Nerve-Muscle Cell Trophic Communication: Introductory Remarks

Author(s):  
Hugo L. Fernandez ◽  
J. Alejandro Donoso
Keyword(s):  
eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Gilles Ouanounou ◽  
Gérard Baux ◽  
Thierry Bal

Excitability differs among muscle fibers and undergoes continuous changes during development and growth, yet the neuromuscular synapse maintains a remarkable fidelity of execution. Here we show in two evolutionarily distant vertebrates (Xenopus laevis cell culture and mouse nerve-muscle ex-vivo) that the skeletal muscle cell constantly senses, through two identified calcium signals, synaptic events and their efficacy in eliciting spikes. These sensors trigger retrograde signal(s) that control presynaptic neurotransmitter release, resulting in synaptic potentiation or depression. In the absence of spikes, synaptic events trigger potentiation. Once the synapse is sufficiently strong to initiate spiking, the occurrence of these spikes activates a negative retrograde feedback. These opposing signals dynamically balance the synapse in order to continuously adjust neurotransmitter release to a level matching current muscle cell excitability.


1973 ◽  
Vol 62 (3) ◽  
pp. 255-270 ◽  
Author(s):  
J. H. Steinbach ◽  
A.J. Harris ◽  
J. Patrick ◽  
D. Schubert ◽  
S. Heinemann

Nerve and muscle cells from clonal lines interact in vitro, resulting in the association on the muscle surface of an area of increased acetylcholine sensitivity with a site of nerve-muscle contact. This localization of acetylcholine sensitivity on the muscle cell to a site of contact between nerve and muscle was found to occur when acetylcholine receptors on the muscle had been blocked with α-neurotoxin. Localization was also found to occur when the nerve cell had been prevented from releasing acetylcholine. It is concluded that neither the presence of active acetylcholine receptors on the muscle, nor the release of acetylcholine from the nerve, was required for the events leading to the localization of acetylcholine sensitivity in vitro.


1988 ◽  
Vol 254 (3) ◽  
pp. C345-C364 ◽  
Author(s):  
R. J. Bloch ◽  
D. W. Pumplin

The clustering of acetylcholine receptors (AChR) in the postsynaptic membrane of newly innervated muscle fibers is one of the earliest events in the development of the vertebrate neuromuscular junction. Here, we describe two hypotheses that can account for AChR clustering in response to innervation. The "trophic factor" hypothesis proposes that the neuron releases a soluble factor that interacts with the muscle cell in a specific manner and that this interaction results in the local accumulation of AChR. The "contact and adhesion" hypothesis proposes that the binding of the nerve to the muscle cell surface is itself sufficient to induce AChR clustering, without the participation of soluble factors. We present a model for the molecular assembly of AChR clusters based on the contact and adhesion hypothesis. The model involves the sequential assembly of three distinct membrane domains. The first domain to form serves to attach microfilaments to the cytoplasmic surface of the muscle cell membrane at sites of muscle-nerve adhesion. The second domain to form is clathrin-coated membrane; it serves as a site of insertion of additional membrane elements, including AChR. Upon insertion of AChR into the cell surface, a membrane skeleton assembles by anchoring itself to the AChR. The skeleton, composed in part of actin and spectrin, binds and immobilizes significant numbers of AChR, thereby forming the third membrane domain of the AChR cluster. We make several predictions that should distinguish this model of AChR clustering from one that invokes soluble, trophic factors.


Author(s):  
Naagarajan Narayanan ◽  
Paul Lengemann ◽  
Kun Ho Kim ◽  
Liangju Kuang ◽  
Tiago Sobreira ◽  
...  

Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).


1979 ◽  
Vol 7 (5) ◽  
pp. 1169-1169
Author(s):  
S. WONNACOTT
Keyword(s):  

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