Profiling the molecular signature of satellite glial cells at the single cell level reveals high similarities between rodents and humans

1. Introduction

Peripheral sensory neurons located in dorsal root ganglia (DRG) relay sensory information from the peripheral tissue to the brain. Satellite glial cells (SGCs) are unique glial cells in which they form an envelope that completely surround each sensory neuron.25,57–59 This organization allows for close bidirectional communication between SGC and their enwrapped soma. Satellite glial cells actively participate in the information processing of sensory signals.28 Morphological and molecular changes are elicited in SGCs by pathological conditions such as inflammation, chemotherapy-induced neuropathic pain, as well as nerve injuries.1,9,23,24,31,80 These studies also point to the contribution of SGCs to abnormal pain conditions under injurious conditions.19,25,28

Our recent analysis of SGCs at the single cell level revealed that SGCs share functional and molecular features with astrocytes.1,2 Despite great morphological differences, SGCs and astrocytes share many signaling mechanisms, including potassium buffering through the inwardly rectifying potassium channel Kir4.1 and intercellular signaling through gap junctions.26 Both cell types also undergo major changes under pathological conditions, which can have neuroprotective function but can also contribute to disease and chronic pain.26

Most of the available information on SGC function has been obtained in rodents, which limits the potential for clinical translation. Only a small number of studies have investigated the molecular characteristics of human SGC.21 Some evidence point to a role of SGC in human pathological conditions. In patients with Friedreich Ataxia, an autosomal recessive neurodegenerative disease, SGC proliferate, form gap junctions and abnormal multiple layers around the neurons,33,34 likely leading to alterations in the bidirectional communication between SGCs and neurons. Satellite glial cells also play a role in viral infection such as herpes simplex virus or varicella zoster virus.16,83 In HIV-1 infection of macaques, the virus that causes AIDS, in which peripheral neuropathy and pain are common, an upregulation of glial fibrillary acidic protein (GFAP) in SGCs was observed.44 The hemagglutinating encephalomyelitis virus belongs to the family of coronavirus and was shown to replicate within rat sensory neurons and accumulate in lysosome-like structures within SGCs, suggesting that SGCs may restrict the local diffusion of the virus.40 Dorsal root ganglion sensory neurons and their SGC coat represent a potential target for multiple viral invasions in the peripheral nervous system.

A better understanding of SGC responses to mechanical, chemical, and viral insults and how SGCs communicate with sensory neurons will be important for future targeted therapies to treat pathological nerve conditions. To facilitate translation of findings in rodent models, a direct comparison with human tissues is thus needed. Here, we present a single-cell level analysis of SGCs in humans, mice, and rats. We find that some of the key features of SGCs, including their similarities with astrocytes and the enrichment of biological pathways related to lipid metabolism and peroxisome proliferator–activated receptor-alpha (PPARα) signaling, are largely conserved between rodents and humans. We also find notable differences in ion channels and receptors expression, which may suggest differences in SGC–neuron communication and function in painful conditions and other peripheral neuropathies. Our study highlights the potential to leverage on rodent SGC properties and unravel novel mechanisms and potential targets for treating human nerve injuries and other pathological conditions.

2. Materials and methods 2.1. Animals and procedures

All animals were approved by the Washington University School of Medicine Institutional Animal Care and Use Committee under protocol A3381-01. All experiments were performed in accordance with the relevant guidelines and regulations. All experimental protocols involving rats and mice were approved by the Washington University School of Medicine (protocol #20180128). Mice and rats were housed and cared for in the Washington University School of Medicine animal care facility. This facility is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care and conforms to the PHS guidelines for Animal Care, Accreditation—7/18/97, USDA Accreditation— Registration # 43-R-008. Eight to 12-week-old female C57Bl/6 mice and adult male Lewis rats were used for single-cell RNA-sequencing (scRNAseq) studies.

2.2. Single-cell RNA sequencing in mice and rats

L4 and L5 DRG from mice (2 biological independent samples, n = 3 mice for each sample) and rats (2 biological independent samples, n = 2 rats for each sample) were collected into cold Hanks balanced salt solution (HBSS) with 5% Hepes and then transferred to warm papain solution and incubated for 20 minutes in 37°C. Dorsal root ganglia were washed in HBSS and incubated with collagenase for 20 minutes in 37°C. Ganglia were then mechanically dissociated to a single-cell suspension by triturating in culture medium (Neurobasal medium), with GlutaMAX, Pen-Strep, and B-27. Cells were washed in HBSS + Hepes + 0.1%BSA solution and passed through a 70-μm cell strainer. The Hoechst dye was added to distinguish live cells from debris, and cells were FACS sorted using MoFlo HTS with Cyclone (Beckman Coulter, Indianapolis, IN). Sorted cells were washed in HBSS + Hepes + 0.1% BSA solution and manually counted using a hemocytometer. The solution was adjusted to a concentration of 500 cells/μL and loaded on the 10x Chromium System. The mouse data set used in this study is the naïve data set used in our previous study.2

Single-cell RNAseq libraries were prepared using GemCode Single-Cell 3′ Gel Bead and Library Kit (10x Genomics). A digital expression matrix was obtained using 10x's CellRanger pipeline (build version 3.1.0) (Washington University Genome Technology Access Center). Quantification and statistical analysis were performed with Partek Flow package (build version 9.0.20.0417). Filtering criteria are low quality cells and potential doublets that were filtered out from analysis using the following parameters: total reads per cell: 600 to 15,000, expressed genes per cell: 500 to 4000, and mitochondrial reads <10%. A noise reduction was applied to remove low-expressing genes ≤1 count. Counts were normalized and presented in a logarithmic scale in the counts per million approach. We applied variance stabilizing transformation to count data using a regularized negative binomial regression model (Seurat::SCTransform) followed by removal of unwanted variation caused by known nuisance or batch factors (scale expression). The principal component analysis using the Louvain clustering algorithm was then undertaken followed by an unbiased clustering (graph-based clustering) algorithm implemented in Partek. Clustering was performed using the compute biomarkers algorithm, which computes the genes that are expressed highly when comparing each cluster. Seurat3 integration was used to obtain cell type markers that are conserved across samples, and clusters were assigned to a cell population by at least 3 established marker genes. Clusters are presented in a t-distributed stochastic neighbor embedding plot, using a dimensional reduction algorithm that shows groups of similar cells as clusters on a scatter plot. Differential gene expression analysis was performed using 3 different models: compute biomarkers following regularized negative binomial regression, nonparametric analysis of variance, and the Partek algorithm GSA that integrate multiple statistical models. Gene lists from each statistical model were intersected to remove potentially false positive genes. The intersected listed were then applied for all downstream analyses. A gene was considered differentially expressed if it has a false discovery rate step-up (P value adjusted) P ≤ 0.05 and a Log2fold-change ≥±2. The differentially expressed genes were subsequently analyzed for enrichment of Gene Ontology (GO) terms and the KEGG pathways using the Partek flow pathway analysis. Partek was also used to generate figures for t-distributed stochastic neighbor embedding and scatter plot representing gene expression.

2.3. Human tissue collection

For single nucleus RNAseq (snRNAseq) and transmission electron microscopy (TEM), human DRG were obtained from Anabios, Inc (San Diego, CA) (donor #1), or Mid-America Transplant (St. Louis, MO) (donors #2-5). L4-L5 DRG were extracted from tissue or organ donors less than 2 hours after aortic cross clamp and was immediately snap frozen and stored at −80°C until use. Details regarding the donors for snRNAseq are included below (Tables 1 and 2).

Table 1 - Donor information for snRNAseq Donor # Age Sex Race DRG level BMI COD 1 44 Female Asian L4 CVA 2 56 Female Black L5 23.13 Anoxia/OD 3 23 Male White L5 21.37 Head trauma/MVA 4 45 Male White L4, 5 28.8 Anoxia 5 51 Female White L5 33.49 Anoxia

BMI, body mass index; COD, cause of death; DRG, dorsal root ganglia.


Table 2 - Donor information for immunohistochemistry studies Donor # Age Sex Race DRG level BMI COD 6 46 Female White L1, 2 20.91 Anoxia 7 44 Female Middle Eastern L1, 4 22.2 CVA/SAH 8 53 Female White L4, 5 25.48 CVA/Stroke 9 54 Female White L1-5 25.9 CVA/Stroke

BMI, body mass index; COD, cause of death; DRG, dorsal root ganglia.

For immunohistochemistry studies, human DRG were obtained from organ donors with full legal consent for use of tissue in research and in compliance with procedures approved by Mid-America Transplant. The Human Research Protection Office at Washington University in St. Louis provided an institutional review board waiver. Details regarding the donors for immunohistochemistry are included below.

2.4. Single-nucleus RNA sequencing from the human sample

To make the tissue suitable for nuclei isolation, the entire DRG was processed into smaller pieces by cryopulverization using the CryoPrep (Covaris; CP02). Nuclei were isolated according to Martelotto with some modifications.45 We elected to apportion the cryopulverized tissue and process the portions in parallel using 2 different buffers to evaluate potential effects on nuclei representation. One homogenization buffer was EZ Nuclei Lysis Buffer (Sigma; NUC101-1KT) with 0.5% RNasin Plus (Promega; N2615), 0.5% SUPERase-In (ThermoFisher; AM2696), and 1 mM Dithiothreitol (DTT).22 The other homogenization buffer was CHAPS detergent, salts, and Tris buffer (CST) buffer (NaCl2 146 mM, Tris HCl pH 7,5 10 mM, CaCl2 1 mM, MgCl2 21 mM, 0.49% 3-((3-cholamidopropyl) dimethylammonio)-1-propanesulfonate (CHAPS) (Millipore-Sigma), 0.01% BSA, 0.5% SUPERasin-in, and 0.5% RNasin Plus), as described in Slyper et al.68 Using the EZ buffer, the samples were homogenized on ice using 18 strokes of Pestle A followed by 18 strokes of Pestle B. The homogenate was filtered through a 50 μm filter (Sysmex; 04-004-2327) into a 2 mL microcentrifuge tube (Eppendorf; 022431048). An additional 0.5 mL of homogenization buffer was used to wash the Dounce homogenizer and filter. The sample was then placed on ice, whereas the remaining samples were processed. The sample was centrifuged at 500g at 4°C for 5 minutes to obtain a crude pellet containing spinal nuclei. The supernatant was removed and discarded, being careful to not disturb the pellet. The pellet was resuspended in 1.5 mL of homogenization buffer and allowed to sit on ice for 5 minutes at 500g, 4°C for 5 minutes. This wash step was repeated twice more for a total of 3 washes. The final pellet was resuspended in 0.5 mL of nuclei resuspension buffer (NRB) containing 6 μM 4′,6-diamidino-2-phenylindole (ThermoFisher; D1306). The suspension was filtered through a 20 μm filter (Sysmex; 04-004-2325) into a polypropylene tube and kept on ice. Using the CST buffer, the samples were homogenized on ice using 18 strokes of Pestle A followed by 18 strokes of Pestle B in 1 mL of CST buffer. The homogenate was filtered through a 50 μm filter into a 15 mL conical. An additional 1 mL was used to wash the filter and then 3 mL of CST was added, bringing the total volume to 5 mL. The suspension was spun down at 500g for 5 minutes at 4°C. The supernatant was removed, and the pellet was resuspended in 0.5 mL of CST containing 6 μM of 4′,6-diamidino-2-phenylindole. The suspension was filtered through a 20 μm filter into a polypropylene tube and kept on ice. Fluorescence-activated nuclear sorting (FANS) was performed to purify nuclei from debris on a FACSAria II (BD). Gates were set to isolate DAPI+ singlet nuclei based on forward scatter and side scatter as well as fluorescence intensity. The instrument was set to 45 pounds per square inch of pressure, and a 85 μm nozzle was used, with sterile phosphate-buffered saline (PBS) sheath fluid. Nuclei were sorted into a 1.5 mL microcentrifuge tube containing 15 μL of NRB at 4°C. For each sample, 18,000 events were sorted into the collection tube. The sorted nuclei and NRB total volume were approximately 45 μL, allowing for the entire loading of the suspension into the Chromium Single Cell 3′ v3 solution (10x Genomics) without any further manipulation. 10x libraries were processed according to the manufacturer's instructions. Completed libraries were run on the Novaseq 6000 (Illumina). A digital expression matrix was obtained using the 10X CellRanger pipeline as above.

2.5. Tissue preparation and immunohistochemistry

Mice were perfused with PBS buffer, followed by 4% paraformaldehyde. After isolation of mouse DRG, the tissue was postfixed using 4% paraformaldehyde for 1 hour at room temperature. Tissue was then washed in PBS and cryoprotected using 30% sucrose solution at 4°C overnight. Next, the tissue was embedded in optimal cutting temperature, frozen, and mounted for cryosectioning. Mouse frozen sections were cut at 12 μm for subsequent staining. Freshly dissected human DRG were sectioned to 40 μm and fixed and stored as free floating in a cryoprotectant. Mouse DRG sections mounted on slides and human floating DRG sections were washed 3 times in PBS and then blocked in solution containing 10% donkey serum in 0.1% Triton-PBS for 1 hour. Next, sections were incubated overnight in blocking solution containing primary antibody. The next day, sections were washed 3 times with PBS and then incubated in blocking solution containing a secondary antibody for 1 hour at room temperature. Finally, sections were washed 3 times with PBS and mounted using ProLong Gold Antifade (Thermo Fisher Scientific). Images were acquired at ×10 or ×20 using a Nikon TE2000E inverted microscope. Antibodies were as follows: TUJ1 (Tubb3/βIII tubulin) antibody (BioLegend catalog #802001, RRID:AB_291637), FABP7 (Thermo Fisher Scientific Cat #PA5-24949, RRID:AB_2542449), and fatty acid synthase (FASN) (Abcam, Catalog #ab128870). Stained sections with only secondary antibody were used as controls. Quantification of SGC markers in human and mouse DRG sections were performed in ImageJ, where the % of neurons surrounded by at least 1 SGC expressing the indicated markers out of total number of neurons in each section was quantified. n = 4 biological independent replicates. Unpaired t test. Data are presented as mean values ±SD.

2.6. Transmission electron microscopy of mice and human dorsal root ganglia

Mice were perfused with 2.5% glutaraldehyde with 4% paraformaldehyde in 0.1 M cacodylate buffer, and DRG were drop fixed to the same fixation buffer for a postfix. A secondary fix was performed with 1% osmium tetroxide. Freshly collected human DRG samples were drop fixed in 2.5% glutaraldehyde + 2% paraformaldehyde in 0.15 M (final concentration) cacodylate buffer pH 7.4 with 2 mM calcium chloride overnight at 4°C. Samples were then vibratomed in the same buffer used for fixation and sections collected into buffer in well plates. For TEM, tissue was dehydrated with ethanol and embedded with Spurr resin. Thin sections (70 nm) were mounted on mesh grids and stained with 8% uranyl acetate followed by Sato lead stain. Sections were imaged on a Jeol (JEM-1400) electron microscope and acquired with an AMT V601 digital camera (Washington University Center for Cellular Imaging).

3. Results 3.1. Profiling satellite glial cells from humans, mice, and rats at the single-cell level

To define the similarities and differences between SGC across different species, we performed snRNAseq of L4 and L5 human DRG and scRNAseq of L4 and L5 mouse and rat DRG using the Chromium Single Cell Gene Expression Solution (10x Genomics) (Fig. 1A). We chose to perform scRNAseq in rodents because we previously showed that this method efficiently captures SGCs.1,2 We opted for snRNAseq in human DRG because the tissue was frozen and the large size of cells in human may limit their capture rate in the 10x platform. The number of sequenced human nuclei from 5 donors (donor information is in the methods section) was 19,865, with an average of 129,520 mean reads per cell, 1480 mean genes per cell, and a total of average 25,643 genes detected. The number of sequenced mouse cells from 2 independent biologically replicates (pooled DRG from 3 mice for each replicate) was 6343 with an average of 65,378 mean reads per cell, 1510 mean genes per cell, and a total of 18,130 genes detected. The number of sequenced rat cells from 2 biologically independent replicates (pooled DRG from 2 rats for each replicate) was 15,892, with an average of 41,594 mean reads per cell, 2132 mean genes per cell, and a total of 17,137 genes detected. Low quality cells and doublets were filtered out from downstream analysis (see filtering criteria in the methods). Human cells from different donors clustered together by the cell type, with the exception of donor #3, in which SGCs clustered separately from the other 4 donors (Fig. 1B). Batches from mice and rats demonstrated high similarities in cell clustering (Fig. 1B).

F1Figure 1.:

Profiling DRG cells from mice, rats, and humans. (A) t-SNE plot of human (18,648 cells), mouse (6251 cells), and rat (11,432 cells) DRG cells colored by cell populations with fraction of distribution. (B) t-SNE plots separated by batch or donors of human (donor1 6444 cells, donor2 3498 cells, donor3 3957 cells, donor4 3871 cells, and donor5 878 cells), mouse (batch1 1929 cells batch2 4322 cells), and rat (batch1 6074 cells batch2 5358 cells). (C) t-SNE overlay for expression of the SGC marker gene Fabp7 in human, mouse, and rat. DRG, dorsal root ganglia; SGC, satellite glial cell; t-SNE, t-distributed stochastic neighbor embedding.

To identify cluster-specific genes, we calculated the expression difference of each gene between that cluster and the average in the rest of the clusters (analysis of variance fold change threshold >1.5). Examination of cluster-specific marker genes revealed major cellular subtypes including neurons, SGC, endothelial cells, Schwann cells, pericytes, smooth muscle cells, macrophages, mesenchymal cells, and connective tissue cells (Table 3 and Fig. 1A).1 Human-specific marker genes were used to classify cell populations: macrophages (CD163 and MRC1), mesenchymal cells (APOD and PDGFRA), endothelial cells (FLT1, PECAM, and CLDC5), connective tissue or mesenchymal cells (COL1A1 and DCN), myelinating Schwann cells (PRX, MAG, and PMP22), SGCs (FABP7 and CDH19), myelinating or nonmyelinating Schwann cells and SGCs (S100B), T-cells (Cd2, Cd3g, and Cd28), and smooth muscle cells (MYOCD, ACTA2, and DES) (Supplementary Fig. 1A, available at https://links.lww.com/PAIN/B599; and Table 3). Rodents had slightly different cell types and markers: macrophages (Cd68 and Aif1), pericytes (Kcnj8 and Pdgfrb), neurons (Tubb3, Gal, Tac, and Prph), SGC (Cdh19, Fabp7, and Kcnj10), Schwann cells (Prx, Mag, and Pmp2), mesenchymal cells (Apod and Pdgfra), smooth muscle cells (Myocd, Acta2, and Des), endothelial cells (Flt1, Pecam, and Cldn5), and connective tissue (Col1a1 and Dcn) (Supplementary Figs. 1B and C, available at https://links.lww.com/PAIN/B599, and Table 3). The cell clusters obtained from the mouse data set matched our previous data set1 (Supplementary Fig. 1D, available at https://links.lww.com/PAIN/B599).

Table 3 - Top 10 differentially expressed genes in each cell population compared with all other cell types in the dorsal root ganglia (fold change threshold >1.5). Human Top genes Connective tissue Endothelial Macrophages Mesenchymal Smooth muscle nmSC mySC SGC T cells 1 SIK2 LIFR RBPJ FTX PRKG1 NRXN1 FMN2 GPR98 PARP8 2 LMO4 PTPRM SLC1A3 USP53 MYH11 ANK3 CTNNA3 HMGCS1 THEMIS 3 PRDM6 EMCN CD163 SLC22A3 INPP4B GPM6B FUT8 TTC6 RASGRP1 4 ANKRD62 ANO2 TCF12 ACADL PIP5K1B CNKSR3 DRP2 CTNND2 CD2 5 BTBD11 VWF MRC1 SLC2A1 RBPMS LRRC8B MAG TRDN LCK 6 GMDS EGFL7 SYK ANKH DGKG MYO1E NCMAP QRFPR STAT4 7 NET1 TCF4 SPTLC2 GRIK2 MYO1B IL34 CDH7 RIMS1 SKAP1 8 GALNT12 MKL2 LRRK2 LAMA2 FAM13C CADM2 ANKRD30B HEY2 IL7R 9 FOXC1 FLT1 DENND3 PAMR1 ABCC9 KCNMB4 LRRC7 SHANK2 ACAP1 10 GLCE CLDN5 SLC9A9 NGFR LDB3 ST6GALNAC5 PMP22 MMD2 CD96 Mouse Top genes Connective tissue Endothelial Macrophages Mesenchymal Neurons Pericytes Schwann cells SGC Smooth muscle T cells 1 SAA1 CLDN5 LY86 MFAP4 GAL KCNJ8 NCMAP FABP7 PLN CAMP 2 SAA2 LY6C1 PF4 SFRP4 TAC1 ACE2 SLC36A2 BCAN FBXL22 NGP 3 CDKN2A SOX17 CCL12 SLC47A1 PRPH ADRA2A FAM178B RP24-247B20.1 TCF15 S100A8 4 OSR2 GPIHBP1 BCL2A1B COMP ELAVL4 ABCC9 CLDN19 MMD2 ACTA2 S100A9 5 LUM SLCO1A4 C1QC SLC4A10 SCG2 COLEC11 MLIP ACSBG1 MYH11 LTF 6 A2M GRRP1 CCL4 H19 STMN2 TRPC6 PRX LRRTM1 KCNA5 1100001G20RIK 7 CCL11 PLVAP CD74 IGF2 RPRM KCNE4 PMP2 DHRS2 TAGLN RETNLG 8 APOD FLT1 C1QA PROK2 TRPV1 RGS5 KCNK1 TEX40 MAP3K7CL LCN2 9 6030408B16RIK RBP7 MS4A6C DIO2 EEF1A2 AGTR1A IL17B GM2115 TESC LY6G 10 CDKN2B ELTD1 CTSS NOV ISL1 PLA1A OTOP1 LECT1 NTF3 MMP8 Rat Top genes Connective tissue Endothelial Macrophage Mesenchymal Neuron Pericytes Schwann cell SGC 1 SCARA5 CLDN5 C1QA CLDN11 ADCYAP1 KCNJ8 MAG TYRP1 2 POSTN FLT1 LYZ2 KCNJ13 SCG2 RGS5 SLC36A2 IGFBP2 3 CRISPLD2 CYYR1 C1QC GZMM SNHG11 ACTA2 CLDN19 CSN1S1 4 LOC100911545 SLCO14A C1QB SLC16A11 CALCB NDUFA4L2 NCMAP SCRG1 5 DNAH11 FAM110D TYROBP ALDH1A3 NTRK1 CCL19 SYCE3 SPP1 6 RBP4 ABCG2 AIF1 IGFBP6 RIT2 HIGD1B KCNK1 CDH15 7 GAD1 SOX17 FCER1G CPXM2 PCBD1 NPY1R BCAS1 FABP7 8 MYOC PROM1 CCL4 KLF5 SYT1 RASL11A PRX SCD 9 SRPX ADGRL4 CXCL2 GJB2 LAMP5 INPP4B KCNA1 FBLN5 10 MEOX1 PLVAP CCL6 TBATA NSG2 ADRA2A MME LOC102553138

DRG, dorsal root ganglia; mySC, myelinating Schwann cell; nmSC, nonmyelinating Schwann cell; SGC, satellite glial cell

We previously showed that although the actual percentage of neuronal cells in the mouse DRG is about 12%, the number of neurons detected in our scRNAseq analysis was only about 1%,1,2 which might be a result of the dissociation protocol that is biased towards nonneuronal cells. Another possibility is neuronal damage during the tissue dissociation process or the fact that sensory neurons are relatively large cells and are less amenable for single-cell studies. In the rat samples, only 0.5% of cells were neurons, and no neuronal cells were detected in the human sample (Fig. 1A). Nevertheless, our protocol achieved recovery of SGCs from all species with 42% in humans, 55% in mice, and 74% in rats (Fig. 1A), allowing us to compare the molecular profile of SGC across species.

We recently described that fatty acid–binding protein 7 (Fabp7) is a specific marker gene for SGC and that the FABP7 protein is highly enriched in mouse SGC compared with other cells in the DRG.1 t-distributed stochastic neighbor embedding plots overlaid for Fabp7 demonstrated that Fabp7 is also enriched in human and rat SGC (Fig. 1C). To validate Fabp7 expression at the protein level, we performed immunostaining of DRG sections from mouse and human, which revealed specific FABP7 labelling of SGC surrounding sensory neurons in both species (Figs. 2A and B).

F2Figure 2.:

FABP7 is an SGC marker in mice and humans. (A and B) Representative images of immunofluorescence staining of human (A) and mouse (B) DRG sections labelled for TUJ1 (magenta) and FABP7 (green). Scale bar: 200 μm (left panel) and 50 μm (right panel). n = 4 biologically independent replicates for both a and b. (C) Representative TEM images of DRG sections from human and mouse showing neuronal cell bodies and its enveloping SGCs (SGC cytoplasm is pseudocolored in green and SCG nuclei are pseudocolored in blue). (D) Quantification of the number of SGC surrounding a single neuron. n = 4 biologically independent animals (mouse) and n = 2 individual donors (human). DRG, dorsal root ganglia; SGC, satellite glial cell; TEM, transmission electron microscopy.

In adult animals, SGC tightly enwrap the soma of each sensory neuron.56,57,59 The gap between SGC and the neuronal surface is only about 20 nm, which is similar to that of the synaptic cleft. This close association between the 2 cell types is essential for efficient mutual neuron–SGC interactions.25 The detailed morphology of the human neuron–SGC unit has only been examined at the light microscopy level in humans.21 To further compare the SGC organization surrounding sensory neurons across species, we performed TEM of human and mouse DRG sections (Fig. 2C), which demonstrated the tight contact between SGCs and neurons in both mouse and human and the increased human sensory neuron soma size, which can be up to 5 times larger than mouse sensory neurons (Fig. 2C).21 Quantification of the number of SGCs surrounding sensory neurons revealed that human sensory neurons are surrounded by significantly more SGCs than mouse neurons (Fig. 2D), consistent with the observations that the number of SGC surrounding sensory neurons increases with increasing soma size in mammals.36,56,59

3.2. Expression of satellite glial cell–specific marker genes in rodents and humans

We next examined the expression of known SGC marker genes in rodents and humans. Cells in the clusters identified as SGCs were pooled together. We identified 7880 SGCs in humans, 3460 SGCs in mice, and 8428 SGCs in rats (Figs. 3A–C). t-distributed stochastic neighbor embedding plots overlaid with Fabp7 demonstrated that, in all species, Fabp7 is expressed at high levels in a majority of SGCs (mice 92%, rats 88%, and humans 96% (Figs. 3A–D). Cadherin19 (Cdh19) has been described as a unique SGC marker in rat Schwann cell precursors71 and in adult rat SGCs.20 We found that Cdh19 was expressed in most human SGCs (98%), whereas only half of SGCs in rodents expressed this gene (56% in mice and 48% in rats) (Figs. 3A–D). Glutamine synthetase

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