Kunkel DD et al. (2001), Ultrastructure of acetylcholine receptor aggreg...

XB-ART-7933

BMC Neurosci 2001 Jan 01;2:19. doi: 10.1186/1471-2202-2-19.

Show Gene links Show Anatomy links

Ultrastructure of acetylcholine receptor aggregates parallels mechanisms of aggregation.

Kunkel DD , Lee LK , Stollberg J .

???displayArticle.abstract???
BACKGROUND: Acetylcholine receptors become aggregated at the developing neuromuscular synapse shortly after contact by a motorneuron in one of the earliest manifestations of synaptic development. While a major physiological signal for receptor aggregation (agrin) is known, the mechanism(s) by which muscle cells respond to this and other stimuli have yet to be worked out in detail. The question of mechanism is addressed in the present study via a quantitative examination of ultrastructural receptor arrangement within aggregates. RESULTS: In receptor rich cell membranes resulting from stimulation by agrin or laminin, or in control membrane showing spontaneous receptor aggregation, receptors were found to be closer to neighboring receptors than would be expected at random. This indicates that aggregation proceeds heterogeneously: nanoaggregates, too small for detection in the light microscope, underlie developing microaggregates of receptors in all three cases. In contrast, the structural arrangement of receptors within nanoaggregates was found to depend on the aggregation stimulus. In laminin induced nanoaggregates receptors were found to be arranged in an unstructured manner, in contrast to the hexagonal array of about 10 nm spacing found for agrin induced nanoaggregates. Spontaneous aggregates displayed an intermediate amount of order, and this was found to be due to two distinct population of nanoaggregates. CONCLUSIONS: The observations support earlier studies indicating that mechanisms by which agrin and laminin-1 induced receptor aggregates form are distinct and, for the first time, relate mechanisms underlying spontaneous aggregate formation to aggregate structure.

???displayArticle.pubmedLink??? 11749670
???displayArticle.pmcLink??? PMC61448
???displayArticle.link??? BMC Neurosci

Species referenced: Xenopus laevis
Genes referenced: grap2

???attribute.lit??? ???displayArticles.show???

	Figure 1. Fluorescent micrographs of Xenopus muscle cells stimulated with laminin-1 (A) and under control conditions (B). Cells were labeled for AChRs with rhodamine α-Bungarotoxin. Sources of light internal to the cell membrane correspond to autofluorescence and should be ignored. Note the increase in the size and number of aggregates found following stimulation with laminin-1.
	Figure 2. Scanning electron micrograph of Xenopus muscle cell membrane stimulated with laminin-1 and immuno-gold labeled for AChRs. The particles appear to be arranged into nanoaggregates (arrows) suggesting a non-random distribution.
	Figure 3. Frequency histograms of experimental nearest neighbor distances. A, laminin-1 induced receptor aggregates (n = 2581, n-reduced = 1468). B, spontaneous receptor aggregates (n = 1527, n-reduced = 905). Arrows, prominent in peaks in agrin-induced receptor aggregates, do not characterize laminin-induced aggregates (A) but may be present in spontaneous aggregates (B). A compared to B, Pearson χ2 p < .0001. Dashed curves, the probability density functions for randomly distributed particles with a hindrance of 16 nm at the respective densities found. A or B compared to data, Pearson χ2 < 10-10. Solid curves – the same functions with the density terms artificially elevated to best approximate the distributions in the range 20 to 40 nm. A or B compared to data, Pearson χ2 p < 10-10. Heavy solid curves, best fit quadratics over the range 20 to 40 nm. A, 300.75 - 14.67 x + 0.19 x2, Pearson χ2 p > 0.22. B, 196.41 - 9.45 x + 0.12 x2, Pearson χ2 p < 0.02.
	Figure 4. Digital montage of seven overlapping micrographs showing gold label locations in a cell stimulated with laminin-1. Arrows, positions of nanoaggregates marked in Figure 2. The different colors represent the distinct nanoaggregates identified by software (black points are not members of any nanoaggregate).
	Figure 5. Examples of gold particle nanoaggregates identified by software. The polygons represent the defined perimeter (Materials and methods), the asterisks the center of mass, and the circles are the smallest centered on the asterisks that encompass all points within the nanoaggregates. A, size = 4 gold particles, density = 3876 particles/μm2, normalized area/perimeter ratio = 0.35, diameter ratio = 0.43. B, size = 6 particles, density = 3333/μm2, area/perimeter ratio = 0.83, diameter ratio = 0.98.
	Figure 6. Frequency histograms of nanoaggregate density. A, laminin-1 induced receptor aggregates (n = 124). B, spontaneous receptor aggregates n = 99). The latter distribution appears to be bimodal, suggesting that there may be two populations of spontaneous aggregates. A compared to B, Pearson χ2 p < .001.
	Figure 7. Frequency histograms of experimental and simulated nearest neighbor distances. A, high density receptor aggregates (n = 218, n-reduced = 146). B, low density receptor aggregates (n = 289, n-reduced = 178). C, simulation of nearest neighbor distances assuming a hexagonal array of receptors with a spacing of 9.9 nm. Arrows, prominent in peaks in agrin-induced receptor aggregates, do not characterize high density aggregates (A) but appear to be represented in low density aggregates (B). A vs. C, Pearson χ2 < 10-10. B vs. C, Pearson χ2 > 0.13.
	Figure 8. Schematic of gold label locations in hexagonal and random nanoaggregates. The size of the gold label symbol represents the known steric hindrance of the labeling paradigm, which includes two antibodies as well as the gold particle itself. A, 20 AChRs lie on a hexagonal grid, which can be labeled by at most 8 gold particles because of steric hindrance. B, only 12 AChRs are present in this randomly arrayed nanoaggregate, but the density of gold particles is higher (12 particles per unit area) than in A. For purposes of illustration this figure assumes that every receptor which can be is labeled, however the argument holds at lower binding efficiencies as well.
	Figure 9. Software determination of gold particle locations. A, enlarged image of raw bitmap showing 6 gold particles. B, 3-Dimensional plot of A illustrates the difficulty in threshold detection of particles. C, the original bitmap convolved with a kernel comprised of the average of 662 gold particles; compare to B with respect to enhancement of gold particle signal and reduction in noise and intensity drift. D, software determination of gold particle locations, based on the center of mass of supra-threshold clusters of pixels. All spatial axes are in units of pixels, coincidentally similar in this instance to the dimensions in nanometers (see calibration in A).
	Figure 10. Frequency histogram of reduced nearest neighbor distances in laminin-1 stimulated cells. Although the number of observations has been reduced (n = 1468 vs. 2581 unreduced) the form of the distribution is clearly very similar to that of the unreduced data (compare to Figure 3A).

References [+] :

Baker, Induction of acetylcholine receptor clustering by native polystyrene beads. Implication of an endogenous muscle-derived signalling system. 1992, Pubmed, Xenbase