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. 2023 Sep 15;9(37):eadi4147.
doi: 10.1126/sciadv.adi4147. Epub 2023 Sep 13.

3D architecture and a bicellular mechanism of touch detection in mechanosensory corpuscle

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3D architecture and a bicellular mechanism of touch detection in mechanosensory corpuscle

Yury A Nikolaev et al. Sci Adv. .

Abstract

Mechanosensory corpuscles detect transient touch and vibration in the skin of vertebrates, enabling precise sensation of the physical environment. The corpuscle contains a mechanoreceptor afferent surrounded by lamellar cells (LCs), but corpuscular ultrastructure and the role of LCs in touch detection are unknown. We report the three-dimensional architecture of the avian Meissner (Grandry) corpuscle acquired using enhanced focused ion beam scanning electron microscopy and machine learning-based segmentation. The corpuscle comprises a stack of LCs interdigitated with terminal endings from two afferents. Simultaneous electrophysiological recordings from both cell types revealed that mechanosensitive LCs use calcium influx to trigger action potentials in the afferent and thus serve as physiological touch sensors in the skin. The elaborate architecture and bicellular sensory mechanism in the corpuscles, which comprises the afferents and LCs, create the capacity for nuanced encoding of the submodalities of touch.

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Figures

Fig. 1.
Fig. 1.. Meissner corpuscles comprise a stack of LCs interdigitated with terminal afferent disks.
(A) FIB-SEM workflow for automated segmentation and machine learning-based 3D reconstruction of a Meissner corpuscle in duck bill skin from 4753 SEM images. (B to D) Three-dimensional architecture of a Meissner corpuscle (B), corpuscle without outer capsule (C), isolated afferents (D). (E) Three-dimensional architecture of a section of afferent 1 and afferent 2 and associated LCs. aff., afferent.
Fig. 2.
Fig. 2.. Lamellar cells interact with the afferent via DCVs and tethers.
(A) Close-up 3D reconstruction of villi protruding from the edge of LC4 and a pseudo-colored scanning electron microscope image of villi (black arrowheads) protruding from the edge of LC4 and contacting the satellite cell and afferent. (B) A pseudo-colored scanning electron microscope image depicting DCVs inside LCs (left) and a corresponding map of the cell types shown in the image (right). (C) A density map of DCVs in LCs. (D to F) Quantification of the total DCV count per LC (D), DCV diameter (E), and distance from each DCV to the closest afferent membrane (F). n is the total number of DCVs. (G) Transmission electron microscopy image of the LC-afferent contact area. Blue arrowheads point to tethers connecting LC and afferent plasma membranes. (H) Three-dimensional reconstruction of a fragment of the LC-afferent contact area.
Fig. 3.
Fig. 3.. Avian Meissner corpuscles detect transient touch.
(A) A bright-field image and schematic representation of the experimental setup to record afferent activity from intact Meissner corpuscle in duck bill skin. (B) Mechanical step stimulus applied with a glass probe (top), representative rapidly adapting single-fiber response comprising APs (middle), and representative single-fiber response in the presence of 1 μM TTX (voltage-gated sodium channel blocker) comprising receptor potentials (bottom). (C) Mechanical step stimulus with long ramp phases (top), representative rapidly adapting single-fiber response comprising APs (middle), and representative single-fiber response in the presence of 1 μM TTX comprising receptor potentials (bottom). (D) Vibratory mechanical stimulus (top), representative single-fiber response comprising APs (middle), and representative single-fiber response in the presence of 1 μM TTX comprising receptor potentials (bottom). (E) Raster plot of rapidly adapting afferent firing for five different corpuscles in response to mechanical stimuli of two different indentation depths. Each vertical dash represents an individual AP. TTX, tetrodotoxin.
Fig. 4.
Fig. 4.. Activation of a single LC is sufficient to drive afferent firing.
(A and B) Bright-field image (A) and schematic representation of the experimental setup (B) for simultaneous electrophysiological recordings from LC and afferent of a Meissner corpuscle in duck bill skin. (C) Current injection applied to the LC (ILC, top), voltage response and APs in the LC recorded with a potassium-based internal solution (VLC, middle), and extracellular voltage and APs in the afferent (Vaff, bottom). (D) Voltage step stimulus applied to the LC (VLC, top), current response with potassium-based internal solution in the LC (ILC, middle), and extracellular voltage and APs in the afferent (Vaff, bottom). (E) Raster plot of afferent AP firing for individual corpuscles during LC activation by either depolarizing current injections in the current clamp (blue) or voltage steps to 0 mV in the voltage clamp (maroon). Each vertical dash represents an individual AP. (F) Total number of afferent APs versus latency between onset of the stimulus and first AP. Dots represent data from individual corpuscles. The solid line is a fit to the liner equation and dashed lines are 95% confidence intervals of the linear fit. (G) Afferent AP frequency when LCs held at −70 and 0 mV. Lines connect data pairs from individual corpuscles. Wilcoxon matched pairs test.
Fig. 5.
Fig. 5.. LC activation triggers afferent firing via a calcium-dependent mechanism.
(A) Exemplar traces recorded in a Meissner afferent in response to LC activation by voltage clamp with a cesium-based internal solution to quench potassium efflux (control), following the removal of extracellular Ca2+ and the addition of 300 μM Cd2+ to block voltage-activated calcium channels (No Ca2+) and upon reintroduction of calcium and removal of Cd2+ (Wash). VLC, voltage step stimulus applied to the LC; ILC, current response in the LC; Vaff, extracellular voltage and APs in the afferent. (B) Quantification of the effect of calcium removal on LC-induced afferent firing. Lines connect data from the same afferent (n = 5 afferents). The difference between control and wash was not significant (P = 0.6856). Friedman test with Dunn’s correction for multiple comparisons.

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