RESUMO
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.
RESUMO
Aminoglycoside ototoxicity involves the accumulation of antibiotic molecules in the inner ear hair cells and the subsequent degeneration of these cells. The exact route of entry of aminoglycosides into the hair cells in vivo is still unknown. Similar to other small organic cations, aminoglycosides could be brought into the cell by endocytosis or permeate through large non-selective cation channels, such as mechanotransduction channels or ATP-gated P2X channels. Here, we show that the aminoglycoside antibiotic gentamicin can enter mouse outer hair cells (OHCs) via TRPA1, non-selective cation channels activated by certain pungent compounds and by endogenous products of lipid peroxidation. Using conventional and perforated whole-cell patch clamp recordings, we found that application of TRPA1 agonists initiates inward current responses in wild-type OHCs, but not in OHCs of homozygous Trpa1 knockout mice. Similar responses consistent with the activation of non-selective cation channels were observed in heterologous cells transfected with mouse Trpa1. Upon brief activation with TRPA1 agonists, Trpa1-transfected cells become loaded with fluorescent gentamicin-Texas Red conjugate (GTTR). This uptake was not observed in mock-transfected or non-transfected cells. In mouse organ of Corti explants, TRPA1 activation resulted in the rapid entry of GTTR and another small cationic dye, FM1-43, in OHCs and some supporting cells, even when hair cell mechanotransduction was disrupted by pre-incubation in calcium-free solution. This TRPA1-mediated entry of GTTR and FM1-43 into OHCs was observed in wild-type but not in Trpa1 knockout mice and was not blocked by PPADS, a non-selective blocker of P2X channels. Notably, TRPA1 channels in mouse OHCs were activated by 4-hydroxynonenal, an endogenous molecule that is known to be generated during episodes of oxidative stress and accumulate in the cochlea after noise exposure. We concluded that TRPA1 channels may provide a novel pathway for the entry of aminoglycosides into OHCs.
