Lopez-Porras, A. I. | bioRxiv Science

bioRxiv2024

Myosin XVA isoforms participate in the mechanotransduction-dependent remodeling of the actin cytoskeleton in auditory stereocilia

Auditory hair cells form precise and sensitive staircase-like actin protrusions known as stereocilia. These specialized microvilli detect deflections induced by sound through the activation of mechano-electrical transduction (MET) channels located at their tips. At rest, a small MET channel current results in a constant calcium influx, which regulates the morphology of the actin cytoskeleton in the shorter transducing stereocilia. However, the molecular mechanisms involved in this novel type of activity-driven plasticity in the stereocilium cytoskeleton are currently unknown. Here, we tested the contribution of myosin XVA (MYO15A) isoforms. We used electron microscopy to evaluate morphological changes in the cytoskeleton of auditory hair cell stereocilia after the pharmacological blockage of resting MET currents in cochlear explants from mice that lacked one or all isoforms of MYO15A. Hair cells lacking functional MYO15A isoforms did not exhibit MET-dependent remodeling in their stereocilia cytoskeleton. In contrast, hair cells that only lack the long isoform of MYO15A exhibited increased MET-dependent stereocilia remodeling, including remodeling in stereocilia from the tallest non-transducing row of the bundle. We conclude that MYO15A isoforms not only enable but also fine-tune the MET-dependent remodeling of the actin cytoskeleton in transducing stereocilia and contribute to the stability of the tallest row.

neuroscience↗

bioRxiv2023

Large-scale annotated dataset for cochlear hair cell detection and classification

Our sense of hearing is mediated by cochlear hair cells, localized within the sensory epithelium called the organ of Corti. There are two types of hair cells in the cochlea, which are organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains a few thousands of hair cells, and their survival is essential for our perception of sound because they are terminally differentiated and do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. However, the sheer number of cells along the cochlea makes manual quantification impractical. Machine learning can be used to overcome this challenge by automating the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, human, pig and guinea pig cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 90,000 hair cells, all of which have been manually identified and annotated as one of two cell types: inner hair cells and outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to supply other groups within the hearing research community with the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

neuroscience↗