Semi-automated Quantification of Hair Cells in the Mature Mouse Utricle

Maturation of type I and type II rat vestibular hair cells in vivo and in vitro

Vestibular sensory epithelia contain type I and type II sensory hair cells (HCI and HCII). Recent studies have revealed molecular markers for the identification of these cells, but the precise composition of each vestibular epithelium (saccule, utricle, lateral crista, anterior crista, posterior crista) and their postnatal maturation have not been described in detail. Moreover, in vitro methods to study this maturation are not well developed. We obtained total HCI and HCII counts in adult rats and studied the maturation of the epithelia from birth (P0) to postnatal day 28 (P28). Adult vestibular epithelia hair cells were found to comprise ∼65% HCI expressing osteopontin and PMCA2, ∼30% HCII expressing calretinin, and ∼4% HCII expressing SOX2 but neither osteopontin nor calretinin. At birth, immature HCs express both osteopontin and calretinin. P28 epithelia showed an almost adult-like composition but still contained 1.3% of immature HCs. In addition, we obtained free-floating 3D cultures of the epithelia at P1, which formed a fluid-filled cyst, and studied their survival and maturation in vitro up to day 28 (28 DIV). These cultures showed good HC resiliency and maturation. Using an enriched medium for the initial 4 days, a HCI/calretinin+-HCII ratio close to the in vivo ratio was obtained. These cultures are suitable to study HC maturation and mature HCs in pharmacological, toxicological and molecular research.

PCP auto count: a novel Fiji/ImageJ plug-in for automated quantification of planar cell polarity and cell counting

Introdution: During development, planes of cells give rise to complex tissues and organs. The proper functioning of these tissues is critically dependent on proper inter- and intra-cellular spatial orientation, a feature known as planar cell polarity (PCP). To study the genetic and environmental factors affecting planar cell polarity, investigators must often manually measure cell orientations, which is a time-consuming endeavor. To automate cell counting and planar cell polarity data collection we developed a Fiji/ImageJ plug-in called PCP Auto Count (PCPA). Methods: PCPA analyzes binary images and identifies "chunks" of white pixels that contain "caves" of infiltrated black pixels. For validation, inner ear sensory epithelia including cochleae and utricles from mice were immunostained for βII-spectrin and imaged with a confocal microscope. Images were preprocessed using existing Fiji functionality to enhance contrast, make binary, and reduce noise. An investigator rated PCPA cochlear hair cell angle measurements for accuracy using a one to five agreement scale. For utricle samples, PCPA derived measurements were directly compared against manually derived angle measurements and the concordance correlation coefficient (CCC) and Bland-Altman limits of agreement were calculated. PCPA was also tested against previously published images examining PCP in various tissues and across various species suggesting fairly broad utility. Results: PCPA was able to recognize and count 99.81% of cochlear hair cells, and was able to obtain ideally accurate planar cell polarity measurements for at least 96% of hair cells. When allowing for a <10° deviation from "perfect" measurements, PCPA's accuracy increased to 98%-100% for all users and across all samples. When PCPA's measurements were compared with manual angle measurements for E17.5 utricles there was negligible bias (<0.5°), and a CCC of 0.999. Qualitative examination of example images of Drosophila ommatidia, mouse ependymal cells, and mouse radial progenitors revealed a high level of accuracy for PCPA across a variety of stains, tissue types, and species. Discussion: Altogether, the data suggest that the PCPA plug-in suite is a robust and accurate tool for the automated collection of cell counts and PCP angle measurements.

PCP Auto Count: A Novel Fiji/ImageJ plug-in for automated quantification of planar cell polarity and cell counting

Background

During development, planes of cells give rise to complex tissues and organs. The proper functioning of these tissues is critically dependent on proper inter- and intra-cellular spatial orientation, a feature known as planar cell polarity (PCP). To study the genetic and environmental factors affecting planar cell polarity investigators must often manually measure cell orientations, which is a time-consuming endeavor.

Methodology

To automate cell counting and planar cell polarity data collection we developed a Fiji/ImageJ plug-in called PCP Auto Count (PCPA). PCPA analyzes binary images and identifies "chunks" of white pixels that contain "caves" of infiltrated black pixels. Inner ear sensory epithelia including cochleae (P4) and utricles (E17.5) from mice were immunostained for βII-spectrin and imaged on a confocal microscope. Images were preprocessed using existing Fiji functionality to enhance contrast, make binary, and reduce noise. An investigator rated PCPA cochlear angle measurements for accuracy using a 1-5 agreement scale. For utricle samples, we directly compared PCPA derived measurements against manually derived angle measurements using concordance correlation coefficients (CCC) and Bland-Altman limits of agreement. Finally, PCPA was tested against a variety of images copied from publications examining PCP in various tissues and across various species.

Results

PCPA was able to recognize and count 99.81% of cochlear hair cells (n = 1,1541 hair cells) in a sample set, and was able to obtain ideally accurate planar cell polarity measurements for over 96% of hair cells. When allowing for a <10° deviation from "perfect" measurements, PCPA's accuracy increased to >98%. When manual angle measurements for E17.5 utricles were compared, PCPA's measurements fell within -9 to +10 degrees of manually obtained mean angle measures with a CCC of 0.999. Qualitative examination of example images of Drosophila ommatidia, mouse ependymal cells, and mouse radial progenitors revealed a high level of accuracy for PCPA across a variety of stains, tissue types, and species. Altogether, the data suggest that the PCPA plug-in suite is a robust and accurate tool for the automated collection of cell counts and PCP angle measurements.

Sox2 is required in supporting cells for normal levels of vestibular hair cell regeneration in adult mice

Sox2 is a transcription factor that is necessary in the mammalian inner ear for development of sensory hair cells and supporting cells. Sox2 is expressed in supporting cells of adult mammals, but its function in this context is poorly understood. Given its role in the developing inner ear, we hypothesized that Sox2 is required in vestibular supporting cells for regeneration of type II hair cells after damage. Using adult mice, we deleted Sox2 from Sox9-CreER-expressing supporting cells prior to diphtheria toxin-mediated hair cell destruction and used fate-mapping to assess regeneration. In utricles of control mice with normal Sox2 expression, supporting cells regenerated nearly 200 hair cells by 3 weeks post-damage, which doubled by 12 weeks. In contrast, mice with Sox2 deletion from supporting cells had approximately 20 fate-mapped hair cells at 3 weeks post-damage, and this number did not change significantly by 12 weeks, indicating regeneration was dramatically curtailed. We made similar observations for saccules and ampullae. We found no evidence that supporting cells lacking Sox2 had altered cellular density, morphology, or ultrastructure. However, some Sox2-negative supporting cell nuclei appeared to migrate apically but did not turn on hair cell markers, and type I hair cell survival was higher. Sox2 heterozygotes also had reduced regeneration in utricles, but more hair cells were replaced than mice with Sox2 deletion. Our study determined that Sox2 is required in supporting cells for normal levels of vestibular hair cell regeneration but found no other major requirements for Sox2 in adult supporting cells.