Semi-automated quantification of hair cells in the mature mouse utricle

Sung, Cathy Yea Won; Barzik, Melanie; Costain, Tucker; Wang, Lizhen; Cunningham, Lisa L.

doi:10.1016/j.heares.2021.108429

Cited by 4 publications

(8 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previously published automated cell counting programs also often struggle to cope with overlapping cells, which can require advanced machine learning systems [38], labor intensive optical clearing methods [45], or user guided segmentation of cells prior to machine analysis [26]. In the case of inner ear tissues this issue can be particularly problematic where, for example, there are little to no options for the labeling of cell nuclei in the neurons of the auditory nerve which makes segmentation nearly impossible.…”

Section: Discussionmentioning

confidence: 99%

“…A similar problem persisted for decades with regard to sensory hair cells where myosin or other non-nuclear proteins were the best available markers. More recently, immunolabeling of the nuclear protein POU4F3 has been proposed in a semi-automated method for hair cell counting [26], but even with a nuclear marker, there appear to be difficulties with segmentation requiring manual separation of doublets and triplets of overlapping cells by the user. This problem may be partly solvable from the staining and imaging side of the approach where we have found that immunolabeling spectrin in hair cells provides better segmentation than staining of POU4F3 (data not shown).…”

Section: Discussionmentioning

confidence: 99%

“…However, consistently obtaining high quality and similar SNR micrographs, especially across different samples, is often challenging. Indeed, this is a limitation inherent in several previously published cell quantification programs as well [26,37,38]. While we were able to successfully run PCPA on images of suboptimal quality (both in terms of image dpi and antibody SNR ratio) by using the pre-processing steps recommended, we have also included several features in the PCPA outputs (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…As the fusion of neighboring cells in micrographs is a common problem in automated image analysis [26][27][28], we developed an optional Doublet Splitting mode, where PCPA will separate two cells that touch or overlap by splitting the doublet mass in half, then treating each half as a discreet cell during subsequent steps (Fig B in S1). This optional function cannot recurse beyond separating two conjoined cells.…”

Section: Pcpa Identifies White Pixels In a Binary Image And Aggregate...mentioning

confidence: 99%

See 3 more Smart Citations

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

Stansak,

Baum,

Ghosh

et al. 2024

Preprint

View full text Add to dashboard Cite

Background: During development, planes of cells give rise to complex tissues and organs. The proper functioning of some cell types is critically dependent on proper inter- and intracellular spatial orientation in regards to the overall tissue, a feature known as planar cell polarity (PCP). To study the genetic and environmental factors affecting planar cell polarity investigators must 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 Planar Cell Polarity Auto Count (PCPA) to analyze binary images and identify "chunks" of white pixels that contain "caves" of infiltrated black pixels. Cochleae (P4) and utricles (E17.5) from wildtype mice were immunostained for Beta-Spectrin and imaged on a confocal microscope. Images were preprocessed using existing ImageJ functionality to enhance contrast, make binary, and reduce noise. An investigator rated P4 cochlear angle measurements produced by PCPA from P4 cochlea for accuracy using a 1-5 agreement scale. For E17.5 cochlear samples, we compared mean angle measurements per utricular region derived using PCPA against manually derived angle measurements. 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 accurate planar cell polarity measurements for over 96% of hair cells. When allowing for a <10 degree deviation from human rater performance PCPA was able to accurately measure over 98% of cochlear hair cells. When manual angle measurements were compared to PCPA's measurements for E17.5 utricles, PCPA's mean measurements fell within -9 to +10 degrees of manually obtained mean angle measures. 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 plugin suite is a robust and accurate tool for the automated collection of cell counts and PCP angle measurements.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Pcpa Identifies White Pixels In a Binary Image And Aggregate...mentioning

confidence: 99%

See 2 more Smart Citations

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

Stansak,

Baum,

Ghosh

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The postnatal maturation of the rat and mouse vestibular HCs and their fragility to experimental manipulation are significant factors that condition the establishment of in vitro models to study their biology and pathology. In one popular preparation, utricles are obtained from adult mice and are maintained as free floating specimens for a few (up to 7, usually 1 to 4) days ( Cunningham et al, 2002 ; Cunningham, 2006 ; Sung et al, 2022 ). These explants have been frequently used to study ototoxicity and to evaluate otoprotective treatments in mature HCs, but culturing the sensory epithelium causes a cellular stress that probably masks the earliest responses to the toxicity being analyzed.…”

Section: Introductionmentioning

confidence: 99%

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

Borrajo,

Sedano,

Palou

et al. 2024

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

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.

show abstract