Introduction
The vertebrate inner ear contains mechanosensory organs that sense sound and balance. In mammals, the cochlea senses sound, the saccule and utricle sense horizontal and vertical acceleration, respectively, and the cristae in each of the semicircular canals sense angular head movements, which is critical for maintaining balance and the vestibulo-ocular reflex (Highstein and Holstein, 2012). Cristae exhibit significant age-related degeneration of hair cells, particularly type I hair cells (Rauch et al., 2001; Lopez et al., 2005). Dysfunction of crista is therefore implicated in balance disorders and falls in the elderly, as well as in the pathology of Meniere’s, benign paroxysmal positional vertigo and other balance disorders.
Whereas other sensory organs in the inner ear have been profiled by single-cell RNA-seq (scRNA-seq), no studies to date have analyzed the crista ampullaris. Analysis of scRNA-seq data from the utricle, cochlea, and endolymphatic sac have revealed developmental transitions and rare cell types of possible importance to the etiology of hearing and vestibular disorders (Burns et al., 2015; Honda et al., 2017; Yamashita et al., 2018; Korrapati et al., 2019; Hoa et al., 2020; Ranum et al., 2019; Petitpré et al., 2018; Shrestha et al., 2018; Sun et al., 2018). The sensory epithelium of the crista includes type I and type II hair cells each having distinct morphology and synapses, support cells and glia (Desai et al., 2005). Five nonsensory cell types of the ampulla have been described morphologically: (1) transitional epithelial cells bordering the sensory epithelium, (2) periotic mesenchyme surrounding the ampulla epithelium, (3) dark cells of the ampulla, the osmiophilic and endolymph-producing cells, (4) melanocytes underlying the dark cells and (5) light cells, the osmiophobic cells of the planum semilunatum and the ampulla roof and wall (Köppl et al., 2018; Kimura et al., 1964; McLamb and Park, 1992; Tachibana et al., 1987; Nakai and Hilding, 1968; Bairati and Iurato, 1960; Ten Cate and Rarey, 1992). Understanding the cellular composition of the crista and the gene expression in each cell type is a critical step towards understanding inner ear development, function, and vestibulopathies.
In mammals, regeneration in the vestibular organs is slow, highly variable and limited to Type II-like hair cells with immature hair bundle morphology (Kinoshita et al., 2019; Sayyid et al., 2019; Forge et al., 1993). An unexplained phenomenon of importance to the goal of therapeutic regeneration of hair cells in the vestibular system is the perinatal window of greater regeneration-competence in support cells (Slowik and Bermingham-McDonogh, 2013a). In adult cristae, a subset of support cells maintains competence to convert into hair cells in response to Notch inhibition (Slowik and Bermingham-McDonogh, 2013b), which implies heterogeneity of support cells in the crista.
To gain insights into the cellular composition of the crista during the perinatal window of greater regeneration-competence of support cells, we performed single-cell RNA-seq in crista ampullaris microdissected from E16, E18, P3, and P7 mice. We identified and validated many novel cell types, cell-specific markers, and developmental changes in cellular composition of the crista that are in addition to the support cells we initially aimed to study. Integrated analysis of the data provides novel insights into the pathways and transcription factors that may regulate cell-specific gene expression and functions in the crista as well as the cell types involved in vestibular disease.
Results
Cellular diversity in the crista ampullaris
Cells were dissociated from crista ampullaris of mice at E16, E18, P3, and P7 and their gene expression was analyzed by scRNA-seq (Figure 1a). Dimensional reduction was performed using UMAP to visualize transcriptional differences in cells (Figure 1b). Based on enrichment for known markers (Figure 1c and d), we identified major cell types as shown in Figure 1b. Clustering detects the major cell types at all four ages examined, although the proportions of some types change between E16 and P7. Cluster analysis identifies distinct cell groups enriched with known markers for hair cells, support cells, dark cells of the crista as well as nonsensory epithelial cells of the ampulla roof and wall, glia, otic mesenchymal cells, macrophages, and vascular cells (Figure 1b–d). Clustering also identifies transcriptionally distinct subtypes of cells. Analysis of the cellular subtypes, markers and dynamics for each major cluster is shown separately in Figures 2, 3, 4, 5, 6 and 7 and described below. The specific tissue for dissociation into single cells included the SE, transitional epithelium, the epithelial cells making up the walls of the ampulla, ampullar associated mesenchyme and the glial cells associated with the peripheral processes of the vestibular neurons. The cell bodies of the neurons were not included.
Figure 1.
Cellular diversity in the crista ampullaris.
(a) Cristae, including the ampullae, were dissected from E16, E18, P3, and P7 mice, then dissociated for single-cell RNA-seq (scRNA-seq) analysis of cell types and gene expression. (b) UMAP of batch-corrected scRNA-seq datasets from E16, E18, P3, and P7 crista ampullaris. (c) Expression of known marker genes in each of the major cell groups detected by scRNA-seq and the G2/M maker
Figure 2.
Hair cell and support cell subtypes and dynamics during development.
(a) Highlights the position of support cells and hair cells in UMAP space relative to the whole dataset (i.e. E16, E18, P3, and P7 combined). (b) Cluster analysis in support cells and hair cells. (c and d) show expression of markers and Notch pathway genes, respectively, relative to cell cluster, pseudotime and developmental time. Additional color bars indicate whether markers are known or novel in specificity, implicated in vestibular diseases and dysfunction or in the Notch pathway. (e) Pseudotime of the support cell–hair cells trajectory in cristae. Note that the trajectory between support cells and hair cells is continuous. (f) The relative contributions of support cell and hair cell subtypes to the composition of the support cell and hair cell clusters at the indicated developmental stages. Note that the contribution of the
Figure 2—figure supplement 1.
Oncomodulin immunofluorence in type I hair cells of the crista ampullaris.
IF for oncomodulin (
Figure 2—figure supplement 2.
Localization of hair cell and support cell markers.
RNA in situ hybridization data from the Allen Developing Mouse Brain Atlas is shown for cluster-specific markers in E15.5 cristae (
Figure 2—figure supplement 3.
Developmental stage and pseudotime in crista epithelial cells.
(a and b) show developmental stage and pseudotime on UMAP in cells from the whole dataset, respectively. (b) Is replicated from Figure 2e for easy comparison with (a). (c) shows pseudotime in cell on UMAP for each developmental stage analyzed.
Figure 2—figure supplement 4.
RNA velocity analysis in crista epithelial cells.
Figure 2—figure supplement 5.
Localization of anti-Id1 in crista.
(a) Id1 (
Figure 2—figure supplement 6.
Heat-shock pathway dynamics during support cell development.
(a) Shows expression of heat shock response genes relative to support cell and hair cell clusters, pseudotime and developmental time. Note that most
Figure 2—figure supplement 7.
Fgf pathway in the developing crista ampullaris.
(a) Shows the expression of Fgf ligands and receptors in UMAP of the crista epithelium. Maximum expression is shown at lower right of each UMAP panel. In (b), The expression of Fgf ligands, receptors, binding proteins, and targets in the developing crista ampullaris is visualized by heatmap.
Figure 3.
Glial cell diversity and dynamics.
(a) Highlights the position of glial cells in UMAP space relative to the whole dataset. (b) Cluster analysis in glia. (c) Expression of markers relative to cell cluster, developmental stage and pseudotime. (d) Pseudotime of the developmental trajectory in glia. (e) The relative contributions of cell clusters to the composition of glia at the indicated developmental stages. Note that Schwann cells and myelinating cell markers increase with the developmental time.
Figure 3—figure supplement 1.
Developmental stage relative to UMAP in crista glial cells.
Glial cells in the whole dataset shown in UMAP with color-coding by developmental stage.
Figure 3—figure supplement 2.
Localization of glial cell markers.
RNA in situ hybridization data from the Allen Developing Mouse Brain Atlas is shown for cluster-specific markers in E15.5 cristae. Insets show the cluster specificity in UMAP.
Figure 4.
Cellular diversity in the nonsensory ampulla epithelium.
(a) Highlights the position of the nonsensory epithelial cells of the ampulla in UMAP space relative to the whole dataset. (b) Cluster analysis in nonsensory ampulla epithelium. (c) Expression of markers relative to cell cluster and developmental time. Additional color bars indicate whether markers are known or novel in specificity or implicated in vestibular diseases and dysfunction. (d) The relative contributions of cell clusters to the nonsensory ampulla epithelium at the indicated developmental ages. (e)
Figure 4—figure supplement 1.
Localization of cluster-specific markers in nonsensory ampulla epithelium.
RNA in situ hybridization data from the Allen Developing Mouse Brain Atlas is shown for cluster-specific markers in E15.5 cristae. Insets show the cluster specificity in UMAP.
Figure 5.
Mesenchymal cell diversity and dynamics.
In (a), Labeling of endogenous IgG (
Figure 5—figure supplement 1.
Localization of cluster-specific markers in otic mesenchyme surrounding the ampulla.
Panels show RNA in situ hybridization data for cluster-specific markers in E15.5 cristae from the Allen Developing Mouse Brain Atlas. Insets show specificity in the UMAP space. Expression patterns in the left–right UMAP axis relate to distance of the mesenchyme from the ampulla epithelium. Scale bar = 300 μm.
Figure 5—figure supplement 2.
Slc1a3-CreER activity in the anterior canal, horizontal canal and utricle.
Figure 6.
Melanocyte dynamics.
(a)
Figure 7.
Macrophage and vascular cell diversity and dynamics.
(a) Highlights the positions of macrophages and vascular cells in UMAP space relative to the whole dataset. (b) The relative contributions of cell clusters to the composition of the vasculature at the indicated developmental stages. A subset of macrophages is not associated with blood vessels (Figure 5a). (c) Expression of markers relative to macrophage cluster. (d) Relative expression of markers in endothelial cells and pericytes. (e) Cluster analysis in the macrophages. (f) Pseudotime of the macrophage trajectory.
Figure 7—figure supplement 1.
Localization of macrophage markers.
RNA in situ hybridization data from the Allen Developing Mouse Brain Atlas is shown for macrophage cluster-specific markers in E15.5 B6 cristae. Insets show the cluster specificity in UMAP.
Figure 7—figure supplement 2.
Developmental stage relative to UMAP in ampulla macrophages.
Macrophages in the whole dataset shown in UMAP with color-coding by developmental stage.
Heterogeneity and developmental changes in the sensory epithelium and glia
Clustering identifies six transcriptionally distinct clusters of support cells and hair cells (Figure 2a–c). Two clusters of hair cells show specific expression for known markers of vestibular type I and type II hair cell subtypes,
Trajectory analysis shows that the SC–HC transition cells are transcriptionally most similar to the type II hair cells (Figure 2c–e, Figure 2—figure supplement 3). Genes involved in hair cell differentiation such as
To determine whether support cell clusters indeed represent distinct cell populations, we examined the localization of the cluster-specific markers Id1, Sox2, and Atoh1 in situ. Anti-Id1 IF demonstrates 20–40% of support cells in the crista (Figure 2i and l, Figure 2—figure supplement 5, Video 1, Video 2). Atoh1 IF detects ~30 cells in the support cell layer in addition to some Myo7a+ and Myo7a- cells in the hair cell layer in the P0 crista (see
Video 1.
Id1 immunofluorescence in P0 crista.
Video shows a series of 1 micron optical sections per second imaged in P0 B6 cristae showing anti-Sox2 (
Video 2.
Id1 immunofluorescence in P4 crista.
Video shows a series of 1 micron optical sections per second imaged in P4 Hes5-GFP cristae from a colleagues’ colony showing anti-Sox2 (white), anti-Id1 (
Based on the known role of Notch-signaling in crista sensory development (Kiernan et al., 2001), expression of ligands, receptors and targets of the Notch-signaling pathway was of particular interest. We found enrichment of the Notch targets
The FGF pathway has been shown by our lab and others to be important in the development of the sensory epithelium in the cochlea (Hayashi et al., 2008; Yang et al., 2019; Chang et al., 2004; Pirvola et al., 2000) and is implicated in crista development (Chang et al., 2004; Pirvola et al., 2000) but the Fgf ligands involved in canal and crista formation are unclear. We therefore looked at the expression of all 4 FGF receptors and all ligands in our single cell combined dataset. We find that Fgfs 1, 3, 7, 8, 9, 10, 16, and 21 are expressed in either the support cells, SC–HC transition cells or the hair cells (Figure 2—figure supplement 7a and b). In the crista,
Clustering identifies four clusters of glia: glial progenitors,
Cellular diversity and developmental dynamics in the nonsensory ampulla epithelium and otic mesenchyme
Clustering detects transcriptionally distinct nonsensory epithelial cells in the crista ampullaris including transitional epithelial cells, dark cells and novel subtypes of the ampulla roof and wall (Figure 4a–c, see Figure 4—figure supplement 1 for RNA-ISH validation). Transitional epithelial cells were identified based on expression of the known markers
The remaining nonsensory epithelial cells comprise four clusters expressing markers also having spatially distinct expression patterns within the ampulla roof and wall (Figure 4b–c, Figure 4—figure supplement 1). The markers of the roof cell cluster identified by scRNA-seq
Mesenchyme surrounding the crista ampullaris consists of histologically distinct spatial domains: dense mesenchyme associated with the ampulla epithelium, loose mesenchyme containing the vasculature and dense mesenchyme near the boney otic capsule (Figure 5a). Clustering detects transcriptionally distinct subtypes of mesenchymal cells corresponding to these three spatial domains (Figure 5c, see Figure 5—figure supplement 1 for RNA-ISH validation). For example, the dense mesenchyme associated with the ampulla epithelium expresses
In addition to fibroblast-like cells, ampulla mesenchyme includes melanocytes (Figure 6). As a proportion of total mesenchymal cell numbers, melanocytes increase ~3.5-fold by P7 from E18 (Figure 6b). Similarly, the area occupied by pigmented cells increases ~3.5-fold in P7 versus P0 crista ampullaris (Figure 6c–e). Several genes showed downregulation in P7 melanocytes versus P3 (Figure 6f).
Ampulla mesenchyme also includes blood vessels and macrophages; many macrophages in the ampulla localize to blood vessels (Figure 5a). Clustering detects endothelial cells, pericytes and distinct subtypes of macrophages in the crista ampullaris (Figure 1, Figure 7).
Comparative analysis of cochlear and crista hair cell and support cell expression
The hair and support cells of the cochlea and the crista have similarities but are specialized functionally, which suggests that similarities and differences can be found at the transcriptional level. To compare the gene expression profile of crista hair cells and support cells to those in the cochlea, we aligned a publicly available dataset of P7 cochlea cells from Kolla et al., 2020 to the P7 crista cells of the present study, then clustered the cells, identified cell type clusters based on known markers and performed differential expression analysis. UMAP and clustering suggest that crista cells including support cells and hair cells resemble cochlear cells (Figure 8a). Heatmaps show shared and specific markers for crista vs. cochlea support cells and hair cells identified by differential expression analysis (Figure 8b). Differential expression analysis identifies known cochlea-specific support cell markers
Figure 8.
Comparative analysis of P7 crista ampullaris and P7 cochlea.
(a) Shows the relatedness of scRNA-seq data from Kolla et al. for P7 Swiss Webster cochlea (
Expression of genes associated with vestibular dysfunction and disease in the crista ampullaris
For insights into the cellular players in vestibulopathies, in Figure 9—source data 1 we show cluster analysis of expression in crista ampullaris cells of genes associated with vestibular diseases and disorders (i.e. Meniere’s disease, vertigo, motion sickness, circling, and hyperactivity in mice and relevant gene ontology terms). Clustering shows that many of the genes associated with vestibular disorders are expressed predominantly in support cells and hair cells (Figure 9 shows a subset, Figure 9—source data 1 shows all vestibular disorder genes). However, some of these genes implicated in vestibular dysfunction are also expressed in other cell types of the ampulla. For example, macrophages show enrichment for
Figure 9.
Expression of genes associated with vestibular disease and dysfunction in the crista ampullaris.
The heatmap summarizes the expression of a subset of genes associated with vestibular disease and dysfunction in cell clusters of the crista ampullaris. Figure 9—source data 1 shows the full list of vestibular disorder-associated genes. Column color bars indicate the major cell types and subtypes. Row color bars denote the following:
Discussion
scRNA-seq is a powerful technology for studying cellular diversity and changes in developing tissues. Our results provide several new insights into the composition and development of the crista and identify markers for novel subtypes of support cells, nonsensory epithelial cells, macrophages, glia, and mesenchymal cells. Most notably, we found cell cluster-specific markers that predicted stereotypic gene expression domains not previously described in the ampulla epithelium and mesenchyme. Second, this analysis resolves novel developmental transitions at the transcriptional level including the separate lineages of type I and type II hair cells, the maturation of Scwann cells as well as evidence for nonsensory–support cell conversion and macrophage diversity and local proliferation. Third, we showed this dataset can be leveraged to identify the stage- and lineage-dependent transcriptional changes during the formation of hair cells in the crista. We have uploaded this dataset to GEO (GSE168901) for independent investigation and reanalysis as the informatics tools and research questions continue to evolve.
Support cell subtypes and postnatal hair cell addition in the crista
Several findings increase our understanding of hair cell recruitment from precursors in the support cell layer of the developing crista. Findings from trajectory analysis, the changes in cluster proportions and RNA velocity analysis (Figure 2 and Figure 2—figure supplement 3) suggest recruitment of hair cells from the support cell layer. Transitioning cells are Atoh1+ and we found these cells in the support cell layer by IF in neonatal cristae. Based on the expression of both support cell and hair cell markers and the basal position of their Atoh1+ nuclei, transitioning cells likely represent the immature hair cells previously identified in utricle based on morphological characteristics including nuclei in the basal layer (Rüsch et al., 1998; Li and Forge, 1997).
Our findings increase the understanding of hair cell differentiation in the vestibular system. Whereas most Anxa4+ type II hair cells form postnatally in the utricle (McInturff et al., 2018; Burns et al., 2012), we identify an Anxa4-enriched cluster of hair cells in E16 scRNA-seq dataset as well as in the hair cell layer of E15.5 RNA ISH images of crista (Figure 2, Figure 2—figure supplement 2). Our analysis provides evidence that type I and type II hair cells differentiate from a common immature hair cell population and we have identified differential gene expression in the type I and type II lineage including
Between E18 and P7, clusters of type I hair cells, type II hair cells and
We have identified specific expression patterns of Fgf ligands in the crista and found that Fgf7 and Fgf21 show specificity to the two types of hair cells. Furthermore, we find Fgf7 in the transition to type I hair cells and Fgf21 in transition to type II cells. The roles of Fgf7 and Fgf21 in inner ear development and function are unknown as far as we know. Findings from other systems implicate Fgf7 in presynaptic organization. For example, Fgf7 promotes clustering of anti-synapsin+ vesicles and neurite branching in cultured motorneurons (Umemori et al., 2004). In vivo,
To our surprise, inducible Hsp70 IF is present in apical processes extending from a subset of support cells at P7 but not at P3. The anti-Hsp70 foci are adjacent both to hair bundles and the apex of a subset of support cells. It is unclear from which cells these foci originate. When we initially found upregulation of heat-shock response genes in support cells by P7, we hypothesized that heat-shock response was likely artifactual and caused by stress from dissociation. However, when we acutely dissect cristae, fix and stain, we find that Hsp70 indeed increases, suggesting that Hsp70 is upregulated by P7 in the crista. Upregulation of expression of heat shock response genes was observed at P7 in hair cells, support cells, nonsensory epithelial cells by scRNA-seq. Exosomal secretion of Hsp70 from support cells promotes hair cell survival in the utricle and cochlea (Breglio et al., 2020; May et al., 2013; Taleb et al., 2009). Additionally, there is an association of a single-nucleotide polymorphism in
Novel cell types in the ampulla roof and possible functions
scRNA-seq analysis resolved detailed expression profiles for transitional epithelial cells and dark cells and for novel cell types in the roof of the nonsensory ampulla epithelium. Further study will be needed to determine the precise relationships between the cell-specific gene expression pattern identified by cluster analysis and the morphological variations (e.g., microvilli, granules, cell shape, and osmiophilicity) identified by earlier histological analysis in ampulla epithelium. Regardless, these results provide insights into the development and function of the ampulla epithelium. Nonsensory ampulla epithelial cells and support cells express the peptidase
The cellular heterogeneity found in the ampulla epithelium may reflect differences in developmental lineage. Cristae derive from the dorsal otocyst (Li et al., 1978), with sensory specification evident by E11.5–12 (Morsli et al., 1998). At E12-E13, outpockets of the dorsal otocyst termed the canal pouches remodel to form the tube-like epithelium of semicircular canals and ampullae. This process involves apical fusions of the central walls of the pouches to form bilayered epithelium termed the canal fusion plates, then basal detachment and resorptions of the epithelial cells in the canal fusion plates into the rims of the pouches to form the canals (Morsli et al., 1998; Martin and Swanson, 1993; Rakowiecki and Epstein, 2013; Salminen et al., 2000). These cellular movements that remodel the canal fusion plate into the semicircular canals are regulated through morphogenetic gradients in signaling of Wnt, Notch, Bmp and Netrin 1 (Ntn1) within the rims and plates (Kiernan et al., 2001; Rakowiecki and Epstein, 2013; Salminen et al., 2000; Chang et al., 2008). For example,
Schwann cell development and implications for the study of demyelinating disease
Glia in the cochleovestibular nerve are derived from the neural crest (Sandell et al., 2014) and otic placode (Xu et al., 2017). In mouse, glia are known to proliferate within the cochleovestibular nerve up to birth (Ruben, 1967) and in response to injury (Lang et al., 2011). Consistent with this, many glia express G2/M markers at E18 and these glial progenitors decline by P7. Furthermore, myelination markers such as
Implications of mesenchymal cell diversity in the ampulla
Our analysis resolved detailed expression profiles for several previously unknown subtypes of mesenchymal cells. Specifically, we identified three types of mesenchyme: dense mesenchyme associated with the ampulla epithelium, dense mesenchyme near the boney otic capsule and, in between, loose mesenchyme containing vasculature. Cluster specificity correlated corresponded well to spatial specificity in ISH (Allen Atlas) of cluster-specific markers revealing stereotypic patterns of localization of the subtypes both along a spatial axis between ampulla epithelium and the cartilaginous otic capsule and in loose (
Macrophages show enrichment for several genes associated with vestibular disorders including Meniere’s disease, which raises the question of whether these cells have important roles in vestibular disease. Furthermore, cluster analysis resolved two transcriptionally distinct subtypes of macrophages:
In our dataset, we did not have sufficient numbers endothelial cells and pericytes to make fine distinctions. Clustering can make tenuous divisions in small groups of cells but these ‘over-clustered’ groups had no convincing specific markers. Enrichment for these cells and other rare cells prior to scRNA-seq may resolve novel subtypes as has been shown for endothelial cells and pericytes in other systems (He et al., 2018).
Conclusions
Our findings add to the fundamental understanding of the cellular diversity of the ampulla. Several novel subtypes of epithelial and mesenchymal cells were identified using scRNA-seq: Id1+ and
Materials and methods
Mice
For scRNA-seq, timed pregnant C57BL/6J mice (B6; Jackson stock: 000664, RRID:IMSR_JAX:000664) were purchased and aged to E18, P3, and P7. For the E16 sample, Sox2-GFP mice (Jackson stock: 07592) were bred to generate a timed pregnant litter. For most immunofluorescence (IF) studies, C57BL/6J mice were bred to generate timed pregnant litters. Two supplementary images show tissue collected opportunistically from Slc1a3-CreER:LNL-tTA:tetO-mAscl1-ires-GFP mice (Todd et al., 2020) and Hes5-GFP (Nelson et al., 2011) lines used in our colleagues’ published research. To induce CreER, tamoxifen (1.5 mg in 100 μL of corn oil) was administered to adult mice daily for 5 days. Stages were verified by Theiler’s criteria. Mice were housed in the University of Washington Department of Comparative Medicine. All procedures were reviewed and approved by the Institutional Animal Care and Use Committee of the University of Washington and performed in accordance with NIH guidelines.
Dissociation of cells
All three cristae, including the ampullae, were dissected from E16 mice (n = 6), E18 mice (n = 5), P3 mice (n = 8), and P7 mice (n = 12) in ice cold Hank’s buffered salt solution (HBSS; Cat. No. 14025–92; Thermo Fisher Scientific; Waltham, MA). For the E18, P3, and P7 samples, half of the cristae were dissected away from the ampulla to increase the proportion of sensory cells. Scarpa’s ganglion was not included. Dissected cristae and cristae with ampulla intact were then pooled (1:1) and dissociated by treatments with collagenase and papain as follows. First, cristae were digested in 2% collagenase IV (Worthington Biochemical; Lakewood, NJ) at 37°C for 5 min. A 10% vol of FBS was added and cristae were washed in HBSS three times. Second, cristae were digested in 2% collagenase II (Worthington) at 37°C for 30 min. As before, a 10% vol of FBS was added and cristae were washed in HBSS three times. Third, cristae were dissociated to single cells using the papain dissociation kit (Worthington, #LK003150) for approximately 1 hr with trituration every 10 min. then stopped with the addition of ovomucoid and spun per the manufacturer’s instructions. Cells were strained through the cell strainer and counted with a hemocytometer. A total of 7000 cells were then input into the 10X protocol.
scRNA-seq and analysis
Libraries for scRNA-seq were prepared using the Chromium Single Cell 3’ Library and Gel Bead Kit v3 (10x Genomics; Pleasanton, CA) per the manufacturer’s instructions. Reads were aligned to mm10 and filtered using the Cell Ranger pipeline. Cell numbers and depth are reported in Supplementary file 1. We used Monocle 3 (Cao et al., 2019), Seurat 3 (Stuart et al., 2019), velocyto (La Manno et al., 2018), and scVelo (Bergen et al., 2020) packages for scRNA-seq analysis. Normalization (SCTransform Hafemeister and Satija, 2019), batch correction (batchelor Haghverdi et al., 2018/IntegrateData), principal component analysis and dimensional reduction (UMAP McInnes et al., 2018) were performed in Seurat. Clustering (Leiden Traag et al., 2019) and trajectory analysis (learn_graph) were performed in Monocle 3. RNA velocity was analyzed using velocyto and scVelo. For heatmaps and FeaturePlots, raw counts were corrected for depth of sequencing and batch effects and scaled and centered using ScaleData in Seurat 3.1. Gene expression was plotted using pheatmap v1.0.12. Differential expression analysis was performed on raw counts using FindMarkers within Seurat 3.1. Gene set enrichment analysis (GSEA Subramanian et al., 2005) was performed on fold differences in expression using the fgsea package (Sergushichev, 2016) as described previously (Wilkerson et al., 2019) for canonical pathways (i.e. KEGG Kanehisa et al., 2019, Reactome Jassal et al., 2020, Biocarta Nishimura, 2001 and PID Schaefer et al., 2009) and transcription factor targets (Xie et al., 2005) from MSigDB v7.0 (Liberzon et al., 2015). Gene lists for vestibular disease and dysfunction were curated by supplementing gene lists from Malacards (Rappaport et al., 2017), OMIM (Amberger et al., 2019), MSigDB v6.2 (Liberzon et al., 2015) and the International Mouse Phenotyping Consortium (IMPC) (Bowl et al., 2017) with gene–disease associations from literature (Vijayakumar et al., 2019; Frejo et al., 2016; Jones and Jones, 2014; Gazquez and Lopez-Escamez, 2011; Hromatka et al., 2015; Oh et al., 2019).
Tissue isolation and immunofluorescence and 3D imaging
Temporal bones were fixed overnight at 4°C in 4% paraformaldehyde (Cat. No. 15710; Electron Microscopy Sciences; Hatfield, PA) diluted in phosphate-buffered saline (PBS; Cat. No. BP399; Thermo Fisher Scientific). Tissues were washed 3 ×~30 min in PBS. Temporal bones in some experiments were decalcified (167 mM/5% EDTA/PBS for five days at 4°C with daily exchanges), embedded in 4% agarose and sectioned at 200 μm with a vibratome. For whole mounts, ampullae were microdissected from the temporal bones. To uncover the crista sensory epithelium, the roof and wall epithelium of the ampulla were dissected away from cristae. To remove otoliths that stuck to cristae during dissection, cristae were decalcified in 167 mM (~5%) EDTA/PBS overnight at 37°C. For experiments using goat anti-Wnt3 or mouse anti-Myo7a, antigen retrieval was performed in sodium citrate buffer (10 mM Sodium citrate, 0.05% Tween 20, pH 6.0) for 45 min in a vegetable steamer. Cristae and vibratome sections were blocked (10% donkey serum/0.5% Triton-X-100/PBS) overnight at 4°C. Tissues were then incubated overnight in primary antibodies (Table 1) diluted in block solution at room temperature. After 3 × 1 hr washes in 0.5% Triton-X-100/PBS, tissues were incubated at least 1 hr in block, then overnight in secondary antibodies diluted in block at room temperature. After 3 × 1 hr washes in 0.5% Triton-X-100/PBS, tissues were mounted (Fluoromount-G; Cat. No. BP399; Southern Biotech; Birmingham, AL) under No. one cover slips and imaged using a Zeiss LSM880 with Airyscan. Linear adjustments to micrographs were made using ‘Levels’ in Adobe Photoshop v21.1.1 to increase signal:noise.
Table 1.
Antibodies used for immunofluorescence.
Atoh1 | Rabbit | 1:1000 | 21215–1-AP | Proteintech | AB_10733126 |
Hsp70 | Rabbit | 1:1000 | PA5-28003 | Invitrogen | AB_2545479 |
Iba1 | Rabbit | 1:1000 | 019–19741 | Wako | AB_839504 |
Id1 | Rabbit | 1:1000 | BCH-1/37–2 | Biocheck | AB_2713996 |
Myo7a | Rabbit | 1:1000 | 25–6790 | Proteus | AB_10015251 |
Myo7a* | Mouse | 5 μg/ml | MYO7A 138–1 | DSHB | AB_2282417 |
Nefm | Chick | 1:200 | ab134458 | Abcam | AB_2860025 |
Ocm | Rabbit | 1:1000 | Omg4 | Swant | AB_10000346 |
Pecam1 | Rat | 1:50 | 551262 | BD Pharmingen | AB_398497 |
Sox2 | Goat | 1:200 | sc-17320 | Santa Cruz | AB_2286684 |
Wnt3* | Goat | 1:125 | PA5-18516 | Thermo | AB_10979520 |
*Requires antigen retrieval.
RNA in situ hybridization
Digoxigenin (DIG)-labeled
Morphometric quantitation and manual cell counting
For support cell and hair cell counts, total nuclei expressing specific markers were manually counted using Fiji/ImageJ v2 (Schindelin et al., 2012) as described previously (Wilkerson et al., 2018). Total hair cell counts made in P0 B6 cristae (Figure 2) are compared to our previously published >P14 B6 dataset (Wilkerson et al., 2018). For hair cell counts, anterior and posterior cristae were grouped together and counts represent total hair cell nuclei per crista. For pigmented cell area measurements in Fiji, ‘Threshold’ was used to isolate the pigmented cell signal and the area above threshold measured. To test for dependence of pigmented area, Id1+ support cell counts and Atoh1+ cells in the support cell layer on age, two-sided Student’s t-tests (alpha = 0.05) were performed using ‘t.test’ in ‘stats v3.6.2’ in RStudio v1.2.5033. To test for crista hair cell count dependence on age and crista-type, two-way ANOVA and multiple linear regression analysis were performed using ‘aov’ and ‘TukeyHSD’ in ‘stats v3.6.2’ in RStudio v1.2.5033.
2 Institute for Stem Cells and Regenerative Medicine, University of Washington Seattle United States
3 Department of Biochemistry, University of Washington Seattle United States
University of Sheffield United Kingdom
California Institute of Technology United States
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Abstract
This study provides transcriptomic characterization of the cells of the crista ampullaris, sensory structures at the base of the semicircular canals that are critical for vestibular function. We performed single-cell RNA-seq on ampullae microdissected from E16, E18, P3, and P7 mice. Cluster analysis identified the hair cells, support cells and glia of the crista as well as dark cells and other nonsensory epithelial cells of the ampulla, mesenchymal cells, vascular cells, macrophages, and melanocytes. Cluster-specific expression of genes predicted their spatially restricted domains of gene expression in the crista and ampulla. Analysis of cellular proportions across developmental time showed dynamics in cellular composition. The new cell types revealed by single-cell RNA-seq could be important for understanding crista function and the markers identified in this study will enable the examination of their dynamics during development and disease.
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