scholarly journals A cell–cell repulsion model on a hyperbolic Keller–Segel equation

2020 ◽  
Vol 80 (7) ◽  
pp. 2257-2300
Author(s):  
Xiaoming Fu ◽  
Quentin Griette ◽  
Pierre Magal
Keyword(s):  
A Cell ◽  
eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Nathan T Henderson ◽  
Sylvain J Le Marchand ◽  
Martin Hruska ◽  
Simon Hippenmeyer ◽  
Liqun Luo ◽  
...  

Cortical networks are characterized by sparse connectivity, with synapses found at only a subset of axo-dendritic contacts. Yet within these networks, neurons can exhibit high connection probabilities, suggesting that cell-intrinsic factors, not proximity, determine connectivity. Here, we identify ephrin-B3 (eB3) as a factor that determines synapse density by mediating a cell-cell competition that requires ephrin-B-EphB signaling. In a microisland culture system designed to isolate cell-cell competition, we find that eB3 determines winning and losing neurons in a contest for synapses. In a Mosaic Analysis with Double Markers (MADM) genetic mouse model system in vivo the relative levels of eB3 control spine density in layer 5 and 6 neurons. MADM cortical neurons in vitro reveal that eB3 controls synapse density independently of action potential-driven activity. Our findings illustrate a new class of competitive mechanism mediated by trans-synaptic organizing proteins which control the number of synapses neurons receive relative to neighboring neurons.


2019 ◽  
Author(s):  
Eleanor M Denham ◽  
Michael I Barton ◽  
Susannah M Black ◽  
Marcus J Bridge ◽  
Ben de Wet ◽  
...  

AbstractDose-response experiments are a mainstay of receptor biology studies and can reveal valuable insights into receptor function. Such studies of receptors that bind cell surface ligands are currently limited by the difficulty in manipulating the surface density of ligands at a cell-cell interface. Here we describe a generic cell surface ligand system that allows precise manipulation of cell surface ligand densities over several orders of magnitude. We validate the system for a range of immunoreceptors, including the T cell receptor (TCR), and show that this generic ligand stimulates via the TCR at a similar surface density as its native ligand. This system allows the effect of surface density, valency, dimensions, and affinity of the ligand to be manipulated. It can be readily extended to other receptor-cell surface ligand interactions, and will facilitate investigation into the activation of, and signal integration between, cell surface receptors.


1998 ◽  
Vol 111 (17) ◽  
pp. 2635-2644 ◽  
Author(s):  
B. Blumbach ◽  
Z. Pancer ◽  
B. Diehl-Seifert ◽  
R. Steffen ◽  
J. Munkner ◽  
...  

Porifera (sponges) are the oldest extant metazoan phylum. Dissociated sponge cells serve as a classic system to study processes of cell reaggregation. The reaggregation of dissociated cells is mediated by an extracellularly localized aggregation factor (AF), based on heterophilic interactions of the third order; the AF bridges two cells by ligating a cell-surface-bound aggregation receptor (AR). In the present study we report cloning, expression and immunohistochemical localization of a polypeptide from the marine sponge Geodia cydonium, which very likely represents the AR. The presumed AR gene gives rise to at least three forms of alternatively spliced transcripts of 6.5, 4.9 and 3.9 kb, as detected by northern blotting. Two cDNA clones corresponding to the shorter forms were already reported earlier; here we present an analysis of the largest. All three putative polypeptides feature scavenger receptor cysteine-rich (SRCR) domains. The largest form, SRCR-SCR-Car, is a cell-surface receptor of molecular mass 220 kDa, which is assumed to be the cell-adhesion receptor AR; the second form, SRCR-Re, is also a putative receptor of 166 kDa, while the third form, SRCR-Mo, is a soluble molecule of 129 kDa. The SRCR-SCR-Car molecule consists of fourteen SRCR domains, six short consensus repeats (SCRs), a C-terminal transmembrane domain and a cytoplasmic tail; its fourteenth SRCR domain features an Arg-Gly-Asp tripeptide. To obtain monoclonal antibodies, a 170-amino-acid-long polypeptide that is found in all three forms of the SRCR-containing proteins was expressed in E. coli. In a western blot of sponge cells lysate the monoclonal antibody raised against the recombinant polypeptide recognized two major immuno-reacting polypeptides (220 and 117 kDa) and two minor bands (36 and 32 kDa). The antibody was found to react with antigen(s) predominantly localized on the plasma membranes of cells, especially those of spherulous cells. In a functional assay Fab' fragments of the antibodies suppressed AF-mediated cell-cell reaggregation. Additionally, a recombinant SRCR-soluble fragment effectively inhibited AF-mediated cell-cell reaggregation. We conclude that the 220 kDa SRCR-containing protein of the sponge G. cydonium is very likely the AR.


2013 ◽  
Vol 9 (6) ◽  
pp. 406-406
Author(s):  
Jasmine Lee ◽  
Jien Wu ◽  
Yinyue Deng ◽  
Jing Wang ◽  
Chao Wang ◽  
...  

Author(s):  
Dongshunyi Li ◽  
Jun Ding ◽  
Ziv Bar-Joseph

Abstract Motivation Recent technological advances enable the profiling of spatial single-cell expression data. Such data present a unique opportunity to study cell–cell interactions and the signaling genes that mediate them. However, most current methods for the analysis of these data focus on unsupervised descriptive modeling, making it hard to identify key signaling genes and quantitatively assess their impact. Results We developed a Mixture of Experts for Spatial Signaling genes Identification (MESSI) method to identify active signaling genes within and between cells. The mixture of experts strategy enables MESSI to subdivide cells into subtypes. MESSI relies on multi-task learning using information from neighboring cells to improve the prediction of response genes within a cell. Applying the methods to three spatial single-cell expression datasets, we show that MESSI accurately predicts the levels of response genes, improving upon prior methods and provides useful biological insights about key signaling genes and subtypes of excitatory neuron cells. Availability and implementation MESSI is available at: https://github.com/doraadong/MESSI


2011 ◽  
Vol 82 (3) ◽  
pp. 619-633 ◽  
Author(s):  
Stéphane Perchat ◽  
Thomas Dubois ◽  
Samira Zouhir ◽  
Myriam Gominet ◽  
Sandrine Poncet ◽  
...  

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