The regularity of sustained firing reveals two populations of slowly adapting touch receptors in mouse hairy skin

Abstract

Touch is initiated by diverse somatosensory afferents that innervate the skin. The ability to manipulate and classify receptor subtypes is prerequisite for elucidating sensory mechanisms. Merkel cell-neurite complexes, which distinguish shapes and textures, are experimentally tractable mammalian touch receptors that mediate slowly adapting type I (SAI) responses. The assessment of SAI function in mutant mice has been hindered because previous studies did not distinguish SAI responses from slowly adapting type II (SAII) responses, which are thought to arise from different end organs, such as Ruffini endings. Thus we sought methods to discriminate these afferent types. We developed an epidermis-up ex vivo skin-nerve chamber to record action potentials from afferents while imaging Merkel cells in intact receptive fields. Using model-based cluster analysis, we found that two types of slowly adapting receptors were readily distinguished based on the regularity of touch-evoked firing patterns. We identified these clusters as SAI (coefficient of variation = 0.78 +/- 0.09) and SAII responses (0.21 +/- 0.09). The identity of SAI afferents was confirmed by recording from transgenic mice with green fluorescent protein-expressing Merkel cells. SAI receptive fields always contained fluorescent Merkel cells (n = 10), whereas SAII receptive fields lacked these cells (n = 5). Consistent with reports from other vertebrates, mouse SAI and SAII responses arise from afferents exhibiting similar conduction velocities, receptive field sizes, mechanical thresholds, and firing rates. These results demonstrate that mice, like other vertebrates, have two classes of slowly adapting light-touch receptors, identify a simple method to distinguish these populations, and extend the utility of skin-nerve recordings for genetic dissection of touch receptor mechanisms.

Fig. 1.

Schematic of the epidermis-up ex vivo skin–nerve preparation (A). The hindlimb skin of a mouse is mounted in a perfusion chamber, with the attached saphenous nerve resting on a mirror in the adjoining recording chamber. The skin is perfused with synthetic interstitial fluid (SIF), saturated with 95% O₂-5% CO₂. Bath temperature is monitored by a thermistor (Therm) and maintained at 32°C. The preparation is visualized with a fluorescence-equipped stereomicroscope (Micro) connected to a camera and computer for image capture. The computer also controls electrical stimuli from a stimulus generator and mechanical stimuli via a motor controller. The motor controller drives a stepper motor (M) mounted to a rigid arm and an X/Y stage. A ceramic probe is mounted to the end of a cantilever arm with an in-line force transducer (FT). Force data are sent to the computer via an amplifier and captured along with differential recordings of extracellular potentials in a nerve bundle. Extracellular potentials are sent in parallel to an oscilloscope and a speaker for aural detection of action potentials. B: image of the mechanical stimulator. C: a skin–nerve preparation mounted in the recording chamber. The edge of the skin is denoted by a dotted black line. Pigmented areas of skin are in the active growth phase (anagen) of the hair cycle.

Fig. 2.

Receptive field (RF) areas and von Frey thresholds are higher on the dermal surface than the epidermal surface. Measurements were made from both the epidermal and dermal surfaces on the same set of afferents by flipping the skin over during recording (n = 7). RF size was calculated as the area of an ellipsoid with measured diameters and had median values of 0.17 mm² (epidermal) and 0.26 mm² (dermal). A: fold change in RF area from epidermal to dermal surface. Each connected pair of points indicates a single afferent and shows the change in measured RF size due to skin orientation, with the absolute size of the dermal RF indicated at the right (mm²). B: superimposed action potentials from one of the afferents used in the epidermis vs. dermis comparisons. Ten action potentials are from an epidermal stimulus (black) and 10 are from a dermal stimulus (gray). C: von Frey force thresholds also increased when measured from the dermal surface (P = 0.01, Wilcoxon one-tailed signed-rank test). Only 3 pairs are visible due to overlap of multiple afferents (n = 7). D: the same data as shown in C, but with von Frey forces converted to minimum potential pressures, based on the assumption of a simple cylindrical probe. Because von Frey filaments do not monotonically increase in diameter, this conversion to pressure causes a spurious reversal of some trends in the data.

Fig. 3.

Flow chart for classifying touch receptors in the epidermis-up mouse skin–nerve preparation. After locating a mechanosensitive afferent with a mechanical search, A-afferents and C-fibers can easily be distinguished based on their conduction velocities. Aδ-fibers can usually be distinguished from Aβ-fibers by conduction velocity, but there is some overlap between the 2 populations. Slowly adapting (SA), rapidly adapting (RA), and any remaining A-mechanonociceptor (AM) or D-hair fibers can then be distinguished by mechanical thresholds, RF sizes, and adaptation properties. Slowly adapting types I and II (SAI and SAII, respectively) responses are differentiated by the regularity of their static-phase firing rates, which is quantified as the coefficient of variation (CoV) of interspike intervals (ISIs; see Figs. 4–6). Plots in each afferent-type box show a typical response, as instantaneous firing frequency vs. time, to a 5-s touch stimulus. Twenty mechanically evoked action potentials from the example fiber are superimposed to the right of each plot to show matching waveforms.

Fig. 4.

Two classes of SA mechanoreceptors exist in mice. Model-based cluster analyses on ≤4 variables including minimum dynamic ISI, mean static ISI, CoV of static ISIs, and minimum static ISI were performed on 17 SA fibers using the MClust package for R. A: the model and cluster number combination with the lowest Bayesian information criterion (BIC) that grouped together fluorescence microscopy-confirmed SAI fibers was equal size and shape ellipsoids, with their axes aligned with the coordinate axes (EEI, hollow circles). Minimum BIC with this model was −142 at 2 clusters. Other models shown are equal size and shape ellipsoids with either the same orientation (EEE, black squares) or freely oriented (EEV, gray triangles). Other models tested had minimum BIC above −100. B: all fibers used for cluster analysis plotted along the 2 discriminant variables. Fiber classification based on the best model chosen by the analysis from A is indicated by an open circle or gray triangle. Clusters for the best fit model were ellipsoids of the same volume with long axes perpendicular to the CoV coordinate. Clusters are indicated as dashed ellipses with radii of 3SDs centered around the mean of each cluster. C: univariate cluster analysis of CoV for all fibers yielded a higher BIC (−1), but categorized the fibers into the same clusters and provided the lowest BIC of any other single variable. The best fit was to an equal variance model (open circles) with 2 clusters. Results of variable variance model fitting are shown as gray triangles. D: mean CoV of interspike interval values plotted as a histogram of all fibers. For each afferent, values were calculated as the mean of the CoV of all stimuli. There is a bimodal distribution with maximal separation at 0.49. Afferents confirmed as SAI fibers by fluorescent microscopy lie within the cluster with CoV >0.49, leading to the designation of these 2 populations as SAI and SAII.

Fig. 5.

SAI receptive field images and responses to touch stimuli. Micrographs (A and B) show the Merkel-cell cluster innervated by this SAI afferent. Arrowheads indicate the same 3 Merkel cells in both images. A: an epifluorescence micrograph of the touch dome demonstrating enhanced green fluorescent protein (eGFP, green) in Merkel cells in the living skin–nerve preparation. Asterisk (*) denotes the position of the guard hair. B: confocal z-series projection of the same touch dome shows 22 Merkel cells in the cluster. C: recorded force values during a family of 5-s displacements. D: voltage traces showing action potential trains for each stimulus. The SAI afferent responds to increased force with an increase in firing rate while maintaining its irregular firing pattern. Responses are shown from static-phase pressures of about 30–150 kPa. This particular afferent was chosen as an example of the hallmark irregularity of SAI responses, although its firing rate falls below the mean for SAI afferents. There is an RA unit present in this recording as well, visible at the end of the top 2 traces as an approximately 200-μV peak that was easily discriminated and did not interfere with data analysis.

Fig. 6.

SAII receptive field image and responses to touch stimuli. A: micrograph of the skin of an FM1-43-injected mouse from which the recordings in B and C were taken. The receptive field of this afferent (dashed ellipse) does not overlap with 2 labeled touch domes (asterisks) visible in this field. B: force family for the voltage traces shown below. Each stimulus lasted for 5 s. Some mechanical ringing is visible at the onset of each stimulus, which decayed to below baseline well before the static phase. C: the SAII afferent responded with low, stochastic firing to very light stimuli (top trace), but more intense stimulation elicited robust and highly regular spike trains. When CoV values across stimulus intensity are averaged prior to afferent comparisons, the impact of low-firing rate responses is reduced. To avoid classification error, it is important to use stimuli sufficient to exceed this irregularity range (<15–20 Hz). Responses are shown from roughly 25- to 150-kPa static pressures. Two additional units are visible as low-amplitude action potentials, one at all stimulus intensities and one at only the highest 2 stimulus levels.

Fig. 7.

Firing rate data for SAI responses (open circles) and SAII responses (gray squares) are shown in A and B (error bars denote ±SE). Data represent individual stimuli across afferents in 200-kPa bins, demonstrating that SAI and SAII afferents produce similar firing rates in response to displacement stimuli. A: mean firing rate during the dynamic phase (t = 0–200 ms, calculated as the inverse of the mean ISI) plotted against peak dynamic force. B: mean firing rate for the static phase (2–4.5 s) plotted against the mean static-phase force (n = 113 stimuli from 11 SAI afferents and 27 stimuli from 7 SAII afferents). C: histogram of normalized static-phase ISIs for SAI (black outline) and SAII (solid gray) responses. Note the wide dispersion of intervals in SAI responses relative to SAII. To allow comparison of intervals across stimulus intensities and afferents, each interval is normalized to the mean interval for their stimulus of origin (SAI, n = 3,348 intervals; SAII, n = 1,533 intervals).