter a defined region in an under-agarose assay or agarose spot assay. To mitigate possible ambiguity in whether motion observed in these assays is directed by the chemoattractant gradient or by chemokinesis, we developed a mathematical model to determine when such methods indeed indicate directed motion of cells. In contrast to previous analyses of chemotaxis assays, we report not just the gradients that arise in the assays but also resulting cell motion. We applied the model to data obtained from rigorous measurements and show, as examples, that MDA-MB-231 breast-cancer cells are at least 20 times less sensitive to gradients of EGF or CXCL12 than neutrophils are to formyl peptides; we then used this information to determine the extent to which gradient sensing increases the rate of boundary crossing relative to a random-motility control. Results show, for example, that in the filter assay, 2–4 times as many neutrophils pass through the filter when exposed to a gradient as when the gradient is absent. However, in the other combinations of cells and assays we considered, only 10–20% more cells are counted as having migrated in a directed, rather than random, motility condition. We also discuss the design of appropriate controls for these assays, which is difficult for the under-agarose and agarose spot assays. Moreover, although straightforward to perform with the filter assay, reliable controls are often not done. Consequently, we infer that chemotaxis is frequently over-reported, especially for cells like MDA-MB-231 cells, which move slowly and are relatively insensitive to gradients. Such results provide insights into the use of chemotaxis assays, particularly if one wants to acquire and analyze quantitative data.

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“…(2009) but using information-theoretic arguments, Nguyen et al. (2015) investigated how concentration (and thus gradient) measurements are degraded by receptor diffusion, and Nguyen et al. (2014) determined the theoretically optimal spatial distribution of receptors to avoid bias in estimating gradient direction, which turned out to be non-uniform.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Models of Neural Development

Goodhill

2018

iScience

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Constructing a functioning nervous system requires the precise orchestration of a vast array of mechanical, molecular, and neural-activity-dependent cues. Theoretical models can play a vital role in helping to frame quantitative issues, reveal mathematical commonalities between apparently diverse systems, identify what is and what is not possible in principle, and test the abilities of specific mechanisms to explain the data. This review focuses on the progress that has been made over the last decade in our theoretical understanding of neural development.

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The influence of receptor positioning on chemotactic information

Cited by 9 publications

References 20 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

Determining whether observed eukaryotic cell migration indicates chemotactic responsiveness or random chemokinetic motion

Theoretical Models of Neural Development

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